BIOACCUMULATION AND RISK ASSESSMENT OF BUTACHLOR IN THE SOIL ECOSYSTEM

BY

ENEFE NDIDI

(PG/M.Sc/PhD/09/51051)

DEPARTMENT OF BIOCHEMISTRY FACULTY OF BIOLOGICAL SCIENCES

UNIVERSITY OF NIGERIA, NSUKKA

JULY, 2015

i

BIOACCUMULATION AND RISK ASSESSMENT OF BUTACHLOR IN THE SOIL ECOSYSTEM

BY

ENEFE NDIDI

(PG/M.Sc/PhD/09/51051)

DEPARTMENT OF BIOCHEMISTRY

FACULTY OF BIOLOGICAL SCIENCES

UNIVERSITY OF NIGERIA,

NSUKKA

SUPERVISOR: PROF. I.N.E ONWURAH

JULY, 2015

ii

BIOACCUMULATION AND RISK ASSESSMENT OF BUTACHLOR IN THE SOIL ECOSYSTEM

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE DEGREE IN DOCTOR OF PHILOSOPHY IN

ENVIRONMENTAL BIOCHEMISTRY (PhD), IN THE DEPARTMENT OF BIOCHEMISTRY, UNIVERSITY OF NIGERIA NSUKKA

BY

ENEFE NDIDI

(PG/MS.c/PhD/09/51051)

DEPARTMENT OF BIOCHEMISTRY, UNIVERSITY OF NIGERIA, NSUKKA.

SUPERVISOR: PROF. I.N.E ONWURAH

JULY, 2015

iii

CERTIFICATION

Enefe Ndidi, a post graduate student with registration number PG/M.Sc/PhD/09/51051 in the

Department of Biochemistry, Faculty of Biological sciences, University of Nigeria Nsukka, has

satisfactorily completed the requirements for the award of the degree of Doctor of Philosophy in

Environmental Biochemistry. The work embodied in this report is original and has not been

submitted in part or full for any other diploma or degree of this or in any other University.

---------------------------- ----------------------------- Prof I.N.E Onwurah Prof O.F.C Nwodo (Supervisor) (Head of Department)

------------------------------ External Examiner

iv

ACKNOWLEDGEMENTS

My utmost thanks go to the Almighty God for enabling me carry out this research work

successfully; for His immeasurable grace and provision all through the programme. I wish to acknowledge the immense contributions of my supervisor, Professor .I.N.E Onwurah; his

assistance, explanation, suggestions and encouragement helped me greatly in the completion of

this work. I am grateful to you, Sir.

My gratitude also goes to my lecturers and senior colleagues who contributed to the success of

this work, such personalities are; Professor O.F.C Nwodo, Head of Department of Biochemistry,

University of Nigeria Nsukka, Dr C.S Ubani, Dr Parker E. Joshua of the Department of

Biochemistry, University of Nigeria Nsukka; Professor Ajogi I.(In memory), Professor O.P.

Ajagbonna ., Dr O.K. Olabode ., Dr O.C Jegede., Dr (Mrs) .F. C. Nwinyi., Dr I. Casmir., Dr S.

Enem., Dr M. Onakpa., Dr F. Sanni., Mr I.Orokpo and Mr J. Fwangle, all of the Faculty of

Veterinary Medicine, University of Abuja.

My special appreciation goes to my parents Chief & Mrs D.O. Enefe and my sisters: Barrister

Kechim Mbaeyi, Ifaka Enefe, Capt. and Mrs Ifiok Eno for their support, encouragement and

prayers which were in no small measure throughout my study.

This work would have been impossible but for the assistance and support of persons whom I

acknowledge with profound gratitude; Dr A.T. Orishadipe and his team; Dr Stella Emmanuel

and Mr Bwai Macham David of the Advanced Chemistry Laboratory, Sheda Science and

Technology Complex (SHETSCO) Abuja; Mrs Vivian O. Osadebe and Mr C. Onu, of the

Department of Crop Science, UNN; Professor S.C. Udem and Dr R.I Onoja ., of the Faculty of

Veterinary Medicine UNN., Mr Austin Okorie, of the Department of Pharmacology ,UNN., Dr

(Mrs)Y. Akalusi and Dr L. Ikpa; of the Micro biology Unit of the Veterinary Research Institute

NVRI) Vom, Jos. Finally I wish to express my sincere gratitude to the University of

Abuja/TETFUND for their profound contributions to the funding of this research work.

v

DEDICATION

This research work is dedicated to the Almighty God, my loving Father and my Helper who made it possible.

vi

ABSTRACT

Bioaccumulation of butachlor in plants following its application in the farm against weeds was evaluated using Phaseolus vulgaris (bean plant). Also, the risk of the consumption of such plants with some amount of bioaccumulated butachlor by non-target humans was studied using rabbits as animal model. The field experiments were carried out by crop cultivation with the application of 4.0 liters per hectare (2.6 kg a.i/ha), 4.4 liters per hectare (2.9 kga.i/ha) and 5.0 liters per hectare (3.2 kg a.i/ha) concentrations of butachlor at pre-emergence of the bean plant and the leaves of the plant were analyzed for the presence of butachlor residues using GC-MS , the result gave 0.10, 0.13 and 0.20 ppm bioaccumulated butachlor respectively for the concentrations of the butachlor applied to the plots of land. For 28 days three replicate groups of rabbits (4 per group) were fed the leaves containing these different concentrations (0.10, 0.13 and 0.20 ppm) of butachlor while the control groups which were composed of three replicates, were fed the plants cultivated in plots not treated with the herbicide. The rabbits were allowed access to water ad libitum. At the end of this exposure period, significant increases (p < 0.05) were observed in Cytochrome P450 (CYP) protein and increases in Glutathione S-transferase (GST) activity of the post-mitochondria liver fractions which were observed for the groups of rabbits fed the leaves having butachlor at the concentrations of 0.13 and 0.20 ppm in a time- and concentration-dependent manner; The liver marker enzymes, aspartate aminotransferase and alkaline phosphatase (AST, ALP) activities increased significantly (p < 0.05) for the rabbits fed the leaves with butachlor concentrations of 0.13 and 0.20 ppm in a time and concentration dependent manner thus suggesting a possible body defiance mechanism for herbicide detoxification. There was fluctuations in the ALT activity, with a decrease observed in group 4 rabbits that consumed the highest concentrations. Histological sections of the liver tissues of the exposed rabbits thus revealed no pathological alterations on day 28. The pesticide biomarker enzyme results is an indicative of induction and animal exposure to xenobiotics. The two enzymes (CYP and GST) could however be overwhelmed when the concentration of the herbicide increase, or upon chronic exposure, resulting to toxicity. The study shows that the manufacturers’ recommended application rate for butachlor (2.6 kg a.i/ha) poses no health risk; however, the application rates above the recommended rate could pose some risk when butachlor bioaccumulates in edible plants that are consumed. Thus, this work underlines the importance of strict adherence to the manufacturers’ and regulatory bodies directives, in the application of this herbicide butachlor in the soil ecosystem.

vii

TABLE OF CONTENTS

Contents Pages Title Page - - - - - - - - - - i

Certification- - - - - - - - - - - iii Acknowledgements - - - - - - - - - iv

Dedication - - - - - - - - - - v Abstract - - - - - - - - - - vi

Table of Contents - - - - - - - - - vii List of Figures - - - - - - - - - xi

List of Tables - - - - - - - - - - xii List of Abbreviations - - - - - - - - - xiv

CHAPTER ONE: INTRODUCTION 1.1 Bioaccumulation of Herbicide - - - - - 3

1.2 Risk Assessment of Herbicide - - - - - 5 1.3 Bean Plant (Phaseolus vulgaris) - - - - - 6

1.4 Historical Use of Pesticide - - `- - - - 7 1.5 Classification of Pesticide - - - - - - 8

1.5.1 Classification of Herbicide - - - - - - 9 1.5.1.1 Classification based on Method of Application - - - 9

1.5.1.2 Classification based on the Type of Vegetation - - - 9 1.5.1.3 Classification based on Activity/Mode of Action - - - 9

1.5.1.4 Classification based on Chemical Nature/family - - - 10 1.6 Butachlor - - - - - - - 11

1.6.1 Physicochemical Properties of Butachlor- - - - - 12 1.6.2 Toxicity of Butachlor - - - - - - - 12

1.7 Mode of Action of Herbicides in Target Plants - - - 12 1.8 The Soil Ecosystem - - - - - - - 14

1.9 Fate of Herbicides in the Soil Ecosystem - - - - 18 1.9.1 Chemical and Photochemical Degradation - - - - 18

viii

1.9.2 Biological Degradation - - - - - - 21

1.10 Metabolism Herbicide in Plants - - - - - 24 1.11 Metabolism of Herbicide in Animals - - - - 28

1.11.1 Phase I - - - - - - - - - 29 1.11.2 Phase II - - - - - - - - 31 1.12 Metabolism of Butachlor in Animals - - - - - 32

1.13 Toxicity of Metabolites - - - - - - 34 1.14 Biomarkers of Pesticide (Herbicides) - - - - - 34

1.15 The Liver Marker Enzymes - - - - - - 35 1.15.1 Aspartate Transaminase - - - - - - 36

1.15.2 Alanine Transaminase - - - - - - - 36 1.15.3 Alkaline phosphatase - - - - - - - 36

1.16 Hepatotoxicity - - - - - - - - 36 1.17 Lipid Peroxidation - - - - - 37

1.18 Aim and Objectives of the Study - - - - - 38 1.18.1 Aim of the Study - - - - - - - 38

1.18.2 Specific objectives of the study - - - - 38

CHAPTER TWO: MATERIALS AND METHODS 2.1 Materials - - - - - - - - 39

2.1.1 Chemicals - - - - - - - - 39 2.1.2 Equipment/Glasswares - - - - - - 39

2.1.3 Plant Material - - - - - - - - 41 2.1.4 Experimental Animal - - - - - - - 41

2.1.5 Area of Study - - - - - - - - 41 2.2 Methods - - - - - - - - 41

2.2.1 Experimental Design - - - - - - - 41 2.2.2 Animal protocol - - - - - - - 44

2.2.3 Soil Analysis - - - - - - - - 44 2.2.4 Plant Extraction of Butachlor - - - - - - 44

2.2.5 Identification and Quantification of Butachlor (GC-MS) - - 45

ix

2.2.6 Determination of Bioaccumulation Factor - - - - 45

2.2.7 Determination of Hazard Quotient (HQ) and Health Risk Index (HRI) - 46 2.2.8 Preparation Post-Mitochondria Supernatant - - - - 46

2.2.9 Determination of Liver Total Cytochrome P450- - - - 46 2.2.10 Determination of liver Glutathione S-Transferase - - - 48 2.2.11 Assay of Serum ALT Activity - - - - - 49

2.2.12 Assay of Serum AST Activity - - - - - 50 2.2.13 Assay of Serum ALP Activity - - - - - 50

2.2.14 Determination of Liver Total Protein Concentration - - 51 2.2.15 Determination of Body Weight of Rabbits - - - - 52

2.2.16 Histological Evaluation of Liver Tissues of Rabbits - - - 52 2.3 Statistical Analysis - - - - - - - 52

CHAPTER THREE: RESULTS 3.1 Soil Analysis - - - - - - - - - 53 3.2 Chromatograms of Butachlor in Standard and Phaseolus vulgaris leaf extract - 53 3.2.2 Butachlor Concentration in Phaseolus vulgaris leaf extract - - - 67

3.2.3 Bioaccumulation Factor (BAF) - - - - - - 68

3.3 Pesticide Biomarkers - - - - - - - 71 3.3.1 Effect of Different Concentrations of Bio-accumulated Butachlor in Phaseolus vulgaris

leave on the Liver Total Cytochrome P450 (CYP) of Rabbits - - - 71

3.3.2 Effect of Different Concentrations of Bio-accumulated Butachlor in Phaseolus vulgaris Leave on the Liver of Glutathione S-transferase (GST) Rabbits- - - 73

3.4 Liver Marker Enzymes - - - - - - - 75

3.4.1 Effect of Different Concentrations of Bio-accumulated Butachlor in Phaseolus vulgaris Leaves on the Activity of Serum Aspartate Aminotransferase (AST) of Rabbits - 75

3.4.2 Effect of Different Concentrations of Bio-accumulated Butachlor in leaves of Phaseolus vulgaris on the Activity of Serum Alanine Aminotransferase (ALT) of Rabbits- 77

3.4.3 Effect of Different Concentrations of Bio-accumulated Butachlor in leaves of Phaseolus vulgaris on the Activity Serum Alkaline Phosphatase (ALP) in Rabbits- - -79

x

3.5 Effect of Different Concentrations of Bio-accumulated Butachlor in Leaves of Phaseolus vulgaris on Mean Body Weight of Rabbits - - - - - 81

3.6 Effect of Different Concentrations of Bio-accumulated Butachlor in the leaves of Phaseolus vulgaris on Liver Total Protein of Rabbit- - - - 83

3.7 Histolological Examination of liver tissues of rabbits indirectly exposed to butachlor herbicide - - - - - - - - - 85

CHAPTER FOUR : DISCUSSION 4.1 Discussion - - - - - - - - - 89

4.2 Conclusion - - - - - - - - - 99 4.3 Recommendation. - - - - - - - - 99

Reference - - - - - - - - - 101 Appendices - - - - - - - - - 122

xi

LIST OF FIGURES

Pages

Figures1a-b: Chemical Structure of Butachlor and its metabolite in Animals- - -11

Figure 2: Schematic of Fatty acid Synthesis and Elongation in Plants. - - - -13

Figure 3: General Pathway for Abiotic and Biotic Transformation of Pesticide - -24

Figure 4: General Pathway for Xenobiotic Metabolism in Animals - - - -29

Figure 5: Metabolism of Butachlor in Plants/Animals- - - - - -33

Figure 6: Black Beans seeds (Phaseolus vulgaris) - - - - - - -40

Figure 7: Butastar Commercial Formulation of Butachlor- - - - - -40

Figure 8a-d: Bean plant at two, four and six weeks after planting- - - - -42

Figure 9a-c: Chromatogram / MS of Butachlor standard 1 - - - - -55

Figure 10a-b: Chromatogram/MS of Butachlor standard 2- - - - - -57

Figure11a-c: Chromatogram/MS of Leaf extract (T3) - - - - - -59

Figure 12a-c: Chromatogram/MS of Leaf extract (T2) - - - - - -62

Figure 13a-c: Chromatogram/MS of Leaf extract (T1) - - - - - -64

Figure14: Chromatogram/MS of Control extract (T1) - - - - - -66

xii

LIST OF TABLES

Pages

Table 1: Soil Analysis - - - - - - - - -54

Table 2: Butachlor Herbicide Concentration in Phaseolus vulgaris leaf extract- - -68

Table 3: Bioaccumulation Factor (BAF) of Butachlor in bean plant leaves- - - -69

Table 4: Estimated Quantities of Butachlor Consumed (ppm) by Rabbits for the period of experiment. - - - - - - - - -70

Table 5a/b: Estimated Hazard Quotient and Health Risk Index for consumption of different concentrations of butachlor by an average body weight of 70kg- - - -71

Table 6: Liver Cytochrome P450 (CYP) levels of Liver of Rabbits exposed to different concentrations of bioaccumulated butachlor in the diet.- - -73

Table 7: Liver Glutathione S-transferase activity of Liver of Rabbits exposed to different concentrations of bioaccumulated butachlor in the diet. - - -75

Table 8: Serum AST activity of Rabbits exposed to different concentrations of bioaccumulated butachlor in the diet. - - - - - - -77 Table 9: Serum ALT activity of Rabbits exposed to different concentrations of

bioaccumulated butachlor in the diet. - - - - - - -79

Table 10: Serum ALP activity of Rabbits exposed to different concentrations of bioaccumulated butachlor in the diet. - - - - - - -81

Table 11: Body Weight of Rabbits exposed to different concentrations of bioaccumulated butachlor in the diet. - - - - - - -83

Table 12: Liver Total Protein of Rabbits exposed to different concentrations of bioaccumulated butachlor in the diet. - - - - - - -85

xiii

LIST OF PLATES Plate 1: A photomicrograph of liver sections from control (1) and experimental groups 2,3,4 at day 1- - - - - - - -- - - -- -87

Plate 2: A photomicrograph of liver sections from control (1) and experimental groups 2,3,4 at day 14 - - - - -- - - -- -88

plate 3: A photomicrograph of liver sections from control (1) and experimental groups 2,3,4 at day 28 - -- - - -- - - - -89

xiv

LIST OF ABBREVIATIONS

EPA -Environmental Protection Agency MRL -Maximum Residue Limit VLCFA -Very Long Chain Fatty Acid CYP -Cytochrome P450 GST -Glutathione S-transferase ADI -Acceptable Daily intake HRI -Health risk index HQ -Hazard Quotient RfD -Reference Dose of Contaminant FAO -Food and Agricultural Organisation POP -Persistent organic Pollutant BAF -Bioaccumulation Factor Kow -Octanol/Water Partition Coefficient Kd -Adsorption Coefficient a.i -active ingredient m.a.s.l -miles above sea level GC-MS -gas chromatography-mass spectrometry

1

CHAPTER ONE INTRODUCTION

One of the most important tasks of the economy of developing countries such as Nigeria is to

develop the agricultural sector so as to increase and generate employment, promote self-

sufficiency in food, improve the standard of living, increase gross domestic production and

contribute to general development. To attain food sufficiency, government encourages farmers

to use improved seeds, fertilizers, irrigation and pesticides; thus leading to a higher pesticide

usage, with many problems often associated, such as unsafe use, persistence in the

environment, toxicity to bees, fish and wild life, contamination of water sources, persistent

pesticide accumulating in food chain, negative impact on earth worms and other non-target

organisms being identified (Akinloye et al., 2011).

Pesticide is the term used for a broad range of chemicals and biologicals used for pest control.

The Environmental Protection Agency (EPA) defines a pesticide as any substance or mixture

of substances/chemicals intended to prevent, destroy, repel or mitigate pests (undesirable

animals and plants) (USEPA, 2006). Pesticide also includes plant growth regulators, defoliants

or desiccants (Hagtrum and Subramanyam, 2006). They are manufactured and used in most

countries around the world to protect agricultural, horticultural and forestry crops as well as

increasing their productivity. Pesticide types include: insecticides, herbicides, fungicides,

bactericides, rodenticide nematicides, etc (Ware and Whitacre, 2004). Herbicides are

agrochemicals used for controlling weeds in different crops and they are the most widely used

pesticides (Senseman, 2007).

The use of herbicides has increased worldwide over the years in other to secure food supply for

the teaming global population. In the tropical regions, Nigeria in particular, an intensive

practice has led to higher herbicide usage especially where agricultural labour is scarce or

expensive; herbicides save the farmer’s time by replacing laborious manual weed control.

Many farmers and extension agents lack the technical skills for proper and effective use of

pesticides, resulting to many unfortunate consequences which include; human and livestock

exposure to pesticide poisonings, crop injuries, and environmental pollution (Dugie et al.,

2

2008) Butachlor (N-butoxymethyl)-2-chloro-2’,6-diethylacetamide) is a member of the

chloroacetamide family of herbicides. It is a selective systemic herbicide manufactured by

Monsanto USA in 1970, for the pre-emergent control of annual grasses and certain broad leaf

weeds in rice, barley, wheat and some other leguminous crops (Yu et al., 2003). Butachlor is

the active ingredient of formulations sold under the trade name Machete (USA),

Butaforce/Butastar (Nigeria). It is thought to inhibit the synthesis of lipids, alcohols, fatty

acids, proteins, isoprenoid and flavonoids in non-target plants (Ecobichon, 2001; Heydens et

al., 2002; Gotz and Boger, 2004). Butachlor can degrade rapidly under optimal conditions but

in some soil that lack suitable microbial degraders, it may remain biologically active and

persist for a long time (Lin et al., 2000). The increased application of butachlor on rice ,tea,

wheat, beans and other crops, has been shown to exert detrimental effects on earthworms

(Muthukaruppan and Gunasekaran, 2010) and other non-target animals (Kumari et al., 2009;

Debnath et al., 2002). Studies show that it is a potential threat to agro-ecosystem and human

health through food chains (Tilak et al., 2007; Sinha, 1995). Ecotoxicological studies also

suggested that butachlor and their metabolites may be harmful (genotoxic, neurotoxic) to

aquatic invertebrates (Ateeq et al., 2002, 2006; Tilak et al., 2007; Yin et al., 2007), microbial

communities (Min et al., 2002; Debnath et al., 2002), and possibly being carcinogenic in

animals including apoptosis-resulting from DNA strand breaks and chromosomal aberrations

in cultured mammalian cells (Sinha et al., 1995; Panneerselvam et al., 1999; Geng et al.,

2005a). Butachlor as well as other members of the chloroacetanilide including acetochlor,

alachlor and metoalchlor have been shown to be mutagenic and carcinogenic in rats/mice upon

acute exposure and these have been thoroughly reviewed (USEPA, 1998; Dearfield et al.,

1999; Wilson and Takei, 1999). Butachlor contamination of 0.163ppb has been recorded in

groundwater collected from tube wells adjacent rice fields in Philippines (Natarajan, 1993).

Butachlor has been banned in some countries like Canada and Europe; and it is not been used

for rice cultivation in USA probably because of its toxicity, hydrophobicity, bioaccumulation

and its negative impact on wildlife and humans via the food chain (Kannan et al., 1996; WHO,

2010a). However it is in prevalent use in continents such as Latin America, Asia and Africa.

Many of the herbicides widely used in the 1960s and 1970s have been phased out and replaced

by the newer, safer and more potent herbicides discovered later. The use of some older

3

herbicides has also been restricted, reduced and even eliminated in view of environmental and

toxicological problems. Developing countries maintain that they cannot ban certain older

pesticides, for reasons of cost and/or efficacy. Thus the dilemma of cost/efficacy versus

ecological impacts, including long range impacts via atmospheric transport and access to

modern pesticide formulations at low cost remains a contentious global issue (Stephenson and

Solomon, 1993; FAO, 1995). According to the Stockholm Convention on Persistent Organic

Pollutants (POPs), nine of the twelve most dangerous POPs are pesticides. The POPs are

compounds that resist degradation and thus persist in the environment for longer periods. They

have the ability to bioaccumulate, biomagnify and bioconcentrate; hence they are poisonous to

non-target organisms (Stochlm, 2009). Persistence is usually described in terms of the half-life

(T ½) of a chemical in water, soil, sediment, or air. The T½ is the amount of time necessary for

a given amount of chemical released into the environment to decrease to one-half of its initial

value. Millions of tons of pesticides are applied annually, however less than 5% of these

products are estimated to reach the target organism, with the remainder being deposited on the

soil and non-target organism as well as moving into the atmosphere and water (Hamilton and

Crossley, 2004). The fate of an herbicide applied on the soil include: chemical and

photochemical degradation, microbial degradation, volatilization, runoff into water bodies,

leaching into groundwater, adsorption by soil particles and uptake by plants/animals which may

result to bioaccumulation. This is dependent on abiotic environmental conditions (temperature,

moisture, soil pH, etc) microbial or plant species (or both), pesticide characteristics (chemical

or physical-hydrophobicity, Kow, etc (Lyman, 1995; Schnoor, 1996).

1.1 Bioaccumulation of Herbicides When herbicides are applied, acceptable remainders of active substances (maximum residue

limit, MRL) can often be detected in cultivated plants depending on the physico-chemical

properties of the active substances of herbicides and ways of detoxification, some of these

pollutants tend to increase concentration while passing through organisms of higher trophic

levels, thus leading to a significant bioaccumulation in food chains (Allinson and Morita,

1995). Bioaccumulation is the process by which organisms accumulate chemicals such as

pesticides both directly from the abiotic environment (i.e., water, air, soil) and from dietary

sources (trophic transfer) (Baron, 1995). Studies have shown that herbicides or its metabolites

4

can enter into the human body along food chain, where they may be metabolised or

accumulated in fatty tissues and this creates potential health risks to human (Hodgson and

Levi, 1997). Bioaccumulation occurs when an organism absorbs a toxic substance at a rate

greater than that at which the substance is lost. Thus, the longer the biological half-life of the

substance, the greater the risk of chronic poisoning, even if environmental levels of the toxin

are not very high (Hamilton and Crossley, 2004). Bioaccumulation is a natural process that

gradually concentrates non-toxic levels of pollutants into toxic levels within a biota causing

unpleasant side effects (Connell, 1990). The regular intake of sub toxic levels of persistent

pollutants can gradually bioaccumulate up to toxic levels and after some time produce chronic

effects. From the roots of plants, the pesticides move by translocation to stems and then often

a strong bioaccumulation occurs in the leaves (Bicalho and Langenbach, 2012) or fruits and

such crops where pesticides are used intensively maybe consumed by cattle, humans or wild

life. A strong increase in the concentrations of these molecules can occur in a process called

biomagnification. In order to minimize ecotoxicity, there is the need for the restriction of

inappropriate use of pesticide, thus removing them from the food chain and water reserves.

Bioaccumulation studies are used to assess the rate and extent of contaminant accumulation in

a given lower trophic level and this is important for assessing the hazard it poses for a higher

trophic level of a food chain (USEPA, 2000). The extent of chemical accumulation is

expressed in form of bioaccumulation factor (BAF); this is a ratio of the concentration of the

chemical in the organism (plant, animal tissue) to that in the surrounding environment (soil,

air, water). It is a major criterion for assessing bioaccumulation. The greater the value of BAF,

the more the chemical accumulates in the plant/animal and the higher the risk of exposure to

humans. Another criterion for bioaccumulation potential is the n- octanol/water partition

coefficient (Kow); this is the ratio of a chemical’s solubility in n-octanol to its solubility in

water at equilibrium. It is often used to express lipophilicity or hydrophobicity. For organic

chemicals, log Kow ranges from –3 to 7. Organic chemicals that have log Kow higher than 2 are

usually hydrophobic and considered liable to bioaccumulate in biota (Oliver and Charlton,

1984; Elzerman and Coates, 1987; Franke et al., 1994; USEPA, 2000). Herbicide use can

result to environmental, ecological and health effects. In health effects, they may cause acute

or chronic effects when exposed. In animals and humans, these effects range from simple

5

irritation of the skin and eyes to more severe and chronic effects affecting the nervous system

(Gorell et al., 1998; Tanner et al., 2011; Mostafallou and Abdollahi, 2012), disruption of

hormonal functions causing reproductive problems (Bosveld et al., 1995; Bretveld et al.,

2006) ,carcinogenetic (Ou et al., 2000), teratogenic (Paganelli et al., 2010) genotoxic, or

result to mortality (Dieter et al., 1996).

1.2 Risk Assessment of Herbicides The analysis of herbicides and their residues had in the past aided objective re-evaluation and

reassessment of these substances on a benefit-risk analysis basis and their subsequent

withdrawal from use when found to be hazardous to human health and the environment

(Achudume, 2011). Risk assessment of chemicals is described as a process intended to

calculate or estimate the risk to a given target organism, system or (sub) population, including

identification of attendant uncertainties, following exposure to a particular chemical taking

into account the inherent characteristics of the agent of concern as well as the characteristics

of the specific target system (OECD, 2003). Risk Assessment is the central component of risk

analysis and provides a scientific basis for risk management decisions on measures that may

be needed to protect human health. It evaluates the possible danger in the consumption of

organic chemicals by animals and human. Risk is characterized by assessing the Hazard

Quotient (HQ) and the Health risk index (HRI). The HQ is a simple ratio of single exposure

and effect values and may be used to express hazard or relative safety (Gerba, 2010; Wang et

al., 2005). Assessments may be undertaken for acute (short term) or chronic (long term)

exposures, where acute exposure covers daily average and chronic if exposure is over the

entire lifetime.

In most countries, herbicides must be approved for sale and use by government agencies such

as Environmental Protection Agency (EPA) and the National Agency for Food and Drug

Administration (NAFDAC) under the Food Quality Protection in Nigeria. Pesticides are

regulated after complex studies (10 field trials or tests) to ensure that these products do not

pose adverse effects to humans or the environment. Standards are then set for the level of

pesticide residue that is allowed in or on crops (USEPA, 2000; Hamilton and Crossley, 2004).

Internationally, risk assessment of chemical substances present in or on food forms the core

work of Joint Food and Agricultural Organisation and the World Health Organisation

6

(FAO/WHO and Expert committee on Food Additives (JECFA). These organisations base

their evaluations on scientific principles and ensure consistency in their risk assessments

determination, Also the Codex Alimentarius Commission (established by FAO and WHO in

1962) together with the committee establishes maximum residue limits (MRL) for pesticide

residues, veterinary drug residues, contaminants and food additives in order to facilitate

international trade and protect the health of consumers (WHO/ FAO, 2010a). Each year,

140,000 tons of pesticides are sprayed onto crops in the European (EU) alone. Fruits and

vegetables are the crops mostly contaminated. According to data from the EU’s pesticides

action network in 2008, some 350 different pesticides were detected in food produced in the

EU. More than 5% of products contained pesticides at levels exceeding the EU maximum

permitted levels (Fenik et al., 2011). Scientific researchers have shown that several health

effects due to pesticides were apparent at much lower doses than the typical levels of pesticide

residues found in food (Nebeker et al., 1994; Walz, 2010). Studies have also been carried out

in some other countries and the detection of pesticides/residues in food and drinks were

reported; some of which are above or below the maximum residue limit (MRL), as stated by

the Codex Maximum Residue limits/Extraneaous Maximum Residue limit (MRL/EMRL)

(Tadeoa et al., 2000; Tseng et al, 2002,Sun et al., 2005; Chang et al., 2005; WHO/FAO,

2006; Darko and Acquaah, 2008; Qiu et al., 2010; Etonihu et al., 2011; Fenik et al., 2011).

1.3 Bean Plant (Phaseolus vulgaris) The bean plant is a herbaceous legume grown annually for its edible fruit, either the dry seed

or the unripe fruit, both of which are referred to as beans. It belongs to the family known as

leguminosae. It is a warm season growing legume that does better under subtropical and

temperate conditions. It requires a moderate well-distributed rainfall (300-400 mm per crop

cycle) with average temperatures range between 17.5°C and 27°C. The common bean grows

well on a large variety of soils with pH ranging from 4 to 9. It does better on well-drained,

sandy loam, silt loam or clay loam soils, rich in organic content. The duration of the cycle for

the common bean ranges from 60–90 days depending on the variety. The leaves of this

leguminous plant is also occasionally used as vegetable, the leaves and the straw can be used

for fodder and fed fresh to livestock. The creeping variety is cultivated around the warm

season (Ferreira et al., 1997). The black bean variety popularly called Akidi, is commonly

grown in the eastern part of Nigeria for its protein rich seed and edible leaves.

7

1.4 Historical Use of Herbicides. Long before 2000 BC, humans have utilized pesticides to protect their crops. The first known

pesticide is elemental sulfur dusting used in ancient summer about 450 years ago in ancient

Mesopotia. By the 15-19th century saw the use of toxic chemicals such as arsenic mercury,

lead to nicotine and other natural pesticides like pyrethrum which is derived from

chrysanthemums, and rotenone, which is derived from the roots of tropical vegetables in the

1950s (Miller, 2002). Paul Muller discovered that DDT was a very effective insecticide and

the organochlorines became dominant, however later replaced by the organophosphates and

carbamates by 1975. Herbicides became common in the 1940s–1950s led by the triazine and

other nitrogen-based compounds, carboxylic acids and glyphosate (Miller, 2002). The first

widely used herbicide was 2, 4–dichlorophenxyacetic acid (2, 4-DPNA) which was

commercialized by the paint company Sherwin–Williams. It is easy and inexpensive to

manufacture, kills many broad leaf plants, however, high doses of 2, 4-DPNA could be

harmful. The low cost of 2,4–DPNA led to continued usage today and it remains one of the

most commonly used herbicides in the world. Seventy-five percent of all pesticides in the

world are used by developed countries, but use in developing countries is increasing (Ritter,

2009). The triazine family of herbicides which include atriazine, was being discovered to be

the herbicide family of greatest concern regarding ground water contamination. Glyphosate

sold with a brand name Roundup was introduced in 1974 for non-selective weed control, and

it is now a major herbicide due to the development of crop plants resistant to it. In the 1970

the use of chemicals such as DDT and some organochlorines were banned Under the

Stockholm Convention on Persistent Organic pollutant, because of their long persistence in

the environment, although DDT is still been used in some developing nations to treat malaria

and tropical diseases (WHO, 1989). Today organochlorine pesticide levels are still detected

in fish from waterways (Chindah et al., 2004). World-wide, an estimated 2.3 billion kg of

1,600 different pesticides are applied yearly (Pimentel, 1995). In Europe, the total agricultural

use of pesticides is estimated to be 350 000 tons of active ingredients per year (Kreuger, 1999)

It has been established that pesticide application in Nigeria ranges from 125,000 to 130,000

metric tons yearly (Asogwa and Dongo, 2009). World Health Organisation maintained that an

estimated three (3) million farmers in developing countries experience acute poisoning from

8

pesticide and eighteen thousand (18000) of them eventually died from this (FAO, 2002).

Nigeria is not immune to this phenomenon, one hundred and twelve (112) people were

hospitalized and two (2) children died after eating beans preserved with pesticides in Bekwara

Local Government Area of Cross Rivers state. Again, one hundred and twenty (120) students

of a secondary school in Doma, Gombe State became sick as a result of eating food items

contaminated by pesticides (Shaibu, 2008). Abrahame and Brunt, (1984) explained that

though data on the amount of pesticide use generally in Africa is difficult to ascertain, it has

been established that import of pesticide into the continent is on the increase. Nigeria ranked

first according to Bull, (1982) among West African countries importing pesticides from the

United Kingdom having imported 16,462 metric tonnes of pesticide in 1980; it accounts for

about 93% of United Kingdom’s pesticide exports to West African countries. According to

Lee, 2006, 75% of all pesticide is used in developed countries and yet developing countries

with just 25% of global pesticide use, accounts for a disproportional number of cases of

pesticide poisoning and deaths. Some of the inherent problems in pesticide application

include: toxicity, phytotoxicity, mismanagement and maintenance of equipment, poor

availability of pesticides/equipment, lack of safety measures, extension services, wrong

dosage of pesticide and pesticide misuse (Asogwa and Dongo, 2009). Problems associated

with herbicide hazards to man and the environment are not confined to the developing

countries. Developed nations have already suffered these problems, and still facing some

problems in certain locations. For many reasons, the severity of herbicide hazards is much

pronounced in Third World Countries (Mansour, 2004). Today about 4500 pesticides are in

general use all over the world, out of which 25 have high toxicity potential to a wide range of

flora and fauna of economic importance (Adhikary and Sahu, 2001).

1.5 Classification of Pesticides Pesticides can be classified according to target species; insecticides, herbicides, fungicides,

bactericides, rodenticides, nematicides and avicides (Ware and Whitacre, 2004); pattern of use

(defoliants, repellants), chemical structure (organochlorines, organophosphates, carbamates,

chloroacetamides and phenoxyacetic acids), mechanism of action (enzyme inhibitors and

photosystem inhibitors). Pesticides can also be classified as inorganic, synthetic or biological

9

(biopesticides). Biological biopesticides include microbial pesticides and biochemical

pesticides (Ware, 2000).

1.5.1 Classification of Herbicides Herbicides can be classified based on: (a) Method of application/use (b) Type of vegetation

controlled, (c) Mode of action/activity and (d) Chemical nature/family.

1.5.1.1 Classification based on Method of Application

They can be soil applied or foliar applied. Soil- applied herbicides are applied to the soil and

are taken up by the roots and/or hypocotyls of the target plant. There are two main types of

soil applied herbicides

a. Pre-plant incorporated herbicides which are applied prior to planting and mechanical

incorporation into the soil. They are mixed with the soil before seeding. This incorporation is

another way to prevent dissipation through photodecomposition and/or volatility.

b. Pre-emergent Herbicides are applied to the soil before the crop and weed emerges thus

preventing germination or early growth of weed seeds

Foliar applied herbicides 5are applied to plant foliage since they have foliar activity. Post

emergent herbicides are applied to the soil or foliage after the germination of crops and weeds

(Senseman, 2007).

1.5.1.2 Classification based on the Type of Vegetation:

Selectivity is the process by which a herbicide controls certain plants but leaves others

unharmed. Herbicides can be selective or non-selective i.e. the selective herbicides kill

specific targets (weeds) while leaving the desired crop relatively unharmed. Non selective

herbicide kill all type of plant material including target and non-target plants, when in contact,

hence they are commonly used for preparation of land, industrial sites, railways and waste

ground, forestry, wildlife habitat and pasture systems (Senseman, 2007).

1.5.1.3 Classification based on Activity/Mode of Action This refers to how they are translocated in plants.

a. Contact herbicides (non-systemic) destroy only the plant tissue in contact with the

chemical, they are fast acting herbicides however less effective on perennial plants which are

able to grow from rhizomes, roots or tubers.

10

b. Systemic herbicides (translocated): are translocated through the plant, either from

foliar application down to the roots or from soil application up to the leaves and stems. They

are capable of controlling perennial plants and may be slower acting but ultimately more

effective than contact herbicides (Rao, 2000).

1.5.1.4 Classification based on chemical nature/family

Herbicide may be divided into two groups – Inorganic and organic herbicide. The inorganic

herbicides are made up of inorganic compounds which include copper sulphate, sodium

arsenate, sulphur acid and sodium chlorate. They were used between 1896–1930s, however

organic herbicides dominate modern agriculture. The organic herbicides include; Phenoxy

carboxylic acid herbicides e.g. 2,4-dichlorophenoxyacetic acid, Triazines (atrazine)

Bipyridyliums (paraquat), Sulphonyl Ureas, Dinitroanilines and Chloroacetamides (butachlor)

(Rao, 2000). Chloroacetamides belong to a subgroup of the acetanilides or acetamides

(substituted acidamide), having a phenyl ring attached to the amide nitrogen. Some of the

members of the acetamides are applied post-emergence while others are pre-emergence; all

are effective on germinating weeds (shoot and root inhibitors). The herbicidal mode of action

is not totally understood, however, it is known that this class of herbicides inhibits

biosysnthesis of lipids, fatty acids, proteins, isoprenoids and flavonoid in plants (Heydens et

al., 2002). Studies showed that they cause herbicidal effect via conjugation of acetyl

coenzyme A and other sulfhydryl-containing enzymes with consequent inhibition of critical

function needed for the germination or survival of seedlings. The effective shelf-life of most

chloroacetamide is of the order of 6-12weeks. The members of the acetamides include;

alachlor, acetochlor, butachlor, metolachlor, propachlor and allidochlor.

1.6 Butachlor

1.6.1 Physicochemical Properties of Butachlor

Butachlor (N-butoxymethyl) -2-chloro-2’,6-diethylacetamide-C17 H26 NO2Cl) is an amber

coloured liquid with a faint sweet odour, with a molecular weight of 311.9g. The solubility of

butachlor in water is 20ppm at 25oC, it is semi-volatile and miscible with alcohol, ether, n-

hexane, acetone and benzene. The partition coefficient (1-octanol/water)Kow is3.16 X 1004

11

and logKow is 4.50 at pH 7, while the Koc is 700mL/g and the vapour pressure is 2.90×10-6

mmHg (=3.86×10–4 Pa) (25°C). The specific gravity /density is 1.076 (25oC) and it is not

hydrolyzable. The melting and boiling points are -0.55 and 156oC respectively. The half-life

in soil due to biodegradability (aerobic degradation) is 42 -70 days (6-10weeks) (Heydens et

al., 2002).The structure of butachlor and its metabolite-2,6 diethylacetamide are shown below

in figures 1a and b.

CH2CH3

N

CH2CH3COCH2Cl

CH2O(CH2)3CH3

a) Structure of Butachlor

b) Metabolite of butachlor in animal

Figure 1a: Chemical Structure of Butachlor b) Metabolite of butachlor in animal.

Butachlor was developed by Monsanto and commercialized as machete USA in 1970 for the

pre-emergent control of annual grasses and certain broad leaf weeds in rice, barley, wheat and

some other leguminous crops. It is the active ingredient of an emulsifiable concentrate sold

under the trade name Butastar and Butaforce in Nigeria. Butachlor is a selective systemic

herbicide, absorbed primarily by the germinating shoots and secondarily by the roots, with

translocation throughout the plant, giving higher concentrations in vegetative parts than in the

reproductive parts (Rao, 2000). It is known to inhibit cell division mainly by inhibiting lipid

and protein synthesis. It’s activity is dependent on water availability such as rainfall following

12

treatment, overhead irrigation or applications to standing water as in rice culture. In soil its

degradation is principally by microbial activity (Rao, 2000).

1.6.2 Toxicity of Butachlor

World Health Organisation (WHO) has classified butachlor under Class ΙΙΙ toxicity level.

Studies on acute toxicity have been investigated and it was discovered that the acute oral LD50

for rat is 2000 mg/kg bw, mice 4747 mg/kg bw, for rabbits >5010mg/kg bw and the LC50 for

fish 0.1-0.14mg/l. Other studies done on rabbits by exposure to butachlor for 21 days at dose

levels of 250mg/kg/day showed signs of dermal irritation with LD50>13000mg/kg (Wilson

and Takei, 1999; Kreiger, 2001). The chronic (subchronic) toxicity of butachlor has also been

evaluated in dogs, mice and rats. The primary target organs have been shown to be the liver,

kidney and bladder in one or more species (Wilson and Takei, 1999).

1.7 Mode of Action of Herbicides in Target Plants

Herbicides bring about various physiological and biochemical effects on the growth and

development of emerging seedlings as well as established plants, either on or after coming

into contact with the plant surface or reaching the site of action within the plant tissue. The

net result is death of the plant. These physiological and biochemical effects are followed by

various types of visual injury symptoms on susceptible plants. These include chlorosis,

defoliation stunting, necrosis, growth stimulation, cupping of leaves, marginal leaf burn,

desiccation, delayed emergence, germination failure etc (Rao, 2000).

The rate of appearance of these signs varies with the characteristic actions of the herbicide and

depends on the degree of tolerance or susceptibility of the plant species. Environmental

factors and soil conditions affecting plant growth, as well as herbicide formulation and

application method significantly influence the effect of herbicides. Herbicides differ in their

site of action, there are more than one site of action and the primary site is the most sensitive

which is affected first; as the herbicide concentration builds up in the tissue, the secondary

and tertiary sites may be involved. The different physiological and chemical processes that

occur within the living plant include; photosynthesis, mitochondrial activities, protein/nucleic

acid biosynthesis, pigment biosynthesis, fatty acid/lipid biosynthesis, amino acid biosynthesis,

13

hydrolytic enzyme activities, aromatic compound biosynthesis, etc. (Rao, 2000).Studies show

that butachlor acts by inhibiting the elongase responsible for the elongation of very long chain

fatty acids (VLCFA) and geranyl geranyl pyrophosphate cyclisation enzymes (Matthes et al.,

1998; Gotz and Boger, 2004). A majority of VLCFAs is located in the plasma membrane and

as cuticular and epicuticular waxes. When absent the membrane loses stability and becomes

leaky leading to death of the herbicide-treated plant (Matthes and Böger, 2002).

Fatty Acid Biosynthesis and Elongation

Figure 2. Simplified schematic of fatty acid synthesis and elongation in plants. Abbreviations: ACCase, acetyl-CoA carboxylase; ACP, acyl carrier protein; ACS, acetyl-CoA synthase; CoA, coenzyme A; dims, cyclohexanedione inhibitors; FAS, fatty acid synthase; fops, aryloxyphenoxy propionate inhibitors; PDC, pyruvate dehydrogenase complex. Source: Gronwald, (1991). Lipid biosynthesis inhibitors. Weed Sci. 39:435-449.

14

1.8 The Soil Ecosystem

The Soil is a complex ecosystem of many species including plants, fauna and microorganisms.

It is a variable mixture of mineral and organic materials with living, dead, decaying biologic

components, air and water (Tomaz, 2013). The fate of any herbicide depends on its properties,

environmental factors and the properties of the soils to which it is applied.

(i) Soil properties that affect the uptake of pesticide (herbicide) The uptake of a xenobiotic by the crop, following a pesticide treatment, depends on the degree

of exposure from both the roots and aerial parts of the plant. Pesticides on the surface of the

plant or in the soil will be subject to a range of environmental factors, e.g. photolysis and

microbial activity, which can result in degradation of the pesticide. These degradation

products and the parent pesticide are therefore available for absorption. A further factor

influencing the uptake of xenobiotics from the soil is the interaction of chemicals with the soil

(Hellstrom, 2004).

(a) Soil Adsorption This process takes place when pesticides sprayed on the soil surface adhere to the soil

particles and organic matter. Soil properties that affect herbicide adsorption are soil pH,

organic matter content, soil moisture, soil temperature and soil colloids (Rao, 2000). Soils

high in organic matter or clay are the most adsorptive. A pesticide that is adsorbed by the soil

is less likely to volatilize, leach or be broken down by microbes. However, it will move with

the soil if the soil is eroded. They are not strongly adsorbed to sandy soils. Herbicides are

adsorbed to soil colloids to varying degrees and the colloids have negatively charged sites to

which herbicides can be adsorbed. Adsorption reduces herbicide activity in soils because the

molecules adsorbed to the colloids may not be available for desorption. Desorbed or non-

sorbed molecules are bio-available and can move into the food chain or into ground water

(Kerle et al., 2007). Adsorption/Desorption are thus the key processes controlling herbicide

efficacy, dissipation and behavior in soil as well as the contamination of ground and surface–

waters. Absorption is the movement of pesticides into organisms (plants, animals) or

structures (wood). To be absorbed into the roots, the xenobiotic needs to be bioavailable or

present in the soil–water compartment, a function of the interactions of the chemical with soil

15

organic matter or clay particles. This interaction is measured as the adsorption coefficient, Kd

or Koc ; Koc is the tendency of herbicide sorption to organic carbon. Higher values (greater

than 1000) indicate a herbicide that is very strongly attached to soil and is less likely to move

unless soil erosion occurs. Lower values (less than 300-500) indicate herbicide that tends to

move with water and have the potential to leach or move with surface runoff (Monaco et al.,

2002; Connell, 1990). The Koc for butachlor is 700ml/g which indicates moderate soil sorption

as compared to trifluralin with Koc of 7000ml/g which strongly attaches to soil.

The uptake of compounds by the root is therefore a function of the soil adsorption coefficient

of the xenobiotic, the concentration gradient between the soil solution and that inside the root,

the octanol/water partition coefficient Kow (lipophilicity), degree of ionization, and on the

mass flow of water. The most important property is hydrophobicity, which usually is

expressed as the 1-octanol/water partition coefficient (Kow), or more often log Kow. This is the

ratio of a chemical’s solubility in n-octanol to its solubility in water at equilibrium (Bacci,

1994). Log Kow spans over a wide range for different organic compounds (Hellstrom, 2004). It

is an important basis for estimating bioaccumulation factor (BAF). The Kow also provides

information on how strongly organic and inorganic compounds are likely to bind to soil or

sediment particles, or to partition into lipid (octanol) versus aqueous phase liquids. Strong

binding indicates a high potential to persist and accumulate in soils and sediments;

soil/sediment binding also tends to be correlated with the potential to bio accumulate. Since

lipophilic substances with high octanol-water coefficient remain preferencially in soils and

with little bioavailability thus they have low bioaccumulation potential (Connell, 1990). More

hydrophobic compounds, having a higher Kow, are sorbed more strongly to organic particles in

the soil. Due to the solubility of 20ppm and high hydrophobicity of log kow 4.5 butachlor

presents high adsorption in soils with medium to high organic matter (Wang et al., 1999)

(b) Soil Organic Matter (SOM) Organic matter consists of decaying plant material. The content of organic carbon in soil is

one of the most important environmental factors influencing root-uptake of non-ionic organic

compounds from soil into roots. The higher the soil organic matter content, the greater the

soil’s ability to hold both water and adsorbed pesticides. To further describe the distribution of

a chemical in soil, the soil-water partition coefficient (Kd) is used. Kd is generally

16

proportionally to the hydrophobicity of the compound and to the amount of soil organic

matter (Hellstrom, 2004). The smaller the Kd value the greater the concentration of herbicide

in solution. In soils with high organic matter content and clay content, lipophilic and charged

pesticides are retained in the soil organic matter for longer time and the uptake into plants

decreases (Trapp et al., 1990). Thus a soil with higher organic matter content will have more

pesticide adsorbed to the soil, and this reduces detachment and leaching, but may have a

higher runoff potential because more of the chemical is retained in the surface zone of the soil.

The reverse occurs in low organic matter sandy soils with low cation exchange capacity

(CEC). Some studies have also shown that soil amendment with manure compost may reduce

bioavailability by retaining the toxic organic chemicals in the organic matter and therefore

reduce the hazardous effects by bioaccumulation (Jiang et al., 2010; Tomaz, 2013).

Ecotoxicology depends on soil organic matter (SOM). When SOM is high the

ecotoxicological effects are low and when the SOM is low the effects are high (Tomaz, 2013).

(c) Soil Texture and Structure Soil texture is the relative proportions of sand, silt, and clay-sized particles. Percolating water

moves faster in sandy soils, and fewer binding sites are available for the adsorption of

dissolved chemicals when compared to clay or silt soils. Though sandy soils are more prone to

pesticide movement, leaching may also occur in clay or silt soils. Soil structure which is the

shape or arrangement of soil particles plays an important role in determining the size and

shape of the pores through which water moves. Small amounts of pesticides may also move

through soil cracks. Light textured sandy soils do not adsorb and retain high amount of

hazardous products and this will both bioaccumulate in living tissues and pollute water

sources. In soils of this type plants strongly adsorb pesticides resulting in enhanced

contamination with subsequent phytotoxicity and toxicological effects on fauna (Covaci et al.,

2010). Soils may function as a filter or as source of pollutants, depending mainly on the kind

of soil. It has been shown that the soil infiltration capacity depends on soil texture

characteristics, porosity and humidity. Soils with a sandy texture are more susceptible to the

process of leaching (less adsoption), while clay soils have greater pesticide adsorption

potential and less leaching potential (Tomaz, 2013).

17

(d) Soil pH Soil pH will affect the electrical charge of certain pesticides. The electrical charge will

determine the type and degree of adsorption. It also affects the ionic or molecular character of

the chemical, the ionic character and the cation exchange capacity (CEC) of the soil colloids,

as well as the activity of soil microorganisms (Rao, 2000). Non-ionic herbicides such as the

chloroacetamides do not react with water and do not carry any electrical charge, but they are

still affected by soil pH as they are polar in nature. Differences in the pH of the soil affect its

ability to adsorb and retain herbicide molecules, thereby affecting leaching of the herbicide

through the soil profile. Different herbicides respond differently to changes in soil pH and Soil

pH has been shown to affect the speed of degradation of chloracetamides. Liu et al. (2002)

reported that the greatest degradation of acetochlor took place under strong alkaline conditions

(pH 12) and was lower under acidic conditions (pH < 5). However, soil pH also affects

microbial degradation of the herbicide as it influences the microbial life in the soil. Microbe

numbers tend to increase in soils with a neutral pH, resulting in a faster loss of activity in

these soils due to greater microbial activity (Rao, 2000). Soil pH influences the growth of

microorganism, for instance bacteria and actinomyces are favored by soils having a medium

to high pH and their activity is reduced below pH 4.5. Hence the persistence, uptake as well as

bio-accumulation of butachlor are enhanced at low pH. Butachlor is easily hydrolysed at

alkaline pH and as such not effective in the soil with high pH since alkaline pH favours the

growth of microorganisms that enhance its degradation (WSSA, 2002).

(e) Soil Moisture Herbicide adsorption and phytotoxicity is very dependent on soil moisture, which is important

for herbicide movement, particularly the herbicide is moving through mass flow (Rao, 2000).

The amount of moisture in the soil affects the amount of the herbicide particles that can be

adsorbed by the soil, as these molecules tend to compete with water molecules for absorption

sites on mineral colloids. The space available for herbicides to go into solution also decreases

as soils dry out, as such less free herbicide is present in dry soils. Under dry conditions, plants

are therefore less likely to absorb toxic concentrations of herbicide (Rao, 2000). When soil

moisture is replenished, herbicide will desorb from the colloids and re-enter the soil solution.

18

1.9 Fate of Herbicides in Soil Ecosystem Most herbicides are applied as water based sprays using ground equipment or applied aerially

using helicopters or air plants. The ground equipment varies in design, it could be self-

propelled sprayers, towed handled, or horse drawn sprayers. The metabolic fate of herbicides

is dependent on abiotic environmental conditions (temperature, moisture, soil pH etc)

microbial or plant species (or both), herbicides characteristics (chemical or physical-

hydrophobicity, pKa, Kow, etc (Schnoor, 1996; Lyman, 1995). In the environment, organic

pollutants such as herbicides can be degraded by Abiotic: chemical (Sarmach and Sabadie,

2002), photochemical (Nelieu et al., 2001) or by Biotic/biological processes (van Eerd et al,

2003). Other ways by which herbicides can be removed from site of application via physical

processes include; surface run-offs from agricultural lands into streams or rivers, adsorption

by soil particles (Hamilton and Crossley, 2004). Degradation rates after release to the

environment vary widely between substances, with half-lives from minutes to many years.

Degradation rates and the half-lives of herbicides are specific for one location and season. The

following are ways of degradation of herbicides.

1.9.1 Chemical/Photochemical Degradation: These are abiotic processes that result in the

chemical or physical breakdown of the chemical components of the pesticides(herbicides)

leading to reactions such as oxidation, hydrolysis of the chemicals into ground water (leaching

into solution), reduction, photolysis and volatilization. Chemical decomposition of herbicides

in soils is affected by soil moisture, pH, herbicide adsorption, soil temperature and types of

ions that are present in the soil solution (Hamilton and Crossley, 2004)

(a) Photo decomposition: The molecules of some herbicides are unstable in light (ultraviolet)

thus they are readily degraded by light when left on soil surface for an extended period of

time. This process plays an important part of the degradation of pre-emergence herbicides.

Ultraviolet ion is absorbed by the molecules of these light sensitive herbicides and this

destabilizes the herbicide molecules, causing them to lose their herbicidal activity or become

more phytotoxic. At UV wavelengths reaching the earth’s surface, sunlight has sufficient

energy to cause direct photochemical reactions by rearranging or cleaving carbonyl double-

bonds, carbon–halogen, carbon–nitrogen, some carbon–carbon, and peroxide O–O bonds, but

not enough to cleave most carbon–oxygen or carbon–hydrogen bonds (Mill, 1993). Lyman

19

(1995) states that the end result of photolysis may include such reactions as dissociation or

fragmentation, rearrangement or isomerization, cyclization, photo-reduction by hydrogen-ion

extraction from other molecules, dimerization and related addition reactions, photoionization

and electron transfer reactions.

Photolysis is relatively insensitive to temperature and pH effects compared to hydrolysis

(Mill, 1993). However, as would be expected, photolysis is strongly affected by factors

influencing the spectral distribution, intensity and duration of sunlight. Such factors include

latitude, time and date, cloud cover, dust, etc. and the extent of absorption of UV–βradiation

by atmospheric ozone. Laboratory studies have generally found that direct or indirect

photolysis occurs more slowly on soil surfaces than in water. Only a thin layer of soil is either

reached directly by photons or indirectly by diffusion of reaction products such as singlet

oxygen. Hence, the extent to which photolysis occurs is affected by the amount of exposure of

the soil surface to sunlight and the amount of pesticide available at the soil surface. Once

incorporated into the soil by cultivation or leached in by rain or irrigation, a large proportion

of pesticide is likely to be unavailable for photolysis, unless returned to the surface by

volatilization (Hamilton and Crossley, 2004). The rate and extent of photochemical

degradation depends on the chemical nature of the compound, the wave length of light and the

presence of other chemicals (Stamgroom et al., 2000). The acetamides are slow to undergo

photolyzed reaction particularly under soil conditions. Photodecomposition of butachlor

involves debutoxymethylation, dechlorination followed by hydroxylation, O-dealkylation and

polymerization.The photodecomposed products include 2chloro-2, 6, diethyl acetanilide, 2

Hydroxy 2, 6 diethyl N-(butoxymethyl) acetamide and N-2’, 6’ – diethylphenyl 2, 3

dihydrosazole 4-one (Lin et al., 2000)

(b) Volatilization: Volatility is a physical process in a substance and involves a change from

a solid or liquid state to gaseous state. Soil applied herbicides compete with soil moisture for

sites on soil colloids. Herbicides molecules loosely held to soil colloids may be moved to the

soil surface with water by capillary action and lost to the atmosphere by volatilization. It is

highly dependent on the physical properties of the molecule; vapour pressure, octanol/water

20

partition coefficient, water solubility, adsorption coefficient, the type and condition of the

surface on which the herbicide is deposited (Hodgson and Goldstein, 2001; Mill, 1993).

(c) Hydrolysis: This refers to the cleavage of a bond and formation of a new bond with the

oxygen atom of water, i.e introducing HOH or OH into the molecule gives the generalization

that hydrolysis may be important in any molecule where alkyl, carbonyl or imino carbon

atoms are linked to halogen, oxygen or nitrogen atoms or groups through σ-bonds. Hydrolysis

may occur abiotically or biotically and this is a major means of chemical alteration in the

degradation pathways of many pesticides. Abiotic hydrolysis may be the principal means of

pesticide degradation where biological activity is low. These reactions may be strongly pH-

dependent, occurring in the presence of H2O, H3O+ and OH− to varying degrees (respectively,

neutral, acid and base hydrolysis), and related to the acid–base dissociation characteristics

(pKa) of the molecule. The rate of hydrolysis increases with increasing temperature, and may

be affected by other environmental factors, such as whether the pesticide is present in solution

or adsorbed to particles. In general, hydrolysis products are more polar than the molecules

from which they are derived and may be significantly more water soluble and less subject to

bioaccumulation (Holland and Sinclair, 2004).

(d) Solubility: This process shows the capacity of a pesticide or a chemical to dissolve in

water, Solubility is often expressed in milligrams per liter (mg/l) or parts per million (ppm).

Pesticides with high degree of solubility enjoy greater tendency to pass through the soil and

reach to groundwater. Others with solubility of less than 1.0 mg/l are normally strongly

adsorbed or attached to sediment and loss to surface waters via soil erosion and is of primary

environmental concern. Herbicides differ in their solubility in water; the greater the solubility

of an herbicide, the greater the amount of that herbicides that gets into soil water.

(e) Adsorption-desorption: Adsorption refers to the adhesion of pesticide molecules on

the surface of soils. This adhesion is the result of physical or chemical attraction between

substances. Desorption is the reverse of adsorption and it refers to the tendency of pesticide

molecules to separate or become detached from the surfaces of soils to which they are

attached. The adsorption of a herbicide into the soil (based on Kd or Koc) can result in a

reduced ability of microorganisms to break it down, as the herbicide is less readily available

21

(or accessible) in the soil solution. Thus the greater the adsorption the less degradation on the

herbicide (Rao, 2000)

(f) Leaching: Leaching refers to the downward movement of water and its dissolved

substances in the soil. It is a physical process by which a herbicide may be removed from the

soil profile. Leaching of herbicides is affected by the chemical properties of the herbicide, the

soil texture, solubility of the herbicide, adsorption of herbicide and by the amount of water

reaching the soil (Holland and Sinclair, 2004)

(g) Persistence Persistence is the property of pesticides, which determines how long they can survive in the

environment. The degree of persistence is determined by the length of time a pesticide can

remain in the environment and also its effective durability in combating the target pests.

Persistence can be expressed in terms of half-life, or the time required for one-half of the

pesticide to discompose to products or other molecule than the original pesticide. Pesticides

with long degradation half-lives will typically have greater annual pesticide losses in runoff

than pesticides with smaller half-lives due to the longer key period where significant amount

of pesticides and precipitation occur (Leonard, 1990). The persistence of butachlor in soils

depends on many factors like soil moisture, soil temperature, organic matter content and

microbial activity (Charkroaborty et al., 1990; Kerle et al., 2007).

1.9.2 Biological Degradation: Abiotic degradation processes may be significant in the dissipation

of pesticides from air, soil and water. However, in many cases pesticides or their initial

degradation products are relatively stable to abiotic degradation processes. Pesticide residues

may also reach environments where conditions are unfavorable for abiotic degradation to

occur (e.g. unsuitable pH for hydrolysis or protection from sunlight). Fortunately, biological

processes, primarily microbial metabolism, are often highly effective in assisting the

dissipation of pesticides once they reach the environment. It includes biotic processes such as

microbial or plant metabolism which is a major route of detoxification. However, herbicides

may be biologically unavailable because of compartmentalization which occurs as a result of

pesticide adsorption to soil and soil colloids without altering the chemical structure of the

original molecule (Holland and Sinclair, 2004).

22

(i) Microbial Degradation: Much microbial metabolism affecting herbicides in the

environment occurs through co-metabolism, i.e. metabolic reactions transform the herbicide

molecule incidentally, without the organism deriving energy or useful metabolites for cell

growth or division, or only using a portion of the molecule. Microbial activity may also lead

to polymerization involving pesticide or metabolite molecules, amide and ether hydrolysis

dealkylation, dehalogenation, hydroxylation of aromatic ring, oxidation and additions such as

acetylation or methylation, or conjugation with endogenous substrates such as glycosides or

amino acids. Changes to the original molecule through these processes may assist in

detoxification and elimination of the pesticide. Microbial Metabolism/cometabolism

(Aerobically or Anaerobically), takes place through enzymatically mediated oxidative or

reductive reactions or other degradative processes mediated by hydrolases, amidases etc.

Microorganisms such as bacteria, possess or use several enzymatic pathways including a

variety of xenobiotic metabolizing enzymes to protect themselves against the potentially toxic

effects of pesticides. The metabolic fate of xenobiotics (pesticides) involves two phase

metabolism including cytochrome P450 mediated- Phase I reactions (in some microorganism)

and the transferase-mediated conjugation reactions (Phase II) (Van Eerd et al,

2003).Metabolites formed by organisms initially taking up a pesticide may be amenable to

assimilation by other organisms, so enabling degradation to proceed (Holland and Sinclair,

2004). Microbial breakdown tends to increase when temperatures are warm, soil pH is

favourable, soil moisture and oxygen are adequate and soil fertility is good (Rao, 2000).

Butachlor is readily degraded by soil microbes. Under aerobic conditions the half-life of

butachlor ranges from 3-5 weeks under laboratory conditions. Under anaerobic conditions

degradation of butachlor in soil was accelerated (Roberts and Hutson, 1999). Studies have

shown that organic amendments hastened the degradation of butachlor due to the presence of

microbes (Prakash and Suseela, 2000).

(ii) Mineralization: This is the microbial conversion of an compound from an organic

form to an inorganic form as in pesticide degradation whereby it results to carbon dioxide,

ammonia or water as a terminal metabolite. Soil micro-organisms biotautilize the herbicide as

a source of carbon or other nutrients. Chemicals such as 2, 4-D are rapidly broken down in

the soil while others are less easily broken down e.g 2,4 5-T. Though, some others such as

23

atrazine are very persistent and are slowly broken down (Stephenson and Solomon, 1993).

Mineralization of pesticide molecules by microorganisms often occurs only slowly or to a

very limited extent, although the parent molecule may be significantly altered. Mineralization

may be indefinitely delayed by incorporation of residues into soil organic matter. Assimilation

of useful portions of the original molecule (e.g. as protein) may also delay release of carbon as

carbon dioxide(CO2), nitrogen as ammonia(NH3), etc., with those components again being

assimilated by higher organisms in the food chain and potentially being incorporated into

human foods without being completely mineralized. Residues of unchanged pesticide or

metabolites may persist and may accumulate with repeated use. The extent to which such

residues are bioavailable depends on their water solubility and the strength of adsorption or

binding to soil or sediment (Holland and Sinclair, 2004).

Figure 3: General Pathway for Abiotic and Biotic Transformation of Herbicides

24

1.10 Metabolism of Herbicides in Plants Non-target species may have one or a combination of responses to ultimately detoxify an

agrochemical. Development of a detoxification mechanism depends on three factors, concentration of

the herbicide present, environmental conditions and plant characteristics. Some non-target plants

growing on pesticide-polluted environments may experience local extinction due to non-tolerance

(Boutin et al, 2000). The qualitative and quantitative nature of residues in a biological system

following its exposure to a pesticide or its metabolites is a function of the following processes: • Absorption – movement across a biological cell wall or membrane

• Distribution – transport within the system

• Metabolism – biological or chemical modification of the pesticide

• Elimination – the pesticide or the products of metabolism are eliminated from active

cell processes.

(a) Absorption

Is the movement of xenobiotic across the membranes into the plant tissue. This includes

absorption from the site of exposure and subsequent absorption from the systemic circulation.

Xenobiotics can pass into and out of cells by passive diffusion or active transport mechanisms

(Sterling, 1994). It is concluded that weakly acidic herbicides can reach a higher concentration

in the cell than that on the outside due to ion trapping in the alkaline components of the cell.

The cytoplasm has a pH of approximately 7.5. Weakly basic herbicides are described as

accumulating in the more acidic cell compartments such as the vacuole, pH 5.5.

(b) Distribution The degree and manner in which a herbicide is taken up and distributed within the plant is

dependent on the physical and chemical properties of the herbicide. Plants take up pesticides

mainly through leaf surfaces, fruits and roots; once inside the plant, the pesticide can be

distributed within the plant either from cell to cell or via the vascular system. A pesticide

taken up by roots from the soil can take alternatively or simultaneously, two pathways to

reach the xylem vessels where it is moved to the top of the plant with the transpiration stream

in the xylem (1) the Apoplastic pathway (2) the Symplastic route.(Rao, 2000)

25

1. The Apoplastic System includes all the non-living portions of the plant cell walls and

xylem elements that form a water permeable continuum through which both short and long-

distance solute transport occurs and this is by mass flow and diffusion (passive transport).

The main function of the xylem is to transport water and dissolved solutes from the roots to

the foliage part of the plant. Some herbicides such as atrazine and diuron move mainly on the

apoplastic system. These herbicides are taken up by plant roots and move upwards in the

transpiration stream, leading to the accumulation of these herbicides in the leaf margins, and

as a result yellowing of these leaves. Herbicides that move mainly in the apoplast do not

accumulate in the growing points of plants or tissues of high metabolic activity (metabolic

sink) but may be adsorbed on the cellulose tissues of the cell wall (Rao, 2000).

2. The Symplastic System: This is the living plant tissue bounded by the plasmalemma and

connected via plasmodesmata. It is the continuum of interconnected protoplasm of living cells

of plant. It is a reactive environment that places chemicals in proximity to enzymes and other

reactants. Movement within the conductive portion of the symplast (Phloem) occurs by mass

flow and diffusion (active transport). Some herbicides appears to be restricted to either the

apoplastic (xylem) or symplastic (phloem) pathways while others termed ambimobile, move

in both domains. Non polar or less lipophilic herbicides take the apoplastic pathway and polar

or more lipophilic herbicides such as 2,4-D, glyphosate and paraquat tend to take the

symplastic pathway (Sterling, 1994). Herbicides that move in the symplastic are

characterized by a tendency to accumulate in the sinks of treated plants (i.e. growing points of

plants or tissues). They are generally inhibitors of metabolic activities directly associated

with growth (Rao, 2002)

(c) Metabolism In general plants have mechanisms for the degradation or sequestration of most pesticides.

These metabolic transformations, which include degradation and detoxification, occur in both

tolerant and susceptible plant species, but in the tolerant species they take place at a rate much

faster than herbicide accumulation and before the chemical can disrupt the metabolic

processes. In susceptible plants species, the herbicide undergo transformations in small

amounts and more slowly. Some herbicides undergo metabolic transformations that may

result in increased phytotoxicity (Rao, 2000). Most often, these biotransformation

mechanisms are independent of the mode of action and physiological lesions involved in the

26

pesticidal activity. However they relate to the functional or reactive groups or linkages in the

compound which are susceptible to enzymatic or chemical breakdown (Rao, 2000).

There is growing concern from ecological standpoint about the accumulation of herbicide

residue in plant either in the form of the parent compounds or their metabolites. The pathways

of metabolism depend on the balance of enzymes of various capabilities, present in different

plant species, and the chemical reactions that are possible. The rate of metabolic attack on a

pesticide by plants varies with the species type, the time of residence in or on the plants and

the degree of entry into the plants. With some major exceptions, microorganisms, insects,

plants and mammals metabolize foreign organic compounds by the same major pathways

(Hatzois, 1991). The processes in plants are in most cases slower than in animals however

most animals have better degrading, circulating and excreting systems than plants. Plants tend

to store pesticides and their metabolic products for longer periods and pesticide metabolism

generally results in detoxification but at times, the transformation products have equal if not

greater toxicity than the respective parent compound (van Eerd et al., 2003)

Plant metabolism can be divided into three phases; Transformation (Phase I), Conjugation

(Phase II), and Storage (Phase III) processes. The initial metabolic reactions (Phase I

reactions) are primarily catalyzed by cytochrome P450 enzymes by the generation of functional

groups (hydroxyl, carboxylic acid and amine groups) in the pesticide structure using different

transformational mechanism such as oxidation, reduction or hydrolysis to produce a more

water soluble and usually less toxic product than the parent (van Eerd et al., 2003).

The second phase involves the conjugation of a pesticide or pesticide metabolite from phase I,

to a sugar, amino acid, or glutathione which are soluble conjugates and increases the water

solubility thus reduces toxicity compared with the parent pesticide. The major plant products

involved in conjugation are glucose, malonic acid, amino acids and glutathione and the

conjugated products can be esters, amides, ethers, thioethers or glycosides. Glutathione

conjugation is an important phase II transformation in plants (Hatzios, 1991). In the presence

of the enzyme glutathione S-transferase, glutathione reacts within a range of substrates

including epoxides, aryl and alkyl halides, and other electrophilic compounds. Glutathione S-

27

transferases are homo or heterodimer, multifunctional enzymes located in the cytosol, which

catalyze the nucleophillic attack of the sulphur atom of GSH by the electrophilic centre of the

substrate (Armstrong, 1994). Glutathione S-transferases in plant were first studied because of

their ability to detoxify herbicides (Marrs, 1996) and GST based metabolism imparts

herbicide selectivity in several plant species The enzymatic conjugation of xenobiotics with

glutathione (GSH) via glutathione-S-transferase (GST) is more common than non-enzymatic,

however, the non-enzymatic conjugation has been shown to occur in metabolism of several

herbicides including triazines, acetamides and sulphonylureas in species where the GST

activity in plant was low (Tal et al., 1995). Phase II metabolites have little or no phytotoxicity

and may be stored in the vacuoles (Sanderman, 1992; Korte et al., 2000).

The third phase involves the conversion of phase II metabolites into secondary metabolites

which may also be non-toxic (Hatzios, 1991). It involves reactions such as hydroxylation,

alkylation, polymerization etc. Reactions of this third phase results in the formation of non-

extractable or bound residue. As in co-polymerisation of pesticides with lignin to form

insoluble structures (Skidmore et al., 1998). Three major pathways have been detected for

phase III reactions in plants; export into cell vacuoles, export into the intracellular space, and

deposition into lignin or other cell components (Roberts, 2000). The Phase III reaction is a

natural regulatory mechanism by which the plant decreases water solubility of their

pesticide/residue thereby reducing their reactivity and toxicity. It also reduces mobility of

pesticides in the plant symplast and allows their removal to vacuole apoplast or plant matrix.

Several enzymes have been detected in plants that were active against pesticides. Butachlor is

metabolized rapidly, primarily to polar water soluble metabolites. Its detoxification may

involve GSH or hGSH conjugation (Abass, 2010).

(d) Elimination Although, plants do not have a classical excretory system, they do effectively eliminate

xenobiotic compounds by removing them from active cell processes by storage in the cell

vacuole, which is a large fluid filled cavity within the cell bounded by a membrane called the

tonoplast, with the fluid containing sugars, salts, pigments and waste products dissolved in

water (Cole, 1994), or by reaction with the structural compartments of the plant, e.g. lignin

28

and cellulose, or by exudation from the roots into the soil (Walker et al., 1994), or through

volatilization. Pesticide residues eliminated from cell processes by reaction with lignin and

cellulose represent bound residues and require specific assessment of their relevance during

risk assessment.

1.11 Metabolism of Herbicide in Animals Animals that feed on plants may ingest one or more herbicide/residue produced in or on the

plant and this is subject to metabolism either by bacteria in the intestine or it is absorbed

alongside with that via the skin and respiratory tract and then transported to the liver; the liver

being the primary site of pesticide transformation for the purpose of facilitating clearance to

water–soluble products via detoxification. Some exogenous chemicals may be excreted

largely unchanged (original form), but most persistent environmental contaminants are highly

lipophilic and require metabolic conversion before elimination from the organism (Ahokas et

al., 1994). Xenobiotic biotransformation is the process by which lipophilic compounds (e.g

pesticides) are metabolised through enzymatic catalysis to hydrophilic metabolites that are

eliminated directly or after conjugation with endogenous cofactors via renal or biliay

excretions. (Oesh et al., 2000)

Without biotransformation, lipophilic xenobiotics would be excreted from the body so slowly

that they would eventually overwhelm and kill the organism (Parkinson, 2001). Nonetheless,

this change in chemical properties may also result in changes in their biological activity; in

some cases, biotransformation not only leads to inactivation of toxic compounds, but can also

result in more toxic carcinogenic products (Stegeman and Lech, 1991). Xenobiotics

metabolism is divided mainly into two phases: Phase I and II.

29

Figure 4: General pathway for xenobiotic metabolism

Source: (Ahokas and Pelkonen, 2007; Liska et al., 2006)

1.11.1 Phase I Phase I reactions generally involve oxidation, reduction, and hydrolytic reactions as well as

some other miscellenous-reactions. These reactions are mediated primarily by the cytochrome

P450 (CYP) enzyme system and other enzymes (e.g. flavin monoxygenases, peroxidases,

amine oxidases, dehydrogenases, xanthine oxidases) also catalyse the oxidation of certain

functional groups (Hodgson and Goldstein, 2001; Parkinson, 2001). The cytochrome P450

(CYP) comprises a large multi-gene family of hemoproteins involved in the metabolism of

xenobiotics (endogenous or exogenous) in living organisms. They have an approximate

molecular weight of 50,000 dalton and more than 500 different cytochromes P450 have been

cloned and sequenced (Nelson et al, 1993). CYP- xenobiotic interactions involve either

induction or inhibition of metabolising enzymes. Inhibition can take place in several ways

including the destruction of pre-existing enzymes, inhibition of enzyme synthesis or by

30

complexing and thus inactivating the metabolising enzyme. They have been classified into

families and subfamilies on the basis of the sequence homology of the corresponding genes.

The enzymes are thus identified by a number denoting the family, a letter denoting the sub-

family and a number identifying the specific member of the sub-family and iso-enzyme (CYP

1A). Cytrochromes P450enzymes were discovered around 1960 and until recently, the catalytic

functions of these hemoproteins appear to be the transfer of one atom from O2 into various

substrates. CYP oxidation reactions involve a complex series of steps; the initial step involves

the binding of a substrate to oxidized CYP, followed by a one-electron reduction catalyzed by

NADPH cytochrome P450 reductase to form a reduced cytochrome-substrate complex.

RH + O2 + 2e’ + 2H -(NADPH or NADH)→ ROH + H20+NADP+ or NAD+

Oxidation Reaction Path catalyzed by Cytochrome P450

RH=Xenobiotic

The next several steps involve interaction with molecular oxygen O2, the acceptance of a

second electron from NADPH.Cyt.B5 reductase and then the subsequent release of H2O and

the hydroxylated product (Rose and Hodgson, 2004).

Cytochrome P450 dependent monoxygenases play two main roles in living organisms; some

catalyse oxidation steps involved in the biosynthesis or biodegradation of endogenous

compounds like steroids or fatty acids or prostagladins. Another class, plays a key role in the

oxidative biotransformation of exogenous molecule from the environment, facilitating their

elimination from living organisms (Bogaards et al., 1995). The initial reaction of metabolism

(oxidation and reduction) usually involves a microsomal phase I enzyme which include many

of the iso forms of CYP active in the CYP-dependent monoxygenase system as well as flavin

monoxoygenase. In addition to hydroxylation, these enzymes catalyze a wide range of

reactions, including those involving deamination, dehalogenation, desulfuration, epoxidation,

peroxygenation, and reduction. Many different pesticide monoxygenation reactions are

attributed to CYPs, including epoxidation (e.g. dieldrin) N-alkylation (e.g. alachlor, atrazine),

on dealkylation (e.g. chlorfenrinphos), S-oxidation e.g. (phorate) and oxidative desulfuration

(e.g. parathion) (Hodgson and Levi, 1997), Hydroxylations (e.g. sulponylurea, butachlor).

31

CYPs are found in high concentrations in the liver, accounting for 1 to 2% mass of

hepatocytes (Lester et al., 1993) but are also present in a variety of other tissues including the

lung, kidney, the gastrointestinal tract, skin and brain (Husøy et al., 1994; Stegeman and

Hahn, 1994; Ortiz-Delgado et al., 2002).

1.11.2 Phase II

In phase II, the phase I products are not usually eliminated rapidly but undergo a subsequent

reaction in which endogenous substrates such as glucuronic acid, sulphuric acid, acetic acid or

amino acid combines with the new functional groups to form a highly polar conjugate to make

them more easily excreted. Some of the most prevalent reactions involved in phase II

reactions are sulfation, glucuronidation and glutathione conjugation (Rose and Hodgson,

2004). Glutathione S-transferase is important in the metabolism of organophosphorus

pesticides, halogenated herbicides such as the chloroacetanilides and chloro-S-triazines (Abel

et al., 2004b; Cho and Kong, 2007). The conjugation products are typically further

metabolized and in humans, excreted as urinary mercapturic acids. Interestingly, the addition

of GSH molecular weight of 307 to these 200- 300 molecular-weight xenobiotics creates a

product that exhibits a species-dependent disposition due to differences in size thresholds for

biliary transport in this range. In general these enzymatic reactions are beneficial in that they

help eliminate foreign compounds; however sometimes these enzymes transform an otherwise

harmless substance into a reactive form; a phenomenon known as metabolic activation.

Glutathione S-transferase, GST (E.C2.5.1.18) is a family of multi-functional proteins found at

relatively high concentrations in the mammalian liver as well as a wide variety of extra

hepatic tissues catalyzing the formation of conjugates between reduced glutathione (GSH) and

a wide variety of compounds including toxins, pesticides, and PAHs, etc (Eaton and Bammler,

1999; Halliwell and Gutteridge, 2007). The reaction between tripeptide glutathione and the

electrophilic centre of pollutants (xenobiotics) represent the main reaction of phase ΙΙ

detoxification. GSTs can catalyse neuclophilic aromatic substitutions, michael additions to

,β–unsaturated ketones and epoxide ring openings all of which result in the formation of

GSH conjugates and the reduction of hydroproxides, resulting in the formation of oxidized

glutathione (GSSG). GSH-conjugates are rarely excreted in the urine due to their high

molecular weight but could be eliminated in the bile. These conjugates could also be

32

metabolized further and excreted ultimately as mercapturic conjugates (Salinas and Wong,

1999; Sheehan et al., 2001)

R—X + Gluthathione Glutathione S-tranferase G—S—R + X---H

G—S—R + Acceptor γ glutamyl transferase Cysteinyl glycine—R + γGlutamyl acceptor

Cysteinyl glycine—R γ-glutamyl transpeptidase R—Cysteine + Glycine

R—Cysteine + Acetyl CoA N-acetyltransferase Mercapturic acid + Coenzyme A

Glutathione Conjugation of Xenobiotics and Mercapturic Acid Biosynthesis. R-X Substrate, G-S-R Glutathione Conjugate Source: Parkinson and Ogilvie (2009). In: Casarett & Doull’s Toxicology.

1.12 Metabolism of Butachlor in Animals

Metabolism of Butachlor in animals (rats) follow three major pathways

1) Cytochrome P450 mediated hydroxylation of the aromatic ring, its ethyl groups and the N-

buthoxymethylene group,oxidative removal and replacement of chlorine atom,N-dealkylation.

2) Cleavage of the amide bonds via aryl amidase to form 2, 6-diethylaniline which could be

further oxidized to 4-amino-3,5, diethyl phenol(liver)

3) Conjugation with glutathione followed by mercapturic metabolic pathway in the liver

(Singh et al., 1982; Ou and Lin, 1992).

Coleman et al. (2000) have also determined the metabolism of butachlor to 2 chloro N- 2,6-

diethylphenyl acetanilide (CDEPA) and 2,6-diethylaniline (DEA) both in rat and human liver.

Although the exact mechanism of carcinogenicity of butachlor is not known but the possible

mechanism involves the formation of a DNA-reactive metabolite, 2,6-diethybenzoquinone

imine (Ou et al., 2000). Prolonged exposure to butachlor has been found to be toxic to spotted

snakehead fish (Channa punctate), and accumulates through food chain (Tilak et al., 2007). It

has been reported to be neurotoxic to land snails,genotoxic to toads and frog tadpoles,

33

flounder and catfish (Ateeq et al., 2005; Geng et al., 2005a; Yin et al., 2007, 2008) and

causes DNA strand breaks and chromosomal abberrations in cultured mammamallian cells

(Sinha et al., 1995; Paneerselvam et al., 1999).

Figure 5: Metabolism of Butachlor in animals/plants (Singh et al., 1982)

2-----alcohol from oxidative dechlorination 13, 21---------methyl sulfones 3------Hydrolytic product of dealkylation and oxidation 11,19, 20- -----glucuronide sulfate conjugate 4------Oxanilic acid 18---------methyl sulfide 5 and 6-oxidation of butoxy moiety 14,15,16 and 17----mercapturic acids 7--------dechlorinated product 22 and 23-----sulfates from hydroxylation 9--------glutathione conjugate

34

1.13 Toxicity of Metabolites

In general, metabolites are less toxic than their parent compounds, because they are usually

more water-soluble and therefore, more rapidly excreted. There are notable exceptions for

which biotransformation results in an inherently more toxic product. Such reactions are

generally referred to as activation reactions. These reactive metabolites may combine

covalently with cellular constituents such as DNA, RNA, or protein; and carcinogenesis,

mutagenesis, and cellular necrosis are often attributable to such reactive metabolites

(Guengerich, 1992, 1993; Anders et al., 1992; Levi and Hodgson, 2001). Hollingworth et al.

(1995) reviewed reactive metabolites with particular reference to agrochemicals. The

metabolic production of a more toxic compound is sometimes called lethal synthesis to

emphasize that biotransformation in this instance is the source of danger. Of particular

concern has been the role of metabolic activation in the carcinogenic process, particularly in

the formation of DNA adducts by reactive metabolites. For example, monooxygenase

enzymes have been postulated to play a role in the metabolic activation of alachlor and

metolachlor (Feng et al., 1990; Jacobsen et al., 1991; Li et al., 1992).

1.14 Biomarkers of Pesticides in Animals/Plants/Soil. The need for early detection and assessment of the impacts of contamination in the aquatic

environment has led to the development of biomarkers (biological indicators) (Peakall, 1994).

A biomarker is generally used in a broad sense to include almost any measurement reflecting

an interaction between a biological system and a potential hazard, which may be chemical,

physical or biological (WHO, 1993). Biomarker can also be defined as a “change in a

biological response, ranging from molecular through cellular and physiological responses to

behavioural changes, which can be related to exposure to or toxic effects of environmental

chemicals (Peakall, 1994). Pesticide exposure in human can be measured in two ways, either

through direct monitoring by measuring biomarkers from individuals or by developing models

(plants, animals or micro-organisms) to assess exposure (Otitoju and Onwurah, 2007).

35

Biomarkers can be broadly divided into three main categories: exposure, effects, or

susceptibility. Selected biomarkers should indicate that the organism has been exposed to

pollutants (exposure biomarkers) and/or the magnitude of the organism’s response to the

pollutant (effect biomarkers or biomarkers of stress) (Cajaraville et al., 2000). A biomarker of

exposure consists of the measurement of a xenobiotic substance, a metabolite of a xenobiotic

substance, or an effect directly attributable to such a substance in an organism Biomarkers of

effect are alterations of physiology, biochemistry or behavior directly attributable to exposure

to a xenobiotic substance. Closely related to biomarkers of effect are biomarkers of

susceptibility, which indicate increased vulnerability of organisms to disease, physical attack

(such as low temperatures), or chemical attack from other toxicants. They serve as indicators

of a particular sensitivity of individuals to the effect of a xenobiotic or to the effects of a

group of such compounds. This can be genetic markers that include alterations in

chromosomal structure such as restriction fragment length polymorphism’s (RFLPs),

polymorphism of enzyme activities Furthermore, the criteria for any biomarkers, are that they

should be sensitive, reliable and easy to measure and that they should be related with the

“health” and “fitness” of the organisms (Stegeman et al., 1992). Pesticides have been shown

to be inducers or inhibitors of Cytochrome P450 and the mechanism of induction of CYP have

been demonstrated to be at either at the transcriptional or post transcriptional level (Bucheli

and Fent, 1995).

1.15 The Liver and Marker Enzymes The liver is the major organ involved in the biotransformation of xenobiotics which include

pesticides and as such it is rich in xenobiotic metabolizing enzymes which include

cytochrome P450 and glutathione S-transferase. The high level of oxidative metabolism in the

liver makes this organ a possible target for more toxic metabolic products activation when

detoxifying and protective mechanisms are overwhelmed (Murray et al., 1996). The liver is

also rich in aminotransaminases intracellularly since they are involved in the transfer of amino

groups between compounds (transamination reactions ). Changes in their activities reflect

changes in specific organ/tissue such as the liver (Marie, 1994). The liver enzymes AST and

ALT are usually low in the blood, so in most cases if liver cells are damaged, they may leak

36

into the plasma resulting to an increase in activity. Hence they are used as biomarkers of

injured hepatocytes, while alkaline phosphatase in some cases indicates bile duct epithelial

damage. These enzymes are commonly monitored clinically and in animal studies to detect

hepatotoxicity (Nelson and Cox, 2000).

1.15.1 Alanine amino transaminase (ALT) ALT is a cytosolic enzyme found predominantly in the liver but also smaller amounts in the

kidneys, heart, muscles, and pancreas. ALT catalyzes the reversible transamination of

oxaloacetate and L-alanine to L-glutamate and pyruvate. It is a more specific indicator of liver

damage than AST (Michel, 1998).

1.15.2 Aspartate amino transaminase (AST) AST is a cytosolic and mitochondrial enzyme found in the liver, heart, skeletal muscle,

kidneys, brain, and red blood cells. It catalyzes the reversible transamination of L-aspartate

and α-ketoglutarate to oxaloacetate and L-glutamate. Increase in AST however is not specific

for Liver damage since it is also found in other organs and tissues in high concentrations

(Murray et al., 1996)

1.15.3 Alkaline phosphatase (ALP) In Animals, alkaline phosphatase is present in all tissues throughout the entire body, but is

particularly concentrated in liver, bile duct, kidney, bone and the placenta. It catalyzes the

splitting of phosphoric acid from phosphoric esters. ALP is involved in the transport of

metabolites across cell membranes.It plays the role of phosphate metabolism and prevents the

external membrane from being damaged. ALP and ALT are used as markers for cell

membrane integrity (Murray et al., 1996)

1.16 Hepatotoxicity Chemically induced cell injury can be thought of as involving a series of events occurring in

the affected animal and often in the target organ itself. The events are as follows; (1)The

chemical agent is activated to form the initiating toxic agent, (2) the initiating toxic agent is

either detoxified or causes molecular changes in the cell,(3) the cell recovers or there are

irreversible changes,(3) irreversible changes may culminate in cell death.

37

When the concentration of the reactive metabolites exceeds the capacity of detoxification

systems, acute (necrosis) or chronic (mutagenesis, carcinogenesis and teratogenesis) toxicity

can occur. Thus anything that results in reduced biotransformation of a toxic metabolite to an

inactive metabolite or that increases the conversion of harmless xenobiotic to reactive

metabolite, increases the probability that a toxic response will occur (Hodgson and Levi,

1997).

1.17 Lipid Peroxidation

Lipid peroxidation is the metabolic process in which reactive oxygen specie (ROS) result in

the oxidative deterioration of lipids. Lipid peroxidation is a well-established mechanism of

cellular injury in both plants and animals, and is used as an indicator of oxidative stress in

cells and tissues (Gutteridge, 1995). Increased ROS production occurs in inflammation,

during radiation, or during metabolism of hormones, drugs and environmental toxins. This can

overwhelm endogenous protective antioxidant mechanisms and increase ROS-mediated

damage to membrane structure and function. Such ROS reactions can also lead to protein

damage, including DNA repair enzymes and polymerases, impairment, and production of

aldehyde by-products such as malondialdehyde (MDA) and 4-hydroxy-2-nonenal (HNE).

Lipid Peroxidation (MDA) and Antioxidants can be employed as biomarkers of tissue damage

(Gutteridge, 1995).

In Nigeria, studies have centered mainly on crude oil and petroleum products toxicity on

plants, aquatic organisms and animals (Omoregie et al., 1990; Chindah et al., 2001; Ubani et

al., 2012). Also studies on pesticide(herbicide) toxicity on aquatic animals (Chindah et al.,

2004; Nwani et al., 2013); however studies on the effects of pesticide(herbicide) exposure via

the food chain are scanty despite several decades of its introduction, the wide use and

magnitude. This research could give information on; (1) The possible bioaccumulation of this

herbicide in cultivated plants, (2) Whether the recommended/standard application rate as

stated by herbicide manufacturers, is safe and also (3) the effect of improper or excessive use

of this herbicide when applied.

38

1.18 Aim and Objectives of the Study

1.18.1 Aim of the Study The research work was aimed at assessing the possible bioaccumulation of butachlor/residues

in the leaves of an edible plant, (Phaseolus vulgaris) and assessment of it’s possible toxicity

in animal (rabbit) as indicative of its possible effect in man.

1.18.2 Specific Objectives of the study The study was carried out, following these specific objectives:

1) To cultivate the plant with the application of different concentrations of butachlor herbicide.

2) To assay for butachlor/residues and determine the bioaccumulation in the bean plant leaves.

3) To estimate the health risk index upon consumption of the butachlor herbicide//residue from

plant.

4) To assay the liver enzyme, total Cytochrome P450 as biomarker of exposure to pesticides

5) To assay the activity of the liver enzyme, Glutathione S-transferase as biomarker of exposure

to pesticides

6) To assay the activities of some liver marker enzymes (AST, ALP, ALT) in the rabbits.

7) To determine the histological evaluation of the liver tissues of the rabbit.

39

CHAPTER TWO MATERIALS AND METHODS

2.1 Materials

2.1.1 Chemicals

Acetone, n-hexane, anhydrous sodium sulphate, bovine serum albumin standard(BSA),

ethanol, potassium hydroxide, sucrose, hydrochloric acid, potassium chloride, copper sulphate

Folin ciocalteau, sodium hydrogen diphosphate, sodium phosphate, ethylenediamine tetracetic

acid, sodium chloride, formalin, haematoxylin and eosin stain, aspartate aminotransferase

(AST) randox kit, alanine aminotransferase (ALT) randox kit and alkaline phosphatase (ALP)

Quimca test kit, Butastar EC commercial formulation (50%w/v a.i.butachlor) manufactured

by Naintong Jiangchan Agrochemicals, China. Butachlor analytical standard 98.3% purity,

Reduced Glutathione and 1 chloro-2,4-dinitrobenzene solution (CDNB) were purchased from

Zayo-Sigma Aldrich, Total Cytochrome P450 Elisa kit by Antibodies Online, Germany. chromogenic substrate (phenolphthalein monophosphate) Colour Developer,Standard (30

U/L). Solution R1( Phosphate buffer,L-alanine and - oxoglutarate) Solution R2:2,4-

dinitrophenylhydrazine. Reagent1( Phosphate buffer,L-aspartate and oxoglutarate)Reagent 2(

2,4-dinitrophenylhydrazine). The Solutions for Protein Analysis include the following;

Solution 1:2% of Sodium carbonate (Na2CO3) in 1M Sodium hydroxide NaOH.2g Na2CO3 in

100ml 1M NaOH. Solution 2:0.5g CuSO4 in 1% of Na-K Tartrate Solution 3: 1ml of Sol.2 in

50ml Sol.1 Solution 4:1N Folin Ciocalteau (1:1dilution)

2.1.2 Equipment

Thermo Scientific Trace GC-MS Ultra, Cecil CE 7500-7000 series Aquarius UV-Vis

spectrophotometer, Centrifuge, pH meter, electrical weighing balance, mechanical scale,

rotary evaporator, microplate reader(450nm), refrigerator, freezer and incubator

2.1.3 Plant Material

The black bean (Phaseolus vulgaris) seeds popularly known as Akidi in Eastern Nigeria, were

obtained from the local market in Nsukka, cleaned, sundried and used throughout the study.

The picture of the seed is shown on page 40.

40

Figure 6: Black beans seeds (Phaseolus vulgaris): Akidi

Figure 7: Butastar commercial formulation of butachlor

41

2.1.4 Experimental Animals

Male rabbits (n=48) with average weight of 1.2kg- (Lop breed)were obtained from the Animal

House of the Department of Pharmacology, University of Nigeria, Nsukka. Growers marsh rabbit

feeds purchased from the local market in Nsukka.

2.1.5 Area of Study

The Field experiment was conducted at the Research Farm of the Department of Crop Science,

University of Nigeria, Nsukka for a period of 2months (May-July 2012). The Research farm is

located within the Nsukka Campus of the University and this lies within longitude 07o 29N

latitude 06 51E and 400miles above sea level (m.a.s.l). It is characterized by two peak rainfall

seasons.

2.2 Methods

2.2.1 Experimental Design

The study area had a 240m2 dimension and beds were constructed, each with a 10m2 dimensions

and a 0.5m distance maintained between the beds with a 1m furrow spacing. A plant spacing of

75cm between rows with a 50cm within rows was adopted for the bean plant (Dugjie et al., 2008).

Recommended application rate/dosage of herbicide at pre-emergence for bean is (4.0l/ha).

Butachlor at three different concentrations were applied to the plots at the pre-emergence stage;

T1-4.0 l/ha (2.6 kg a.i/ha), T2-4.4 l/ha (2.9 kg a.i/ha),T3-5.0 l/ha (3.2 kg a.i/ha). These

concentrations were adopted based on the pilot study that showed that the herbicide was

phytotoxic to the bean plant at certain concentrations.The bean seeds were planted and the

butachlor herbicide of different concentrations, applied at pre-emergence stage to crops and left to

grow for 5weeks. Concentrations of the standard application rate (T1-4.0l/ha) and different

application rates of herbicide (T2-4.4l/ha, T3- 5.0l/ha) were used on the crop separately. (The control

plot C did not receive herbicide application).

42

Figure 8a: Bean plant at two weeks after planting. C-Control plot,T1-Test plot(4.0 l/ha-2.6 kg a.i/ha

butachlor)

Figure 8b: Bean plant at two weeks after planting.T3-Test plot (5.0 l/ha-3.2 kg a.i/ha butachlor)

43

Figure 8c: Bean plant at four weeks after planting. T1-Test plot (4.0 l/ha-2.6 kg a.i/ha,T2-4.4 l/ha(2.9

kg a.i/ha), T3-Test plot(5.0 l/ha-3.2 kg a.i/ha butachlor

Figure 8d: Bean plant at six weeks after planting. T1-Test plot (4.0 l/ha-2.6 kg a.i/ha,T2-4.4 l/ha(2.9

kg a.i/ha)

44

2.2.2 Animal Protocol

The rabbits were kept in metabolic cages at the Animal House of the Department of Home

science and Dietetics UNN, to acclimatize for 7days prior to the commencement of the

experiment. They were maintained on a regular feed of grower’s marsh and water ad libitum.

The rabbits were divided into four (4) groups with three (3) subgroups each consisting of four

(4) rabbits. Group 1 served as the control group (with subgroups Days 1, 14, 28) all fed with

the plant cultivated without the application of butastar. Group 2 were animals fed with the

bean plant (leaves) cultivated with the application of 4.0 l/ha of the herbicide. Group 3 were

animals fed with the bean plant cultivated with the application of 4.4 l/ha of the herbicide,

while Group 4 were animals fed with the bean plants cultivated with the application of 5.0l/ha

of the herbicide. They were all fed with an average weight of 100g of the leaves per rabbit

twice daily (Iyeghe-Erakpotobor and Muhammad, 2008) and water ad libitum. Five milliliters

(5mls) of blood was collected from each animal via the jugular vein, on Days 1, 14 and 28 of

the experiment, into plain bottles for the enzyme assays. After days 1,14 and 28, the rabbits

were sacrificed by severing the jugular vein after light ether anaesthesia. Liver samples were

excised, washed and stored in 10% formal saline for histological examinations. Handling,

management and use of animals for experimentation were in conformity with laboratory

Animal Rights Regulation of the University of Nigeria, Nsukka.

2.2.3 Soil Analysis

Soil characterization was carried out in the Department of Soil Science UNN; by Bouyoucous

Hydrometer method (Bouyoucous, 1951). A known quantity of soil(100g) was collected from

a depth of 0-15cm.The physicochemical properties were analysed.

2.2.4 Plant Extraction of Butachlor Extraction of the herbicide from the bean plant leaves was carried out by solvent extraction

method using acetone/n-hexane. (1:1vol). Twenty grams(20g) of the bean plant leaves was

washed with deionized water, chopped and blended with 10ml deionized water, using a

national blender for 1min (4-5 cycles). A known quantity (100ml) of acetone and hexane was

added, shaken for 3mins and then filtered through a 10g anhydrous sodium sulphate in a

funnel. An additional 1:1vol of acetone and hexane were added to the residue, mixed

45

thoroughly and filtered again. Both filterates were mixed, centrifuged and the supernatant

removed and concentrated to 2ml using a rotary evaporator (Chang et al., 2005)

2.2.5 Identification and Quantification of Butachlor A stock solution (100 mg/l) was prepared with n-hexane, and working standard solutions with

concentration ranges of 0-2 mg/l (ppm) were prepared by dissolving in appropriate volume of

hexane. The herbicide/residue was determined using gas chromatography-mass spectrometry

(GC-MS).

A known volume of 1µl each of the six different concentrations of the standards and sample

were injected into the Thermo-Scientific Trace GC coupled to DSQ 11 mass spectrometer and

equipped with an AS 3000 auto sampler and a split/split–less injector. The column used was a

TR-5MS (30×0.25 mm i.d), 0.25m d.f coated with 5% diphenyl -95% polydimethyl siloxane

operated with the following oven temperature programme. Initial temp.:140oC, initial time:

1min, Increasing temp.: 8oC/min, Final temp, : 300oC held for 5mins, Injection temperature

and volume was 250oC and 1µl respectively, injection mode, mode, split/split 15:1 carrier gas:

Helium at 30cm/s linear velocity and inlet pressure 99.8KPa, detector temperature 280oC. The

components of the standard and sample were identified based on the basis of their retention

indices. Identification and confirmation was further done by comparison of their mass spectra

with published spectra (Adams, 1989) and those of reference compounds from library of

National Institute of Standard and Technology (NIST) database. Quantification of the sample

was done by comparison of the peak area and concentration to that of the analytical standards.

A plot of the peak areas versus concentration of the standards was made and from the linear

equations the unknown sample concentrations were then calculated (Chang et al., 2005).

2.2.6 Determination of Bioaccumulation Factor (BAF) The Bioaccumulation factor was calculated using the method of Connell (1990),as shown

below

BAF = gsurroundin in the mical)(Conc..cheAmount

system biologicalin mical)(Conc..cheAmount

46

BAF =soil toexposedButachlor ofAmount

plantin Butachlor ofAmount

2.2.7 Determination of Hazard Quotient (HQ) and Health Risk Index (HRI)

The risk of intake of contaminated vegetables on human health was characterized by Hazard

quotient (HQ) and Health risk index and these were determined using the method as adopted

by WHO (1997), Chary et al. (2008); Gerba (2010); Gupta et al. (2013).

The following equation was adopted:

HQ = (W plant)× (Mplant) /RfD(ADI) × Baverage weight

Where

W : is the weight of contaminated plant material consumed (kgd-1)

M : is the concentration of contaminant in vegetables (mg/kg(ppm )

` RfD : -Is the food reference dose for the contaminant (mg/kg bw/d )(ADI)

B : is the average adult body weight(kg).(70kg)

Daily Intake of Contaminant: This was determined by the following equation.

DIC = Ccontaminant × Dfood intake/ B average weight

Where:

Ccontaminat. = concentration of contaminant in plants (mg/kg) (ppm)

D = Average daily intake of vegetables (0.345kg/person/day)(WHO,1997)

Health Risk Index (HRI): The health risk index was calculated using the following formula:

HRI =DIC/ RfD(ADI)

2.2.8 Preparation of Post Mitochondrial Supernatant (S9 Fraction) This was carried out as described by Nilsen et al. (1998). Five grams (5g) of liver tissue was

homogenized with 50ml of cold Phosphate Buffered Saline (PBS) (pH 7.2), 5times. The

homogenate was then centrifuged for 20mins at 10,000g. The Supernatant containing the

microsomes and enzymes was carefully harvested with a pipette and stored (-20oC) in tubes

for total protein and enzyme assays.

47

2.2.9 Determination of Liver Total Cytochrome P450 The liver enzyme cytochrome P450 (CYP) was assayed using a total cytochrome P450 ELISA

kit as described by Nilsen et al. (1998).

Principle of Assay It is a quantitative assay that employs the competitive enzyme immunoassay technique. The

microtiter plate in the kit has been pre-coated with an antibody specific for CYP. Standards

and samples are then added to the micro titer plate wells and CYP if present, will bind to the

antibody pre-coated wells. The horse radish peroxidase-conjugated to CYP is added to the

wells and further on the A and B substrate for the HRP added. The enzyme, HRP and

substrate were allowed to react over a short period of incubation, only those wells that contain

CYP and enzyme-conjugated will exhibit a change in colour to blue. The enzyme-substrate

reaction is terminated by the addition of a sulphuric acid solution and the colour changes from

blue to yellow, which is then measured spectrophotometrically at a wave length of 450nm

using a microplate reader. The intensity of the colour is inversely proportional to the

Cytochrome P450 concentration, since CYP from samples and CYP-HRP conjugate compete

for the anti-CYP antibody binding site, and since the number of site is limited, as more sites

are occupied by CYP from the sample, fewer sites are left to bind CYP-HRP conjugate.A

standard curve was plotted relating the intensity of the color (O.D) to the concentration of the

standards.

The post mitochondria supernatant (PMS) was used as the sample. Physiological saline was

used as dilution buffer (×10).The assay procedure was followed as stated by the manual in the

Kit

Reagent Preparation: All the kit components were brought to room temperature.

Procedure: The desired number of coated wells (48) was secured and100µl each of the six

standards and the diluted samples were added to the appropriate well in the antibody pre-

coated microtiter plate. A known quantity (100µl) of PBS (pH 7.2) was added in the blank

control well. Ten microliter (10 µl) of the balance solution was dispensed into the 100µl

specimens and mixed very well. Fifty microliter (50 µl) was then added to each well with the

exception of the blank and mixed very well. The Plate was covered and incubated for 1 hour

48

at 37oC. After the incubation, the microtiter plate was washed manually by aspirating the

contents of the plate into a sink, and washing with the wash solution. The wash solution was

prepared by diluting 10ml with 990 ml of distilled water. This was repeated four times (i.e. a

total of five washes). After washing, the plate was inverted and blot dried by hitting unto an

absorbent paper until no moisture appears. Fifty microliter (50 µl) of substrate A and 50 µl of

substrate B were added to each well including the blank control well, subsequently, the plate

was covered and incubated for 15mins at 37oC. Fifty microliter (50 µl) of the stop solution

was then added to each well and mixed very well. The optical density (O.D) was determined

immediately at 450 nm using the microplate reader. A standard curve was plotted with the

standard concentrations the O.D and the CYP concentration in each sample were then

interpolated from the standard curve.

2.2.10 Assay of Liver Glutathione S-transferase Activity

The catalytic activity of liver GST was measured spectrophotometrically at 340 nm by

modified method of Habig et al. (1974) with 1 chloro2-4 dinitrobenzene and GSH as

substrates.

Principle of Assay Glutathione-S-transferase catalyzes the conjugation of 1-chloro 2, 4 dinitrobenzene (CDNB)

and reduced glutathione to form a glutathione-conjugate. The increase in absorbance is

monitored spectrophotometrically at 340nm.

Procedure: A known quantity (2.7 ml) of phosphate buffer (pH 7.2) and 0.1ml each of

3.0mM chloro dinitrobenzene (CDNB) and 0.1M reduced glutathione were pipetted into test-

tubes, mixed and transferred into the cuvette of the spectrophotometer, then 0.1ml of the liver

PMS was added and mixed thoroughly by inversion and the change in absorbance was

monitored at 60secs interval for 180secs. The glutathione S-transferase activity was expressed

as U (nmole/min)/ml), where one unit of GST activity was calculated as nmol of 1 chloro 2-4-

dinitrobenzene conjugate formed per minute per ml enzyme.

49

Calculation:

3.0= total volume of of assay (millilitres)

Df= dilution factor (10)

9.6= Millimolar extinction coefficient of Glutathione -1-chloro-2,4-dinitro benzene

conjugate at 340nm

0.10= volume of enzyme used (millimeter)

2.2.11 Assay of Serum Alanine Aminotransferase (ALT) Activity

Liver marker enzymes such as alanine aminotransferase (ALT) and aspartate

aminotransferase (AST) activities were assayed by the method of Reitman and Frankel (1957)

using Randox test kit.

Principle of Assay

ALT catalyzes the reversible transamination of -oxaloacetate and L-alanine to L-glutamate

and pyruvate. The pyruvate reacts with 2,4-dinitrophenylhydrazinein the presence of NADH

to pyruvate hydrazone. ALT is measured spectrophotometrically at 546nm by monitoring the

concentration of pyruvate hydrazone formed with 2, 4dinitrophenylhydrazine.

-Oxaloacetate + L-alanine ALT/GPT→L-glutamate + pyruvate + 2,4 dinitrophenylhydrazine----

pyruvate hydrazine. To a known quantity (0.5 ml) of solution 1 of the randox test kit in tubes for samples and

reagent blank, 0.1 ml of the samples and distilled water were added accordingly, it was mixed

and incubated for 30 min in an incubator at 37oC. A 0.5 ml of solution 2 was then added to

tubes, mixed and allowed to stand for 20 mins at room temperature. A known quantity, 5 ml

of sodium hydroxide was the added to the tubes and mixed. The Absorbance of sample

(Asample) was read against the reagent blank after 5mins,using the UV spectrophotometer (546

nm).The activity of the ALT of the serum samples were read from the standard calibration

chart in international unit per litre (IU/L).

50

Calculation

ALT in Sample (IU/L) = Standard of Conc. standard Absorbancesample Absorbance

×

2.2.12 Assay of Serum Aspartate Aminotransferase (AST) Activity

Principle of Assay AST catalyzes the reversible transamination of L-aspartate and α-ketoglutarate to oxaloacetate

and L-glutamate. AST is measured spectrophotometrically at 546nm, by monitoring the

concentration of oxaloacetate hydrazine formed with 2,4-dinitrophenylhydrazine.

- ketoglutarate + L-aspartate AST/GOT L-glutamate + Oxaloacetate+ NADH + H+→2,4

dinitrophenylhydrazine →oxaloacetatehydrazine

Procedure To 0.5ml of Reagent 1 in tubes for samples and reagent blank, 0.1 ml of the samples and

distilled water were added accordingly, it was mixed and incubated for 30 minutes in an

incubator at 37oC. Solution 2 (0.5 ml) was then added to tubes ,mixed and allowed to stand

for 20 min at room temp. Sodium hydroxide (5ml) was the added to the tubes and mixed. The

Absorbance of sample (Asample) was read against the reagent blank at 546 nm after 5minutes,

using the UV spectrophotometer. The activity of the ALT of the serum samples were read

from the standard calibration chart in international unit per litre (IU/L).

Calculation:

AST in Sample (IU/L) = Standard of Conc.standard Absorbancesample Absorbance

×

2.2.13 Assay of Serum Alkaline Phosphatase (ALP) Activity

Alkaline phosphatase activity was assayed using the method of Klein et al. (1960) and

Quimica Clinica Applicada (QCA) test kit.

51

Principle of Assay Serum alkaline phosphatase hydrolyses a colourless substrate of phenolphthalein

monophosphate, producing a phosphoric acid and phenolphthalein which, at alkaline pH

turns into a pink colour, the concentration, an indication of the presence of alkaline

phosphatase and this can be spectrophotometrically measured.

Procedure To 1ml of the distilled water was added 1drop of substrate in tubes for samples and standard,

it was mixed and incubated at 37oC for 5 min. A quantity, 0.1ml of standard and sample were

then added, mixed and incubated at 37oC for 5 min, after which 5ml of colour developer was

added; The Absorbance of the samples and standard were read at 550 nm with the UV

Spectrophotometer. The activity of ALP was calculated using the formula on the test kit

manual.

Calculation:

130

standard of AbsorbanceSample of Absorbance

×

Where 30= standard solution of alkaline phosphatase in water

2.2.14 Determination of Liver Total Protein Concentration

Determination of liver total protein concentration was carried out by the method of modified

Lowry et al. (1951)

Principle of Assay Under alkaline conditions, the divalent copper ions form complex with peptide bonds in

which it is reduced to monovalent ions. Monovalent copper ions and aromatic protein residues

then react with Folin Ciocalteu reagent (a mixture of phosphotungstic acid and

phosphomolybdic acid) to produce a very unstable product that decomposes in alkaline to

molybdenum/tungsten blue (reduced folin reagent). The concentration of the reduced Folin is

measured spectrophotometrically at 750 nm. Thus the total concentration of protein in the

sample can be deduced from the concentration of aromatic residues that reduce the Folin

reagent.

52

Procedure

To a known quatity of 0.1ml of PMS in sample test tube, 5ml of solution 3 and incubated at

50oC for 5 mins; then cooled to room temperature. A 0.5 ml of solution 4 was then added,

mixed and incubated at room temperature for 30minutes. A protein standard bovine serum

albumin (BSA) 2mg/ml was used to prepare series of concentration ranges (0-2 mg/ml). The

Absorbances were read at 750 nm and a plot of the absorbances against concentrations gave

the standard curve; the unknown concentrations of protein in the PMS test samples were

calculated as follows;

Calculation:

Absorbance of standard

2.2.15 Determination of Mean Body Weight of Rabbits

Mean body weight were carried out with the use of a weighing balance. The rabbits were

weighed on the Days 1, 14 and 28

2.2.16 Histological Evaluation of Liver Tissues of Rabbits The histological evaluation was carried out as described by Bancroft et al., 1996. Tissue

specimen from the liver of the control and experimental animals were sectioned, fixed in 10%

buffered formalin and dehydrated in ascending grades of ethanol. Thereafter, the tissue

sections were cleared in chloroform overnight, infiltrated and embedded in molten paraffin

wax. The blocks were later trimmed and sectioned at 5—6µm thickness. The sections were

deparaffinized in xylene, taken to water, and subsequently stained with haematoxylin and

eosin (H & E). The stained slides were studied under a photomicroscope with a magnification

of × 400 (Bancroft et al, 1996).

2.3 Statistical Analysis The results were expressed as mean + S.D. Comparisons were made between control and

treatment groups and using one way and two-way analysis of variance (ANOVA) SPSS

version 17; and subjected to LSD post hoc test for multiple comparison. Duncan new multiple

range test was used to compare means. Values at p ˂ 0.05 were regarded as statistically

significant.

53

CHAPTER THREE

RESULTS

3.1 Soil Analysis The result of the soil analysis revealed that the textural class of the soil was observed to be

Sandy-Clay-Loam, with the percentages of particle size( total sand and clay), pH , organic

matter content, cation exchange capacity , carbon, nitrogen and phosphorus contents as shown

in Table 1 .

3.2 Chromatograms of Butachlor in the Standard and Phaseolus Vulgaris Leaf Extracts

The chromatograms of two of the six butachlor standards are shown in Figures 9-10. The gas

chromatography-mass spectrometry was able to detect the parent butachlor ion in the plant

extract. Figures 11 a, b and c show the test sample 3(T3), the chromatogram with a retention

time of 14.84minutes, the fragmentation pattern and the molecular structure of butachlor found

all the extract. Figures 12a and b show the chromatogram of the test sample 2(T2) with a

retention time at 14.86 minutes and the fragmentation pattern; and Figures 13 a and b show the

test sample 1 (T1), chromatogram with a retention time 14.53 minutes, the fragmentation

pattern. In the control sample, no butachlor/residue was detected as shown in figures 14 a and b.

54

Soil Analysis Result

55

Figure 9a: Chromatogram of butachlor standard 1, S1. It shows the relative abundance of the

butachlor ion and the total run time of 26minutes.The retention time (butachlor elution time) for S1

is 14.96minutes)

56

Figure 9b: Mass Spectrometry of standard 1. It shows the fragmentation pattern of the butachlor

standard the various fragments and their masses in relation to their charges (mass/charge ratio)

57

Figure 9c: Molecular structure of butachlor(S1). This was observed in all the butachlor standard

58

Figure 10a: Chromatogram of Butachlor standard. It shows the relative abundance of the

butachlor ion and the total run time of 26minutes.The retention time (butachlor elution time) for S2

is 14.86minutes.

59

Figure 10b: Mass Spectrum of Butachlor standard 2(S2): It shows the fragmentation pattern of the

butachlor standard the various fragments and their molecular masses in relation to their charges

(mass/charge ratio)

60

3.2.2 Chromatograms of Plant Extract

Figure 11a: Chromatogram of Leave extract (T3). It showing the presence of the parent butachlor

in the leaf Extract, the relative abundance and the retention time of butachlor at 14.84minutes

61

Figure 11b: Mass spectrum of (T3) . It shows the fragmentation pattern of the butachlor, the various

fragments and their molecular masses in relation to their charges (mass/charge ratio)

62

Figure 11c: Molecular structure of butachlor. This was identified in the Phaseolus vulgaris Leaf

extract (T3), also in the extract of T2 and T1

63

Figure 12a: Chromatogram of Leaf extract (T2): showing the presence of the parent butachlor in

the Phaseolus vulgaris leaf Extract, the relative abundance and the retention time of butachlor

14.86minutes

64

Figure 12b: Mass Spectrum of T2 It shows the fragmentation pattern of the butachlor, the various

fragments and their molecular masses in relation to their charges (mass/charge ratio)

65

Figure 13a: Chromatogram of leaf extracts T1, showing the presence of the parent butachlor in the

leaf Phaseolus vulgaris leaf extract, the relative abundance and the retention time of butachlor

14.53minutes

66

Figure 13b: Mass Spectrum of leaf extract (T1), showing the fragmentation pattern of the butachlor

the various fragments and their molecular masses in relation to their charges (mass/charge ratio)

67

Figure 14: Control samples of the Phaseolus vulgaris leaf extract- Butachlor was not detected at

the range of retention time in the standard (14.64-15.13minutes) Elution was not observed in the

chromatogram

68

3.2.2 Butachlor Concentration in Phaseolus vulgaris leaf extract

Table 2: Butachlor herbicide in Phaseolus vulgaris leaf extract

n=2, Mean + SD

p < 0.05 Significantly different ND-Not detected , a.i-active ingredient

Concentrations of Butachlor Applied on the various soil samples

Concentrations of Butachlor bioaccumulated in the leave extract (ppm)

Control

No butachlor applied

ND

(T3) 5.0l/ha(3.2kg a.i/ha)

0.20+0.014 C1

(T2)- 4.4l/ha(2.9kg a.i/ha) 0.13+0.00014 C2

(T1)- 4.0l/ha (2.6kg a.i/ha) 0.10+0.014 C3

69

3.2.2 Bioaccumulation Factor (BAF)

The BAF of butachlor in the plant is shown in Table 2. An increase was observed in the order:

T3>T2>T1

Table 3: Bioaccumulation factor (BAF) of butachlor in bean plant

Plots Amount of butachlor

Applied on the Soil (mg/m2)

Amount of butachlor

detected in bean Plant(mg/kg)

Bioaccumulation Factor (BAF) * 10-4

T1 260 0.10 3.8

T2 290 0.13 4.5

T3 320 0.20 6.3

70

Table 4: Estimated quantities of butachlor consumed (ppm) by the rabbits for the period of experiment

Concentrations consumed

Experimental Period (Days)

1 14 28

C1 (0.10 ppm) 1 14 28

C2 (0.13 ppm) 1.3 18.2 36

C3 (0.20 ppm) 2 28 56

71

Table 5a: Estimated Hazard Quotient and Health Risk Index for the consumption of different concentrations of butachlor from average weight of 0.200kg vegetable/day (As adopted in the experiment) by an average body weight of 70kg. Table 5b: Estimated Hazard Quotient and Health Risk Index for the consumption of different concentrations of butachlor from average weight of 0.345kg vegetable/day by an average body weight of 70kg.

Daily average weight of vegetable consumption= 0.345kg/person/day

Butachlor

Conc.

C1 (0.10 ppm) C2 (0.13 ppm) C3 (0.20 ppm)

Hazard Quotient

0.56 0.74 1.10

Health Risk Index

0.60 0.70 1.10

Butachlor Conc.

C1(0.10ppm)

C2(0.13ppm)

C3(0.20ppm)

Hazard Quotient

0.98 1.28 1.97

Health Risk Index

0.98 1.28 1.97

72

3.3 Pesticide Biomarkers

3.3.1 Effect of Different Concentrations of Bio-accumulated Butachlor in Phaseolus vulgaris leave on the Liver Total Cytochrome P450 (CYP) of Rabbits

Cytochrome P450 levels for the groups 2, 3, 4 and the control (group 1)are presented in Table

6. On day 1 of the experiment, there was no significant difference (p > 0.05) in the CYP levels

of group 2 compared with control. However, there was a reduction in the CYP level of group

3; (although, not significant (p > 0.05) and group 4 (significant p > 0.05) compared with the

control. There was no significant difference in the CYP level of group 2 on day 14. However

there was a reduction in groups 3 which was considered significant (p < 0.05) and group 4

which was considered not significant (p > 0.05) compared with the control. A significant

increase (p ˂ 0.05) was observed on day 28, after prolonged exposure in groups 3 and 4 when

compared with the control. The increase on day 28 was observed to be concentration

dependent, implying that with the consumption of the higher concentrations of the bio

accumulated butachlor the level of CYP increased (Table 6). Within group 2 there was an

increase on day 14 and 28 though it was not significant but within groups 3 and 4 there was

significant increase (p < 0.05) on the 14th and 28th day and this was observed to be

concentration and time-dependent; that is, as the days progressed, with increase in

consumption of bio accumulated butachlor, the CYP increased.

73

`Table 6: Liver total cytochrome P450 (CYP) levels of rabbits exposed to different concentrations of bio-accumulated butachlor in the leaves of Phaseolus vulgaris.

CYP (ng/ml)

Experimental period (Days)

Experimental groups 1 14 28

Group 1 (control) 10.98 ± 2.12ac 12.72 ± 1.31ac 11.80 ± 0.47ac

Group 2 (0.10ppm) 10.76± 0.97c 12.12 ± 1.39ac 12.30 ± 0.99a

Group 3 (0.13ppm) 8.77 ± 0.57b 9.99 ± 0.93b 14.41 ± 2.01cd

Group 4 (0.20ppm) 8.11 ± 0.61b 10.72 ± 0.65bc 16.16 ± 3.16d

Values expressed as mean ±SD, n= 4.

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

Group1 (Control)- Animals fed with plants cultivated without the application of the Herbicide-0.00ppm

Group 2- (Animals fed with plants containing bio accumulated butachlor concentration of 0.10 ppm)

Group 3- (Animals fed with plants containing bio accumulated butachlor concentration of 0.13 ppm)

Group 4- (Animals fed with plants containing bioaccumulated butachlor concentration of 0.20 ppm)

74

3.3.2 Effect of Different Concentrations of Bio-accumulated Butachlor in Phaseolus vulgaris Leave on the Liver of Glutathione S-transferase (GST) Rabbits

The GST activity presented as mean ± SD for groups 2, 3, 4 and the control group (1) are in

Table 7. On day 1, there was a decrease in GST activity in group 2 when compared with the

control group, though not significant but there was significant decrease (p < 0.05) in groups 3

and 4 when compared to the control group 1. On day 14, there was no significant difference

between group2 and the control group, but there was a significant decrease (p < 0.05) in group

3 and a significant increase (p < 0.05) in group 4 when compared with the control group 1. On

the Day 28, there was also a significant increase (p < 0.05) in groups 2, 3 and 4 when

compared with the control group1, with the highest in group 4 (Table 6). In groups 3 and 4 a

similar trend could be observed, in that there was an initial decrease in GST on Day 1 of the

experiment and then on days 14 and 28 there was a consistent increase (p < 0.05) in the GST

activity.

75

Table 7: Liver glutathione S-transferase activity of rabbits exposed to different concentrations of bio-accumulated butachlor in the leaves of Phaseolus vulgaris.

GST activity(IU/ml enzyme)

Experimental period (Day)

Experimental groups 1 14 28

Group 1 (control) 2.43 ± 1.50ac 2.83 ± 0.57ab 2.33 ± 0.78a

Group 2 (0.10ppm) 2.18 ± 1.34a 2.03 ± 0.33ac 5.45 ± 0.86d

Group 3(0.13ppm) 1.03 ± 0.30ac 1.38 ± 0.43c 6.75 ± 2.82bd

Group 4( 0.20ppm) 0.86 ± 0.02c 3.95 ± 1.10d 8.10 ± 1.26b

Values expressed as mean ± SD, n= 4

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

76

3.4 Liver Marker Enzymes

3.4.1 Effect of Different Concentrations of Bio-accumulated Butachlor in Phaseolus vulgaris Leaves on the Activity of Serum Aspartate Aminotransferase (AST) of Rabbits

The AST activity presented as mean ± SD for groups 2, 3 and 4 rabbits fed with 0.10, 0.13

and 0.20 ppm of bioaccumulated butachlor in the leaves and the control (group 1) are shown

in Table 8. On day 1 a significant increase (p ˂ 0.05) was observed in groups 3 and 4,

compared with the control (group 1). On days 14 and 28 there was also a significant increase

(p < 0.05) in the AST activities when groups 3 and 4 were compared with the control (group

1). The effect was observed to be concentration and time dependent. Within groups 2, 3 and 4

a similar trend was observed, in that the AST was consistently increasing (significant p <

0.05) as the days increased, with the highest in group 4 (day 28). Comparing across the groups

on the different days; in group 1 there was no significant differences observed within the

period of the experiment. Within group 2, there was significant increase observed in the AST

activities on day 28 compared with that of day 14. Within groups 3 and 4 a similar trend was

observed, in that the AST increased consistently as the days increased with the highest AST

activity observed in group 4 rabbits on day 28.

77

Table 8: Serum AST activity of rabbits exposed to different concentrations of bio accumulated butachlor in the leaves of Phaseolus vulgaris.

AST (IU/L)

Experimental period (Days)

1 14 28

Experimental groups

Group 1 (control) 36.25 ± 5.91a 36.00 ± 5.48a 45.00 ± 14.24a

Group 2(0.10ppm) 51.75 ± 7.81ab 53.75± 11.33b 98.00 ±16.87d

Group 3(0.13ppm) 64.25 ± 15.35b 98.25 ± 12.99bc 128.50 ± 38.31cd

Group 4(0.20ppm) 76.50 ± 9.68b 96.00 ± 11.92c 132.50 ± 13.87d

Values expressed as mean ±SD, n= 4

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

78

3.4.2 Effect of Different Concentrations of Bio-accumulated Butachlor in leaves of Phaseolus

vulgaris on the Activity of Serum Alanine Aminotransferase (ALT) of Rabbits

The ALT activity presented as mean ± SD for groups 2, 3 and 4 rabbits fed with 0.10, 0.13

and 0.20 ppm of bioaccumulated butachlor in the leaves and the control (group 1) are shown

in Table 9. There was no significant difference (p > 0.05) in the ALT activity of all the groups

on day 1 of the experiment; though, there was a decrease (not significant) in group 4 when

compared with the control. On day 14, there was a significant increase at p < 0.05 level, in

group 3 when compared with the control, whereas for group 4 (highest herbicide

concentration) there was significant decrease (p < 0.05), when compared with the control. In

group 4 there was no significant difference when compared with the control but there was

decrease (significant p < 0.05) when compared with group 3 on day 28. A similar trend was

observed in within groups 2 and 3; an increase which was significant (p < 0.05) in group 3 on

day 14 and then a subsequent decrease on day 28. However group 4 was different especially

on day 14 in which there was a significant decrease when compared across the days and as

well as with the control.

79

Table 9: Serum ALT activity of rabbits exposed to different concentrations of bio accumulated butachlor in the leaves of Phaseolus vulgaris.

ALT (IU/L)

Experimental Period (Day)

1 14 28

Experimental groups

Group 1 (control) 24.50 ± 4.51a 26.50 ± 3.69a 24.00 ± 6.38a

Group 2(0.10ppm) 27.50 ± 5.26a 37.25 ± 13.69a 31.25 ± 12.18a

Group 3 (0.13ppm) 31.00 ± 6.06a 42.75 ± 6.96b 36.50 ± 5.57ab

Group 4(0.20ppm) 20.75 ± 6.95a 10.75 ± 1.71c 26.75 ± 3.78a

Values expressed as mean ±SD, n= 4

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

80

3.4.3 Effect of Different Concentrations of Bio-accumulated Butachlor in leaves of Phaseolus

vulgaris on the Activity Serum Alkaline Phosphatase (ALP) in Rabbits

The ALT activity for groups 2, 3 and 4 rabbits administered 0.10, 0.13 and 0.20ppm of

butachlor and the control (group 1) are shown in Table 10.On day 1 there was no significant

differences in the ALP activities of groups 2, 3, and 4 when compared with the control

group1.However there was a decrease in group 2 and 3 which was not significant. On day 14,

there was significant increase (p ˂ 0.05) in all three groups (2, 3, 4) when compared with the

control group1. Likewise on day 28 there was a significant increase (p < 0.05) in ALP

activities of groups 3 and 4 (concentration and time dependent); with a significant decrease (p

> 0.05) in group 2, when compared with the control. In groups 3 and 4 a similar trend was

observed in that there was an increase on day 14 and then a non-significant decrease, on day

28(however still significantly increased when compared with the control. In group 2 a

significant increase in the ALP activity on day 14 was observed with a significant decrease (p

> 0.05) on day 28.

81

Table 10: Serum ALP activity of rabbits exposed to different concentrations of bio accumulated butachlor in the leaves of Phaseolus vulgaris.

ALP (IU/L)

Experimental Period (Days)

Experimental groups 1 14 28

Group 1 (control) 40.25 ± 11.11a 36.25 ± 6.55ab 44.00 ±12.99a

Group 2(0.10ppm) 32.25 ± 7.14ad 47.25 ± 11.0b 28.75 ± 2.50d

Group 3(0.13ppm) 34.00 ± 9.49a 68.25 ± 23.2b 58.25 ± 7.28c

Group 4(0.20ppm) 42.50 ± 12.82a 70.50 ± 12.6c 61.00 ± 8.76c

Values expressed as mean ±SD, n= 4

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

82

3.5 Effect of Different Concentrations of Bio-accumulated Butachlor in Leaves of Phaseolus

vulgaris on Mean Body Weight of Rabbits

The mean body weights of the rabbits for groups 2, 3 and 4 and the control group 1 are shown

in Table 11. It was observed that there was no significant difference in the mean body weight

of the rabbits in groups 2, 3 and 4 when compared with the control group1 on days 1, 14 and

28; however it was observed that within each group, the body weight decreased slightly as in

Day 14 with a subsequent increase on Day 28.

83

Table 11: Mean body weight of rabbits exposed to different concentrations of bio-accumulated butachlor in the leaves of Phaseolus vulgaris.

Body Weight(kg)

Experimental Period (Days)

1 14 28

Experimental groups

Group 1 (control) 1.3 ± 0.1a 1.1 ± 0.1b 1.3 ± 0.04a

Group 2 (0.10ppm) 1.3 ± 0.2a 1.1 ± 0.3ab 1.4 ± 0.5a

Group 3 (0.13ppm) 1.5 ± 0.1a 1.0 ± 0.1b 1.4 ± 0.4ab

Group 4 (0.20ppm) 1.3 ± 0.2ab 1.4 ± 0.2b 1.6 ± 0.3ab

Values expressed as mean ±SD, n= 4

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

84

3.6 Effect of Different Concentrations of Bio-accumulated Butachlor in the leaves of Phaseolus vulgaris on Liver Total Protein of Rabbits

The results in Table 12 reveals that groups 2 and 3 when compared with the control group (1)

on day 1 were not significantly different (p > 0.05) However, a significant increase(p <

0.05)was observed in group 4 when compared with group 1 on day 1;also a non-significant

increase in group 3. There was a significant increase (p < 0.05) in group 2, 3 and 4 when

compared with the control on day 14. On day 28 there was no significant differences observed

in all test groups when compared with the control although a non-significant decrease was

observed. Comparing across on the different days, within each group, it was observed that the

protein concentration decreased slightly, as in Day 14 (significant in groups 1 and 4) with a

subsequent increase which was significant on Day 28.

85

Table 12: Liver total protein of rabbits exposed to different concentrations of bioaccumulated butachlor in the diet

Liver Protein

Experimental Period (Days)

1 14 28

Experimental groups

Group 1 (control) 7.93± 0.51a 5.95± 0.47b 16.28± 1.43c

Group 2(0.10ppm) 8.93± 0.30ab 8.20± 0.82a 14.53± 1.74c

Group 3(0.13ppm) 8.58± 1.21ab 7.30± 0.59a 15.63± 0.99c

Group 4(0.20ppm) 9.88± 1.19b 7.13± 0.61d 16.25 ±0.84c

Values expressed as mean ±SD, n= 4

Mean values with different letters as superscript in the same column and row are considered significant (p < 0.05) while mean values with the same letters as superscripts are considered non-significant (p > 0.05).

Figures 16-18 shows the photomicrograpd groups 2,3 and 4 for the period of the exp

86

3.6 Histological Evaluation of Liver Tissue of Rabbits Indirectly Exposed to Butachlor Herbicide

Plates 1 – 3 show the photomicrographs of the liver sections of the control group (1) and the

groups 2, 3 and 4 fed with leaves containing 0.10, 0.13 and 0.20 ppm of butachlor respectively

for the period of the experiment. Liver histologic observations of the control group showed

normal histopathology which include; radially arranged hepatic cords around the central vein

separated from each other by sinusoids radiating from the central veins to the periphery of

liver lobules, no signs of nuclear fragmentation, no cytoplasmic vacuolization and no signs of

degeneration or necrosis were observed. (Figs 15-17). These normal features were also

observed in the liver tissues of the rabbits in groups 2, 3 and 4 fed with leaves containing the

three (3) different concentrations of the butachlor herbicide (C1, C2 and C3) on days 1, 14 and

28 of the experiment (Figs 15, 16 and 17 photomicrographs).

87

Liver Sections at Day 1 of Groups1-4

Plate 1: A photomicrograph of liver sections from control (1) and experimental groups 2,3 and 4 after one day of feeding the rabbits with the butachlor bio-accumulated leaves. Showing normal features portal area (P) and plates of hepatocytes (arrowed). Radially arranged hepatic cords around the central portal vein(P) separated from each other by sinusoids radiating from the central veins to the periphery of liver lobules, no signs of nuclear fragmentation, no cytoplasmic vacuolization and no signs of degeneration or necrosis were observed. H and E × 400.

1 2

3

P

P

P

4

P

88

Liver Sections at day14

Plate 2: A photomicrograph of liver sections from control (1) and experimental groups 2,3 and 4 after one day of feeding the rabbits with the butachlor bio-accumulated leaves. Showing normal features portal area (P) and plates of hepatocytes (arrowed). Radially arranged hepatic cords around the central portal vein(P) separated from each other by sinusoids radiating from the central veins to the periphery of liver lobules, no signs of nuclear fragmentation, no cytoplasmic vacuolization and no signs of degeneration or necrosis were observed. H and E × 400.

1 2

P

3 4

P P

P

89

Liver Sections at day 28 (week 4)

Plate 3: A photomicrograph of liver sections from control (1) and experimental groups 2,3 and 4 after one day of feeding the rabbits with the butachlor bio-accumulated leaves. Showing normal features portal area (P) and plates of hepatocytes (arrowed). Radially arranged hepatic cords around the central portal vein(P) separated from each other by sinusoids radiating from the central veins to the periphery of liver lobules, no signs of nuclear fragmentation, no cytoplasmic vacuolization and no signs of degeneration or necrosis were observed. H and E × 400.

4

P

3

P

P

2 1

P

90

CHAPTER FOUR

DISCUSSION

The outcome of the soil analysis showed that the soil contain a very high percentage of sand (74%).

This could have enhanced the uptake of the herbicide by the plant; since herbicides are known to

adsorb less to sandy soil (Rao, 2000; Tomaz, 2013), resulting to a higher bioavailability of the

herbicide by the bean plant as observed in the present study. Also the low percentage of soil organic

matter may have also affected the herbicide uptake since there was less adsorption to soil and organic

matter, less microbial degradation, resulting to bioavailability of the herbicide in the soil-water

compartment and thus uptake and bioaccumulation. (Tomaz, 2013)

The sorption of herbicides by soil is important in determining their environmental fate, such as

bioavailability, toxicity, biodegradation, persistence, and leachability in soil. The adsorption

coefficient Koc, is the tendency of herbicide sorption to organic carbon in the soil. According to

Connell, (1990) higher values (greater than 1000) indicate a pesticide that is very strongly attached to

soil and is less likely to move unless soil erosion occurs. Lower values (less than 300-500) indicate

pesticides that tend to move with water and have the potential to leach or move with surface runoff.

From literatures it has been reported that the Koc of butachlor herbicide is about 700ml/g in soils

(Roberts et al., 1998; Connell, 1990). Thus it may be inferred that butachlor has a moderate soil

sorption and the tendency to move with water (bioavailable in the soil-water compartment), thus

uptake and bio accumulation in the plant is enhanced.

The soil pH was observed to be 5.4 which is towards acidic and thus less survival for microrganisms

that can degrade the herbicide. The octanol/water partition coefficient is a measure of a chemicals

affinity for the hydrophobic portion in soil. The n-octanol/water partition coefficient of butachlor has

been reported to be 3.16 ×10-4 and the Log Kow is 4.50(Roberts et al., 1998); the log kow of butachlor

could be said to be high, based on the fact that organic chemicals that have log Kow higher than 2 are

usually hydrophobic and considered liable to bio accumulate in biota. (Oliver and Charlton 1984;

Elzerman Studies have shown that the herbicide, butachlor persists in the aquatic system for a long

period of time hence its toxicity to aquatics (Tilak et al., 2007). Persistence of butachlor have also

been studied at two levels of application in different soils at three different sites under three moisture

regimes air-dry, field capacity and submergence (Prakash and Suseela, 2000). Soil properties that

91

may affect the uptake of herbicides by plant and thus bioaccumulation include: the soil texture and

shape, soil organic matter content, organic carbon, soil adsorption, soil pH and soil moisture (Coates,

1987; Franke et al., 1994).

The gas chromatography-mass spectrometry (GC-MS) analysis from this study, showed the presence

of the butachlor compound. The chromatographic profile of the analytical butachlor standards S1 and

S2 are shown in Figs 9-11; showing that the parent butachlor compound was eluted at that retention

time. The mass spectra in the standards showed the fragment 176 as the parent ion of butachlor,

indicating that the molecule is partly retained after an impart by an electron. The result showed the

chromatographic profile of the plant leaf extracts (T1-T3). Since the retention time and fragmentation

pattern are characteristic of a particular compound run under similar GC conditions, the standards

were used in the identification and quantification of butachlor in the Phaseolus vulgaris leaf extracts.

The GC-MS (Figs 11-13) result obtained showed the presence of the parent butachlor in the bean

plant leaves, with concentrations of C1 (0.10 ppm), C2 (0.13 ppm) and C3 (0.20 ppm), corresponding

to the plants cultivated with T1 (2.6 kg a.i/ha), T2 (2.9 kga.i/ha) and T3 (3.2 kg a.i/ha) respectively

after 6weeks of planting; whereas in the control plant cultivated without the application of the

herbicide, no butachlor was detected. Statistically, the result showed that butachlor concentration

increased significantly (p < 0.05) in C2 when compared with C1. Similarly, butachlor concentration

also increased significantly (p < 0.05) in C3 compared with C1. The plant cultivated with a

concentration of T1 (2.6kg a.i/ha), is the standard rate for butachlor in bean plant as recommended by

the manufacturers; and with this, there was an accumulation of 0.10ppm butachlor in the plant leaves.

At higher concentrations of T2 (2.9 kg a.i/ha) and T3 (3.2 kg a.i/ha), the butachlor accumulated was

observed to be higher (0.13 and 0.20 ppm respectively), giving a 30% and 100% increase from

0.10ppm concentration respectively. This implies increasing accumulation of butachlor as

concentration increases. Bioaccumulation of herbicides in vegetables have also been reported in the

research findings of Kaphalia et al. (1990); Tadeo et al. (2000); Anderson and Poulsen, 2001; Tseng

et al. (2002) ; Qiu et al. (2010) and Etonihu et al. (2011).

The herbicide levels determined in this study (0.13 and 0.20 ppm) when compared to some reports in

literatures on butachlor and other pesticide (herbicide) levels in vegetables/food, appeared to be

higher (Gorell et al., 1998; Jaga, 2003; Etinohu et al., 2011). Although, the level of butachlor at 0.1

92

ppm (mg/kg) is in agreement with the value of 0.1mg/kg pesticide level as observed by Olshan and

Daniels (1997)

The results showed the bioaccumulation factor (BAF) in the plant. Bioaccumulation factor expresses

the extent of chemical accumulation in the plant/animal. The BAF was observed to be increasing with

respect to increase in the concentration of the herbicide applied, in the following order T3>T2>T1.

This implies that the higher the amount of herbicide applied, the greater the bioaccumulation in the

plant leaves. It has been established that the greater the BAF, the greater the accumulation and the

greater the risk of pesticide(Van der Oost et al., 2003).

It was observed in the result that the estimated quantities of butachlor consumed in parts per million

by the exposed rabbits for the period of experiment increased, in the rabbit fed the butachlor

contaminated plant leaves, and this was in a concentration/time dependent manner. The risk in the

consumption of the bioaccumulated butachlor was assessed by determining the hazard quotient (HQ)

and Health Risk Index (HRI) for an average human body weight of 70 kg. It was observed that the

HRI upon consumption of an average weight of 0.200 kg vegetable containing bioaccumulated

butachlor of 0.10, 0.13 and 0.20 ppm was 0.57, 0.74 and 1.10 respectively over a lifetime. This

implies that there is no significant risk in the consumption of the first two concentrations but there is

significant risk upon the consumption of the latter concentration. It was also observed that the HRI

upon consumption of an average weight of 0.345 kg (WHO, 1997) vegetable containing

bioaccumulated butachlor of 0.10, 0.13 and 0.20 ppm was 0.98 1.28,1.97 respectively over a

lifetime. This implies that upon consumption of 0.10 ppm, there was no significant risk, while upon

the consumption of the two latter concentrations, there is significant risk. Based on the fact that when

HRI < 1 it indicates no significant risk over a lifetime of exposure, while HRI > 1 indicates a

significant risk upon exposure and the contaminant may produce an adverse effect (Gupta et al.,

2013; Chary et al., 2008; Gerba, 2010; USEPA, 2003).

Animals that feed on plants may ingest one or more pesticide/residue produced in or on the plant and

this is subject to metabolism either by bacteria in the intestine and external to the cells of the animal,

or it is absorbed alongside with that via the skin and respiratory tracts and then transported to the

liver. The liver is the primary site of xenobiotics bio-transformation (pesticides) for the purpose of

facilitating their clearance through excretion of water–soluble products via detoxification. The high

level of oxidative metabolism in the liver, makes this organ a possible target for more toxic

93

metabolites when detoxifying and protective mechanisms are overwhelmed (Hodgson and Levi,

1997). The liver is also rich in xenobiotic metabolizing enzymes which include cytochrome P450 and

glutathione S-transferase. Pesticides are known to be substrates for these enzymes as well as inducers

or inhibitors (Melancon, 1996).

Cytochrome P450 are enzymes involved in phase Ι metabolism of xenobiotics. In the result of the total

cytochrome P450 (CYP), there was a non-significant reduction observed in the levels of CYP in group

2. However, there was a significant (p < 0.05) reduction in CYP of group 3 and 4 rabbits when

compared with that of the control group, on day 1.This may be attributed to the presence of small

quantities of the butachlor (higher concentration) which was consumed from the plant on days 1 and

14, hence there was an immediate utilization of the detoxifying enzyme cytochrome P450 in the body

system of the rabbits causing a reduction, however, as the days went by, with more quantities of the

plant with higher butachlor concentration being consumed, there was an induction of

synthesis/production of the detoxifying enzyme, as could be observed by the increase (significant at p

˂ 0.05) on day 28, after prolonged exposure for groups 3 and 4, when compared with the control

(group1) on day 28 as well as within the group. The increase was be observed to be time-dependent.

The result obtained showed that a higher concentration of butachlor that bioaccumulated in plants

consumed in group 4 (0.20 ppm) resulted to an increase in the levels of liver CYP by 37% and also in

group 3 by 22% when compared to the control group (1); while in group 1 which contained no

herbicide, there was no induction and in group 2. There was little or no induction of CYP. Such was

also observed in an acute study by Pogrmic-Majkic et al. (2012), where there was a similar effect of

atrazine herbicide on the liver CYP however in this case, a higher concentration of atrazine increased

the levels of CYP by 56% when compared with the control. This result of CYP induction by

herbicide, is also in agreement with some other acute and chronic studies of direct exposure of fish

and rats to butachlor and atrazine (Islam et al., 2002; Farombi et al., 2008).

Glutathione S-transferases (GSTs) are ubiquitous multifunctional enzymes which play key role in

phase 2 of cellular detoxification especially xenobiotics such as pesticides (Ezemonye and Tongo,

2010). The major activity of GST is the conjugation of compounds with electrophilic centers to the

tripeptide glutathione (Oakley, 2011). The glutathione conjugates are metabolized further to

mecapturic acid and then excreted. A significant ( p > 0.05) reduction in GST activity was observed

in group 2 when compared with the control on day 1 of the experiment; likewise on the day 14; this

94

could be due to the fact that herbicide present for detoxification was in small quantities. However,

there was an increase on the day 28 but not as much as in group 3 and 4 which had higher

concentrations of the herbicide. In groups 3 and 4 a similar trend could be observed in that, there was

an initial decrease in GST activity, which was significant (p < 0.05) when compared with the control

on day 1 of the experiment, indicating a rapid utilization of the GST for detoxification of the

butachlor herbicide; and then on the days 14 and 28; there was a consistent and significant increase (p

< 0.05) in the GST activity. This is most likely due to the prolonged exposure to butachlor in groups 3

and 4 (higher concentrations), such that the enzyme was induced in other to cope with the

detoxification of the higher concentration of butachlor in the liver. The time-dependent increase in

GST as observed in the present study is in agreement with some other research findings involving a

direct exposure to butachlor in several fish species (Otto and Moon, 1996; Shalaby et al., 2007). Also,

an exposure to atrazine herbicide has been shown to cause the induction of GST in hepatic

microsomes and cytosol of Fisher rats (Islam et al., 2002). It is possible that an increase in the activity

of GST contributes to the elimination of reactive oxygen species, induced by the herbicide from the

cell (Jin et al., 2010). The increased GST activity also suggests that the enzyme may be responsible

for the conversion of butachlor to more hydrophilic metabolites which could increase its elimination

rate from the organism. However, it was also reported that in the absence of acetyl CoA, the GSH

conjugate was metabolized to butachlor cysteine conjugate (Ou and Lin, 1992). Farombi et al. (2008)

also observed a significant increase in the liver GST of fish exposed to butachlor concentrations of 1-

2.5 ppm; however, they observed a significant decrease in kidney GSTwith increased

malondialdehyde (MDA), an indication of increased lipid peroxidation, suggesting that the kidney

was subjective to severe oxidative toxicity during the exposure. In vitro incubation of liver and

kidney fractions with butachlor showed that butachlor was first bio transformed by conjugation with

GSH by the enzyme GST to form butachlor glutathione conjugate which was further transported to

the kidneys to form mercapturic acid by N- acetylation (Farombi et al., 2008). The GST result from

the present study however contravened the reduction in liver GST activity of birds exposed to

pesticide diet, as reported by Ezeji et al. (2012).

This study also evaluates the effect of butachlor on some liver marker enzymes and the hepatic tissue.

To determine the hepatotoxic effect on the liver, the analysis of serum constituents has proved to be a

useful tool in the detection and diagnosis of metabolic disturbances and disease incidence processes

(Aldrin et al., 1982; Tolba et al., 1997). Enzymes are protein catalysts present mostly in living cells

95

and are constantly and rapidly degraded although, renewed by new synthesis (Coles,1986). The

normal enzyme level in the serum is a reflection of a balance between their synthesis and release, as a

result of the different physiological processes in the body (Zilva and Pannall, 1984). Transamination

involving transaminases, represents one of the principal pathways for the synthesis and deamination

of amino acids, thereby allowing an interplay between carbohydrate, fat and protein metabolism

during fluctuating energy demands of the organism under various adaptive conditions; therefore

attention has been focused on the changes in the aminotransferases; AST and ALT promote

gluconeogenesis from amino acids and they relate changes in their activities to changes in specific

organs/tissues (Marie, 1994; Gabriel and George, 2005; Nelson and Cox, 2000). Liver cells are

particularly rich in transaminases because this organ is the major site for interconversion of food

stuff. AST and ALT are normally found in low concentrations in the blood, when liver cells are

damaged, tissues may leak them into the plasma causing an increase in activity, hence they are

frequently used to diagnose the sublethal/lethal damage to the liver (Jyothi and Narayan, 2000; Dutta

and Arends, 2003). ALT is localized primarily in the cytosol of hepatocytes and it is more sensitive

and specific in hepatocellular damage than AST (Marshall, 2000). An elevated level of AST is not

specific to liver damage hence it is of less diagnostic use to determine liver damage (Michel, 1998).

From this present study, it was observed that there was significant increase (p < 0.05) in the AST

activity of groups 3 and 4 rabbits when compared with the control group (1) as shown in Table 8, and

this signified that exposure of the rabbits to butachlor concentrations of 0.13ppm and 0.20 ppm in the

diet for the period of the experiment, affected the activity of this transaminase. Also, in the present

experiment, AST activity as observed in groups 2, 3 and 4 rabbits, showed a general trend to increase

during the exposure when compared to the control values in group 1; with the highest recorded in

group 4 at day 28. The increase was observed to be concentration and time dependent and this is in

agreement with a chronic study carried out with exposure of sublethal concentrations of butachlor on

Nile tilapia fish Orechromis niloticus (Abbas et al., 2007). Nwani et al. (2013) showed that butachlor

is toxic to fresh water fish Tilapia zilli upon acute exposure with a significant increase in AST

activity. In the present study, it may be implied that the significant increase in AST may be due to

leakage from the liver cells or may be due to leakage from another organ that was affected, since AST

could also be found in other organs such as the kidney and muscle. An increase in AST alone is

however not suggestive of liver damage, so other liver enzymes have to be considered to be

conclusive.

96

From literatures, it is known that elevated levels of liver AST and ALT may indicate the active

utilization of amino acids in energy yielding metabolic processes such as gluconeogenesis to produce

energy to cope with the stress of herbicide detoxification (Adams et al.,1996; Vani et al.,2012)

ALT is found predominantly in the liver but small amounts are found in the kidneys, heart, muscles

and pancreas, it is a more specific indicator of liver damage. The results of the ALT are presented in

Table 9. A similar trend was observed in the ALT activity within groups 2 and 3 during the

experiment. Within groups 2 and 3, there was an increase (significant in group3) on day 14 and then a

non-significant decrease on day 28 but in group 4, there was a significant decrease (p < 0.05) in the

ALT activity on the 14th day of the experiment, thus revealing a fluctuating activity. Salah El-deen

and Rogers (1991) observed a similar result and stated that this fluctuation in ALT activity may be

attributed to a number of factors such as leakage from liver and muscle into the blood, liver enzymes

inhibition by the effect of the pollutant and/or disturbances in Kreb’s cycle. Shalaby et al. (2007) also

showed a significant decrease in ALT on the day 30 of exposure of butachlor herbicide in fish and

this, they attributed to the inhibition of enzyme synthesis as a result of the toxic effect of the

herbicide. Some other studies also showed that toxicants can inhibit the activity or synthesis of

enzymes, resulting in decreased activities of the enzymes in the organs, however the mechanism is

not known (Nesckovic et al., 1996; Jung et al., 2003; Mousa ,2004; Ambali et al., 2010). Edori et al.

(2013) observed a significant decrease in ALT of fish exposed to high concentration of paraquat after

21 days. Abbas and Mahmoud (2003) however reported that AST and ALT showed fluctuated

activities in both acute and chronic exposure to thiobencarb (butachlor) in fish species. They pointed

out that toxicants act on carboxyl, amino, sulphydryl, phosphate and other similar groups of cell

components. They also further summarized the possible mode of action as: (1) disruption of the

enzyme system by blocking active sites; (2) formation of stable precipitates or chelation by essential

metabolites (3) immobilizing the catalytic decomposition of essential metabolites; (4) combination of

the substances with the cell membranes, thus affecting their permeability and (5) replacement of the

structurally or electrochemically important elements in the cell when they fail in function.

In the present study it was observed that there was a decrease in the ALT activity of group 4 rabbits

when compared to the control group (1) all through the experiment, especially on day 14 of the

experiment, there may be suppression/inhibition of ALT activity at the highest herbicide

concentration (0.20 ppm).

97

It was also observed that on day 28 there was significant decrease(p < 0.05) in the ALT activity of

groups 2 and 3 rabbits when compared to day 14 of the same groups; it could also be possible that

there may be an inhibition after prolonged exposure (28 days) to these concentrations of the

butachlor. However, in group 4 (0.20 ppm) in which there was greater induction for the detoxification

of the butachlor to result to reduced effect of the herbicide on the enzyme.

In animals, alkaline phosphatase is present in all tissues throughout the entire body, but is particularly

concentrated in the liver, bile duct, kidney and the bone. In groups 2, 3 and 4, a similar trend was

observed with the highest ALP activity on day 14 (Table 10) as in the case of groups 2 and 3 in ALT.

On day 1 there was no significant differences (p > 0.05) in the groups 2, 3 and 4 when compared with

the control group. On day 14, there was significant increase (p ˂ 0.05) in all three groups (2, 3 and 4)

when compared with the control group. However, on day 28, there was a decrease in the ALP activity

from day 14 in each group, however, for groups 3 and 4, the differences were still significantly

increased (p < 0.05) when compared with the control groups. This increase was observed to be

concentration and time dependent especially on day 14 of the experiment. An increase in ALP was

also observed in studies carried out by Shalaby et al. (2007). This fluctuation in ALP on the days 1,

14 and 28 may also be attributed to liver enzyme inhibition as observed of ALT activity or as result of

leakage from the liver due to slight injury.

From the result of liver enzymes in the present study, it could probably be that there was a profound

effect after 14 days of exposure of butachlor on the liver, to have resulted to the significant increase

in the AST and ALP activities in groups 2 and 3 rabbits, but however due to the increased/induced

levels of detoxifying enzymes (CYP and GST), there was increased detoxification of the butachlor, as

such reducing the effect of butachlor and resulting to a reduction in the effect on ALP and AST

activities as observed on day 28 of the experiment.

Liver histologic observations of the control group showed radially arranged hepatic cords around the

central vein which are separated from each other by sinusoids radiating (capillaries) from the central

veins to the periphery of liver lobules, no signs of nuclear fragmentation, no cytoplasmic

vacuolization, no signs of degeneration or necrosis were observed. These features were also observed

in the liver tissues of the rabbits in groups 2, 3 and 4 which were exposed to the three (3) different

concentrations of the butachlor herbicide (C1, C2, C3) on days 1, 14 and 28 of the experiment.

98

Histological sections of the liver of the exposed rabbits thus revealed no pathological alterations after

28 days of exposure to butachlor.

The liver enzyme AST and ALP increased upon exposure to the butachlor concentrations of 0.13 and

0.20 ppm. However the histological examination showed no visible pathological alterations. It is

possible that the architecture of the liver tissue was not affected at these concentrations, for the

duration of indirect exposure. The concentrations and duration of exposure to butachlor was not

sufficient to cause remarkable membrane damage in the liver cells. A study by Dwivedi et al, 2012.,

showed that butachlor induced dissipation of mitochondrial membrane DNA damage and necrosis in

human blood cells. Although the actual mechanism of butachlor in human is not known but if it is

similar to that observed in plant in affecting the cell membranes and with the findings of Dwivedi et

al., 2012; it could be possible that butachlor affects the cell membranes (especially the mitochondrial

membrane) thus slightly affecting the permeability resulting to significant increases in the activities

of AST (from the mitochondria) and ALP(in the membranes). However due to induced detoxifying

enzymes and short duration of exposure, the effect of the butachlor may have reduced. ALT and ALP

are indicators of membrane integrity. This could probably indicate that there was little or no

disruption of the liver tissues at the different concentrations. Hence there was no visible pathological

liver damage observed. In the present study, the increase in CYP and GST levels in the liver could

also indicate the accelerated metabolism of butachlor thus resulting to little or no effect of the

herbicide on the liver tissue for the period of the experiment as shown by the histopathology result.

Upon exposure to toxicants, the cellular component of the liver which seems to be affected most is

the cellular membrane. Toxicants have been observed to either have increased the cellular membrane

permeability thereby enhancing enzyme leaching or leaking out of the liver to the blood or may have

reduced the permeability, forcing the enzymes to accumulate in the cells (Gabriel et al., 2009;

Yousafzai and Shakoori, 2011). Assays on lipid peroxidation though was not undertaken in the

present study, would give a clue on the state of the cellular membrane in the liver; if there was a

disruption to cause a release of the intracellular enzymes into the blood or the extent of membrane

disintegration.

There was no significant difference (p > 0.05) in mean body weight of rabbits in groups 2, 3 and 4

when compared with the control group on all the days of the experiment; thus it can be inferred that

the butachlor herbicide had no significant effect on the mean body weight of the rabbits of groups 2, 3

99

and 4 when compared with the control group1. This result may also be explained that, there may be

no bioaccumulation of the herbicide in the animal tissue of the rabbits since bioaccumulation of

butachlor herbicide have been shown to influence the growth rate, muscle protein and body weight of

animals exposed to herbicides (Hodson et al., 1978). It was observed that within all the groups, the

mean body weight decreased slightly as observed on day 14, with a subsequent increase on day 28.

This could be attributed to the change in diet (growers marsh to bean leaves), since the animals may

be trying to adjust to the new diet and as such a reduction in food consumption resulting to a

reduction in mean body weight; then with a later acceptance of the new diet there was an increase in

consumption as well as the gain in body weight.

The result for the liver total protein is presented in table 12. There was no significant difference (p >

0.05) between groups 2, 3 when compared with the control group on day 1, but a significant increase

(p < 0.05) was observed between group 4 and group 1 on day 1. On day 14 there was a significant

increase (p < 0.05) in group 2 only when compared with the control group; however, there was a

significant decrease on day 28 in group 2 only. Within groups 3 and 4, it was observed that the

protein concentration decreased slightly, as in day 14 with a subsequent increase which was

significant on day 28; this could be a reflection of the increase in the CYP and GST enzymes as a

result of their induction in the liver. Butachlor has been shown to cause remarkable protein loss at

lethal as well as sublethal concentrations (Rajput et al., 2012). They attributed the decrease in protein

may be to the impairment of protein synthesis or increase in the rate of its degradation to amino acids.

This may be fed to TCA cycle through aminotransferase probably to cope with high energy demands

in order to meet the stress condition. The decrease in proteins might be due to their utilization in cell

repair and tissue organization with the formation of lipoproteins, which are important cellular

constituents of cell membranes and cell organelles present in cytoplasm (Harper, 1985). The decrease

in protein content as a result of toxicity stress has already being reported by Borah and Yadav (1995);

Muley et al. (2007); Singh and Bhati (1994). The decrease in liver protein during dimethoate

exposure may be due to increased catabolism and decreased anabolism of proteins (Khare and Singh,

2002). In the present study, this initial decrease in the liver total protein, could be attributed to the

initial decrease in the enzyme levels for detoxification (CYP and GST) as observed on days 1 and 14

in groups 2, 3 and 4 rabbits; since these enzymes are components of the total protein. However; upon

induction of the detoxifying enzymes, an increase was reflected in the total protein on day 28 of the

experiment.

100

This study showed that liver marker enzyme (AST, ALP) activities increased significantly (p < 0.05)

with exposure to 0.13 and 0.20 ppm butachlor concentrations; however, there may be an inhibition of

ALT activity at certain concentrations during the experiment and since ALT is more specific for liver

damage, this agrees with the fact that there was no observable adverse or pathological liver damage as

shown by the histopathology of the liver albeit, the indications of exposure to the herbicide by the

marker enzymes. The study also revealed that a subchronic exposure to 0.13 and 0.20 ppm

concentrations of butachlor in the diet led to a significant increase in the two pesticide biomarker

enzymes; Cytochrome P450 and glutathione S-transferase of the phases Ι and ΙΙ detoxification

reactions, in a concentration and time–dependent manner. From the above, it could therefore be

suggested that the enzyme detoxification mechanism; the induced cytochrome P450 and glutathione S-

transferase were able to detoxify the butachlor herbicide at the varied concentrations such that there

was no profound effect on the liver; hence the butachlor herbicide was not toxic to the liver of the

animals at these concentrations, when consumed in the diet for the period of the experiment.

However, the study show the possibility of a more toxic response upon chronic exposure to butachlor

when improperly applied.

4.2 Conclusion

The present study showed that there was bioaccumulation of butachlor in the bean plant, and this

increased with respect to the concentrations of butachlor applied to the soil. It also showed that the

manufacturers’ recommended application rate for butachlor (2.6 kg a.i/ha) posed no health risk,

however the application rates above the recommended rate could pose some risk when butachlor

bioaccumulates in edible plants that are consumed.

4.3 Suggestions for Further Studies

v It is recommended that further studies (chronic) be done; analysis of these enzymes as well as

histology on other organs such as kidney, muscle or bladder of animals, to determine the

toxicity of the butachlor herbicide.

v There is a need for regular testing and monitoring of herbicide residues in vegetables and

grains by pesticide regulatory bodies, to ascertain the maximum residue limits (MRL) are not

exceeded and to prevent their excessive build up in the food chain.

101

v It is recommended that farmers or agriculturalists adhere strictly to the manufacturers’ and

regulatory bodies in the application of this herbicide in the soil ecosystem, so as to reduce the

risk associated with herbicide/residue bioaccumulation in plant parts above the MRLs and

subsequent consumption by animals in the food chain. v There should be a health enlightenment programme to enlighten citizens including farmers on

the proper use of pesticides and the effects of pesticide residues in order to curb the potential

health risk to consumers.

102

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54

Table 1: The physicochemical properties of the Soil sample from the field area

Text Class Particle Size % pH Value Organic Matter % Exchangeable Bases(me/S100g soil) Exch. acidity me/100g soil

P

(ppm)

Sandy Clay Loam

Clay Silt Fine sand

Coarse sand

H2O KCl C O.M N2 Na+ K+ Ca2+ Mg2+ CEC

Cmol/kg

Base Sat.%

H+ Avail Phos.

(SCL) 19.30± 2.30

7.00± 0.00

26.00±6.70

48.00± 4.40

5.40±0.40

5.00±0.10

1.08±0.10

1.86±0.18

0.116± 0.03

0.39±0.01

0.24±0.02

5.60±0.10

2.40±0.5

10.80±0.55

79.92±0.40

1.60±0. 40 28.60± 18.6

Values are Mean ± SD n=2

122

APPENDICES

APPENDIX I: Standard Curves

123

APPENDIX II: Chromatograms of Butachlor Standards(S3-S6)

124

Chromatogram/Mass spectrum of Butachlor standard (S3)

125

Chromatogram/Mass spectrum of Butachlor standard (S4)

126

Chromatogram/Mass spectrum of Butachlor standard (S6)

127

APPENDIX 111:Statistical Analysis for Results

There is statistical difference between the C1 and C2 at 0.05 level of significance also there is significance difference between C1 and C3 and there is statistical difference between C2 and C3 at 0.05 level of significance.

ONE WAY ANOVA

Butachlor in sample Statistical Analysis

at 0.05 significance level

Samples Conc. 1 Conc.2 MEANS std deviation C1 0.1 0.08 0.09 0.01414 C2 0.1275 0.1277 0.128 0.00014 C3 0.2 0.18 0.19 0.01414 MEANS 0.1425 0.1292 ANOVA

Sum of Squares df

Mean Square F Sig.

Between samples 0.01 2 0.005 38.267 0.007

Within samples 0.0004 3 0.0001 Total 0.011 5 POST HOC TEST Duncan

Subset for alpha = 0.05

SAM N 1 2 3 1 2 0.09 2 2 0.1276 3 2 0.19 Sig. 1 1 1 Means for groups in homogeneous subsets are displayed.

128

Oneway {Day 1}

Descriptives

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body Weight

Group 1=Normal Control 4 1.2750 .09574 .04787 1.1227 1.4273 1.20 1.40

Group 2=0.10 ppm of Herbicide 4 1.3125 .24622 .12311 .9207 1.7043 1.10 1.55

Group 3=0.13 ppm of Herbicide 4 1.4375 .17017 .08509 1.1667 1.7083 1.20 1.60

Group 4=0.20 ppm of Herbicide 4 1.4000 .24833 .12416 1.0049 1.7951 1.10 1.70

Total 16 1.3563 .19138 .04784 1.2543 1.4582 1.10 1.70

Total Protein

Group 1=Normal Control 4 7.9250 .51235 .25617 7.1097 8.7403 7.40 8.60

Group 2=0.10 ppm of Herbicide 4 8.9250 .29861 .14930 8.4498 9.4002 8.60 9.30

Group 3=0.13 ppm of Herbicide 4 8.5750 1.20934 .60467 6.6507 10.4993 7.50 9.90

Group 4=0.20 ppm of Herbicide 4 9.8750 1.19826 .59913 7.9683 11.7817 8.10 10.60

Total 16 8.8250 1.08597 .27149 8.2463 9.4037 7.40 10.60

AST

Group 1=Normal Control 4 36.7500 4.03113 2.01556 30.3356 43.1644 32.00 41.00

Group 2=0.10 ppm of Herbicide 4 51.7500 7.80491 3.90246 39.3306 64.1694 42.00 61.00

Group 3=0.13 ppm of Herbicide 4 64.2500 15.34872 7.67436 39.8268 88.6732 48.00 81.00

Group 4=0.20 ppm of Herbicide 4 76.5000 9.67815 4.83908 61.0999 91.9001 69.00 90.00

Total 16 57.3125 17.70016 4.42504 47.8807 66.7443 32.00 90.00

ALT

Group 1=Normal Control 4 24.5000 4.50925 2.25462 17.3248 31.6752 21.00 31.00

Group 2=0.10 ppm of Herbicide 4 27.5000 5.25991 2.62996 19.1303 35.8697 22.00 32.00

Group 3=0.13 ppm of Herbicide 4 31.0000 6.05530 3.02765 21.3647 40.6353 22.00 35.00

129

Group 4=0.20 ppm of Herbicide 4 20.7500 6.94622 3.47311 9.6970 31.8030 15.00 29.00

Total 16 25.9375 6.46497 1.61624 22.4926 29.3824 15.00 35.00

ALP

Group 1=Normal Control 4 40.2500 11.11680 5.55840 22.5607 57.9393 25.00 51.00

Group 2=0.10 ppm of Herbicide 4 32.2500 7.13559 3.56780 20.8957 43.6043 24.00 41.00

Group 3=0.13 ppm of Herbicide 4 34.0000 9.48683 4.74342 18.9043 49.0957 22.00 43.00

Group 4=0.20 ppm of Herbicide 4 42.5000 12.81926 6.40963 22.1017 62.8983 30.00 60.00

Total 16 37.2500 10.24695 2.56174 31.7898 42.7102 22.00 60.00

Cyt_P450

Group 1=Normal Control 4 10.9768 1.73524 .86762 8.2156 13.7379 8.57 12.61

Group 2=0.10 ppm of Herbicide 4 10.7605 .79543 .39771 9.4948 12.0262 9.90 11.82

Group 3=0.13 ppm of Herbicide 4 8.7741 .46249 .23125 8.0381 9.5100 8.12 9.14

Group 4=0.20 ppm of Herbicide 4 8.1052 .50128 .25064 7.3076 8.9029 7.56 8.77

Total 16 9.6541 1.56876 .39219 8.8182 10.4901 7.56 12.61

GST

Group 1=Normal Control 4 2.4250 1.49750 .74875 .0421 4.8079 .80 4.10

Group 2=0.10 ppm of Herbicide 4 2.1750 1.34009 .67004 .0426 4.3074 .70 3.50

Group 3=0.13 ppm of Herbicide 4 1.0250 .29861 .14930 .5498 1.5002 .70 1.40

Group 4=0.20 ppm of Herbicide 4 .2625 .22809 .11404 -.1004 .6254 .10 .60

Total 16 1.4719 1.28580 .32145 .7867 2.1570 .10 4.10

130

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .068 3 .023 .566 .648

Within Groups .481 12 .040

Total .549 15

Total Protein

Between Groups 7.940 3 2.647 3.257 .060

Within Groups 9.750 12 .813

Total 17.690 15

AST

Between Groups 3480.188 3 1160.063 11.417 .001

Within Groups 1219.250 12 101.604

Total 4699.438 15

ALT

Between Groups 228.188 3 76.063 2.289 .130

Within Groups 398.750 12 33.229

Total 626.938 15

ALP

Between Groups 288.500 3 96.167 .897 .471

Within Groups 1286.500 12 107.208

Total 1575.000 15

Cyt_P450

Between Groups 24.588 3 8.196 7.979 .003

Within Groups 12.327 12 1.027

Total 36.915 15

GST

Between Groups 12.260 3 4.087 3.911 .037

Within Groups 12.539 12 1.045

Total 24.799 15

131

Post Hoc Tests

Multiple Comparisons

Dependent Variable (I) Groups (J) Groups Mean Difference

(I-J)

Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

Body Weight LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -.03750 .14161 .796 -.3460 .2710

Group 3=0.13 ppm of Herbicide -.16250 .14161 .274 -.4710 .1460

Group 4=0.20 ppm of Herbicide -.12500 .14161 .395 -.4335 .1835

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control .03750 .14161 .796 -.2710 .3460

Group 3=0.13 ppm of Herbicide -.12500 .14161 .395 -.4335 .1835

Group 4=0.20 ppm of Herbicide -.08750 .14161 .548 -.3960 .2210

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control .16250 .14161 .274 -.1460 .4710

Group 2=0.10 ppm of Herbicide .12500 .14161 .395 -.1835 .4335

Group 4=0.20 ppm of Herbicide .03750 .14161 .796 -.2710 .3460

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control .12500 .14161 .395 -.1835 .4335

Group 2=0.10 ppm of Herbicide .08750 .14161 .548 -.2210 .3960

Group 3=0.13 ppm of Herbicide -.03750 .14161 .796 -.3460 .2710

Total Protein LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -1.00000 .63738 .143 -2.3887 .3887

Group 3=0.13 ppm of Herbicide -.65000 .63738 .328 -2.0387 .7387

Group 4=0.20 ppm of Herbicide -1.95000* .63738 .010 -3.3387 -.5613

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 1.00000 .63738 .143 -.3887 2.3887

Group 3=0.13 ppm of Herbicide .35000 .63738 .593 -1.0387 1.7387

Group 4=0.20 ppm of Herbicide -.95000 .63738 .162 -2.3387 .4387

Group 3=0.13 ppm of Herbicide Group 1=Normal Control .65000 .63738 .328 -.7387 2.0387

132

Group 2=0.10 ppm of Herbicide -.35000 .63738 .593 -1.7387 1.0387

Group 4=0.20 ppm of Herbicide -1.30000 .63738 .064 -2.6887 .0887

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 1.95000* .63738 .010 .5613 3.3387

Group 2=0.10 ppm of Herbicide .95000 .63738 .162 -.4387 2.3387

Group 3=0.13 ppm of Herbicide 1.30000 .63738 .064 -.0887 2.6887

AST LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -15.00000 7.12756 .057 -30.5296 .5296

Group 3=0.13 ppm of Herbicide -27.50000* 7.12756 .002 -43.0296 -11.9704

Group 4=0.20 ppm of Herbicide -39.75000* 7.12756 .000 -55.2796 -24.2204

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 15.00000 7.12756 .057 -.5296 30.5296

Group 3=0.13 ppm of Herbicide -12.50000 7.12756 .105 -28.0296 3.0296

Group 4=0.20 ppm of Herbicide -24.75000* 7.12756 .005 -40.2796 -9.2204

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 27.50000* 7.12756 .002 11.9704 43.0296

Group 2=0.10 ppm of Herbicide 12.50000 7.12756 .105 -3.0296 28.0296

Group 4=0.20 ppm of Herbicide -12.25000 7.12756 .111 -27.7796 3.2796

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 39.75000* 7.12756 .000 24.2204 55.2796

Group 2=0.10 ppm of Herbicide 24.75000* 7.12756 .005 9.2204 40.2796

Group 3=0.13 ppm of Herbicide 12.25000 7.12756 .111 -3.2796 27.7796

ALT LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -3.00000 4.07610 .476 -11.8811 5.8811

Group 3=0.13 ppm of Herbicide -6.50000 4.07610 .137 -15.3811 2.3811

Group 4=0.20 ppm of Herbicide 3.75000 4.07610 .376 -5.1311 12.6311

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 3.00000 4.07610 .476 -5.8811 11.8811

Group 3=0.13 ppm of Herbicide -3.50000 4.07610 .407 -12.3811 5.3811

Group 4=0.20 ppm of Herbicide 6.75000 4.07610 .124 -2.1311 15.6311

Group 3=0.13 ppm of Herbicide Group 1=Normal Control 6.50000 4.07610 .137 -2.3811 15.3811

133

Group 2=0.10 ppm of Herbicide 3.50000 4.07610 .407 -5.3811 12.3811

Group 4=0.20 ppm of Herbicide 10.25000* 4.07610 .027 1.3689 19.1311

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control -3.75000 4.07610 .376 -12.6311 5.1311

Group 2=0.10 ppm of Herbicide -6.75000 4.07610 .124 -15.6311 2.1311

Group 3=0.13 ppm of Herbicide -10.25000* 4.07610 .027 -19.1311 -1.3689

ALP LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide 8.00000 7.32149 .296 -7.9521 23.9521

Group 3=0.13 ppm of Herbicide 6.25000 7.32149 .410 -9.7021 22.2021

Group 4=0.20 ppm of Herbicide -2.25000 7.32149 .764 -18.2021 13.7021

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -8.00000 7.32149 .296 -23.9521 7.9521

Group 3=0.13 ppm of Herbicide -1.75000 7.32149 .815 -17.7021 14.2021

Group 4=0.20 ppm of Herbicide -10.25000 7.32149 .187 -26.2021 5.7021

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control -6.25000 7.32149 .410 -22.2021 9.7021

Group 2=0.10 ppm of Herbicide 1.75000 7.32149 .815 -14.2021 17.7021

Group 4=0.20 ppm of Herbicide -8.50000 7.32149 .268 -24.4521 7.4521

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 2.25000 7.32149 .764 -13.7021 18.2021

Group 2=0.10 ppm of Herbicide 10.25000 7.32149 .187 -5.7021 26.2021

Group 3=0.13 ppm of Herbicide 8.50000 7.32149 .268 -7.4521 24.4521

Cyt_P450 LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide .21624 .71667 .768 -1.3452 1.7777

Group 3=0.13 ppm of Herbicide 2.20270* .71667 .010 .6412 3.7642

Group 4=0.20 ppm of Herbicide 2.87154* .71667 .002 1.3100 4.4330

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -.21624 .71667 .768 -1.7777 1.3452

Group 3=0.13 ppm of Herbicide 1.98645* .71667 .017 .4250 3.5479

Group 4=0.20 ppm of Herbicide 2.65530* .71667 .003 1.0938 4.2168

Group 3=0.13 ppm of Herbicide Group 1=Normal Control -2.20270* .71667 .010 -3.7642 -.6412

134

Group 2=0.10 ppm of Herbicide -1.98645* .71667 .017 -3.5479 -.4250

Group 4=0.20 ppm of Herbicide .66884 .71667 .369 -.8926 2.2303

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control -2.87154* .71667 .002 -4.4330 -1.3100

Group 2=0.10 ppm of Herbicide -2.65530* .71667 .003 -4.2168 -1.0938

Group 3=0.13 ppm of Herbicide -.66884 .71667 .369 -2.2303 .8926

GST LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide .25000 .72280 .735 -1.3248 1.8248

Group 3=0.13 ppm of Herbicide 1.40000 .72280 .077 -.1748 2.9748

Group 4=0.20 ppm of Herbicide 2.16250* .72280 .011 .5877 3.7373

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -.25000 .72280 .735 -1.8248 1.3248

Group 3=0.13 ppm of Herbicide 1.15000 .72280 .138 -.4248 2.7248

Group 4=0.20 ppm of Herbicide 1.91250* .72280 .021 .3377 3.4873

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control -1.40000 .72280 .077 -2.9748 .1748

Group 2=0.10 ppm of Herbicide -1.15000 .72280 .138 -2.7248 .4248

Group 4=0.20 ppm of Herbicide .76250 .72280 .312 -.8123 2.3373

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control -2.16250* .72280 .011 -3.7373 -.5877

Group 2=0.10 ppm of Herbicide -1.91250* .72280 .021 -3.4873 -.3377

Group 3=0.13 ppm of Herbicide -.76250 .72280 .312 -2.3373 .8123

*. The mean difference is significant at the 0.05 level.

Oneway {Day 14}

Descriptives

135

N Mean Std.

Deviation

Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body Weight

Group 1=Normal Control 4 1.0750 .08660 .04330 .9372 1.2128 1.00 1.15

Group 2=0.10 ppm of Herbicide 4 1.0250 .12583 .06292 .8248 1.2252 .90 1.20

Group 3=0.13 ppm of Herbicide 4 1.0000 .14142 .07071 .7750 1.2250 .80 1.10

Group 4=0.20 ppm of Herbicide 4 1.2750 .08660 .04330 1.1372 1.4128 1.20 1.40

Total 16 1.0938 .15042 .03760 1.0136 1.1739 .80 1.40

Total Protein

Group 1=Normal Control 4 5.9500 .46547 .23274 5.2093 6.6907 5.30 6.40

Group 2=0.10 ppm of Herbicide 4 8.2000 .82057 .41028 6.8943 9.5057 7.40 9.30

Group 3=0.13 ppm of Herbicide 4 7.3000 .59442 .29721 6.3541 8.2459 6.60 8.00

Group 4=0.20 ppm of Herbicide 4 7.1750 .61305 .30653 6.1995 8.1505 6.40 7.80

Total 16 7.1563 1.00397 .25099 6.6213 7.6912 5.30 9.30

AST

Group 1=Normal Control 4 36.0000 5.47723 2.73861 27.2845 44.7155 30.00 42.00

Group 2=0.10 ppm of Herbicide 4 53.7500 11.32475 5.66238 35.7298 71.7702 44.00 70.00

Group 3=0.13 ppm of Herbicide 4 98.2500 12.99679 6.49840 77.5692 118.9308 87.00 115.00

Group 4=0.20 ppm of Herbicide 4 96.0000 11.91638 5.95819 77.0384 114.9616 86.00 113.00

Total 16 71.0000 29.40295 7.35074 55.3323 86.6677 30.00 115.00

ALT

Group 1=Normal Control 4 26.5000 3.69685 1.84842 20.6175 32.3825 21.00 29.00

Group 2=0.10 ppm of Herbicide 4 37.2500 13.69611 6.84805 15.4564 59.0436 21.00 54.00

Group 3=0.13 ppm of Herbicide 4 42.7500 6.94622 3.47311 31.6970 53.8030 37.00 51.00

Group 4=0.20 ppm of Herbicide 4 10.7500 1.70783 .85391 8.0325 13.4675 9.00 13.00

Total 16 29.3125 14.47167 3.61792 21.6011 37.0239 9.00 54.00

ALP Group 1=Normal Control 4 34.7500 5.43906 2.71953 26.0952 43.4048 29.00 42.00

136

Group 2=0.10 ppm of Herbicide 4 47.2500 10.99621 5.49811 29.7526 64.7474 34.00 60.00

Group 3=0.13 ppm of Herbicide 4 68.2500 23.20022 11.60011 31.3333 105.1667 47.00 93.00

Group 4=0.20 ppm of Herbicide 4 70.5000 12.55654 6.27827 50.5197 90.4803 60.00 88.00

Total 16 55.1875 20.13693 5.03423 44.4573 65.9177 29.00 93.00

Cyt_P450

Group 1=Normal Control 4 12.7217 1.07055 .53527 11.0182 14.4251 11.65 14.18

Group 2=0.10 ppm of Herbicide 4 12.1183 1.13545 .56773 10.3116 13.9251 10.52 13.08

Group 3=0.13 ppm of Herbicide 4 9.9936 .76236 .38118 8.7805 11.2067 9.39 11.07

Group 4=0.20 ppm of Herbicide 4 10.7244 .53077 .26539 9.8798 11.5690 10.06 11.36

Total 16 11.3895 1.38277 .34569 10.6527 12.1263 9.39 14.18

GST

Group 1=Normal Control 4 2.8250 .57373 .28687 1.9121 3.7379 2.10 3.50

Group 2=0.10 ppm of Herbicide 4 2.0250 .33040 .16520 1.4993 2.5507 1.70 2.40

Group 3=0.13 ppm of Herbicide 4 1.3750 .42720 .21360 .6952 2.0548 .80 1.70

Group 4=0.20 ppm of Herbicide 4 3.9500 1.10905 .55453 2.1852 5.7148 2.60 5.30

Total 16 2.5438 1.16388 .29097 1.9236 3.1639 .80 5.30

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .187 3 .062 4.902 .019

Within Groups .152 12 .013

Total .339 15

Total Protein

Between Groups 10.262 3 3.421 8.450 .003

Within Groups 4.858 12 .405

Total 15.119 15

137

AST

Between Groups 11560.500 3 3853.500 32.854 .000

Within Groups 1407.500 12 117.292

Total 12968.000 15

ALT

Between Groups 2384.188 3 794.729 12.594 .001

Within Groups 757.250 12 63.104

Total 3141.438 15

ALP

Between Groups 3543.188 3 1181.063 5.581 .012

Within Groups 2539.250 12 211.604

Total 6082.438 15

Cyt_P450

Between Groups 18.786 3 6.262 7.594 .004

Within Groups 9.895 12 .825

Total 28.681 15

GST

Between Groups 14.767 3 4.922 10.638 .001

Within Groups 5.552 12 .463

Total 20.319 15

Post Hoc Tests

Multiple Comparisons

Dependent Variable (I) Groups (J) Groups Mean Difference

(I-J)

Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

Body

Weight LSD Group 1=Normal Control

Group 2=0.10 ppm of Herbicide .05000 .07971 .542 -.1237 .2237

Group 3=0.13 ppm of Herbicide .07500 .07971 .365 -.0987 .2487

Group 4=0.20 ppm of Herbicide -.20000* .07971 .027 -.3737 -.0263

138

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -.05000 .07971 .542 -.2237 .1237

Group 3=0.13 ppm of Herbicide .02500 .07971 .759 -.1487 .1987

Group 4=0.20 ppm of Herbicide -.25000* .07971 .009 -.4237 -.0763

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control -.07500 .07971 .365 -.2487 .0987

Group 2=0.10 ppm of Herbicide -.02500 .07971 .759 -.1987 .1487

Group 4=0.20 ppm of Herbicide -.27500* .07971 .005 -.4487 -.1013

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control .20000* .07971 .027 .0263 .3737

Group 2=0.10 ppm of Herbicide .25000* .07971 .009 .0763 .4237

Group 3=0.13 ppm of Herbicide .27500* .07971 .005 .1013 .4487

Total

Protein LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -2.25000* .44988 .000 -3.2302 -1.2698

Group 3=0.13 ppm of Herbicide -1.35000* .44988 .011 -2.3302 -.3698

Group 4=0.20 ppm of Herbicide -1.22500* .44988 .019 -2.2052 -.2448

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 2.25000* .44988 .000 1.2698 3.2302

Group 3=0.13 ppm of Herbicide .90000 .44988 .069 -.0802 1.8802

Group 4=0.20 ppm of Herbicide 1.02500* .44988 .042 .0448 2.0052

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 1.35000* .44988 .011 .3698 2.3302

Group 2=0.10 ppm of Herbicide -.90000 .44988 .069 -1.8802 .0802

Group 4=0.20 ppm of Herbicide .12500 .44988 .786 -.8552 1.1052

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 1.22500* .44988 .019 .2448 2.2052

Group 2=0.10 ppm of Herbicide -1.02500* .44988 .042 -2.0052 -.0448

Group 3=0.13 ppm of Herbicide -.12500 .44988 .786 -1.1052 .8552

AST LSD Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -17.75000* 7.65806 .039 -34.4355 -1.0645

Group 3=0.13 ppm of Herbicide -62.25000* 7.65806 .000 -78.9355 -45.5645

139

Group 4=0.20 ppm of Herbicide -60.00000* 7.65806 .000 -76.6855 -43.3145

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 17.75000* 7.65806 .039 1.0645 34.4355

Group 3=0.13 ppm of Herbicide -44.50000* 7.65806 .000 -61.1855 -27.8145

Group 4=0.20 ppm of Herbicide -42.25000* 7.65806 .000 -58.9355 -25.5645

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 62.25000* 7.65806 .000 45.5645 78.9355

Group 2=0.10 ppm of Herbicide 44.50000* 7.65806 .000 27.8145 61.1855

Group 4=0.20 ppm of Herbicide 2.25000 7.65806 .774 -14.4355 18.9355

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 60.00000* 7.65806 .000 43.3145 76.6855

Group 2=0.10 ppm of Herbicide 42.25000* 7.65806 .000 25.5645 58.9355

Group 3=0.13 ppm of Herbicide -2.25000 7.65806 .774 -18.9355 14.4355

ALT LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -10.75000 5.61712 .080 -22.9887 1.4887

Group 3=0.13 ppm of Herbicide -16.25000* 5.61712 .014 -28.4887 -4.0113

Group 4=0.20 ppm of Herbicide 15.75000* 5.61712 .016 3.5113 27.9887

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 10.75000 5.61712 .080 -1.4887 22.9887

Group 3=0.13 ppm of Herbicide -5.50000 5.61712 .347 -17.7387 6.7387

Group 4=0.20 ppm of Herbicide 26.50000* 5.61712 .000 14.2613 38.7387

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 16.25000* 5.61712 .014 4.0113 28.4887

Group 2=0.10 ppm of Herbicide 5.50000 5.61712 .347 -6.7387 17.7387

Group 4=0.20 ppm of Herbicide 32.00000* 5.61712 .000 19.7613 44.2387

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control -15.75000* 5.61712 .016 -27.9887 -3.5113

Group 2=0.10 ppm of Herbicide -26.50000* 5.61712 .000 -38.7387 -14.2613

Group 3=0.13 ppm of Herbicide -32.00000* 5.61712 .000 -44.2387 -19.7613

ALP LSD Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -12.50000 10.28601 .248 -34.9113 9.9113

Group 3=0.13 ppm of Herbicide -33.50000* 10.28601 .007 -55.9113 -11.0887

140

Group 4=0.20 ppm of Herbicide -35.75000* 10.28601 .005 -58.1613 -13.3387

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 12.50000 10.28601 .248 -9.9113 34.9113

Group 3=0.13 ppm of Herbicide -21.00000 10.28601 .064 -43.4113 1.4113

Group 4=0.20 ppm of Herbicide -23.25000* 10.28601 .043 -45.6613 -.8387

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 33.50000* 10.28601 .007 11.0887 55.9113

Group 2=0.10 ppm of Herbicide 21.00000 10.28601 .064 -1.4113 43.4113

Group 4=0.20 ppm of Herbicide -2.25000 10.28601 .831 -24.6613 20.1613

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 35.75000* 10.28601 .005 13.3387 58.1613

Group 2=0.10 ppm of Herbicide 23.25000* 10.28601 .043 .8387 45.6613

Group 3=0.13 ppm of Herbicide 2.25000 10.28601 .831 -20.1613 24.6613

Cyt_P450 LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide .60334 .64209 .366 -.7957 2.0023

Group 3=0.13 ppm of Herbicide 2.72801* .64209 .001 1.3290 4.1270

Group 4=0.20 ppm of Herbicide 1.99724* .64209 .009 .5982 3.3962

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -.60334 .64209 .366 -2.0023 .7957

Group 3=0.13 ppm of Herbicide 2.12467* .64209 .006 .7257 3.5237

Group 4=0.20 ppm of Herbicide 1.39390 .64209 .051 -.0051 2.7929

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control -2.72801* .64209 .001 -4.1270 -1.3290

Group 2=0.10 ppm of Herbicide -2.12467* .64209 .006 -3.5237 -.7257

Group 4=0.20 ppm of Herbicide -.73078 .64209 .277 -2.1298 .6682

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control -1.99724* .64209 .009 -3.3962 -.5982

Group 2=0.10 ppm of Herbicide -1.39390 .64209 .051 -2.7929 .0051

Group 3=0.13 ppm of Herbicide .73078 .64209 .277 -.6682 2.1298

GST LSD Group 1=Normal Control

Group 2=0.10 ppm of Herbicide .80000 .48099 .122 -.2480 1.8480

Group 3=0.13 ppm of Herbicide 1.45000* .48099 .011 .4020 2.4980

141

Group 4=0.20 ppm of Herbicide -1.12500* .48099 .037 -2.1730 -.0770

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -.80000 .48099 .122 -1.8480 .2480

Group 3=0.13 ppm of Herbicide .65000 .48099 .202 -.3980 1.6980

Group 4=0.20 ppm of Herbicide -1.92500* .48099 .002 -2.9730 -.8770

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control -1.45000* .48099 .011 -2.4980 -.4020

Group 2=0.10 ppm of Herbicide -.65000 .48099 .202 -1.6980 .3980

Group 4=0.20 ppm of Herbicide -2.57500* .48099 .000 -3.6230 -1.5270

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 1.12500* .48099 .037 .0770 2.1730

Group 2=0.10 ppm of Herbicide 1.92500* .48099 .002 .8770 2.9730

Group 3=0.13 ppm of Herbicide 2.57500* .48099 .000 1.5270 3.6230

*. The mean difference is significant at the 0.05 level.

Oneway {Day 3}

Descriptives

N Mean Std.

Deviation

Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body

Weight

Group 1=Normal Control 4 1.2625 .04787 .02394 1.1863 1.3387 1.20 1.30

Group 2=0.10 ppm of Herbicide 4 1.4375 .50229 .25114 .6383 2.2367 .70 1.80

142

Group 3=0.13 ppm of Herbicide 4 1.3500 .37859 .18930 .7476 1.9524 1.10 1.90

Group 4=0.20 ppm of Herbicide 4 1.5625 .34970 .17485 1.0060 2.1190 1.10 1.95

Total 16 1.4031 .34228 .08557 1.2207 1.5855 .70 1.95

Total

Protein

Group 1=Normal Control 4 16.2750 1.42916 .71458 14.0009 18.5491 15.30 18.40

Group 2=0.10 ppm of Herbicide 4 14.5250 1.73662 .86831 11.7617 17.2883 12.10 16.20

Group 3=0.13 ppm of Herbicide 4 15.6250 .99121 .49561 14.0478 17.2022 14.50 16.90

Group 4=0.20 ppm of Herbicide 4 16.2500 .84261 .42131 14.9092 17.5908 15.30 17.10

Total 16 15.6688 1.37391 .34348 14.9366 16.4009 12.10 18.40

AST

Group 1=Normal Control 4 35.0000 14.23610 7.11805 12.3472 57.6528 23.00 55.00

Group 2=0.10 ppm of Herbicide 4 98.0000 16.87207 8.43603 71.1528 124.8472 80.00 118.00

Group 3=0.13 ppm of Herbicide 4 128.5000 38.31014 19.15507 67.5400 189.4600 80.00 168.00

Group 4=0.20 ppm of Herbicide 4 132.5000 13.86843 6.93421 110.4322 154.5678 114.00 145.00

Total 16 98.5000 45.31078 11.32769 74.3556 122.6444 23.00 168.00

ALT

Group 1=Normal Control 4 24.0000 6.37704 3.18852 13.8527 34.1473 19.00 33.00

Group 2=0.10 ppm of Herbicide 4 31.2500 12.17580 6.08790 11.8756 50.6244 15.00 42.00

Group 3=0.13 ppm of Herbicide 4 36.5000 5.56776 2.78388 27.6404 45.3596 29.00 42.00

Group 4=0.20 ppm of Herbicide 4 26.7500 3.77492 1.88746 20.7433 32.7567 22.00 31.00

Total 16 29.6250 8.41328 2.10332 25.1419 34.1081 15.00 42.00

ALP

Group 1=Normal Control 4 44.0000 12.98717 6.49359 23.3345 64.6655 30.00 59.00

Group 2=0.10 ppm of Herbicide 4 28.7500 2.50000 1.25000 24.7719 32.7281 26.00 32.00

Group 3=0.13 ppm of Herbicide 4 58.2500 7.27438 3.63719 46.6748 69.8252 53.00 69.00

Group 4=0.20 ppm of Herbicide 4 61.0000 8.75595 4.37798 47.0673 74.9327 54.00 73.00

Total 16 48.0000 15.39697 3.84924 39.7955 56.2045 26.00 73.00

Cyt_P450 Group 1=Normal Control 4 11.7968 .38566 .19283 11.1832 12.4105 11.34 12.28

143

Group 2=0.10 ppm of Herbicide 4 12.2994 .80859 .40430 11.0127 13.5860 11.16 12.93

Group 3=0.13 ppm of Herbicide 4 14.4094 1.68959 .84480 11.7208 17.0979 12.23 16.35

Group 4=0.20 ppm of Herbicide 4 16.1634 2.58632 1.29316 12.0480 20.2788 13.02 19.35

Total 16 13.6672 2.30425 .57606 12.4394 14.8951 11.16 19.35

GST

Group 1=Normal Control 4 2.3250 .78049 .39025 1.0831 3.5669 1.60 3.30

Group 2=0.10 ppm of Herbicide 4 5.4500 .86987 .43493 4.0658 6.8342 4.20 6.20

Group 3=0.13 ppm of Herbicide 4 6.7500 2.82902 1.41451 2.2484 11.2516 3.70 9.40

Group 4=0.20 ppm of Herbicide 4 8.1000 1.25698 .62849 6.0999 10.1001 7.00 9.90

Total 16 5.6563 2.65932 .66483 4.2392 7.0733 1.60 9.90

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .197 3 .066 .504 .687

Within Groups 1.561 12 .130

Total 1.757 15

Total Protein

Between Groups 8.062 3 2.687 1.592 .243

Within Groups 20.252 12 1.688

Total 28.314 15

AST

Between Groups 24354.000 3 8118.000 15.122 .000

Within Groups 6442.000 12 536.833

Total 30796.000 15

ALT Between Groups 359.250 3 119.750 2.046 .161

Within Groups 702.500 12 58.542

144

Total 1061.750 15

ALP

Between Groups 2642.500 3 880.833 11.571 .001

Within Groups 913.500 12 76.125

Total 3556.000 15

Cyt_P450

Between Groups 48.605 3 16.202 6.264 .008

Within Groups 31.039 12 2.587

Total 79.643 15

GST

Between Groups 73.232 3 24.411 8.918 .002

Within Groups 32.848 12 2.737

Total 106.079 15

Post Hoc Tests

Multiple Comparisons

Dependent Variable (I) Groups (J) Groups Mean

Difference (I-J)

Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

Body

Weight LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -.17500 .25500 .506 -.7306 .3806

Group 3=0.13 ppm of Herbicide -.08750 .25500 .737 -.6431 .4681

Group 4=0.20 ppm of Herbicide -.30000 .25500 .262 -.8556 .2556

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control .17500 .25500 .506 -.3806 .7306

Group 3=0.13 ppm of Herbicide .08750 .25500 .737 -.4681 .6431

Group 4=0.20 ppm of Herbicide -.12500 .25500 .633 -.6806 .4306

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control .08750 .25500 .737 -.4681 .6431

Group 2=0.10 ppm of Herbicide -.08750 .25500 .737 -.6431 .4681

145

Group 4=0.20 ppm of Herbicide -.21250 .25500 .421 -.7681 .3431

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control .30000 .25500 .262 -.2556 .8556

Group 2=0.10 ppm of Herbicide .12500 .25500 .633 -.4306 .6806

Group 3=0.13 ppm of Herbicide .21250 .25500 .421 -.3431 .7681

Total

Protein LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide 1.75000 .91862 .081 -.2515 3.7515

Group 3=0.13 ppm of Herbicide .65000 .91862 .493 -1.3515 2.6515

Group 4=0.20 ppm of Herbicide .02500 .91862 .979 -1.9765 2.0265

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -1.75000 .91862 .081 -3.7515 .2515

Group 3=0.13 ppm of Herbicide -1.10000 .91862 .254 -3.1015 .9015

Group 4=0.20 ppm of Herbicide -1.72500 .91862 .085 -3.7265 .2765

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control -.65000 .91862 .493 -2.6515 1.3515

Group 2=0.10 ppm of Herbicide 1.10000 .91862 .254 -.9015 3.1015

Group 4=0.20 ppm of Herbicide -.62500 .91862 .509 -2.6265 1.3765

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control -.02500 .91862 .979 -2.0265 1.9765

Group 2=0.10 ppm of Herbicide 1.72500 .91862 .085 -.2765 3.7265

Group 3=0.13 ppm of Herbicide .62500 .91862 .509 -1.3765 2.6265

AST LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -63.00000* 16.38343 .002 -98.6964 -27.3036

Group 3=0.13 ppm of Herbicide -93.50000* 16.38343 .000 -129.1964 -57.8036

Group 4=0.20 ppm of Herbicide -97.50000* 16.38343 .000 -133.1964 -61.8036

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 63.00000* 16.38343 .002 27.3036 98.6964

Group 3=0.13 ppm of Herbicide -30.50000 16.38343 .087 -66.1964 5.1964

Group 4=0.20 ppm of Herbicide -34.50000 16.38343 .057 -70.1964 1.1964

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 93.50000* 16.38343 .000 57.8036 129.1964

Group 2=0.10 ppm of Herbicide 30.50000 16.38343 .087 -5.1964 66.1964

146

Group 4=0.20 ppm of Herbicide -4.00000 16.38343 .811 -39.6964 31.6964

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 97.50000* 16.38343 .000 61.8036 133.1964

Group 2=0.10 ppm of Herbicide 34.50000 16.38343 .057 -1.1964 70.1964

Group 3=0.13 ppm of Herbicide 4.00000 16.38343 .811 -31.6964 39.6964

ALT LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -7.25000 5.41025 .205 -19.0379 4.5379

Group 3=0.13 ppm of Herbicide -12.50000* 5.41025 .039 -24.2879 -.7121

Group 4=0.20 ppm of Herbicide -2.75000 5.41025 .620 -14.5379 9.0379

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 7.25000 5.41025 .205 -4.5379 19.0379

Group 3=0.13 ppm of Herbicide -5.25000 5.41025 .351 -17.0379 6.5379

Group 4=0.20 ppm of Herbicide 4.50000 5.41025 .422 -7.2879 16.2879

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 12.50000* 5.41025 .039 .7121 24.2879

Group 2=0.10 ppm of Herbicide 5.25000 5.41025 .351 -6.5379 17.0379

Group 4=0.20 ppm of Herbicide 9.75000 5.41025 .097 -2.0379 21.5379

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 2.75000 5.41025 .620 -9.0379 14.5379

Group 2=0.10 ppm of Herbicide -4.50000 5.41025 .422 -16.2879 7.2879

Group 3=0.13 ppm of Herbicide -9.75000 5.41025 .097 -21.5379 2.0379

ALP LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide 15.25000* 6.16948 .029 1.8079 28.6921

Group 3=0.13 ppm of Herbicide -14.25000* 6.16948 .039 -27.6921 -.8079

Group 4=0.20 ppm of Herbicide -17.00000* 6.16948 .017 -30.4421 -3.5579

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control -15.25000* 6.16948 .029 -28.6921 -1.8079

Group 3=0.13 ppm of Herbicide -29.50000* 6.16948 .000 -42.9421 -16.0579

Group 4=0.20 ppm of Herbicide -32.25000* 6.16948 .000 -45.6921 -18.8079

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 14.25000* 6.16948 .039 .8079 27.6921

Group 2=0.10 ppm of Herbicide 29.50000* 6.16948 .000 16.0579 42.9421

147

Group 4=0.20 ppm of Herbicide -2.75000 6.16948 .664 -16.1921 10.6921

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 17.00000* 6.16948 .017 3.5579 30.4421

Group 2=0.10 ppm of Herbicide 32.25000* 6.16948 .000 18.8079 45.6921

Group 3=0.13 ppm of Herbicide 2.75000 6.16948 .664 -10.6921 16.1921

Cyt_P450 LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -.50252 1.13723 .666 -2.9803 1.9753

Group 3=0.13 ppm of Herbicide -2.61252* 1.13723 .040 -5.0903 -.1347

Group 4=0.20 ppm of Herbicide -4.36658* 1.13723 .002 -6.8444 -1.8888

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control .50252 1.13723 .666 -1.9753 2.9803

Group 3=0.13 ppm of Herbicide -2.11000 1.13723 .088 -4.5878 .3678

Group 4=0.20 ppm of Herbicide -3.86406* 1.13723 .005 -6.3419 -1.3862

Group 3=0.13 ppm of Herbicide

Group 1=Normal Control 2.61252* 1.13723 .040 .1347 5.0903

Group 2=0.10 ppm of Herbicide 2.11000 1.13723 .088 -.3678 4.5878

Group 4=0.20 ppm of Herbicide -1.75406 1.13723 .149 -4.2319 .7238

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 4.36658* 1.13723 .002 1.8888 6.8444

Group 2=0.10 ppm of Herbicide 3.86406* 1.13723 .005 1.3862 6.3419

Group 3=0.13 ppm of Herbicide 1.75406 1.13723 .149 -.7238 4.2319

GST LSD

Group 1=Normal Control

Group 2=0.10 ppm of Herbicide -3.12500* 1.16989 .020 -5.6740 -.5760

Group 3=0.13 ppm of Herbicide -4.42500* 1.16989 .003 -6.9740 -1.8760

Group 4=0.20 ppm of Herbicide -5.77500* 1.16989 .000 -8.3240 -3.2260

Group 2=0.10 ppm of Herbicide

Group 1=Normal Control 3.12500* 1.16989 .020 .5760 5.6740

Group 3=0.13 ppm of Herbicide -1.30000 1.16989 .288 -3.8490 1.2490

Group 4=0.20 ppm of Herbicide -2.65000* 1.16989 .043 -5.1990 -.1010

Group 3=0.13 ppm of Herbicide Group 1=Normal Control 4.42500* 1.16989 .003 1.8760 6.9740

148

Group 2=0.10 ppm of Herbicide 1.30000 1.16989 .288 -1.2490 3.8490

Group 4=0.20 ppm of Herbicide -1.35000 1.16989 .271 -3.8990 1.1990

Group 4=0.20 ppm of Herbicide

Group 1=Normal Control 5.77500* 1.16989 .000 3.2260 8.3240

Group 2=0.10 ppm of Herbicide 2.65000* 1.16989 .043 .1010 5.1990

Group 3=0.13 ppm of Herbicide 1.35000 1.16989 .271 -1.1990 3.8990

*. The mean difference is significant at the 0.05 level.

Oneway {Group 1 = Normal Control}

Descriptives

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body Weight

Day 1 4 1.2750 .09574 .04787 1.1227 1.4273 1.20 1.40

Day 14 4 1.0750 .08660 .04330 .9372 1.2128 1.00 1.15

Day 28 4 1.2625 .04787 .02394 1.1863 1.3387 1.20 1.30

Total 12 1.2042 .11958 .03452 1.1282 1.2801 1.00 1.40

Total Protein

Day 1 4 7.9250 .51235 .25617 7.1097 8.7403 7.40 8.60

Day 14 4 5.9500 .46547 .23274 5.2093 6.6907 5.30 6.40

Day 28 4 16.2750 1.42916 .71458 14.0009 18.5491 15.30 18.40

Total 12 10.0500 4.74696 1.37033 7.0339 13.0661 5.30 18.40

AST

Day 1 4 36.7500 4.03113 2.01556 30.3356 43.1644 32.00 41.00

Day 14 4 36.0000 5.47723 2.73861 27.2845 44.7155 30.00 42.00

Day 28 4 35.0000 14.23610 7.11805 12.3472 57.6528 23.00 55.00

149

Total 12 35.9167 8.27327 2.38829 30.6601 41.1733 23.00 55.00

ALT

Day 1 4 24.5000 4.50925 2.25462 17.3248 31.6752 21.00 31.00

Day 14 4 26.5000 3.69685 1.84842 20.6175 32.3825 21.00 29.00

Day 28 4 24.0000 6.37704 3.18852 13.8527 34.1473 19.00 33.00

Total 12 25.0000 4.65149 1.34277 22.0446 27.9554 19.00 33.00

ALP

Day 1 4 40.2500 11.11680 5.55840 22.5607 57.9393 25.00 51.00

Day 14 4 34.7500 5.43906 2.71953 26.0952 43.4048 29.00 42.00

Day 28 4 44.0000 12.98717 6.49359 23.3345 64.6655 30.00 59.00

Total 12 39.6667 10.17424 2.93705 33.2023 46.1311 25.00 59.00

Cyt_P450

Day 1 4 10.9768 1.73524 .86762 8.2156 13.7379 8.57 12.61

Day 14 4 12.7217 1.07055 .53527 11.0182 14.4251 11.65 14.18

Day 28 4 11.7968 .38566 .19283 11.1832 12.4105 11.34 12.28

Total 12 11.8317 1.31475 .37954 10.9964 12.6671 8.57 14.18

GST

Day 1 4 2.4250 1.49750 .74875 .0421 4.8079 .80 4.10

Day 14 4 2.8250 .57373 .28687 1.9121 3.7379 2.10 3.50

Day 28 4 2.3250 .78049 .39025 1.0831 3.5669 1.60 3.30

Total 12 2.5250 .95834 .27665 1.9161 3.1339 .80 4.10

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .100 2 .050 7.945 .010

Within Groups .057 9 .006

Total .157 11

150

Total Protein

Between Groups 240.305 2 120.152 142.944 .000

Within Groups 7.565 9 .841

Total 247.870 11

AST

Between Groups 6.167 2 3.083 .037 .964

Within Groups 746.750 9 82.972

Total 752.917 11

ALT

Between Groups 14.000 2 7.000 .281 .761

Within Groups 224.000 9 24.889

Total 238.000 11

ALP

Between Groups 173.167 2 86.583 .807 .476

Within Groups 965.500 9 107.278

Total 1138.667 11

Cyt_P450

Between Groups 6.097 2 3.048 2.124 .176

Within Groups 12.918 9 1.435

Total 19.014 11

GST

Between Groups .560 2 .280 .264 .774

Within Groups 9.542 9 1.060

Total 10.102 11

Post Hoc Tests

Multiple Comparisons

Dependent Variable (I) Days (J) Days Mean

Difference (I-J)

Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

151

Body Weight LSD

Day 1 Day 14 .20000* .05621 .006 .0728 .3272

Day 28 .01250 .05621 .829 -.1147 .1397

Day 14 Day 1 -.20000* .05621 .006 -.3272 -.0728

Day 28 -.18750* .05621 .009 -.3147 -.0603

Day 28 Day 1 -.01250 .05621 .829 -.1397 .1147

Day 14 .18750* .05621 .009 .0603 .3147

Total Protein LSD

Day 1 Day 14 1.97500* .64829 .014 .5085 3.4415

Day 28 -8.35000* .64829 .000 -9.8165 -6.8835

Day 14 Day 1 -1.97500* .64829 .014 -3.4415 -.5085

Day 28 -10.32500* .64829 .000 -11.7915 -8.8585

Day 28 Day 1 8.35000* .64829 .000 6.8835 9.8165

Day 14 10.32500* .64829 .000 8.8585 11.7915

AST LSD

Day 1 Day 14 .75000 6.44097 .910 -13.8205 15.3205

Day 28 1.75000 6.44097 .792 -12.8205 16.3205

Day 14 Day 1 -.75000 6.44097 .910 -15.3205 13.8205

Day 28 1.00000 6.44097 .880 -13.5705 15.5705

Day 28 Day 1 -1.75000 6.44097 .792 -16.3205 12.8205

Day 14 -1.00000 6.44097 .880 -15.5705 13.5705

ALT LSD

Day 1 Day 14 -2.00000 3.52767 .585 -9.9801 5.9801

Day 28 .50000 3.52767 .890 -7.4801 8.4801

Day 14 Day 1 2.00000 3.52767 .585 -5.9801 9.9801

Day 28 2.50000 3.52767 .496 -5.4801 10.4801

Day 28 Day 1 -.50000 3.52767 .890 -8.4801 7.4801

152

Day 14 -2.50000 3.52767 .496 -10.4801 5.4801

ALP LSD

Day 1 Day 14 5.50000 7.32386 .472 -11.0677 22.0677

Day 28 -3.75000 7.32386 .621 -20.3177 12.8177

Day 14 Day 1 -5.50000 7.32386 .472 -22.0677 11.0677

Day 28 -9.25000 7.32386 .238 -25.8177 7.3177

Day 28 Day 1 3.75000 7.32386 .621 -12.8177 20.3177

Day 14 9.25000 7.32386 .238 -7.3177 25.8177

Cyt_P450 LSD

Day 1 Day 14 -1.74490 .84714 .070 -3.6613 .1715

Day 28 -.82008 .84714 .358 -2.7364 1.0963

Day 14 Day 1 1.74490 .84714 .070 -.1715 3.6613

Day 28 .92481 .84714 .303 -.9915 2.8412

Day 28 Day 1 .82008 .84714 .358 -1.0963 2.7364

Day 14 -.92481 .84714 .303 -2.8412 .9915

GST LSD

Day 1 Day 14 -.40000 .72811 .596 -2.0471 1.2471

Day 28 .10000 .72811 .894 -1.5471 1.7471

Day 14 Day 1 .40000 .72811 .596 -1.2471 2.0471

Day 28 .50000 .72811 .510 -1.1471 2.1471

Day 28 Day 1 -.10000 .72811 .894 -1.7471 1.5471

Day 14 -.50000 .72811 .510 -2.1471 1.1471

*. The mean difference is significant at the 0.05 level.

153

Oneway {Group 2 = 0.10 ppm of Herbicide}

Descriptives

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body Weight

Day 1 4 1.3125 .24622 .12311 .9207 1.7043 1.10 1.55

Day 14 4 1.0250 .12583 .06292 .8248 1.2252 .90 1.20

Day 28 4 1.4375 .50229 .25114 .6383 2.2367 .70 1.80

Total 12 1.2583 .34957 .10091 1.0362 1.4804 .70 1.80

Total Protein

Day 1 4 8.9250 .29861 .14930 8.4498 9.4002 8.60 9.30

Day 14 4 8.2000 .82057 .41028 6.8943 9.5057 7.40 9.30

Day 28 4 14.5250 1.73662 .86831 11.7617 17.2883 12.10 16.20

Total 12 10.5500 3.12163 .90114 8.5666 12.5334 7.40 16.20

AST

Day 1 4 51.7500 7.80491 3.90246 39.3306 64.1694 42.00 61.00

Day 14 4 53.7500 11.32475 5.66238 35.7298 71.7702 44.00 70.00

Day 28 4 98.0000 16.87207 8.43603 71.1528 124.8472 80.00 118.00

Total 12 67.8333 25.02665 7.22457 51.9322 83.7345 42.00 118.00

ALT

Day 1 4 27.5000 5.25991 2.62996 19.1303 35.8697 22.00 32.00

Day 14 4 37.2500 13.69611 6.84805 15.4564 59.0436 21.00 54.00

Day 28 4 31.2500 12.17580 6.08790 11.8756 50.6244 15.00 42.00

Total 12 32.0000 10.80404 3.11886 25.1354 38.8646 15.00 54.00

ALP

Day 1 4 32.2500 7.13559 3.56780 20.8957 43.6043 24.00 41.00

Day 14 4 47.2500 10.99621 5.49811 29.7526 64.7474 34.00 60.00

Day 28 4 28.7500 2.50000 1.25000 24.7719 32.7281 26.00 32.00

154

Total 12 36.0833 10.90003 3.14657 29.1578 43.0089 24.00 60.00

Cyt_P450

Day 1 4 10.7605 .79543 .39771 9.4948 12.0262 9.90 11.82

Day 14 4 12.1183 1.13545 .56773 10.3116 13.9251 10.52 13.08

Day 28 4 12.2994 .80859 .40430 11.0127 13.5860 11.16 12.93

Total 12 11.7261 1.10316 .31846 11.0251 12.4270 9.90 13.08

GST

Day 1 4 2.1750 1.34009 .67004 .0426 4.3074 .70 3.50

Day 14 4 2.0250 .33040 .16520 1.4993 2.5507 1.70 2.40

Day 28 4 5.4500 .86987 .43493 4.0658 6.8342 4.20 6.20

Total 12 3.2167 1.85758 .53624 2.0364 4.3969 .70 6.20

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .358 2 .179 1.633 .248

Within Groups .986 9 .110

Total 1.344 11

Total Protein

Between Groups 95.855 2 47.928 38.054 .000

Within Groups 11.335 9 1.259

Total 107.190 11

AST

Between Groups 5468.167 2 2734.083 17.310 .001

Within Groups 1421.500 9 157.944

Total 6889.667 11

ALT Between Groups 193.500 2 96.750 .798 .479

Within Groups 1090.500 9 121.167

155

Total 1284.000 11

ALP

Between Groups 772.667 2 386.333 6.508 .018

Within Groups 534.250 9 59.361

Total 1306.917 11

Cyt_P450

Between Groups 5.659 2 2.830 3.296 .084

Within Groups 7.727 9 .859

Total 13.387 11

GST

Between Groups 29.972 2 14.986 16.891 .001

Within Groups 7.985 9 .887

Total 37.957 11

Post Hoc Tests

Multiple Comparisons

Dependent Variable (I) Days (J) Days Mean

Difference (I-J)

Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

Body Weight LSD

Day 1 Day 14 .28750 .23408 .251 -.2420 .8170

Day 28 -.12500 .23408 .606 -.6545 .4045

Day 14 Day 1 -.28750 .23408 .251 -.8170 .2420

Day 28 -.41250 .23408 .112 -.9420 .1170

Day 28 Day 1 .12500 .23408 .606 -.4045 .6545

Day 14 .41250 .23408 .112 -.1170 .9420

Total Protein LSD Day 1 Day 14 .72500 .79355 .385 -1.0701 2.5201

Day 28 -5.60000* .79355 .000 -7.3951 -3.8049

156

Day 14 Day 1 -.72500 .79355 .385 -2.5201 1.0701

Day 28 -6.32500* .79355 .000 -8.1201 -4.5299

Day 28 Day 1 5.60000* .79355 .000 3.8049 7.3951

Day 14 6.32500* .79355 .000 4.5299 8.1201

AST LSD

Day 1 Day 14 -2.00000 8.88663 .827 -22.1030 18.1030

Day 28 -46.25000* 8.88663 .001 -66.3530 -26.1470

Day 14 Day 1 2.00000 8.88663 .827 -18.1030 22.1030

Day 28 -44.25000* 8.88663 .001 -64.3530 -24.1470

Day 28 Day 1 46.25000* 8.88663 .001 26.1470 66.3530

Day 14 44.25000* 8.88663 .001 24.1470 64.3530

ALT LSD

Day 1 Day 14 -9.75000 7.78353 .242 -27.3576 7.8576

Day 28 -3.75000 7.78353 .641 -21.3576 13.8576

Day 14 Day 1 9.75000 7.78353 .242 -7.8576 27.3576

Day 28 6.00000 7.78353 .461 -11.6076 23.6076

Day 28 Day 1 3.75000 7.78353 .641 -13.8576 21.3576

Day 14 -6.00000 7.78353 .461 -23.6076 11.6076

ALP LSD

Day 1 Day 14 -15.00000* 5.44799 .022 -27.3242 -2.6758

Day 28 3.50000 5.44799 .537 -8.8242 15.8242

Day 14 Day 1 15.00000* 5.44799 .022 2.6758 27.3242

Day 28 18.50000* 5.44799 .008 6.1758 30.8242

Day 28 Day 1 -3.50000 5.44799 .537 -15.8242 8.8242

Day 14 -18.50000* 5.44799 .008 -30.8242 -6.1758

Cyt_P450 LSD Day 1 Day 14 -1.35780 .65521 .068 -2.8400 .1244

Day 28 -1.53885* .65521 .043 -3.0210 -.0567

157

Day 14 Day 1 1.35780 .65521 .068 -.1244 2.8400

Day 28 -.18105 .65521 .789 -1.6632 1.3011

Day 28 Day 1 1.53885* .65521 .043 .0567 3.0210

Day 14 .18105 .65521 .789 -1.3011 1.6632

GST LSD

Day 1 Day 14 .15000 .66604 .827 -1.3567 1.6567

Day 28 -3.27500* .66604 .001 -4.7817 -1.7683

Day 14 Day 1 -.15000 .66604 .827 -1.6567 1.3567

Day 28 -3.42500* .66604 .001 -4.9317 -1.9183

Day 28 Day 1 3.27500* .66604 .001 1.7683 4.7817

Day 14 3.42500* .66604 .001 1.9183 4.9317

*. The mean difference is significant at the 0.05 level.

Oneway {Group 3 = 0.13 ppm of Herbicide}

Descriptives

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body Weight

Day 1 4 1.4375 .17017 .08509 1.1667 1.7083 1.20 1.60

Day 14 4 1.0000 .14142 .07071 .7750 1.2250 .80 1.10

Day 28 4 1.3500 .37859 .18930 .7476 1.9524 1.10 1.90

Total 12 1.2625 .30236 .08728 1.0704 1.4546 .80 1.90

Total Protein Day 1 4 8.5750 1.20934 .60467 6.6507 10.4993 7.50 9.90

158

Day 14 4 7.3000 .59442 .29721 6.3541 8.2459 6.60 8.00

Day 28 4 15.6250 .99121 .49561 14.0478 17.2022 14.50 16.90

Total 12 10.5000 3.92243 1.13231 8.0078 12.9922 6.60 16.90

AST

Day 1 4 64.2500 15.34872 7.67436 39.8268 88.6732 48.00 81.00

Day 14 4 98.2500 12.99679 6.49840 77.5692 118.9308 87.00 115.00

Day 28 4 128.5000 38.31014 19.15507 67.5400 189.4600 80.00 168.00

Total 12 97.0000 35.52464 10.25508 74.4287 119.5713 48.00 168.00

ALT

Day 1 4 31.0000 6.05530 3.02765 21.3647 40.6353 22.00 35.00

Day 14 4 42.7500 6.94622 3.47311 31.6970 53.8030 37.00 51.00

Day 28 4 36.5000 5.56776 2.78388 27.6404 45.3596 29.00 42.00

Total 12 36.7500 7.53326 2.17466 31.9636 41.5364 22.00 51.00

ALP

Day 1 4 34.0000 9.48683 4.74342 18.9043 49.0957 22.00 43.00

Day 14 4 68.2500 23.20022 11.60011 31.3333 105.1667 47.00 93.00

Day 28 4 58.2500 7.27438 3.63719 46.6748 69.8252 53.00 69.00

Total 12 53.5000 20.28210 5.85494 40.6134 66.3866 22.00 93.00

Cyt_P450

Day 1 4 8.7741 .46249 .23125 8.0381 9.5100 8.12 9.14

Day 14 4 9.9936 .76236 .38118 8.7805 11.2067 9.39 11.07

Day 28 4 14.4094 1.68959 .84480 11.7208 17.0979 12.23 16.35

Total 12 11.0590 2.71817 .78467 9.3320 12.7861 8.12 16.35

GST

Day 1 4 1.0250 .29861 .14930 .5498 1.5002 .70 1.40

Day 14 4 1.3750 .42720 .21360 .6952 2.0548 .80 1.70

Day 28 4 6.7500 2.82902 1.41451 2.2484 11.2516 3.70 9.40

Total 12 3.0500 3.12192 .90122 1.0664 5.0336 .70 9.40

159

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .429 2 .214 3.345 .082

Within Groups .577 9 .064

Total 1.006 11

Total Protein

Between Groups 160.845 2 80.423 86.218 .000

Within Groups 8.395 9 .933

Total 169.240 11

AST

Between Groups 8265.500 2 4132.750 6.622 .017

Within Groups 5616.500 9 624.056

Total 13882.000 11

ALT

Between Groups 276.500 2 138.250 3.578 .072

Within Groups 347.750 9 38.639

Total 624.250 11

ALP

Between Groups 2481.500 2 1240.750 5.465 .028

Within Groups 2043.500 9 227.056

Total 4525.000 11

Cyt_P450

Between Groups 70.324 2 35.162 28.901 .000

Within Groups 10.949 9 1.217

Total 81.273 11

GST Between Groups 82.385 2 41.193 14.934 .001

Within Groups 24.825 9 2.758

160

Total 107.210 11

Post Hoc Tests

Multiple Comparisons

Dependent Variable (I) Days (J) Days Mean

Difference (I-J)

Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

Body Weight LSD

Day 1 Day 14 .43750* .17902 .037 .0325 .8425

Day 28 .08750 .17902 .637 -.3175 .4925

Day 14 Day 1 -.43750* .17902 .037 -.8425 -.0325

Day 28 -.35000 .17902 .082 -.7550 .0550

Day 28 Day 1 -.08750 .17902 .637 -.4925 .3175

Day 14 .35000 .17902 .082 -.0550 .7550

Total Protein LSD

Day 1 Day 14 1.27500 .68293 .095 -.2699 2.8199

Day 28 -7.05000* .68293 .000 -8.5949 -5.5051

Day 14 Day 1 -1.27500 .68293 .095 -2.8199 .2699

Day 28 -8.32500* .68293 .000 -9.8699 -6.7801

Day 28 Day 1 7.05000* .68293 .000 5.5051 8.5949

Day 14 8.32500* .68293 .000 6.7801 9.8699

AST LSD

Day 1 Day 14 -34.00000 17.66431 .086 -73.9594 5.9594

Day 28 -64.25000* 17.66431 .005 -104.2094 -24.2906

Day 14 Day 1 34.00000 17.66431 .086 -5.9594 73.9594

Day 28 -30.25000 17.66431 .121 -70.2094 9.7094

161

Day 28 Day 1 64.25000* 17.66431 .005 24.2906 104.2094

Day 14 30.25000 17.66431 .121 -9.7094 70.2094

ALT LSD

Day 1 Day 14 -11.75000* 4.39539 .025 -21.6931 -1.8069

Day 28 -5.50000 4.39539 .242 -15.4431 4.4431

Day 14 Day 1 11.75000* 4.39539 .025 1.8069 21.6931

Day 28 6.25000 4.39539 .189 -3.6931 16.1931

Day 28 Day 1 5.50000 4.39539 .242 -4.4431 15.4431

Day 14 -6.25000 4.39539 .189 -16.1931 3.6931

ALP LSD

Day 1 Day 14 -34.25000* 10.65494 .011 -58.3532 -10.1468

Day 28 -24.25000* 10.65494 .049 -48.3532 -.1468

Day 14 Day 1 34.25000* 10.65494 .011 10.1468 58.3532

Day 28 10.00000 10.65494 .372 -14.1032 34.1032

Day 28 Day 1 24.25000* 10.65494 .049 .1468 48.3532

Day 14 -10.00000 10.65494 .372 -34.1032 14.1032

Cyt_P450 LSD

Day 1 Day 14 -1.21958 .77994 .152 -2.9839 .5448

Day 28 -5.63531* .77994 .000 -7.3997 -3.8710

Day 14 Day 1 1.21958 .77994 .152 -.5448 2.9839

Day 28 -4.41572* .77994 .000 -6.1801 -2.6514

Day 28 Day 1 5.63531* .77994 .000 3.8710 7.3997

Day 14 4.41572* .77994 .000 2.6514 6.1801

GST LSD

Day 1 Day 14 -.35000 1.17438 .772 -3.0066 2.3066

Day 28 -5.72500* 1.17438 .001 -8.3816 -3.0684

Day 14 Day 1 .35000 1.17438 .772 -2.3066 3.0066

Day 28 -5.37500* 1.17438 .001 -8.0316 -2.7184

162

Day 28 Day 1 5.72500* 1.17438 .001 3.0684 8.3816

Day 14 5.37500* 1.17438 .001 2.7184 8.0316

*. The mean difference is significant at the 0.05 level.

Oneway {Group 4 = 0.20 pp of Herbicide}

Descriptives

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Body Weight

Day 1 4 1.4000 .24833 .12416 1.0049 1.7951 1.10 1.70

Day 14 4 1.2750 .08660 .04330 1.1372 1.4128 1.20 1.40

Day 28 4 1.5625 .34970 .17485 1.0060 2.1190 1.10 1.95

Total 12 1.4125 .25948 .07491 1.2476 1.5774 1.10 1.95

Total Protein

Day 1 4 9.8750 1.19826 .59913 7.9683 11.7817 8.10 10.60

Day 14 4 7.1750 .61305 .30653 6.1995 8.1505 6.40 7.80

Day 28 4 16.2500 .84261 .42131 14.9092 17.5908 15.30 17.10

Total 12 11.1000 4.05956 1.17189 8.5207 13.6793 6.40 17.10

AST

Day 1 4 76.5000 9.67815 4.83908 61.0999 91.9001 69.00 90.00

Day 14 4 96.0000 11.91638 5.95819 77.0384 114.9616 86.00 113.00

Day 28 4 132.5000 13.86843 6.93421 110.4322 154.5678 114.00 145.00

Total 12 101.6667 26.54099 7.66172 84.8033 118.5300 69.00 145.00

ALT Day 1 4 20.7500 6.94622 3.47311 9.6970 31.8030 15.00 29.00

163

Day 14 4 10.7500 1.70783 .85391 8.0325 13.4675 9.00 13.00

Day 28 4 26.7500 3.77492 1.88746 20.7433 32.7567 22.00 31.00

Total 12 19.4167 8.08431 2.33374 14.2801 24.5532 9.00 31.00

ALP

Day 1 4 42.5000 12.81926 6.40963 22.1017 62.8983 30.00 60.00

Day 14 4 70.5000 12.55654 6.27827 50.5197 90.4803 60.00 88.00

Day 28 4 61.0000 8.75595 4.37798 47.0673 74.9327 54.00 73.00

Total 12 58.0000 16.00568 4.62044 47.8305 68.1695 30.00 88.00

Cyt_P450

Day 1 4 8.1052 .50128 .25064 7.3076 8.9029 7.56 8.77

Day 14 4 10.7244 .53077 .26539 9.8798 11.5690 10.06 11.36

Day 28 4 16.1634 2.58632 1.29316 12.0480 20.2788 13.02 19.35

Total 12 11.6643 3.77596 1.09002 9.2652 14.0635 7.56 19.35

GST

Day 1 4 .2625 .22809 .11404 -.1004 .6254 .10 .60

Day 14 4 3.9500 1.10905 .55453 2.1852 5.7148 2.60 5.30

Day 28 4 8.1000 1.25698 .62849 6.0999 10.1001 7.00 9.90

Total 12 4.1042 3.45861 .99841 1.9067 6.3017 .10 9.90

ANOVA

Sum of Squares df Mean Square F Sig.

Body Weight

Between Groups .166 2 .083 1.303 .319

Within Groups .574 9 .064

Total .741 11

Total Protein Between Groups 173.715 2 86.857 103.333 .000

Within Groups 7.565 9 .841

164

Total 181.280 11

AST

Between Groups 6464.667 2 3232.333 22.657 .000

Within Groups 1284.000 9 142.667

Total 7748.667 11

ALT

Between Groups 522.667 2 261.333 11.985 .003

Within Groups 196.250 9 21.806

Total 718.917 11

ALP

Between Groups 1622.000 2 811.000 6.103 .021

Within Groups 1196.000 9 132.889

Total 2818.000 11

Cyt_P450

Between Groups 135.170 2 67.585 28.075 .000

Within Groups 21.666 9 2.407

Total 156.836 11

GST

Between Groups 122.995 2 61.498 64.462 .000

Within Groups 8.586 9 .954

Total 131.581 11

Post Hoc Tests Multiple Comparisons

Dependent Variable (I) Days (J) Days Mean Std. Error Sig. 95% Confidence Interval

165

Difference (I-J) Lower Bound Upper Bound

Body Weight LSD

Day 1 Day 14 .12500 .17863 .502 -.2791 .5291

Day 28 -.16250 .17863 .387 -.5666 .2416

Day 14 Day 1 -.12500 .17863 .502 -.5291 .2791

Day 28 -.28750 .17863 .142 -.6916 .1166

Day 28 Day 1 .16250 .17863 .387 -.2416 .5666

Day 14 .28750 .17863 .142 -.1166 .6916

Total Protein LSD

Day 1 Day 14 2.70000* .64829 .002 1.2335 4.1665

Day 28 -6.37500* .64829 .000 -7.8415 -4.9085

Day 14 Day 1 -2.70000* .64829 .002 -4.1665 -1.2335

Day 28 -9.07500* .64829 .000 -10.5415 -7.6085

Day 28 Day 1 6.37500* .64829 .000 4.9085 7.8415

Day 14 9.07500* .64829 .000 7.6085 10.5415

AST LSD

Day 1 Day 14 -19.50000* 8.44591 .046 -38.6060 -.3940

Day 28 -56.00000* 8.44591 .000 -75.1060 -36.8940

Day 14 Day 1 19.50000* 8.44591 .046 .3940 38.6060

Day 28 -36.50000* 8.44591 .002 -55.6060 -17.3940

Day 28 Day 1 56.00000* 8.44591 .000 36.8940 75.1060

Day 14 36.50000* 8.44591 .002 17.3940 55.6060

ALT LSD

Day 1 Day 14 10.00000* 3.30194 .014 2.5305 17.4695

Day 28 -6.00000 3.30194 .103 -13.4695 1.4695

Day 14 Day 1 -10.00000* 3.30194 .014 -17.4695 -2.5305

Day 28 -16.00000* 3.30194 .001 -23.4695 -8.5305

166

Day 28 Day 1 6.00000 3.30194 .103 -1.4695 13.4695

Day 14 16.00000* 3.30194 .001 8.5305 23.4695

ALP LSD

Day 1 Day 14 -28.00000* 8.15135 .007 -46.4396 -9.5604

Day 28 -18.50000* 8.15135 .049 -36.9396 -.0604

Day 14 Day 1 28.00000* 8.15135 .007 9.5604 46.4396

Day 28 9.50000 8.15135 .274 -8.9396 27.9396

Day 28 Day 1 18.50000* 8.15135 .049 .0604 36.9396

Day 14 -9.50000 8.15135 .274 -27.9396 8.9396

Cyt_P450 LSD

Day 1 Day 14 -2.61920* 1.09712 .041 -5.1011 -.1373

Day 28 -8.05820* 1.09712 .000 -10.5401 -5.5763

Day 14 Day 1 2.61920* 1.09712 .041 .1373 5.1011

Day 28 -5.43900* 1.09712 .001 -7.9209 -2.9571

Day 28 Day 1 8.05820* 1.09712 .000 5.5763 10.5401

Day 14 5.43900* 1.09712 .001 2.9571 7.9209

GST LSD

Day 1 Day 14 -3.68750* .69065 .000 -5.2499 -2.1251

Day 28 -7.83750* .69065 .000 -9.3999 -6.2751

Day 14 Day 1 3.68750* .69065 .000 2.1251 5.2499

Day 28 -4.15000* .69065 .000 -5.7124 -2.5876

Day 28 Day 1 7.83750* .69065 .000 6.2751 9.3999

Day 14 4.15000* .69065 .000 2.5876 5.7124

*. The mean difference is significant at the 0.05 level.