Heavy metals effect on Plant health and growth

Zn`s effect on health and growth of Eruca Sativa

Research article: The effects

of Zinc soil contamination on

the health and growth of rocket

Eruca Sativa (Mill)

Author: Ryan Pullen

Supervisor: Nigel Chaffey

Institution: Bath Spa University

Year: 2013/14

Key words: Zinc, Eruca Sativa, Heavy metals, Chlorosis, growth, Health

Abstract length: 190 words, 1101 characters (inc spaces)

Word count: 4998 words, 31731 characters (inc spaces)

Including critique and future work: 5792 words, 36743 characters

(inc spaces)

1



Abstract

2


Background: Rocket (Eruca Sativa) is grown crop around the world and is

commonly used in salad; it is a fairly tolerant species to drought

and poor quality soils. Zn is an essential micronutrient for plants

and plays roles in many different physiological functions, however

due to the high levels of pollution soils have become contaminated.

Phyto-extraction is a method of using higher plants to translocate

organic contaminants into harvestable biomass to remediate soils.

Methodology: Eruca Sativa was grown in 3 treatments and a control over

the course of 49 days over which time observations on health and

growth were made, they were then harvested and the fresh weight, dry

weights, Zn uptake in leaf and shoot, Chlorophyll content were

measured.

Results/discussion: Significantly reduced biomass production at

highest treatment (1200mg/kg) suggesting toxic contamination,

significantly greater chlorophyll production at low treatment than

at higher treatment suggesting Zn effects chlorophyll content but

can become toxic and cause chlorosis. Significant Zn uptake as

treatments got higher, At 1200mg/kg median Zn content was

4857.14mg/L at highest treatment uptake boomed suggesting that Eruca

Sativa is a tolerant plant which excludes contaminants until a

threshold is reached, between 800 and 1200 mg/kg contamination.

3


Abstract

Introduction Eruca sativa - 6 Heavy metals - 6 Plants relationship with heavy metals - 7 Bioavailability - 8 Zinc - 8 Heavy metal tolerance - 9 Remediation techniques - 10 Phyto extraction - 11 Aims - 12 Objectives - 12

Methodology

Greenhouse

Greenhouse conditions - 13 Sowing and potting - 13 Sample size and treatment - 13 Randomizing - 14 Observations and monitoring - 14 Harvesting - 14

Laboratory analysis

Fresh and dry weights - 15 Atomic absorption spectrophotometry (AAS) - 15 Soil tests - 15 Chlorophyll content - 16 Statistical analysis - 16

Results

Fresh weight - 17 Dry weight - 18 Zn uptake in leaf - 19

4


Zn uptake in shoot - 20 Total Zn uptake - 21 Leaf vs. shoot comparison - 22 Chlorophyll content - 23 Chlorophyll ratio - 26 Purpling - 26 Flowering - 27

Discussion

Zn`s physiological roles - 28 Zn toxicity - 30 Eruca sativa tolerance - 30 eruca sativa phyto extraction potential - 32 conclusion - 34

Critique - 35

Future work - 36

Acknowledgments - 38

References - 39

Appendix - 53

5


Eruca sativa

Rocket (Eruca Sativa) is a member of the Brassicacceae family (Abassi et

al., 2013).and is an endemic species originating from the

Mediterranean (Barlas et al., 2011; Abassi et al., 2013) and is now

grown worldwide due to its tolerance of dry, disturbed land (Al-

quarainy, 2009)

It grows from 20 to 50cm in height (Barlas et al., 2011) Eruca Sativa

growth is quicker in Higher temperatures and longer day lengths

(Dolezalova et al., 2013). Eruca Sativa is known to bolt into flowers in

longer days (Jaske, 2012) although it is usually harvested when the

leaves are young for salads (Dolezalova et al., 2013) Eruca Sativa has

also got medicinal purposes (Abassi et al., 2013) and is known to

6


have many properties such as astringent, digestive, emollient,

laxative, tonic, stomachic, anti-inflammatory for colitis and

stimulant properties (Barlas et al., 2011; Abassi et al., 2013). Eruca

Sativa bio-components has also got cancer prevention potential

(Michael et al.,2011; Ambrosone and Tang, 2009; Higdon et al., 2007) as

well as use as an aphrodisiac (Dolezalova et al., 2013).

It is an easily grown species (Barlas et al., 2011) and has natural

resistance to drought and pathogenic invasion (Abassi et al., 2013).

Eruca Sativa has been noted as a highly tolerant species and can

accumulate some HM (Saleh, 2001), it is notably tolerant of salts

(Ashraf & Harris, 2004)

Heavy metals

“Heavy Metals” (HM) are defined as a metallic element with a

density between 4-5g/cm3 (Jarup, 2003; Nagajyoti et al., 2010).

Commonly found HM include Lead (Pb), chromium (Cr), arsenic (As),

zinc (Zn), cadmium (Cd), copper (Cu) (Wuana & Okieimen, 2011). In

toxic concentrations HMs can cause damage to the ecology,

environmental, nutritional and evolutionary characteristics of the

polluted area (Babula et al., 2008). HM pollution boomed during the

1900`s industrial revolution leading to high levels of soil, water

and atmospheric contamination (Jarup, 2003).

7


Soils are HMs sinks (Wuana & Okieimen, 2011) HMs originate from the

earths crustal rock and are released through weathering processes

(Wuana & Okieimen, 2011) although its anthropogenic sources such as;

fertilisers, mine tailings, pesticides, sewage sludge and smelting

have caused unnaturally high contamination (Wuana & Okieimen, 2011).

Concentration of HMs persists as they are not degraded from

microbial or chemicals like organics, reducing soil quality (Lasat,

2002). Prolonged contamination of soils severely reduces the soil

quality (Oliviera and Pampulha, 2006) However changes to chemical

form are possible (Wuana & Okieimen, 2011). Humans require HMs as

they are essential micro-nutrients but whilst essential, HMs can be

poisonous at toxic levels (Duiribe et al., 2007). There is currently

a widespread issue with dietary Zn deficiency (Myers, 2014).

HMs and plants

HMs and plants have complex relationships. HMs is essential

nutrients in trace concentrations for healthy growth as Plants

require the nutrients for essential physiological functions (Tangahu

et al., 2011). Deficient or toxic concentrations can cause

disruptions to essential functions leading to poor health or death.

(Nagajyoti et al., 2010) The degree of toxicity or deficiency the

plant has to tolerate to survive is affected by Metal Form and

8


concentration, bioavailability and species (Nagajyoti et al., 2010).

High and low concentrations of HM in soil can negatively affect crop

growth, as these metals interfere with metabolic functions in

plants, including inhibition of photosynthesis and respiration and

degeneration of main cell organelles, even leading to death of

plants (2001; Schmidt, 2003; Schwartz et al., 2003).

Bioavailability

Bioavailability is the measure Zn available for uptake,

Bioavailability of Zinc primarily depends on the concentration in

the soil, Ph of the soil and its chemical form (Lin & Aarts 2012;

Pilon-Smits, 2005) exposure time, species, environmental conditions

which also affects bioavailability (Lin & Aarts 2012). Zn is more

available in low Ph soil as Ph reduces Zn concentration in solution

( Rout & Das, 2003). Zn interacts with other HM in the soil. Zn

balances with other HMs affects the bioavailability. An essential

balance for Zn is P, high levels of P cause Zn deficiencies

(Mousavi, 2011) the relationship between Zn vs. Cu. Is such that if

one is taken up in high concentration it inhibits the uptake of the

other (Mousavi, 2011) whilst Zn vs. Fe have a sympathetic

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2266886/#B53




relationship, however Zn in excess can severely reduce Fe uptake

(Mousavi et al., 2013).

Zinc

Zn is an essential micro-nutrient for physiological functions. Zn is

a building block for enzymes; in addition many enzymatic reactions

are activated by zinc (Mousavi, 2011). Zinc exerts a great

influence on many plant life processes, such as; Nitrogen metabolism

and uptake of nitrogen and protein quality; photosynthesis and

chlorophyll synthesis, carbon anhydrase activity; resistance to

abiotic and biotic stresses and protection against oxidative damage

(Cakmak, 2000; Shulin et al., 2009).

Figure 1: Zinc concentration and its effect on the likelihood

of the symptoms deficiency and toxicity being present (Lin &

Aarts, 2012).

Zn deficiency is commonly reported in crop growth (Assuncao et al.,

2010) Zn deficient plants suffer from physiological stress caused by

10


enzyme dysfunction and other metabolic function disruptions

(Mousavi, 2011) Symptoms of deficiency include stunted growth,

inter-venial chlorosis in younger leaves, necrotic tips and

photosynthetic problems (Rout & das, 2003).

Zn toxicity leads plants to suffer from physiological stress caused

by enzyme dysfunction and other metabolic function disruptions

(Mousavi, 2011). Zn excess can cause: ATP synthesis (Mousavi et

al.,2013), other symptoms include chlorosis, smaller leaves and

necrotic leaf tips (Rout & Das, 2003; Sagardoy et al.,2008)

HM tolerance

HM tolerant species fit into three strategic types HM tolerance;

excluders, indicators and accumulators (Ghosh & Singh 2005; Mganga,

2011; Bert et al.,2000)

Figure 2 – Strategies for coping with high HM contamination in

soil (Ghosh & Singh 2005)

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Indicator species accumulate metals into tissues to a level that

reflects the concentration in the soil regardless of high or low

levels (Bakker, 2008). Excluders prevent metals from entering the

above ground tissues however there`s still accumulation in the roots

(Ghosh & Singh 2005; Dahmani- Muller et al., 2000 ), HM ions are

excluded by cell wall binding and many other mechanisms

increasing tolerance (Hall, 2002).

Accumulator species concentrate the HMs in above ground tissues;

these are species known to accumulate metals at concentrations

higher than in the soil (Maestri et al., 2010, Babula et al., 2008;).

To be classified an accumulator HM uptake must exceed 10 000 mg/kg

Zn and Mn, 1000 mg/kg for Co, Cu, Ni, As and Se, and 100 mg/kg Cd

(Mcgrath and Zhou, 2002) there are between 400 and 450 known hyper

accumulators (Padamavathiamma & Lu, 2007).

Bio remediation

Bioremediation are techniques for reducing HM contamination, many

techniques like chemical washing and physical removal are available

(Sarma, 2011; Garbisu & alkorta, 2001; Lone et al., 2008) However

such methods cause irreversible changes to the soil, reducing its

fertility (Padamavathiamma & Lu, 2007; Diacono & Montemurra, 2009).

Another method used is phytoremediation; the use of HM tolerant

plants to translocate or alter contaminants to reduce their

concentrations (Pal et al., 2010) .

12


(Table 1) – Commonly described methods of phytoremediation adapted

from, (Ghosh, Padamavathiamma & Lu, 2007; Vamerali et al., 2009)

process mechanism contaminant

Phyto-extraction Hyper-accumulation of

metals in harvestable

tissues

Inorganics

Phyto-stabilisation Metal retention in the

root

Inorganics

Phyto-volatilization Evaporation of

dissolved contaminants

from leaves

Organics/Inorganics

Phyto-transormation/

Phyto-degradation

Microbial

degradation/speciation

of contaminant in

plant tissues

Organics/inorganics

Phyto-filtration/

rhizo-filtration

Root and Rhizome

accumulation

Organics/Inorgancs

Phyto-extraction

Phyto-extraction is the remediation technique which uses higher

plants to concentrate HM in harvestable tissues (Pal et al., 2010).

Hyper-accumulators take up and translocate HMs from the soil into

harvestable tissues (Hooda, 2007). Metal chelation agents can be

13


used for encouraging the uptake of HM (Vangrosvield et al., 2009;

Tandy et al., 2004;Khan et al., 2000).

Effective species for Phyto-extraction must fit these criteria

(Padamavathiamma & Lu 2007)

Large Biomass

High accumulation of metals

Has the ability to transport large amounts of metals into

harvestable biomass

Genetics for high tolerance to metals

Rapid growth

Resistant to disease and pests.

The harvested waste material has many applications; combustion for

energy, metal recycling or production of fertilisers (Alkorta et

al., 2004)

There is a desire for effective, cheap and green techniques (Pilon-

smits, 2005). Phytoextraction is currently receiving a lot of

attention as it is both cheap and green (Badr et al., 2012). However

The disadvantage of phytoremediation is the time it takes, time

taken for a species to grow is significantly slower than chemical or

physical approaches (Vangrosvield et al., 2009) and should be

considered a long term solution (Prasad & frietas,2003)

14


Aims:

Zn is an essential element for plants and can encourage great health

at optimised treatments but can become deficient or toxic and cause

ill health. Phyto-extraction is an exciting research topic looking

into the abilities of plant species of accumulating HMs in very high

concentrations. The aim of this study is to evaluate the effects of

Zn on the health and growth and the tolerance and accumulation of Zn

in Eruca Sativa.

Objectives:

To grow Eruca Sativa in varied Zn concentrations

To assess the growth and health of the plants, comparing

chlorophyll concentration, Zn accumulation and biomass

production

To observe several health indicators such as chlorosis and or

purpling, shoot size, death and flowering.

15


Methodology

Greenhouse Maintenance

The greenhouse was kept at consistent temperature and light levels

by heaters and growth lights extending hours of light to 16 and

ensuring that the temperature does not go below 0oC.

Sewing and potting

300 seeds were sown in seed trays in the compost with vermiculite

and perlite for improved germination and seedling growth conditions

(takahashi et al., 2006;Sari &Karaipekil, 2007). Once germinated 3

individuals were transferred into 1L pots, and then grown for 7 days

so any that had died or failed to make the transfer unharmed were

replaced.

16


Sample size and Treatment application

The treatments selected were 400mg/kg, 800mg/kg and 1200mg/kg of

zinc adapted from a similar study by Ozdener & Aydin (2010), these

will hereafter be referred to control, low, medium, high treatments.

These were made up by diluting 219.78g of ZnSO4.7H2O (Zinc Sulphate)

into 500Ml for 100mg/kg and applying appropriate Ml for each

treatment via a pipette. To calculate the volume of compound to be

administered for each treatment this formula was used.

Compound

weight (g) =

mg/kg element X

dilution rate X 100

1000

%

element

(full Calculations in appendices A).

For each treatment there were 20 pots with 3 individuals in

totalling 60 plants per treatment (total = 240). Half the pots were

designated for study A (fresh, and dry weights and Zn uptake )and B

(chlorophyll content)(Figure 3). Each was labelled and the growth

phase had begun.

17


Figure 3: distribution of the samples by treatment and which study

there were applicable to.

Randomising

The pots were randomly assigned its growing position in the

greenhouse space using a random number generator (appendices B)

in excel (Microsoft, 2010).

Observations and monitoring

After the initial 21 days of the growth phase weekly observations

began. Observations of leaves exhibiting purpling and how dark the

purpling had become, quantity dying or dead plants, shoot length,

size of leaf, and from week 5 onwards individuals that had flower

and the number of flowers.

Harvesting

The harvesting process consisted of cutting the shoot at the base

just above the soil, hence cutting the above ground portion from the

18


roots, this was done delicately to get the whole shoot rather than

cut it short. The leaf and shoot tissues from each pot were then

carefully placed in labelled paper bags.

Laboratory analysis

Fresh and dry weights

Fresh weights were taken immediately after harvesting. The samples

were then left over night in an oven to dry them out. The next day

the samples were checked to ensure they were completely dried, once

fully dried dry weights were taken.

Atomic absorption spectrophotometer (AAS)

The leaf tissue was separated from the shoot and then approximately

1g was weighed out for leaf and another 1g for shoot, However for

the samples from the 1200 treatment not enough material for each

compartment therefore plant materials mixed. The exact weight was

recorded ( 2 d.m).

Once weighed samples were digested in labelled kjeldatherm tubes in

the fume cupboard with 5Ml nitric acid. Samples were then refluxed

at 120ᵒC for 20 minutes followed by 20 minutes at 160ᵒC. once cooled

the digested solution was filtered through whatman no.54 paper into

50Ml volumetric flasks made up with distilled water.

19


Zn concentration was determined using the AAS which had been

calibrated. Throughout testing many of the samples were read as

“OVER” so a 1 in 10 dilution was required for each sample. (RSC,

undated).

Soil tests

The compost used for the growth phase was tested for its Ph – using

the method described in Eckert and Sims (2011) and organic matter –

using the method described in Mathiessen (2006).

Chlorophyll content

Chlorophyll content was determined by using the method set out in

Inskeep & Bloom (1985)

0.1g of leaf was weighed out and then macerated in 12.5Ml of acetone

twice. The liquid was decanted into a separate clearly labelled

tube. This solution was equally weighed out between two centrifuge

tubes and spun in the centrifuge at 3000rpm for 3 minutes. Once

completed the solution was poured into a 50Ml volumetric flask. The

solution was then decanted into cuvettes.

20


In the spectrophotometer the absorbance of the samples at

wavelengths 646.6 and 663.6 were recorded 4 samples at a time.

Chlorophyll content calculated from equations in Porro (2002).

Chlorophyll a (µg/Ml) = 12.25 (A663.6) – 2.55

(A646.6)

Chlorophyll b (µg/Ml) = 20.31 (A646.6) – 4.91

(A663.6)

Total chl (µg/Ml) = 17.76 (A646.6) + 7.34 (A663.6)

Statistical analysis

Data was assessed for normality using the Sharpiro-Wilk test prior

to running further statistical analysis, the results of which led to

the following: data with more than two sets, For non-parametric

data Kruskal Wallis was used, for parametric (ANOVA) with Tukeys HSD

test to determine where the significance was. For data with only 2

sets, 2 sample T tests were used.

21


Results

Fresh weights

trace 400 800 12000

2

4

6

8

10

12

14

Applied treatment Zn (ppm)

Fresh weight (g)

Figure 4: Mean Fresh weight post-harvest per applied treatment

of Zn, with 95% confidence error bars.

Figure 4 shows There was significantly less fresh weight from those

in the high treatment (Mean 5.8g; Median: 5.89g) than each other

treatment (p value = 0.007) but no significance between the medium

treatment (Mean: 12.56g), low treatment (Mean 10.3g) and control

(Mean: 9.51).

22


Dry weights

trace 400 800 12000.00

0.50

1.00

1.50

2.00

2.50

Applied treatment zn (ppm)

Dry weight (g)

Figure 5: Mean dry weight post-harvest per applied treatment

mg/kg of Zn, with 95% confidence error bars. 800> 400> control

> 1200

Data in figure 5 shows Significantly less dry weight from those in

the high treatment (Mean, Median) than that of each of the other

23


treatments (p value = 0.002) but no significantly different Mean dry

weights between the rest.

Tissue Zn content

trace 400 8000

100

200

300

400

500

600

700

800

Applied Zn treatment (ppm)

Zn concentration in tissue (mg/L)

Figure 6: Mean Zn content (mg/L) in the shoot tissues from each

treatment, with 95% confidence intervals.

24


Significantly different shoot Zn uptake between each treatment

(kruskal wallis = 20.66, P value <0.001) medium treatment (Median:

512.82 mg/L) had significantly greater uptake than low treatment

(Median: 166.67 mg/L) which was significantly greater than the

control (Median: 27.86 mg/L). (Figure 6)

trace 400 8000

100

200

300

400

500

600

700

800

900

1000



25


Figure 7: Mean Zn content (mg/L) in leaf tissue from each

treatment, with 95% confidence intervals.

Significantly different leaf Zn uptake between each treatment

(kruskal wallis = 18.28, P value <0.001) medium treatment (Median:

758.62 mg/L) had significantly greater uptake than low treatment

(Median: 464.65 mg/L) which had significance over control (Median:

24.83 mg/L). (Figure 7)

trace 400 800 12000

500100015002000250030003500400045005000


Zn concentration in ttissue (mg/L)

0 400 800 12000

1000

2000

3000

4000

5000

6000


Zn concentratin in tissues

Figure 8: Mean Zn content (mg/L) in the all harvestable tissues

(leaf+Shoot) from each treatment, with 95% confidence

intervals. Figure 9: Individual plot of total Zn uptake,

displaying the increasing Zn uptake throughout the treatments.

26


Figures 8,9 illustrate the Significantly different total Zn uptake

between each treatment (kruskal wallis = 31.55, P value <0.001) the

Highest treatment had significantly greater Zn uptake (Median:

4857.14mg/L) medium treatment (Median: 351.33 mg/L) had

significantly greater uptake than low treatment (Median: 193.33

mg/L) which had further significance over the control (Median: 15.44

mg/L).

Leaf vs. shoot comparison

27


trace 400 8000

100

200

300

400

500

600

700

800

900

1000

leafshoot



Figure 10: Zn content comparisons between leaf and shoot

material for each treatment, showing the translocating ability

of eruca sativa.

There was significantly greater Zn content in the leaves than in the

shoot in the low treatment. Leaf content (Mean: 532mg/L) was

significantly greater than the Zn content in the shoots (221 mg/L).

(P value = 0.001). However there was No significance at medium

treatment Leaf Tissue (Mean: 945 mg/L) was not significantly greater

than shoot tissues (Mean: 752mg/L) (P value = 0.462). Neither was

there significance for the control. Shoot Tissue (Mean: 36.4 mg/L)

28


was not significantly greater than leaf tissues (Mean: 31.7 mg/L).

(P value = 0.605). (Figure 10)

Chlorophyll A content

trace 400 800 12000

0.5

1

1.5

2

2.5

3

3.5


chlorophyll content (µg/ml)

Figure 11: Chlorophyll A content in leaf tissues at each

treatment, using Porro`s (2002) chlorophyll content equation.

Low > medium > high > control.

29


In figure 11 its shown that Chlorophyll A content in the low

treatment (Mean: 2.91ug/Ml, Median:2.96ug/Ml) was significantly

greater than each of the other treatments. Each of the other

treatments were not significantly different to each other. The

Means of each were almost level 1.63 ug/Ml, 1.68 ug/Ml, 1.65 ug/Ml

for control, 800 and 1200 treatments respectively.

Chlorophyll B Content

30


trace 400 800 12000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


Chlorophyll content (ug/ml)

Figure 12: Chlorophyll A content in leaf tissues at each

treatment, using porro`s (2002) chlorophyll content equations

Low>medium>control>high.

Chlorophyll B content in the low treatment (Mean: 2.91ug/Ml,

Median:2.96ug/Ml) was significantly greater than the control and the

high treatments but not significantly greater than the medium

treatment (Mean: 0.62ug/Ml, Median: 0.64ug/Ml). (P value = 0.009)

(figure 12).

31


32


Figure 13: total Chlorophyll content in leaf tissues at each

treatment, using porro`s (2002) chlorophyll content equation.

Low> medium> control> high.

Mean total chlorophyll content of those grown in the low treatment

(Mean: 3.79ug/Ml, Median: 3.74ug/Ml) treatment was significantly

greater (p value = 0.002) than the other treatments. There was no

significance between the other treatments; Means were 2.22 ug/Ml,

2.30 ug/Ml, 2.16 ug/Ml for control, medium and high treatments

respectively. (figure 13).

33

trace 400 800 12000

0.5

1

1.5

2

2.5

3

3.5

4

Appied treatment Zn (ppm)

Chlorophyll content (ug/ml)


Table 2: Leaf chlorophyll content ratio`s A/B in each treatments.

Chlorophyll ratio

A/B

contr

ol 400 800 1200

Mean

2.737

499

3.377

527

2.727

979

3.207

932

Media

n

2.792

959

3.449

15

2.578

887

3.304

642

No significantly different chlorophyll ratios were found, Zn

contamination had no effect on the ratios between A/B (P value =

0.423)

Purpling of leaves and mortality

Table 3: percentage of plants that are healthy or that are showing

necrosis, purpling on a weekly basis throughout the growth period.

34


Week

contro

l

400mg/

kg

800mg/

kg 1200mg/kg

necro

sis

purpli

ng

healt

hy

necro

sis

purpli

ng

health

y

necro

sis

purpli

ng

healt

hy

necros

is %

purpli

ng %

healt

hy

% %

leave

s % % %

Leaves

% % %

leave

s % % %

leave

s %

3 6.7 21.7 71.7 3.3 23.3 73.3 11.7 36.7 51.7 30.0 35.0 35.0

4 6.7 31.7 61.7 5.0 31.7 63.3 16.7 48.3 35.0 36.7 40.0 23.3

5 8.3 50.0 41.7 8.3 43.3 48.3 21.7 51.7 26.7 48.3 43.3 8.3

6 10.0 70.0 20.0 10.0 68.3 21.7 30.0 56.7 13.3 55.0 45.0 0.0

7 10.0 83.3 6.7 10.0 76.7 13.3 33.3 53.3 13.3 61.7 38.3 0.0

Flowering

35


trace 400 800 12000

10

20

30

40

50

60

70

80

90

100

% flowered% leafy

Figure 15: % of individuals which flowered for each treatment.

94.4% of the control treatment plants flowered, of the plants

grown in the low treatment 59.3% of the plants flowered. The

Medium treatment flowered 39.2% of the time and at the highest

treatment 40% of the plants flowered.

Discussion

36


Physiological roles of zinc

Zn is an essential nutrient for Chlorophyll biosynthesis which

requires Zn dependant enzymes throughout production (Mousavi, 2011),

Zn in excess reduces NADPH production in chloroplasts (Mousavi et

al.,2013), Zn can also effect photosynthesis efficiency (Cakmak,

2008) and the uptake of Fe, an essential nutrient for chlorophyll

biosynthesis (Broadly, 2007). In this study chlorophyll in plants

grown in low levels of Zn contamination were significantly greater

than the other treatments (figure 13) this is likely to be due to

Zn`s role in the biosynthesis of chlorophyll, increasing

photosynthetic ability and the fact that there was not Fe deficiency

as Zn concentrations were not excessive so chlorophyll production

was not inhibited.

There was a large reduction in chlorophyll content in the leaves of

those grown in the highest treatment (figures 11-13), this suggests

that Zn began to inhibit the production mechanisms of chlorophyll

became toxic causing the significant reductions in chlorophyll

content. at toxic levels Zn can cause many physiological disruptions

and a reduction in enzyme productivity (Mousavi, 2011)This suggests

that at between 800 and 1200 mg/kg symptoms of Zn toxicity have

begun to show, this was also an observation made in Ozdener & Aydin

(2010). Reduced chlorophyll could also be a resultant of Fe

deficiency brought on by the High levels of zinc (Mousavi, 2011).

37


Zn can contribute to the metabolism of N, an essential micro-

nutrient in the physiological mechanisms for chlorophyll pigments

biosynthesis (Mousavi, 2011). Neeto et al(2005) found that N

metabolism and bioavailability plays a major role in the ratio of

chlorophyll A and B that is synthesised. This study found that there

was no significance between the 2 pigments suggesting that Zn had no

effect on the pigment ratio. (Table 2)

Biomass production and plant growth requires many mechanisms, many

of these mechanisms require Zn (Mousavi et al., 2013) and these

include Auxin production a growth hormone which encourages the rapid

growth of plants (Zamimalova, 2003), cell cycles and cell elongation

which accelerates growth (Stals and Inze, 2001), This is paired with

Auxin`s role in cell cycle encouraging rapid mitosis (Beemster,

2003). Photosynthesis (Cakmak, 2008), Photosynthesis is essential

for maximising biomass production, poor photosynthetic ability can

lead to stunted growth (allen and Forsberg, 2001). Despite Zn

contributing to many physiological mechanisms associated with

biomass production there was no significant biomass production,

fresh and dry weights did slightly increase but not significantly

(figure 4) and there were no obvious signs of improvement with Zn

addition or Zn deficiency in the control, this again was also found

by Ozdener & Aydin (2010). Whilst it is likely that Zn does

encourage the growth of biomass this study does not provide solid

38


backing to the idea that Zn is highly essential for biomass

production.

However there were significant results from the Fresh and dry

weights for the high treatment, there was a significant drop in the

biomass production (fugures 4,5) A likely explanation for this is

that Zn was applied in toxic concentrations leading to the

inhibition and disruption to the physiological mechanism behind

biomass production. It is also possible that the excess of Zn has

also largely affected the Bioavailability of other nutrients in the

soil that are essential for biomass production, implying that

stunted growth and lack of biomass are symptoms of Zn toxicity,

concurrent with current beliefs (Rout & das, 2003; Mousavi et al.,

2013; Cakmak, 2008)

There are many uncertainties with the results of fresh weight and

dry weights. Firstly Fresh and dry weights are not the only growth

factors that can measure the biomass production and do not provide

the whole story. Shoot length and leaf size can further explain the

role of Zn of plants however Eruca Sativa bolted throughout the latter

portion of the growth phase (figure 15) When flowered Eruca Sativa has

very low biomass and is a tall thin shoot with limited leaf material

and small delicate flowers (Barlas et al 2011) Eruca Sativa is known to

be quick bolting into flower in longer warmer days (Jaske, 2012).

As this study was done with 16 hour lighting in the greenhouse, It

39


is likely that the day lengths causing many individuals to flower

has majorly effected the reliability of fresh and dry weights. Zn is

known to play many roles in biomass production, and there were

slight however non-significant increases in biomass production for

low and medium treatments which could imply Zn does improve yield

but other factors have prevented significant results.

Zn toxicity

Results from this study suggest that in the highest treatment

1200mg/kg Zn toxicity became a serious issue. There was reduced

biomass (figure 4) and chlorophyll production (figure 13) and

throughout growth phase observations were made that those grown in

the highest treatment were showing multiple symptoms of Zn toxicity

(table 3) and multiple individuals could not tolerate the high

levels of Zn. It is widely known that high HM contamination in soil

can prevent proper development (Smical et al., 2008). One potential

resultant to Zn stress in Eruca Sativa was the prevalence of purpling

of leaves at higher treatments. There was a higher proportion of

individuals exhibiting signs of inter-vienal and leaf tip purpling

at the higher treatments. The correlation between the prevalence of

40


leaves purpling and the contamination levels suggest that Zn in high

doses can lead to leaves becoming a discoloured purple.

Eruca Sativa tolerance

Eruca sativa can be grown worldwide due to its tolerance of dry,

disturbed land (Al- quarainy, 2009) and has the ability to grow in a

range of soils and conditions (Cag et al., 2004). Eruca Sativa growing

healthily in this diversity of conditions suggests that it is a

fairly hardy, versatile and tolerant species and Eruca Sativa has also

been observed to not only tolerate but to accumulate some HMs in low

concentrations. (Saleh, 2001).

There was a significant rise in the level of Zn uptake (figures 8,

9) in harvestable tissues for every rise in Zn treatment, as there

was in Ozdener & Aydin (2010). The increases between the controls,

low and medium treatments were steady, however the difference noted

between the medium and high treatment was far more significant.

Excluder species are tolerant to heavy metal contamination in the

growth medium however there is a threshold at which uptake rapidly

increases (Hall, 2002), The results from this and Ozdener & Aydin

(2010) suggest that Eruca Sativa has a Zn threshold at which uptake

increases and beings to suffer symptoms of toxicity (figure 8)

41


HM tolerant species fit into three strategic types HM tolerance;

excluders, indicators and accumulators (Ghosh & singh, 2005). The

patterns of HM uptake are distinctive and hence easy to identify

tolerance strategy deployed by plants under HM stress.

Results from this study (figure 9) suggest that Eruca Sativa employs an

exclusion strategy to tolerate the high levels of Zn contamination

in the higher treatments. Tolerance of HMs requires genetic

homeostatic ability to cope with the stress of highly contaminated

soils (Cobbett & Goldsburgh, 2002) exclusion mechanisms include

aspects such as transport uptake, distribution, chelation and/or

sequestration of metals into specific tissues (Grotz, 2006). Typical

exclusion specific mechanisms include binding of the cell wall,

sequestering ions in the cell vacuoles, complexion of the metal,

Heat shock protiens, organic and amino acids (Hall, 2002; Cobbett,

2000). The mechanisms allow Hm tolerance through exclusion, results

indicate that Eruca Sativa`s tolerance strategy is likely to be formed

by a combination of exclusion techniques. HM exclusion requires

plants genetics to provide adequate homeostatic functions, including

aspects such as transport uptake, distribution, chelation and/or

sequestration of metals into specific tissues (Grotz, 2006). This

studies results show that Eruca sativa is also tolerant to Zn

deficiency, as was the case in Ozdener & Aydin (2010). This

suggests that as a species it is capable of tolerating both slightly

42


toxic and deficient soils, suggesting that as a species it has a

highly adaptive and versatile range for regulation and tolerance.

Eruca sativa phyto-extraction potential

There are many factors that can account for a species capabilities

and efficiency as a hyper accumulator, Padamavathiamma and Lu (2007)

set out the following criteria for defining a species as a hyper

accumulator:

Large Biomass

As seen in this study Eruca Sativa only produces a few grams of biomass

(figure 4) and only grows up to 50cm with a small shoot it is a

small sized species much like fellow Brassicaccae (Barlas et al.,

2011) whereby the lack of biomass production reduces its suitability

(Tangahu et al.,2011; Pulford & Watson, 2003)

Total HM uptake = biomass x metal accumulation.

Eruca Sativa is therefore less suitable for phyto-extraction

High accumulation of metals

To be defined as a Zn hyper-accumulator a species must accumulate

10,000mg/kg of Zn (Mcgrath and Zhou, 2002). At the highest

contamination level that did not appear to be toxic, the medium

43


treatment Zn uptake was significantly less than this figure (figure

8) suggesting that Eruca Sativa is not a hyper accumulator of Zn. Zn

becomes far to toxic before accumulation reaches the level required

to be defined as a hyper-accumulator, limiting its extraction

qualities.

the ability to transport large amounts of metals into

harvestable biomass

the ability to uptake HMs from the soil and translocate them is an

essential ability for a hyper-accumulator, as is sequestering them

into organelles for use in physiological mechanisms and storage

(Williams et al., 2000; Tian et al., 2009)Results suggests that there

was limited transporting of Zn from the cell wall into the

harvestable plant, due to exclusion mechanisms deployed by Eruca

Sativa, there was also not any significance in the leaf and shoot

content suggesting that its ability to sequester HMs into organelles

is limited

Genetics for high tolerance to metals and drought

Eruca Sativa is a very versatile species grown worldwide despite drought

and disrupted soils, often grown along pathways and in dry fields

with limited water supply (Abassi et al., 2013). Furthermore it is a

species with capable tolerance and genetic ability to be tolerant of

44


metals as discussed above, however at very high contamination levels

it can succumb to toxicity.

Rapid growth

Eruca Sativa is an easy to grow and rapid species (Barlas et al., 2011).

These study further backs this up, this study was done through the

winter months so growth conditions were not perfect despite the

light and temperature being regulated in the greenhouse yet it took

only 49 days after being sown to reach its maximum size.

Resistant to disease.

Eruca Sativa suffered at the highest treatment level however this was

due to toxicity not because of disease. Eruca Sativa has been identified

as a species which has natural resistance to drought and pathogenic

invasion (Abassi et al., 2013)

Conclusion

Zn effect

45


It is possible that Zn concentration has a limited effect on

growth; however in high contamination levels Zn can have a

highly negative effect on growth, stunted growth and reduced

ability to bolt into flower are symptoms of Zn toxicity.

At the low treatment with 400 parts per million applied the

productivity and health of Eruca Sativa was at its greatest, this

suggest that Zn can have many positive effects and contributes

to the physiological mechanisms that can provide optimised

yield.

Treatments with higher contaminations caused reduced health and

productivity and signs of stress begin to show. The above 800

mg/kg contamination noticeable and significant symptoms of

toxicity began to kick in

Zn does not have an effect on the biomass production of Eruca

Sativa, but it does have an effect on the production of

chlorophyll, high chlorophyll content was measured at low level

treatments.

Eruca Sativa

Eruca sativa is not a hyper-accumulator of Zn, it does not

hyper accumulate Zn into harvestable biomass.

It is likely that it has the ability to tolerate Zn up to a

threshold in the same nature an HM excluder species would,

whereby below the threshold Zn uptake is low but once past the

46


threshold Zn begins to flood into the harvestable biomass and

severe toxicity begins.

Eruca Sativa is a very easy to grow, tolerant species that can

withstand a lot of stresses and still be healthy.

Critique

Not enough matter for separate compartment: one problem was that

separate Zn analysis for the leaf and shoot for the high treatment

was not possible so they needed to be mixed only allowing a total Zn

uptake.

Competition effected results: there were three individuals grown in

each pot and the seeds acquired were not homogenous therefore there

is the chance that competition has occurred throughout the growth

phase and altered the results.

The roots were not harvested: The roots were not harvested and

washed for Zn uptake analysis and for other observational purposes.

Had this been done translocation factor could have been considered

as well as previously reported symptoms of Zn deficiency and

toxicity on the root.

47


Weights were totals rather than leaves/shoots: a minor criticism of

the methodology separate shoot and leaf, fresh and dry weights were

not taken, the weights recorded were for the whole of the

harvestable portion.

Soil samples post-harvest: Another area in which this project could

have been improved with increased time frame for analysis would have

been post-harvest soil tests for Ph and other metal concentrations.

This was not done due to timing issues.

Flowering: Due to day length extending and the natural flowering

cycle of eruca sativa Meant many of the individuals flowered before

the harvesting stage; this is unlike practises for Eruca Sativa crop

growth and harvesting as it is commonly harvested prior to flowering

for use in saladsLack of physiological analysis: Due to lack of

resources and time many of the physiological effects of zinc could

not be analysed any more deeply than observations. Given an extended

time frame and greater resources many physiological factors such as

enzyme and hormone activity could have been analysed.

Sulphur effect on the growth: The compound used to create the

standard solution that the treatments were based on was zinc

sulphate. The fact that high levels of Zinc were required for

setting up treatments it Means that a high concentration of sulphate

will also be in the treatment applied., there was a plan to conduct

48


a parallel sulphur based experiment however it was not possible due

to lack of greenhouse and the time frame was too narrow to conduct

the studies one after the other. Furthermore the concentrations of

sulphur were not excessive; in fact it can be said that sulphur

toxicity is not likely as its presence reduces Ph which in itself

reduces the bioavailability of sulphur.

Further work

This study has provided additional framework to our knowledge of

heavy metal and species relationships. Expansion is greatly

necessary on what is already known of this relationship. There is a

huge field of work in this area and it is expanding at a relatively

rapid speed due to its importance scientifically and commercially.

Phyto exclusion and more generally Phytoremediation are incredible

exciting regions of biological science, and is one that is receiving

a lot of attention. The implications of further research down this

area could be huge and it is one that should be recommended greatly.

Pollution and soil contamination has become a real issue and a grand

talking point from many perspectives and dealing with the

repercussions of industrial boom and continued emissions of Heavy

metals is emerging as an area that is greatly in need of expansion.

Zinc is an essential micro nutrient and has received a lot of

attention from researchers. Zn is an essential component of health

49


and growth of plants knowledge on the topic can be further expanded.

Likewise there is also further work that can be done in the

physiological departments of heavy metals. Each Heavy metal is

essential to plants, each one having countless physiological roles.

Increasing the work in the field of Heavy metal and plant

interactions should be channelled through a more physiological

route, identifying Mechanism essential for crop survival or thriving

would be incredibly useful.

Eruca Sativa is clearly a species capable of tolerating harsh conditions

and has potentially got hyper-accumulative capabilities for other

heavy metals. This study suggests that its tolerance is due to its

genetic capabilities as a Heavy metal excluder.

Eruca Sativa is a commonly produced crop for consumption. Optimisation

of crop yield and increased growth speeds has many commercial

implications.

Hyper-accumulators are a relatively new research area and can always

be improved, their application can provide a coping device for

contaminated soil remediation an area that is clearly one that is

held to be of high importance.

As to the specifics of Zn and Eruca Sativa there are many expansions.

This study was a general over sight of the relationship with

inconclusive results in some areas. There are still a lot of

50


specifics to be looked into. This study was by no Means perfect and

the flaws identified in the critique can be ironed out, and the data

collected can be expanded in terms of numbers and specialised in

terms of the physiological effects.

Acknowledgments

I would like to thank Darrell Watts for all of his time and his

incredible support throughout the past 6 months.

Im also grateful for the help from Laura, James, jenny and Derek.

Their time and assistance was valued and from them I learnt a lot.

And lastly I’d like to Thank Nigel Chaffey for his guidance and

encouragement over the course of this process. His supervision was

much appreciated.

51


Thank you to my friends and family

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72


Appendix

1. Randomizing table

2. Soil and water tests resulta

3. Metal calculations.

4. Tables of results

5. Anova and tukeys HSD readings

6. Kruskal wallis readings

7. T test readings

8. Boxplots and individuals plots

9. Risk assessment

73


Randomizing table

400b10 800b3 1200b8 400a4 400a8

1200a7 400a9 Ta6 400b1 400b2

400b6 800a5 Tb6 1200b4 800a2

1200a1 800a1 1200a6 1200a2 1200b6

Ta7 Ta5 1200b2 400b8 1200b5

1200a8 800b10 Ta2 Tb10 400b9

Ta4 Ta8 1200b7 400a6 400a2

800b2 800a4 800b9 Ta1 400b7

400b4 800b1 1200a9 Tb5 Ta10

400b3 1200a4 800b5 800a3 Ta3

400a5 Tb7 800b7 800a8 1200b1

400a1 1200a5 Tb2 400a7 800a7

1200a10 400a3 400a10 800a9 Tb4

Tb8 1200b9 800b8 Tb1 1200b3

Tb3 800a10 800b4 400b5 1200b10

800a6 Ta9 800b6 Tb9 1200a3

Table 4: Positioning of samples on the greenhouse bench. The rocket

was placed on a bench as close to the growing lights. Labels =

Treatment (t, 400, 800, 1200) – analysis group (A or B) - sample

number (1-10)

74


Soil samples

Ph – 5.5

Organic matter – 45%

Water samples

Samples of The water used for watering the plants throughout the

growth phase was taken, each of the 10 samples came out with 0mg/g

of zinc content.

Metal calculations for treatments

ZnSO4. 7H2O

RMM 287.56

RAM Zn 65.4

% ZN 22.75

Weight of compound required for

100mg/kg Zn (1l dilution)

439.5g

Weight of compound required for

100mg/kg Zn (500mL dilution)

219.8g

75


RAM S 32.1

% S 11%

mg/kg S per 1000 Zn 111.5

mg/kg S per 1 Zn 0.11

Table 5: Zn sulphate treatment calculations

Treatment (mg/kg) ML`s of solution applied for

treatment

control 0

400 (low) 4

800 (medium) 8

1200 (high) 12

Table 6: Treatments calculations

Table 7: individual dry weights

Dry weight (g)

76


Sample control 400 800 1200

1 1.59 1.99 No data No data

2 2.27 1.75 3.83 1.17

3 1.29 2.99 1.44 1.35

4 1.93 1.77 2.46 No data

5 2.57 2.16 1.52 1.17

6 2.32 1.76 3.45 1.20

7 1.45 2.17 3.30 0.73

8 1.07 3.48 1.49 0.84

9 1.41 2.57 1.54 No data

10 1.31 1.96 2.29 No data

Number 10.00 10.00 9.00 6.00

Mean 1.72 2.26 2.37 1.08

Median 1.52 2.08 2.29 1.17

ST dev.0.4884070.553151 0.896394 0.217565

95% CIUpper 2.07 2.66 3.06 1.30

Lower 1.37 1.86 1.68 0.85

77


Table 8: individual fresh weights

Fresh weight (g)

Sample control 400 800 1200

1 9.58 9.38 No data No data

2 11.72 8.14 17.12 3.48

3 7.85 15.25 9.07 5.24

4 10.77 7.3 11.89 No data

5 13.65 4.32 6 7.62

6 12.06 7.69 15.67 7.71

7 8.38 10.83 19.47 6.54

8 6.66 16.8 7.7 4.22

9 7.83 11.94 12.83 No data

10 6.62 11.36 13.31 No data

Number 10.00 10.00 9.00 6.00

Mean 9.51 10.30 12.56 5.80

Median 8.98 10.11 12.83 5.89

ST dev.2.3118863.576746 4.191676 1.617636

95% CIUpper 11.17 12.86 15.78 7.50

Lower 7.86 7.74 9.34 4.10

78


Table 9: individual leaf Zn content

Leaf Zn concentration (mg/kg)

Samplecontrol 400.00800.00 1200.00

1 41.67 464.65 1041.67 No data

2 68.97 705.88 2172.04 No data

3 20.20 644.44 914.89No data

4 20.41 765.96 469.39No data

5 21.74 357.89 500.00No data

6 31.25 350.52 659.79No data

7 22.99 333.33 577.78No data

8 26.67 721.65 1409.09 No data

9 440.00 758.62No data

10 No data

N 8.00 9.00 10.00 0.00

Mean 31.74 531.59 944.81No data

Median24.83 464.65 758.62No data

79


SDEV 15.61 166.43 517.09No data

95% CIlower 18.69 403.66 574.91No data

Upper 44.78 659.52 1314.71 No data

Table 10: individual shoot Zn content

Shoot Zn concentration (mg/kg)

Samplecontrol 400.00800.00 1200.00

1 20.62 324.32 363.64No data

2 26.32 142.86 1025.00 No data

3 25.00 116.28 1747.13 No data

4 40.82 160.92 1454.55 No data

5 23.53 363.64 512.82No data

6 29.41 148.94 215.05No data

7 50.63 166.67 480.00No data

8 75.00 231.88 623.38No data

9 333.33 342.86No data

10 No data

80


N 8.00 9.00 9.00 0.00

Mean 36.42 220.98 751.60No data

Median27.86 166.67 512.82No data

SDEV 17.35 89.81 506.91No data

95% CIlower 21.91 151.95 361.95No data

Upper 50.92 290.01 1141.25 No data

Table: 11 individual total Zn uptakes

total Zn concentration (mg/kg)

samplecontrol 400.00800.00 1200.00

1 15.57 197.24 351.332946.24

2 23.82 212.18 799.264750.00

3 11.30 190.18 665.514901.10

4 15.31 231.72 480.985402.30

5 11.32 180.38 253.214204.08

6 15.17 124.86 218.714857.14

7 18.41 125.00 264.445043.48

8 25.42 238.38 508.124978.72

81


9 193.33 275.374240.00

10

N 8.00 9.00 9.00 9.00

Mean 17.04 188.14 424.104591.45

Median15.44 193.33 351.334857.14

SDEV 4.90 38.25 192.53681.80

95% CIlower 12.94 158.74 276.114067.37

upper 21.14 217.54 572.095115.53

Table 12: individual chlorophyll A content

Chlorophyll A

sample trace 400 800 1200

1 1.510453.26285 2.4558 1.648252 1.1756 2.4895 1.415 1.53753 2.736051.8897 1.8744 3.10614 0.759051.5176 1.32005 1.49315 1.1317 3.4573 1.3476 0.70955

6 2.2695 3.94275 0.9806 1.418557 2.0847 4.8141 2.06438 1.3471 3.05405 2.03019 1.627852.8718 1.590610 1.8259

N 9 10 9 6mean 1.626889 2.912555 1.675383 1.652175median 1.510452.962925 1.5906 1.5153SDEV 0.591292 0.973151 0.436801 0.71827295% CIlower 2.081396 3.608706 2.011138 2.405956

82


upper 1.172382 2.216404 1.339629 0.898394

Table13: individual chlorophyll B content

Chlorophyll B

sample trace 400 800 1200

1 0.571151.16105 0.7323 0.400192 0.551060.83452 0.59012 0.541023 0.909290.51558 0.63744 0.741684 0.255110.60686 0.51245 0.616685 0.530080.90952 0.38568 0.371396 0.826261.11999 0.43634 0.376537 0.6303 1.40724 0.792788 0.482320.87827 0.78729 0.562670.662 0.6740410 0.56044

N 9 10 9 6mean 0.590916 0.865547 0.616483 0.507915median 0.562670.856395 0.63744 0.470605SDEV 0.1793 0.277933 0.139296 0.1384995% CIlower 0.728738 1.064369 0.723556 0.653252upper 0.453093 0.666725 0.509411 0.362578

Table 14: individual total chlorophyll (A+B) contentChlorophyll A+B total

Sample trace 400 800 1200

1 2.085684.43269 3.19467 2.052822 1.729873.33071 2.00896 2.082663 3.652692.41032 2.51688 3.856034 1.0162 2.12857 1.83607 2.113835 1.664874.37603 1.73688 1.082896 3.101885.07327 1.41961 1.798867 2.720586.23421 2.862668 1.833053.94048 2.822799 2.1949 3.54142 2.2689610 2.39123

83


N 9 10 9 6Mean 2.222191 3.785893 2.296387 2.164515Median 2.085683.74095 2.26896 2.06774SDEV 0.763529 1.236651 0.560787 0.83532395% CI Lower 2.809091 4.67054 2.727446 3.041132Upper 1.635291 2.901246 1.865328 1.287898

Chlorophyll A/B ratio

Sample trace 400 800 1200

1 2.644577 2.810258 3.353544 4.1186692 2.133343 2.983152 2.397817 2.8418543 3.008996 3.665193 2.940512 4.1879254 2.975383 2.500742 2.575959 2.4211915 2.134961 3.801236 3.494088 1.9105256 2.746714 3.520344 2.24733 3.7674297 3.307473 3.420952 2.6038758 2.792959 3.477348 2.5788879 2.893081 4.338066 2.35980110 3.257976

N 9 10 9 6Mean 2.737499 3.377527 2.727979 3.207932Median 2.792959 3.44915 2.578887 3.304642SDEV 0.368062 0.497748 0.4163 0.8697895% CI lower 3.020416 3.733594 3.047976 4.12071Upper 2.454581 3.021459 2.407983 2.295154

ANOVA and tukeys HSD readings

One-way ANOVA: dry weight versus treatment

Source DF SS MS F PTreatment 3 7.651 2.550 6.10 0.002Error 31 12.961 0.418Total 34 20.612S = 0.6466 R-Sq. = 37.12% R-Sq. (ad) = 31.04%

84


Individual 95% CIs for Mean Based onPooled StepLevel N Mean Step -+---------+---------+---------+--------0 10 1.7190 0.5148 (------*------)400 10 2.2599 0.5831 (------*------)800 9 2.3688 0.9508 (------*-------)1200 6 1.0752 0.2383 (--------*--------)-+---------+---------+---------+--------0.60 1.20 1.80 2.40

Pooled Step = 0.6466Grouping Information Using Tukey Methodtreatment N Mean Grouping800 9 2.3688 A400 10 2.2599 A0 10 1.7190 A B1200 6 1.0752 B

Means that do not share a letter are significantly different.

Tukey 95% Simultaneous Confidence IntervalsAll Pairwise Comparisons among Levels of treatment

Individual confidence level = 98.93%

treatment = 0 subtracted from:

treatment Lower Center Upper --------+---------+---------+---------+-400 -0.2443 0.5409 1.3261 (------*-----)800 -0.1569 0.6498 1.4565 (-----*------)1200 -1.5505 -0.6439 0.2628 (-------*------)--------+---------+---------+---------+--1.2 0.0 1.2 2.4


treatment Lower Center Upper --------+---------+---------+---------+-800 -0.6978 0.1089 0.9156 (------*------)1200 -2.0914 -1.1848 -0.2781 (------*-------)--------+---------+---------+---------+--1.2 0.0 1.2 2.4


treatment Lower Center Upper --------+---------+---------+---------+-1200 -2.2190 -1.2937 -0.3683 (------*-------)--------+---------+---------+---------+--1.2 0.0 1.2 2.4

One-way ANOVA: fresh weight versus treatment

Source DF SS MS F Ptreatment 3 167.7 55.9 4.88 0.007Error 31 355.2 11.5

85


Total 34 522.9

S = 3.385 R-Sq = 32.07% R-Sq(adj) = 25.49%

Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev +---------+---------+---------+---------0 10 9.512 2.437 (-------*------)400 10 10.301 3.770 (------*-------)800 9 12.562 4.446 (-------*-------)1200 6 5.802 1.772 (--------*---------)+---------+---------+---------+---------3.0 6.0 9.0 12.0

Pooled StDev = 3.385

Grouping Information Using Tukey Method

treatment N Mean Grouping800 9 12.562 A400 10 10.301 A B0 10 9.512 A B1200 6 5.802 B


Tukey 95% Simultaneous Confidence IntervalsAll Pairwise Comparisons among Levels of treatment



treatment Lower Centre Upper ---------+---------+---------+---------+400 -3.321 0.789 4.899 (------*------)800 -1.173 3.050 7.273 (------*------)1200 -8.457 -3.710 1.036 (-------*-------)---------+---------+---------+---------+-6.0 0.0 6.0 12.0


treatment Lower Centre Upper ---------+---------+---------+---------+800 -1.962 2.261 6.484 (------*------)1200 -9.246 -4.499 0.247 (-------*------)---------+---------+---------+---------+-6.0 0.0 6.0 12.0


treatment Lower Centre Upper ---------+---------+---------+---------+1200 -11.605 -6.761 -1.916 (-------*-------)---------+---------+---------+---------+-6.0 0.0 6.0 12.0

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One-way ANOVA: Porro A versus pot

Source DF SS MS F Ppot 3 11.238 3.746 6.45 0.002Error 30 17.430 0.581Total 33 28.667

S = 0.7622 R-Sq = 39.20% R-Sq(adj) = 33.12%

Individual 95% CIs For Mean Based onPooled StDevLevel N Mean StDev ---+---------+---------+---------+------0 9 1.6269 0.6272 (--------*--------)400 10 2.9126 1.0258 (--------*-------)800 9 1.6754 0.4633 (--------*--------)1200 6 1.6522 0.7868 (----------*---------)---+---------+---------+---------+------1.20 1.80 2.40 3.00



pot N Mean Grouping400 10 2.9126 A800 9 1.6754 B1200 6 1.6522 B0 9 1.6269 B


Tukey 95% Simultaneous Confidence IntervalsAll Pairwise Comparisons among Levels of pot


pot = 0 subtracted from:

pot Lower Centre Upper ---------+---------+---------+---------+400 0.3322 1.2857 2.2391 (-------*-------)800 -0.9297 0.0485 1.0267 (-------*--------)1200 -1.0684 0.0253 1.1189 (--------*--------)---------+---------+---------+---------+-1.2 0.0 1.2 2.4


pot Lower Centre Upper ---------+---------+---------+---------+800 -2.1906 -1.2372 -0.2838 (-------*-------)1200 -2.3319 -1.2604 -0.1888 (-------*--------)---------+---------+---------+---------+-1.2 0.0 1.2 2.4


pot Lower Centre Upper ---------+---------+---------+---------+

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1200 -1.1169 -0.0232 1.0704 (--------*--------)---------+---------+---------+---------+-1.2 0.0 1.2 2.433 1.9723

S = 0.2123 R-Sq = 31.47% R-Sq(adj) = 24.62%One-way ANOVA: Porro B versus pot

Individual 95% CIs For Mean Based onPooled StDevLevel N Mean StDev ---+---------+---------+---------+------0 9 0.5909 0.1902 (-------*------)400 10 0.8655 0.2930 (------*------)800 9 0.6165 0.1477 (------*------)1200 6 0.5079 0.1517 (-------*--------)---+---------+---------+---------+------0.40 0.60 0.80 1.00



pot N Mean Grouping400 10 0.8655 A800 9 0.6165 A B0 9 0.5909 B1200 6 0.5079 B





pot Lower Centre Upper ---------+---------+---------+---------+400 0.0091 0.2746 0.5401 (-------*------)800 -0.2468 0.0256 0.2980 (-------*-------)1200 -0.3875 -0.0830 0.2215 (--------*-------)---------+---------+---------+---------+-0.35 0.00 0.35 0.70


pot Lower Centre Upper ---------+---------+---------+---------+800 -0.5146 -0.2491 0.0164 (-------*------)1200 -0.6560 -0.3576 -0.0592 (--------*-------)---------+---------+---------+---------+-0.35 0.00 0.35 0.70

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pot Lower Centre Upper ---------+---------+---------+---------+1200 -0.4131 -0.1086 0.1960 (--------*--------)---------+---------+---------+---------+-0.35 0.00 0.35 0.70Error 30 27.557 0.919Total 33 44.587

S = 0.9584 R-Sq = 38.20% R-Sq(adj) = 32.02%

One-way ANOVA: Porro total versus pot

Individual 95% CIs For Mean Based onPooled StDevLevel N Mean StDev ---+---------+---------+---------+------0 9 2.2222 0.8098 (-------*-------)400 10 3.7859 1.3035 (------*-------)800 9 2.2964 0.5948 (-------*-------)1200 6 2.1645 0.9151 (---------*---------)---+---------+---------+---------+------1.60 2.40 3.20 4.00



pot N Mean Grouping400 10 3.7859 A800 9 2.2964 B0 9 2.2222 B1200 6 2.1645 B





pot Lower Centre Upper +---------+---------+---------+---------400 0.3649 1.5637 2.7625 (-------*-------)800 -1.1558 0.0742 1.3042 (-------*--------)1200 -1.4328 -0.0577 1.3175 (---------*--------)+---------+---------+---------+----------3.0 -1.5 0.0 1.5


pot Lower Centre Upper +---------+---------+---------+---------

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800 -2.6883 -1.4895 -0.2907 (-------*-------)1200 -2.9687 -1.6214 -0.2740 (--------*--------)+---------+---------+---------+----------3.0 -1.5 0.0 1.5


pot Lower Centre Upper +---------+---------+---------+---------1200 -1.5070 -0.1319 1.2433 (--------*--------)+---------+---------+---------+----------3.0 -1.5 0.0 1.5

Kruskal-wallis readings

Kruskal-Wallis Test: Leaf Zn uptake versus treatment

Kruskal-Wallis Test on Leaf Zn uptake

treatment N Median Ave Rank Z

0 8 24.83 4.5 -4.00

400 9 464.65 14.8 0.62

800 9 758.62 20.2 3.26

Overall 26 13.5

H = 18.28 DF = 2 P = 0.000

Kruskal-Wallis Test: Shoot Zn Uptake versus treatment

Kruskal-Wallis Test on Shoot Zn Uptake


0 8 27.86 4.5 -4.00

400 9 166.67 13.6 0.05

800 9 512.82 21.4 3.83

Overall 26 13.5

H = 20.65 DF = 2 P = 0.000

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H = 20.66 DF = 2 P = 0.000 (adjusted for ties)

Kruskal-Wallis Test: Zn uptake versus treatment

Kruskal-Wallis Test on Zn uptake


0 8 15.44 4.5 -4.24

400 9 193.33 13.2 -1.62

800 9 351.33 21.8 1.28

1200 9 4857.14 31.0 4.42

Overall 35 18.0

H = 31.55 DF = 3 P = 0.000

T-test readings

Two-Sample T-Test and CI: 400 shoot, 400 leaf

Two-sample T for 400 shoot vs. 400 leaf

SE

N Mean StDev Mean

400 shoot 9 221.0 95.3 32

400 leaf 9 532 177 59

Difference = mu (400 shoot) - mu (400 leaf)

Estimate for difference: -310.6

95% CI for difference: (-456.3, -164.9)

T-Test of difference = 0 (vs. not =): T-Value = -4.65 P-Value = 0.001 DF = 12

Two-Sample T-Test and CI: control shoot, control leaf

Two-sample T for control shoot vs. control leaf

N Mean StDev SE Mean

control shoot 8 36.4 18.5 6.6

control leaf 8 31.7 16.7 5.9

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Difference = mu (control shoot) - mu (control leaf)

Estimate for difference: 4.68

95% CI for difference: (-14.37, 23.73)

T-Test of difference = 0 (vs. not =): T-Value = 0.53 P-Value = 0.605 DF = 13

Two-Sample T-Test and CI: 800 shoot, 800 leaf

Two-sample T for 800 shoot vs. 800 leaf

N Mean StDev SE Mean

800 shoot 9 752 538 179

800 leaf 9 945 548 183

Difference = mu (800 shoot) - mu (800 leaf)

Estimate for difference: -193

95% CI for difference: (-739, 352)

T-Test of difference = 0 (vs. not =): T-Value = -0.75 P-Value = 0.462 DF = 15

Boxplots and individual plots

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Figure 16: boxplot of chlorophyll A content between treatments

Figure 17: individual plot of chlorophyll A content between

treatments

Figure 16: boxplot of chlorophyll A content between treatments

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Figure 18: boxplot of chlorophyll B content between treatments

Figure 19: Individual plot of chlorophyll B content between

treatments

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Figure 20: boxplot of chlorophyll total content between treatments

Figure 21: individual plot of chlorophyll total content between

treatments

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Figure 22: boxplot of fresh weights between treatments

Figure 23: individual plot of fresh weights between treatments

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Figure 24: boxplot of dry weights between treatments

Figure 25: individual plot of dry weights between treatments

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Figure 26: Boxplot of chlorophyll ratios

Figure 26: individual plots of chlorophyll ratios

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SCHOOL OF SOCIETY, ENTERPRISE & ENVIRONMENT

RISK ASSESSMENT

STUDENT LABORATORY WORK

The purpose of this risk assessment is to identify potential hazards

associated with the proposed laboratory work, and to identify control

measures that eliminate or minimise risk to an acceptable level.

99


Notes for completion of Summary:

Students should complete this Summary page after identifying hazards and

appropriate controls in Table A and rating the level of risk using

Table B. If you are working alone you must also complete Table C.

SUMMARY OF RISK ASSESSMENT

Student name: Ryan Pullen

Student number: 228329

Module Code: BY6001

Date(s) of laboratory work:

from 4th Nov., 2013, in TE

and WE labs and N Park

greenhouse

Risk

Assessment ID number:

(office use)

Proposed laboratory work:

soil preparation, heavy metal uptake

measurements, fresh weigh, dry weight

measurements, chlorophyll extraction

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Level of Risk

Low

(delete as applicable after completing

table A and consulting table B below)

Student signature

and date Ryan, Oct

2013

Supervising tutor signature

and date

Area Safety Manager

signature and date

101


Table A Details of Risk Assessment

Notes for completion of Table A:

NB Separate risk assessments must be completed for each type of

activity planned.

Hazards: list significant hazards, for example: chemicals and

chemical reactions, fire or explosions, biohazards, radiation,

noise, high/low temperatures, electricity, radiation; or hazards

arising from the use of equipment, machinery and glassware.

Who might be harmed? Identify groups of people at risk from the

identified hazards, such as staff, students, general public, other?

Column 3 Controls: list precautions that are necessary to control

hazards, for example: proper labelling, storage and containment of

chemicals, provision and use of personal protective equipment, clear

instructions and training for handing chemicals and using equipment,

etc. Is First Aid provision adequate? Are particular measures

necessary to protect disabled or vulnerable colleagues?

Comments/Further action: are there other issues or concerns, which

require further action to reduce risk to an acceptable level?

Lone working should be avoided wherever possible. Will you be

working alone? Yes – in greenhouse (delete as appropriate). If yes

state under Comments/further action how you will be able to summon

help if an accident or emergency arises and complete Table C.

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Hazards Who might

be harmed?

Controls Comments/

further action

Zinc sulphates

or sulphur

compounds used

to level sulphur

mg/kg

Me, anyone

else

working

nearby.

Lab coat, goggles,

gloves, face mask

Prepare with care.

Observe usual

laboratory best

practice, e.g. no

hand-to-mouth

operations, wash

hands before

eating…

Acetone for

chlorophyll

extraction

Me, anyone

else

working

nearby

Lab coat, goggles,

gloves, face mask.

Fume cupboard.

Take care whilst

using the solvent.

Ensure room used

is well-

ventilated.

Zinc

contaminated

plant material

Me, anyone

else who

uses or

enters the

greenhouse/

anyone in

contact

Lab coats, gloves.

Face mask and

goggles when

grinding dried plant

material

Make sure anyone

entering the

greenhouse is

aware of the risks

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with the

soil or

plant

Heating block

for zinc uptake

digestion stage

Me , anyone

in the room

whilst it

is on

Make sure to turn

it off when it

isn’t in use

Nitric acid Me, anyone

else

working

nearby

Lab coat, goggles,

gloves, face mask.

Fume cupboard to

contain fumes.

Use with great

care

Zinc

contaminated

soil, dried

plant material,

and solutions

Me, anyone

else

working

nearby

Ensure al is

appropriately

disposed of at end

of project.

Greenhouse work,

slips, trips

etc.

me Be careful and tidy Have phone on me

at all times so I

can contact anyone

if anything

happens

Table B Level of Risk

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Notes for completion of Table B:

Use table B to assess the level of risk (high, medium, low) by

estimating the likelihood of the identified hazards occurring, then

the potential severity of the consequences. If the activity is

assessed to be high risk action must be taken to reduce it to an

acceptable level (medium or low) – this should be discussed with the

Area Safety Manager if necessary.

Severity of

consequences

Likelihood

of hazard

Minor

injury/

modest

damage

Significant

accident/signif

icant damage

Major injury or

death/

major destructive

damage

Probably will occur Medium

Risk

High Risk High Risk

Possibly will occur Low Risk Medium Risk High Risk

Unlikely to occur Low Risk Low Risk Medium Risk

Table C: Working alone - only do so if it unavoidable.

In the event of an accident or emergency you must be contactable and

be able to contact others from where you will be working. You must

provide this information on each occasion that you work alone. It is

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particularly important that a responsible adult is willing to act on

your behalf in an emergency or if you do not log off – provide

details below:

I agree to notify my contact with a log off time on each occasion I

work alone

Student signature: Ryan Pullen

2. Details of responsible adult (e.g. parent /partner/ friend)

Notes: Thank you for agreeing to act as a point of contact. By

doing so you are indicating your willingness to take appropriate

action on behalf of the student in the event of an emergency, or if

s/he does not log off. In practice this Means: if s/he has not

logged off 15 minutes after the scheduled time, you must try to

contact her/him at 10 minute intervals; if, after one hour, there is

no response then you must begin a search – this might include

contacting the emergency services.

Name of contact: Steven Pullen (Father)

Phone number or other Means of contact: home phone:

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01454880934 mobile number: 07818011996 email: thepullens@

Hotmail.co.uk

Signature of contact: Steven Pullen

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Heavy metals effect on Plant health and growth

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Transcript of Heavy metals effect on Plant health and growth