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Improved lentil production by utilizing genetic variability in response tophosphorus fertilizationMuhammad Rasheeda; Ghulam Jilanib; Imran Ali Shaha; Ullah Najeebc; Tanveer Iqbalb

a Department of Agronomy, PMAS Arid Agriculture University, Rawalpindi, Pakistan b Department ofSoil Science, PMAS Arid Agriculture University, Rawalpindi, Pakistan c Crop Sciences Institute,National Agriculture Research Centre, Islamabad, Pakistan

First published on: 27 September 2010

To cite this Article Rasheed, Muhammad , Jilani, Ghulam , Shah, Imran Ali , Najeeb, Ullah and Iqbal, Tanveer(2010)'Improved lentil production by utilizing genetic variability in response to phosphorus fertilization', Acta AgriculturaeScandinavica, Section B - Plant Soil Science, 60: 6, 485 — 493, First published on: 27 September 2010 (iFirst)To link to this Article: DOI: 10.1080/09064710903183562URL: http://dx.doi.org/10.1080/09064710903183562

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ORIGINAL ARTICLE

Improved lentil production by utilizing genetic variability in response tophosphorus fertilization

MUHAMMAD RASHEED1, GHULAM JILANI2, IMRAN ALI SHAH1, ULLAH NAJEEB3 &

TANVEER IQBAL2

1Department of Agronomy, PMAS Arid Agriculture University, Rawalpindi 46300, Pakistan, 2Department of Soil Science,

PMAS Arid Agriculture University, Rawalpindi 46300, Pakistan, 3Crop Sciences Institute, National Agriculture Research

Centre, Islamabad 45500, Pakistan

AbstractA field experiment was undertaken for evaluating the performance of three lentil genotypes with phosphorus (P) fertilizationat four rates: 0, 40, 60, and 80 kg P2O5 ha�1 under rain-fed conditions. Genotypes of lentil were: Masoor-93, Markaz-2001,and NARC-02/2. Masoor-93 showed the highest seed yield, crop-growth rate, net assimilation rate, and seed proteincontents among all the tested cultivars. P applied at the highest rate (80 kg ha�1) caused the best positive response withrespect to physiological traits, growth attributes, and yield components. Furthermore, the application of P-fertilizer wasfound to be feasible in economic terms, as the net return, value-to-cost ratio, and relative increase in income were enhancedsuccessively at higher phosphorus rates. It was concluded that for maximum potential yield of lentil, genotype Masoor-93 isthe best suited under rain-fed conditions provided that its P nutrition is enhanced. The pronounced genetic variability inlentil-yield traits suggests that nutrient-efficient germplasm can be screened through breeding programmes to promote lentilproduction.

Keywords: Crop growth, economic returns, genetic diversity, harvest index, net assimilation rate, nodulation.

Introduction

Among the pulses, lentil is of special interest with

23.7% content of grain protein, almost double that of

cereals and slightly higher than meat, egg, and fish

(Pellet & Shadarevian, 1970). In addition to protein

its seed is a rich source of minerals and vitamins as

human food, while the straw serves as high-value

animal feed. Lentil (Lens culinaris Medik) is grown

under both irrigated as well as rain-fed conditions in

most regions of the world. It is among the important

pulses for crop intensification in West Asia and

diversification in South Asia (Sarker et al., 2004).

However, lentil yields at the farm level are far below

the genetic potential of its cultivars. Unavailability of

the tested site-specific lentil cultivars and imbalanced

use of fertilizers could be the contributing factors

towards these lower yields. Most of the soils under

lentil cultivation are low-to-medium in available

phosphorus (P), therefore they respond positively to

P-fertilizer application (Singh et al., 2005). Further,

improvement in the genotypes would be helpful to get

the highest response from lower-P soils.

Phosphorus contributes substantially to increased

yield of legumes by enhancing the physiological

functions of the crop plants, root development, and

nodulation (Sharma & Sharma, 2004). Phosphorus

application not only increases the dry matter and

seed yield of lentil but also enhances the N- and P-

content of the seed by increasing nodulation and

root development (Balyan & Singh, 2005). Jilani

et al. (2007) reported that among various sources of

plant nutrients applied to maize, the application of

Corresponding authors: Muhammad Rasheed, Assistant Professor, Department of Agronomy, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi

46300, Pakistan. Tel: 0092-51- 9290757. Fax: 0092-51-9290160. Email: rasheed7864@hotmail.com

Ghulam Jilani, Associate Professor, Department of Soil Science, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi 46300, Pakistan. Tel: 0092-51-

9062241. Fax: 0092-51-9290160. Email: jilani@uaar.edu.pk

Acta Agriculturae Scandinavica Section B � Soil and Plant Science, 2010; 60: 485�493

(Received 23 May 2009; accepted 13 July 2009)

ISSN 0906-4710 print/ISSN 1651-1913 online # 2010 Taylor & Francis

DOI: 10.1080/09064710903183562

Downloaded By: [PERI Pakistan] At: 13:49 14 October 2010

NPK fertilizers at the recommended level gave the

highest crop yields and nutrients uptake.

Higher doses of P to lentil induce early flowering

but delay maturity due to enhanced nitrogenase

activity of intact root nodules and a balancing effect

of P on lentil physiological processes and uptake of

other nutrients (Khan et al., 2006). Garg et al.

(2004) found that phosphorus application signifi-

cantly ameliorated the negative effects of drought on

physiological parameters of moth bean genotypes, as

P had the ability to improve yield under water-

limited conditions. However, higher rates of P could

cause only additional nutrient absorption but not

any added increase in plant growth. Also, the high

rates of P-fertilizer application cause a high level of

P fixation in the soil (Ramos-Hernandez & Flores-

Roman, 2008).

Therefore, it is necessary to perform comprehen-

sive studies on the requirement and response of

various crops to P fertilization. This experiment was

carried out with the objectives of improving yield and

physiological response of lentil cultivars through no

or lower P as well as through enhanced P nutrition.

Materials and methods

Site and experiment

This field study was conducted at the Agronomy

Research Farm of Pir Mehr Ali Shah Arid Agriculture

University, Rawalpindi, Pakistan during the years

2005�2006 under rain-fed conditions. Rawalpindi’s

climate is sub-humid to sub-tropical continental,

receiving on average 1044 mm annual rainfall, with

more than 50% occurring in the monsoon season from

July to September. The mean maximum temperature

ranges from 25.6 to 39.4 8C in June and the mean

minimum temperature ranges from 3.2 to 16.7 8C in

January. The characteristics of field soil were: pH

8.34, electrical conductivity 0.16 dS m�1, organic

matter 3.6 g kg�1, Kjeldahl total nitrogen 0. 42 g

kg�1, available phosphorus 4.32 mg kg�1, extractable

potassium 92.5 g kg�1, and sandy clay loam texture.

This field experiment was laid out according to a

randomized complete-block design with split-plot

arrangement by keeping lentil genotypes in main

plots and phosphorus rates in sub-plots. The sub-

plot size was 4.5 m�1.5 m, and the treatments were

replicated thrice. The treatments included three

genotypes of lentil, viz. Masoor-93, Markaz-2001,

and NARC-02/2; and four rates of phosphorus

fertilizer, viz. 0, 40, 60, and 80 kg P2O5 ha�1 as

single superphosphate. Lentil cultivars exhibit con-

siderable genetic variation in morphological and

agronomic traits, phenological characters including

responses in flowering to temperature and photo-

period, winter-hardiness, drought tolerance, and

disease and insect resistance (Sarker & Erskine,

2006). Therefore, three promising genotypes of len-

til recommended for cultivation in Pakistan were

selected for their P-response studies. In all the

treatments a basal dose of 60 kg N ha�1 was applied

as urea. Fertilizers were applied at the time of

sowing, and crop was sown in 30-cm-distant rows

with seed rate of 20 kg ha�1. The crop was har-

vested at its full maturity, and threshed manually.

Data collection

Agronomic parameters of plant growth and crop

yield (as given in Table I & II ) were recorded at

harvest by standard field procedures on ten ran-

domly selected plants from each sub-plot treatment,

and the average per plant was calculated. Harvest

Table I. Effect of phosphorus on plant biometry of lentil genotypes.

Treatment Shoot length

(cm)

Branch count

(# plant�1)

Nodule count

(# plant�1)

Nodule weight

(mg nodule�1)

Maturity period

(days)

Phosphorus levels (kg ha�1)

0 (CK) 29.7 d* 4.82 d 93.1 c 31.5 d 182.7 d

40 31.5 c 4.97 c 110.4 b 35.1 c 187.6 c

60 33.9 b 5.35 b 130.6 a 38.5 b 192.4 b

80 35.7 a 5.63 a 65.8 d 44.4 a 198.6 a

LSD-values 0.4 0.12 2.6 0.7 0.4

Genotypes

Masoor-93 34.5 a* 5.45 a 121.0 a 39.9 a 192.7 a

Markaz-2001 33.2 a 5.27 b 97.6 b 38.0 b 189.8 b

NARC-02/2 30.4 b 4.63 c 81.2 c 34.2 c 189.1 b

LSD-values 1.7 0.09 4.3 0.5 0.8

P�G interaction NS NS NS NS NS

Coefficient of variation (%) 11.9 12.6 13.6 18.2 13.6

*Means in a column bearing different letter(s) have a statistically significant difference at P50.01. NSMeans have a statistically

nonsignificant difference at P50.01.

486 M. Rasheed et al.

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index and Leaf area index were calculated by

Equations (1) and (2):

Harvest index�Seed yield

Biological yield�100 (1)

Leaf area index� (number of plants m�2)

�(leaf count plant�1)�(average leaf area) (2)

Crop-growth rate (CGR) and net assimilation rate

(NAR) were calculated through the formulae of

Beadle (1987), as shown in Equations (3) and (4):

CGR(g m�2 day�1)�W2 � W1

t2 � t1

(3)

where,

W2�Dry weight m�2 of land area at second harvest

W1�Dry weight m�2 of land area at first harvest

t2�time corresponding to second harvest

t1�time corresponding to first harvest

NAR(g m�2 day�1)�TDM

LAD(4)

where,

TDM�Total dry matter

LAD � Leaf area duration, as determined by the

following Equation (5):

LAD�(LAI 1�LAI2)�(t2�t1)1=2 (5)

where,

LAI1�leaf area index at t1LAI2�leaf area index at t2t1�time of first observation

t2�time of second observation

For estimating the protein content in lentil seeds,

first the Kjeldahl analysis method was used to

determine total nitrogen (N) in the grains (Johnson

et al., 1985), then protein content (% w/w) was

estimated as 6.25�N.

Phosphorus analysis

Phosphorus contents in lentil grain and straw were

determined by taking 1.0 g of dried ground sample

in a digestion tube. Concentrated HNO3 (10 mL)

was added to the tube followed by the addition of 5

mL of concentrated HClO4 (70%). The ingredients

were digested in a digester until the colors cleared

up. The digested material was diluted to 25 mL

volume using distilled-deionized water (Ryan et al.,

2001). For P estimation, 1.0 mL of digested material

was taken into a 10-mL tube. Aqueous 2M HNO3

solution (2 mL) was added and the mixture was

diluted to 8 mL with distilled water. Thereafter,

1 mL of ammonium molybdate-ammonium vana-

date solution was added and the volume was made to

10 mL with distilled water. The tube was shaken and

allowed to stand for 20 minutes. The absorbance

was measured by spectrophotometer (Spectronic 2l)

at 430 nm and was compared with the absorbance of

standard phosphorus curve.

Data analysis

Data on plant parameters influenced by various

phosphorus levels and lentil genotypes were analysed

statistically by analysis of variance (Steel et al., 1997)

using statistical software MSTAT-C (Freed et al.,

1991). Data were analysed through two-factor fac-

torial completely randomized design for interaction

among treatments, and the means separation by

Tukey test (p50.01).

Table II. Effect of phosphorus on yield attributes of lentil genotypes.

Treatment Pods count

(# plant�1)

Seeds count

(# pod�1)

Pod weight

(g pod�1)

Seed weight

(g plant�1)

100-Seed weight

(g)

Phosphorus levels (kg ha�1)

0 (CK) 30.8 d* 1.75 d 1.18 d 2.59 d 1.87 d

40 34.9 c 1.81 c 1.48 c 4.11 c 1.96 c

60 38.1 b 1.85 b 1.75 b 5.35 b 2.07 b

80 42.0 a 1.95 a 2.08 a 6.64 a 2.18 a

LSD-values 2.6 0.02 0.03 0.22 0.04

Genotypes

G1 Masoor-93 39.8 a* 1.90 a 1.83 a 6.24 a 2.17 a

G2 Markaz-2001 37.3 a 1.85 b 1.68 b 4.52 b 2.05 b

G3 NARC-02/2 32.3 b 1.77 c 1.35 c 3.26 c 1.85 c

LSD-values 4.3 0.01 0.06 0.40 0.08

P�G interaction NS NS * NS NS

Coefficient of variation (%) 15.8 12.8 16.8 16.0 14.2

*Means in a column bearing different letter(s) have a statistically significant difference at P50.01. NSMeans have a statistically

nonsignificant difference at P50.01.

Lentil genotypes response to phosphorus 487

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Procedures for economic analysis were adopted

from CIMMYT (1988). Expenditure incurred on

P-fertilizer, and incomes of produce, were calculated

on the basis of market rates (GOP, 2006). The

following economic parameters were derived thro-

ugh the formulae shown in Equations (6)�(8):

Net return (NR)

�value of increased yield-cost of nutrient sources

(6)

Value cost ratio (VCR)�value of increased yield

}cost of nutrient sources

(7)

Relative increase in income (RII)

�(net income} income at control)�100 (8)

Results and discussion

Plant biometry

Lentil plant biometric parameters including shoot

length, count of branches, nodules count and

weight, and total growth period up to maturity

were measured; data are presented in Table I. There

was a highly significant difference (p50.01) among

three genotypes, with the highest values of all the

growth attributes in genotype Masoor-93, and the

lowest one that of NARC-02/2. The only nonsigni-

ficant difference was between Masoor-93 and

Markaz-2001 for shoot length, and between

Markaz-2001 and NARC-02/2 for maturity period.

Genetic variability and variable response of cultivars

to the prevalent environment were the main factors

for the difference in the growth of lentil cultivars

(Khan et al., 2002).

Application of phosphorus at different levels also

affected the growth of lentil genotypes significantly.

Each increment in P rate enhanced the growth

parameters significantly; however, the number of

nodules declined at the highest rate of P-fertilizer.

Balyan & Singh (2005) reported that phosphorus

application increased the nodulation. Higher P-rates

lengthened the period of crop maturity significantly.

Khan et al. (2006) also reported that P lengthened

the time of field maturity in lentil. The highly positive

growth response of lentil to all the applied P-levels

was mainly due to acute P-deficiency in soil. Rehman

and Barnard (1998) also recorded a promotional

effect of phosphorus on the growth traits of lentil.

Yield attributes

The yield attributes included the number of pods per

plant and their weight, seeds count per pod, seed

weight per plant, and 100-seed weight (Table II).

There were significant differences among cultivars

for all yield parameters, except that Masoor-93 and

Markaz-2001 had statistically similar pods count per

plant. Masoor-93 was statistically superior to the

other two cultivars for all the studied yield attributes;

and among the others NARC-02/2 gave the lowest

values. Differential response to environmental con-

ditions and variability in fruiting potential among the

cultivars were the reasons for differences in yield-

contributing plant parameters.

Phosphorus fertilization also affected the yield

parameters of lentil significantly. The rate of 80 kg

P ha�1 was statistically superior to lower rates,

which had significant differences among each other

for all the parameters (Table II). Yield attributes

were increased linearly with successive increase in

the rates of applied P. The positive response was due

to the fact that P improved the reproductive poten-

tial of the plants. Amanullah and Nawabzada (2004)

also reported the promotional effect of phosphorus.

Enhancement of yield parameters was due to the

increased supply of P, more nodules and N-uptake

by plant. Masauskas et al. (2008) related the seed

weight positively with yield increase under the

significant effect of P-application.

Grain yield

Seed yield is one of the most important and

phenomenal yield components which describe the

overall potential of the genotype. There were sig-

nificant differences among three cultivars with the

highest grain yield (1300 kg ha�1) of Masoor-93,

and the lowest yield of 957 kg ha�1 was from

NARC-02/2 9 (Figure 1). Masoor-93 gave a higher

yield due to the greater number of pods per plant

and seed weight per plant. The variable yield

potential of different lentil genotype has also been

Figure 1. Grain yield of lentil genotypes as influenced by various

phosphorus levels.

488 M. Rasheed et al.

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reported by Sadiq et al. (1998). Lentil genotypes

differ in their root traits (root length and root-hair

density), which significantly influence the plant

uptake of nutrients (Gahoonia et al., 2006). Geno-

types with prolific root-hair formation are superior in

the uptake of nutrients, so would have better growth

and yield.

Phosphorus is involved in a number of metabolic

functions and is especially important for grain

formation (Balyan & Singh, 2005); therefore, its

proper supply to the crops improves their yields. It is

needed in relatively large amounts by legumes for

growth and nitrogen fixation, and it was found to

increase leaf area, biomass, yield, nodulation, and

nutritional quality in peas (Yemane & Skjelvag,

2003). In our study, different levels of P also affected

the seed yield significantly. The seed yield increased

linearly with each successive increment of P from

40�80 kg ha�1 over control with average corre-

sponding values of 797, 951, and 1119 kg ha�1. The

possible and logical reason was that yield compo-

nents of the crop were highly improved with the

applied P, and that they contributed towards in-

creased seed yield. Enhanced seed yield of lentil by

increasing P-levels was also reported by Kumar and

Kumar (2006). Improved fertilization enhances the

crop-grain yields due to increased availability and

uptake of macro- and micronutrients (Ahmad et al.,

2008; Shaheen et al., 2009).

Harvest index

Harvest index is an indication of the physiological

ability of a cultivar to convert the dry matter into

economic yield. Harvest index of lentil varied sig-

nificantly among three genotypes (Figure 2). The

highest value of harvest index (45.8) was given by

Masoor-93 and the lowest one (41.3) by NARC-02/2

genotype. Harvest index was also affected signifi-

cantly by different phosphorus levels, bearing average

maximum value of 43.5 with 80 kg ha�1 against the

average lowest (36.4) in control treatment.

Leaf area index

As seen from Figure 3 for leaf area index (LAI) of

lentil, there were highly significant differences among

the treatment means of cultivars as well as that of P-

levels. The highest LAI was attained by Masoor-93

and the lowest in NARC-02/2, showing respective

average values of 2.19 and 1.65, respectively. Among

the P-levels the highest value for LAI was observed at

80 kg P ha�1, and all the levels had significant

differences with each other. The average lowest

value of 1.57 LAI was found in control without

P-application. These results are supported by the

findings of Khan (2002) who reported that enhanced

P-application increased the LAI of chickpea.

Crop-growth rate

The highest crop-growth rate (CGR) was attained by

Masoor-93 with an average value of 4.70 g m�2

day�1 and the average lowest (2.95 g m�2 day�1)

was in NARC-02/2 (Figure 4). The increase in CGR

might be attributed to the increased nodulation in

Masoor-93 as compared with the other two cultivars.

Crop-growth rate was also influenced significantly

by different P-levels. It increased linearly with each

successive increment of P-level, showing the corre-

sponding average values of 3.22, 4.01, and 5.05 g

m�2 day�1 against the control average (2.62 g m�2

day�1). The interaction of genotype�phosphorus-

rate treatments was also statistically significant at

P50.05. Masoor-93 at 80 kg ha�1 performed the

best while NARC-02/2 in control (P0) gave the

lowest CGR-value. Enhanced CGR might be due

to the greater number and weight of nodules per

plant causing an increased supply of N to the plant.

Figure 3. Leaf area index of lentil genotypes as influenced by

various phosphorus levels.

Figure 2. Harvest index of lentil genotypes as influenced by

various phosphorus levels.

Lentil genotypes response to phosphorus 489

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This phenomenon resulted in better utilization of

P and other nutrients that promoted crop growth.

Khan (2002) reported that P-application increased

the crop-growth rate in chickpea.

Net assimilation rate

The net assimilation rate (NAR) differed signifi-

cantly among different cultivars, being maximum

(5.83 g m�2 day�1) in Masoor-93 (Figure 5).

The average lowest NAR (3.61 g m�2 day�1) was

in NARC-02/2 genotype. Different rates of P-

application also affected NAR significantly, being

the average highest (5.48 g m�2 day�1) in control

without P. The NAR decreased specifically with each

increment in P-level, showing values of 4.82, 4.26,

and 3.66 g m�2 day�1, respectively. The highest net

assimilation rate in control plot was due to lower LAI

and CGR which have an inverse relationship with

NAR. These results are supported by the findings of

Khan (2002).

Grain protein content

Seed protein concentration differed significantly

among cultivars, having the average highest value

(25.5%) in Masoor-93 and the average lowest

(21.4%) in NARC-02 (Figure 6). Masoor-93 is

inherently more efficient in protein synthesis than

are the other two cultivars (Sadiq et al., 1998).

Protein concentration was also affected significantly

by different rates of P-fertilizer. Protein contents in

grains increased linearly with each increment of P

over control, showing average values of 22.79, 24.87,

and 26.80% at 40, 60, and 80 kg P ha�1, respec-

tively. Increase in protein contents might be due to

the higher number of nodules per plant and their

nitrogen-fixing ability with increased P-application.

Guhey et al. (2000) reported that the increased P-

levels improved the protein contents of crop seeds.

Albayrak et al. (2008) also obtained the highest dry-

matter yield and crude protein content (%) of

pastures from the N- and P-fertilizer treatments.

Phosphorus content

Phosphorus contents in lentil grain and straw were

significantly influenced by different rates of phos-

phorus and also varied among the genotypes (Table

III). The highest concentration of phosphorus in the

grains (0.37%) was found with 80 kg P ha�1,

followed by 60 kg P ha�1 which was statistically at

par with 40 kg P ha�1. The lowest P-content was

recorded in P0 (control) treatment. Contrarily, the P-

contents in the straw were statistically similar at P-

application of 60 and 80 kg P ha�1, being superior to

that with control and 40 kg P ha�1, which also

differed nonsignificantly with each other. Singh et al.

(2005) found that the P-concentration in the lentil

grain and straw was increased at enhanced rates of P-

application. Among the three cultivars, significantly

higher P-content in grain (0.36%) was found in V1

Figure 4. Growth rate of lentil genotypes as influenced by various

phosphorus levels.

Figure 5. Net assimilation rate of lentil genotypes as influenced by

various phosphorus levels.

Figure 6. Grain protein content of lentil genotypes as influenced

by various phosphorus levels.

490 M. Rasheed et al.

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Table III. Effect of phosphorus rates on the phosphorus content (%) in lentil genotypes.

Phosphorus content (%) in lentil grain Phosphorus content (%) in lentil straw

Treatment

(kg P ha�1) V1 (Masoor-93) V2 (Markaz-2001) V3 (NARC-02/2) Mean* V1 (Masoor-93) V2 (Markaz-2001) V3 (NARC-02/2) Mean*

0 (CK) 0.32 NS 0.30 0.29 0.30 c 0.08 NS 0.08 0.07 0.08 b

40 0.35 0.32 0.31 0.33 b 0.09 0.08 0.07 0.08 b

60 0.37 0.34 0.32 0.34 b 0.10 0.09 0.08 0.09 a

80 0.40 0.37 0.35 0.37 a 0.11 0.09 0.08 0.09 a

Mean* 0.36 a 0.33 b 0.32 b 0.10 a 0.09 b 0.08 c

*Means in a column/row bearing different letter(s) have a statistically significant difference at P50.01. NSMeans have a statistically nonsignificant difference at P50.01.

Table IV. Economic output (in US$) of using phosphorus fertilizer for lentil production.

Treatment (kg P ha�1) Income from lentila Income over control

Cost of phosphorus

fertilizerb Net return Value-to-cost ratio

Relative increase

in income

0 (CK) 409.50 � � � � �40 502.11 92.61 37.2 55.41 2.49 122.6

60 599.13 189.63 55.8 133.83 3.40 146.3

80 704.97 295.47 74.4 221.07 3.97 172.2

aPrice of lentil grain�US$ 0.63 kg�1. bPrice of phosphorus fertilizer�US$ 0.93 kg�1 (GOP, 2006).

Len

tilgen

otypes

respon

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phosp

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(Masoor-93) as compared with the other two geno-

types, which were statistically at par. However, P-

contents in the straw of the three genotypes had

significant differences, having the highest value in

Masoor-93 and the lowest in NARC-02/2. Signifi-

cant genotypic differences for P-contents in the

shoots of lentil among various cultivars were also

reported by Gahoonia et al. (2006).

Economics of phosphorus use

The economics of P-fertilizer use in lentil at various

rates was calculated in terms of net return (NR),

value-to-cost ratio (VCR), and relative increase in

income (RII) as shown in Table IV. The income over

control (no P-application) from the lentil grain

increased with each increment of P. Although the

expenditure on fertilizer was increasing at elevated

rates, still the net returns were considerably en-

hanced with successive rates of P-fertilizer. Similarly,

the highest figure of value-to-cost ratio (3.97) was

obtained at 80 kg P ha�1. The highest RII (US$

172.2) was also found with the highest rate of P-

fertilizer. Jilani et al. (2007) reported that the sole

use of NPK fertilizers in maize, although they gave

the highest total income compared with integrated

use of organic, bio and chemical fertilizers, however,

the NR-, VCR-, and RII-values became less due to

the higher cost of NPK fertilizers.

Generally, lentil cultivars reflected a genetic varia-

bility in response to phosphorus nutrition under

rain-fed cultivation. Masoor-93 was found the best

with respect to growth and yield traits, while NARC-

02 gave a poor response. Phosphorus application

was able to improve the growth and yield of lentil

genotypes, so each increment in P rate produced

significant results. Phosphorus also increased protein

and P-contents in lentil. It is inferred that, under

rain-fed conditions, higher yields of lentil could be

ensured through the selection of appropriate geno-

type like Masoor-93 with higher application of P.

Further, the use of P-fertilizer at higher rates is

economically feasible with respect to NR-, VCR-,

and RII-values. Pronounced genetic response of

lentil to phosphorus suggests that nutrient-efficient

germplasm can be achieved through breeding pro-

grammes for enhancing its production.

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