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EXECUTIVE COUNCIL : 2017-2020

Zone I : Dr Brij Nandan, SKUAST, Samba (J&K)

Zone II : Dr C Bharadwaj, IARI, New Delhi

Zone III : Dr Rajib Nath, BCKV, Kalyani

Zone IV : Dr Baldev Ram, AU, Kota

Councillors

Dr Puran Gaur, ICRISAT, HyderabadDr Shiv Kumar, ICARDA, MoroccoDr BB Singh, GBPUA&T, PantnagarDr DK Agarwal, ICAR-IISS, MauDr Sarvajeet Singh, PAU, LudhianaDr J Souframanian, BARC

Chief PatronDr Trilochan Mohapatra

PatronDr JS Sandhu

Co-patronDr NP Singh

Zone V : Dr DK Patil, Badnapur

Zone VI : Dr P Jagan Mohan Rao, RARRS, Warangal

Zone VII : Dr P Jayamani, TNAU, Coimbatore

Zone VIII: Dr AK Parihar, ICAR-IIPR, Kanpur

PresidentDr NP Singh

SecretaryDr PK Katiyar

Joint SecretaryDr Jitendra Kumar

TreasurerDr RK Mishra

Vice PresidentDr Guriqbal Singh

Editors

Editor-in-ChiefDr CS Praharaj

The Indian Society of Pulses Research andDevelopment (ISPRD) was founded in April 1987 with thefollowing objectives: To advance the cause of pulses research To promote research and development, teaching and

extension activities in pulses To facilitate close association among pulse workers

in India and abroad To publish “Journal of Food Legumes” which is the

official publication of the Society, published four timesa year.

Membership : Any person in India and abroad interestedin pulses research and development shall be eligible formembership of the Society by becoming ordinary, life orcorporate member by paying respective membership fee.

Membership Fee Indian (Rs.) Foreign (US $)Ordinary (Annual) 500 40Life Member 5000 400Admission Fee 50 10Library/ Institution 5000 400Corporate Member 7500 -

INDIAN SOCIETY OF PULSES RESEARCH AND DEVELOPMENT(Regn. No. 877)

The contribution to the Journal, except in case of

invited articles, is open to the members of the Societyonly. Any non-member submitting a manuscript will berequired to become annual member. Members will beentitled to receive the Journal and other communicationsissued by the Society.

Renewal of subscription should be done in Januaryeach year. If the subscription is not received by February15, the membership would stand cancelled. Themembership can be revived by paying readmission fee ofRs. 50/-. Membership fee drawn in favour of Treasurer,Indian Society of Pulses Research and Development,through D.D. may be sent to the Treasurer, IndianSociety of Pulses Research and Development, ICAR-Indian Institute of Pulses Research, Kanpur208 024, India. In case of outstation cheques, an extraamount of Rs. 50/- may be paid as clearance charges.

Dr Aditya Pratap, ICAR-IIPR, KanpurDr Narendra Kumar, ICAR-IIPR, KanpurDr Naimuddin, ICAR-IIPR, KanpurDr Meenaal Rathore, ICAR-IIPR, KanpurDr Archana Singh, ICAR-IIPR Regional Station, BhopalDr Abhishek Bohra, ICAR-IIPR, Kanpur

Journal of Food Legumes(Formerly Indian Journal of Pulses Research)

Vol. 30 (1) January-March 2017

CONTENTSRESEARCH PAPERS

1. Genetic diversity analysis among local bean (Phaseolus vulgaris L.) cultivars using RAPD markers 1

Nirja Thakur, Subash Chand Parmar and Amarjit K Nath

2. PCR based race identification of Fusarium oxysporum f. sp. ciceri using molecular markers 6

KN Poornima, PR Sabaale, Prakash G Patil, Alok Das, KR Soren and NP Singh

3. In vitro plant regeneration in pigeonpea [Cajanus cajan (L.) Millsp] using various explants 11

Nandha Abhijeeta K and Madariya Rajesh B

4. Inheritance of resistance to Mungbean Yellow Mosaic Virus (MYMV) in intra and inter-specificcrosses of Vigna 15

Basavaraja T, Niranjana Murthy, Shashi Kumar P and Satheesh Naik SJ

5. Identification of MYMV resistant and photo-thermo insensitive lines in mungbean 20

A Nishant Bhanu, MN Singh and K Srivastava

6. Estimation of genetic variability and inter-relationships of quantitative traits for improvementof kabuli chickpea (Cicer arietinum L.) 25

Neha Dhuria and Anita Babbar

7. Genetic variability for selective tolerance to imazethpyr in chickpea (Cicer arietinum L.) 30

K Bhanu Rekha, V Jayalakshmi, T Srinivas, M Sudha Rani and P Umamaheswari

8. Effect of integrated nutrient management in soybean [Glycine max (L.) Merill] under temperatecondition 36

MA Aziz, Narinder Panotra, Tahmina Mushtaq, Tahir Mushtaq, IA Jehangir and Tajamul Islam

9. High temperature stress and its implication on growth, biomass and yield of normal and lateseeded fieldpea genotypes 41

Vijay Laxmi and GP Dixit

10. Physiological and biochemical adaptation of chickpea (Cicer arietinum L.) genotypes undermoisture stress 45

Vaishali Sharma, Jagmeet Kaur, Sarvjeet Singh, Inderjit Singh, Satvir Kaur and Norah Johal

11. Beet army worm, Spodoptera exigua (Hubner): An emerging pest of chickpea inWestern Maharashtra 50

AP Chavan, SR Kulkarni, RV Datkhile and SK Patil

12. Economics of rajmash cultivation in Eastern Jammu region 54

Sanjeev Kumar, SP Singh, Anil Bhat and Manish Kumar Sharma

13. Impact of cluster front line demonstrations on productivity and profitability of chickpea(Cicer arietinum L.) 57

AK Mauriya, Vinod Kumar, Anita Kumari, Pankaj Kumar, Mamta Kumari and MZ Hoda

SHORT COMMUNICATIONS

14. Effect of maleic hydrazide on inducing dormancy in green gram (Vigna radiata L.) 61

PM Gadhave, VR Shelar and BS Munde

15. Characterization of cowpea [Vigna unguiculata (L.) Walp.] germplasm 64

S Anish, R Usha Kumari and C Parameswari

16. Stability analysis for seed yield in blackgram (Vigna mungo L. Hepper) 66

G Vijay Kumar, M Vanaja, P Vagheera, P Sathish, K Premkumar, B Sarkar and M Maheswari

List of Referees for Vol. 30(1) 69

Journal of Food Legumes 30(1): 1-5, 2017

Genetic diversity analysis among local bean (Phaseolus vulgaris L.) cultivarsusing RAPD markersNIRJA THAKUR, SUBASH CHAND PARMAR and AMARJIT K NATH

Department of Biotechnology, Dr YS Parmar University of Horticulture and Forestry, Nauni, Solan, HimachalPradesh, India; E-mail: [email protected](Received: May 28, 2016; Accepted: November 20, 2017)

ABSTRACT

Random amplified polymorphic markers were used toevaluate genetic variations among nine bean cultivars(Phaseolus vulgaris L.) of Kinnaur district, Himachal Pradesh.Thirty five polymorphic RAPD markers generated 230 bands.Among these, 209 bands were polymorphic (90.86%) and 45were unique. The primer OPA09 gave highest polymorphicinformation content (PIC) value of 0.90 while primer OPA16 had lowest PIC value (0.58). Resolving power was 20 forOPA-11 and 106 for OPP-16. Jaccard’s coefficients basedgenetic similarity varied from 0.32-0.65. UPGMA basedclustering patterns divided cultivars into two main groupsand subgroups.

Key words: Common bean, Polymorphism, RAPD markers

The common bean is one of the most importantlegume crop worldwide (Anonymous 2009). It is majorsource of micronutrients e.g., iron, zinc, thiamin and folicacid (Pennington and Young 1990, Broughton et al. 2003).The annual global bean production is approximately 12million metric tons, with 5.5 and 2.5 million metric tons alonein Latin America Caribbean (LAC) and Africa, respectively(Broughton et al. 2003, Anonymous 2012a). The highestproducer is India at more than 4 million metric tons per year(Anonymous 2012b). Thus development of improvedcultivars is one of the important objectives of Indianbreeding program. However, due to lack of propercharacterization of genetic diversity, it could not be usedsystematically in breeding programs.

Classical methods based on morpho-agronomic traitshave been used to characterize genetic diversity amongcommercial cultivars, landraces and wild cultivars.Although, morphological data are easy to use foridentification of genotypes, the number of distinctivecharacteristics is limited. Moreover, agronomiccharacteristics are often multi-genic and their expression iseasily influenced by the environment. DNA markersdeveloped to study genetic diversity and crop evolutionare considered to be better as compared to morphologicmarkers (Burle et al. 2010). They can reveal differencesamong genotypes at DNA level and provides direct, reliableand efficient tool for germplasm characterization,conservation and management. The molecular markers,including RFLP (restriction fragment length polymorphism),RAPD (random amplified polymorphic DNA) and AFLP

(amplified fragment length polymorphism) have beenexplored in common bean diversity studies. RAPDapproach using arbitrary primers requires only nanogramquantities of template DNA, no radioactive probes and isrelatively simple as compared to other techniques. RAPDand AFLP markers have been used to investigate geneticvariability within landraces of common bean (Ojuederie etal.2014, Ariyarathna et al. 2013). Microsatellite markers havebeen used to study the genetic variability and gene poolidentity among common bean genotypes (Zhang et al.2008). Newly discovered techniques like Td-DAMD-PCR,Td-SSR and CAPS-microsatellite have also been used tostudy bean diversity (Ince and Karaca 2011). Informationon biodiversity studies using DNA markers in local commonbean cultivars of Kinnaur district of Himachal Pradesh islacking. Therefore aim of present study was to assess thegenetic diversity among the local common bean cultivarsusing RAPD markers.

MATERIALS AND METHODS

Plant material: Local bean cultivars viz., Luxmi, Contender,Kanchan, Kaju, Triloki, Baspa, Jawala, Kailash and Capsulewere used to study the genetic diversity. The seeds ofthese cultivars were procured from Vegetable ResearchStation, Kalpa, Kinnaur district, Himachal Pradesh.Isolation of genomic DNA: Genomic DNA was isolatedfrom young leaves of plants grown in pots [by addinginsoluble polyvinylpyrollidone (PVP) in tender leaves (10%(w/w)] by the method of Doyle and Doyle (1987). DNA waspurified by successive RNase treatment followed by phenol:chloroform extraction. The DNA pellet was washed with70% ethanol, vacuum dried and dissolved in of TE buffer200 µl depending upon its yield. These aliquots of DNAwere stored at -200C for further use. The quality of DNAwas checked by calculating the ratio of absorbance at 260nm and 280 nm, using a UV/VIS Spectrophotometer. Todetermine DNA concentration, an aliquot of DNA sampleswere suitably diluted and absorbance (A) was determinedat 260 nm.PCR Amplification and Gel Electrophoresis: The DNAsamples were amplified using PCR as described by Williamset al. (1990). Forty arbitrary 10-mer primers were used forPCR amplification. The polymerase chain reaction wasperformed in a reaction volume of 20 µl contained 11.7 µl ofsterile distilled water, 2 µl Taq DNA polymerase buffer (1X),

2 Journal of Food Legumes 30(1), 2017

1 µl MgCl2 (2 mM), 2 µl dNTPs (1 mM), 0.3 µl Taq DNApolymerase (1 U), 2 µl random primer (10 pmol) and 1 µlgenomic DNA (50-100 ng). All the samples were given initialdenaturation at 94ºC for 5 minutes in a thermal cycler. Fortyfive PCR cycles were carried out for OPA series primers and42 cycles for OPP series primers. Each cycle consisted of30 seconds of denaturation at 94ºC, 1 minute of annealingat 35ºC for OPP series primers and 37ºC for OPA seriesprimers, 2 minutes of extension at 72ºC and a final extensionof 7 minutes at 72ºC. PCR products were allowed to standat 4ºC for 5 minutes. The amplification products wereseparated on 1.2% agarose gel. Gene Ruler TM, 100bp-3kbladder was used as standard and the gel was run at 65 V.The image of the amplified DNA was using geldocumentation system.Data analysis: Each amplified product was scored for theirpresence or absence. Co-migrating bands were consideredto represent the same locus and thus treated as the sameband while scoring. Presence of an amplified product wasdesignated as ‘1’ and absence was marked as ‘0’. Intensityof the bands was not taken into consideration while scoring.A pair wise similarity index was constructed using Jaccardcoefficients, it was subjected to UPGMA cluster analysisand a dendrogram was constructed using NTSYS-pc,version 2.02h software (Rohlf 1998). Polymorphicinformation content (PIC value) for each primer wascalculated as described by Anderson et al. (1993). Thepower of each primer to distinguish among common beancultivars was evaluated by resolving power (Rp) (Prevostand Wilkinson 1999).

RESULTS AND DISCUSSION

The CTAB method has been successfully used forDNA extraction from common bean leaves (Kumar et al.2014, Cabral et al. 2011). However, insoluble PVP duringDNA extraction from leaves of bean seedlings has not beenused by other workers. Razvi et al. (2013) isolated genomicDNA from common bean leaves by using modified CTABmethod. Sadeghi and Cheghamirza (2012) also usedmodified CTAB method for genomic DNA extraction fromcommon bean leaves. Molecular characterization of localbean cultivars was investigated using 40 random decamerprimers. DNA polymorphism was shown by 35 primers andthe primer generated a unique set of amplification productsranging from 102 bp (OPA-02) to 1950 bp (OPP-04) (Fig.1 &Fig. 2). Number of bands for each primer ranged from 3(OPA-10, OPA-13 and OPA-16) to 12 (OPA-19). Totalnumbers of bands amplified were 230, out of which 209were polymorphic and 21 were monomorphic (Table 1).Percentage of polymorphic bands ranged from 76.4% to82.4% and 45 unique bands were obtained. Specific RAPDmarkers obtained for cultivars could be used for theiridentification. Maximum number of unique bands wasobtained for Triloki and Baspa cultivars and minimumnumber for Contender cultivar. Ariyarathna et al. (2013)

used 5 RAPD primers (OPA-1, OPA-08, OPD-03, OPB-17and OPG-05) to investigate genetic diversity among 30 beangenotypes, which generated 18 polymorphic bands andlevel of polymorphism was 20 %. Razvi et al. (2013) used15 primers to discriminate 13 common bean genotypes, outof which 7 (OPA-01, OPA-02, OPA-03, OPA-10, OPA-11,OPA-13 and OPA-15) showed polymorphism. They reported63 polymorphic bands with 96.62 % polymorphism. Filimonet al. (2011) used 8 RAPD primers to evaluate geneticdiversity among 8 common bean (Phaseolus vulgaris L.)cultivars, out of which 4 primers (OPD-08, OPG-03, OPG-12and OPY-20) showed polymorphism. They obtained 33bands out of which 17 were polymorphic and 16monomorphic, showing 48.84% polymorphism. Szilagyi etal. (2011) obtained 56 DNA bands using 4 primers (OPA-17, OPG-05, OPG-06 and OPG-14) from 20 common beancultivars out of which 29 bands were polymorphic, showing51.78% polymorphism. Mavromatis et al. (2010) obtainedtwo poly morphic bands out of 160 bands using 20 randomprimers (OPB-07, OPB-10, OPB-16, OPB-17, OPC-01, OPC-03, OPC-04, OPC-05, OPC-06, OPC-07, OPC-08, OPC-09,OPC-10, OPD-11, OPD-20, OPE-14, OPE-06, OPF-04, OPF-11 and OPF-19) to assess genetic diversity among mainlocal landraces and commercial cultivars of Phaseolusvulgaris L. cultivated in Greece. Jaccard’s similarity

Figure 1. RAPD profile using primer OPA-18 and OPA-19(M-marker, 1-Luxmi 2-Contender 3-Triloki 4-Capsule5-Kanchan 6-Kaju 7-Baspa 8-Kailash 9-Jawala)

Thakur et al. : Genetic diversity analysis among local bean (Phaseolus vulgaris L.) cultivars using RAPD markers 3

coefficient ranged from 0.32 to 0.65 indicating sufficientgenetic diversity among bean cultivars used in presentstudies. Low similarity value was observed between Trilokiand Jawala cultivars and highest between Kailash andJawala cultivars. Razvi et al. (2013) reported similaritycoefficient values of 27.72-82.35 in 13 bean genotypes byusing Dice coefficient. Filimon et al. (2011) calculatedgenetic similarity by Nei and Li coefficient in 8 commonbean cultivars and reported it to vary greatly (60% - 96%).Mavromatis et al. (2010) reported Jaccard’s similarity valuesin common bean genotypes to range from 0.84-0.98. Jose etal. (2009) reported Jaccard’s similarity coefficient in commonbean to range from 0.50 to 0.95. In present studies, PICvalue ranged from 0.58 (OPA-16) to 0.90 (OPA-09) andresolving power ranged from 20 (OPA-11) to 106 (OPP-16)were obtained. Sadeghi and Cheghamirza (2012) reportedmean PIC value for RAPD primers in 21 common bean

genotype to be 0.382. Blair et al. (2006) calculated PIC valuefor 129 microsatellite markers in 44 common bean genotypesand reported it to range from 0.446-0.594. Buso et al. (2006)also calculated PIC value in 85 representative accessionsof bean from gene bank and it ranged from 0.23 to 0.80.

Cluster analysis of RAPD data obtained duringpresent studies was used to construct dendrogram usingUPGMA cluster analysis (Rohlf 1998). This resulted in twomain clusters viz., A and B. The cluster A was subdividedfurther into 2 sub-clusters C and D (Fig. 3). Sub cluster Cwas further divided into 2 sub-clusters E and F, whichincluded Luxmi and Contender cultivars, showing 72 %similarity with each other. Sub cluster D included only Trilokicultivar, showing 66 % similarity with Luxmi and Contender.Cluster B was also divided further into 2 sub-clusters Gand H. The sub-cluster G had further 2 sub-clusters I and J.Cluster I included Capsule and Kanchan cultivars showing71 % similarity with each other. Cluster J included Kaju andBaspa cultivars, which showed 74 % similarity with eachother. Kailash and Jawala were included in a separate clusterH and they showed maximum similarity of 79 %. Both clustersA and B merged into a single cluster at 39% similarity.Genetic similarity was also compared with morphologicaltraits like seed colour and seed size but these charactersdid not seem to be related with molecular analysis.Mavromatis et al. (2010) also found seed morphologicalcharacteristics and agronomic performance in main locallandraces and commercial cultivars of Phaseolus vulgaris

Table 1. Summary of RAPD amplified products from bean cultivars

Description Luxmi Contender Triloki Capsule Kanchan Kaju Baspa Kailash Jawala Number of bands scored 105 89 109 110 104 119 102 109 105 Number of monomorphic bands 21 21 21 21 21 21 21 21 21 Number of polymorphic bands 84 68 88 89 83 98 81 88 84 Average number of fragments per primer 3.0 2.54 3.11 3.14 2.97 3.4 2.91 3.11 3.0 Average number of polymorphic bands per primer 2.4 1.94 2.51 2.54 2.37 2.8 2.31 2.51 2.4 Percentage of total polymorphic bands 80.0 76.4 80.7 80.9 79.8 82.4 79.4 80.7 80.0 Number of unique bands 5 3 8 4 4 4 8 5 4

Figure 2. RAPD profile using primer OPP-06 and OPP-17(M-marker, 1-Luxmi 2-Contender 3-Triloki 4-Capsule5-Kanchan 6-Kaju 7-Baspa 8-Kailash 9-Jawala) Figure 3. RAPD dendrogram using Jaccard’s coefficient


L. of Greece not to be related with genetic similarity. Razviet al. (2013) constructed dendrogram based on RAPD datausing UPGMA (Dice coefficient) that divided common beangenotypes into 3 clusters in which cluster-1 containedmaximum number of 7 genotypes, cluster-2 contained 5genotypes and cluster-3 contained only 1 genotype. Filimonet al. (2011) constructed dendrogram based on Nei and Li(1979) that divided 8 common bean cultivars into two mainclusters (A and B). Cluster A comprised of all Romanianbean cultivars while cluster B contained all Columbiancultivars. Biswas et al. (2010) constructed a dendrogrambased on genetic distance in 14 French bean genotypes asdescribed by Nei’s (1972) and obtained 2 main clusters.The findings of the present investigations indicated highgenetic diversity in local bean cultivars of Kinnaur districtof Himachal Pradesh, which could be used in bean breedingprograms. RAPD markers were found to be effective inassessing diversity. Specific RAPD markers obtained forcultivars could be used for their identification.

ACKNOWLEDGEMENTS

Financial support by University Grant Commissionin the form of major research project F.No-41-531/2012 (SR)dated 17-07-2012 is gratefully acknowledged.

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PCR based race identification of Fusarium oxysporum f. sp. ciceri using molecularmarkersKN POORNIMA, PR SABAALE, PRAKASH G PATIL, ALOK DAS, KR SOREN and NP SINGH

ICAR-Indian Institute of Pulses Research, Kanpur-208024, India; E-mail: [email protected](Received: January 13, 2017; Accepted: March 14, 2017)

ABSTRACT

The present study deals with molecular characterization ofsix different races of Fusarium oxysporum f. sp. ciceri (Foc)using different marker techniques, like gene specific ITS(Inter transcribed spacers), SCAR (Sequence characterizedamplified region) and CAPS (Cleaved amplified polymorphicsequences. The ITS primers FDP 9 and FDP14 differentiatedrace 4 and race 2, respectively. The SCAR primers FocR0-M15f/R and FocR5-L10f/R identified 900bp bands for race2and race 5 among all races. Restriction analysis of theundifferentiating alleles obtained by FDP 25 ITS primer inall the races depicted a 500bp unique band in race 4, whichcould be used as CAPS marker in Foc race identification.Multiplexing of positive ITS primers was done in order tofacilitate race identification based on more than one loci ofthe Foc genome. The above efforts facilitate a high-throughput DNA fingerprinting of Foc races that becomesvery essential during plant-pathogen interaction studies andplant breeding efforts emphasized upon resistance responsein chickpea genotypes.

Key words: CAPS, Fusarium wilt, ITS, SCAR

Chickpea (Cicer arietinum L.) is an important pulsecrop grown all around the world. It being third mostimportant grain legume in the world confines 90% of itsproduction and productivity to Asia (Joshi et al. 2001).Other than Asia it is cultivated in North and Central America,Mediterranean region, the west Asia, Northern Africa andEastern Africa. It is mostly grown as a rainfed crop afterrainy season in the semi-arid tropics.

Chickpea is used as a source of protein by people inthe developing countries where they depend upon lowpriced food for meeting dietary requirements. This cropplays an important role in sustaining soil productivity byfixing upto 141kg nitrogen per ha (Ahlawat et al. 1981).India is the largest producer of chickpea and accounts for68.47% of the total area and 67.02% of total globalproduction. This represents 35.16% of total pulse area and50.34% of total pulse production in India (Ghosh et al.2015). Biotic and abiotic stresses have recurrently affectedthe productivity of this crop. Among the biotic stresses,chickpea wilt caused by Fusarium oxysporum f.sp. ciceri(Foc) has witnessed losses upto 40 % in the world and 10-

15% annually in India (Ghosh et al. 2015). The occurrenceand severity has been found to be directly proportional tothe density of pathogen population (Bhatti and Kraft 1992).

Two pathotypes (yellowing and wilting) and eightpathogenic races (races 0,1A, 1B/C, 2, 3, 4, 5 and 6) of Fochave been described to date (Casas et al. 1985). Theprimitive methods of race identification involved differentialscreening of chickpea wherein we look for pathogenecitygroups followed by identification of races. This method isvery time consuming, laborious and influenced by variousenvironmental parameters such as temperature and humidity(Haware and Nene 1982). Although, there are several setsof differential cultivars available, some of the differentiationis based on intermediate reactions (Sharma et al. 2005). Toovercome these problems, several other approaches havealso been attempted. Previously, serological andelectrophoretic variability of proteins isolated from IndianFoc races has been studied by Desai et al. (1992a). Basedon antigens, they identified close relationships betweenraces 1, 2 and 3, while race 4 was different. Biochemicalanalysis of the four Foc races has revealed variation intotal sugar and amino acid content for race 3 as comparedto races 1, 2 and 4 (Desai et al. 1992b). Protein based markershave been cumbersome to analyze and hence DNA-basedmarkers have gained importance these days. Races 0, 1B,1C, 5 and 6 were distinguished by RAPD fingerprinting(Jiménez Gasco et al. 2001) and sequence characterizedamplified regions (SCAR) markers have been developedfor races 0 and 6, while a race 5 specific identification assayhas been developed using touchdown PCR (Jiménez-Gascoand Jiménez-Diaz 2003). Dubey et al. 2010 have performedITS-RFLP fingerprinting and found Foc specific markersbased on ITS region. The markers produced an amplicon of292bp and were validated against the isolates of thepathogen collected from different locations of India.

With the gaining importance of Fusarium wilt diseaseof chickpea and use of DNA markers for pathogenidentification, the present study envisages to differentiatethe six races of Foc mostly found in India. Additionally,CAPS and multiplex PCR profiles have been used todifferentiate the different races of Foc.

Poornima et al. : PCR based race identification of Fusarium oxysporum f. sp. ciceri 7


The mycelium of single spore cultures of 6 races ofFusarium oxysporum f.sp. ciceri was cultured at ICAR-IIPR, Kanpur using PDA (Potato dextrose agar). The colonymorphology of all the races was recorded. High quality andquantity DNA was extracted from the mycelium of Fusariumoxysporum f.sp. ciceri using the protocol described byJimenez et al. (2003). About 47 primer pairs including ITSspecific and SCAR markers previously reported were usedto fingerprint the races of Foc (Table 3). The amplificationreaction was carried out in a 0.2 ml thin walled PCR tubewith total volume of 20 µl reaction mixture for each sample.The mixture containing reagent include template DNA(50ng), dNTP (20pM) 0.5µl, 10X Taq Buffer 2 µl, Primer(10pM) (Forward+Reverse) 2 µl, Taq Polymerase (1U) 0.5µl, Milli Q Water 14 µl. PCR was run using the program asunder: Pre denaturation at 940C for 5 min, denaturation at940C for 2 min, Annealing at 52-550C for 1 min, Elongationat 720C for1 min, Final Extension 720C for 10 min and holdingtemperature at 40C. The PCR program as discussed byJimenez et al. 2003 was followed for SCAR primers. 1.2%agarose gels were prepared to run and visualize the amplifiedproducts by gel electrophoresis. For analyzing thevariations within the amplified products the PCR clean-upwas done as per the manufacture’s Sure Extract spin PCR/Gel Extraction Kit.

The purified amplicons were used for restrictiondigestion using EcoRI and Hind III using the followingcomponents: 1µl-DNA (concentration1µg/µL) 2µl-10 xbuffer, 1µl-Restriction enzyme, 16µl-Sterile distilled water,incubated at 370C for 1hour. The restricted fragments wererun on 1.5% agarose electrophoresis gel for further analysisof the ITS-RFLP otherwise known as CAPS marker.Multiplex PCR was done using three primer sets asrepresented in Table 2. Equal concentration (25 pM) of eachprimers was used in the PCR master mix (Faria et al. 2012)with final volume of 50µl.


Pure cultures of Fusarium oxysporum f. sp. ciceri races:Single spore cultures of six different races of Foc grown inPDA developed a cottony velvety mat that varied in itscolour among the different races as shown in Figure 1. Thisis in accordance with the results of Ortiz et al. (2011) whohave described Foc isolates of group 4 and 5 to be cottonyvelvety. Race 1 had a yellowish tinge, race 2 and 5 werefound to be creamish, pinkish tinge in race 3 and 4 and aviolet tinge in race 6. Variation in colour on PDA brothmedium for Foc races has also been reported (Groenewaldet al. 2006). The aerial mycelium is white and can change toa variety of colors -from violet to dark purple depending onthe strain of F. oxysporum. Environmental conditions suchas growth medium, light and temperature can cause pigmentproduction in F. oxysporum (Rodrigues and Menezes 2005).

High quality and quantity (2µg/µl) of DNA was obtainedby method described earlier by Jimenez et al. (2003). All themolecular analysis was amenable using the isolated DNA.Identification of polymerphism using different primers:Different marker systems have been employed in racialdifferentiation of pathogenic fungi. Similarly a set of 29primers targeting the inter transcribed spacer regions andelongation factors was amplified by polymerase chainreaction. Of the 29 primer sets, FDP 2 targeted the ITS regionof the ribosomal gene, FDP 3 targets the mitochondrialrRNA gene designed basically for verticillium species (Liet al. 1994). FDP3 has shown polymorphic banding patternaround 700bp among the different races (Table 1, Figure2A). FDP 4 targets the elongation factor 1 and polymorphicbands of 600 and 700bp were obtained as specified earlierby Mbofung et al. (2007). FDP 5 targeting the intergenicspacer region varied in its amplicon from the expected sizerange of 1500. FDP 9 distinguishes race 4 with a specificband of 2kb. About 1kb band was obtained from FDP14specifically for race 2, whereas Ortiz et al. 2011 reported 1kb band for race 6 in their study. FDP 29 is another primerset targeting elongation factor (ef1/ef2) genes giving adistinct 800bp band in race 4 among all races. Use of ESTbased markers for describing the variability amongpathotypes has been seen in recent past. Arif et al. 2012have targeted the translation elongation factor (EF-1á) fordifferentiating the isolates of Fusarium solani.

The other marker system employed in racialidentification has been the SCARS. Lievens et al. (2007)developed specific Sequence Characterized AmplifiedRegions (SCAR) primers to identify F. oxysporum f. sp.cucumerinum. Similarly, a set of SCAR primers previouslyused in Foc race identification by Jimenez et al. (2003) werealso employed in present study. The main advantage ofSCARs is that they are quick and easy to use. In addition,SCARs have a high reproducibility and are locus-specific.The 45th primer pair gave a specific expected amplicon of900bp in race 5 (Figure 2B). The 47th primer gave ampliconof 500 bases in all the races. The results obtained havebeen different from those reported by Jimenez et al. (2003).The expected amplicon length has been accurate but therace in which the expected banding pattern has to appear isvariable.

In order to find further polymorphism and capturesequence difference among the different races, CAPS(Cleaved amplified polymorphic sequence) analysis wasperformed. Gurjar et al. (2009) have performed ITS-RFLP todifferentiate the pathogenic races of Foc. The amplifiedmonomorphic bands of 700bp from primer FDP 25 with allthe 6 races of Foc were eluted and restriction digestionwith EcoR I resulted in a 500 and 400 bp band in race 4. Thisshows the presence of single nucleotide polymorphism inrace 4 for the allele that targets the translation elongationfactor gene region of Fusarium species (Figure 2C).


Table 1. Types of marker techniques used and amplicons obtained among six races of Fusarium oxysporum f. sp. ciceri

Marker Technique and Primer name

Expected Amplicon Size in bp

Race 1 Race 2 Race 3 Race 4 Race 5 Race 6 (bp)

ITS specific FDP 2 200 - 200 300 300 300 200 FDP 3 450 700 700 600 500 600 700 FDP 4 700 - 700 600 700 600 600 FDP 5 1500 - 2000 2000 2500 2500 2000 FDP 9 2000 - - - 2000 - - FDP 14 1000 - 1000 - - - - FDP 25 700 700 600 600 700 600 600 FDP 29 700 - 700 700 800 700 700 SCAR FocR0-M15f/FocR0 M15r 900 - 900 - - - - FocR1B/C-N5f/FocR1B/C-N5r 500 500 500 500 500 500 500 FocR5-L10f/FocR5 L10r 900 - - - - 900 - FocR6-O2f/ FocR6O2r 1000 - 800 - - - - CAPS FDP 25 restricted with EcoRI 700 700 700 700 500 700 700 Table 2. Primer sets used in multiplex PCR to

differentiate six races of fusarium oxysporum f.sp. ciceri

S.No Race Primer name Amplicon size (bp) 1. 1 FDP-3

FDP-5 FDP-12

720 2500 400

2. 2 FDP-11 FDP-14

Primer-36

900 1000 400

3. 3 FDP-9 FDP-22

Primer -30

500 100 300

4. 4 FDP-1 FDP-7 FDP-9

2100 2500 500

5. 5 FDP-14 FDP-17 FDP-19

700 1000 1500

6. 6 FDP-7 FDP-19 FDP-22

500 700 200

Figure 1. Macroscopic characteristics of Foc Race 1 with ayellowish tinge, race 2 and 5 with creamish, pinkish tinge in race3 and 4 and a violet tinge in race 6

Figure 2. A. Agarose gel showing 700bp polymorphic markerbands targeting the ITS region of fusarium oxysporum f. sp. ciceriamplified in six races by FDP 3, B. Sequence characterizedamplified region (SCAR) 45th primer pair FocR5-L10f/FocR5-L10r showing a 900 bp race 5 specific band,C. CAPS markerdeveloped for race 4 identification showing a 500bp and 400bpband after restriction with EcoRI where as no polymorphismwas obtained after restriction with Hind III, D. Multiplex PCRprofile using ITS and elongation factor specific markers for race2, 3, 5 and 6

Another approach that could be used to decipherthe fingerprint of different races of foc is by using multiplex-PCR. In this method highly conserved target genesequences specific to the pathogen of interest are detected.Boureau et al. (2013) used multiplex-PCR assay foridentification of Xanthomonas pathogen. Two and threeprimer sets were prepared to amplify specific differentiatingbands in different races of Foc (Figure 2D). The differentprimer sets used are given in Table 2. Among six races onlyfour races could be differentiated through multiplex-PCR.

The amplicon of each primer is selected in such a way thatthe bands could be easily resolved on 2.0% agarose. Inrace 2, FDP11, FDP 14 and 36th primer of Table 3 yielded theexpected bands of 900bp, 1kb and 400bp respectively thatwould differentiate the race 2 from other races. Similarly,FDP 9, FDP22 and 30th primer pair yielded 500bp, 100bp and300bp bands respectively for race 3. FDP14, FDP17 andFDP19 showed 700bp, 1000bp and 1500bp bands specificto race 5 followed by 500bp, 700bp and 200bp bands withFDP7, FDP19 and FDP22 respectively for race 6. Thesecombinations of primers can be used to differentiate thedifferent races of Foc by the scientific community. Further,application of these markers on different isolates of Foccollected all over India can give us an idea about thediversification of different races. This article can be takenas a reference to source of markers that can be used foridentification of Fusarium oxysporum f. sp. ciceri and the

Poornima et al. : PCR based race identification of Fusarium oxysporum f. sp. ciceri 9

Table 3. List of primers used with their sequences for racial differentiation of fusarium oxysporum f. sp. ciceri

Sl. No. Primers name Sequence 1 FDP-1 F: CTT GGT AGG GGG GAC AGA CAC GC R: CCA TTCCAC GCTCGA CAG ACC T 2 FDP-2 F: CTT GGT GTT GGG ATC TGT GTG CAAR: ACA AAT TAC AAC TCG GGC CCG AGA 3 FDP-3 F: CAGCAGTGAGGAATATTGGTCAATGR: GCGGATCATCGAATTAAATAACAT 4 FDP-4 F: ATGGGTAAGGAAGACAAGACR: GGAAGTACCAGTGATCATGTT 5 FDP-5 F: GAGACAAGCATATGACTACTG R: AATACAAGCACGCCGACAC 6 FDP-6 F: GTGTCGGCGTGCTTGTATTR: GGTTCAATTTGATGTCGGCT 7 FDP-7 F: AGCCGACATCAAATTGACCR: GTGTGAAATTGGAAAGTCGG 8 FDP-8 F: CCGACTTTCCAATTTCACAC R: CCAACACATGGGTGGTACCG 9 FDP-9 F: CCAGACTTCCACTGCGTGTCR: CACGCCAGGACTGCCTCGT

10 FDP-10 F: GGCGTTTCGCAGCCTTACAATGAAG R:GACTCCTTTTTCCCGAGGTAGGTCAGAT 11 FDP-11 F: GGAGAGCAGGACAGCAAAGACTA R: GGAGAGCAGCTACCCTAGATACACC 12 FDP-12 F: GAGAGCAGGGTCAGCGTAGATAG R: GCAGCAGAAGAGGAAGAAAATGTA 13 FDP-13 F: GGAAGCTTGGCATGACATAC R: AAGCTTGGGCACCCTCTT 14 FDP-14 F: GAGCAGTCAATGGCAATGG R: AGAGCAGGGTCAGCGTAGATA 15 FDP-15 F: GGAGAGCAGTAGAGTTACAGCAGTATTR: GGAGAGCAGCTACCCTAGATACACC 16 FDP-16 F: CGATTGGTTTGGTTCTGGC R: TTTCATATAGCATGGATCAAC 17 FDP-17 F: ACCATTAGGACTGAGTTTG R: GCTTGAATAGCGATCCTTC 18 FDP-18 F: GTCACACACAAATTCACTAG R: TGGGTGTAGTCCGGGTTG 19 FDP-19 F: GCTTTTGCTCCGTTCAAGTCC R: GGCCACTCTCACCGATCT 20 FDP-20 F: GCTTTTGCTCCGTTCAAGTCC R: GGCCACTCTCACCGATCT 21 FDP-21 F: GAAGCTAATACGCCATAAAC R: CTTCACAGTCCCTTTTCAC 22 FDP-22 F: ACACTGTTTGGGACCGAATCA R: ATAGAAGAGCCCATCCGATAA 23 FDP-23 F: TGGAGATCATTGGCTGT R: ACTGAAAGGTCGGGTAAA 24 FDP-24 F:GCGCCCCATATGTTTAAATTATATGGAGR:GCGATGGGGATATTTTCTTTATTATCAG 25 FDP-25 F: ATGGGTAAGGA(A/G)GACAAGAC R: GGA(G/A)GTACCAGT(G/C)ATCATGTT 26 FDP-26 F: CTGTCGCTAACCTCTTTATCCA R: CAGTATGGACGTTGGTATTATATCTAA 27 FDP-27 F: CTTTCCGCCAAGTTTCTT R: TGTCAGTAACTCGACGTTGTTG 28 FDP-28 F: CTTCCTGCGATGTTTCTCC R: AATTGGCCATTGGTATTATATATCTA 29 FDP-29 F: ATGGGTAAGGAGGACAAGAC R: GGAAGTACCAGTGATCATGTT 30 FOF1 FOR1 F: ACATACCACTTGTTGCCTCG R: CGCCAATCAATTTGAGGAACG 31 FACFFACR F: GGGATATCGGGCCTCA R: GGGATATCGGCAAGATCG 32 FEF1 FER1 F: CATACCTATACGTTGCCTCG R: TTACCAGTAACGAGGTGTATG 33 CLPRO1CLPRO2 F: TGCATCAGACCACTCAAATCCT R: GCGAGACCGCCACTAGAT 34 Red-F Red-R F: ATCGATTTTCCCTTCGACTC R: CAATGATGATTGTGATGAGAC 35 FC01F FC01R F: ATGGTGAACTCGTCGTGGC R: CCCTTCTTACGCCAATCTCG 36 ITSF ITS R F: AACTCCCAAACC CCTGTGAACATA R: TTTAACGGCGTGGCCGC 37 FUM1 FFUM1 R F: CCATC ACAGTG GGACACAGT R: CGTATCGTCAGCATGATGTA GC 38 B6003 B6004 F: TCTACGACACTCCCAAAGTC R: CAAACCAGATTCCTAAACGC 39 Foc 1-F Foc 2-R F: CAGGGGATGTATGAGGAGGCT R: GTGACAGCGTCGTCTAGTTCC 40 FocTR4 F: CACGTTTAAGGTGCCATGAGAG R: CGCACGCCAGGACTGCCTCGTGA 41 Me8SCAR2 Em5SCAR F:TGA GTC CAA ACC GGA CTA CAAG R:GAC TGC GTA CGA ATT AAC TCT ACG 42 FocR0-M15f FocR0-M15r F: GGAGAGCAGGACAGCAAAGACTA R: GAGAGCAGCTACCCTAGATACACC 43 FocR1B/C-N5f FocR1B/C-N5r F:GAGAGCAGGGTCAGCGTAGATAG R:GCAGCAGAAGAGGAAGAAAATGTA 44 FocR5-L10f FocR5-L10r F: GGAAGCTTGGCATGACATAC R: AAGCTTGGGCACCCTCTT 45 FocR6-O2f FocR6-O2r F: GAGCAGTCAATGGCAATGG R: AGAGCAGGGTCAGCGTAGATA 46 FocR6-P18f FocR0-M15r F: GGAGAGCAGTAGAGTTACAGCAGTATTR: GGAGAGCAGCTACCCTAGATACACC 47 FocR6-P18F FocR0-MI5r F: GGAGAGCAGTAGAGTTACAGCAGTATT R: GGAGAGCAGCTACCCTAGATACACC

1 0 Journal of Food Legumes 30(1), 2017

different techniques such as CAPS analysis and multiplex-PCR used for their classification.

A set of primers differentiating the different races ofFoc have been identified and defined in the present study.Fingerprinting based on more than one loci has also beenachieved here using multiplex-PCR.

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In vitro plant regeneration in pigeonpea [Cajanus cajan (L.) Millsp] using variousexplantsNANDHA ABHIJEETA K and MADARIYA RAJESH B

Department of Biotechnology, Junagadh Agricultural University, Junagadh-362001, India; E-mail:[email protected](Received: May 28, 2016; Accepted: January 16, 2017)

ABSTRACT

An efficient method for plant regeneration via callusformation has been developed in pigeonpea using twovarieties (BDN-2 and GT-101). Three different explants viz.,leaf, hypocotyl and root excised from 15-20 days old in vitroraised seedlings were cultured on basal MS medium.Greenish coloured callus were observed using various mediaaccording to explants. Shoots were found in MS + 1.0 mg/lNAA + 4.0 mg/l Adenine. Elongated shoots were transferredin MS + 1.0 mg/l IAA media for rooting. Rooted plants weretransferred in pot for acclimatization.

Key words: Callus regeneration, In vitro, Pigeonpea

Pigeonpea is an important multi-use legume shrub ofthe tropics and subtropics region.It is one of the preferredpulse crops in dryland areas where it is intercropped orgrown in mixed cropping system with cereals or other shortduration annuals (Joshi et al. 2001). In combinationwith cereals, pigeonpea make a well-balanced human food.Pigeonpea contains high levels of protein, approximately19.5% in mature and 7.2% in immature (Smartt and Nwokolo2012), while research has shown that the protein content ofthe immature seeds is of a higher quality. The seeds containtwo globulins, cajana in and concojan in, accounting for 58per cent and 8 percent of the total nitrogen respectively.The globulins, which form the chief proteins of seed, appearto be characterized of the genus. The world acreage ofpigeonpea is 6.22 million ha with annual production of about4.74 million tonnes, and productivity of 762 kg/ha. Indiawith its area of 4.02 million hectares produces 2.97 milliontonnes with a productivity of 740 kg/ha. The area in Gujaratis 2.22 million ha, while production is 2.46 million tonneswith an average yield of 1105 kg/ha (Anonymous 2016).The improvement of pigeonpea with regard to pests,lowering allergenic protein levels in seeds, and improvingthe quality of protein is, therefore, desirable (Venkatachalamand Lakshmi Sita 2008). Despite the importance ofpigeonpea in semi arid regions of the world, little concertedresearch effort has been directed towards pigeonpea cropimprovement. BDN 2 had advantages as indeterminatehabit, mid-early maturation, tolerant to wilt, while GT 101were selected for its high yielding, mid-early maturing, whiteseeded with tolerant to wilt and sterility mosaic diseases.

In micro propagation, the introduction of new charactersinto pigeonpea by means of genetic manipulation is of greatpotential value, especially of the traits that would conferresistance to disease and pests.


Seeds of pigeonpea [Cajanus cajan (L.) Millsp.]varieties viz., BDN 2 and GT 101 were procured from PulseResearch Station, Junagadh Agricultural University,Junagadh for this study. Seeds were surface sterilized withBavistin for 30 min and washed 4-5 times with sterile distilledwater followed by surface sterilization with 0.1% (w/v)mercuric chloride for 10-15 min and washed 4-5 times withsterile distilled water. The seeds were kept in half MS(Murashige and Skoog 1962) medium over Paper Bridge.Germination of the seeds occurs in 15-20 days at 25 + 20 Cwith a light intensity of 20-25 µE m-2 s-1 for 16 hrs/dayphotoperiod. After germination of plantlet, leaf, hypocotyland root were cut into five mm size and transferred in MSmedia containing various growth regulators for 15 daysafter that the callus were transfer in fresh MS media withgrowth regulator. Frequent transfer was required to avoidbrowning of callus.

Flow chart for the procedure

Mature seeds were soaked in bavistin solution for20 to 30 min

Seeds were washed with tap water 3-4 times andthen washed the explants with sterile double distilled

water 4-5 times

Seeds were soaked in mercuric chloride for 10 min

Seeds were washed with sterile double distilledwater 4-5 times

Washed seed were placed immediately in MS media overpaper bridge for germination


Seeds were in 15-20 days at 25 + 20 C with a lightintensity of 20-25 µE m-2 s-1 for 16 hrs day photoperiod

From germinated plantlets various explants as leaf,hypocotyl and root were collected for further experimentand transfer into MS media containing various growth

regulatorsCulture media and condition: All three explants, leaf,hypocotyl and root, were transferred into regenerationmedia contain MS medium with 3% sucrose. This mediumwas augmented with 1.0-2.5mg/l 2,4-D,1.0mg/l Kin, 0.2-5.0mg/l BA either individually or in combination. All mediawere adjusted to pH 5.8 prior to the addition of 0.8% (w/v)agar and autoclaved at 1210C and 15lb pressure for 15 min.Callus induction: All three explants, leaf, hypocotyl androot were used for callus induction in MS mediasupplemented by 2,4-D (1.0-2.5 mg/l) either alone or incombination with BA (0.2-1.0 mg/l) and Kin (1.0 mg/l) orwith combination of BA (2.5-5.0 mg/l) with each of the threereplication. After three weeks callus were transferred intofresh media for its maintenance in friable and viable stage.Appropriately grown callus were transferred for shootformation.Shoot initiation and elongation: Leaf, hypocotyl and rootderived callus of both the varieties were used for shootregeneration. The MS medium supplemented by BA (1.0-2.5 mg/l) and their combination with IAA (0.5-1.5mg/l) andNAA (0.2-1.0 mg/l) was used for regeneration of shoots.Initiated shoot were transferred into MS mediasupplemented with NAA (0.1-1.0 mg/l) and BA (5.0 mg/l) incombination with IAA (0.5 mg/l) with or without adenine.Elongated shoots were transferred into rooting mediacontaining IBA or IAA. Rooted plants were transferredinto pot.Statistical analysis: All the experiments were repeated threetimes under the defined and controlled condition of thelaboratory. The data on callus induction, shoot initiation,multiple shoot production and rooting were statistically

analyzed using completely randomized block design (CRD)and factorial completely randomized design as per stagesaccording to Steel and Torrie (1960).


Surface sterilised seeds cultured on paper bridge inhalf strength MS medium without any growth regulator intest tubes showed 80% germination after 15-20 days. Invitro organogenesis induction from immature cotyledons,embryonal axes (George and Eapen 1994) and cotyledonand leaf explants (Sreenivasu et al. 1998) in solid mediumwas obtained from Cajanus cajan.Callus induction: Leaf, hypocotyl and root explants ofboth genotypes of pigeonpea expanded. The most suitablemedium for the maintenance of callus was selected on thebasis of callus morphology (and not on the basis of callusfresh weight produced).

The callus initially induced from the leaf explant waswhite in colour, semi-friable and small in size in MS + 2,4-D(1.0 mg/l) + BA (0.2 mg/l), while the hypocotyl derived calluswas greenish white and white in colour larger in size, friableand morphogenic in nature in MS + Kin (1.0 mg/l) + BA (5.0mg/l). On the other hand the root derived callus wasbrownish white in colour, semi-friable, larger in size andmorphogenic in nature produced in media containing MS +1.0 mg/l 2,4-D + 0.5 mg/l BA (Table 1). Whitish green andlight green highly expanded callus were observed byPrabhakaran and Elumalai (2014), while Anbazhagan andGanapati (1999) observed greenish white compact friablecallus in leaf and internode explants. Similar result wasobserved in present study.

Among all explants hypocotyl produced highest percent of callus (56.4%), while leaf and root, respectivelyshowed less callus induction (51.1% and 46.7%).Shreenivasu et al. (1998) obtained callus induction in leafand cotyledon explants by culturing them on MSsupplemented with TDZ. The positive effect of 2,4-D oncallus initiation were reported by Anbazhagan and Ganpati(1999). Higher callusing per cent was also reported by

Table 1. Effect of different concentration of 2,4-D, BA and Kin on callus formation from leaf, hypocotyl and root explantsresponse (%) after three weeks in culturing media

Media Explant response days (%) 2,4-D BA Kin Leaf Hypocotyl Root

1.5 - - 11.1 (56.1%) 8.8 (69.9%) 10.5 (63.6%) 2.0 - - 12.0 (57.6%) 10.1(76.7%) 11.1 (63.3%) 2.5 - - 12.6 (61.9%) 9.9 (74.6%) 13.4 (66.1%) - 2.5 1.0 13.4 (58.5%) 10.0 (80.2%) 12.1 (56.0%) - 5.0 1.0 12.1 (52.2%) 11.1 (91.7%) 10.7 (59.7%)

1.0 0.2 - 12.5 (60.9%) 11.5 (88.7%) 10.7 (64.8%) 1.0 0.5 - 12.1 (52.9%) 9.8 (79.7%) 8.9 (70.3%) 1.0 1.0 - 12.7 (63.2%) 10.1 (81.9%) 12.7 (68.1%) 1.5 0.2 - 13.1(51.8%) 8.6 (69.5%) 11.2 (67.8%) 1.5 0.5 - 13.0 (54.7%) 9.0 (76.1%) 10.1 (63.3%) 1.5 1.0 - 14.1 (60.0%) 9.2 (81.5%) 10.6 (63.7%)

Abhijeeta & Rajesh : In vitro plant regeneration in pigeonpea [Cajanus Cajan (L.) Millsp.] using various explants 1 3

Prabhakaran et al. (2011) on MS medium containing IAA,Kin and 2,4-D.Shoot initiation and elongation: The initiation of the shootwas also influenced by the genotype, explant and mediaused for the experiment. GT-101 produced higher numberof shoot (54.6%) with least days for shoot initiation (32.6),while hypocotyl explants produced higher number of shoot(56.4%) followed by leaf and root (51.1 and 46.7),respectively. MS + 5.0 mg/l BA + 0.5 mg/l IAA + 2.0 mg/ladenine produced higher number of shoots per callus piecewhile MS media supplemented with 1.0 mg/l NAA with 4.0mg/l adenine produced more elongated shoots then othermedia combinations. Hypocotyl produced highest numberof shoots (5.7) than leaf and root explants.

In present study, effectiveness of growth regulatordepended on the explant used as 2,4-D with BA was moreeffective for leaf and root explants, while for hypocotylexplants Kin with BA was more responding. Geetha et al.(1998) and Prasad et al. (2011) reported shoot productionfrom leaf, cotyledon and shoot tip. Jain and Chaturvedi(2004) obtained higher number of shoots from cotyledonarynode.Rooting and establishment of plantlets: Elongated andwell developed shoots (3-4 cm long) were excised from theshoot clumps and transferred to MS medium augmentedwith various concentrations of IBA (0.2-0.5 mg/l) and IAA(1.0-1.25 mg/l). The frequency of rooting per shoot wassignificantly different among the genotype, explant andmedia used for treatment. Hypocotyl explant of BDN-2genotype cultured on MS medium augmented with 1.0 mg/l IAA was most responsive for rooting. Mohan andKrishnamurthy (1998) obtained higher per cent rooting (80-85%) on MS supplemented with 1.0 mg/l IBA. Jain andChaturvedi (2004) observed highest percentage of rooting(100%) on MS supplemented with 0.25 mg/l IAA, NAA and

IBA. In present study, higher per cent of shooting werealso obtained by IAA followed by IBA.

The rooted shoots were transferred in small earthenpots containing a mixture of soil: sand: manure in 3:1:1 ratio.After two weeks, potted plants were shifted to shadycondition for acclimatization.

REFERENCE

Anbazhagan VR and Ganapathi A. 1999. Somatic embryogenesis incell suspension cultures of pigeonpea (Cajanus cajan). PlantCell Tissue Organ Culture 56: 179-184.

Anonymous 2016. Area, production and productivity of pigeonpea.Pulses in India: Retrospect and prospects 2: 42-45.

Geetha N, Venkatachalam P, Prakash V and Lakshmi Sita G. 1998.High frequency induction of multiple shoots and plantregeneration from seedling explants of pigeonpea (Cajanus cajanL.). Current Science 75: 1036-1041.

George L and Eapen S. 1994. Organogenesis and embryogenesisfrom diverse explants of pigeonpea. Plant Cell Reports 13:417-420.

Jain M and Chaturvedi HC. 2004. In vitro cloning of Cajanus cajanvar. Bahar through prolific shoot bud differentiation in leafsegments and production of fertile plants. Indian Journal ofBiotechnology 3: 258-262.

Joshi PK, Rao PP, Gowda CLL, Jones RB, Silim SN, Saxena KB andKumar J. 2001. The world chickpea and pigeonpea economies:facts, trends, and outlook. Patancheru 502 324, Andhra Pradesh,India: International Crops Research Institute for the Semi-AridTropics.

Figure A-F: (A) Different explants: a) hypocotyl, b) leaf, c) root;(B) Callus initiation: a) hypocotyl, b) leaf, c) root; (C) Callusmaintenance: a)hypocotyl, b) leaf, c) root; (D) In vitroorganogenesis and shoot induction: a) hypocotyl, b) leaf, c) root;(E) Rooting, root length and number or root in in vitro developedplantlets; (F) Establishment of rooted plantlets

Table 2. Effect of various genotypes and explants on days toshoot initiation

Genotype Days to shoot initiation

Per cent shooting (%)

BDN-2 34.1 48.2 GT-101 32.6 54.6

Table 3. Effect of different concentration of BA, IAA andAdenine on number of shoots per callus piece

Table 4. Effect of different media on shoot length

Media Conc. (mg/l) No. of shoots per callus piece BA IAA Adenine Leaf Hypocotyl Root 5.0 0.5 - 4.9 6.4 4.7 5.0 0.5 2 4.5 7.3 4.5 5.0 0.5 4 4.8 5.6 4.8

Media Conc. (mg/l) Shoot length (cm) NAA Adenine Leaf Hypocotyl Root 1.0 - 5.2 6.9 4.1 1.0 2.0 4.8 5.6 3.9 1.0 4.0 4.5 5.7 5.7


Murashige T and Skoog F. 1962. A revised medium for rapid growthand bio assays with tobacco tissue cultures. Physiologia Plantarum15: 473-497.

Mohan ML and Krishnamurthy KV. 1998. Plant regeneration inpigeonpea [Cajanus cajan (L.) Millsp.] by organogenesis. PlantCell Reports 17: 705-710.

Prabhakaran M, Elumalai S,Ramganesh S and Prakasam V. 2011.High frequency induction of callus from seedling explants ofpigeonpea [Cajanus cajan (L) Millsp.] for genetictransformation. Current Botany 2(6): 15-17.

Prabhakaran M and Elumalai S. 2014. An efficient in vitroregeneration of shoot from cotyledon derived callus of Pigeonpea[Cajanus cajan (L.) Millsp.]. Indian Streams Research Journal3(12): 1-7.

Prasad MG, Prasad TNVKV and Sundhakar P. 2011. In vitro

proliferation of shoot regeneration from embryo of Cajanuscajan L. (var. LGG-29). Journal of Developmental Biology andTissue Engineering 3(5): 62-65.

Smartt J and Nwokolo E. 2012. Proximate composition of pigeonpea seeds. Food and feed from legumes and oilseeds. 66 pp.

Sreenivasu K, Malik SK, Ananda Kumar P and Sharma RP. 1998.Plant regeneration via somatic embryogenesis in pigeonpea[Cajanus cajan (L.) Millsp]. Plant Cell Reports 17: 294-297.

Steel RGD and Torrie JH. 1960. Principle and Procedures of Statistics.McGraw Hill Book Company, Inc. New York. Pp 99-128.

Venkatachalam P and Lakshmi Sita G. 2008. Genetic transformationas a tool for improvement of Pigeon Pea [Cajanus cajan (L.)Millsp.] In: Handbook of New Technologies for GeneticImprovement of Legumes. Pp 125-145.


Inheritance of resistance to Mungbean Yellow Mosaic Virus (MYMV) in intraand inter-specific crosses of VignaBASAVARAJA T1, NIRANJANA MURTHY2, SHASHI KUMAR P3 and SATHEESH NAIK SJ4

1,4ICAR-Indian Institute of Pulses Research, Kanpur-208024, India; 2,3All India Co-ordinated Research Networkon Potential Crops Scheme, Main Research Station, Hebbal and Gandhi Krishi Vignana Kendra, University ofAgricultural Sciences, Bangalore-560065, India; E-mail: [email protected](Received: May 30, 2016; Accepted: November 8, 2016)

ABSTRACT

The mode of inheritance of resistance to mungbean yellowmosaic virus (MYMV) in intra and inter-specific crosses ofmungbean has been studied in the present investigation. Aninfector row technique was used for evaluating parents, F1and F2 plants for MYMV resistance. No insecticide wassprayed in order to maintain the natural whitefly populationin experimental field. In the field condition, only after 80%of plants showed MYMV incidence and the scoring of thetest materials was done by MYMV disease reaction scale.According to the mean disease score, the mungbeangenotypes were categorized into five groups resistant (R),moderately resistant (MR), moderately susceptible (MS),susceptible (S) and highly susceptible (HS). The resultsshowed that in all the three intraspecific F2 populationsegregated in 1: 3 (Resistance: Susceptible) ratio indicatingsingle recessive gene whereas in case of all Interspecificcrosses between mungbean and ricebean, segregation of F2population was in 3(R) : 1(S) ratio which clearly indicatessingle dominant gene governs YMV resistance in ricebean.

Key words: Inheritance, Mungbean Yellow Mosaic Virus,Vigna spp.

Mungbean [Vigna radiata (L.) Wilczek], also knownas green gram, is an important source of dietary proteinacross Asia. The mungbean is native to India-Burma regionof South-East Asia. It is widely grown in tropical and sub-tropical regions as a monoculture and as a component incropping systems. Mungbean seed contains about 24 percent protein (Haytowitz and Matthews 1986). In India,mungbean is grown in an area of 3.2 million hectares with aproduction of 1.4 million tonnes and a productivity of 437kg/ha (Agristat, 2013). The major mungbean producingstates in India are Andhra Pradesh, Maharashtra, Karnatakaand Rajasthan which account for about 70 per cent of totalproduction. In Karnataka, the total area under mungbean is5.28 lakh hectares with a total production of 1.08 lakh tonnesand an average productivity of 205 kg/ha (Agristat, 2013).

The production constraints of pulses includingmungbean are biotic and abiotic stresses. Diseases areprominent among biotic stresses which are known to affectthe productivity. Fungal, bacterial and viral diseases areconsidered as major limiting factors for the production of

mungbean in the tropical and subtropical countries (Maliand Thottappilly 1986). More than 20 viruses are reportedfrom various mungbean growing areas worldwide. Amongthese viruses, mungbean yellow mosaic virus (MYMV) isthe most serious disease which may cause 80-100 per centyield reductions (Chant 1960, Shoyinka 1974, Williams1977). Mungbean yellow mosaic virus severely affectsvegetative parts of the plant (Bashir et al. 2002). It maycause 14 to 54 per cent decrease in plant height, 30 to 95 percent decrease in dry stem weight of cowpea and mungbean(Ilyas 1999). MYMV produces typical yellow mosaicsymptoms.

The yield of mungbean is stagnant over the yearsbecause of the narrow genetic variability in the primarygene pool. The limited gene pool of the cultivated speciesof Vigna has restricted the conventional plant breedingprogrammes to improve the yield with resistance to bioticand abiotic stress factors. There had been alwayspossibility of improving the crop by incorporating wildresistant genes to the cultivated species. For producingthe crop types which combine the high productivity, qualityand resistance to pest and disease, it has become necessaryto widen the gene pools of the cultivated species throughintra and inter-specific hybridization (Stebbins 1958). Toproceed in this direction of gene transfer and introgressionof desired resistant gene, information on inheritance ofresistance to MYMV disease is essential. Inheritance ofresistance to MYMV in mungbean has been studiedextensively using different resistant sources but resultswere contradictory. Inheritance studies of MYMV resistancehave revealed that the resistance is controlled by a singlerecessive gene (Saleem et al. 1998), dominant gene (Sandhuet al. 1985).

In view of these earlier reports, more extensive studyis needed in order to confirm the mode of inheritance of theresistance. Meanwhile, understanding the inheritance ofresistance to MYMV is of prime importance in mungbeanbreeding programmes. The sources of resistance to MYMVare very rare in the germplasm of mungbean while, highproportion of ricebean (Vigna umbellata) and urdbean(Vigna mungo) lines resistant to MYMV are available.Monika et al. (2001) and Pandiyan et al. (2008) have reported


that ricebean contains desirable genes for MYMVresistance. Hence, transfer of genes for MYMV resistancefrom rice bean to mungbean may be a possible means todevelop MYMV resistant mungbean varieties. Keeping thisin view, the present study was under taken to investigatethe inheritance of resistance to MYMV in inter and intra-specific crosses of mungbean.


The experiments were conducted during Summer 2012and Kharif 2013 at the experimental plots of All India Co-ordinated Research Network on Potential Crops Scheme,Main Research Station (MRS), Hebbal and GandhiKrishiVignana Kendra (GKVK), University of AgriculturalSciences, Bangalore. The basic materials used for thepresent study included the cultivars belonging to twoVigna spp. viz., Vigna radiata (mungbean) and Vignaumbellata (rice bean). The material comprised five lines ofmungbean viz., Selection 4, BGS 9, Yellow mung, Chinamung and DGGV 2 and five lines of rice bean viz., RBL 1,KBR 1, RBL 35, RBL 50 and RBL 6 which were used asparents in hybridization. The parental lines of mungbeanand ricebean included in the study along with their sourceand disease reaction for Mungbean Yellow Mosaic Virus(MYMV) are presented in the Table 1.

In the Intra-specific crosses of mungbean, Selection-4 was used as male parent because it is moderately resistantto MYMV while, BGS 9, China mung and DGGV 2 aresusceptible to MYMV which were used as female parents.For hybridization, direct crosses were attempted betweenmale and female parents of selected mungbean lines. Inter-specific hybridization was done by crossing between twoVigna species viz., Vigna radiata and Vigna umbellata.Five mungbean lines viz., Selection 4, BGS 9, Yellow mung,China mung and DGGV 2 which are agronomically superiorand well adapted varieties but susceptible to MYMV wereused as female parents. Five ricebean lines viz., RBL 1,KBR 1, RBL 35, RBL 50 and RBL 6 which are highly resistantto MYMV were used as male parents in intra-specifichybridization.

The seeds from three inter specific hybrids ofmungbean and nine inter specific hybrids of mungbeanand ricebean were harvested to raise F2 population. Thethree inter-specific crosses were Selection 4 × BGS 9,Selection 4 × Chinamung and Selection 4 × DGGV 2 and thenine inter-specific crosses were RBL 1 × Selection 4, KBR1 × Selection 4, KBR 1 × China mung, KBR 1 × Yellow mung,RBL 50 × BGS 9, RBL 35 × BGS 9, RBL 1 × BGS 9, RBL 35 ×DGGV 2 and RBL 35 × China mung. The experiment wasconducted without replication as it was segregatingmaterial. The sowing was done with a spacing of 30 cmbetween rows and 10 cm between plants with rows lengthof 4 meters. Each F2 was raised with minimum of 150-200plant population. Yellow mung, a highly susceptible

mungbean cultivar for MYMV, was used as infector andwas sown along with all the F2 population of intra and inter-specific crosses to create disease epidemic in the test plants.All standard agronomic practices were followed to raise agood crop. At the time of harvest, observations wererecorded on all the plants including their parents and F1sfor quantitative characters. The parents, F1 hybrids of intraand inter-specific crosses with their respective F2 populationwere subjected for disease resistance screening at 50 daysafter sowing. The F2 plants were classified into differentclasses based on per cent disease incidence for MYMV forparents, F1 hybrids and individual plants of each F2population as per the procedure given by Selvi et al. 2006(Table 2).

The ratio of phenotypes [resistant (R): susceptible

(S)] of F2 plants was used to test the hypothesis thatresistance was controlled by a single dominant gene orsingle recessive gene. Heterogeneity among F2 populationswas evaluated using the contingency test and the resultsobtained were analyzed using the Chi-square test. To screenthe F1 hybrids of intra and inter-specific crosses for MVMVdisease resistance under natural field condition duringSummer (February-April). Mungbean variety, Yellow mungwhich is highly susceptible to MYMV was used as diseasespreader and two rows of spreader were planted all aroundthe experiment in order to attract white fly and to enhanceinfection of MYMV.


Mungbean yellow mosaic virus is widespread in themajor mungbean growing areas in India. A severe outbreakof MYMV in the southern and northern states is currentlycausing serious concern to mungbean growers and to themungbean industry in these regions. Resistance to MYMVwas determined by visual symptomatology. Symptomlesslines were assumed to be resistant. As mungbean lines canbe infected without showing symptoms, it is possible thatthese are not resistant lines. Breeding for cultivars havingresistance is a commonly accepted and effective strategyfor controlling the MYMV disease and also prevent themultiplication of virus. The knowledge of inheritance ofresistance genes and role of each gene in the developmentof resistance or susceptibility will be very useful for themungbean breeders to breed MYMV resistant varieties.The present experiment was designed to study theinheritance of MYMV disease resistance in intra and inter-specific crosses of mungbean. Parents and F1 hybrids werescreened for MYMV reaction at the pod formation stageusing the scale given by Selvi et al. (2006). When 100%plants of the susceptible check were completely infectedwith MYMV, the per cent disease incidence by MYMV in

100

plants ofnumber Total plants infected ofNumber Per cent disease incidence =

Basavaraja et al. : Inheritance of resistance to MYMV in Vigna 1 7

Table 1. The parental lines of mungbean and ricebean used in the study and their disease reaction for Mungbean YellowMosaic Virus (MYMV)Common name Parental lines Disease reaction Source

Mungbean 1 Selection-4 Moderately Resistant UAS, Dharwad 2 BGS-9 Susceptible UAS, Raichur 3 Yellowmung Highly Susceptible UAS, Raichur 4 Chinamung Susceptible UAS, Raichur 5 DGGV-2 Susceptible UAS, Raichur

Rice bean 1 RBL 1 Resistant

AICRN on Potential Crops, UAS, Bangaluru.RBL lines belong to PAU, Ludhiana

2 KBR 1 Resistant 3 RBL35 Highly Resistant 4 RBL50 Resistant 5 RBL 6 Highly Resistant

Table 2. MYMV disease reaction scale

Source: MYMV disease reaction scale given by Selvi et al. (2006)

Table 3. Screening of Inter-specific hybrids of ricebean and mungbean and their parents for MYMV disease under naturalfield condition

Table 4. Screening of intra-specific hybrids of mungbeanand their parents for MYMV disease under naturalfield conditionScale Per cent Disease Incidence Disease reaction

0 No infection Highly resistant (HR) 1 1-5% Mottling of leaves Resistant (R) 3 5-10% Mottling of leaves Moderately resistant (MR) 5 10-25% Mottling and yellow

discoloration leaves Moderately susceptible(MS)

7 25-50% Mottling and yellow discoloration of leaves

Susceptible (S)

9 >50% Severe yellow mottling leaves, reduced flower and fruits

Highly susceptible (HS)

S. No.

Parents/ crosses

Total plants

Infected plants

% Disease

Incidence

Disease score

Disease reaction

1. Selection-4 (♂) 20 2 10.00 3 MR BGS 9(♀) 18 2 11.11 5 MS F1s 15 6 40.00 7 S

2. Selection-4 (♂) 22 2 9.09 3 MR Chinamung ♀) 18 12 66.67 9 HS F1s 18 5 27.78 7 S

3. Selection-4 (♂) 18 2 11.11 3 MR DGGV 2 (♀) 19 12 63.16 7 S F1s 16 3 18.75 5 MS

SI.No. Parents/crosses Total plants Infected plants % Disease incidence Disease score Disease reaction 1. RBL 1 (♂) 20 0 0.00 0 HR Selection-4 (♀) 21 2 9.52 3 MR F1s 20 2 10.00 3 MR

2. KBR-1 (♂) 22 0 0.00 0 HR Selection-4 (♀) 22 2 9.09 3 MR F1s 22 2 9.09 3 MR

3. KBR1 (♂) 22 1 4.55 1 R Chinamung (♀) 22 12 54.55 7 HS F1s 22 2 9.09 3 MR

4. KBR1 (♂) 20 0 0.00 0 HR Yellowmung (♀) 20 13 65.00 7 HS F1s 19 2 10.53 3 MR

5. RBL 50 (♂) 22 0 0.00 0 HR BGS9 ( ♀) 21 14 66.67 7 S F1s 18 1 5.56 3 MR

6. RBL35 (♂) 20 0 0.00 0 HR BGS 9 (♀) 19 12 63.16 7 HS F1s 18 1 5.56 3 MR

7. RBL 1 (♂) 22 1 4.55 1 R BGS 9 (♀) 19 5 26.32 7 S F1s 19 2 10.53 3 MR

8. RBL 35 (♂) 22 0 0.00 0 HR DGGV 2 (♀) 18 14 77.78 7 HS F1s 17 2 11.76 3 MR

9. RBL 35 (♂) 19 0 0.00 0 HR Chinamung (♀) 18 16 88.89 7 HS F1s 16 4 25.00 3 MR


parents and F1 hybrids were recorded 50 days after sowing,on individual plant basis.

In the inter-specific hybrids of mungbean, all threeF1 hybrids showed susceptibility to MYMV disease with aper cent disease incidence range from 18.75 to 40.0 with adisease score of 3 to 5 (Table 4). (if the resistance isgoverned by single recessive gene, then F1 should beuniformly susceptible with at par score of the parents)

In the inter-specific hybrids of mungbean × ricebean,all nine F1 hybrids showed moderately resistance to MYMVdisease with per cent disease incidence ranges from 5.56 to25.0 with a disease score of 3 (Table 3).

In the three F2 segregating populations of inter-specific crosses of mungbean, a good fit of 1:3 (Resistant:Susceptible) ratio was observed. This suggests that a singlerecessive gene controls resistance to MYMV disease inmungbean (Table 5).

On the other hand, nine F2 segregating populationsof inter-specific hybrids of mungbean × rice bean, a goodfit of 3:1 (Resistant: Susceptible) ratio was observed whichsuggested that a single dominant gene controls theresistance to MYMV disease in mungbean (Table 5)(if single dominant gene is responsible then F1 should behaving same reaction as of male parent).

There are conflicting reports about the genetics ofresistance to MYMV, claiming both resistance andsusceptibility to be dominant. In mungbean, resistance wasfound to be monogenic dominant. Present study has thesupport of the earlier reports by Gupta et al. (2005), Singhand Singh (2006), Sudha et al. (2013). The digenic recessivenature of resistance was reported by Singh et al. (2013)monogenic recessive control of MYMV resistance has alsobeen reported by Mishra et al. (2007).

The simple genetics of resistance to MYMV inmungbean will aid the breeders in the development of highyielding resistant genotypes through simple selection inthe segregating generations of crosses between resistantand susceptible genotypes.

REFERENCES

Bashir M, Iqbal MS, Ghafoor A, Ahmed Z and Qureshi AS. 2002.Variability in cowpea germplasm for reaction to virus infectionunder field conditions. Pakistan Journal of Botany 34: 47-48.

Chant SR. 1960. The effect of infection with tobacco mosaic andcowpea yellow mosaic viruses on the growth rate and yield ofcowpea in Nigeria. Journal of Experimental Agriculture 28: 114-120.

Gupta SK, Singh RA and Chandra S. 2005. Identification of a singledominant gene for resistance to mungbean yellow mosaic virusin black gram (Vigna mungo (L.) Hepper). Journal of PlantBreeding and Genetics 37(2): 85-89.

Haytowitz OB and Matthews RH. 1986. Composition of foods:legumes and legume products. United States Department ofAgriculture. Agriculture Hand Book 3: 8-16.

Ilyas MB. 1999. Production constraints of pulses in Pakistan. In:Proc. of 2nd National Conference of Plant Pathology, Universityof Agriculture Faisalabad, Pakistan pp 36-40.

Mali VR and Thottappilly G. 1986. Virus disease of cowpeas in thetropics. Rev. Tropic. Plant Disease 3: 361-403.

Mishra SP and Asthana AN. 2007. Inheritance of yellow mosaicvirus resistance in mungbean (Vigna radiata (L.) Wilczek). IndianJournal of Agricultural Sciences 23(1): 214-219.

Monika KP, Singh and Sareen PK. 2001. Cytogenetics studies inmungbean-rice bean hybrids. Journal of Applies Genetics 2(2):13-16.

Pandiyan M, Ramamoorthi N, Ganesh SK, Jebaraj S, Nagarajan PandBalasubramanian P. 2008. Broadening the genetic base andintrogression of MYMV resistance and yield improvementthrough unexplored genes from wild relatives in mungbean. PlantMutation Reports 2(2): 33-43.

Table 5. Inheritance of MYMV disease resistance in F2 populations of intra and inter-specific crosses

*Significance at p= 0.05

Number of plants in F2 Interspecific crosses (Mungbean) Resistant Susceptible

Total plants Expected Ratio χ2 calculated value (3:1)

χ2 Table value*

Selction-4× BGS 9 (R×S) 62 149 211 1:3 2.16 3.84 Selction-4× Chinamung (R×S) 57 127 184 1:3 3.51 3.84 Selction-4× DGGV 2 (R×S) 50 122 172 1:3 1.54 3.84 Inter-specific crosses(Ricebean is male parent so write other way)

3:1

RBL 1 × Selection-4 (R×S) 86 38 124 3:1 2.11 3.84 KBR 1 × Selection-4 (R×S) 94 42 136 3:1 2.51 3.84 KBR 1 × Chinamung (R×S) 90 42 132 3:1 3.27 3.84 KBR 1 × Yellowmung (R×S) 105 47 152 3:1 2.84 3.84 RBL 50× BGS 9 (R×S) 130 55 185 3:1 2.21 3.84 RBL 35 × BGS 9 (R×S) 115 50 165 3:1 2.47 3.84 RBL 1 × BGS 9 (R×S) 107 47 154 3:1 2.50 3.84 RBL 35 × DGGV2 (R×S) 98 44 142 3:1 2.71 3.84 RBL 35 × Chinamung (R×S) 115 47 162 3:1 1.08 3.84

Basavaraja et al. : Inheritance of resistance to MYMV in Vigna 1 9

Saleem M, Haris W and Malik IA. 1998. Inheritance of yellowmosaic virus resistance in mungbean. Pakistan Journal ofPhytopathol 10: 30-32.

Sandhu TS, Brar JS, Sandhu SS and Verma MM. 1985. Inheritance ofresistance to MYMV in green gram. Trend in Biosciences 22(1):607-611.

Selvi R, Muthiah AR, Manivannan N, Raveendran TS, Manicckamaand Samiyappan R. 2006. Tagging of RAPD marker resistancein mungbean [Vigna radiata (L.) Wilczek]. Asian Journal ofPlant Sciences 5(2): 277-280.

Shoyinka SA. 1974. Status of virus diseases of cowpea in Nigeria. Inpro.1st IITA Grain legume improvement workshop. pp 325.

Singh Gajraj, Singh Subhadra, Sheoran OP. 2013. Inheritance of

mungbean yellow mosaic virus resistance in mungbean [Vignaradiata (L.) wilczek]. Legume Researh 36(2): pp 131.

Singh SK and Singh MN. 2006. Inheritance of resistance to mungbeanyellow mosaic virus in mungbean. Indian Journal & PulsesResearch 19: 21.

Stebbins GL. 1958. The in viability, weakness and sterility ofinterspecific hybrids. Advances in Genetics 9: 147-215.

Sudha M, Karthikeyan A, Anusuya P, Ganesh NM, Pandiyan M,Senthil N and Raveendran M. 2013. Inheritance of resistanceMYMV in inter and intraspecific crosses of mungbean (Vignaradiata). American Journal of Plant Sciences 4: 1924-1927.

Williams RJ. 1977. Identification of multiple disease resistance incowpea. Tropical Agriculture 54(1): 53-59.


Identification of MYMV resistant and photo-thermo insensitive lines in mungbeanA NISHANT BHANU, MN SINGH and K SRIVASTAVA

Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi-221005, India; E-mail: [email protected](Received: March 18, 2017; Accepted: April 24, 2017)

ABSTRACT

Production and productivity of mungbean [Vigna radiata (L.)Wilczek], a self-pollinated crop grown in different seasonsi.e. Kharif, Rabi and Zaid in India, is adversely affected bylow (<15ºC) and high (>40ºC) temperature regimes as wellas susceptibility to prevalent diseases (mungbean yellowmosaic, cercospora leaf spot and powdery mildew). Thishampers the horizontal expansion of crops in diverse agro-climatic regions. However, ricebean [Vigna umbellata(Thunb.) Ohwi & Ohashi] represents useful reservoir ofdisease resistance genes as well as source of photo-thermoinsensitivity. Five genotypes of ricebean viz., RBL 1, RBL 6,RBL 9, RBL 35 and RBL 50 were evaluated for photo-thermoinsensitivity and resistance to yellow mosaic disease. Out ofthe five ricebean genotypes evaluated, RBL 9 had shownsubstantial amount of photo-thermo insensitivity as itflowered and set pods at both high (42.1ºC) as well as low(11ºC) temperature besides being resistant to yellow mosaicdisease. Pollen viability studies indicate 72% and 76% viablepollen at both low (11ºC) and high (42.1ºC) temperature,respectively. To transfer the desirable genes, three inter-specific crosses were made involving RBL 9 with threemungbean varieties (KM 2241, TM 96-2, K851). Inter-specificcross K 851 x RBL 9 exhibiting maximum pollen fertility of56.6%, with limited pod setting and resistance to MYMVdisease might be useful in developing the high yieldingmungbean genotypes.

Key words: Inter-specific hybridization, MYMV, photo-thermo insensitivity, pollen viability, Vignaradiata, Vigna umbellata

Production and productivity of pulses are affectedby several biotic (viral, fungal, bacterial pathogens andinsects) and abiotic (temperature, drought, salinity, water-logging etc.) stresses (Sahoo et al. 2002). Mungbean [Vignaradiata (L.) Wilczek] and urdbean [Vigna mungo (L.)Hepper] are the important grain legumes being grownthroughout the year (kharif, Rabi and zaid) in the country.Among biotic factors, mungbean yellow mosaic virus(MYMV) disease is one of the most destructive anddevastating diseases that limits the mungbean productionthroughout Asia, including India (Nariani, 1960, Nene 1973,Alam et al. 2014, Kumar et al. 2014). Yield loss of 76-100 percent has been reported in susceptible cultivars (Ayub etal. 1989, Gupta et al. 2013). Apart from this, a major constraintin horizontal expansion of mungbean is their photo-thermosensitive nature that makes them vulnerable to photoperiodand temperature fluctuations. Breeding for photo-thermo

insensitivity and disease resistance requires donors forthese traits without a possibility of linkage drag. With theadvent of molecular tools and techniques, new sources ofresistance to MYMV have been identified (Chen et al. 2012).It was reported that germplasm of V. umbellata and V.glabrescens have potential sources of photo-thermoinsensitivity (Pratap et al. 2012). By means of breeding, themajor genes or traits governing biotic stress resistance andabiotic stress tolerance can be introgressed into thesusceptible genotypes (Sehrawat et al. 2013a, 2014b). Widehybridization has been a promising option to transferdesirable genes from related species to mungbean.Moreover, ricebean [V. umbellata (Thunb.) Ohwi &Ohashi], an underutilized crop possesses many usefulcharacteristics such as disease resistance, particularly toMYMV, CLS and bacterial leaf spot along with the highestpotential grain yield among the Ceratotropis spp. (Somtaet al. 2006, Sehrawat and Yadav 2014). Legume virusesincluding DNA begomo viruses like MYMV are a threat tothe production of several legume crops i.e., mungbean,urdbean, cowpea etc. (Akram et al. 2015) Depending onthe severity of the MYM disease infection, the yield penaltyin mungbean may reach up to 85% (Haq et al. 2010). Everyyear, increasing incidence and epiphytotic conditions forMYMV is encountered. This may be attributed to acombination of determinants such as elevated populationof viruliferous whitefly, build-up of inoculum potential insome hosts besides wide range of favourable environmentalconditions (Shad et al. 2006). Hence, there is a possibilityof breakdown of resistance to MYMV under this complexecosystem. In fact, some begomo viruses have emerged asa serious and potential threat to many crops (Hamid 1999).Screening of mungbean genotypes in response to MYMVunder field conditions is required to determine the greaterresistance of genotypes to MYMV. Its utilization indeveloping stable resistant variety will enable to encounterthe favourable environmental conditions for the diseasedevelopment owing to the presence of enormous vectorpopulation in the field.

Hence, present investigation was initiated foridentification of photo-thermo insensitive donors in V.umbellata coupled with resistance against MYMV andconsequently their utilization in introgression of desirablegenes in mungbean through interspecific hybridization fordeveloping photo-thermo insensitive and MYMV resistantvarieties with wider adaptability.

Bhanu et al. : MYMV resistant and photo-thermo insensitive lines in mungbean 2 1


Seeds of five genotypes of ricebean, namely, RBL 1,RBL 6, RBL 9, RBL 35 and RBL 50 and three varieties ofmungbean viz., K 851, TM 96-2, KM 2241 were procuredfrom Department of Genetics & Plant Breeding, Institute ofAgricultural Sciences, BHU, Varanasi. For photo-thermoinsensitivity screening, seeds of parental lines were plantedin crossing block in cemented pots during the Kharif 2014.Each of ricebean genotypes was crossed with each ofmungbean variety in line x tester design for obtaining 15inter-specific crosses. Hybridization was completed usinghand emasculation and pollination (Boling et al. 1961). Thestigma of the mungbean is highly receptive in the earlyhours of the day. Therefore, the emasculation was donebetween 04:00-06:00 p.m. and pollination was performed inthe subsequent morning between 06:00 and 08:00 a.m.Observations were recorded on growth habit, growthpattern, plant height, days to first flowering, days tomaturity, per cent pod set besides pollen fertility (%) forscreening photo-thermo insensitivity. Viability of the freshpollen samples was determined based on observations onstainability of fresh pollen grains by acetocarmine techniqueas described by Roberts (1977). Two hundred pollen grainswere counted per slide with five slides each. Per cent pollenfertility was calculated as (the ratio between total numberof stained pollen and total number of pollen × 100). Normaldeeply stained pollen grains were counted as viable, whileweakly stained were recorded as non-viable (Pearson andHarney 1984). The planted material was maintained in thepots till June 2015.

Field trials for screening of MYMV disease weredone under natural conditions in randomized block designwith two replications using infector row method. One rowof infector line CO-5 variety of urdbean was raised afterevery two test entries to evaluate MYMV disease infection.Plants were randomly selected and number of leavesshowing clear symptoms (veinal yellowing and scatteredbright yellow spots) and total number of leaves were countedand percent disease incidence was calculated (Wheeler1969). Genotypes were scored on an arbitrary scale rangingfrom 0-5 as Highly Resistant (HR), Resistant (R), ModeratelyResistant (MR), Susceptible (S) and Highly Susceptible(HS) based on disease severity (Bashir et al. 2005 and Akhtaret al. 2009) (Table 1). Based on the recorded observations,ricebean genotypeshowing photo-thermo insensitivity andresistance against MYMV disease, the inter-specifichybrids along with the parents were grown in the potsduring kharif 2015 and data was further recorded foraforesaid six traits. Hybrids and their parents were alsoscreened for MYMV disease symptoms under fieldconditions.


During the study, wide variation was found in theweather parameters. Weekly maximum and minimum

temperature during the period of study i.e. July 2014 toMay 2015 is shown in figures 1 (a and b). The maximum andminimum temperature from July 2014 to December 2014varied from 17.9º-36.7ºC and 6.2º-28.7ºC, while that fromJanuary 2015 to May 2015, ranged from 14.5º-42.8ºC and7.8º-28.7ºC, respectively. Average sunshine hours rangedbetween 1.4 and 9.3 h during 2014 and 1.0-9.8 h during2015. Minimum temperature was recorded during the monthof December while maximum was recorded during the monthof May. Genotypes which survived and successfullycompleted reproductive phase during the cooler months ofDecember-January as well as during the warmer months ofApril-May were considered as photo- thermo insensitive.Large variations in days to flowering and maturity wereobserved among the ricebean and mungbean genotypeswhich ranged between 36-62 days and 65-125 days,respectively. Delay in pod set was also observed ingenotypes where onset of flowering was delayed. Afterattaining the complete maturity, plants could senesce anddie naturally in field. Ricebean genotype RBL 35 and RBL50 and all the three mungbean genotypes viz., K851, TM96-2, KM 2241 senesced and died after completing theirfirst life cycle by the end of November. However, ricebeanRBL 1, RBL 6 and RBL 9 rejuvenated again in January-February when the temperatures started to rise and showednormal growth during spring/summer season. This wasfollowed by normal flowering and pod set. The number ofdays to first flower was not influenced by the day length atmoderate temperature (up to 35ºC) in both mungbean andricebean. However, as the day length shortened andtemperature dropped down below 25ºC, the vegetativegrowth slowed down, consequently leading to delayedreproductive growth of ricebean genotypes RBL 35 andRBL 50 and all mungbean genotypes viz., K 851, TM 96-2,KM 2241. Contrary to this, with the decreasing temperature(minimum and maximum temperature between 10°C and25°C) and variable day length, the reproductive growthwas not much affected in case of ricebean genotypes RBL1, RBL 6 and RBL 9 as these sustained normal floweringand pod set even when the minimum temperature droppedto 15ºC. Observing normal reproductive behaviour in coolertemperature, pollen viability studies were conducted at lowtemperature i.e. 11.0ºC and 13.1ºC during first and secondweek of February 2015 and high temperature i.e. 42.8ºCand 42.1ºC during third and fourth week of May 2015. Atlow temperature i.e. 11ºC the pollen structure was alsonormal in ricebean genotypes RBL 1, RBL 6 and RBL 9,suggesting that these genotypes are relatively tolerant tocooler temperature. Among the five ricebean genotypesstudied, the maximum pollen viability of 76.8% and 72 %was exhibited by RBL 9 at low (11.0°C) and high (42.1°C)temperature, respectively. Hence, RBL 9 genotype wasidentified as photo- thermo insensitive genotype. Effect ofphotoperiod and temperature on pollen fertility of V.umbellata and V. glaberesens was also reported by Pratapet al. (2012). The ricebean genotype RBL 9 exhibited profuse


Table 1. Disease scoring scale (0-5) for MYMV disease based on percentage disease incidence (PDI)

012345678910

0102030405060708090

100

July

02-

08

09-1

5

16-2

2

23-2

9

30-0

5

Aug

06-

12

13-1

9

20-2

6

27-0

2

Sep

03-0

9

10-1

6

17-2

3

24-3

0

Oct

01-

07

08-1

4

15-2

1

22-2

8

29-0

4

Nov

05-

11

12-1

8

19-2

5

26-0

2

Dec

03-

09

10-1

6

17-2

3

24-3

1

27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

Temperature Max. Temperature Min. R. H. (Morn.) R. H. (Even.) Sunshine Hours

Figure 1a: Agro-meteorological parameters during the crop season(July 2014-December 2014).

growth habit with height of 125cm, long pods and boldseeds. While most of the ricebean genotypes flowered in60-62 days, the RBL 9 taken only 58 days for first flowering.

The crossability, pollen fertility, growth habit, growthpattern, days to first flowering, plant height and days tomaturity of inter-specific hybrids involving V. radiata andV. umbellata have been presented in Table 3 (a and b).Considerable variation was found in all inter-specificcrosses. The number of seeds pod-1 in F1 hybrid variedfrom 1 to 4. Highest (11.1%) and lowest (4.1%) crossabilitywas recorded in the inter-specific cross, TM 96-2 x RBL 9and KM 2241 x RBL 9, respectively. Varying degree ofsuccess in inter-specific hybridization was reported in earlierstudies also (Chen et al. 1977, Chowdhury and Chowdhury1977, Ahn and Hartmann 1977, 1978) owing to rreproductive

obstructions between the species (Adinarayanamurty etal. 1993). Nevertheless, in our study, results showed thatall the selected male and female parents were cross-compatible with each other. The hybrid seedlings initiallyshowed poor growth. However, after seedling stagevigorous growth of the hybrid plants was observed. Theindeterminate growth character of V. umbellata wasdominant in the F1 plants. Change in growth habit andflowering period was exhibited in the hybrids as theyshowed more vegetative growth and delayed floweringcompared to the parent. Appreciable increase in hybridvigour for seed size was observed over the parental lines.Large seed size may improve the grain yield per plant.Inheritance of bi-parental morphological characters by thehybrids confirmed their genetic purity (Dongre et al. 2010).The average pollen viability was observed to be maximum(56.6%) in the cross, K 851 x RBL 9 which was in conformitywith earlier reports (Ganeshram 1993, Subramaninan andMuthiah 2000).

Most accepted and effective strategy to control theMYMV disease and prevent the multiplication of virus isbreeding of cultivars with resistance. However, limitedsource of variability prevailing among the mungbeangenotypes limits the successful hybridization in most ofthe cases. A high proportion of ricebean (Vigna umbellata)lines containing desirable gene for MYMV resistance areavailable (Monika et al. 2001, Pandiyan et al. 2010).

In the present investigation, screening of genotypesof mungbean and ricebean showed that all the ricebeangenotypes are highly resistant. However, the mungbeangenotype KM 2241 was found to be resistant whereas TM96-2 and K 851 were moderately resistant and highlysusceptible, respectively. During kharif 2015, three inter-specific crosses involving RBL 9 with three mungbeanvarieties (KM 2241, TM 96-2, K 851) along with the parentswere screened for MYM symptoms under naturalepiphytotic field conditions. All the hybrids and their maleparent (RBL 9) were found to be highly resistant to MYMVdisease, while the female parent K851 was found to be highlysusceptible to MYMV (Table 4 a and b). Present studycorroborates earlier findings of Pandiyan et al. (2010) and

Disease Scale

Percent Infection Visual Symptoms Category Reaction Group

0 All plant free of disease symptoms

Complete absence of symptoms Highly Resistant HR

1 1-10%* Small yellowish spots scattered on some leaves Resistant R 2 11-20%* Yellowish bright spots common on leaves, easy to observe Moderately Resistant MR 3 21-30%* Yellowish bright specks common on leaves, easy to observe with larger

patches of symptoms Moderately Susceptible MS

4 30-50%* Bright yellow specks or spots on all leaves, minor stunting of plants and less number of pods

Susceptible S

5 50%* Yellowing or chlorosis of all leaves on whole plant, shortening of internode, severe stunting of plants with no yieldor few flowers and deformed pods produced with small, immature and shriveled seeds

Highly Susceptible HS

*Plants showing disease symptoms

Figure 1b: Agro-meteorological parameters during the crop season(January 2015-May 2015).

0

2

4

6

8

10

12

0102030405060708090

100

08-

14

15-

21

22-

28

29-

04

Feb

05-

11

12-

18

19-

25

26-

04

Ma

rch

05-

11

12-

18

19-

25

26-

01

Ap

ril0

2-0

8

09-

15

16-

22

23-

29

30-

06

May

07-

13

14-

20

21-

27

28-

03

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Temperature Max. Temperature Min. R. H. (Morn.) R. H. (Even.) Sunshine Hours

Bhanu et al. : MYMV resistant and photo-thermo insensitive lines in mungbean 2 3

Table 3 a. Growth habit, growth pattern, plant height, days to first flowering and maturity, and pollen fertility (%) forgenotypes (2014)

Crop Genotype Growth habit Growth pattern Plant height (cm)

Days to first flowering

Days to maturity

Pollen fertility (%) (42.1ºC) (11ºC)

Ricebean RBL 1 Tall, semi-compact with twinning habit Indeterminate 120 60 120 40.6 25.4 Ricebean RBL 6 Tall, semi-compact with twinning habit Indeterminate 115 60 125 36.8 22.4 Ricebean RBL 9 Tall, semi-compact with twinning habit Indeterminate 125 58 125 76.8 72.8 Ricebean RBL 35 Tall, semi-compact with twinning habit Indeterminate 115 62 115 0.00 0.00 Ricebean RBL 50 Tall, semi-compact with twinning habit Indeterminate 110 62 120 0.00 0.00 Mungbean KM 2241 Medium, erect and compact Determinate 62 36 70 40.00 0.00 Mungbean TM 96-2 Medium, erect and compact Determinate 60 38 65 44.6 0.00 Mungbean K 851 Medium, erect and compact Determinate 72 40 77 38.7 0.00

Table 3 b. Growth habit, growth pattern, plant height, days to first flowering and maturity, and pollen fertility (%) for inter-

specific crosses (2015)

Cross Growth habit Growth pattern

Plant height (cm)

Crossability (%)

Days to first flowering

Days to maturity

Pollen fertility (%)

KM 2241 x RBL 9 Semi erect and compact Indeterminate 86 4.1 54 96 24.3 K 851 x RBL 9 Semi erect and compact Indeterminate 88 4.4 54 110 56.6 TM 96-2 x RBL 9 Semi erect and compact Indeterminate 72 11.1 52 104 42.4

Table 4 a. Disease scoring scale for the genotypes for Mungbean Yellow Mosaic Virus (2014)

S. No. Crop Plant Material Percentage Disease Incidence Disease Score Disease Reaction 1 Ricebean RBL 1 0 0 Highly Resistant 2 Ricebean RBL 6 0 0 Highly Resistant 3 Ricebean RBL 9 0 0 Highly Resistant 4 Ricebean RBL 35 0 0 Highly Resistant 5 Ricebean RBL 50 0 0 Highly Resistant 6 Mungbean KM 2241 3.6 1 Resistant 7 Mungbean TM 96-2 11.6 2 Moderately Resistant 8 Mungbean K 851 82.1 5 Highly susceptible

Table 4 b. Disease scoring scale for the genotypes and crosses for Mungbean Yellow Mosaic Virus (2015)

S. No. Crop Plant Material Percentage Disease Incidence Disease Score Disease Reaction 1 Ricebean RBL 1 0 0 Highly Resistant 2 Ricebean RBL 6 0 0 Highly Resistant 3 Ricebean RBL 9 0 0 Highly Resistant 4 Ricebean RBL 35 0 0 Highly Resistant 5 Ricebean RBL 50 0 0 Highly Resistant 6 Mungbean KM 2241 4.8 1 Resistant 7 Mungbean TM 96-2 15.8 2 Moderately Resistant 8 Mungbean K 851 86.5 5 Highly susceptible 9 Mungbean x Ricebean KM 2241 x RBL 9 0 0 Highly Resistant 10 Mungbean x Ricebean TM 96-2 x RBL 9 0 0 Highly Resistant 11 Mungbean x Ricebean K 851 x RBL 9 0 0 Highly Resistant

Sehrawat and Yadav (2014). Further evaluation ofsegregating generations of these hybrids will help indetermining the inheritance of resistance and photo-thermosensitivity and lead to development of stable and improvedbreeding linesof mungbean .

Present study concludes that the RBL 9 genotype ofricebean possess substantial amount of pollen fertility atboth extremes of temperature (high and low) exhibitingphoto-thermo insensitive behaviour along with resistance

to MYMV disease. The hybrids developed utilising this asdonor in hybridization exhibited a high level of resistanceagainst MYMV disease. Inter-specific hybridizationmediated MYMV disease resistance can be introduced inother vulnerable Vigna species also to improve MYMVdisease resistance. F2 populations developed can be furtherused as a mapping population or to develop recombinantinbred lines for the identification of gene/quantitative traitloci for MYMV resistance and photo-thermo insensitivity.


ACKNOWLEDGEMENT

We are thankful to the Department of Science andTechnology, Govt. of India for funding and supporting theresearch programme by providing the DST INSPIREFellowship to the first author.

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Estimation of genetic variability and inter-relationships of quantitative traits forimprovement of kabuli chickpea (Cicer arietinum L.)NEHA DHURIA and ANITA BABBAR

Department of Plant Breeding & Genetics, JNKVV, Jabalpur-482004, Madhya Pradesh, India; E-mail:nehadhuria.14@ gmail.com(Received: August 18, 2016; Accepted: December 21, 2016)

ABSTRACT

The present investigation was carried out during Rabi 2013-14 and 2014-15 in Seed Breeding Farm, College ofAgriculture, Jabalpur (M.P.) to estimate the genotypicvariability, characters association and direct and indirecteffects of characters towards yield and its contributing traitsof 68 kabuli chickpea (Cicer arietinum L.) genotypes, grownin RCBD with 3 replications in normal planting. Resultsrevealed that height of first fruiting node and number ofseeds per plant had maximum GCV and PCV as well as highheritability along with high genetic advance as % of meanunder all the environments and number of effective podsper plant in EI and EII indicating ample scope for geneticimprovement and selection. Correlation analysis revealedthat seed yield per plant was highly significant and positivelycorrelated with total number of pods per plant, number ofeffective pods per plant, number of seeds per plant, biologicalyield per plant and harvest index in all environmentsindicating strong linkage at genetic level. Considering thecorrelation and path coefficient analysis an ideal plant typein kabuli chickpea would be one with more effective podsand having high harvest index and biological yield per plant.Comprehensive examination of pooled results revealed thatmost putative lines of kabuli chickpea based on seed yieldwere IPCK 2004-29, IPCK 2009-145, CSJK 4, NBeG 176,PKV 4, IPCK 2002-29, IPCK 2004-29-1, ICCV 13310, ICCV13314, ICCV 13309, JGK 27, JGK 12, JGK 23, JGK 1, JGK 3and KAK 2.

Key words: Correlation coefficient analysis, Genotypicvariability, Heritability, Path coefficient analysis

Among pulses chickpea (Cicer arietinum L.) is amajor crop widely grown during Rabi season. The geneticarchitecture of seed yield can be better resolved throughcomponent traits rather than yield per se, as yield is theend product of multiplicative interactions between variousyield components. Therefore, genetic variability isessentially required for making genetic improvement incomponent traits. The mutual relationship between variousplant characters and its direct and indirect effects on seedyield ensure the actual contribution of an attribute as wellas its influence through other traits. Hence, availableinformation will be very helpful to assess the appropriatebreeding strategies and identification of promisinggenotypes for improvement of kabuli chickpea.


Sixty eight genotypes of kabuli chickpea were grownin randomized completely block design with 3 replicationsfor two years in EI (2013-14) and EII (2014-15) at SeedBreeding Farm, College of Agriculture, Jabalpur (M.P.),India. Standard statistical analysis was employed togenerate data for different analysis. Observations wererecorded on 16 quantitative characters viz., days to flowerinitiation, days to 50% flowering, days to pod initiation,days to maturity, plant height, height of first fruiting node,number of primary branches per plant, number of secondarybranches per plant, total number of pods per plant, numberof effective pods per plant, number of seeds per plant,number of seeds per pod, 100 seed weight, biological yieldper plant, harvest index and seed yield per plant. The meandata were subjected to standard statistical techniques toevaluate and isolate the most promising genotypes basedon pooled analysis.


Estimates of variance were highly significant in EI,EII and pooled analysis for all the economical andphenological traits under study. A relative comparison ofthe magnitude of PCV and GCV for different traits revealedthat the maximum amount of variability was present in heightof first fruiting node and number of seeds per plant underboth environments (Table 1), which is in agreement withthe findings of Arora and Jeena (2001) and Kumar et al.(2001). Babbar et al. (2012), indicated that the selection ofthese traits would be effective and number of effective podsper plant and seed yield per plant also revealed high GCVand PCV in EI and EII but exhibited moderate effect in pooledanalysis. Low GCV and PCV were noted for 100 seed weightin all the environments. High heritability along with highgenetic advance as % of mean were noted for the traits likeheight of first fruiting node, number of effective pods perplant and number of seeds per plant in all the environments.Similar results were reported by Arora and Jeena (2001),Singh and Singh (2013) and Padmavathi et al. (2013) forseed yield per plant, indicating predominantly the presenceof additive gene action in the expression of these traits andconsequently chance of improving these traits throughsimple selection. High heritability estimates accompanied


with low genetic advance as percentage of mean wasestimated for days to maturity in all the environmentsreflects the presence of non-additive gene effects.

Association analysis was undertaken to determinethe direction of selection and number of characters to be

considered in improving seed yield. In this study, seedyield per plant was highly significant and positivelycorrelated with total number of pods per plant, number ofeffective pods per plant, number of seeds per plant,biological yield per plant and harvest index in EI, EII and

Table 1. Genetic parameters for quantitative traits of kabuli chickpea in EI, EII and pooled analysis

GCV = genotypic coefficient of variance, PCV = phenotypic coefficient of variance, ECV = environmental coefficient of variance,GA = genetic advance, h2(bs) = heritability in broad sense, HFN = height of first fruiting node, PB = number of primary branches per plant,SB = number of secondary branches per plant, TP = total number of pods per plant, EP = number of effective pods per plant, SP = number ofseeds per pods, SPP = number of seeds per plant, 100SW = 100 seeds weight, BY = biological yield per plant, HI = harvest index andSY = seed yield per plant

Range Coefficient of Variation Character Env Grand mean Min Max GCV (%) PCV (%) ECV (%)

h2 (bs) GA at 5% GA % of mean at 5%

EI 42.9 32.6 73.3 28.2 28.5 3.4 98.5 24.8 57.8 EII 42.2 32 72.6 28.2 28.4 3.6 98.4 24.3 57.7

DFI

Pooled 42.5 33 73 28.2 28.3 2.3 99.3 24.7 58.0 EI 50.7 42.6 81.3 23.3 23.5 3.1 98.2 24.2 47.6 EII 48.6 38.6 80 25.2 25.4 3.1 98.5 25.1 51.6

DF 50%

Pooled 49.7 40.3 80.6 24.2 24.3 2.1 99.2 24.7 49.7 EI 59.4 47.6 88.6 18.9 19.1 2.3 95.5 23.0 38.8 EII 58.9 46.3 86 19.1 19.2 2.7 98.0 22.9 38.9

DPI

Pooled 59.2 47.1 87.3 18.9 19.0 1.7 99.2 23.0 38.9 EI 116.2 101.6 132.3 4.6 4.8 1.3 91.9 10.6 9.1 EII 117.5 103 135.6 4.1 4.4 1.5 88.5 9.5 8.1

DM

Pooled 116.9 102.3 134 4.4 4.5 1.0 95.0 10.3 8.8 EI 62.6 46.6 83.5 12.6 13.0 3.3 93.3 15.7 25.1 EII 64.1 47.6 84.5 12.2 12.5 2.7 95.1 15.7 24.6

PH

Pooled 63.3 47.1 83.7 12.4 12.6 2.1 97.0 16.0 25.2 EI 7.7 3.5 27.4 71.5 71.8 6.5 99.2 11.3 64.7 EII 7.4 3.7 25.0 65.9 66.7 10.2 97.7 10.0 64.3

HFN

Pooled 7.6 3.6 26.0 68.7 68.9 5.4 99.4 10.7 64.0 EI 2.4 1.9 3.2 9.97 13.4 8.9 55.4 0.3 15.2 EII 2.4 2.1 3.0 7.2 11.8 9.3 37.2 0.2 9.05

PB

Pooled 2.4 2.0 3.1 8.13 10.1 6.0 64.1 0.3 13.4 EI 8.1 4.2 14.9 24.2 27.7 13.6 75.9 3.5 43.4 EII 8.6 4.9 16.8 24.1 25.2 7.5 91.1 4.0 47.5

SB

Pooled 8.4 4.3 15.9 24.2 25.5 7.9 90.0 3.9 47.5 EI 37.7 16.4 68.3 25.8 28.1 11.0 84.6 17.5 48.9 EII 57.2 26.7 90.5 28.8 30.5 9.9 89.5 32.0 56.2

TP

Pooled 46.4 27.0 73.6 21.3 22.5 7.2 89.7 19.3 41.6 EI 24.9 9.5 60.8 34.8 37.9 14.8 84.7 16.5 66.1 EII 41.4 11.6 79.5 37.8 39.4 10.9 92.3 31.0 74.9

EP

Pooled 33.2 15.3 62.0 29.5 30.9 8.9 91.7 19.3 58.3 EI 1.9 1.1 2.8 12.6 20.2 15.8 38.6 0.30 16.1 EII 1.1 0.5 2.0 20.3 26.7 17.4 57.5 0.30 31.7

SP

Pooled 1.5 1.13 2.0 10.6 16.5 12.6 41.5 21.4 14.1 EI 26.6 8.8 59.2 35.2 37.8 13.7 86.7 18.0 67.6 EII 45.8 12.1 93.0 42.4 44.4 13.3 90.9 38.1 83.3

SPP

Pooled 36.2 13.2 65.9 32.2 33.7 9.9 91.4 23.0 63.4 EI 35.3 24.5 49.5 14.3 14.9 4.3 91.5 9.9 28.2 EII 35.1 25.0 49.3 14.4 14.9 3.7 93.6 10.1 28.8

100SW

Pooled 35.2 24.7 49.4 14.4 14.7 2.8 96.3 10.2 29.1 EI 40.3 23.1 85.5 23.7 26.3 11.4 81.6 17.7 43.9 EII 51.2 26.7 86.7 26.5 28.8 11.1 85.0 25.8 50.4

BY

Pooled 45.7 31.8 80.3 18.7 20.4 8.0 84.5 16.2 35.5 EI 22.4 10.3 37.8 26.7 31.2 16.1 73.4 10.5 47.2 EII 31.3 9.7 46.3 29.7 32.6 13.4 83.0 17.5 55.8

HI

Pooled 26.8 12.5 38.7 23.8 25.6 9.4 86.3 12.2 45.5 EI 8.9 3.7 19.3 32.2 36.3 16.9 78.9 5.2 59.0 EII 16.3 4.0 32.0 36.1 38.5 13.5 87.7 11.4 69.6

SY

Pooled 12.6 5.4 20.2 26.3 28.2 10.0 87.3 6.4 50.7

Dhuria & Babbar : Genetic variability and inter-relationships of quantitative traits of kabuli chickpea 2 7

pooled analysis (Table 2). These findings in accordancewith Dar et al. (2012), Kumar et al. (2012), Waseem et al.(2014), Tesfamichael et al. (2015), Joshi and Yasin (2015)shows strong linkage at genetic level. While days tomaturity, number of primary branches per plant and numberof secondary branches per plant exhibited significantpositive correlation in EI and number of seeds per pods inEII indicating fluctuation trend in different environment.These traits seem to be major yield factors, hence selectionof these traits will be effective for constructing plant typeof kabuli chickpea for high seed yield in differentenvironments. On the other hand, height of first fruitingnode revealed significant negative correlations with seedyield per plant in all the environments. However, 100 seedsweight in EI, days to flower initiation in EII and remainingfour traits viz., days to 50% flowering, days to pod initiation,days to maturity, plant height and number of secondarybranches per plant expressed highly significant negativeassociation with seed yield per plant in EII and pooledanalysis.

Genotypic path analysis revealed that days to flowerinitiation had the highest positive direct effect on seedyield per plant followed by harvest index, biological yieldin EI, EII and pooled analysis (Table 3). Shrivastava et al.(2012), Padmavathi et al. (2013), Joshi and Yasin (2015) havefound same results for harvest index and biological yield.While number of effective pods per plant in EI and days to50 % flowering in EII had expressed high positive directeffects towards seed yield per plant. Similar results havealso been reported by Kumar et al. (2012), Waseem et al.(2014). Thus, these traits had maximum contribution towardsseed yield per plant. Therefore a simple selection based onthese traits can easily enhance the yield level.

Total number of pods per plant showed negative directeffect on seed yield per plant in both the environments.These results are not in agreement with the findings ofDar et al. (2012), Kumar et al. (2012), and Padmavathi et al.(2013). However, days to 50% flowering in EI and Pooledanalysis, number of effective pods per plant (Pooledanalysis) and number of secondary branches per plant in

Table 2. Correlation coefficient analysis for quantitative traits of kabuli chickpea in EI, EII and pooled analysisCha. ENV DFI DF50% DPI DM PH HFN PB SB TP EP SP SPP 100SW BY HI SY

EI 1.00 0.982*** 0.971*** 0.231*** 0.600*** 0.855*** 0.365*** 0.528*** 0.078 -0.266*** 0.319*** -0.267*** -0.239** 0.2174** -0.222* -0.0834EII 1.00 0.99*** 0.972*** 0.221** 0.555*** 0.857*** 0.265*** 0.594*** -0.240 ** -0.48*** -0.130 -0.516*** -0.231** 0.1507 * -0.597*** -0.487***

DFI

Pooled 1.00 0.993*** 0.98*** 0.233*** 0.587*** 0.864*** 0.414*** 0.584*** -0.147* -0.493*** 0.166* -0.527*** -0.242*** 0.257*** -0.548*** -0.452EI 1.000 0.977*** 0.238*** 0.590*** 0.846*** 0.367*** 0.521** 0.1030 -0.234*** 0.324*** -0.234*** -0.262*** 0.238*** -0.222** -0.074EII 1.000 0.979*** 0.220 ** 0.536*** 0.845*** 0.263*** 0.579*** -0.226 ** -0.469*** -0.120 -0.500*** -0.230** 0.1387* -0.570*** -0.469***

DF 50%

Pooled 1.000 0.985*** 0.237*** 0.575*** 0.855*** 0.411*** 0.571*** -0.135 -0.485*** 0.165* -0.514*** -0.252*** 0.258*** -0.545*** -0.449***EI 1.000 0.258*** 0.580*** 0.848*** 0.344*** 0.489*** 0.1118 -0.236*** 0.335*** -0.231*** -0.235 ** 0.229*** -0.234*** -0.0799EII 1.000 0.206 ** 0.511*** 0.827*** 0.238*** 0.521*** -0.204** -0.445*** -0.110 -0.466*** -0.246*** 0.1415* -0.553*** -0.450***

DPI

Pooled 1.000 0.240*** 0.559*** 0.848*** 0.372*** 0.527*** -0.136 -0.47*** 0.175* -0.499*** -0.248*** 0.237*** -0.544*** -0.450***EI 1.000 0.220 ** 0.251*** 0.365*** 0.332*** 0.351*** 0.25 *** 0.177 * 0.380*** -0.0423 0.402*** 0.206** 0.4105***EII 1.000 0.215** 0.224** 0.035 0.286*** -0.193** -0.25*** -0.139 * -0.305*** -0.019 -0.200** -0.139* -0.321***

DM

Pooled 1.000 0.225** 0.243*** 0.255*** 0.323*** -0.019 -0.101 0.036 -0.13 -0.032 0.045 -0.014 -0.132EI 1.000 0.59*** 0.376*** 0.332*** 0.1357 -0.131 0.218** -0.1459* -0.002 0.385*** -0.366*** -0.061EII 1.000 0.566*** 0.334*** 0.323*** -0.098 -0.232*** -0.226 ** -0.324 *** 0.0173 0.215** -0.467*** -0.285***

PH

Pooled 1.000 0.593*** 0.434*** 0.34*** -0.012 -0.245*** 0.035 -0.321*** 0.008 0.407*** -0.534*** -0.267***EI 1.000 0.310*** 0.488*** 0.0513 -0.254*** 0.338 *** -0.276*** -0.181** 0.198** -0.317*** -0.1708*EII 1.000 0.263*** 0.527*** -0.266 ** -0.510*** -0.039 -0.504*** -0.190** 0.097 -0.569*** -0.486***

HFN

Pooled 1.000 0.353*** 0.524*** -0.204** -0.529*** 0.227** -0.538*** -0.192** 0.188** -0.582*** -0.508***EI 1.000 0.566*** 0.241 *** 0.1116 0.078 0.060 0.0503 0.356*** 0.0346 0.210**EII 1.000 0.343*** -0.0067 -0.052 -0.151* -0.144* 0.110 0.135 -0.174* -0.072

PB

Pooled 1.000 0.557*** 0.038 -0.121 -0.019 -0.222** 0.078 0.288*** -0.190** -0.068EI 1.000 0.278 *** 0.1151 0.251*** 0.068 -0.165* 0.411*** 0.0919 0.246***EII 1.000 -0.199 ** -0.340*** -0.1168 -0.422*** -0.179* 0.107 -0.398*** -0.371***

SB

Pooled 1.000 -0.016 -0.223* 0.142* -0.322*** -0.179* 0.313*** -0.240*** -0.216**EI 1.000 0.7835*** -0.068 0.649*** -0.319*** 0.615*** 0.355*** 0.687***EII 1.000 0.836*** -0.0526 0.752*** -0.077 0.551*** 0.372*** 0.720***

TP

Pooled 1.000 0.825*** -0.148* 0.724*** -0.241*** 0.554*** 0.363*** 0.710***EI 1.000 -0.269*** 0.724*** -0.1844** 0.525*** 0.440*** 0.736***EII 1.000 -0.0678 0.846*** 0.0110 0.324*** 0.623*** 0.822***

EP

Pooled 1.000 -0.317*** 0.821*** -0.095 0.292*** 0.597*** 0.799***EI 1.000 -0.0756 -0.0871 0.0043 -0.110 -0.122EII 1.000 0.382*** -0.169* 0.074 0.257*** 0.305***

SP

Pooled 1.000 0.013 -0.179* 0.002 -0.900 -0.081EI 1.000 -0.322*** 0.453*** 0.545*** 0.787***EII 1.000 -0.098 0.359*** 0.676*** 0.913***

SPP

Pooled 1.000 -0.235*** 0.210** 0.665*** 0.864***EI 1.000 -0.166* -0.013 -0.138*EII 1.000 -0.029 0.075 0.0774

100 SW

Pooled 1.000 -0.143* 0.049 -0.017EI 1.000 -0.037 0.550***EII 1.000 -0.257*** 0.375***

BY

Pooled 1.000 -0.283*** 0.272***EI 1.000 0.714***EII 1.000 0.717***

HI

Pooled 1.000 0.746***EI 1.000EII 1.000

SY

Pooled 1.000


Table 3. Estimation of genotypic path for quantitative traits in EI, EII and pooled analysis

Env-1-(R square=0.9636 Residual effect= 0.1908)Env-2-(R square=0.9815 Residual effect= 0.1359)Pooled -(R square=0.9741 Residual effect= -0.1611)

EI had the maximum negative direct effect on seed yield perplant. Shrivastava et al. (2012) recorded difference in resultsfor number of effective pods per plant.

Path analysis exhibited that biological yield, harvestindex and number of effective pods per plant in EI wasyield determining components in kabuli chickpea. It notonly exhibited maximum direct effect on seed yield but alsoshowed high positive indirect effect via other charactersand significant and positive correlation on seed yield perplant. The above finding suggests that these charactersshould be given due importance at the time of breedingprogramme for improvement of seed yield. Harvest indexrecorded highest positive indirect effect on seed yield perplant via number of seeds per plant followed by number ofeffective pods per plant, total number of pods per plant inall environments. Thus, selection of these characters mayenhance the yield potential widely in all the environmentsunder study. However, it exhibited maximum negativeindirect effect through plant height followed by days to

flower initiation, days to 50% flowering, days to podinitiation and height of first fruiting node in all environments.The results are in close agreement with the findings ofShrivastava et al. (2012), Padmavathi et al, (2013) and Joshiand Yasin (2015). Therefore, this character should beconsidered in the selection programme during chickpeaimprovement rather than making selection for yield per se.These traits should be taken into account while formulatingbreeding strategies of chickpea in different plantings. Theresidual effect was very low indicating that characterselected for the study was appropriate.

Considering the correlation and path coefficientanalysis for seed yield per plant and its component traitsan ideal plant type in kabuli chickpea would be one withmore effective pods and having high harvest index andbiological yield per plant. Therefore, more emphasis shouldbe given to these components while making selection forhigher seed yield in chickpea. Comprehensive examinationof pooled analysis results revealed that the 16 most putative

Cha Env DFI DF50% DPI DM PH HFN PB SB TP EP SP SPP 100SW BY HI SY EI 0.9697 0.9618 0.9526 0.2342 0.6025 0.8413 0.4715 0.5891 0.0888 -0.284 0.5193 -0.2814 -0.243 0.2315 -0.2545 -0.0993EII 2.0577 -2.0532 -2.0273 -0.4866 -1.181 -1.7961 -0.9667 -1.2888 0.5226 1.0403 0.3566 1.1237 0.5025 -0.3377 1.3641 -0.5248

DFI

Pooled 0.7987 0.796 0.788 0.1909 0.477 0.6956 0.413 0.4888 -0.1219 -0.4116 0.2163 -0.4415 -0.1968 0.2223 -0.4752 -0.4865EI -0.9007 -0.9081 -0.8936 -0.2309 -0.5596 -0.7793 -0.4441 -0.5402 -0.1061 0.2307 -0.4849 0.2317 0.2472 -0.2372 0.2396 -0.0883EII 2.4215 2.4268 2.4011 0.5714 1.3424 2.0929 1.0708 1.4675 -0.5778 -1.1949 -0.3908 -1.275 -0.5903 0.3667 -1.5412 -0.5037

DF 50%

Pooled -0.7599 -0.7624 -0.7545 -0.1859 -0.4465 -0.6574 -0.3855 -0.455 0.1075 0.3876 -0.2056 0.4095 0.1956 -0.2155 0.4504 -0.4815EI 0.0979 0.0981 0.0997 0.0271 0.0604 0.0856 0.0462 0.0558 0.0115 -0.0267 0.0533 -0.0254 -0.0244 0.0246 -0.0282 -0.1005EII -0.4412 -0.443 -0.4478 -0.0979 -0.237 -0.3793 -0.1754 -0.2447 0.0996 0.2082 0.0661 0.2202 0.1159 -0.0692 0.2769 -0.4878

DPI

Pooled -0.0138 -0.0138 -0.014 -0.0034 -0.008 -0.0119 -0.0065 -0.0077 0.002 0.007 -0.0038 0.0073 0.0035 -0.0036 0.0082 -0.4823EI 0.0017 0.0018 0.002 0.0072 0.0018 0.0019 0.0035 0.0027 0.0029 0.002 0.0022 0.003 -0.0003 0.0034 0.0018 0.4773EII -0.0126 -0.0126 -0.0117 -0.0534 -0.012 -0.0128 -0.0057 -0.0169 0.0118 0.0144 0.0103 0.0177 0.0007 0.0113 0.0087 -0.351

DM

Pooled -0.0242 -0.0247 -0.0249 -0.1013 -0.0239 -0.0253 -0.0335 -0.0351 0.0017 0.0108 -0.0068 0.0141 0.003 -0.0054 0.0018 -0.1411EI 0.0212 0.021 0.0207 0.0083 0.0341 0.021 0.0175 0.0132 0.0051 -0.0053 0.0127 -0.0059 -0.0002 0.0146 -0.0145 -0.083EII 0.019 0.0183 0.0175 0.0074 0.0331 0.0196 0.0182 0.0116 -0.0033 -0.0081 -0.0102 -0.0115 0.0007 0.0082 -0.0172 -0.3042

PH

Pooled 0.0361 0.0354 0.0345 0.0143 0.0604 0.0366 0.0326 0.0222 -0.0007 -0.0159 0.0038 -0.0208 0.0005 0.0268 -0.035 -0.2944EI -0.0366 -0.0362 -0.0362 -0.011 -0.026 -0.0422 -0.0174 -0.0237 -0.0025 0.0118 -0.0228 0.0124 0.0083 -0.0092 0.0153 -0.1892EII 0.0511 0.0505 0.0496 0.014 0.0347 0.0585 0.0254 0.0329 -0.0169 -0.0317 -0.0035 -0.0317 -0.012 0.0065 -0.0376 -0.53

HFN

Pooled -0.0099 -0.0098 -0.0097 -0.0028 -0.0069 -0.0114 -0.005 -0.0063 0.0025 0.0063 -0.0039 0.0064 0.0023 -0.0023 0.0072 -0.5469EI 0.0358 0.036 0.0341 0.0353 0.0378 0.0304 0.0736 0.0554 0.0208 0.0056 0.0341 0.0055 0.006 0.0338 0.0063 0.2854EII 0.0403 0.0379 0.0336 0.0091 0.0471 0.0372 0.0858 0.0487 0.0034 -0.0072 -0.0255 -0.0204 0.0161 0.021 -0.0287 -0.1435

PB

Pooled 0.019 0.0185 0.017 0.0121 0.0198 0.0162 0.0367 0.0256 0.0024 -0.0056 0.0017 -0.0097 0.0035 0.0118 -0.0074 -0.0991EI -0.1145 -0.1121 -0.1056 -0.071 -0.0729 -0.1057 -0.1419 -0.1884 -0.0629 -0.026 -0.1009 -0.0153 0.0353 -0.0859 -0.0312 0.316EII -0.0332 -0.0321 -0.029 -0.0168 -0.0186 -0.0298 -0.0301 -0.053 0.0112 0.0198 0.0107 0.0245 0.0106 -0.0065 0.0249 -0.4223

SB

Pooled -0.0921 -0.0898 -0.0828 -0.0522 -0.0552 -0.0837 -0.1049 -0.1505 0.0032 0.0365 -0.0332 0.054 0.0283 -0.0532 0.0401 -0.2412EI -0.0139 -0.0177 -0.0175 -0.0604 -0.0227 -0.0089 -0.0429 -0.0507 -0.1517 -0.1292 0.0132 -0.1091 0.0543 -0.1021 -0.0643 0.7599EII 0.0345 0.0324 0.0302 0.0299 0.0137 0.0392 -0.0054 0.0287 -0.1359 -0.1195 0.0086 -0.1083 0.011 -0.0795 -0.0576 0.777

TP

Pooled -0.0293 -0.0271 -0.0282 -0.0032 -0.0022 -0.0416 0.0126 -0.0041 0.1923 0.1677 -0.0516 0.1476 -0.0495 0.1141 0.0769 0.7757EI -0.09 -0.078 -0.0823 0.0868 -0.0477 -0.086 0.0234 0.0424 0.2616 0.3072 -0.0826 0.2444 -0.0674 0.1724 0.1656 0.8003EII -0.1067 -0.1039 -0.0981 -0.057 -0.0514 -0.1143 -0.0178 -0.0788 0.1855 0.211 -0.0071 0.1883 0.0018 0.0744 0.1436 0.8762

EP

Pooled 0.0931 0.0919 0.0905 0.0193 0.0475 0.1004 0.0277 0.0438 -0.1577 -0.1808 0.0711 -0.1569 0.0197 -0.0545 -0.1178 0.8544EI 0.0309 0.0308 0.0308 0.0173 0.0214 0.0311 0.0267 0.0308 -0.005 -0.0155 0.0576 -0.0057 -0.0087 0.0046 -0.0124 -0.1141EII -0.0085 -0.0079 -0.0073 -0.0095 -0.0151 -0.0029 -0.0147 -0.01 -0.0031 -0.0017 0.0493 0.0194 -0.0125 0.0037 0.0116 0.3131

SP

Pooled 0.0015 0.0015 0.0015 0.0004 0.0003 0.0019 0.0003 0.0012 -0.0015 -0.0022 0.0056 -0.0003 -0.0016 0.0001 -0.0012 -0.2064EI -0.0444 -0.0391 -0.039 0.0628 -0.0263 -0.0449 0.0115 0.0124 0.1101 0.1218 -0.0152 0.1531 -0.0541 0.0763 0.0937 0.8391EII -0.1177 -0.1132 -0.106 -0.0715 -0.0746 -0.1166 -0.0512 -0.0997 0.1718 0.1923 0.0847 0.2155 -0.0236 0.0849 0.1527 0.9478

SPP

Pooled -0.1438 -0.1397 -0.1359 -0.0361 -0.0896 -0.1476 -0.0686 -0.0934 0.1997 0.2258 -0.0159 0.2601 -0.0657 0.0558 0.1831 0.8956EI 0.0079 0.0086 0.0077 0.0015 0.0002 0.0062 -0.0026 0.0059 0.0113 0.0069 0.0047 0.0111 -0.0315 0.0063 0.0003 -0.173EII -0.0058 -0.0058 -0.0061 -0.0003 0.0005 -0.0049 0.0044 -0.0047 -0.0019 0.0002 -0.006 -0.0026 0.0237 -0.0006 0.002 0.0805

100 SW

Pooled -0.0132 -0.0137 -0.0135 -0.0016 0.0004 -0.0107 0.0051 -0.0101 -0.0138 -0.0058 -0.0157 -0.0135 0.0535 -0.0083 0.0028 -0.0273EI 0.1065 0.1165 0.1102 0.2098 0.1915 0.0971 0.2047 0.2035 0.3003 0.2503 0.0353 0.2225 -0.0893 0.4462 0.0031 0.5837EII 0.0746 0.0687 0.0702 -0.0964 0.1133 0.0501 0.1115 0.0554 0.2659 0.1605 0.0345 0.1792 -0.0116 0.4548 -0.117 0.3899

BY

Pooled 0.116 0.1178 0.1082 0.0223 0.1852 0.0848 0.1343 0.1474 0.2475 0.1256 0.0067 0.0894 -0.0645 0.4169 -0.1261 0.2688EI -0.1707 -0.1716 -0.1841 0.1603 -0.2775 -0.2365 0.0557 0.1078 0.2757 0.3505 -0.1402 0.3982 -0.0053 0.0045 0.6503 0.7708EII -0.3825 -0.3664 -0.3568 -0.0936 -0.2992 -0.371 -0.1927 -0.2705 0.2443 0.3925 0.1352 0.4087 0.0476 -0.1484 0.577 0.762

HI

Pooled -0.4647 -0.4615 -0.4584 -0.0137 -0.4527 -0.4929 -0.1573 -0.208 0.3124 0.5089 -0.175 0.5497 0.0409 -0.2363 0.7812 0.7889

Dhuria & Babbar : Genetic variability and inter-relationships of quantitative traits of kabuli chickpea 2 9

lines of kabuli chickpea were IPCK 2004-29, IPCK 2009-145, CSJK 4, NBeG 176, PKV 4, IPCK 2002-29, IPCK 2004-29-1, ICCV 13310, ICCV 13314, ICCV 13309, JGK 27, JGK12,JGK 23, JGK 1, JGK 3 and KAK 2. These genotypes exhibitedhigh values in relation to yield related traits.

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Babbar A, Prakash V, Tiwari P and Iquebal MA. 2012. Geneticvariability for chickpea (Cicer arietinum L.) under late sownseason. Legume Research 35(1): 1-7.

Dar SA, Ishfaq A, Khan MH, Pir FA, Ali G and Manjar A. 2012.Studies on genetic variability and Interrelationship for yield andyield component characters in chickpea (Cicer arietnum L.).Trends in Biosciences 5(2): 119-121.

Joshi P and Yasin M. 2015. Interrelationship among yield and yieldcontributing traits in RILs and their parents in Chickpea (Cicerarietinum L.). Indian Journal of Applied and Pure Biology 30(1):97-100.

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Genetic variability for selective tolerance to imazethpyr in chickpea (Cicerarietinum L.)K BHANU REKHA, V JAYALAKSHMI, T SRINIVAS, M SUDHA RANI and P UMAMAHESWARI

Regional Agricultural Research Station, Nandyal, Andhra Pradesh-518502, India; E-mail: [email protected](Received: January 17, 2017; Accepted: March 3, 2017)

ABSTRACT

Herbicide tolerant varieties offer opportunity for timelycontrol of weeds through need-based applications ofherbicides. Post-emergence herbicides for weed control inchickpea could be efficiently used when the availablecultivars are not sensitive to the given herbicide. In order toidentify sources of herbicide tolerance for the commonlypost emergence herbicide viz., imazethapyr, a study wasundertaken involving thirty chickpea genotypes duringwinter 2015-16. Assessment of genotypes following herbicideapplication revealed large genetic variation for tolerance toimazethapyr. Herbicide tolerance scores (HTS) of genotypesranged from 2.0 to 3.7 at 10 days after spray. At 30 days afterspray, except JG 11 (2.3) all other genotypes recovered fullyand recorded HTS of 2.0. But the overall decrease in grainyield due to imazethapyr was 18.5 % which ranged from1.63% to 45% across genotypes. A few promising chickpealines viz., ICCIL 01034, ICCV 09106, ICCIL 01026, ICCIL01031, ST-3-D-2, NBeG 49, NBeG 3, NBeG 47 and JG 11were identified with tolerant to moderately tolerant reactionto imazethapyr with less yield penalty. In both ‘control’ and‘spray’ plots, high values of heritability and genetic advancewere also recorded for shoot biomass, 100 seed weight, harvestindex and grain yield.

Key words: Genetic advance, Grain yield, Herbicide tolerancescore, Heritability, Imazethapyr

Annually chickpea is grown in an area of 14.80 m hain the world producing 14.23 m t with an average productivityof 962 kg ha-1. In India, chickpea is cultivated in 10.74 m hawith production of 9.88 m t and a productivity of 919.9 kgha-1 (Anonymous 2016). The success story of chickpeacultivation in the country is mainly attributed to growinghigh yielding varieties with matching productiontechnologies. If this could be coupled with cost cuttingpractices such as farm mechanization, this would lead to itspromotion. However, use of machines is mostly confinedto some of the field operations except for weeding andharvesting in chickpea. Hand weeding and mechanical weedcontrol methods were traditionally followed in thedeveloping countries. Moreover, the crop is sensitive toherbicides and use of herbicide is not popular. Amongstherbicides meant to be applied at different stages of thecrop/weed, again choice of post-emergence herbicides islimited in comparison to pre-emergence herbicides due tosensitivity of crop to such application. In addition, the pre-

emergence herbicides are effective in controlling weeds atearly stage of seedling growth, but weeds germinating aftercrop emergence become dominant in the field and causesubstantial yield losses (Solh and Pala 1998). Thus,management of weeds in chickpea is expensive especiallywhen it is carried out through manual weeding. This couldbe solved by herbicide tolerant cultivars as these becomestolerant to post emergence application of herbicides. Hence,there is a need to screen and develop such varieties so thatweeds are controlled efficiently and the cultivation of cropbecomes remunerative.


The present study was carried out during winterseason of 2015 at Regional Agricultural Research Station,Nandyal, Andhra Pradesh (located at 15º29' N latitude and78º29' E longitude with an altitude of 211.76 m above meansea level) that comes under the scarce rainfall agro-climaticzone of the state. Out of thirty genotypes taken for theexperiment, 25 were obtained from International CropsResearch Institute for the Semi-Arid Tropics (ICRISAT),Patancheru and the remaining five were obtained fromgenetic stock of Regional Agricultural Research Station,Nandyal, Andhra Pradesh. These thirty genotypes werecombined with two herbicide treatments (that involved a‘spay’ and ‘control’) and were evaluated in a RandomizedBlock design with three replications. Each genotype wasraised in one row plot of 4 meter length with inter rowspacing of 30 cm and plant to plant spacing of 10 cm so asto evaluate the influence of herbicide on yield and yieldattributes of chickpea. Standard recommended agronomicmeasures were taken up to raise a healthy crop. Thegenotypes in spray plots were applied with post emergenceherbicide of imazethapyr (62.5 g/ha) at 30 days after sowingand herbicide tolerance scores (HTS) at 10, 20 and 30 daysafter spray were recorded using 1-5 scale (1for highlytolerant and 5 for highly sensitive). Observations wererecorded based on five randomly selected plants for 11characters such as days to 50% flowering, days to maturity,plant height, number of branches and pods per plant, SPADchlorophyll meter reading (SCMR), specific leaf area (SLA),shoot biomass, 100 seed weight, harvest index and grainyield. Standard statistical techniques were used for analysisof data.

Rekha et al. : Genetic variability for selective tolerance to imazethpyr in chickpea (Cicer arietinum L.) 3 1


Assessment of plant appearance and leaf symptomsafter herbicide application was proved to be a rapid andreliable measurement of tolerance to imazethapyr inchickpea (Taran et al. 2010). Imazethapyr, an imidazolinone(IMI includes Imazethapyr) compound, is used as a selectiveherbicide to control most annual grasses and certain broadleaf weeds. Imazethapyr inhibits amino acid synthesis andcan be applied both as pre-emergence as well as post-emergence in chickpea and other legume crops. Theyprovide flexibility in application time, lower rates ofapplication and have low mammalian toxicity (Tan et al.2015). These compounds act by inhibiting acetolactatesynthase (ALS, E.C. 4.1.3.18), a key enzyme in the synthesisof branched-chain amino acids like valine, leucine andisoleucine (Stidham 1991). After being translocated throughphloem, it inhibits ALS resulting in the death of meristematiccells and finally the whole plant (Little and Shaner 1991).The imidazolinone group of herbicides is registered in

Turkey for the control of broadleaf weeds in chickpea(Kantar et al. 1999).

The present experimental results on herbicidetolerance and other attributes revealed significantdifferences among 30 genotypes (for 8 out of 11 charactersunder spray and 10 out of 11 characters in control. Thedifferences among the genotypes for number of branchesand specific leaf area in spray and SPAD Chlorophyll MeterReading (SCMR) in both control and spray were however,not significant. The per se performance of 30 genotypes inspray and control revealed that herbicide tolerance scores(HTS) of genotypes ranged from 2.0 to 3.7at 10 days afterspray (Table 1). Sixteen genotypes viz., ICCV 10, ICCV 08109,ICCIL 04021, ICCV 08102, ICCIL 04016, ICCV 97105, ICCV11101, ST-3-D-2, ICCV 95008, ICCV 97007, ICCV 95013, ICCV93122, ICCV 93054, ICCV 96005, ICC 1205 and N BeG 119recorded HTS of 2.0 which was observed at 10 days afterspray and were categorized as tolerant. The genotype NBeG47 (with HTS of 3.7) was moderately tolerant having visual

Table 1. Per se performance of thirty chickpea genotypes at 10 DAS as influenced by imazethapyr application

Table 1 contd..............

S. No.

Genotype Days to 50% flowering (days)

Days to maturity (days)

Plant height (cm)

Branches/plant Pods/plant SPAD chlorophyll meter reading

Control Spray Control Spray Control Spray Control Spray Control Spray Control Spray 1 ICCV 10 46.0 59.3 78.3 92.7 36.4 32.3 13.5 15.2 27.5 18.7 47.4 44.8 2 ICCV 08109 43.0 51.3* 80.3 86.0 41.7* 36.7 15.1 15.9 35.2* 18.2 45.5 46.8 3 ICCIL 01034 37.7** 55.0 81.7 90.0 36.5 36.7 15.9 16.5 31.2 22.0 45.8 45.5 4 ICCV 09106 36.3** 51.0* 76.3 84.3* 33.7 34.1 16.7 16.5 29.9 27.6 48.5 44.1 5 ICCIL 01026 40.3** 54.0 76.3 86.3 37.5 35.0 12.9 15.7 31.4 23.5 43.7 41.9 6 ICCIL 04021 46.0 55.0 80.3 86.7 36.9 37.7 14.6 16.4 26.0 26.0 43.2 40.2 7 ICCIL 04004 44.3 58.3 85.3 88.7 35.3 32.1 14.7 18.4 27.3 21.9 44.8 46.3 8 ICCIL 01031 38.0** 54.3 75.0* 84.0* 34.9 35.9 16.0 18.8 34.1 19.9 44.4 42.8 9 ICCV 08102 42.0* 52.0 83.3 91.7 43.5** 41.5** 12.9 17.2 30.2 27.6 47.2 43.2

10 ICCV 04307 42.0* 51.3* 84.7 97.7 39.9 38.0 11.4 14.7 24.2 20.1 40.9 40.7 11 ICCIL 04016 46.0 52.7 84.7 84.7* 38.3 32.9 14.0 12.9 28.1 20.1 45.3 42.4 12 ICCV 97105 55.0 57.0 80.3 92.3 38.4 35.1 12.1 15.4 25.6 18.7 47.5 43.2 13 ICCV 11101 36.3** 49.7** 75.7 84.7* 35.7 33.9 13.4 13.1 31.8 20.1 42.1 47.0 14 N BeG 510 37.3** 49.7** 76.3 84.7* 35.5 35.2 15.2 11.8 24.8 22.2 43.0 44.8 15 ST-3-D-2 45.3 58.7 78.0 92.0 37.7 38.3 16.6 21.7 29.8 23.4 45.7 44.7 16 ICCV 95008 42.0* 60.0 76.3 92.0 37.1 30.9 14.5 14.7 30.5 21.9 48.7 46.8 17 ICCV 97007 58.3 59.3 85.7 98.3 34.1 33.1 11.2 13.5 25.6 14.2 46.0 43.9 18 ICCV 95013 45.7 56.0 78.3 91.0 34.3 29.9 14.5 15.5 28.8 19.8 42.5 46.9 19 ICCV 93122 55.0 60.0 80.3 93.7 38.3 30.9 14.1 15.2 30.6 24.5 46.3 45.6 20 ICCV 93054 36.7** 51.0* 75.0* 84.7* 32.9 31.7 16.7 17.0 33.5 22.2 43.9 44.1 21 ICCV 96005 45.7 59.0 79.3 91.3 39.1 34.5 12.1 16.5 28.3 19.7 45.6 44.8 22 JSC 38 53.0 60.0 82.0 92.3 39.8 33.1 16.6 14.4 29.7 19.4 42.7 43.4 23 JAKI 9218 45.3 52.3 77.0 84.3* 36.2 30.5 13.5 12.4 28.4 17.1 50.1 40.9 24 KAK 2 44.6 53.7 80.0 85.7 44.7** 39.9* 12.9 16.5 30.7 34.2** 47.9 41.8 25 ICC 1205 57.6 60.0 87.0 91.7 39.0 33.1 15.3 15.7 32.0 24.3 44.3 47.1 26 N BeG 49 36.6** 51.3* 79.7 83.7* 37.1 35.0 18.3* 14.5 34.2 23.7 41.8 44.5 27 JG-11 36.3** 50.7 79.3 83.0** 32.9 35.0 17.4 14.1 33.9 22.0 45.5 42.6 28 N BeG 3 42.6 54.0 77.0 86.7 36.7 33.3 13.5 16.0 31.5 27.6 41.2 45.1 29 N BeG 47 40.0** 51.3* 77.7 86.3 46.3** 48.3** 11.6 12.7 33.4 22.9 40.9 44.8 30 N BeG 119 36.3** 50.3** 75.0* 83.7* 34.1 32.8 12.5 14.9 23.0 22.2 44.4 42.8

Mean 43.7 54.6 79.5 88.5 37.5 34.9 14.3 15.5 29.7 22.2 44.9 44.1 SEm (±) 0.6 1.2 1.5 1.3 1.5 1.5 1.3 1.9 1.7 2.8 2.5 1.9 CD (P=0.05) 1.7 3.3 4.2 3.7 4.2 4.3 3.7 NS 4.8 8.1 NS NS CD (P=0.01) 2.2 4.3 5.5 4.9 5.5 5.8 4.9 NS 6.3 10.7 NS NS CV (%) 2.3 3.7 3.2 2.6 6.8 7.6 15.8 20.9 9.8 22.2 9.7 7.4


Table 1…….. Contd…..

*Significant at P=0.05, ** Significant at P=0.01, DAS1: Days after spray

S. No Genotype

Specific Leaf Area (cm2 g-1)

Shoot biomass (g/plot ) Harvest index (%) 100 in-seed

weight (g) Grain yield

(kg/ha ) Herbicide Score

(Days after spray)

Control Spray Control Spray Control Spray Control Spray Control Spray Spray

10 DAS 20 DAS 30 DAS 1 ICCV 10 131.5 199.0 194.7 199.0 50.7 41.7 20.0 17.7 1650 1389 2.0 2.0 2.0 2 ICCV 08109 181.0 192.0 212.3 204.0 43.4 38.3 23.2 21.3 1534 1292 2.0 2.0 2.0 3 ICCIL 01034 193.1* 179.3 291.3* 255.7 52.2 39.7 31.7 32.0 2522** 1789 2.3 2.3 2.0 4 ICCV 09106 107.7 170.6 269.7 244.7 63.5** 56.1** 24.3 23.3 2856** 2289** 2.7 2.0 2.0 5 ICCIL 01026 151.0 209.5 237.7 248.2 60.8** 44.2 32.3 33.3 2412** 1850 2.3 2.3 2.0 6 ICCIL 04021 189.1 147.7 201.7 222.7 50.2 26.7 32.7 31.0 1662 979 2.0 2.0 2.0 7 ICCIL 04004 176.8 182.0 212.2 180.0 46.5 29.9 22.8 19.0 1650 897 2.3 2.0 2.0 8 ICCIL 01031 186.4 155.1 236.5 293.2 59.4** 47.7 34.2 35.3 2355* 2317** 2.3 2.0 2.0 9 ICCV 08102 209.7** 208.4 288.3 307.3* 44.2 46.9 26.5 22.7 2139 2379** 2.0 2.0 2.0

10 ICCV 04307 198.3* 193.2 198.3 161.7 41.9 45.5 36.5 37.7 1384 1189 2.3 2.0 2.0 11 ICCIL 04016 137.8 136.7 198.7 242.8 42.7 28.8 23.2 20.0 1412 1162 2.0 2.0 2.0 12 ICCV 97105 200.7* 189.6 200.7 197.7 48.0 32.1 25.3 24.7 1584 1055 2.0 2.0 2.0 13 ICCV 11101 178.8 171.9 189.7 226.7 59.3** 45.1 24.2 27.0 1867 1689 2.0 2.0 2.0 14 N BeG 510 211.3** 199.7 222.7 257.8 57.0* 46.9 40.0** 42.7** 2117 1995 3.3 2.0 2.0 15 ST-3-D-2 149.7 153.5 267.3 250.7 52.8 51.0* 27.0 25.7 2372* 2114* 2.0 2.0 2.0 16 ICCV 95008 123.1 191.0 177.8 167.7 50.2 37.2 21.3 23.3 1489 1022 2.0 2.7 2.0 17 ICCV 97007 88.7 148.7 199.3 166.3 18.5 29.8 20.0 20.7 612 797 2.0 2.0 2.0 18 ICCV 95013 131.5 138.5 212.2 210.5 45.7 42.1 21.2 19.0 1629 1489 2.0 2.0 2.0 19 ICCV 93122 155.2 135.4 230.8 167.5 41.0 44.6 20.0 19.7 1579 1217 2.0 2.0 2.0 20 ICCV 93054 137.0 202.3 256.7 203.3 62.2** 50.8* 24.5 22.3 2662** 1722 2.0 2.7 2.0 21 ICCV 96005 203.3* 181.1 254.7 216.3 47.3 33.1 25.7 22.3 2005 1162 2.0 2.0 2.0 22 JSC 38 210.7** 204.8 224.0 210.2 47.7 35.5 31.0 25.7 1789 1250 2.3 2.0 2.0 23 JAKI 9218 161.0 194.7 219.7 196.3 60.2** 45.4 22.5 28.0 2200 1500 3.0 2.7 2.0 24 KAK 2 112.5 181.8 256.0 181.8 53.3 57.6** 26.7 31.7** 2279* 1739 2.3 2.0 2.0 25 ICC 1205 136.7 144.6 212.3 172.3 42.8 31.7 22.0 15.3 1522 917 2.0 2.0 2.0 26 N BeG 49 208.2** 158.3 275.0 353.3** 54.0 44.2 30.2 30.3 2455** 2612** 2.7 2.0 2.0 27 JG-11 154.3 189.5 271.0 240.3 63.9** 48.9 25.0 23.7 2889** 1917 3.3 3.0 2.3 28 N BeG 3 151.7 138.0 258.8 293.7 50.8 42.9 30.2 30.7 2179 2129* 2.3 2.0 2.0 29 N BeG 47 124.3 176.3 285.5 295.7 55.4 37.7 30.0 32.7 2622** 1850 3.7 2.0 2.0 30 N BeG 119 225.9** 200.6 153.3 270.8 60.5** 51.8* 37.5** 43.0** 1550 2334** 2.0 2.0 2.0

Mean 164.2 175.8 230.3 227.9 50.9 41.8 27.1 26.7 1650 1389 SEm (±) 10.5 20.1 21.2 27.7 2.2 3.0 2.4 1.1 198 223 CD (P=0.05) 29.6 NS 59.9 78.5 6.2 8.5 6.8 3.2 562 630 CD (P=0.01) 39.4 NS 79.7 104.5 8.3 11.3 9.1 4.2 747 839 CV (%) 11.0 19.8 15.9 21.1 7.5 12.4 15.4 7.2 17.5 24.1

symptoms of fair plant appearance with moderate burning/chlorosis of leaves. Three genotypes viz., JAKI 9218 (3.0),NBeG 510 (3.3) and JG 11 (3.3) were also moderately tolerant.HTS ranged between 2.3 to 2.7 in ICCV 09106 (2.7), NBeG49 (2.7), ICCIL 01034 (2.3), ICCIL 01026 (2.3), ICCIL 04004(2.3), ICCIL 01031 (2.3), ICCV 04307 (2.3), JSC 38(2.3), KAK2 (2.3) and NBeG 3 (2.3); and were categorized as tolerant.

Similar to the present study, a range of naturalvariation for tolerance to imazethapyr/imazamox wasreported in chickpea (Taran et al. 2012, Gaur et al. 2013,Chaturvedi et al. 2014, Jayalakshmi et al. 2015). The existenceof genetic variation in the present study indicates that it isfeasible to improve tolerance to imazethapyr byconventional breeding using tolerant genotypes. Althougheffects of herbicides on the different chickpea cultivarswere similar in many cases, some cultivars appeared to bemore sensitive than others. These differences were notcorrelated with the type of seed in chickpea (bold seededor kabuli versus small seeded or desi), and the underlyingreasons for such differential responses were littleunderstood (Taran et al. 2012).

At 20 days after spray, HTS in different genotypesranged from 2.0 to 3.0. As many as 24 genotypes recoveredfully and were categorized as tolerant with HTS of 2.0 whilefive genotypes had HTS ranged between 2.3 and 2.7. Onlyone genotype (JG 11 with HTS of 3.0) was moderatelytolerant having visual symptoms of fair plant appearancewith moderate burning/chlorosis of leaves. At 30 days afterspray, except JG 11, all the genotypes recovered fully.Therefore, the best categorization of the tolerant and thesensitive genotypes was to be made at 10 days after spray.

Among genotypes, mean grain yield per plot incontrol ranged from 612 kg/ha (ICCV 97007) to 2889 kg/ha(JG 11). In spray, the range was from 797 kg/ha (ICCV 97007)to 2612 kg/ha (NBeG 49). Grain yield was reduced in mostof the genotypes due to spray. The overall decrease ingrain yield due to herbicide spray was 18.5 % (ranged from45% in ICCIL 04004 to 1.63% in ICCIL 01031). Reduction ingrain yield was however, observed up to 49% in spray in 21breeding lines studied at four locations (Sajja et al. 2015).Here in the present experiment, there was no yield penaltyin genotypes like NBeG 119, ICCV 97007, ICCV 08102 and


NBeG 49. These are needed to be tested extensively forutilization in breeding programmes so as to exploit PGR forcommercial cultivation after standardizing their performanceby further screening.

The influence of herbicide on other charactersindicated that days to 50 per cent flowering was delayed intest genotypes under spray. It was extended by a day inICCV 97007 whereas the flowering in ICCV 95008 wasdelayed for 18 days. This was due to injury to apical budswhen herbicide was sprayed followed by proliferation ofnew flushes that started flowering a little late compared tocontrol. Similarly in comparison to control, maturity periodwas also delayed by 3.4 days in ICCIL 04004 and 15.7 daysin ICCV 95008. The general mean of plant height was 37.5cm and 34.9 cm in control and spray, respectively. Plantheight was also reduced at least by 5.0 cm due to spray ofherbicide (ICCIL 04016 with 5.4 cm, JAKI 9218 with 5.7 cm,ICC 1205 with 5.9 cm, ICCV 95008 with 6.2 cm, JSC 38 with6.7 cm and ICCV 93122 with a maximum of 7.4 cm). It wasalso reported that application of imazethapyr caused delayedflowering and maturity, reduced plant height and yield inchickpea (Taran et al. 2012).

Similarly, the mean value for number of branches perplant ranged from 11.2 (ICCV 97007) to 18.3 (N BeG 49) witha general mean 14.3 in control. In spray, this trait rangedbetween 11.8 (NBeG 510) to 21.7 (ST-3-D-2) with a generalmean of 15.5. Spraying of herbicide resulted in death of

apical buds. The genotypes recovered after spray andproduced branches again and therefore, some of thegenotypes viz., ST-3-D-2 (5.1), ICCV 96005 (4.4) and ICCV08102 (4.3) produced more number of branches comparedto control. Due to herbicide spray, there was a drasticreduction in number of pods in most of the genotypes. Thedecrease was higher in ICCV 08109 (17) and ICCIL01031(14.2), whereas the pod number of genotypes viz.,NBeG 119 (0.8), ICCV 09106 (2.3), ICCV 08102 (2.6), NBeG510 (2.6) and NBeG 3 (3.9) and ICCIL 04021 (0) were notinfluenced by herbicide spray. Thicker leaves (low SLA)indicated higher potential for greater assimilation underdrought stress. Low SLA, as a selection criterion forenhancing transpiration efficiency (TE), was thus,suggested as economically surrogate trait for droughttolerance (Wright et al. 1994). Here in the presentexperiment, the mean SLA ranged from 88.7 cm2g-1 (ICCV97007) to 225.9 cm2g-1 (NBeG 119) in control with a meanvalue of 164.2 cm2g-1 while in spray, it ranged from 135.4cm2g-1 (ICCV 93122) to 209.5 cm2g–1 (ICCIL 01026) with themean value of 175.8 cm2g-1. However, these differences werenon-significant among the genotypes in spray which mightbe due to injury to the foliage following herbicide sprayand possible recovery of genotypes a little later.

Similarly in control, shoot biomass per plot rangedfrom 153.3 g (NBeG 119) to 291.3 g (ICCIL 01034). ICCIL01034 (291.3 g) was significantly superior to general mean

Table 2…….. Contd…..

Table 2. Estimates of genetic parameters following application of imazethapyr for 11 characters in 30 chickpea genotypes.

S. No Character Mean Range Genotypic coefficient of variation (GCV) (%)

Control Spray Control Spray Control Spray 1 Days to 50 % flowering (days) 43.72 54.61 36.33-58.33 49.66-60.00 14.90 6.35 2 Days to maturity (days) 75.00 83.67 75.00-87.00 83.00-98.00 3.93 4.63 3 Plant height (cm) 34.13 32.80 32.93-46.33 29.93-48.26 7.87 9.79 4 Branches per plant 14.32 15.45 11.20-18.26 11.81-21.73 9.41 5.49 5 Pods per plant 29.70 22.19 22.99-35.16 14.16-34.16 9.22 11.70 6 SPAD Chlorophyll Meter Reading 44.89 44.10 40.89-50.07 40.19-47.06 1.32 1.17 7 Specific Leaf Area (cm2 g-1) 164.23 175.79 88.70-225.89 135.40-209.48 21.32 7.59 8 Shoot biomass (g/plot) 230.29 227.94 153.33-291.33 161.66-353.33 12.59 17.40 9 Harvest Index (%) 50.88 41.79 18.49-63.93 26.66-57.60 17.71 18.36 10 100-seed weight (g) 27.05 26.72 20.00-40.00 15.33-43.00 18.35 26.39 11 Seed yield (g/plot) 117.93 96.07 83.00-173.33 47.83-156.66 24.53 29.17

S.No. Character Phenotypic coefficient of variation (PCV) (%)

Heritability (h2) (%)

Genetic advance (GA)

Genetic advance as % of mean

Control Spray Control Spray Control Spray Control Spray 1 Days to 50 % flowering(days) 14.96 6.69 99 90 13.36 6.78 30.57 12.42 2 Days to Maturity(days) 4.34 4.86 82 90 5.84 8.04 7.34 9.09 3 Plant height (cm) 8.79 10.72 80 83 5.44 6.42 14.51 18.41 4 Branches per plant 13.11 13.23 51 17 1.99 0.72 13.90 4.69 5 Pods per plant 10.82 17.35 72 45 4.80 3.60 16.18 16.25 6 SPAD chlorophyll meter reading 5.42 4.40 -06 07 -0.30 0.28 -0.67 0.64 7 Specific Leaf Area (cm2g-1) 22.25 13.71 91 30 69.13 15.22 42.09 8.66 8 Shoot biomass (g/plot) 15.58 21.24 65 67 48.27 66.98 20.96 29.38 9 Harvest Index (%) 18.23 19.70 94 86 18.04 14.73 35.45 35.25

10 100-seed weight (g) 20.40 26.72 80 97 9.20 14.35 34.01 53.70 11 Seed yield (kg/ha) 26.52 32.31 85 81 55.12 52.10 46.74 54.24


of 230.3 g. Among spray, it ranged from 161.7 g (ICCV04307) to 353.3g (NBeG 49). NBeG 49 (353.3 g) recordedhighly significant value while ICCV 08102 (307.3 g) recordedsignificantly superior value compared to the general meanof 227.9 g. Again there was reduction in biomass ingenotypes due to spray viz., KAK 2 (74.2 g) and ICCV93122 (63.3 g) which could be attributed to reduction innumber of pods per plant. Reduction in grain yield andother yield attributes was also reported due to spray ofimazethapyr in 21 breeding lines of chickpea evaluated atfour locations (Sajja et al. 2015).

Harvest index is an important physiological indexthat provides a useful measure of source sink relationship.Here also, harvest index ranged from 18.5 per cent (ICCV97007) to 63.9 per cent (JG 11) in control. ICCV 09106(63.5%), ICCIL 01026 (60.8%), ICCV 93054 (62.1%), JAKI9218 (60.2%), JG 11(63.9%), N BeG 119 (60.5%), ICCIL 01031(59.4%) and ICCV 11101 (59.3%) recorded highly significantvalues of harvest index compared to the mean value of50.9% in control. NBeG 510 (57.0 %) was found to besignificantly superior to the general mean. Similarly, amongspray, the mean value ranged from 22.6 per cent (ICCIL04021) to 57.6 per cent (KAK 2). The genotypes viz., ICCV09106 (56.1%) and KAK 2 (57.6%) recorded higher valuesof harvest Index compared to that of general mean (41.8%).ST-3-D-2 (51.0%), ICCV 93054 (50.8%) and NBeG 119 (51.8%)were significantly superior to the general mean value of41.8%. Thus, harvest index (HI) was not influenced by sprayof herbicide in almost all the genotypes. However, ICCIL04021 recorded inferior harvest index under spray owing toits poor yield (58.7 g). Similarly, in the present study, 100-seed weight ranged from 20.0 g (ICCV 97007) to 40.0 g (NBeG 510) in control whereas it varied from 15.3 g (ICC 1205)to 43.0 g (NBeG 119) in spray. Increase in 100-seed weightin spray was reported in 21 breeding lines studied at fourlocations (Sajja et al. 2015).

The performance of 30 genotypes as affected by postemergence application of imazethapyr was quantified interms of genetic parameters of variability. Phenotypic andgenotypic coefficient of variation (PCV and GCV),heritability in broad sense and genetic advance as per centof mean (GAM) for 11 characters were estimated underboth control and spray conditions (Table 2). High PCV andGCV values were recorded for grain yield and specific leafarea in control, whereas high PCV and GCV values wererecorded for grain yield and 100-seed weight in spray. Thecorrespondence between PCV and GCV values for grainyield and 100-seed weight clearly indicated that these traitswere less influenced by the environment and therefore,these are useful traits in the selection process. PCV andGCV values for most of the traits exhibited same trend inspray and control conditions except for SLA. Shoot biomass,100-seed weight, harvest index and grain yield recordedhigh values of heritability and genetic advance in bothcontrol and spray. These traits should be given priority inbreeding programmes intended to improve tolerance to

imazethapyr as they could be improved with ease with simplephenotypic selection and with greater expected genetic gain.Some legumes and many oilseed crops are sensitive to IMIherbicides and could be severely injured by the presenceof herbicide in the soil at a level as low as 0.5 ppb or lessthan 5% of the recommended rates for weed control (Stork1995).

The existence of tolerance to imazethapyr orimazamox is not unique to chickpea as natural geneticvariation in tolerance to IMI herbicides has been observedin fieldpea with post emergence application of the herbicide(Hanson and Thill 2001). The mode of inheritance oftolerance to ALS-inhibiting herbicides (Acetolactatesynthase) has also been reported to be relatively simplewith a single, dominant nuclear-gene in some species (Leeand Owen 2000, Van Eerd et al. 2004) or a single, partiallydominant gene in others (Boutsalis and Powles 1995,Kolkman et al. 2004). The present study has also indicatedthe possibility for exploitation of chickpea germplasm thatexhibited tolerance to imazethapyr.

REFERENCES

Anonymous 2016. FAO statistical year book. Food and agricultureorganization of the United Nations.

Boutsalis P and Powles SB. 1995. Inheritance and mechanism ofresistance to herbicides inhibiting acetolactate synthase inSonchusoleraceus L. Theoretical and Applied Genetics 91: 242-7 .

Chaturvedi SK, Muraleedhar A, Gaur PM, Mishra N, Singh K andNadarajan N. 2014. Genetic variation for herbicide tolerance inchickpea. Indian Journal of Agricultural Sciences 84: 968-70.

Gaur PM, Aravind K, Srinivasan S, Chaturvedi SK, Sarvjeet S, TripathiS, Inderjit S, Guriqbal S, Das TK, Muraleedhar A, Neelu M,Nagaswamy N and Gowda CLL. 2013. Large genetic variabilityin chickpea for tolerance to herbicides imazethapyr andmetribuzin.

Hanson BD and Thill DC. 2001. Effects of imazethapyr andpendimethalin on lentil (Lens culinaris), pea (Pisumsativum),and a subsequent winter wheat (Triticumaestivum) crop. WeedTechnology 15: 190-194.

Jayalakshmi V, Muniratnam P, Nadeep Kumar N, Peddaswamy D,Gaur PM and Kamakshi K. 2015. Genetic variability fortolerance to post emergence herbicide imazethapyr in chickpea(Cicer arietinum L.). Brain storming meeting on promotion ofpulses in Indo-Gangetic plains of India, 31st August Compendiumof Abstracts p 351.

Kantar F, Elkoca E and Zengin H. 1999. Chemical and agronomicalweed control in chickpea (Cicer arietinum L. cv. Aziziye-94).Turkey Journal of Agriculture and Forestry 23: 631-635.

Kolkman JM, Slabaugh MB, Bruniard JM, Berry S, Bushman BS andOlungu C. 2004. Acetohydroxyacid synthase mutationsconferring resistance to imidazolinone or sulfonylurea herbicidesin sunflower. Theoretical and Applied Genetics 109: 147-59.

Lee JM and Owen MDK. 2000. Comparison of acetolactate synthaseenzyme inhibition among resistant and susceptible Xanthiumstrumarium biotypes. Weed Science 48: 286-90.

Little DL and Shaner DL. 1991. Absorption and translocation ofthe imidazolinone herbicides. In: DL Shaner and SL O’Conner(Eds), CRC Press, Boca Raton, FL, US App. Pp 53-69.


Sajja S, Samineni S, Gadekar M, Jayalakshmi V, Kumar AV, Yasin Mand Rajeev KV. 2015. Effect of post emergence herbicideimazethapyr on phenological and agronomic traits in chickpeabreeding lines. International Plant Breeding Congress (IPBC)and Eucorpia Oil and protein crops section conference ,November 01-05, 2015, WOW Kremlin Palace Hotel, Kenya.

Stidham MA. 1991. Herbicides that inhibit acetohydroxy acidsynthase. Weed Science 39: 428-434.

Solh MB and Pala M. 1998. Weed control in chickpea. OptionsMediterr Ser Semin 9: 93-99.

Stork PR. 1995. Field leaching and degradation of soil appliedherbicides in agradationally textured alkaline soil: chorosulfuronand triasulfuron. Australian Journal of Agriculture Research 46:1445-1458.

Tan S, Evans RR, Dahmer ML, Singh BK and Shaner DL. 2015.Imidazolinone-tolerant crops: History, current status, and future.

Pest Management Science 61: 246-257.

Taran B, Warkentin TD, Vanderberg A and Holm FA. 2010. Variationin chickpea germplasm for tolerance to imazethapyr andimazamox herbicides. Canadian Journal of Plant Sciences 90:139-142.

Taran B, Holm F and Banniza S. 2012. Response of chickpea cultivarsto pre and post emergence herbicide applications. CanadianJournal Plant Science 93: 279-286.

Van Eerd LL, McLea MD, Stephenson GR and Hall JC. 2004.Resistance to quinclorac and ALS-inhibitor herbicides inGaliumspurium is conferred by two distinct genes. Weed Research44: 355-365.

Wright GC, Nageswara Rao RC and Farquhar GD. 1994. Water useefficiency and carbon isotope discrimination under water deficitconditions. Crop Science 34: 92-97.


Effect of integrated nutrient management in soybean [Glycine max (L.) Merill]under temperate conditionMA AZIZ, NARINDER PANOTRA, TAHMINA MUSHTAQ, TAHIR MUSHTAQ, IA JEHANGIR andTAJAMUL ISLAM

Krishi Vigyan Kendra, Shuhama, Srinagar, Sher-e-Kashmir University of Agricultural Sciences and Technologyof Kashmir, Jammu and Kashmir, India; E-mail: [email protected](Received: March 04, 2017; Accepted: April 2, 2017)

ABSTRACT

A field experiment was conducted at Krishi Vigyan Kendra,Srinagar during two consecutive rainy seasons to study theeffect of integrated nutrient management on soybean(Glycine max L.) under temperate condition. Eighteentreatment combinations consisting of three levels of each ofrecommended doses (RD) of inorganic fertilizers (50, 75 and100% RD) and organic manures (control, FYM 10 t ha-1 anddalweed 10 t ha-1), and two levels of biofertilizers (controland dual inoculation with Rhizobium + PSB) were laid outin a randomized complete block design with threereplications. Grain and straw yield increased significantlywith successive increase in RD levels. Both FYM at 10 tha-1 and dual inoculation with Rhizobium and PSB weresignificantly superior in comparison to dalweed at 10 t ha-1

and un-inoculation, respectively. Yield attributes (100-seedweight), number of nodules and protein content in seed alsoshowed similar trend with that of grain yield followingsuccessive increase in RD levels. Similarly, FYM at 10 tha-1 was found superior over Dalweed on the above yieldattributes and seed quality. On the contrary, oil and lysinecontent in seed was higher with application of 75% RD overother levels.

Key words: Grain yield, Organic manure, Seed quality, Soybean

Soybean is an important pulse as well as oilseed cropgrown under diversified agro-ecologies. It needs specialattention to overcome the crisis in edible oil production inIndia. With 40-42% protein and 20-22% oil in seed, it ispopularly known as “Gold of Soil”; and has emerged asone of the major oilseed crops in the country. In spite of itshigh yielding potential, its productivity is too low in India.Among the factors responsible for its low productivity,inadequate fertilizer use and emergence of multiple-nutrientdeficiencies due to poor recycling of organic resourcesand imbalance use of fertilizers are crucial (Chaturvedi etal. 2010). Being an energy rich crop, the requirement ofmajor nutrients including secondary and micronutrients ishigh (Singh et al. 2006). Although the soils are being rich innutrients yet a small part of it is available to plants especiallyunder temperate climatic conditions. Nutrients availabilityalso differs as it is related to physical, chemical andmicrobiological properties of soil and is often associatedwith soil mineralogy. It has been established that continuous

use of high analysis chemical fertilizers leads to deficiencyof secondary and micronutrients, soil salinity andenvironmental pollution. Thus, there seems a wide potentialto upgrade efficiency of these nutrients through betteragronomic practices.

Therefore, the concept of integrated nutrient supplyinvolving use of organic manures and inorganic fertilizershas been developed and practiced to obtain sustainedagricultural production (Gaikwad and Puranik 1996). Inaddition, integration of organic and inorganic sources ofnutrients along with biofertilizers is observed to give higherproductivity and monetary returns in soybean (Singh andRai 2004, Bhattacharyya et al. 2008). Further the organicsources unlike inorganic fertilizers have substantial residualeffect on succeeding crops (Duraisami and Mani 2001,Shivakumar and Ahlawat 2008). Therefore, integratednutrient management (INM) involving use of manures,biofertilizers and chemical fertilizers is the key for betterutilization of resources through producing more crop(s)with less cost so as to realize sustained crop productionand improved soil health. The current experiment wasconducted to study the effect of INM on soybean [Glycinemax (L.) Merill] especially under temperate condition.


A field experiment for studying the effect of integratednutrient management on soybean [Glycine max (L.) Merill]under temperate condition was conducted during rainyseasons of 2009 and 2010 at Krishi Vigyan Kendra, Sher-e-Kashmir University of Agricultural Sciences andTechnology of Kashmir, Shuhama, Srinagar. The soil of theexperimental field was silty clay loam with pH 7.8. It wasmedium in organic carbon (0.70%), available phosphorus(15.36kg ha-1) and available potassium (120.62 kg ha-1); andwas low in available nitrogen (125.52 kg ha-1). Theexperiment was laid out in a factorial randomized blockdesign with 3 levels of inorganic fertilizers, 3 levels oforganic manures and 2 levels of biofertilizers. Chemicalfertilizers were comprised of three levels viz., C1 (50% RD ofN, P, K, Zn), C2 (75% RD of N, P, K, Zn) and C3 (100% RD ofN, P, K, Zn). Recommended dose (RD) is taken as 40:60:20:05(N:P205:K20:Zn, respectively in kg ha-1).

Aziz et al. : Effect of INM in soybean under temperate condition 3 7

Farmyard manure (0.58% N, 0.34% P, 0.60% K) andDalweed (0.35% N, 0.23% P, 0.40% K) each at 10 t ha-1 wereincorporated in soil as per treatment 15 days before sowingof soybean. Slurry of Rhizobium and PSB inoculant wasprepared with concentrated gur solution (20%) as perstandard procedure before adding Rhizobium culture andPSB to it. Then seeds of soybean was treated withRhizobium and PSB inoculants as per treatment so that allthe seeds were uniformly coated with Rhizobium and PSBinoculants (applied at 5 g kg-1 seed); and then allowed todry in the shade before sowing.

Five plants were randomly uprooted along with soilfrom each plot at flowering stage of the crop for countingnumber of nodules. The crop was harvested from the netplots by three pickings of matured pods turning yellowishbrown. Grain yield and stover yield were recorded basedon net plots. Yield attributes such as pods per plant and100-seed weight were measured. The protein content inseed was determined as per Lowry (1951). This is anextension of biuret method as it is known to be 10 timesmore sensitive than the latter. Here, protein reacts with folin-ciocalteu reagent (FCR) to give blue color complex which isformed due to reaction of alkaline copper with protein as inbiuret test and reduction of phosphomolybdic-phosphotungstic components in FCR by amino acidspresent in protein. The intensity of blue colour is measuredcolorimetrically at 660 nm. Oil content in the soybean seedwas estimated by ether extraction method using soxhletapparatus.


Growth and yield attributes: Growth parameters viz.,number of nodules and 100-seed weight differedsignificantly due to nutrient levels (Table 1).With increasein level of recommended inorganic fertilizers, the number ofnodules increased (Singh et al. 2006). Highest number ofnodules (35.0) was recorded with 100% RD. Application ofFYM 10 t ha-1 was found superior to other levels as thesame recorded the highest (33.0) number of nodules.Inoculation with both Rhizobium and PSB resulted inhighest (35.6) number of nodules which was significantlysuperior to that under un-inoculation. Integratedapplication of inorganic fertilizers along with application ofFYM 10 t ha-1 and inoculation with Rhizobium and PSBsignificantly improved nodules/plant. These results are inconformity with the findings of Shivakumar and Ahlawat(2008). The increase in number of nodules/plant was due tofavourable effects of FYM in improving the soil fertilitythrough its positive effects on physical and chemical andbiological soil properties; and is popularly called ‘manureeffect’. Nevertheless, inoculation was significantly superiorto un-inoculation. Yet, the combination of inoculation andchemical fertilization had a significant effect on the totalnumber of nodules/plant (Alam et al. 2009).

100-seed weight with recommended inorganicfertilizers was also found to be superior at 75% RD butfurther increase in its level could not improve it. Similarly,application of 10 t ha-1 FYM recorded highest seed weight(24.1 g) followed by Dalweed (23.8 g) and seed inoculation(24.1 g) over un-inoculation (23.5 g). The superiority ofFYM (10 t ha-1) over Dalweed (10 t ha-1) and the latter overno manure further proved the role of organics inimprovement in seed weight. This might be attributed toavailability of sufficient amount of nutrients in soil underorganics throughout growth period resulting in its betteruptake, plant vigour and superior yield attributes(Shivakumar and Ahlawat 2008). Similar was the effect ofinoculation with biofertilizers over un-inoculation as theseplay an important role in nutrient supply and its availabilityfor nutrient uptake. Besides increasing the availability ofbiologically fixed atmospheric nitrogen and enhancingnative P availability to crop, Rhizobium and PSB haveshown encouraging results in sustaining crop productivityand improving soil fertility (Govindan and Thirumorgan2005). Similarly, integrated nutrient management involvinginorganic fertilizers, manure application and inoculationhas shown better results (Kumpawat 2010).Grain yield: Integrated nutrient management enhanced theyielding ability of soybean (Table 2) as there was an increasein grain yield up to 75% RD (on par with 100% RD). As aresult, highest grain yield (1757 kg ha-1) was recorded at75% RD. Similarly, application of FYM @ 10 t ha-1 andinoculation with Rhizobium and PSB recorded the highestgrain yield (1578 kg ha-1 and 1679 kg ha-1, respectively).Increase in grain yield of soybean was largely due toimprovement in yield attributes viz., pod length, pods/plant,seeds/pod and seed weight. Moreover, grain yield had ahighly significant correlation with pods/plant, grains/podand seed weight (Kumar et al. 2009).

The results also revealed that application of 10 tha-1 FYM or Dalweed recorded higher grain yield over thatin no manure plots since FYM had a definite beneficialeffects both on soil and plant through enabling availabilityof its adequate amounts throughout the growth period.This resulted in better nutrient uptake, plant vigour andsuperior yield attributes (Shivakumar and Ahlawat 2008).Organic manures along with inorganic fertilizers (INM) alsoattributed to higher nutrient availability and adsorption ofnutrients (Kumar et al. 2009). Similarly, inoculation withRhizobium and PSB had a significant effect on grain yieldof soybean due to increased nodulation and BNF, moresolubilization of native P and production of secondarymetabolites by bacteria (Kumar et al. 2009). Therefore,integrated use of inorganic fertilizers along with inoculationof biofertilizers resulted in significant improvement in grainyield (Alam et al. 2009). The favourable effect of integrationof chemical fertilizers, Rhizobium and PSB on growth andyield was also reported by Afzal and Bano (2008). In


addition, synergy in all these (inorganic fertilizers, manureand inoculation with Rhizobium and PSB) had producedsignificantly higher grain yield (Kumpawat 2010).

Similar to grain yield, highest stover yield wasrecorded with 75% RD (on par with 100% RD). Applicationof 10 t ha-1 FYM also improved stover yield over that inDalweed and no manure condition. Similarly, inoculationwith Rhizobium and PSB showed higher observed valuesof stover yield (5441 kg ha-1) over that in un-inoculation.As in the case of grain yield, increase in stover yield of

soybean could be due to adequate supply of essentialnutrients in balanced amount resulting in better crop growthand development (Thirumelai et al. 1993, Kumar et al. 2009).Seed quality: Nutrient management had a significant effecton seed quality parameters in soybean (Table 3). The resultsrevealed that there was corresponding increase of proteincontent in soybean seeds with corresponding increase inrecommended inorganic fertilizers. The highest (36.6 %)protein content was recorded with 100% RD followed byfor 75 % RD (36.1 %) and 50 % RD (36.0 %). Application of

Table 1. Effect of INM on number of nodules and 100-seed weight (g) (pooled data)

Nodule number 100-seed wt.CD (P=0.05) Nodule number 100-seed wt. Organic x Inoculation = 0.248 NSChemical = 0.175 0.325 Chemical x Organic = 0.304 NSOrganic = 0.175 0.325 Chemical x Inoculation = 0.248 0.460Inoculation = 1.43 0.265 Chemical x Organic x Inoculation = 0.430 NS

Chemical Fertilizers

Organic Manures

Bio-inoculation Factor means for Organic Manures Uninoculated (I0) Inoculated (I1) Mean

Nodule number

100-seed weight

Nodule number

100-seed weight Nodule number

100-seed weight

Nodule number

100-seed weight

50% RD (C1)

No Manure 25.93 22.80 34.59 24.07 30.62 23.44 No manure

= 32.09 No manure

= 23.65 FYM (10 t ha-1) 27.27 23.57 34.84 25.01 31.05 24.29 Dalweed (10 t ha-1) 26.79 22.91 33.94 25.07 30.36 23.99

Mean 24.66 23.09 34.46 24.72 30.56 23.91 75% RD (C2)

No Manure 28.16 23.53 35.22 24.87 31.69 24.20 FYM (10 t/ha)

= 33.02 FYM (10 t/ha)


Mean 28.48 35.51 24.48 31.99 24.10 100% RD (C3)

No Manure 32.06 23.71 36.57 22.90 34.31 23.30 Dalweed (10 t/ha) = 32.41

Dalweed (10 t/ha) = 23.76

FYM (10 t ha-1) 33.75 23.91 37.65 23.34 35.70 23.62 Dalweed (10 t ha-1) 33.33 23.81 36.47 23.24 34.90 23.53

Mean 33.05 23.72 36.90 23.16 34.97 23.49 Factor means for Bio-inoculation 29.40 23.54 35.62 24.12

Table 2. Effect of INM on grain and Stover yield (kg ha-1) (pooled data)

Grain yield stover yieldCD (P=0.05) grain yield stover yield Organic x Inoculation = 0.030 NSChemical = 0.021 0.069 Chemical x Organic = 0.037 NSOrganic = 0.021 0.069 Chemical x Inoculation = 0.030 0.098Inoculation = 0.017 0.056 Chemical x Organic x Inoculation = 0.052 NS


Organic Manures Bio-inoculation Factor means for Organic Manures Uninoculated (I0) Inoculated (I1) Mean

Grain yield

Stover yield

Grain yield

Stover yield

Grain yield

Stover yield

Grain yield

Stover yield

50% RD (C1) No Manure 913 3507 1296 4679 1105 4093 No manure

= 1250 No manure

= 4335 FYM (10 t ha-1) 1171 4132 1413 5203 1292 4667 Dalweed (10 t ha-1) 1062 3797 1398 4969 1230 4382

Mean 1049 3811 1369 4950 1210 4382 75% RD (C2) No Manure 1273 3843 1554 5359 1413 4601 FYM

(10 t/ha) = 1578

FYM (10 t/ha) =

4859

FYM (10 t ha-1) 1327 4421 2765 5765 2046 5093 Dalweed (10 t ha-1) 1273 4030 2366 5452 1819 4741

Mean 1290 4098 2228 5525 1757 4812 100% RD (C3) No Manure 1132 3655 1374 4984 1253 4319 Dalweed

(10 t/ha) = 1457

Dalweed (10 t/ha) = 4538

FYM (10 t ha-1) 1289 4156 1507 5625 1397 4890 Dalweed (10 t ha-1) 1202 3906 1445 5109 1323 4538

Mean 1207 3905 1442 5239 1319 4562 Factor means for Bio-inoculation 1179 3937 1679 5241

Aziz et al. : Effect of INM in soybean under temperate condition 3 9

synthesis in the plant and its higher concentration in grain.Moreover, PSB inoculation increased the protein contentin cluster bean (Nagar and Meena 2004). Application ofFYM along with inorganic fertilizer also increased proteincontent in grain of soybean (Alam et al. 2009).

There was an increase in oil content of soybean upto 75 % RD level after which a decreasing trend was analysedin the oil content. The highest (17.2%) oil content insoybean was recorded with 100% RD. Similarly, applicationof organics viz., FYM (10 t ha-1) raised oil content in soybeanseeds (to 18.0 %) followed by that of Dalweed (17.0 %)over no manure application (16.3%). Inoculation withRhizobium and PSB also showed significantly higher oilcontent (18.3%) over no inoculation (15.9%). In addition,combined application of inorganic fertilizers (all the levels),FYM and inoculation with Rhizobium and PSB improvedoil content in seed (Alam et al. 2009, Singh and Rai 2004)due to favourable effect of all these on mineralization ofFYM and improved microbial activity as well. Themineralization of organics enhanced oil content due tosynthesis of fatty acids and their etherification byaccelerating biochemical reaction in glycoxalate cycle (Alamet al. 2009). Similarly, inoculation showed significantlysuperior results over no inoculation (Umale et al. 2002,Wahane et al. (1992).

It is inferred from the two years’ study that under lowto medium fertile soils, inorganic fertilizer combination viz.,30:45:15 kg ha-1 (75% RD N:P2O5:K2O) along with 10 t FYMha-1 and dual inoculation of Rhizobium and PSB could beadequate especially under temperate condition of Kashmirvalley. However, such study needs further validation underdiverse agro- climates.

FYM and Dalweed 10 t ha-1 also increased protein contentof soybean seed over no manure. Combined inoculationwith Rhizobium and PSB also showed superior results overuninoculated control as inoculation recorded the highestprotein content (37.6 % in comparison to 34.1 % in un-inoculation). Moreover, protein content in grains ofsoybean increased successively with correspondingincrease in levels of recommended inorganic fertilizers. Asa result, highest amount of protein content in grain wasobserved at 100 % RD (Alam et al. 2009, Singh and Rai2004).

Protein content in grains was also significantlyinfluenced by application of organic manure. The contentwas maximum under FYM (10 t ha-1) followed by Dalweed(10 t ha-1) and minimum under no manure. Increased proteincontent following FYM could be due to supplementationof soil reservoir through mineralization of organic N and Pof FYM in general and enhanced microbial activity ofammonifiers, nitrifiers and phosphate solublizing bacteriain particular. This was due to higher soil organic carbonthat could have increased root growth and nodulationresulting in increasing nitrogen and phosphorus contentin grain, and hence its higher protein content. It is alsoreported such increase in protein content is attributed toincrease in nitrogen content and role of phosphorus inenergy storage and transfer in forms of ADD and ATP,essential for protein synthesis. A significant positive impactof FYM on protein content of other legumes was alsoreported (Jain et al. 1995, Tiwari et al. 1995). In addition,inoculation significantly increased protein content in graincompared to un-inoculation. Increase in protein contentfollowing inoculation might be due to enhanced BNF alongwith adequate supply of P, thereby enhancing both protein

Table 3. Effect of INM on Protein and Oil content (%) of soybean seeds (pooled data)

Protein content Oil contentCD (P=0.05) Protein content Oil content Organic x Inoculation = 0.031 NSChemical = 0.021 NS Chemical x Organic = 0.038 NSOrganic = 0.021 0.422 Chemical x Inoculation = 0.031 NSInoculation = 0.017 0.344 Chemical x Organic x Inoculation = 0.053 NS


Organic Manures Bio-inoculation Factor means for Organic Manures Uninoculated

(I0) Inoculated

(I1) Mean

Protein content

Oil content

Protein content

Oil content

Protein content

Oil content

Protein content

Oil content

50% RD ( C1 ) No Manure 34.22 15.22 37.07 17.25 35.64 16.23 No manure

= 35.91 No manure


Mean 34.59 15.87 37.46 18.35 36.02 17.11 75% RD ( C2) No Manure 34.41 15.26 37.26 17.22 35.84 16.24 FYM

(10 t/ha) = 36.74

FYM (10 t/ha) = 17.97


Mean 34.68 15.88 37.61 18.42 36.14 17.15 100% RD ( C3) No Manure 35.22 15.30 37.28 17.37 36.25 16.33 Dalweed

(10 t/ha) = 36.10

Dalweed (10 t/ha) = 16.98


Mean 35.44 15.91 37.73 18.26 36.59 16.96 Factor means for Bio-inoculation 34.90 15.89 37.60 18.26


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High temperature stress and its implication on growth, biomass and yield ofnormal and late seeded fieldpea genotypesVIJAY LAXMI and GP DIXIT

Indian Institute of Pulses Research Kanpur-208024, India; E-mail: [email protected](Received: January 27, 2017; Accepted: March 10, 2017)

ABSTRACT

Climatic factors serve as direct inputs to agriculture andany change in climatic factors is bound to have a significantimpact on crop yields and production. Climate change mayhave the most influence on rain fed agriculture being rainfalldependent. Temperature is an important weather parameterwhich affects productivity of rainfed crops. Field experimentswere conducted during rabi (winter) 2011-12 and 2012-2013at Indian Institute of Pulses Research, Kanpur involvingfifteen fieldpea genotypes (sown under normal and latecondition) to study the effect of temperature stress on thecrop. The crop was monitored through membrane stabilityindex, plant height at podding, total biological yield, seedyield and harvest index, which showed significant variationwith seeding dates, genotypes, and their interactiveeffects. Crop was exposed to higher temperature duringflowering and seed filling stages which induced reductionin mean membrane stability index (28.8%), plant height(60.2%), total biomass yield (61.7%), seed yield (68.9%) andharvest index (19.3%). The mean yield stability index was80.7%. On the basis of minimum reduction in observed traits,fieldpea genotypes, KPF103 and DMR 15, had comparativelyhigher amount of tolerence towards high temperature stresswhile IPFD 99-7, IPFD 3-17, IPFD 2-6, IPFD 1-10 weremoderately tolerance to high temperature stress since thesehad more than 75.0% yield stability index.

Key words: Fieldpea, Membrane stability index, Seed yield,Temperature tolerance, Yield stability index

Frequency of hot weather may increase in future dueto global warming (Schneider 1989). Improvement of heattolerance can contribute to sustainability and provides ameans of extending legume cultivation to previouslyunsuitable regions and seasons. The yield loss of fieldpeain India due to high temperature has been projected as 4-5million tonnes/year with every degree rise of temperaturethroughout the growing period even after considering thebenefits of carbon fertilization (Aggarwal 2007). Lateplanting of fieldpea in North West India is common due tothe intensive cropping system, which often delays thesowing of fieldpea up to the middle of January. In the recentpast the minimum and average temperatures have beenincreasing significantly at the rates of 0.06 and 0.030 C peryear, respectively and during the last 32 years, the minimum

temperature has increased by 1.90 C (Pathak and Wassmann2009). Improvement of heat tolerance can contributesustainability and provides a means of extending legumecultivation to nontraditional area. Rise in temperaturedecreases grain size due to high respiration rate anddecrease in rate of starch synthesis that reduces grainweight because of forced grain development (Stone andNicolas 1984, Tashiro and Wardlaw 1990, Warrington et al.1977).


A field experiment was conducted during rabi underirrigated condition at Research Farm of Indian Institute ofPulses Research, Kanpur (260 24’15" N, 800 24’ 36" E at analtitude of 126 m above mean sea level). The soil of theexperimental site was having low available nitrogen (150 kgN/ha), medium available phosphorus (22 kg P2O5/ha) andpotassium (180 kg K2O/ha) during 2011-12 and 2012-13 toevaluate the effect of high temperature at pod formationstage in fieldpea genotypes. Fifteen fieldpea (Pisum sativumL.) genotypes viz., Pant 5, KPF 103, DMR 15, IPFD 98-1,IPFD 99-7, IPFD 5-8, IPFD 4-6, IPFD 3-6, IPFD 2-5, IPFD 3-17, IPFD 2-6, IPFD 1-10, HUDP 16, DPR 13, and Swati wereplanted at two sowing dates i.e. normal sowing on 16th ofNovember, and late sowing on 3rd of January, underirrigated condition. Planting was done in two involving theabove treatment in facterance RBD. The literecered anaverage maximum 26.80C and minimum of 23.90C undernormal; temperature and 34.25 and 31.00C under late sowncondition membrane stability index and plant height at grainfilling stage were recored. Membrane stability index wasdetermined by recording the electrical conductivity of leafleachates in double distilled water at 40° and 1000 C (Sairamet al. 1997).Membrane stability index (MSI) = {100 – (C1/C2) x 100}C1 =Electrical conductivity at 400C, C2 =Electricalconductivity at 1000C

At maturity stage, five plants were harvestedrandomly per replicate and observations were recorded onplant height, biomass, and seed weight per plant and harvestindex. The yield stability index for seed yield was calculatedas per the following formula:


Yield Stability Index (YS)= {GY (H) / GY (N)} x 100GY (H) = Grain yield under stress condition, GY (N) = Grainyield under normal condition


The performance of fifteen fieldpea genotypes undernormal and late seeding conditions for membrane stabilityindex (MSI) at podding stage, plant height, total biologicalyield, seed yield and harvest index revealed that all theseparameters were significance inflenced by seeding dates,genotypes and their interactive effects (Table 1). Thesignificant variations amongst different seeding dates mighthave been due to the changes in temperature during variouscrop growth durations. Membrane stability index amongdifferent genotypes at podding stage ranged between 0.419(DMR 15) to 0.754 (IPFD 3-17) under normal sown conditionand 0.305 (HUDP 16) to 0.503 (IPFD 99-7) under late sowingcondition. Due to high temperature stared under lateseeding, maximum reduction in MSI was recorded in DPR13 (48.3%) followed by IPFD 3-17 (46.5%), while genotypeDMR 15 had minimum reduction in MSI (0.0). It has beenstated that tolerance to high temperature stress in plants isrelated to membrane stability index, compatible solutesconcentration and synthesis of heat shock proteins.Minimum deviation in membrane stability under hightemperature stress indicates comparatively higher amountof tolerance for heat stress. Under normal planting, plantheight among different genotypes significantly rangedbetween 151.4 cm (Pant 5 and IPFD 3-17) and 57.6 cm (IPFD5-8) under late seeding condition, it ranged between 71.9cm (IPFD 99-7) and 25.6 (HUDP 16). Most of the genotypeshad more than 50% percent reduction in plant height under

late seeding condition; and the maximum reduction in plantheight was observed in DPR 13 (79.6%) followed by IPFD1-10 (79.3%) while minimum reduction was noticed in IPFD2-6 (25.7%). The significant variations in these characterswere due to the genetic potential(s) of the genotypes andthe interactive effect(s) with environmental conditionsunder normal and late seeding.

The total biological yield varied significantly amongseeding dates, the genotypes and their interaction effects(Table 2). Among genotypes it ranged between 75.4 g/5plants (DMR 15) to 195.0 g/5 plants (IPFD 3-17) under normalcondition; and 27.2 g/5 plants (IPFD 1-10) to 79.9 g/plant(KPF 103) under late seeding condition. Reduction in totalbiological yield was the highest in IPFD 1-10 (85.6%)followed by IPFD 3-6 (76.8%) while the lowest was noticedin KPF 103 (6.7%). Late seeded crop experienced hightemperature regimes at every stages of crop growth thatrespected in reduced leaf area along with low chlorophyllcontent and reduced photosynthetic activity of plants. Asa result of reduced leaf area, the crop intercepts lessphotosynthetically active radiant (PAR) energy resultingin reduction in total biological yield. The variation inreduction for total biological yield under late seedingcondition revealed that the interactive effect(s) betweengenotypes and environment was quite high.

Significant variations were observed for seed yieldwhich ranged between 22.3 g/5 plants (KPF 103) to 87.9 g/5 plants (IPFD 3-17) under normal seeding condition, whileunder late seeding condition it ranged between 7.1 g/5 plants(Swati) and 25.3 g/5 plants (IPFD 4-6). Reduction in seedyield under late seeding condition was observed to be thehighest in IPFD 3-17 (89.5%) followed by IPFD 1-10 (88.5%)

Table 1. Variations for MSI, plant height, biological yield in fieldpea genotypes under varied planting dates

Note: (N) are normal seeding condition, (L) are late seeding condition and figures in parenthesis are per cent reduction under late seedingcondition.

S.No. Genotypes MSI Plant height (cm) Total yield (g/5 plants)

Normal Late % reduction Normal Late % reduction Normal Late % rediction 1 Pant 5 0.529 0.389 (26.4) 151.4 36.8 (75.7) 101.7 55.9 (45.0) 2 KPF 103 0.462 0.426 (7.8) 64.8 62.5 (0.4) 85.6 79.9 (6.7) 3 DMR 15 0.419 0.419 (0.0) 65.2 35.6 (45.4) 75.4 56.4 (25.2) 4 IPFD 98-1 0.470 0.363 (22.8) 96.1 29.3 (69.5) 95.5 53.2 (44.3) 5 IPFD 99-7 0.603 0.503 (16.6) 120.3 71.9 (40.2) 137.5 72.3 (47.4) 6 IPFD 5-8 0.539 0.341 (36.7) 57.6 30.3 (47.4) 131.5 54.7 (58.4) 7 IPFD 4-6 0.500 0.482 (10.2) 98.1 61.2 (37.6) 108.5 61.9 (42.9) 8 IPFD 3-6 0.612 0.366 (20.4) 116.6 45.2 (61.2) 151.4 35.1 (76.8) 9 IPFD 2-5 0.475 0.364 (23.5) 82.0 30.7 (62.6) 82.9 38.6 (53.4)

10 IPFD 3-17 0.754 0.403 (46.6) 151.4 50.6 (66.6) 195.0 45.5 (76.7) 11 IPFD 2-6 0.507 0.365 (28.1) 77.5 57.6 (25.7) 127.5 38.7 (69.7) 12 IPFD 1-10 0.737 0.403 (45.3) 147.8 30.6 (79.3) 188.2 27.2 (85.6) 13 HUDP 16 0.521 0.305 (41.5) 99.0 25.6 (74.1) 84.9 31.5 (62.9) 14 DPR 13 0.689 0.356 (48.3) 135.5 27.7 (79.6) 162.7 43.2 (73.5) 15 Swati 0.602 0.354 (41.2) 126.9 32.1 (74.7) 79.7 29.4 (63.1)

C.D. (P=0.05) 0.027 5.29 6.41 C.D. (D x G) 3.76 7.47 5.07 CV (%) 4.81 6.32 6.60

Laxmi and Dixit : Effect of temperature stress on fieldpea under varied planting dates of normal and late seeded 4 3

while the lowest reduction in seed yield was observed inKPF 103 (4.5%). High temperature during growth fillingstage of crop growth affected seed development andreduced seed size and seed number per plants. Decline inseed yield under high temperature at grain filling stage hasalso been reported by Sharma-Natu et al. (2006), Prasad etal. 2008 and Saikia et al. 2009. Estimation of yield stabilityindex (Fig. 1A) indicated that it had wide variation amongstgenotypes range of between 41.3 (Pant 5) and 124.7% (IPFD4-6) with a mean of 80.7. It was interesting to note that yieldstability index and membrane stability index were negativelycorrected. The wide variation in yield stability indexamongst genotypes could have been due to variation ininteraction(s) between genotypes and environmentalcondition (G x E).

Harvest index (%) varied significantly among seedingdates, the genotypes and their interactive effects (Table 2).Among genotypes it ranged between 26.0 (KPF 103) to41.6 (IPFD 99-7) under normal seeded condition, and 24.1(Swati) to 40.9 (IPFD 4-6) under late seeding condition.Reduction in harvest index under late seeding conditionwas the highest in IPFD 2-5 (34.4) followed by Swati (28.5)while the lowest was noticed in IPFD 2-6 (14.4). Harvestindices in some of the genotypes (IPFD 4-6 with 19.4%)also registered an increase under late seeding condition ascompared to normal seeding condition. Changes in harvestindex of tepary beans have also been reported by Bhardwajet al. (2002). However in some of the genotypes theestimated harvest index was more than 100% which wasclearly not understood.

It can be concluded from the above results that underlate seeding condition crop experiences higher temperature

Note: Figures in parenthesis are per cent reduction under late seeding compared to normal seeding.

Table 2. Variations for seed yield harvest index and YSI (%) in fieldpea genotypes under varied planting dates

during flowering and seed filling stages which inducedreduction in mean membrane stability index, plant height,total biomass yield, seed yield and harvest index. On thebasis of minimum reduction in observed traits, genotypes,KPF 103 and DMR 15 were receively resistant to hightemperature stress. IPFD 99-7, IPFD 3-17, IPFD 4-6, IPFD 3-6, IPFD 2-6, IPFD 4-6 and IPFD 1-10 were moderately

(A)

Figure 1. Yield stability index (A) and membrane stability index (B)as influenced by high temperature under late seeding condition

(B)

Seed Yield (g/5 plants) Harvest index (%) S.No. Genotypes Normal Late Normal Late

YSI (%)

1 Pant 5 33.9 16.0 (52.8) 33.5 28.6 (14.6) 41.3 2 KPF 103 22.3 21.3 (4.5) 26.0 26.6 (+2.3) 95.5 3 DMR 15 22.7 18.2 (19.8) 30.1 32.3 (+0.67) 80.2 4 IPFD 98-1 37.8 16.5 (56.4) 39.6 31.0 (21.7) 43.6 5 IPFD 99-7 56.9 23.3 (59.1) 41.4 32.2 (22.2) 77.8 6 IPFD 5-8 51.6 15.2 (70.5) 39.2 27.8 (29.1) 70.9 7 IPFD 4-6 35.6 25.3 (28.9) 32.8 40.9 (+19.8) 124.7 8 IPFD 3-6 54.2 13.8 (74.5) 35.8 39.3 (+8.9) 109.8 9 IPFD 2-5 32.1 9.8 (69.5) 38.7 25.4 (34.4) 65.6

10 IPFD 3-17 87.9 9.6 (89.2) 35.2 27.1 (23.0) 77.0 11 IPFD 2-6 51.3 13.3 (74.1) 40.2 34.4 (14.4) 85.6 12 IPFD 1-10 74.9 8.6 (88.5) 39.8 31.6 (20.6) 79.4 13 HUDP 16 28.8 8.0 (72.2) 33.9 25.4 (25.1) 74.9 14 DPR 13 65.9 13.2 (80.0) 40.6 30.3 (25.4) 74.6 15 Swati 26.9 7.1 (73.6) 33.7 24.1 (28.5) 71.5

Mean 46.9 14.6 (68.9) 37.8 30.5 (19.3) 80.7 CD (P=0.05) 1.26 1.01 CD (Genotypes) 3.45 2.76 CD (D x G) 4.88 3.91 CV (%) 9.93 7.15


resistant for high temperature stress. However, furtherstudies are needed to elucidate the various effects of hightemperature on other morpho-physiological as well asbiochemical traits in fieldpea so that a suitable selectioncriterion for breeding can be established.

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Physiological and biochemical adaptation of chickpea (Cicer arietinum L.)genotypes under moisture stressVAISHALI SHARMA, JAGMEET KAUR, SARVJEET SINGH, INDERJIT SINGH, SATVIR KAUR andNORAH JOHAL

Department of Genetics and Plant Breeding, Punjab Agricultural University, Ludhiana-141004, India; E-mail:[email protected](Received: December 28, 2016; Accepted: February 9, 2017)

ABSTRACT

Six chickpea genotypes i.e. tolerant (BGD1094, ILC 3279and L555) and sensitive (GL29095, GL12003 and GNG2171)categorized on the basis of lysimetric screening for moisturestress conditions were evaluated for physiological andbiochemical studies. Tolerant genotypes exhibited higherphotosynthetic rate, Relative Water Content (RWC) and leghaemoglobin content in comparison to sensitive genotypes.Proline, total soluble sugars, superoxide dismutase,peroxidase and catalase activities increased among all thegenotypes but tolerant ones showed higher upheaval andunder moisture stress conditions (rainfed) in contrast tosensitive genotypes. Starch content reduced correspondinglyunder moisture stress with maximum decline (32.36%)observed in GL12003. The accumulation of osmolytes andhigher antioxidative enzymatic activity in tolerant genotypesimparted tolerance to moisture stress in comparison to thesensitive ones.

Key words: Antioxidant enzymes, Chickpea, Droughttolerance

Chickpea (Cicer arietinum L.) is one of the mostimportant grain legumes grown over 13.5 m ha with anaverage productivity of about 967.6 kg/ha, of which Indiasolely contribute about 68% (FAOSTAT 2015). In arid andsemi-arid regions, chickpea is generally grown under rainfedconditions. Other than moisture, cold, heat and salinity aremajor abiotic stresses which hamper the chickpeaproduction. Chickpea faces two types of drought situationssuch as, terminal drought where soil moisture continuouslydecreases towards the end of the growing season andintermittent drought where soil moisture may be depleted ifwinter rain is irregular and insufficient. The crop facesdrought stress either when the water supply to roots isinterrupted or when transpiration rate is very high. Legumeplants have at least two ways to resist drought i.e. droughtavoidance via efficient stomata regulation and droughttolerance via osmotic adjustment (Vadez et al. 2008).

Plants respond to drought stress and becomeaccustomed through various physiological and biochemicalchanges including changes of water use efficiency, pigmentcontent, osmotic adjustment and photosynthetic activity(Farooq et al. 2009). High relative water content (RWC)and low excised-leaf water loss are linked with drought

tolerance. The drought stress often leads to oxidative stressin plants due to higher leakage of electrons towards O2during photosynthetic and respiratory processes causingenhanced production of reactive oxygen species (ROS).The ROS such as superoxide radical (O2), hydroxyl radical(OH), hydrogen peroxide (H2O2) and alkoxy radical (RO)are highly reactive and can change normal cellularmetabolism through oxidative damage to membranes,nucleic acids and proteins (Mittler 2002). When the cropexperiences stress conditions, there is modulation of theactivities of antioxidant enzymes which leads to enhancedcellular protection (Kaur et al. 2012). Plant cells responddefensively to oxidative stress by reducing theconcentration of ROS and maintaining antioxidant defensecompounds and osmolytes. Proline is one of the commonosmolytes which increase in plants under moisture stressand help the plants to maintain cell turgidity (Moayediet al. 2011). The damage caused during stress cold ultimatelystress yield. Therefore, in the present study attempt hasbeen made to elucidate various physiological andbiochemical adaptations in the selected chickpea genotypesthrough lysimetric screening for moisture stress.


Six genotypes of chickpea (Cicer arietinum L.) wereraised in the experimental field of Department of Geneticsand Plant Breeding, Punjab Agricultural University,Ludhiana under irrigated (control) and rainfed conditions.The crop was sown in the month of November 2015 and sixgenotypes (categorized as tolerant viz., BGD 1094, ILC 3279,L 555 and sensitive viz.,GL 29095, GL 12003, GNG 2171 onthe basis of lysimetric screening) were evodited in arandomized block design with three replications. Eachgenotype was accommodated in paired row of 3m length atrow spacing of 40 cm.The physiological (relative watercontent, photosynthetic rate) and biochemical (total solublesugars, superoxide dismutase, peroxidase and catalaseactivity) parameters were estimated from leaves duringreproductive stage. Starch content was estimated from theseed sample at maturity. Leg ahaemoglobin content wasestimated from the nodules during reproductive phase.Physiological parameters: Relative leaf water content wasestimated according to the method of Weatherley (1950)from second and third leaves and was calculated as: RWC


= (Fresh weight-Dry weight /Turgid weight-Dry weight)X100. Photosynthetic rate was recorded as µmole CO2 m

-2

s-1 by using Portable Photosynthesis System (LI-6400XT,LICOR). Leg haemoglobin content from the fresh noduleswas determined by using drabkin’s solution as per themethod described by Wilson and Reisenauer (1963).Biochemical parameters: Proline content both in leavesand seeds was extracted using 3% sulfosalicylic acid andestimated by reacting it with acidic ninhydrin reagent (Bateset al. 1973). Total soluble sugars and starch content wereextracted with 80% ethanol and estimated (Dubois et al.1956).Enzymatic estimation: The enzyme extract for superoxidedismutase (SOD) and peroxidise (POX) was prepared from0.1g fresh leaf sample with 0.1M potassium phosphatebuffer (pH 7.5) containing 1% PVP, 1mM EDTA and 10mM-mercapto ethanol. The enzymes were estimated as perthe protocols given by Marklund and Marklund (1974) forsuperoxide dismutase and Shannon et al. (1966) forperoxidise. The enzyme catalase (CAT) was extracted from0.1g fresh leaf sample with 50mM sodium phosphate buffercontaining 1% PVP and estimated by the methods of Chanceand Maehley (1955).Protein profiling: Protein of the seed of irrigated and rainfedcrop was analyzed using SDS PAGE by Laemmli (1970).Yield parameters: Three plants were taken randomly fromeach plot and average seed yield per plant was recordedand expressed as in grams/plant. Harvest index (HI) definedas the ratio of seed yield to the total biomass at maturityand was expressed in per cent.


Physiological parameters

Photosynthetic rate: Photosynthetic rate decreased underrainfed condition with maximum decline observed insensitive genotypes (54.76%), where as it was 11.65% intolerant genotypes. Among sensitive genotypes, GL 29095showed a maximum reduction (59%) in the photosyntheticrate under rainfed condition. This can be attributed todecline in stomatal conductance under moisture stress(Krouma 2009). Photosynthetic rate of L 555 (tolerantgenotype) showed 8% decline under rainfed condition as

compared with irrigated condition.Relative water content: For efficient physiologicalfunctioning and growth processes of crop, optimum relativewater content is essential and is known as potentialphysiological marker in many crops. In the present study,RWC significantly decreased in all genotypes undermoisture stress condition, but these reductions in tolerantgenotypes were less (9.64%) as compared to sensitive ones(26.14%) (Table1). Among tolerant genotypes BGD 1094and L 555 showed least reduction (9%) while amongsensitive genotypes GL 12003 showed maximum reduction(29%) in RWC under moisture stress. This decline may beattributed to higher water loss through stomatal regulationduring photosynthesis and inefficient water utilizationassimilation under moisture stress (Lobato et al. 2008). Thelesser decline in RWC of tolerant genotypes in comparisonto sensitive ones could be due to efficient controlmechanisms to maintain cell and tissue hydration underwater stress by regulating stomatal opening. The alterationsin RWC in response to water stress have also been reportedby Kaur et al. 2016.Leg haemoglobin content: The leg haemoglobin contentin nodules of the genotypes correlated with RWC havingthe highest decline of 49% in GL 12003 (sensitive) and thelowest of 14% in L 555 (tolerant). Decline in leg haemoglobincontent has also been reported in common bean subjectedto severe moisture stress condition which may be due torestriction of carbohydrate transport from leaves to nodule(Figueriedo et al. 2008). There can be production of O,radicals in stressed genotypes which are reported inMedicago truncatula showing reduced leg haemoglobincontent (Mhadhabi et al. 2009).

Biochemical parameters

Total soluble sugars, proline content and starch content:Proline is the most important organic solute accumulate inhigher plants under drought conditions (Sumera andAsghari 2010). There was low accumulation of total solublesugars and proline content in leaves and seeds underirrigated conditions, while it enhanced noticeably underrainfed condition (Table 2). The mean value of prolinecontent in leaves increased from 1.23µmoles/g to 2.52µmoles/g and in seeds from 1.97µ moles/g to 4.64µ moles/gunder rainfed conditions. Higher increase was observed in

Table 1. Photosynthetic rate, RWC and leghaemoglobin content of chickpea genotypes under different conditions

Data represent mean± standard error of triplicates

Genotype Photosynthetic rate (µmole CO2 m-2 s-1)

RWC (%)

Leghaemoglobin content (mg/g fresh nodule weight)

Irrigated Rainfed Irrigated Rainfed Irrigated Rainfed GL 29095 10.32±1.23 4.21±1.12 71.25±0.75 54.64±0.84 7.54±0.24 4.24±0.25 GL 12003 11.32±0.89 5.13±0.84 76.34±0.84 54.36±0.57 6.22±0.21 3.15±0.24 GNG 2171 11.12±0.89 5.48±1.51 77.64±0.75 57.35±1.21 5.34±0.31 3.48±0.54 BGD 1094 12.34±1.12 10.89±0.89 76.38±1.21 69.54±0.67 6.18±0.34 5.12±0.31 ILC 3279 10.26±1.35 8.67±1.12 76.34±0.84 68.25±0.57 5.63±0.41 4.78±0.25 L 555 10.36±1.48 9.56±1.78 75.89±0.87 68.78±0.68 7.54±0.52 6.45±0.52

Sharma et al. : Physiological and biochemical adaptation of chickpea (Cicer arietinum L.) genotypes 4 7

tolerant genotypes BGD1094 (58.90%) and ILC 3279(63.04%) in leaves and seeds, respectively.Variation in totalsoluble sugars estimated in dry chickpea leaves isrepresented in Table 2. Maximum sugar content wasobserved in L 555 (38.12 mg/g dry weight) and minimum inGL 12003 (29.65 mg/g dry weight) under irrigated condition.In order to maintain the cell turgor, total soluble contentwas increased under moisture stress conditions. GenotypeILC 3279 showed maximum increase of 42.57% in TSScontent under moisture stress condition relative to controlconditions. There was inter-relationship between starchand soluble sugars concentration. Starch content undermoisture stress decreased by 32.36%, 29.02% and 27.34%in the seeds of sensitive genotypes GL 12003, GL 29095and GNG 2171 respectively. Moisture stress however didnot show a pronounced decrease in the starch content oftolerant genotypes. In the seeds of tolerant genotype L555, the moisture stress reduced starch content only to17.65%.

The Present study indicated an increase in solublesugars and proline, while storage compound starch declinedas the stress increased. Changes in quantity of solublesugars in association with moisture stress may be due toincreased sugar biosynthesis, conversion of storage formsof carbohydrates to soluble sugars, breakdown of cell wallpolysaccharides and changes in rate of sugar transport.Under moisture stress condition, lowered water potentialis accompanied by breakdown of starch by hydrolyticenzymes amylases into glucose and maltose that increasesthe osmotic concentration of cell. As a result, cellular turgor,expansion growth, uptake of water and minerals throughroot are maintained. Proline acts as protective osmolytewhich accumulates faster than other amino acids, showsdiverse role in drought tolerance reactive oxygen speciesscavenger, and protection from oxidative damage andstabilizing enzymatic proteins against desiccation. Enzymesinvolved in proline biosynthesis elevates under droughtstress, whereas those of degradation are inhibited (Sumithraand Reddy 2004).Antioxidant enzymes: Water deficit stress influences theanti oxidative defense mechanisms to a great extent, byincreasing the activity of some specific enzymes which

plays a vital role in plant’s tolerance to stress. Among theantioxidant enzymes, superoxide dismutase (SOD)constitutes the first line of defense via detoxification ofsuperoxide radicals to H2O2 (Sairam and Saxena 2000). Inthe present study, activity of SOD was found to be higherin leaves of tolerant genotypes as compared to sensitivegenotypes under control and rainfed conditions (Fig.1).Highest activity was observed in tolerant genotype ILC3279 (351.42 unit enzyme/g FW), whereas lowest activitywas noticed in GNG 2171 (275.60 unit enzyme/g FW) underrainfed conditions. Higher superoxide dismutase activityduring drought stress protects plants from oxidative injury(Arora et al. 2002).

The specific activity of peroxidase in the leaves oftolerant genotype ILC 3279 was increased by 34.07% undermoisture stress condition, whereas the activity of peroxidasein the leaves of sensitive genotypes did not increaseconsiderably (i.e. 22.21 and 23.05 % increase were reportedin GL 29095 and GNG 2171, respectively). Higher level ofperoxidase activity resulted into higher capacity todecompose H2O2 more rapidly (Patel and Hemantaranjan2012).

Catalase eliminates H2O2 by breaking it down directlyto water and oxygen. Under control condition the highestactivity of catalase was found in tolerant genotypes i.e. L555 (943.13 A/min/gFW) and BGD 1094 (934.56 A/min/gFW), whereas lowest activity was observed in sensitivegenotype i.e. GNG 2171 (597.40 A /min/gFW). There wassharp increase in catalase activity observed in ILC 3279(27.70%) when exposed to moisture stress condition (Fig. 3).

0

50

100

150

200

250

300

350

400

GL-29095 GL-12003 GNG-2171 BGD-1094 ILC-3279 L-555

Supe

roxi

de d

ism

utas

e(u

nit e

nzym

e/g

FW

)

Genotypes

Irrigated

Rainfed

Figure 1. Superoxide dismutase activity of chickpea genotypesunder irrigated and rainfed conditions

Data represent mean ± standard error of triplicates

Table 2. Proline content (leaves and seeds), total soluble sugars and starch content in chickpea genotypes under irrigated andrainfed conditions

Genotype

Proline content (leaves) (µmoles/g dry weight)

Proline content (Seeds) (µmoles/g dry weight)

Total soluble sugars (mg/g dry weight)

Starch content (mg/g dry weight)

Irrigated Rainfed Irrigated Rainfed Irrigated Rainfed Irrigated Rainfed GL 29095 1.02±0.20 1.86±0.46 1.52±0.21 3.12±1.31 32.31±1.35 46.31±1.52 34.18±2.03 24.26±2.14 GL 12003 0.95±0.16 1.63±0.51 1.63±0.16 3.06±1.14 29.65±1.67 42.14±1.53 37.48±1.58 25.35±1.64 GNG 2171 1.16±0.21 1.93±0.34 1.56±0.12 3.16±1.06 32.58±1.61 40.24±0.61 36.43±2.12 26.47±2.06 BGD 1094 1.34±0.34 3.26±0.25 2.36±0.31 6.14±1.14 36.57±2.02 65.24±1.25 54.23±2.07 41.48±2.11 ILC 3279 1.53±0.41 3.19±0.14 2.31±0.22 6.25±1.12 36.81±1.39 67.26±1.36 52.34±1.87 42.34±1.92 L 555 1.38±0.42 3.25±0.51 2.43±0.32 6.10±0.76 38.12±1.46 68.31±2.15 49.28±2.16 40.58±2.31 Mean 1.23 2.52 1.97 4.64 34.34 54.92 43.99 33.41


Increased activity of catalase enzyme develops a potentialfor defense against damage as observed in maize genotypes(Helal and Samir 2008).The least increase was observed insensitive genotype GL 29095 (16.41%) under moisturestress. The decrease in catalase activity observed underwater deficit stress could be either caused by inhibition ofnew enzymes or photo inactivation (Basu et al. 2010).

Electrophoretic analysis of total proteins in seedsfrom irrigated condition revealed that bands near to 96 KDamolecular weights were more intense in BGD 1094 and L555; and less intense in GNG 2171. In seeds derived fromrainfed condition, differences were more evident. Bands of

chickpea (Mansourifar et al. 2011).Yield attributes: Under control condition, genotypes BGD1094 (11.3g) and GL 29095 (4.2g) recorded maximum andminimum yield per plant, respectively. Sensitive genotypes,GNG 2171 (74.84%) and GL 12003 (62.86%) showed maximumyield reduction under moisture stress condition. The tolerantgenotype L 555 recorded minimum yield per cent reduction(13.08) due to moisture stress.Harvest index: Harvest index is one of the important yieldcontributing attributes and the data pertaining to it ispresented in Fig. 4. Under rainfed condition, harvest indexwas reduced in all the genotypes and maximum decline wasobserved in sensitive genotypes GNG 2171 (35.98%), GL12003 (35.06%) and GL 29095 (31.84%). Higherphotosynthetic rate due to high RWC of leaves resultedinto minimum decline in harvest index of tolerant genotypes(19.4%). Environmental stresses such as water shortagesespecially during grain filling cause reductions inphotosynthesis and remobilization of stored materials, rate

0

20

40

60

80

100

120

140

160

180

GL-29095 GL-12003 GNG-2171 BGD-1094 ILC-3279 L-555

Pero

xida

se a

ctiv

ity (Δ

A/m

in/g

/FW

)

Genotypes

IrrigatedRainfed

Figure 2. Peroxidase activity of chickpea genotypes under irrigatedand rainfed conditions

0

200

400

600

800

1000

1200

1400

GL-29095 GL-12003 GNG-2171 BGD-1094 ILC-3279 L-555

Cat

alas

e ac

tivity

((ΔA

/min

/g/F

W)

Genotypes

Irrigated

Rainfed

Figure 3. Catalase activity of chickpea genotypes under irrigatedand rainfed conditions

lesser intensity near 96 KDa molecular weights were visiblein BGD 1094, ILC 3279 and L 555. However, 96 KDa molecularweight proteins were less intense in GNG 2171. Bands of 66KDa molecular weights were more intense in control thanstress treatments. 29 KDa bands were more intense in GNG2171 both in irrigated and rainfed conditions. Bands withmolecular weight 20.1 KDa and 14.3 KDa were observedwith high intensity under irrigated than rainfed conditions(Fig. 5). Molecular markers have been used to study theextent of genetic variation. The protein profiling ofgermplasm and use of genetic markers have been widelyand effectively used to determine the taxonomic andevolutionary aspects of several crops (Nisar et al. 2007).The genotypic variations in banding pattern were higher inpresent research in analogy to water stress treatments.These results were in accordance with finding of Iqbal andBano (2009) in wheat. Severe drought stress had effect onprotein banding patterns. However, other water stresstreatments showed no significant effect as observed in

0.00

10.00

20.00

30.00

40.00

50.00

60.00

0.0

2.0

4.0

6.0

8.0

10.0

12.0

GL-29095 GL-12003 GNG-2171 BGD-1094 ILC-3279 L-555

Har

vest

inde

x

Yiel

d pe

r pla

nt(g

/pl)

Genotypes

Irrigated Rainfed Irrigated Rainfed

Figure 4. Yield per plant and harvest index of chickpea genotypesunder irrigated and rainfed conditions

Figure 5. Banding pattern in chickpea genotypes (GL 29095, GL12003, GNG 2171, BGD 1094, ILC 3279 & L 555) under irrigatedand rainfed conditions by SDS-PAGELanes: M - Protein molecular weight marker (14.3-96.4 KDa),Lane : 1- GL 29095 (irrigated), Lane : 2- GL 12003 (irrigated),Lane : 3- GNG 2171 (irrigated), Lane: 4- BGD 1094 (irrigated),Lane: 5- ILC 3279 (irrigated); Lane: 6- L 555 (irrigated); Lane 7-GL 29095 (rainfed), Lane : 8- GL 12003 (rainfed), Lane :9- GNG 2171 (rainfed), Lane: 10- BGD 1094 (rainfed), Lane: 11-ILC 3279 (rainfed); Lane: 12- L 555 (rainfed)

Sharma et al. : Physiological and biochemical adaptation of chickpea (Cicer arietinum L.) genotypes 4 9

and duration of grain filling and grain weight (Sadeghipour2008). Oberoi et al. (2015) has reported that poor capacityof the anti oxidative defense system in sensitive cultivarsseems to be partly responsible for reduced yield potentialunder drought stress.

An assessment of the results shows that moisturestress tolerant genotypes having higher RWC,photosynthetic rate and regulated enzymatic defensemechanism resulted into higher yield in comparison tosensitive genotypes under drought.

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Beet army worm, Spodoptera exigua (Hubner): An emerging pest of chickpea inWestern MaharashtraAP CHAVAN, SR KULKARNI, RV DATKHILE and SK PATIL

Department of Entomology, Mahatma Phule Krishi Vidyapeeth, Rahuri-413722, Maharashtra, India;E-mail: [email protected](Received: August 12, 2016; Accepted: February 20, 2017)

ABSTRACT

Effect of different sowing dates of chickpea on the incidenceof Beet army worm, Spodoptera exigua (Hubner) and its grainyield was studied under Pulses Improvement Project,Mahatma Phule Krishi Vidyapeeth, Rahuri during rabi 2014-15 and 2015-16. Chickpea varieties (ICCL 86111, ICCV 10,ICC 3137 and Digvijay) were sown on nine sowing dates (at15 days interval) viz., 15th September, 1st October, 16th October,31st October, 16th November, 30th November, 15th December,30th December and 15th January. Larvae feed on the seedlingand vegetative stages of chickpea. The insect pest appearedin the field 15 to 20 days after sowing of the crop i.e. atseedling stage and remain it prevailed up to 25 to 30 daysafter germination. Thereafter, the infestation was negligiblefrom flowering to maturity of the crop. Correlation studyrevealed that during 2014-15, there was positive andsignif icant correlation with maximum and minimumtemperature when the crop was sown on 15th September.However, during 30 th November sown crop, there wassignificant negative correlation of maximum temperaturewith higher incidence on the variety Digvijay. Same trendwas observed during 2015-16 and all the varieties showedpositive and signif icant correlation with maximumtemperature when crop was sown on 1st October. Relativehumidity had no significantly association with S. exiguaalmost all the sowing date except at 30th November sowncrop during 2014-15. However, during 2015-16, morningrelative humidity showed positive for significant associationwith S. exigua at 15th September sown crop for all varieties,while Digvijay at 30th November sown crop. The associationof rainfall pattern and the incidence of both the pest atdifferent sowing dates was non significant. It could beconcluded from the present study that early and late sowingof chickpea resulted in higher infestation of S. exigua thanthat of optimum sown crop.

Key words: Beet army worm, Chickpea, Date of sowing, Yield

India ranks first in the production and consumptionof chickpea (Cicer arietinum L.) in the world. It is the thirdimportant food legume after beans and peas, grown in morethan 50 countries (Gaur et al. 2010). In Maharashtra chickpeais cultivated in 14.27 lakh ha with the production of 10.88lakh tons with an annual productivity of 762 kg/ha(Anonymous 2015). It has ability to fix nitrogen and canalso tolerate higher temperature during and after flowering(Cumming and Jenkins 2011, Gan et al. 2006). Eleven different

insect pest species have been reported to attack on chickpeacrop (Rahman et al. 1982). The beet armyworm, Spodopteraexigua (Hubner) (Noctuidae: Lepidoptera) is an emergingimportant pest of chickpea, especially in South central India.The young larvae of S. exigua initially feed gregariouslyon chickpea foliage. As the larvae grow, they becomesolitary and continue to feed on the foliage and producelarge, irregular holes on the leaf (Ahmed et al. 1990, Sharmaet al. 2007). As a leaf feeder, beet army worm consumesmuch more chickpea tissues than the chickpea pod borer,H. armigera, but it has not been reported as a serious peston pods in Western Maharashtra. However, due to climatechange, minor pest becomes major pest. The factorsresponsible includes maximum and minimum temperature,sunshine hours, wind velocity and rainfall pattern. Theoccurrence of such pest in the chickpea fields of PulsesImprovement Project, MPKV, Rahuri appeared on 20 daysafter germination of the crop and remain active up to 25 to30 days after sowing. The infestation could not be seenthereafter in the field. The first two instar of S. exigua aregregarious and scrap the foliage in groups. Fullygrownlarvae devour foliage completely. The skeletonizing offoliage is tropical symptoms of beet army worm damage inmany crops. Third and later instar larvae disperse and maycontinue feeding on foliage. One generation can becompleted in as little as 21-24 days. The lowest level ofbeet army worm that can be tolerated without significantyield loss is an average of 1 larva per square meter of plants(Anonymous 2014). Keeping these in view, the presentstudies were carried our to find the optimum planting timewith minimum pest incidence in relation to yield and toobserve the relationship between weather factors and S.exigua population.


Experiment was conducted under Pulses ImprovementProject, Mahatma Phule Krishi Vidyapeeth, Rahuri,Maharashtra to study the effect of different sowing datesagainst the Spodoptera exigua in chickpea during Rabiseasons of 2014-15 and 2015-16. Total nine sowing dates at15 days interval were executed viz., 15th September, 1st

October, 16th October, 31st October, 16th November, 30th

November, 15th December, 30th December and 15th January.The varieties deployed were ICCL 86111, ICCV 10, ICC 3137

Chavan et al. : Beet army worm: Anemerging pest of Chickpea 5 1

and Digvijay (local popular variety). The experiments werelaid out in factorial randomized block design (FRBD) withthree replications having plot size of 4m x 1.80 m with spacing30 x 10 cm. The chickpea crop plants of different sowingdates were closely examined at regular intervals commencingfrom germination to harvest. The data on the first appearanceof S. exigua in the field was recorded and the larvalpopulation per one meter row length (MRL) was recordeddaily from the randomly tagged five plants in central rowsof each plot starting from germination to pod maturity. Thepods were threshed after harvesting of the crop and grainswere cleaned and dried in the bright sunshine. The grainyield obtained from each plot was converted into kg perhectare. The experimental data was analyzed by MSTAT-Csoftware. The larval population of S. exigua data wastransformed by square root for statistical analysis. Meancomparisons for treatment parameters were compared usingDuncans Multiple Range Test (Steel and Torrie 1960) at 5%level of significance.


Effect of dates of sowing on larval population ofS. exigua during 2014-15: The data regarding survival atlarval population of Spodoptera exigua per meter row lengthin chickpea during 2014-15 showed significant differencesamong sowing dates (Table 1). The maximum larvalpopulation was recorded on chickpea sown on 15 th

September (8.48 larvae/MRL) and 15th January (1.65 larvae/MRL) while the lowest incidence was recorded from15th December (0.00 larvae/MRL) sown crop. It was followedby 16th November (0.25 larvae/MRL), 30th November (0.27

larvae/MRL), 31st October (0.53 larvae/MRL) and30th December (0.56 larvae/MRL) sown crop.

Irrespective of sowing dates, the different varietiesof chickpea grown on different sowing dates showed nonsignificant difference in larval population. However, thelowest larval population of S. exigua was noticed in thevariety ICCV-10 (0.79 larvae/MRL) while the maximum larvalpopulation was observed on Digvijay (1.75 larvae/MRL).Interaction among the different varieties of chickpea grownon different sowing dates showed significant difference inlarval population of S. exigua.Effect of dates of sowing on larval population of S. exiguaduring 2015-16: Larval population of S. exigua per meterrow length in chickpea during 2015-16 showed nonsignificant differences among sowing dates and varieties(Table 1). However, the lowest population of S. exigua wasrecorded from the crop sown on 31st October (0.86 larvae/MRL) while the highest larval population was recorded on15th January sown crop (3.48 larvae/MRL). Moreover, thelowest larval population was observed in ICC-3137(1.60larvae/MRL) while the highest larval population wasobserved in Digvijay (2.40 larvae/MRL). Interaction amongthe different varieties of chickpea grown in different sowingdates shows non-significant difference in larval populationof S. exigua.Effect of dates of sowing on pod damage at harvest andgrain yield during 2014-15, 2015-16: During both thecropping seasons i.e. 2014-15 and 2015-16 (from floweringto harvesting of the crop), the pod damage by S. exiguawas not observed. Significantly higher yield (1727 kg/ha)

*Figure in parenthesis indicate square root transformation

Table 1. Effect of different sowing dates on larval population of Spodoptera exigua in different varieties of Chickpea crop Sowing date

Year 2014-15 Year 2015-16 Variety/ Larval Populations / m row Variety/ Larval Populations / m row

ICCL-86111 ICCV-10 ICC-3137 Digvijay Mean ICCL-86111 ICCV-10 ICC-3137 Digvijay Mean 15 Sept 16.83

(4.13)* 3.67

(2.15) 7.80

(2.75) 11.67 (3.29)

8.48 (3.08)

3.01 (1.96)

1.07 (1.44)

1.35 (1.52)

1.73 (1.65)

1.79 (1.64)

1 Oct 0.93 (1.39)

3.47 (1.91)

0.93 (1.38)

2.00 (1.66)

1.49 (1.58)

1.94 (1.70)

2.02 (1.73)

2.18 (1.77)

3.88 (2.20)

2.51 (1.85)

16 Oct 0.53 (1.23)

0.40 (1.17)

2.67 (1.67)

4.90 (2.19)

1.46 (1.57)

0.04 (1.02)

1.02 (1.35)

3.75 (1.86)

0.86 (1.35)

1.42 (1.39)

31 Oct 0.77 (1.29)

0.67 (1.24)

0.10 (1.05)

0.93 (1.36)

0.53 (1.24)

1.59 (1.52)

0.50 (1.21)

1.00 (1.40)

0.33 (1.14)

0.86 (1.32)

16 Nov 0.00 (1.00)

0.83 (1.29)

0.00 (1.00)

0.43 (1.19)

0.25 (1.12)

4.55 (2.31)

0.77 (1.27)

0.50 (1.19)

0.67 (1.24)

1.62 (1.51)

30 Nov 0.33 (1.14)

0.00 (1.00)

0.00 (1.00)

1.00 (1.38)

0.27 (1.13)

0.00 (1.00)

1.83 (1.62)

0.33 (1.14)

2.88 (1.81)

1.26 (1.39)

15 Dec 0.00 (1.00)

0.00 (1.00)

0.00 (1.00)

0.00 (1.00)

0.00 (1.00)

1.67 (1.55)

2.44 (1.78)

1.94 (1.61)

3.24 (2.05)

2.32 (1.75)

30 Dec 0.00 (1.00)

0.00 (1.00)

5.00 (2.00)

0.00 (1.00)

0.56 (1.25)

3.14 (1.92)

2.53 (1.84)

2.08 (1.56)

1.00 (1.33)

2.19 (1.66)

15 Jan 0.50 (1.19)

0.83 (1.29)

4.50 (2.18)

2.50 (1.87)

1.65 (1.63)

1.17 (1.37)

4.40 (2.14)

1.33 (1.41)

7.03 (2.76)

3.48 (1.92)

Mean 1.22 (1.49)

0.79 (1.34)

1.43 (1.56)

1.75 (1.66)

1.28 (1.51)

1.90 (1.60)

1.84 (1.60)

1.60 (1.50)

2.40 (1.73)

1.93 (1.60)

SEm (±) CD (P=0.05) CV (%)

Sowing date Varieties Interaction (A) (B) (A x B) 0.19 0.12 0.38 0.53 NS 0.15

44.19

Sowing date Varieties Interaction (A) (B) (A x B) 0.16 0.10 0.32

NS NSNS 34.69


was recorded in 31st October sown chickpea crop whichwas statistically at par with 16th October and 16th Novembersown crops. The lowest yield was obtained from 15th Januarysown crop (335 kg/ha) in the year 2014-15. During 2015-16cropping season, maximum yield was recorded (1661 kg/ha) in 31st October sown chickpea crop followed by16th November (1609 kg/ha), 16th October (1533 kg/ha),1st October (1468 kg/ha). Interaction among the differentvarieties of chickpea grown on different sowing datesshowed non-significant difference in grain yield during bothyears (Table 2).Correlation with weather parameter: In case of S. exigua,the correlation weather parameter with its incidence wasdifferent. For 15th September sown crop, there was a positiveand significant correlation with maximum, minimumtemperature between all the varieties. However, during 30th

November sown crop, there was significant and negativecorrelation of maximum temperature with maximum incidenceof S. exigua on variety Digvijay.

Relative humidity had no significant association withS. exigua for almost all the sowing date except for 30th

November sown crop for variety Digvijay. Relative humidityhad positive and significantly correlation with S. exiguafor 15th January sown crop. Morning relative humidity hadsignificantly negative correlation with S. exigua in case ofvariety ICCV 3137 and Digvijay. The association of rainfallpattern and the incidence of both the pest at differentsowing dates was no significant.

Correlation of S. exigua during 2015-16

Correlation with weather parameter: The correlation ofweather parameter with incidence of S. exigua was quitedifferent. For 15th September sown crop, there was a positive

and significant correlation between maximum and minimumtemperature with all the varieties except for Digvijay sownon 15th January. However, all the varieties showed positiveand significant correlation with maximum temperature for1st October sown crop.

Moreover, for 30th November sown crop, ICC 3137showed positive and significantly correlation with eveningrelative humidity only, while Digvijay showed positive andsignificantly correlation with minimum temperature andrelative humidity on (morning and evening). ICC 3137showed both negative and positive (significant) correlationwith maximum and minimum temperature at 15th Decembersown crop. While, for 30th December sown crop, ICCV 10and ICC 3137 showed negative but significant correlationwith minimum and maximum temperature, respectively.

Morning relative humidity had significant positiveassociation with S. exigua for 15th September sown crop,while Digvijay for 30th November sown crop. While, ICCL86111 showed negative and significant correlation withmorning relative humidity for 30th December and 15th

January sown crop. For 30th November sown crop, ICC 3137and Digvijay showed positive and significant correlationwith evening humidity; and only Digvijay showedsignificantly positive correlation with evening humidity for30th December sown crop. The association of rainfall patternand the incidence of both the pest at different sowing dateswas not significant.

The present findings are not discussed due to lackof available literatures. It could be inferred from the presentstudy that early and late sowing of chickpea resulted inhigher infestation of S. exigua than optimum sown chickpeacrop.

Table 2. Effect of different sowing dates on grain yield (kg/ha) of Chickpea

Sowing date

Year 2014-15 Year 2015-16 Yield (kg/ha) Yield (kg/ha)

ICCL-86111 ICCV-10 ICC-3137 Digvijay Mean ICCL-86111 ICCV-10 ICC-3137 Digvijay Mean 15 Sept 1279 1244 1052 1194 1192 1275 1283 1173 1542 1319 1 Oct 1325 1094 1337 1106 1216 1250 1528 1333 1759 1468 16 Oct 1732 1708 1428 1675 1636 1738 1835 1149 1410 1533 31 Oct 1748 2141 1592 1426 1727 1590 1535 1466 2053 1661 16 Nov 1598 1570 1480 1401 1512 1597 1816 1379 1644 1609 30 Nov 877 759 923 1097 914 1285 1354 1224 1230 1273 15 Dec 650 759 305 522 559 1179 1221 1112 1402 1228 30 Dec 384 389 347 510 408 921 803 780 871 844 15 Jan 313 356 342 330 335 528 472 453 662 529 Mean 1101 1113 978 1029 1055 1231 1316 1119 1397 1273 SEm (±) CD (P=0.05) CV (%)

Sowing date Varieties Interaction (A) (B) (A x B)

81.89 54.59 163.796 227.01 NS NS 26.88

Sowing date Varieties Interaction (A) (B) (A x B)

108.50 72.33 217.014 300.76 NS NS

29.58

Chavan et al. : Beet army worm: Anemerging pest of Chickpea 5 3

Table 3. Correlation of weather parameters with S. exiguaDate of sowing

Variety Year 2014-15 Year 2015-16 Weather parameter Weather parameter

Value Tmax Tmin RHI RHII Rainfall Value Tmax Tmin RHI RHII Rainfall 0.01 0.05 0.01 0.05

1. 15 Sept

ICCL-86111 0.5897

0.4683

0.6773** 0.6466** 0.2925 - 0.0852 - 0.0995 0.3248 0.2500 0.5637** 0.5591** 0.2163 -0.0493 -0.1163 ICCV-10 0.6603** 0.6109** 0.2950 - 0.0054 - 0.1219 0.4546** 0.4647** 0.2354 0.0590 -0.0975 ICC-3137 0.5263* 0.4802* 0.2735 - 0.0049 - 0.0696 0.4862** 0.6367** 0.3239* 0.0892 0.0528 Digvijay 0.5419* 0.4947* 0.2853 0.0085 - 0.0750 0.5714** 0.4122** 0.0869 -0.2041 -0.1390

2. 1 Oct

ICCL-86111 0.6055

0.4821

0.0416 0.0349 - 0.0351 - 0.0836 - 0.0032 0.3541 0.2732 0.4548** -0.0302 0.0594 -0.2527 -0.0989 ICCV-10 0.4246 0.3196 0.0364 - 0.1901 0.0055 0.4788** -0.0327 0.0277 -0.2519 -0.1014 ICC-3137 0.0063 - 0.0115 - 0.0787 - 01019 - 0.0160 0.4646** -0.0103 0.0321 -0.2522 -0.0988 Digvijay 0.1213 0.1500 0.1099 0.0601 0.0107 0.4299** -0.0037 0.0647 -0.2201 -0.0953

3. 16 Oct

ICCL-86111 0.6411

0.5139

0.1424 0.2003 0.1309 0.0437 - 0.0390 0.3541 0.2732 -0.3446 0.0972 0.2487 0.1535 0.3062 ICCV-10 0.4327 0.0913 - 0.1553 - 0.1124 - 0.0722 0.0943 0.1151 0.1233 -0.1033 -0.0784 ICC-3137 0.4129 0.3164 0.0095 0.0635 - 0.0897 0.1492 0.1087 0.0462 -0.0357 -0.0511 Digvijay 0.4209 0.3474 0.1022 0.0852 - 0.1414 -0.0587 -0.1787 -0.1398 -0.1295 -0.0613

4. 31 Oct

ICCL-86111 0.6614

0.5324

0.4198 0.3086 0.0652 - 0.0794 0.3713 0.3932 0.3044 0.1387 -0.0232 -0.0726 -0.1552 0.0093 ICCV-10 0.3976 0.0289 - 0.2258 - 0.4219 - 0.1100 -0.1235 -0.2037 -0.1354 -0.2297 -0.0490 ICC-3137 0.3556 0.0235 - 0.2338 - 0.3502 - 0.0150 - - - - - Digvijay 0.4077 0.2427 - 0.0035 - 0.1444 0.2669 0.0808 -0.0537 -0.0350 -0.0912 -0.0371

5. 16 Nov

ICCL-86111 0.6835

0.5529

- - - - - 0.4869 0.3809 0.1488 0.2505 0.2449 0.0721 - ICCV-10 0.0286 - 0.0888 - 0.1108 - 0.1252 - 0.2563 0.1804 -0.0282 -0.0114 - ICC-3137 - - - - - 0.2212 0.3403 0.3750 0.0944 - Digvijay 0.0652 0.1192 0.1022 0.1163 - -0.0947 -0.1170 -0.1043 0.0167 -

6. 30 Nov

ICCL-86111 0.7079

0.5760

- 0.4158 - 0.4934 - 0.1975 - 0.0194 - 0.5614 0.4438 - - - - - ICCV-10 - - - - - 0.2769 0.3784 0.2323 0.3360 - ICC-3137 - 0.1967 - 0.2837 0.0543 0.1369 - 0.1546 0.4372 0.2457 0.5258** - Digvijay - 0.6686* - 0.0884 0.5831* 0.6299* - 0.0544 0.5804** 0.4918* 0.5041** -

7. 15 Dec

ICCL-86111 0.6614

0.5324

0.0637 - 0.0927 - 0.2033 - 0.2786 - 0.1564 0.5368 0.4227 0.0259 0.2248 0.2482 -0.1423 - ICCV-10 - - - - - -0.587 0.0222 -0.0598 -0.1361 - ICC-3137 - - - - - -0.7453** 0.6822** -0.2269 -0.1314 - Digvijay - - - - - -0.3219 -0.1377 0.2842 -0.1417 -

8. 30 Dec

ICCL-86111 0.7646

0.6319

- - - - - 0.3248 0.2500 0.1563 0.0197 -0.2788* -0.1999 -0.0579 ICCV-10 - - - - - -0.1935 -0.2796** -0.0087 -0.0284 -0.0352 ICC-3137 0.8519** 0.8335** - 0.1781 - 0.6407* 0.1131 -0.4196** -0.2046 0.2009 0.1628 -0.0415 Digvijay - - - - - -0.1481 -0.0034 0.0831 0.2864* -0.0211

9. 15 Jan

ICCL-86111 0.7079 0.5760 - 0.3709 - 0.2214 0.1933 0.3584 - 0.1096 0.3248 0.2500 0.1898 0.1773 -0.2766* -0.1837 -0.0431 ICCV-10 0.0878 - 0.1912 0.0424 - 0.2720 - 0.2325 -0.0137 -0.0278 -0.1350 -0.2078 -0.0512 ICC-3137 - 0.0423 - 0.3521 - 0.8521** 0.0124 - 0.1349 -0.2351 -0.2289 -0.0492 -0.0640 -0.0238 Digvijay - 0.0276 -0.4176 - 0.8754** - 0.0990 - 0.3500 0.2667* 0.2695* -0.1952 -0.1283 -0.0724

REFERENCES

Ahmed K. Lal SS, Morris H, Khalique F and Malik BA. 1990. Insectpest problems and recent approaches to solving them on chickpeain South Asia. In: Chickpea in the nineties: Proceedings of 2nd

International Workshop on chickpea improvement, 4-8December 1989. Ed. By Walby B.J., Hall, S.D. InternationalCrops Research Institute for the Semi-Arid Tropics (ICRISAT),Hyderabad Pp 165-168.

Anonymous 2014. Integrated pest management package forchickpea. Bulletin of NCIPM, Govt. of India, Ministry ofAgriculture, Directorate of plant Protection quarantine andstorage, CGO Complex, NH IV, Faridabad.

Anonymous 2015. District wise general statistical information ofAgriculture Department, Part-II Govt. of Maharashtra.

Cumming G and Jenkins L. 2011. Chickpea: Effective cropestablishment, sowing window, row spacing, seedling depth andrate. Northern Pulse Bulletin 7: 6

Gan YT, Siddiquez KHM MacL.eod WJ and Jayakumar P. 2006.Management options for minimizing the damage by ascochyta

blight (Ascochyta rabiei) in chickpea (Cicer arietinum L.). FieldCrops Research 97: 121-134.

Gaur PM, Mallikarjuna N, Knights T, Beebe S, Debouck D, Mejia A,Malhotra RS, Imtiaz M, Sarkar A and Tripathi S. 2010. Geneintrogression in grain legumes. In Grain legumes: Geneticimprovement, management and trade, Eds., S. Gupta, M. Ali, B.B. Singh, Indian Society of Pulses Research and Development:IIPR, Kanpur, India Pp 1-7.

Rahman MM and Mannan MA. 1982. Pest survey of major summerand winter pulses in Bangladesh. In: Proceedings of the NationalWorkshop on Pulses. August 18-19, 1981. Edited by AK Kaul.Published by Director, Bangladesh Agricultural Research Institute.Joydebpur, Dacca Pp 265-273.

Sharma HC, Gowda CLL, Stevenson PC, Ridsdill-Smith TJ, ClementSL, RangaRao GV, Romies J, Miles M and El Bouhssini M. 2007.Host plant resistance and insect pest management in chickpea.In: Chickpea breeding and management. Ed. by Yadav, SS, Redden,RR, Chen, W, Sharma, B, CAB International, Wallingford, UKPp 520-537.

Steel RGD and Torrie JH. 1960. Principles and Procedures ofStatistics, Mcgraw- HillBool. Co. Inc., New York Pp 107-109.


Economics of rajmash cultivation in Eastern Jammu regionSANJEEV KUMAR, SP SINGH, ANIL BHAT and MANISH KUMAR SHARMA

Division of Agricultural Economics and ABM, Sher-e-Kashmir University of Agricultural Sciences and Technology,Jammu, Main Campus, Chatha-180009, India; E-mail: [email protected](Received: December 12, 2016; Accepted: March 29, 2017)

ABSTRACT

An economic analysis of rajmash was carried out inBhaderwah and Bhalla blocks of Doda district of Jammu &Kashmir state during 2015-16. From each selected block,five villages were selected randomly and from each selectedvillage, 10 farmers were selected randomly withoutreplacement so as to constitute a total sample size of 100farmers. The sample comprised of 78 marginal farmers, 14small farmers and 8 medium farmers. Primary data wereused to analyze the results. Which revealed that per hectarecost of cultivation of rajmash was ` 33176 on marginal farms,` 36301 on small farms and ` 37931 on medium farms,respectively with an overall average of ` 35354. On overallcost A1, A2, B1, B2, C1, C2 and C3 were worked out to be `15043, ` 15816, ` 15885, ` 28489, ` 22749, ` 35354 and `38889, respectively. On an average, the returns per rupee ofinvestment over cost A1, A2, B1, B2, C1, C2 and C3 were ` 4.72,` 4.49, ` 4.47, ` 2.49, ` 3.12, ` 2.01 and ` 1.83, respectively..Net income of rajmash cultivation varied from ` 37761 onmarginal farms to ` 32533 on medium farms with an overallaverage of ` 35634. The cost benefit ratio was calculated as2.12, 1.94 and 1.86 on marginal, small and medium farms,respectively. On overall, the cost benefit ratio was workedout to be 2.01.

Key words: Cost Benefit ratio, Net Income, Rajmash

Rajmash (Phaseolus vulgaris L.) is the mostimportant legume grown worldwide for direct humanconsumption. The crop is consumed principally for its dryand mature beans, shell beans (seeds at physiologicalmaturity) and green pods. Rajmash contains high levels ofchemically diverse components (phenols, resistance starch,vitamins, Fructo-oligosaccharides) that have shown toprotect against oxidative stress, metabolic syndrome andmany types of cancer (Camara et al. 2013). It provides21.25% crude protein, 1.7% fat and 70% carbohydrates andrepresents 50 per cent of the grain legume consumedworldwide (Mc Connell 2010). Besides, it contains 0.16 mgiron, 1.76 mg calcium and 3.43 mg zinc per 100 g of ediblepart. Rajmash is the staple food in Latin America, Africaand India. Globally, rajmash is cultivated over an area of29.92 million hectares with an annual production of 23.23million tonnes. Currently, Brazil is the largest producer ofrajmash followed by India, Myanmar and China(Anonymous 2013).

In India, rajmash is grown in an area of about 10.80million hectares with an annual production of 4.87 million

tonnes (Anonymous 2015). It is grown mainly in the statesof Maharashtra, Jammu and Kashmir, Himachal Pradesh,Tamil Nadu (Nilgiri Hills, Palani Hills), Uttar Pradesh, Kerala(Parts of Western Ghats), Karnataka (Chickmangalur Hills)and West Bengal (Darjeeling Hills). North-Western IndianHimalayan state of Jammu and Kashmir exhibits a greatvariation in the agro-climates at macro and micro level,involving cold arid, temperate, intermediate and sub-tropicalzones within a small geographical area of 22.2 millionhectares. It indicates the inherent agriculture potential ofthe state (Sultan 2014). Some of the best rajmash are said tobe grown in Himachal Pradesh and Jammu region of J & K.In J & K, rajmash is grown in Doda, Poonch, Rajouri,Udhampur, Ramban, Kathua and Reasi districts Marwah,Dachhan, Mandi and Bani dry temperate areas of Kishtwardistrict. Going further, the rajmash of Chinta Valley in Dodadistrict, a short distance from Bhaderwah town of Jammuprovince is amongst the finest ever. The J&K governmenthas launched a rajmash project under the Rashtriya KrishiVikas Yojana (RKVY) in the year 2011-12 for a period of fiveyears to boost the production, quality and marketingprospects of rajmash of J & K (Anonymous 2015). Thecrop covering area around 6000 ha under Doda district ofJ&K state. It is mainly grown in Bhaderwah, Bhalla, Marmat,Ghat Doda, Bhalessa, Bhagwah, Thathri, Gundana andAssar blocks of Doda district. It is the niche and valuablecash crop and popular not only in the state, but also atnational level for taste, texture, aroma and palate(Anonymous 2014). Therefore, an attempt is made to studythe cost structure and profitability of rajmash in this studyarea.


The present study was purposively conducted inDoda district of J & K state during 2015-16. The Doda districtwas selected purposively on the basis of crop (secondhighest area covering around 6000 ha under rajmash) inJammu region and its grown for taste, texture, aroma anddefebility. Five villages from each block were selectedrandomly. Further, from each village, 10 farmers wereselected randomly without replacement so as to constitutea total sample size of 100 farmers. The sample farmers werefurther categorized into marginal (up to 1 ha), small (1.01-2ha) and medium farmers (2.01-4 ha) based on their landholding. Thus, the total sample of 100 farmers comprised of78 marginal farmers, 14 small farmers and 8 medium farmers.The primary data on cost and returns were collected by

Kumar et al. : Economics of rajmash cultivation in Eastern Jammu region 5 5

survey by interviewing the rajmash growers directlythrough a pre-tested schedule. For estimating the cost ofcultivation of rajmash, various cost concepts framed byCACP (cost A1, A2, B1, B2, C1, C2 and C3) were used and tofind out the returns, various income measures (grossincome, farm business income, family labour income, netincome and returns per rupee) were estimated.


The cost of cultivation and the returns to differentfactors of production helps in decision making about theselection of an enterprise and hence, these measures wereworked out and presented in Table 1, 2 and 3.Cost structure in production: The cost structure inproduction of rajmash included the cost on productioninputs like, casual labour, family labour, machine labour,bullock labour, seed, manure & fertilizers, plant protectionchemicals, while fixed costs were comprising of rental valueof land, interest on fixed capital and depreciation on farmbuilding and implements. The cost on various inputs usedfor cultivation of rajmash per hectare on the sampleholdings have been worked out (Table 1).

It is evident that the total cost of cultivation ofrajmash was higher on medium farms (` 37931/ha) ascompared to small farms (` 36301/ha) and marginal farms(` 33716/ha) with an averge cost a ` 35354/ha. The

operational cost on marginal farms (` 20093/ha), small farms(` 20636/ha) and medium farms (` 21160/ha) showed adirect relationship with the farm size which constituted 59.59,56.85 and 55.78 percent of the total cost on marginal, smalland medium farms, respectively. On all farms, operationalcost (` 20482/ha) was 57.93 percent of that of total cost.Among the operational cost, expenditure on total humanlabour was the main component followed by expenditureon seed, machine labour and bullock labour. In case offixed cost, the per hectare expenditure on rental value ofowned land was major cost component which was workedout to be ` 11913 on marginal farms, ` 11766 on small farmsand ` 11744 on medium farms. Overall, rental value ofowned land was worked out to be ` 11831/ha.Concept-wise cost of cultivation: The cost of cultivationper hectare on the basis of different cost concepts wereestimated (Table 2). It indicated that all the costs increasedwith increase in the size of holding as there was a direct

Note: Figures in parentheses represents percentage of total cost

Table 1. Structure-wise cost of cultivation in rajmash

S. No.

Particulars Marginal Small Medium All farms

A. Operational Cost i Casual labour 484 2218 3708 1681 ii Family labour 8014 6290 4979 6864 iii Total human labour 8498 8508 8687 8546 iv Machine labour 2682 2763 2864 2746 v Bullock labour 1403 1190 937 1239 vi Seed 4830 4906 4906 4867 vii Manure and fertilizers 898 1211 1395 1094 viii Plant protection

chemicals 239 455 713 405

ix Irrigation charges 0 0 0 0 x Miscellaneous charges 481 498 510 492 xi Interest on working

capital 1057 1100 1144 1089

Sub-Total (A) (from i to xi)

20092 (59)

20636 (56)

21160 (55)

20481 (57)

B. Fixed cost xii Rental value of owned

land 11912 11766 11743 11831

xiii Rent paid for leased-in land

0 1272 1927 773

xiv Sub-Total (xii + xiii) 11912 13038 13671 12604 xv Depreciation 639 1439 1850 1125 xvi Land Revenue 300 300 300 300 xvii Interest on fixed capital 771 886 949 841

Sub-Total (B) (from xiv to xvii)

13623 (40)

15664 (43)

16770 (44)

14872 (42)

Total cost (A+B) 33716 36300 37930 35354

Table 2. Concept-wise cost of cultivation of rajmashCategories Particulars

Marginal Small Medium All farms

Cost-A1 Casual labour 484 2218 3708 1681 Machine labour 2682 2763 2864 2746 Animal labour 1403 1190 937 1239 Seed 4830 4906 4906 4867 Manure and fertilizers 898 1211 1395 1094 Plant protection chemicals 239 455 713 405 Irrigation charges 0 0 0 0 Miscellaneous expenditure 481 498 510 492 Interest on working capital 1057 1100 1144 1089 Depreciation charges 639 1439 1850 1125 Land revenue 300 300 300 300 Total cost- A1 13017 16085 18331 15042 Cost-A2 Cost-A1 13017 16085 18331 15042 Rent paid for leased in land 0 1272 1927 773 Total Cost-A2 13017 17357 20258 15816 Cost-B1 Cost-A1 13017 16085 18331 15042 Interest on fixed capital (excluding land)

771 886 949 841

Total Cost- B1 13788 16972 19280 15884 Cost-B2 Cost-B1 13788 16972 19280 15884 Rental value of owned land 11912 11766 11743 11831 Rent paid for leased in land 0 1272 1927 773 Total Cost-B2 25701 30010 32951 28489 Cost-C1 Cost-B1 13788 16972 19280 15884 Family Labour 8014 6290 4979 6864 Total Cost-C1 21803 23262 24259 22749 Cost-C2 Cost-B2 25701 30010 32951 28489 Family labour 8014 6290 4979 6864 Total Cost-C2 33716 36300 37930 35354 Cost- C3 Cost-C2 33716 36300 37930 35354 Cost of management (10% of Cost-C2)

3371 3630 3793 3535

Total Cost-C3 37087 39930 41724 38889


relationship between costs and farm size. On overall cost-A1, cost-A2, cost-B1, cost-B2, cost-C1, cost-C2 and cost-C3onall farms were worked out to be ` 15043, ` 15816, ` 15885,` 28489, ` 22749, ` 35354 and ` 38889, respectively. TheThetotal cost-C2 i.e. the total cost of cultivation of rajmash waslower on marginal farms among different categories of farmsmainly due to very low expenditure on casual labour andzero amount of rent in case of leased in land as compared tosmall and medium farmers. Cost-C3 was worked out to be` 38889 on overall.Concepts-wise economics: Concepts-wise economics ofrajmash was worked out (Table 4), which depicted thatoverall net returns on all farms over cost-A1, cost-A2, cost-B1, cost-B2, cost-C1, cost-C2 and cost-C3were ` 55945,` 55172, ` 55103, ` 42499, ` 48239, ` 35634 and ` 32099per hectare of rajmash cultivation, respectively. On differentcategories of farms, net returns varied from ` 58459/ha to` 28740/ha. The returns per rupee of investment on allfarms over cost-A1, cost-A2, cost-B1, cost-B2, cost-C1, cost-C2 and cost-C3 were ` 4.72, ` 4.49, ` 4.47, ` 2.49, ` 3.12,` 2.01 and ` 1.83, respectively. On different categories offarms, returns per rupee varied from ` 5.49 to ` 1.69.

Thus, returns per rupee over cost-C2 were highestfor marginal farms (` 2.12) followed by small farms (` 1.94)and medium farms (` 1.86). It revealed that the net returnsand returns per rupee decreased from cost-A1 to cost-C3on different categories of farms as well as on all farms.Productivity and income: The productivity and incomefrom cultivation of rajmash was estimated (Table 3) whichindicated that the productivity of marginal farms (5.24 q/ha) was higher as compared to small farms (5.09 q/ha) andmedium farms (5.08 q/ha). However, on all farms,productivity was 5.17 q/ha. It was found that per hectarefarm business income (profit at Cost A) and family labourincome (profit at Cost B) decreased with increase in size offarm. The results also revealed that the gross income washighest on marginal farms (` 71477/ha) followed by small

farms (` 70598/ha) and medium farms (` 70464/ha). Thismight be due to the reason that with increase in the farmsize farmers could not manage their farm properly and notutilizing their resources efficiently. On all farms, grossincome was ` 70988 per hectare with benefit cost ratio of2.01. Although the benefit cost ratio was higher on marginalfarms (2.12) as compared to small (1.94) and medium farms(1.86) but was for all categories of farms suggesting >1.0was the fact that rajmash cultivation was economically verymuch profitable in the study area and each rupee spent inrajmash cultivation would yield return of ` 2.12 in case ofmarginal farms, ` 1.94 in case of small farms and ` 1.86 incase of medium farms, respectively. On overall, net incomein rajmash cultivation (profit at Cost C) was ` 35634 perhectare.

REFERENCES

Anonymous 2013. Food and Agriculture Organization of the UnitedNations. FAOSTAT database.Website: http://www.fao.org.

Anonymous 2014. Agriculture Department, Jammu. District Dodaat a Glance. Web portal of Doda District, J&K, India. Website:http://doda.gov.in.

Anonymous 2015. Agricultural Statistics at a glance. Directorate ofEconomics and Statistics.Department of Agriculture andCooperation.Ministry of Agriculture, New Delhi.

Anonymous 2015. Website: http://groundreport.com/jk; Accessedon 16 th March, 2015. Website: http://agricoop.nic.in/eands;Accessed on 23rd March, 2015.

Bhat A, Kachroo J and Kachroo D. 2011. Economic Appraisal ofKinnow Production and its Marketing under North-WesternHimalayan Region of Jammu Agriculture Economics ResearchReview 24(2): 283-290.

Camara CRS, Urrea CA and Schlegel V. 2013. Pinto Beans (Phaseolusvulgaris L.) as a Functional Food: Implications on Human HealthAgriculture 3: 90-111.

Mc Connell M, Mamidi S, Lee R, Chikara S, Rossi M, Papa R and MClean P. 2010. Syntenic relationships among legumes revealedusing a gene-based genetic linkage map of common bean.Theoretical and Applied Genetics 40: 110-124.

Sharma H, Singh IP and Burark SS. 2012. Production and ResourceUse Efficiency in Cotton in Hanumangarh District of Rajasthan.Journal of Agricultural Development and Policy 22(2): 63-70.

Sultan SM, Dar SA, and Sivaraj N. 2014. Diversity of CommonBean in Jammu and Kashmir, India: a DIVA-geographicinformation system & cluster analysis. Journal of Applied andNatural Sciences 6(1): 226-233.

Table 3. Concept wise economics of rajmashParticulars Marginal Small Medium All farms Net returns over different cost (`/ha) Cost A1 58459 54512 52132 55945 Cost A2 58459 53240 50205 55171 Cost B1 57688 53625 51183 55103 Cost B2 45775 40587 37512 42498 Cost C1 49673 47335 46203 48238 Cost C2 37760 34297 32532 35633 Cost C3 34389 30667 28739 32098 Returns per rupee over different cost Cost A1 5.49 4.39 3.84 4.72 Cost A2 5.49 4.07 3.48 4.49 Cost B1 5.18 4.16 3.65 4.47 Cost B2 2.78 2.35 2.14 2.49 Cost C1 3.27 3.03 2.90 3.12 Cost C2 2.12 1.94 1.86 2.01 Cost C3 1.93 1.77 1.69 1.83

Table 4. Production and return from cultivation of rajmashParticulars Marginal Small Medium All farmsMain product (q/ha) 5 5 5 5 By- product (q/ha) 4 4 4 4 Value of main product (Rs./ha) 71240 70368 70236 70755 Value of by product (Rs./ha) 236 227 227 232 Gross income (Rs./ha) 71477 70597 70463 70987 Farm business income (Rs./ha) 58459 53240 50205 55171 Family labour income (Rs./ha) 45775 40587 37512 42498 Net income (Rs./ha) 37760 34297 32532 35633 Cost Benefit Ratio 1 : 2 1 : 1 1 : 1 1 : 2


Impact of cluster front line demonstrations on productivity and profitability ofchickpea (Cicer arietinum L.)AK MAURIYA, VINOD KUMAR, ANITA KUMARI, PANKAJ KUMAR, MAMTA KUMARI andMZ HODA

Krishi Vigyan Kendra, Bhagalpur, Bihar Agricultural University, Sabour-813210, Bihar, India; E-mail:[email protected](Received: August 16, 2016; Accepted: December 10, 2016)

ABSTRACT

The present study was conducted in Bhagalpur district ofBihar to evaluate the improved technologies of chickpeaproduction through cluster front line demonstrations(CFLDs) at the farmers’ field. In all, 128 demonstrationswere carried out during rabi, 2015-16. Improved technologiesof chickpea comprised of the use of improved variety (GNG1581), seed treatment with Rhizobium (20g/kg seed),carbendazim (2.5 g/kg seed), recommended dose of manuresand fertilizer application, integrated pest management(pheromone trap at 10-12 traps/ha) practices and integratedcrop management (ICM). CFLD with improved productiontechnologies had yielded 11.2 q/ha which was 17.9% higheras compared to farmer’s practice (9.50 q/ha). In spite ofincrease in yield of chickpea, extension gap and technologyindex existed. Improved production technologies of CFLDgave higher net return (` 46250/ha) with maximum benefitcost ratio (3.53) as compared to farmers’ practices (3.20).

Key words: Chickpea, Economics, Extension gap, Technologygap, Technology index

Chickpea (Cicer arietinum L.) is an important rabiseason food legume crop with extensive geographicaldistribution. The crop contributes 39 per cent to the totalproduction of pulses in the country. In India, it occupiesabout 9.18 million hectare area with production of 8.22 milliontonnes and an average productivity of 900 kg/ha(Anonymous 2013). It is a good source of protein (18-22%), carbohydrate (52-70 %), fat (4-10 %), minerals (calcium,phosphorus, iron) and vitamins. It is an excellent animalfeed. Its straw also had good forage value. Pulsescontribute 11% of the total intake of proteins in India (Reddy2010). In India, frequency of pulses consumption is higherthan any other source of protein, which indicates theimportance of pulses in the daily food habits. India achieveda record food grain production of 265 MT in the year of2013-14 where pulses contributed nearly 19 MT.Government has targeted for total pulses production of20.75 MT in the year 2016-17 which is 21.6% higher thanestimated production of 17.06 MT in the year 2015-16.However, per capita pulses availability has declined from61 g/day in 1950-51 to less than 31.6 g/day in 2014-15 asagainst 70 g/day the standard prescribed by ICMR. Ingeneral, average productivity of chickpea is less mainly

due to its cultivation on marginal/rainfed lands under poormanagement, abiotic stresses, inappropriate productiontechnology (wilt susceptibility and old varieties, under doseof fertilizers and poor plant protection measures) and heavyinfestation of insect pest at various stage of crop. Podborer are the key pest that causes heavy economic lossthroughout the country. One larva of Helicoverpaarmigera is capable of damaging 30 to 40 pods in its lifetime. Estimates indicate that 8 larva reared on 10 plants(in 1 m row) caused up to 39% yield loss. Recently, welfere,Ministry of Agriculture & Farmer’s has taken a new initiativeto augment the production of pulses largely throughenhancement in quality seed production of recommendedvarieties and conduct of large scale Front LineDemonstration in cluster. Realizing the importance ofextending these technologies for increasing theproductivity and profitability at farmer level, cluster frontline demonstrations (CFLDs) were conducted to show theproductivity potential and profitability of chickpea underthe close supervision of scientist of the Krishi VigyanKendra, Bhagalpur. It is believed that these CFLDs wouldenhance the adoptability of technologies based onintegrated crop management in pulses amongst the farmersof Bhagalpur district.


The present study was carried out by KVK,Bhagalpur under Bihar Agricultural University, Sabour,Bhagalpur during winter season at farmers’ fields of twentythree villages of eight block of Bhagalpur district during2015-16 under rainfed/tal/diara areas. One cluster made inone village. All 128 front line demonstrations in cluster withimproved technologies in 40 ha area were conducted indifferent villages. In the demonstration, one control plotwas also kept involving farmers’ practice in each cluster of23 villages. Materials for the present study with respect toCFLD included use of improved variety Gangaur (GNG 1581)at optimum seed rate (75 kg/ha), Rhizobium inoculation,seed treatment with insecticide and fungicide, proper tillage,balance dose of fertilizers (20 kg/ha N + 40-50 kg/ha P2O5)application as basal, proper weed management and IPM(including Spinosad 45 SC 200 ml/ha with sex pheromonetrap for Helicoverpa armigera). Sex pheromone traps wereapplied at10-12 numbers/ha after 25-30 days after sowing.


Spinosad 45 SC 200 ml/ha was sprayed when Helicoverpaarmigera larvae population was more than its critical level.The population of Helicoverpa armigera larvae wasrecorded on five randomly selected plants from five plotsin each cluster. The improved technologies included needbased full crop production package such as recent highyielding varieties, seed treatment with fungicide(Carbendazim 50% WP at 2.5 g/kg seed), insecticide(Imidacloprid 18.6 SL at ml/kg seed) and bio-fertilizer(Rhizobium culture at 20-30 g/kg seed) and maintenance ofoptimum plant population. The sowing was done during20th October to last November in residual moisture at a seedrate of 75 kg/ha after seed treatment in FRI sequence. Weedcontrol with the help of pendimethalin at 1.0 kg a.i./haapplied as pre-emergence and hand weeding was done at25-30 and 50-55 DAS. The crops were harvested at perfectmaturity stage in the month of third week of March to firstweek of April. Crop was harvested either plucked out byhand or cut with sickle.

In general, soils of the area under study were greyishred in colour, medium to heavy in texture with medium tolow fertility status that develops cracks during summer.The average rainfall of this area was 1208 mm with 992 mmrainfall received during 3rd week June to 3rd week of October.The cluster front line demonstration was conducted tostudy the technology gap between the potential yield anddemonstrated yield, extension gap between demonstratedyield and yield under existing practice, and technologyindex. The yield data were collected from both thedemonstration and farmers’ practice by random crop cuttingmethod and analyzed by using simple statistical tools. Forthe study, technology gap, extension gap and technologyindex were calculated as suggested by Samui et al. (2000).

varieties (known as desila in local name) with high seedrate (125-140 kg/ha), without Rhizobium inoculation,imbalanced use of fertilizer, in proper weed control and inproper pod borer (Helicoverpa armigera) control. Pre-sowing trainings were organized involving the selectedfarmers in their village for the crops and local extensionfunctionaries. In demonstration plots, critical inputs in theform of improved variety seed (GNG 1581), bio-fertilizers,fungicide and pheromone trap were provided to the farmersby KVK after the training. Subsequently demonstratedcrops were monitered during different crop growth stagesby the KVK scientists. Finally field day was conductedinvolving adopted farmers, other farmers in the villagesand local extension functionaries so to demonstrate thesuperiority of the technology. Crop yield was recorded fromthe demonstration and control plots at 3-5 plots in eachcluster at the time of harvest. The data on incidence ofdisease, population of insects, seed yield, cost ofcultivation and gross monetary return were collected fromboth improved technologies and farmers’ practice plots.


Yield gap analysis: Remarkable change on yield parameterswas observed. The yield attributing characters viz., plantheight, primary branches/plant, secondary branches/plant,numbers of pods/plant, number of seeds/pod and 100 seedsweight were positively affected by improved technologiesunder CFLD. Maximum varities of yield attributingcharacters were recorded under improved technologies asthese gave maximum yield. The average yield of improvedtechnologies (demonstrated plots) of chickpea was muchhigher than average yield of farmers’ practices (controlplots). The average yield of improved technology was 11.20q/ha which area 1.7 q/ha higher than average farmers’practices (calculated 15.2% yield gap over farmers’practices). It might be due to line sowing with optimumspacing, improved variety with optimum seed rate,Rhizobium inoculation, optimum fertilizer application,proper weed control and Helicoverpa armigera control bypheromone trap. The results indicated that the cluster frontline demonstrations had given a good impact over thefarming community of Bhagalpur district as they weremotivated by the new agricultural technologies applied inthe CFLD plots. Thus finding are incorroboration with thatof Dubey et al. (2010), Meena (2010), Poonia and Pithia(2011).Technology gap analysis: The technology gap in thedemonstration yield over potential yield was 1248 kg/ha.This gap may be attributed to the dissimilarity in the soilfertility status and weather conditions. Similar finding wasalso reported by Singh et al. (2014), Lalit et al. (2015).Extension gap analysis: Average extension gap of 170 kg/ha was recorded in chickpea. This emphasized the need toeducate the farmers through various means for the adoption

Potential yield

Yield gap (%) =Demonstration yield-farmers’ yield

x 100Farmers’ yield

Technology gap = Potential yield - Demonstrated yield

Extension gap = Demonstrated yield – Yield under existing farmer’s practice

Potential yield - Demonstrated yieldTechnology index = x 100

Cluster front line demonstration plot involvingholdings of different categories of farmers in 23 villageswere selected for chickpea. The selection of farmers wasdone village wise. CFLD Farmer with large, medium andsmall holding were included in the study. A group of co-operative farmers were identified based on theirparticipation and feedback received during the preliminarysurvey and interactive meeting. Causes for low crop yieldof chickpea were identified and prioritized throughpreliminary discussion with selected farmers. Based on themajor causes, technological interventions were finalized.Under farmer’s practice (control plots), farmers used old

Mauriya et al. : Impact of cluster front line demonstrations on productivity and profitability of chickpea 5 9

of improved agricultural production technologies to reversethis trend of wide extension gap. The technology gap wasranged 50 to 260 q/ha which might be attributed due todissimilarity in the soil fertility status, agricultural practicesand local climate conditions. More and more use of latestproduction technologies with high yielding variety willsubsequently change this alarming trend of gallopingextension gap. The new technologies will eventuallymotivate farmers to adopt new technology. This finding isin corroboration with the findings of Kirar et al. (2006),Singh et al. (2014).Technology index: The technology index shows thefeasibility of the evolved technology at the farmers’ fields,and the lower the value of technology index the more is thefeasibility of the technology as reduction in technologyindex exhibited the feasibility of technology demonstrated.The CFLD provided a significant positive result and alsogive the researchers an opportunity to demonstrate theproductivity potential and profitability of the integratednutrient management under real farm situation. Similarfindings were reported by Rajiv and Singh (2014), Singh etal. (2014).

Economic analysis: The inputs and outputs prices ofcommodities prevailed during the study of demonstrationswere taken for calculating gross return, cost of cultivation,net return and benefit: cost ratio. ` 18,300/ha higherexpenditure in Cluster Front Line Demonstrations his dueto improved technologies over farmers’ practices (` 17,000/ha). Use of improved technologies in CFLD also increasednet economic return. Maximum net return (` 46,250 /ha)was recorded in CFLD, which was ` 8,850 /ha higher thanfarmer’s practice. The benefit cost ratio of CFLD underimproved technologies was recorded as 3.53. (3.20 underfarmers’ practice). This might be due to higher yieldsobtained in CFLD under improved technologies comparedto farmers practice. This finding is in corroboration withthe findings of Raj et al. (2013).Implications: This study paved the way for extensionworkers for effective and efficient technology transfer inthe field of Agricultural Extension (with good impact andfeedback). The technology index indicates the feasibilityof evolved technology at the farmers’ field. This studysuggests for conducting intensive trainings, cluster frontline demonstrations and receive feedback for effective use

Table 2. Impact of improved technologies under cluster front line demonstration Helicoverpa armigera, yield and yield attributeat harvest stage of chickpea

Table 3. Impact of improved technologies under CFLD on economics of chickpea

Table 1. Differences between improved technologies under CFLD and farmers’ practicesSN. Particular Improved technologies Farmers’ Practice Gap 1. Variety Gangaur (GNG 1581) Desila (old and degenerated) Full gap

2. Seed treatment Carbendazim 50% WP @ 2.5 g/kg seed Imidacloprid 18.6 SL @ 3.0 ml/kg seed Rhizobium culture @ 20 /kg seed

Without seed treatment Full gap

3. Land preparation Three ploughing Three ploughing Nil

4. Sowing time 20th October to last November First week of November to last end of December Partial gap

5. Sowing in residual moisture Yes Yes/No Partial gap

6. Seed rate 75 kg/ha on the basis of seed size (small seeded) 125-140 kg/ha Higher seed rate 7. Fertilizer dose Balance dose of fertilizers (20 kg/ha N + 40-50 kg/ha P2O5) Unbalance/ No use of fertilizer Full gap

8. Weed control Pendimethalin @ 1.0 kg a.i./ha applied as pre-emergence and Hand weeding was done at 25-30 and 50-55 DAS No weeding Full gap

9. Irrigation Nil Nil Nil

10. Plant protection Helicoverpa armigera control by IPM including insecticide and sex pheromone trap No control Full gap

Variables Plant height (cm)

Helicoverpa armigera larvae/five

plants

Primary branches/plant

Secondary branches/plant

Pods/ plant

Seeds/pod 100-seed wt. (g)

Yield (q/ha)

Improved technologies 48.7 2.4 5.4 11.9 70 1.87 18.6 11.2 Farmer’s Practices 62.3 10.7 3.7 8.1 55.7 1.32 17.2 9.5 *1 q = 100 kg

Variables Total cost of cultivation (`/ha) Gross income (`/ha) Net returns (`/ha) B:C ratio Improved technologies 18,300 64,550 46,250 3.53 Farmer’s Practices 17,000 54,400 37,400 3.20

Average yield (q/ha) Per cent increase

Technology gap (q/ha)

Extension gap (q/ha)

Technological index (%) Improved Technology under CFLD Farmers' practice

11.20 9.50 15.20 1248 170 52.7

Table 4. Impact of improved technologies under cluster front line demonstration on Gap in grain yield production


of all means of extension education to educate chickpeagrowers for higher production of the crop and to get highernet return on sustainable basis.

From the above, it can be inferred that both knowledgeand adoption level of the farmers were amplified afterimparting training and conducting by CFLDs also revealedthat the farmers could increase Chickpea productionsignificantly. The productivity and profitability under CFLDover farmers’ practice created awareness and motivatedthe other farmers to adopt these improved technologies.

REFERENCES

Anonymous 2013. Statistical year book, India 2013. Ministry ofstatistics and programme implementation.http://www.http://mospi.nic.in/Mospi_New/upload/SYB2013/index1.html

Dubey Swapanil, Tripath Sarvesh, Singh Pradyuman and SharmaRakesh Kumar. 2010. Yield gap analysis of chickpea productionthrough front line demonstration. Journal of ProgressiveAgriculture 1(1): 42-44.

GOI. 2010. Economic survey of India. Ministry of Finance EconomicDivision GOI, New Delhi 17-22.

Kirar BS, Narshine R, Gupta AK and Mukherji SC. 2006.Demonstration: An effective tool for increasing the productivityof Urd. Indian Research Journal of Extension Education 6(3):47-48.

Lalit M, Patil DJ, Modi, Vasava HM, Gomkale SR. 2015. Evaluationof Front Line Demonstration Programme on Green gram VarietyMeha (IPM-99-125) in Bharuch district of Gujarat. Journal ofAgriculture and Veternary Science 1: 01-03.

Meena BB. 2010. Socio-economic characteristics and technologyuse pattern of farmers. Agricultural Extension Review, January-March 1(2): 16-17.

Poonia TC and Pithia MS. 2011. Impact of front line demonstrationsof chickpea in Gujarat. Legume Research 34(4): 304-307.

Raj AD, Yadav V and Rathod JH. 2013. Impact of front linedemonstration (FLD) on the yield of pulses. International Journalof Science and Research 9(3): 1-4.

Rajiv and Singh Lakhan. 2014. Performance of PulsesDemonstrations in Bundelkhand Zone of Uttar Pradesh, India.Indian Journal of Applied Research 4(3): 1-3.

Reddy AA. 2010. Regional Disparities in Food Habits and Nutritionalintake in Andhra Pradesh, India. Regional and Sectoral EconomicStudies 10: 2.

Samui SK, Mitra S, Roy DK, Mandal AK and Saha D. 2000. Evaluationof front line demonstration on groundnut. Journal of IndianSociety Costal Agricultural Research 18(2): 180-183.

Singh, Dhananjai, Patel AK, Baghel MS, Singh SK, Singh Alka andSingh AK. 2014. Impact of front line demonstration on theyield and economics of chickpea (Cicer arietinum L.) in Sidhidistrict of Madhya Pradesh. Journal of Agriculture Research1(1): 22-25.


Effect of maleic hydrazide on inducing dormancy in green gram (Vigna radiata L.)PM GADHAVE, VR SHELAR and BS MUNDE

Department of Agricultural Botany, Mahatma Phule Krishi Vidhyapeeth, Rahuri, Ahmednagar-413722,Maharashtra, India; E-mail: [email protected](Received: March 10, 2017; Accepted: April 29, 2017)

ABSTRACT

The search for investigation of non conventional methods ofinducing dormancy in green gram to save and retain thequality and quantity of produce against the field sproutingare of greater importance. There are some chemicals whichare capable of altering seed dormancy. Foliar application ofmaleic hydrazide at different growth stages help in alteringdormancy in seed. In present investigation, two genotypesviz., Vaibhav and Kopergaon-1 were sprayed with fiveconcentration of Maleic Hydrazide at 1000, 2000, 3000, 4000and 5000 ppm (along with control) at two stages of crop growthi.e. 40 and 50 DAS. The induction of dormancy was tested bygermination test conducted at 5 days interval immediatelyafter harvest. The study revealed that irrespective of varietiesmaleic hydrazide sprayed at 1000 ppm was most effective forinduction of dormancy up to 40 days.

Key words: Dormancy, Green gram, Maleic hydrazide

Greengram (Vigna radiata L.) belongs to the familyLeguminosae. India is the major pulse growing country inthe world accounting to 23.63 m ha area (35.2%) and 14.76m tonnes (26.65%) of world production. In Maharashtra itis grown in an area of 6.11 lakh ha with an annual productionof 3.71 lakh m tonnes with an average productivity of 553kg/ha (Anonymous 2011). Dormancy is the major problemin mungbean. Therefore, it is important to induce dormancyby non conventional methods to save the produce andretain the seed quality against the field sprouting. Thereare some chemicals which are capable of altering the seeddormancy. Maleic hydrazide in one of these, the effect ofmaleic hydrazide for induction of dormancy in groundnuthas also been reported (Jayadeva 2007). Very little workhas been done with respect to the induction of seeddormancy in green gram. There is a need to identify sourcesof chemicals which can induce certain period of dormancyto minimize yield losses due to in situ germination (AshokKumar 1989). The study on these aspects in green gram isvery meager and therefore, there is an urgent need to studythe induction of dormancy in this crop.

The present study was conducted during Kharif 2012at Seed Technology Research Unit Farm, Department ofAgricultural Botany, Mahatma Phule Krishi Vidyapeeth,Rahuri. Cent per cent maleic hydrazide (MH) in the form ofpowder was used for the foliar spray. Differentconcentrations (1000, 2000, 3000, 4000 and 5000 ppm) of

maleic hydrazide were prepared in adding 3, 6, 9, 12 and 15g of MH powder in 100 ml of distilled water, respectively.Then mixture was dissolved by using KOH pellets with thehelp of magnetic stirrer. Then final volume was made upto3 liters. Care was taken while spraying to prevent the carryover of the drift of solution to the adjoining plots. Maleichydrazide was sprayed at two stages of crop growth (i.e.40 DAS and 50 DAS) with five concentrations viz., 1000,2000, 3000, 4000 and 5000 ppm (along with a absolutecontrol) in both the varieties Vaibhav and Kopergaon-1.

For testing dormancy, the germination percentagewas determined. Four replications of 100 seeds from eachtreatment were kept for germination at 25oC temperature for8 days using between paper method (BP). The germinationpercentage was expressed on the basis of normal seedlingsonly as described in ISTA rules (Anonymous 1999).

In current investigation, the comparison between twogenotypes in respect to per cent germination after sprayingwith various concentrations of MH at 40 and 50 DASrevealed the genotypic differences at 0 to 65 (DAH) (Table1 and 2). The genotype Vaibhav recorded the lowestgermination percent during 0 to 65 days of testing than thegenotype Kopergaon-1. Among the two genotypes Vaibhavresponded well for induction of dormancy by MH spraythan Kopergaon-1 (as the dormancy was inducted up to 40days in Vaibhav, irrespective of concentrations). Thegenotype Kopergaon-1 didn’t respond well for dormancyinduction by MH spray (as the dormancy induced was upto 35 days). After 35 days dormancy was broken and thegermination percent recorded after 35 days was above theIndian Minimum Seed Certification Standards. In general,foliar application of MH at different concentrations reducedthe germination of seeds as compared to control. Sprayingof MH at 1000 ppm was the most effective treatment interms of inducing dormancy as the treated seeds recordedlower gerrmination which might be due to lethal inhibitoryeffect of MH. The genotypes were of non-dormant type asrevealed by the germination of control seeds at 0-65 DAHrespectively. The genotype Vaibhav sprayed with MH at1000 ppm had the minimum germination percentage duringall the periods of testing than the genotype Kopergaon-1stating that maximum dormancy was induced in Vaibhav at1000 ppm concentration of maleic hydrazide. The MHapplication on higher concentration at 40 and 50 DAS of

Short Communication


Table 1. Effect of maleic hydrazide spray on seed germination of green gram genotypes

Figures in parenthesis are arcsin transformed value

Table 2. Interaction of different concentration of malic hydrazide spray on green gram genotypes on seed germination (%)

Figures in parenthesis are arcsin transformed value; V1 is Vaibhav and V2 is Kopergaon; T1, T2, T3, T4 and T5 represents MH at 1000, 2000,3000, 4000 and 5000 ppm respectively

Treatment Seed germination (%)

Days after harvest 0 5 10 15 20 25 30 35 40 45 50 55 60 65

Control 84.00 (72.62)

86.00 (74.36)

87.83 (75.95)

89.00 (77.10)

89.50 (77.40)

90.50 (78.37)

91.5 (79.37)

94.00 (82.25)

95.66 (84.00)

95.00 (83.05)

93.83 (81.75)

93.50 (81.75)

92.50 (80.79)

92.83 (80.66)

1000 ppm MH 13.50 (19.35)

30.83 (33.48)

41.50 (41.07)

48.50 (46.09)

54.00 (49.86)

58.83 (53.39)

65.16 (57.89)

68.50 (60.24)

71.00 (62.28)

75.83 (66.04)

80.67 (69.84)

85.50 (73.75)

88.00 (76.17)

88.50 (76.83)

2000 ppm MH 25.00 (28.66)

38.00 (38.70)

48.50 (46.09)

59.00 (53.46)

65.17 (58.00)

70.17 (61.37)

71.50 (62.49)

75.00 (65.34)

80.00 (69.64)

83.17 (72.09)

87.00 (75.25)

88.83 (76.65)

91.00 (79.05)

92.00 (79.84)

3000 ppm MH 22.00 (26.31)

37.50 (37.84)

46.50 (44.66)

56.83 (51.84)

61.00 (54.90)

66.00 (58.56)

70.33 (61.55)

74.17 (64.64)

77.83 (67.61)

81.83 (70.74)

86.00 (74.25)

88.33 (76.13)

90.50 (78.61)

92.50 (80.08)

4000 ppm MH 19.33 (23.94)

36.17 (36.98)

43.00 (41.98)

54.67 (50.23)

58.00 (52.74)

64.50 (57.62)

68.00 (60.04)

72.33 (63.07)

76.50 (66.64)

80.33 (69.34)

84.83 (73.40)

87.83 (75.73)

90.17 (78.28)

92.17 (79.95)

5000 ppm MH 18.50 (23.32)

35.17 (36.14)

41.50 (41.73)

52.83 (48.97)

57.00 (52.02)

62.67 (56.23)

66.66 (58.94)

70.33 (61.55)

74.50 (64.78)

79.17 (68.45)

83.00 (71.89)

86.50 (74.63)

89.50 (77.52)

90.50 (78.37)

SEm (±) 0.05 0.08 0.06 0.07 0.04 0.10 0.07 0.08 0.10 0.13 0.16 0.17 0.18 0.37 CD (P=0.05) 0.15 0.25 0.18 0.20 0.12 0.29 0.21 0.22 0.31 0.39 0.48 0.49 0.55 1.10

Vaibhav 29.50 (32.25)

42.78 (41.08)

49.83 (45.33)

55.17 (50.75

60.17 (53.12)

64.83 (55.93)

67.56 (58.22)

69.06 (60.55)

75.33 (62.91)

80.83 (65.27)

85 (67.49)

88 (69.33)

89.17 (70.81)

91.06 (72.72)

Kopergaon-1 31.28 (33.58)

45.11 (42.56)

53.11 (47.31)

57.11 (51.98)

63.06 (54.28)

67.72 (57.12)

69.83 (59.08)

76.39 (61.60)

80.17 (64.25)

83.2 (66.31)

87.00 (68.92)

90 (71.66)

91.00. (72.33)

93.00 (73.37)

SEm (±) 0.03 0.05 0.04 0.04 0.02 0.06 0.04 0.04 0.06 0.08 0.09 0.1 0.11 0.21 CD (P=0.05) 0.08 0.14 0.1 0.12 0.07 0.17 0.12 0.13 0.18 0.22 0.27 0.28 0.32 0.63

Treatment Seed germination (%) Days after Harvest

0 5 10 15 20 25 30 35 40 45 50 55 60 65

V1 T1 83.00 (65.65)

85.00 (67.21)

87.00 (68.87)

88 (69.73)

89 (70.63)

90 (71.57)

91.00 (72.54)

93 (74.66)

95.33 (77.54)

95 (77.08)

93.66 (75.43)

92.33 (73.93)

91 (72.54)

92.66 (74.32)

V1 T2 12.00 (20.27)

28.66 (33.37)

40 (39.23)

47 (43.28)

53 (46.72)

57.66 (49.41

64.33 (53.33)

68 (55.55)

70 (56.79)

74.66 (59.78)

79.66 (63.20)

85 (67.21)

87 (68.87)

87 (68.93)

V1 T3 24.00 (29.33)

36.00 (36.87)

47 (43.28)

58 (49.60)

64 (53.13)

70 (56.79)

71 (57.42)

74 (59.34)

78 (62.03)

81.66 (64.65)

86 (68.03)

88.66 (70.33)

90 (71.57)

91.66 (73.26)

V1 T4 21.00 (27.27)

37.00 (37.46)

45 (42.13)

56 (48.45)

60 (50.77)

65 (53.73)

70 (56.79)

73.33 (58.91)

76.66 (61.12)

81 (64.16)

85.33 (67.78)

88.33 (70.03)

89.33 (70.63)

93 (74.66)

V1 T5 19.00 (25.84)

35.33 (36.47)

42 (40.40)

54 (47.29)

57 (49.02)

63 (52.54)

67 (54.94)

72 (58.05)

76 (60.67)

80 (63.43)

83.66 (66.16)

87.66 (69.44)

89 (70.63)

92 (73.57)

V1 T6 18.00 (25.10)

34.66 (36.07)

38 (38.06)

52 (46.15)

56 (48.45)

61.33 (51.55)

66 (54.33)

70 (56.79)

74 (59.34)

78.66 (62.49)

81.66 (64.65)

86 (68.03)

88.66 (70.34)

90 (71.57)

V2 T1 85.00 (67.21)

87.00 (68.87)

88.66 (70.33)

90 (71.57)

90 (71.57)

91 (72.54)

92 (73.57)

95 (77.08)

96 (78.46)

95 (77.08)

94 (75.82)

94.66 (76.66)

94 (75.82)

93 (74.66)

V2 T2 15.00 (22.79)

33.00 (35.06)

43 (40.98)

50 (45)

55 (47.87)

60 (50.77)

66 (54.33)

70 (56.17)

72 (58.05)

77 (61.34)

81.66 (64.65)

86 (68.03)

89 (70.63)

90 (71.57)

V2 T3 26.00 (30.66)

40.00 (39.23)

50 (45)

60 (50.77)

66.33 (54.53)

70.33 (57)

72 (58.05)

76 (60.57)

82 (64.90)

84.66 (66.95)

88 (69.73)

89 (70.63)

92 (73.57)

92.33 (73.93)

V2 T4 23.00 (28.66)

38.00 (38.06)

48 (43.85)

57.66 (49.41)

62 (51.94)

67 (54.94)

70.66 (57.21)

75.00 (60.00)

79 (62.73)

82.66 (65.40)

86.66 (68.59)

88.33 (70.03)

91.66 (73.23)

92 (73.57)

V2 T5 19.66 (26.32)

37.00 (37.46)

44 (41.55)

55.33 (48.06)

59 (50.18)

66 (54.33)

69 (56.17)

72.66 (58.48)

77 (61.34)

80.66 (63.92)

86 (68.03)

88 (69.73)

91.33 (72.88)

92.33 (73.93)

V2 T6 19.00 (25.84)

35.66 (36.67)

45 (42.13)

53.66 (47.10)

58 (49.60)

64 (53.13)

67.33 (55.14)

70.66 (57.21)

75 (60)

79.66 (63.20)

84.33 (66.69)

87 (68.87)

90.33 (71.89)

91 (72.54)

SEm (±) 0.070 0.117 0.086 0.096 0.058 0.140 0.102 0.107 0.148 0.185 0.226 0.234 0.260 0.523 CD (P=0.05) 0.21 0.34 0.26 0.29 0.17 0.42 0.30 0.32 0.44 0.55 0.67 0.70 0.77 1.55

Gadhave et al. : Effect of maleic hydrazide on inducing dormancy in green gram (Vigna radiata L.) 6 3

crop growth failed to induce dormancy as the lowerconcentration might have limited penetration andtranslocation of the chemical to the growing meristem.

Dormancy may block any of the sequential processinvolved in the germination. The earlier reports revealedthat the application of an gibberellic acid inhibitor like MHcould bring about certain changes in the physiological andbiochemical processed like alteration on promoter toinhibitor ratio, moisture content of the seed, waterabsorption capacity of the seeds, protein content and oilcontent of the seed these processed are responsible forseed dormancy by arresting the growth of the embryo.Another important conception is that dormant and nondormant state of the seed are dependent on relative level ofinhibitors and promoters present in the seed (Khan 1977).The non-dormant nature of bunch groundnut was due toincrease in the level of growth promoting auxin during theseed development and maturity (Sreeramulu and Rao 1971).Since MH is an auxin antagonist, the primary effect of MHon inducing dormancy seems to be through interference inthe tryptophan metabolism as the later is the precursor inthe synthesis of auxins (Karivaratharaju and Rao 1972).Besides this, MH is found to increase the content of anotheramino acid, hydroxyproline (Karivaratharaju and Rao 1972,Vaithialingum and Rao 1973) which inhibits auxin inducedcell elongation (Cleland 1963).

The introduction of anti auxins of the seed by meansof foliar application at the time of kernel development maysuppress the auxin formation and induce dormancy(Leopold 1984). Maleic hydrazide, a growth and respiratoryinhibitors, possesses the characteristics of antiauxin andhas been found to be capable of inducing dormancy byantagonizing with auxin in groundnut, potato, sugarbeet,carrot and rice by interfering in root growth and waterabsorption (Wittwar and Hansen 1951, Patterson et al. 1952,Krishnamurthy 1969). Maleic hydrazide application ononion plant prolongs its dormancy via its effect on thelevel of natural growth inhibitor and promoters in the bulbs(Abdel-Rahaman and Issenberg 1974).

The results obtained in present investigation are inconfirmation with the results reported by Jayadeva (2007)and Nautiyal (2004) in groundnut who reported that MHspray at 1000 ppm concentration induced dormancy muchbetter in non-dormant groundnut varieties. Gupta et al.(1985) stated that effect of MH in inducing dormancy ingroundnut varieties was increased with increasing theconcentration and reported MH sprayed at 20 x 103 ppmhad inducted more dormancy than 5 x 103, 10 x 103 and 15 x103 ppm. Randhawa and Nandpuri (1986) reported that MHspray at 1000ppm concentrations reduced the sproutingper cent in onion bulbs. Nagarjun et al. (1980) and Abrarand Jadhav (1991) reported that 250 ppm and 200 ppm,respectively could induce dormancy in bunch groundnutseeds for a period of 3-4 weeks.

It is observed that the foliar application of MH at1000 ppm at 40 and 50 days after sowing were most effectivein inducing dormancy upto 40 days. Thus, foliar applicationof MH can be successfully used as a source for inducingshort duration dormancy in mungbean to minimize yieldlosses due to in situ sprouting.

REFERENCES

Abdul-Rahman and Issenberg FMR. 1974. The role of exogenousplant growth regulators in the dormancy of onion bulbs. Journalof Agricultural Science 82: 113-116.

Abrar AK and Jadhav BB. 1991. Effect of growth regulator, chemicalsand temperature on dormancy in peanut. Annals of PlantPhysiology 5: 64-69.

Anonymous 1999. International Rules for seed Testing. Rules andAnnexes. Seed Science and Technology 13: 299-513.

Ashok Kumar TS. 1989. M.Sc. (Agri.) thesis, University ofAgricultural Sciences, Dharwad 188 pp.

Cleland R. 1963. Hydroxyproline as an inhibitor of auxin inducedcell elongation. Nature 200: 908-909.

Gupta RK, Singh SS and Verma MM. 1985. Introduction of dormancyin groundnut (Arachis hypogeal L.) variety T-64 by maleichydrazide. Indian Journal Agriculture Research 19: 82-86.

Jayadeva B. 2007. Induction of dormancy in summer groundnut(Arachis hypogaea. L). M.Sc. (Agri.) Thesis, University ofMahatma Phule Krishi Vidyapeeth, Rahuri.

Karivaratharaju TV and Rao JS. 1972. Effect of Maleic hydrazideon inducing dormancy in rice. Madras Agricultural Journal 59:257-261.

Khan A. 1977. The physiology and biochemical of seed germination.North-Holland Pub.co. Amersterdom Pp 26.

Krishnamurthy K. 1969. Induction of dormancy in groundnut bypre harvest foliar application of Maleic hydrazide. Indian Journalof Agricultural Sciences 37: 33-36.

Leopold AC. 1984. Maleic hydrazide as antiauxin in plants. PlantScience 114: 9-10.

Nagarjun P, Radder GD and Patil VS. 1980. Effect of foliar applicationof maleic hydrazide on seed quality and seedling vigour in bunchgroundnut. Seed Reserch 8: 121-126.

Nautiyal PC. 2004. Issues related to maintenance of seed viabilityand regulation of dormancy in groundnut. Groundnut Researchin India Pp 321-338.

Paterson DR,Witrwer SH, Willer LF and Sell HM. 1952. The effectof pre-harvest foliar spray of maleic hydrazide on sproutsinhibition and storage quality of potatoes. Plant Physiology 27:135-142.

Randhawa KS and Nandpuri KS. 1986. Effect of plant growthregulators on sprouting of onions under ordinary storageconditions. Indian Journal of Agronomy 11: 238-242.

Sreeramulu N and Rao IM. 1971. Physiological studies on dormancyin seeds of groundnut. Australian Journal of Botany 19: 273-280.

Vaithialingam R and Rao JS. 1973. Effect of MH 30 on the totalamino acids in non-dormant groundnut. Madras AgriculturalJournal 60: 1864-1865.

Wittwer SH and Hansen CM. 1951. The reduction of storage lossesin sugarbeets by pre-harvest foliar sprays of maleic hydrazide.Agronomy Journal 43: 340-341.


Characterization of cowpea [Vigna unguiculata (L.) Walp.] germplasmS ANISH, R USHA KUMARI and C PARAMESWARI

Agriculture College and Research Institute, Madurai, India; E-mail: [email protected](Received: October 25, 2016; Accepted: January 10, 2017)

Short Communication

ABSTRACT

Cowpea is one of the rarely utilized pulses with adequeteprotein content and good fodder value. In the present study,various species of cowpea are evaluated and characterizedfor advancing the germplasm to further breedingprogrammes. Genotypic coefficient of variation, heritabilityand genetic advance were assessed for 50 genotypes of cowpeawhich included Vigna unguiculata, Vigna catjang and Vignasesquipedalis. Genotypes differed significantly for allcharacters studied. High heritability coupled with highgenetic advance was observed for plant height, pod length,peduncle length, number of pods per plant and number ofbranches per plant. Number of cluster per plant had highlysignificant positive correlation with number of pods per plant.Days to 50% flowering significantly but negatively associatedwith peduncle length. Number of branches per plant showedsignificant positive correlation with number of cluster perplant. Number of seeds per pod exhibited significant positivecorrelation with 100 seed weight. Grain yield per plantexhibited significant positive correlation with number ofclusters per plant and number of pods per plant. The studyshowed that number of seeds per pod was the reliable foreffective selection in cowpea.

Key words: Correlation, Heritability, Path coefficient

Cowpea [Vigna unguiculata (L.) Walp] is an importantleguminous vegetable crop mainly grown both in kharifand spring/summer seasons in most parts of India. Cowpeaseeds are good source of protein (24.8%), fat (1.9%),carbohydrate (63.6%), Vitamin A (0.00074 mg), Thiamine(0.00014 mg), Riboflavin (0.00042 mg) and Niacin (0.00281mg). The present study was taken up to understand thevariability, heritability estimates, expected genetic advanceand correlation coefficients. Yield is a complex entity and isassociated with a number of component traits. Thesecharacters are themselves interrelated. Such ainterdependence of the contributory factors often affecttheir direct relationship with yield thereby makingcorrelation coefficient unreliable as selection indices .It ishowever, desirable to know the degree to which differentcomponent characters are correlated among themselves aswell as with the both at genotypic and phenotypic levels.The present investigation was therefore, undertaken todetermine correlation coefficients both at genotypic andphenotypic levels in cowpea.

Fifty cowpea genotypes were grown in RBD with 2replications in 2014. Observations were recorded on fiverandom plants for days to 50% flowering, plant height,number of branches per plant, peduncle length, number ofclusters per plant, number of pods per plant, number ofseeds per pod, pod length, grain yield per plant and 100-seed weight. The data were subjected to statistical analysisand the various genetic parameters such as PCV, GCV,heritability and genetic advance were worked out usingappropriate formula (Singh and Chaudhary 1977 andJohnson et al. 1955). The plot means were used for statisticalanalysis (Panse and Sukhatme 1967). The phenotypic andgenotypic correlations were calculated according toformulae suggested by Al-Jibouri et al. (1958) and Singhand Choudhari (1977).

The performance of 50 genotypes for 10 characterswith the estimate of phenotypic and genotypic correlationco-efficients (Table 1) reveled high GCV for pod length(37.72 %) followed by peduncle length (32.78 %), grain yieldper plant ( 25.72 %), plant height (23.51%), number of podsper plant (20.55 %), number of branches per plant (17.32%), 100 seed weight (13.09 %), days to 50% flowering(9.54%), number of seeds per pod (9.16 %) and number ofcluster per plant (7.19 %).

Heritability was high for 100-seed weight (96.49%)followed by peduncle length (93.95 %), pod length (93.33%),days to 50% flowering (93.27%), plant height (93.11%), grainyield per plant (87.85%), number of pods per plant (77.34%),number of branches per plant (66.78%), number of seedsper pod (44.62%) and number of clusters per plant (26.55%).High heritability coupled with high genetic advance wasobserved for 100 seed weight (96.49 and 26.51%), pedunclelength (93.95 and 65.45%), pod length (93.33 and 75.08%),plant height (93.11 and 46.73 %), grain yield per plant (87.85and 49.66%), number of pods per plant (77.34 and 37.24%)and number of branches per plant (66.78 and 29.16%).

The genotypic correlation coefficients were workedout for all the characters (Table 2). In general genotypiccorrelation coefficients were higher in magnitude over therespective phenotypic correlation coefficients except forfew pairs of characters. Number of cluster per plant hadhighly significant positive correlation with number of podsper plant. Number of cluster per plant showed significantpositive correlation with pod length. Similiarly, number of

Anish et al. : Characterization of cowpea (Vigna unguiculata (L.) Walp.) germplasm 6 5

branches per plant exhibited strong positive correlationwith number of clusters per plant. Peduncle length showedpositive correlation with pod length. Number of seeds perpod exhibited positive correlation with 100 seed weight.Days to 50% flowering was highly significant but negativelycorrelated with peduncle length, pod length and 100 seedweight. Analogous results are reported by Venkatesanet al. (2003) for plant height and number of branches perplant.

REFERENCES

Al-Jibouri HA, Miller HA and Robinson HF. 1958. Genetic andenvironmental variances and co-variances in an upland cottoncross of inter-specific origin. Agronomy Journal 50: 633-636.

Johonson HW, Robinson HF and Comstock RE. 1955. Estimationof genetic and environmental variability in soybeans. AgronomyJournal 47: 314-318.

Panse VG and Sukhatm PV. 1967. Statistical Methods for AgriculturalWorkers Indian Council of Agricultural Research, New Delhi.

Singh RK and Chaudhary BD. 1977. Biometrical methods inquantitative genetic analysis, Kalyani Publishers, New Delhi.

Venkatesan M, Prakash M and Ganesan H. 2003. Genetic variability,heritability and genetic advances analyses in cowpea [Vignaunguiculata (L.) Walp]. Legume Research 26(2): 155-156.

G = Genotypic, P = Phenotypic*Significant at 5% level, **Significant at 1% level

Table 1. Variability, heritability and genetic advance in 50 accessions of cowpea

Table 2. Genotypic and phenotypic correlation coefficients between different traits

Character Mean Range PCV(%) GCV(%) Heritability (%) GA % of mean Days to 50 per cent flowering 40.77 35-53 9.89 9.54 93.27 18.99 Plant height (cm) 41.41 19-67.30 24.37 23.51 93.11 46.73 Number of branches per plant 5.44 3-7 21.19 17.32 66.78 29.16 Peduncle length (cm) 19.47 6.80-36.50 33.82 32.78 93.95 65.45 Number of clusters per plant 8.28 5.0-10.0 13.97 7.19 26.55 7.64 Number of pods per plant 15.05 9.70-24.50 23.37 20.55 77.34 37.24 Pod length (cm) 17.07 7.20-37.50 39.05 37.72 93.33 75.08 Number of seeds per pod 12.04 6.80-15.90 13.72 9.16 44.62 12.61 100-seed weight 10.99 7.30-13.30 13.34 13.09 96.49 26.51 Grain yield per plant (g) 16.50 8.20-29.00 27.44 25.72 87.85 49.66

Character Days to 50 per cent

flowering

Plant height (cm)

Number of branches per

plant

Peduncle length (cm)

Number of clusters

per plant

Number of pods per

plant

Pod length (cm)

Number of seeds per

pod

100-seed weight

(g)

Grain yield per plant (g)

Days to 50 per cent flowering

G -0.083 0.017 -0.408** -0.113 -0.142 -0.268* -0.193 -0.260* -0.066

P -0.071 -0.022 -0.384 -0.030 -0.120 -0.258 -0.095 -0.252 -0.063

Plant height (cm) G -0.018 -0.005 0.082 0.057 -0.021 -0.185 0.123 0.110

P -0.026 -0.011 0.014 0.058 -0.016 -0.100 0.109 0.111

Number of branches per plant

G -0.068 0.248* -0.094 -0.047 -0.181 0.203 -0.162

P -0.033 0.083 -0.093 -0.022 -0.135 0.166 -0.171

Peduncle length (cm) G 0.143 0.187 0.252* -0.012 -0.091 0.273*

P 0.112 0.135 0.243 0.037 -0.080 0.254

Number of clusters per plant

G 0.407** 0.354** -0.263* -0.057 0.490**

P 0.096 0.190 -0.006 -0.015 0.208

Number of pods per plant G 0.146 0.164 0.085 0.659**

P 0.116 -0.002 0.072 0.524

Pod length (cm) G -0.284 0.066 0.247*

P -0.175 0.073 0.213

Number of seeds per pod G 0.244* 0.400**

P 0.154 0.330

100-seed weight (g) G 0.054

P 0.049


Stability analysis for seed yield in blackgram (Vigna mungo L. Hepper)G VIJAY KUMAR1, M VANAJA1, P VAGHEERA1, P SATHISH1, K PREMKUMAR2, B SARKAR1 andM MAHESWARI1

1Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad-500059, India; 2Osmania University,Hyderabad, India; E-mail: [email protected](Received: August 20, 2016; Accepted: December 12, 2016)

ABSTRACT

Stability analysis was carried out for seed yield over threedifferent seasons using 42 F1 hybrids obtained by line × testermating design with 14 lines and three testers of blackgramgenotypes. The analysis of variance revealed that the meansum of square was significant for seed yield due to varieties,environments (linear) and varieties × environmentsindicating that variability was present among the genotypes.Out of 42, five hybrids viz., IC 587753 × PU 19, IC 587753 ×LBG 20, IC 436720 × PU 19, IC 519805 × PU 19 and IC 587752× T 9 proved the best over three environments for seed yield.Environment 1 (kharif) was the most favourable for the betterexpression of seed yield.

Key words: Blackgram, Regression coefficient, Stabilityanalysis

Blackgram an important short duration crop,originated in India with a secondary centre of origin incentral Asia (Pratap and Kumar 2011). India is the largestproducer and consumer of black gram in the world. Themajor blackgram growing states of the country areMaharashtra, Andhra Pradesh, Telangana, Rajasthan,Odisha and Tamilnadu. The seeds of blackgram is anexcellent source of easily digestible good quality protein.It contains 26% protein, 59.6% carbohydrates, 1.4% fats,0.9% fibre, 3.2% minerals and small amount of vitamin B-complex (Srivastava et al. 2001).

Stability analysis has become one of the importanttools for plant breeders in predicting the response ofgenotypes over changing environments. The interactionof genotype with environment has an important bearing inbreeding improved varieties. Genotype × Environment(G × E) interaction has a masking effect on the performanceof a genotype and hence the relative ranking of thegenotypes do not remain the same over differentenvironments. Adaptability of genotypes to environmentalfluctuation is important for the stable crop production overthe environments. It is imperative to have cultivars withstable performance across environment to realize higherseed yield. The genotypes with high mean (x), regressioncoefficient (bi) close to unity and less/no deviation fromregression (S2di) are said to be stable. The present study

was aimed at screening of F1 hybrids for stable seed yieldover three different environments.

The research work was carried out with fourteenblackgram accessions viz., IC 587753, IC 436720, IC 436519,IC 343947, IC 519805, IC 343952, IC 587752, IC 587751,IC 282009, IC 436753, IC 436610, IC 398971, IC 281987 andIC 436652 obtained from NBPGR Regional Centre,Hyderabad. These accessions were originally collected fromdifferent agro-climatic zones of Telangana and AndhraPradesh and used in the crossing program. Three nationallyreleased varieties viz., PU 19, LBG 20 and T 9 were used astesters. 42 crosses were made in line × tester mode withfourteen lines and three testers. Each treatment wasrepresented by a row of 1m length (10 plants per replication)with spacing of 30 x10 cm during Kharif 2013 (environment1), Rabi 2013 (environment 2) and Summer 2014(environment 3). The experiment was laid out in RBD with 3replications. The recommended packages of practices werefollowed to establish successful crop stand. The crop wasgrown in three seasons with varying temperature, humidityand photoperiod in order to assess stability of the hybridsfor seed yield under different environments. The cropexperienced 19.0°C minimum and 38.6oC maximumtemperature, 555.4 mm rainfall for kharif, 8.4°C to 32.0°Ctemperature and 317 mm rainfall rabi, 15.7°C to 41.7°Ctemperature and 109.7 mm rainfall summer season. Thecrop was harvested at the time of physiological maturityand yield data was recorded. Stability analysis was doneas per Eberhart and Russell model (1966). A genotype withhigh mean, unit regression coefficient (bi=1) and the leastdeviation from regression (S2di=0) is considered as ideal,widely adaptable and stable genotype.

Analysis of variance for stability (Table 1) revealedsignificant mean sum of squares due to genotypes,environment + (genotype x environment), environmentlinear, genotype x environment (linear) and pooled deviationwhen tested against pooled error. When tested againstpooled deviations, genotypes, environment linear,environment + (genotype x environment) was significantfor seeds per plant indicating that performance of some ofthe genotypes was not stable over environments. Manyearlier researchers reported the similar results for seed yield

Short Communcation

Kumar et al. : Stability analysis for seed yield in F1s of blackgram (Vigna mungo L. Hepper) 6 7

suitable in favorable environments with unpredictableperformance as their higher mean values with non-significant regression coefficient values were more thanunity and had highly significant deviation from regression.Five hybrids viz., IC 587753 × T 9, IC 436519 × PU 19, IC587752 × PU 19, IC 398971 × LBG-20, IC 281987 × T 9 wereunstable as deviation from regression was significant forseed yield.

It is concluded that out of 42 crosses, five hybridsviz., IC 587753 × PU 19, IC 587753 × LBG 20, IC 436720 × PU19, IC 519805 × PU 19 and IC 587752 × T 9 showed higherseed yield as well as wider adaptability across the

Table 1. Analysis of variance for stability performance forseed yield in Blackgram

*Significant at 5% level, **Significant at 1% level

df Seed Yield (g/pl) Rep within Env. 6 4.1 Varieties 58 6.83** Env.+ (Var.× Env.) 118 4.81* Environments 2 80.87** Var.× Env. 116 3.5 Environments (Lin.) 1 161.74** Var. × Env.(Lin.) 58 3.99 Pooled Deviation 59 2.97** Pooled Error 348 0.9 Total 176 5.48

Table 2. Environmental indices for quantitative charactersin Blackgram


Environments Seed yield Env.1 (kharif) 1.32 Env.2 (rabi) -0.39 Env.3 (summer) -0.93

Table 3. Mean seed yield, regression coefficient (bi) anddeviation from regression (S2di) of blackgramgenotypes in three different environments

in blackgram (Natarajan 2001, Shanthi et al. 2007, Revanappaet al. 2012, Senthil and Chinna 2012) in greengram byManivannan et al. (1998), Patela et al. (2009),Abeytilakarathna (2010) and Nath (2012).

Environmental indices for the three environmentswere calculated for seed yield. The seed yield ranged from-0.93 (environment 3) to 1.32 (environment 1). Among thethree environments studied, environment 1 (kharif) hadfavorable effect on seed yield (Table 2).

The range of seed yield was from 345.5 kg/ha (IC436610 × PU 19) to 601.0 kg/ha (IC 587753 × PU 19). All thehybrids except three hybrids (IC 343967 × LBG 20, IC 282009× LBG 20 and IC 282009 × T 9) recorded non-significantregression coefficient for seed yield per plant. Among 42hybrids, IC 587753 × PU 19 (601.0 kg/ha), IC 587753 × LBG20 (559.0 kg/ha), IC 436720 × PU 19 (549.9 kg/ha), IC 281987× PU 19 (520.5 kg/ha), IC 436652 × LBG 20 (509.3 kg/ha), IC436519 × T 9 (498.8 kg/ha), IC 519805 × PU 19 (496.0 kg/ha),IC 282009 × PU 19 (489.0 kg/ha), IC 587753 × T 9 (480.9 kg/ha) and IC 587752 × T 9 (480.6 kg/ha) were the top tenhybrids for seed yield (Table 3). Out of these, five hybridsIC 587753 × PU 19, IC 587753 × LBG 20, IC 436720 × PU 19,IC 519805 × PU 19 and IC 587752 × T 9 were stable due totheir non significant regression coefficient and deviationfrom regression indicating their wider adaptability acrossthe environments. Rao and Suryawanshi (1988) suggestedthat elite genotype in any practical situation was one withhigh mean performance, desired linear response and low-linear sensitivity (S2di). Revanappa et al. (2012) alsoreported the stable genotypes over environments inblackgram. Two hybrids (IC 436720 × T 9 with 12.13 g/pland IC 436652 × T 9 with 12.59 g/pl) were identified asmedium yielders but stable over three environments forseed yield. Six hybrids viz., IC 436519 × T 9, IC 282009 × PU19, IC 398971 × PU 19, IC 398971 × T 9, IC 281987 × PU 19and IC 436652 × LBG 20 were identified as high yielders and


Hybrid Seed yield Regression coefficient

Deviation from

regression g/pl kg/ha bi S2di

IC 587753 × PU 19 17.17 601.0 2.82 -0.57 IC 587753 × LBG 20 15.97 559.0 3.5 0.12 IC 587753 × T 9 13.74 480.9 -0.05 2.8 * IC 436720 × PU 19 15.71 549.9 3.02 -0.69 IC 436720 × LBG 20 12.12 424.2 1.66 -0.21 IC 436720 × T 9 12.13 424.6 0.7 1.5 IC 436519 × PU 19 12.92 452.2 0.9 9.64 ** IC 436519 × LBG 20 11.93 417.6 2 -0.61 IC 436519 × T 9 14.25 498.8 2.57 15.5 ** IC 343947 × PU 19 13.54 473.9 -0.59 2.28 IC 343947 × LBG 20 12.52 438.2 2.73 0.09 IC 343947 × T 9 14.39 503.7 0.37 2.14 IC 519805 × PU 19 14.17 496.0 0.48 -0.15 IC 519805 × LBG 20 13.52 473.2 1.51 0 IC 519805 × T 9 13.29 465.2 -0.45 0.47 IC 343967 × PU 19 11.32 396.2 0.14 0.6 IC 343967 × LBG 20 11.42 399.7 1.69* -0.95 IC 343967 × T 9 12.35 432.3 -0.76 -0.69 IC587752 × PU 19 11.09 388.2 -1.76 5.35 * IC 587752 × LBG 20 12.87 450.5 -0.57 -0.59 IC 587752 × T 9 13.73 480.6 0 2.62 IC 587751 × PU 19 11.85 414.8 1.2 -0.83 IC 587751 × LBG 20 13.68 478.8 1.14 0.68 IC 587751 × T 9 10.42 364.7 0.07 -0.59 IC 282009 × PU 19 13.97 489.0 1.68 17.84 ** IC 282009 × LBG 20 11.78 412.3 2.22* -0.93 IC 282009 × T 9 11.74 410.9 0.69** -0.95 IC 436753 × PU 19 11.66 408.1 1.56 1.34 IC 436753 × LBG 20 12.22 427.7 2.09 -0.57 IC 436753 × T 9 13.10 458.5 -0.46 0.79 IC 436610 × PU 19 9.87 345.5 -0.2 1.26 IC 436610 × LBG 20 11.72 410.2 0.09 2.2 IC 436610 × T 9 12.79 447.7 -0.36 2.05 IC 398971 × PU 19 13.20 462.0 1.18 12.68 ** IC 398971 × LBG 20 12.21 427.4 -0.05 4.23 * IC 398971 × T 9 13.65 477.8 1.61 12.81 ** IC 281987 × PU 19 14.87 520.5 2.63 5.55 ** IC 281987 × LBG 20 13.47 471.5 3.05 0.2 IC 281987 × T 9 11.74 410.9 -2.48 10.25 ** IC 436652 × PU 19 11.18 391.3 2.33 -0.88 IC 436652 × LBG 20 14.55 509.3 1.88 6.59 ** IC 436652 × T 9 12.59 440.7 0.92 -0.92


environments. Hence, the above hybrids may be used inimprovement of seed yield in blackgram.

REFERENCES

Eberhart SA and Russell WA. 1966. Stability parameters forcomparing varieties. Crop Science 6: 36-40.

Manivannan N, Sethuraman K and Natarajan S. 2002. Studies onstability for seed for yield in urdbean. Legume Research 25(2):147-148.

Natarajan C. 2001. Stability of yield and its components in blackgram. Madras Agricultural Journal 88(7-9): 409-413.

Nath A. 2012. Stability analysis in Mungbean.Thesis. Mahatma PhuleKrishi Vidyapeeth (MPKV), Rahuri, Maharashtra, India.

Patela JD, Naika MR, Chaudhari SB, Vaghelaa KO and KodappullyVC. 2009. Stability analysis for seed yield in greengram [Vignaradiata (L.) Wilczek]. Agricultral Science Digest 29: 24-27.

Pratap A and Kumar J. 2011. History, origin and evolution. In:Pratap A and Kumar J. (eds.) Biology and Breeding of food

legumes, CAB International, Oxfordshire, United Kingdom7 pp.

Rao SK and Suryawanshi. 1988. Genotype x Environment interactionin the genetic diversity of urdbean germplasm collections. LegumeResearch 11: 15-20.

Revanappa SB, Kamannavar PY, Vijaykumar AG, Ganajaxi M,Gajanan DK, Arunkumar B and Salimath PM. 2012. Genotype xenvironment interaction and stability analysis for grain yield inblackgram (Vigna mungo L.). Legume Research 35(1): 56-58.

Senthil Kumar N and Chinna Ghouse Peera SK. 2012. Stability forseed yield in black gram (Vigna mungo L. Hepper). InternationalJournal of Recent Scientific Research 3(5): 336-339.

Shanthi P, Jebaraj S and Murugan E. 2007. Stability analysis inblackgram [Vigna mungo (L.) Hepper]. Legume Research 30(2):154-156.

Srivastava GC, Pal M, Das M and Sengupta UK. 2001. Growth, CO2exchange rate and dry matter partitioning in mungbean (Vignaradiata L.) grown under elevated CO2. Indian Journal ofExperimental Botany 39: 572-577.

6 9

List of Refrees for Vol. 30(1)

The Editorial Board gratefully acknowledges the help rendered by following referees in reviewing manuscripts for theVol. 30 (1), 2017.

Journal of Food Legumes 30(1): 69, 2017

Dr. Guriqbal Singh, TAU, Ludhiana

Dr. R.N. Sharma, IGKVV, Raipur

Dr. Inderjit Singh, PAU, Ludhiana

Dr. C.S. Praharaj, ICAR-IIPR, Kanpur

Dr. J. Souframanian, BARC

Dr. P.S. Basu, ICAR-IIPR, Kanpur

Dr. M.S. Vnkatesh, ICAR-IIPR RRC, Dharwad

Dr. Purushottam, ICAR-IIPR, Kanpur

Dr. R.K. Mishra, ICAR-IIPR, Kanpur

Dr. Sujayanand GK, ICAR-IIPR, Kanpur

Dr. Jitendra Kumar, ICAR-IIPR, Kanpur

Dr. Mohd. Akram, ICAR-IIPR, Kanpur

Dr. Alok Das, ICAR-IIPR, Kanpur

Dr. Hemant Kumar, ICAR-IIPR, Kanpur

Dr. Amrit Lamichaney, ICAR-IIPR, Kanpur

Dr. Debjyoti Sen Gupta, ICAR-IIPR, Kanpur

Journal of Food Legumes (formerly Indian Journal of PulsesResearch) publishes original papers, short communicationsand review articles by renowned scientists, covering all areasof food legumes research. The paper should not have beenpublished or communicated elsewhere. Authors will be solelyresponsible for the factual accuracy of their contribution.Language of publication is English (British).Please send your manuscript to following address:SecretaryISPRDIndian Institute of Pulses ResearchKalyanpur, Kanpur 208 024, IndiaEmail: [email protected] must be submitted through e-mail. You shouldalso submit a hard copy of your manuscript for our officialrecord. Besides author(s) is required to submit a certificatethat the paper is exclusive for Journal of Food Legumes.Manuscripts must conform to the Journal style (see the latestissue). Correct language is the responsibility of the author.After having received your contribution (date of submission),there will be a review process before the editorial board takesdecision regarding acceptance for publication. One copy ofthe revision together with the original manuscript must bereturned to the subject editor or Secretary. The submittedpaper must be one complete word document file comprising atitle page, abstract, text, references, tables, figure legends andfigures. When preparing your text file, please use only TimesNew Roman for text (12 point, double spacing) and Symbolfont for Greek letters to avoid inadvertent charactersubstitutions.FormatEvery original paper should be divided into the following fivesections: ABSTRACT, Key words, INTRODUCTION,MATERIALS AND METHODS, RESULTS ANDDISCUSSION, and REFERENCES. The manuscript should betyped on one side of the paper only, double spaced, and with4-cm margins with page and line numbers. The main title mustbe capital bold. Subheading must be bold italic and Sub-subheading normal italic.At the head of the manuscript, the following informationshould be given: the title of the paper, the name(s) of theauthor(s), the institute where the research was carried out,the present addresses of the authors (foot note) and of thecorresponding author (if different from above Institute).Authors are required to provide running title of the paper.You must supply an E-mail address for the correspondingauthor.The abstract should contain at least one sentence on each ofthe following: objective of investigation (hypothesis, purpose,aim), experimental material, method of investigation, datacollection, result and conclusions. Maximum length of abstractis 175 words. Up to 10 key words should be added at the endof the abstract and separated by comma. Key words must bearranged alphabatically (e.g., EMS, Gamma ray, Mungbean,Mutations, Path coefficient, ......).Each figure, table, and bibliographic entry must have areference in the text. Any correction requested by the reviewershould also be integrated into the file.Manuscript file including tables must be in MS Word andWindows-compatible and must not contain any files otherthan those for the current manuscript. Please do not importthe figures into the text file. The text should be prepared usingstandard software (Microsoft Word); do not use automatedor manual hyphenation.

Length

Manuscripts should not exceed a final length of 15 printedpages, i.e., 5,000 words, including spaces required for figures,tables and list of references. Manuscripts for shortcommunications should not exceed 3000 words (3 printedpages, with not more than a total of 2 figures or tables).

Units, abbreviations and nomenclature

For physical units, unit names and symbols, the SI-systemshould be employed. Biological names should be givenaccording to the latest international nomenclature. Botanicaland zoological names, gene designations and gene symbolsare italicised. Yield data should be reported in kg/ha. The nameof varieties or genotypes must start and end with singleinverted comma (e.g., ‘Priya’, ‘IPA 204’, ......).

Tables and Figures

Tables and figures should be limited to the necessary minimum.Please submit reproducible artwork. For printing of colouredphotograph, authors will be charged Rs. 4000/- perphotograph. It is essential that figures are submitted as high-resolution scans.

ReferencesThe list of references should only include publications citedin the text. They should be cited in alphabetical order underthe first author’s name, listing all authors, the year ofpublication and the complete title, according to the followingexamples:Becker HC, Lin SC and Leon J. 1988. Stability analysis in plantbreeding. Plant Breeding 101: 1-23.Sokal RR and Rholf FJ. 1981. Biometry, 2nd Ed. Freeman, SanFrancisco.Tandon HLS. 1993. Methods of Analysis of Soils, Plants, Waterand Fertilizers (ed). Fertilizer Development and ConsultationOrganization, New Delhi, India. 143 pp.Singh DP. 1989. Mutation breeding in blackgram. In: SA Farookand IA Khan (Eds), Breeding Food Legumes. PremierPublishing House, Hyderabad, India. Pp 103-109.Takkar PN and Randhawa NS. 1980. Zinc deficiency in Indiansoils and plants. In: Proceedings of Seminar on Zinc Wastesand their Utilization, 15-16 October 1980, Indian Lead-ZincInformation Centre, Fertilizer Association of India, New Delhi,India. Pp 13-15.Satyanarayan Y. 1953. Photosociological studies on calcariousplants of Bombay. Ph.D. Thesis, Bombay University, Mumbai,India.In the text, the bibliographical reference is made by giving thename of the author(s) with the year of publication. If there aretwo references, then it should be separated by placing ‘comma’(e.g., Becker et al. 1988, Tandon 1993). If references are of thesame year, arrange them in alphabatic order, otherwise arrangethem in ascending order of the years.While preparing manuscripts, authors are requested to gothrough the latest issue of the journal. Authors are alsorequired to send the names & E-mail address of at least 3-4reviewers appropriate to their articles.

Instructions to Authors

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