Abstract
Plant breeding aims to create new varieties that outperform the parents by combining valuable traits. The breeding cycle of selection–recombination–selection–testing requires resources, time, and experience to deliver improved varieties with appropriate phenology, efficient plant type, higher yield, and better nutritional quality. Pulse breeders have used classical plant breeding methods with modest success, in terms of crop duration, grain yield, and disease resistance, to develop more than 3700 improved varieties of different pulse crops globally. However, these efforts have not achieved the large genetic gains needed to close the gap between demand and supply. Studies have identified a narrow genetic base and high proportion of variance due to environment (E) and genotype × environment (GE) interactions in the total phenotypic variance of pulse crops in multilocation environment trials (MET) as significant factors for reduced selection efficiency, as well as the lengthy breeding cycle. This chapter reviews the present status of pulse crops, production trends, past breeding progress, and the means to accelerate genetic gain. The application of modern tools and techniques of phenotyping, genotyping, experimental design, data management, statistical analysis, and digitalization and mechanization of breeding and testing pipelines is the way forward for accelerating genetic gains in pulse crops to meet the future demands of the increasing population.
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References
Abate T, Shiferaw B, Gebeyehu S, Fenta BA, Negash K, Assefa A, Eshete M, Aliye S, Hagmann J (2011) A systems and partnership approach to agricultural research for development: lessons from Ethiopia. Outlook Agric 40:213–220
Amian AA, Papenbrock J, Jacobsen HJ, Hassan F (2011) Enhancing transgenic pea (Pisum sativum) resistance against fungal diseases through stacking of two antifungal genes (Chitinase and Glucanase). GM Crops 2:104–109
Aragão FJL, Barros LMG, de Sousa MV, Grossi de Sá MF, Almeida ERP, Gander ES, Rech EL (1999) Expression of a methionine-rich storage albumin from the Brazil nut (Bertholletiaexcelsa) in transgenic bean plants (Phaseolus vulgaris L). Genet Mol Biol 22:445–449
Araus JL, Cairns JE (2014) Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci 19:52–61
Arief VN, DeLacy IH, Crossa J, Payne T, Singh R, Braun HJ et al (2015) Evaluating testing strategies for plant breeding field trials: redesigning a CIMMYT international wheat nursery to provide extra genotype connection across cycles. Crop Sci 55:164–177
Arief VN, Desmae H, Hardner C, DeLacy IH, Gilmour A, Bull JK, Basford KE (2019) Utilization of multiyear plant breeding data to better predict genotype performance. Crop Sci 59:1–11
Atkin GN, Frey KJ (1990) Selecting oat lines for yield in low productivity environments. Crop Sci 30:556–561
Baenziger PS, Peterson CJ (1992) Genetic variation: its origin and use for breeding self-pollinated species. In: Stalker TM, Murphy JP (eds) Plant breeding in the 1990s, Raleigh, CAB International, pp 69–92
Becker HH (1995) On the importance of soil homogeneity when evaluating field trials. J Agron Crop Sci 174:33–40
Belete T, Mekbib F, Eshete M (2017) Assessment of genetic improvement in grain yield potential and related traits of kabuli type chickpea varieties in Ethiopia (1974–2009). Adv Crop Sci Tech 5:3. https://doi.org/10.4172/2329-8863.1000284
Bernardo R (2008) Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Sci 48:1649–1664
Bernardo R (2010) Breeding for quantitative traits in plants. Stemma Press, Woodbury
Bernardo R, Yu J (2007) Prospects for genome-wide selection for quantitative traits in maize. Crop Sci 47:1082–1090
Bhatnagar-Mathur P, Shridhar Rao J, Vadez V, Sharma KK (2009) Transgenic strategies for improved drought tolerance in legumes of semi-arid tropics. J Crop Improv 24:92–111
Blary A, Jenczewski E (2019) Manipulation of crossover frequency and distribution for plant breeding. Theor Appl Genet 132:575–592
Blümmel M, Ratnakumar P, Vadez V (2012) Opportunities for exploring variations in haulm fodder traits of intermittent drought tolerant lines in a reference collection of groundnut (Arachis hypogea L). Field Crops Res 126:200–206
Bogale DA, Mekibib F, Fikre A (2015) Genetic improvement of lentil (Lens culinaris Medikus) between 1980 and 2010 in Ethiopia. Malays J Med Biol Res 2:284–297
Boote K, Jones J, Pickering N (1996) Potential uses and limitations of crop models. Agron J 88:704–716
Borges A, González-Reymundez A, Ernst O, Cadenazzi M, Terra J, Gutiérrez L (2019) Can spatial modeling substitute experimental design in agricultural experiments? Crop Sci 59:44–53
Bos I (1983) Optimum number of replications when testing lines or families on a fixed number of plots. Euphytica 32:311–318
Brennan JP, Martin PJ (2007) Returns to investment in new breeding technologies. Euphytica 157:337–349
Brown AHD (1989) Core collections: a practical approach to genetic resources management. Genome 31:818–824
Brumlop S, Finckh MR (2011) Applications and potentials of marker assisted selection (MAS) in plant breeding. Federal Agency for Nature Conservation, Bonn
Chadha ML (2010) Short duration mungbean: a new success in South Asia. APAARI, Bangkok, Thailand, 45 p
Challinor AJ, Watson J, Lobell DB, Howden SM, Smith DR, Chhetri N (2014) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Chang 4(4):287
Champ MM (2002) Pulses and human health. Brit J Nutr 88 (Supplement 3):S237–S319
Chapman SC, Hammer GL, Butler DG (2000) Genotype by environment interactions affecting grain sorghum. III. Temporal sequences and spatial patterns in the target population of environments. Aust J Agric Res 51:223–233
Chauhan YS, Rachaputi R (2014) Defining agro-ecological regions for field crops in variable target production environments: a case study on mungbean in the northern grain region of Australia. Agric Forest Meteor 194:207–217
Choi BH, Kronstad WE (1986) Plant breeding: a numbers game. Korean J Breed 18:80–87
Cluff M (2016) The medium-term market prospects for the global market for pulses, background paper for the report on global economy of pulses, food and agriculture Organization of the United Nations, Rome
Collard BC, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc B Biol Sci 363:557–572
Concibido VC, Denny RL, Lange DA, Orf JH, Young ND (1996) RFLP mapping and molecular marker-assisted selection of soybean cyst nematode resistance in PI 209332. Crop Sci 36:1643–1650
Cowling WA, Li L, Siddique KHM, Banks RG, Kinghorn BP (2018) Modeling crop breeding for global food security during climate change. Food Energy Security e00157. https://doi.org/10.1002/fes3.157
Crismani W, Girard C, Mercier R (2013) Tinkering with meiosis. J Exp Bot 64:55–65
Crosbie TM, Eathington SR, Johnson GR, Edwards M, Reiter R, Stark S et al (2006) Plant breeding: past, present, and future. In: Lamkey KR, Lee M (eds) Plant breeding: the Arnel R. Hallauer International Symposium. Blackwell Publishing, Ames, pp 3–50
Cullis BR, Gleeson AC (1991) Spatial analysis of field experiments-an extension to two dimensions. Biometrics 47:1449–1460
Cullis BR, Gogel B, Verbyla A, Thompson R (1998) Spatial analysis of multi-environment early generation variety trials. Biometrics 54:1–8
Daetwyler HD, Villanueva B, Woolliams JA (2008) Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS One 3:e3395. https://doi.org/10.1371/journal.pone.0003395
Dempewolf H, Baute G, Anderson J, Kilian B, Smith C, Guarino L (2017) Past and future use of wild relatives in crop breeding. Crop Sci 57:1070–1082
Ding D, Zhao Y, Guo H, Li X, Schoenau J, Si B (2018) Water footprint for pulse, cereal, and oilseed crops in Saskatchewan, Canada. Water 10:1609. https://doi.org/10.3390/w10111609
Duvick DN (1984) Genetic contributions to yield gains of U.S. hybrid maize, 1930 to 1980. In: Genetic contributions to yield gains of five major crop plants. (WR Fehr ed), Crop Science Society of America, Special Publication No. 7, Madison, Wisconsin
Eapen S (2008) Advances in development of transgenic pulse crops. Biotechnol Adv 26:162–168
Eapen S, Köhler F, Gerdemann M, Schieder O (1987) Cultivar dependence of transformation rates in moth bean after co-cultivation of protoplasts with Agrobacterium tumefaciens. Theor Appl Genet 75:207–210
Eathington S (2005) Practical applications of molecular technology in the development of commercial maize hybrids, in Proceedings of the 60th annual corn and Sorghum seed research conferences. American Seed Trade Association, Washington, DC
Edmé SJ, Tai PYP, Miller JD (2007) Relative efficiency of spatial analyses for non-replicated early-stage sugarcane field experiments. J Amer Soc Sugarcane Technologists 27:89–104
Fernandes JB, Seguéla-Arnaud M, Larchevêque C, Lloyd AH, Mercier R (2018) Unleashing meiotic crossovers in hybrid plants. Proc Natl Acad Sci U S A 115(10):2431–2436
Frankel OH (1984) Genetic perspectives of germplasm conservation. In: Arber WK et al (eds) Genetic manipulation: impact on man and society. Cambridge University Press, Cambridge, pp 161–170
Gan Y, Liang C, Chai Q, Lemke RL, Campbell CA, Zentner RP (2014) Improving farming practices reduces the carbon footprint of spring wheat production. Nat Commun 5:5012. https://doi.org/10.1038/ncomms6012
Ganguly M, Molla KA, Karmakar S, Datta K, Datta SK (2014) Development of pod borer-resistant transgenic chickpea using a pod-specific and a constitutive promoter-driven fused cry1Ab/Ac gene. Theor Appl Genet 127:2555–2565
Gauch HG, Zobel RW (1996) AMMI analysis of yield trials. In: Kang MS, Gauch HG (eds) Genotype by environment interaction. CRC Press, Boca Raton, pp 85–122
Ghosh S, Watson A, Gonzalez-Navarro OE, Ramirez-Gonzalez RH et al (2018) Speed breeding in growth chambers and glasshouses for crop breeding and model plant research. Nat Protoc 13:2944–2963
González-Barrios P, Díaz-García L, Gutiérrez L (2019) Mega-environmental design: using genotype x environment interaction to optimize resources for cultivar testing. Crop Sci 59:1899–1915
Habier D, Fernando RL, Dekkers JCM (2007) The impact of genetic relationship information on genome-assisted breeding values. Genetics 177:2389–2397
Hajjarpoor A, Vadez V, Soltani A, Gaur P, Whitbread A, Babu DS, Gumma MK, Diancoumba M, Kholová J (2012) Characterization of the main chickpea cropping systems in India using a yield gap analysis approach. Field Crops Res 223:93–104
Hallauer AR, Darrah LL (1985) Critical reviews in plant sciences compendium of recurrent selection methods and their application. Crit Rev Plant Sci 3:1–33
Heffner EL, Sorrells ME, Jannink JL (2009) Genomic selection for crop improvement. Crop Sci 49:1–12
Herzog E, Frisch M (2011) Selection strategies for marker-assisted backcrossing with high-throughput marker systems. Theor Appl Genet 123:251–260
Heslot N, Yang HP, Sorrells ME, Jannink JL (2012) Genomic selection in plant breeding: a comparison of models. Crop Sci 52:146–160
Hickey JM, Dreisigacker S, Crossa J, Hearne S, Babu R, Prasanna BM, Grondona M, Zambelli A, Windhausen VS, Mathews K, Gorjanc G (2014) Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation. Crop Sci 54:1476–1488
Hinchee M, Connor-Ward D, Newell C et al (1988) Production of transgenic soybean plants using Agrobacterium-mediated DNA transfer. Nat Biotechnol 6:915–922
Idrissi O, Sahri A, Houasli C, Nsarellah N (2019) Breeding progress, adaptation, and stability for grain yield in Moroccan lentil improved varieties. Crop Sci 59:925–936
Ignacimuthu S, Prakash S (2006) Agrobacterium-mediated transformation of chickpea with alpha-amylase inhibitor gene for insect resistance. J Biosci 31:339–345
Imrie BC, Shanmugasundaram S (1987) Source of variation in yield in international mungbean trials. Field Crops Res 16:197–208
Jacobs JB, LaFayette PR, Schmitz RJ, Parrott WA (2015) Targeted genome modifications in soybean with CRISPR/Cas9. BMC Biotechnol 15:16. https://doi.org/10.1186/s12896-015-0131-2
Jannink JL, Lorenz AJ, Iwata H (2010) Genomic selection in plant breeding: from theory to practice. Brief Funct Genomics 9:166–177
Ji J, Zhang C, Sun Z, Wang L, Duanmu D, Fan Q (2019) Genome editing in cowpea Vigna unguiculata using CRISPR-Cas9. Int J Mol Sci 20:2471. https://doi.org/10.3390/ijms20102471
Johnson CR, Thavarajah D, Thavarajah P, Fenlason A, McGee R, Kumar S, Combs GF (2015) A global survey of low-molecular weight carbohydrates in lentils. J Food Composit Analys 44:178–185
Joshi PK, Rao PP (2017) Global pulses scenario: status and outlook. Ann NY Acad Sci 1392:6–17
Katsileros A, Drosou K, Koukouvinos C (2015) Evaluation of nearest neighbor methods in wheat genotype experiments. Commun Biometry Crop Sci 10:115–123
Kellya JD, Gepts P, Miklas PN, Coyne DP (2003) Tagging and mapping of genes and QTL and molecular marker-assisted selection for traits of economic importance in bean and cowpea. Field Crops Res 82:135–154
Kempton RA (1984) The use of biplots in interpreting variety by environment interactions. J Agric Sci 103:123–135
Kempton RA, Seraphin JC, Sword AM (1994) Statistical analysis of two-dimensional variation in variety yield trials. J Agri Sci 122:335–342
Kim JI, Kim JY (2019) New era of precision plant breeding using genome editing. Plant Biotechnol Rep 13:419–421
Köhler F, Golz C, Eapen S, Kohn H, Schieder O (1987) Stable transformation of moth bean Vigna aconitifolia via direct gene transfer. Plant Cell Rep 6:313–317
Kumar S, Ali M (2006) GE interaction and its breeding implications in pulses. Botanica 56:31–36
Kumar J, Singh KB, Malhotra RS, Miranda JH, Dasgupta T (1996) Genotype x environment interaction for seed yield in chickpea. Indian J Genet 56:69–78
Kumar S, Gupta S, Chandra S, Singh BB (2004) How wide is the genetic base of pulse crops? In: Ali M, Singh BB, Kumar S, Dhar V (eds) Pulses in new perspective. Kanpur, Indian Society of Pulses Research and Development, pp 211–222. http://eprints.icrisat.ac.in/9335/1/Howwide_211221_20004.pdf
Kumar S, Kumar J, Sarker A (2016) Biodiversity and varietal development of pulses in South Asia. In: Gurung TR, Bokhtiar SM (eds) Pulses for sustainable food and nutrition security in SAARC region, pp 25–32
Lado B, González Barrios P, Quincke M, Silva P, Gutieìrrez L (2016) Modeling genotype x environment interaction for genomic selection with unbalanced data from a wheat breeding program. Crop Sci 56:2165–2179
Li H, Rasheed A, Hickey LT, He Z (2018) Fast-forwarding genetic gain. Trends Plant Sci 23:184–186
Lorenz AJ (2013) Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment. G3 (Bethesda) 3:481–491
Lulsdorf MM, Banniza S (2018) Rapid generation cycling of an F2 population derived from a cross between Lens culinaris Medik. and Lens ervoides (Brign.) Grande after Aphanomyces root rot selection. Plant Breed 137:486–491
Lush JL (1937) Animal breeding plans, 3rd edn. Iowa State College Press, Ames
Mackay MC, Street K (2004) Focused identification of germplasm strategy—FIGS. In: Black CK, Panozzo JF, Rebetzke GJ (eds) Proceedings of the 54th Australian cereal chemistry conference and the 11th wheat breeders’ assembly. Royal Australian Chemical Institute, Melbourne, pp 138–141
Malhotra RS, Singh KB (1991) Classification of chickpea growing environments to control genotype by environment interaction. Euphytica 58:5–12
Manning TS, Gibson GR (2004) Prebiotics. Best Pract Res Clin Gastroenterol 18:287–298
Mannur DM, Babbar A, Thudi M, Sabbavarapu MM, Roorkiwal M, Yeri SB, Bansal VP, Jayalakshmi SK, Yadav SS, Rathore A, Chamarthi SK, Mallikarjuna BP, Gaur PM, Varshney RK (2019) Super Annigeri 1 and improved JG 74: two Fusarium wilt-resistant introgression lines developed using marker-assisted backcrossing approach in chickpea (Cicer arietinum L.). Mol Breed 39:2. https://doi.org/10.1007/s11032-018-0908-9
Massman JM, Jung HJG, Bernardo R (2013) Genome wide selection versus marker-assisted recurrent selection to improve grain yield and Stover-quality traits for cellulosic ethanol in maize. Crop Sci 53:58–66
McCabe D, Swain W, Martinell B et al (1988) Stable transformation of soybean (Glycine Max) by particle acceleration. Nat Biotechnol 6:923–926
McCallum CM, Comai L, Greene EA, Henikoff S (2000) Targeting induced local lesions in genomes (TILLING) for plant functional genomics. Plant Physiol 123:439–442
McCann L, Bethke P, Casler M, Simon P (2012) Allocation of experimental resources used in potato breeding to minimize the variance of genotype mean chip color and tuber composition. Crop Sci 52:1475–1481
Mehrotra R, Gupta G, Sethi R, Bhalothia P, Kumar N, Mehrotra S (2011) Designer promoter: an artwork of cis engineering. Plant Mol Biol 75:527–536
Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829
Michno JM, Wang X, Liu J, Curtin SJ, Kono TJ, Stupar RM (2015) CRISPR/Cas mutagenesis of soybean and Medicago truncatula using a new web-tool and a modified Cas9 enzyme. GM Crops Food 6:243–252
Miklas PN, Kelly JD, Singh SP (2003) Registration of anthracnose-resistant pinto bean germplasm line USPTANT-1. Crop Sci 43:1889–1890
Mitchell DC, Lawrence FR, Hartman TJ, Curran JM (2009) Consumption of dry beans, peas, and lentils could improve diet quality in the US population. J Am Diet Assoc 109:909–913
Möhring J, Piepho HP (2009) Comparison of weighting in two-stage analysis of plant breeding trials. Crop Sci 49:1977–1988
Molvig L, Tabe LM, Eggum BO, Moore AE, Craig S, Spencer D, Higgins TJ (1997) Enhanced methionine levels and increased nutritive value of seeds of transgenic lupins (Lupinus angustifolius L.) expressing a sunflower seed albumin gene. Proc Natl Acad Sci U S A 94:8393–8398
Moreau L, Lemarie S, Charcosset A, Gallais A (2000) Economic efficiency of one cycle of marker-assisted selection. Crop Sci 40:329–337
Mudryj AN, Yu N, Hartman TJ, Mitchell DC, Lawrence FR, Aukema HM (2012) Pulse consumption in Canadian adults influences nutrient intakes. Br J Nutr 108(Suppl1):S27–36
Mudryj AN, Yu N, Aukema H (2014) Nutritional and health benefits of pulses. Appl Physio 39:1–8
Murrell D (2016) Global research and funding survey on pulse productivity and sustainability. https://iyp2016.org/resources/technical-reports/124-pulses-global-research-and-funding-survey/file
Nambiar M, Smith GR (2016) Repression of harmful meiotic recombination in centromeric regions. Semin Cell Dev Biol 54:188–197
Odong TL, van Heerwaarden J, Jansen J, van Hintum TJL, van Eeuwijk FA (2011) Statistical techniques for defining reference sets of accessions and microsatellite markers. Crop Sci 51:2401–2411
Paget MF, Alspach PA, Anderson JAD, Genet RA, Braam WF, Apiolaza LA (2017) Replicate allocation to improve selection efficiency in the early stages of a potato breeding scheme. Euphytica 213:221
Piepho HP, Williams ER (2010) Linear variance models for plant breeding trials. Plant Breed 129:1–8
Piepho HP, Möhring J, Schulz-Streeck T, Ogutu JO (2012) A stage-wise approach for the analysis of multi-environment trials. Biom J 54:844–860
Piepho HP, Williams ER, Michel V (2015) Beyond Latin squares: a brief tour of row-column designs. Agron J 107:2263–2270
Poland J, Rife TW (2012) Genotyping-by-sequencing for plant breeding and genetics. Plant Genome 5:92–102
Rachel A, Hagai C, Yael H (2019) Revisiting the attempts to fortify methionine content in plant seeds. J Experim Bot 70:4105–4114. https://doi.org/10.1093/jxb/erz134
Ragot M, Lee M, Dargie JD (eds) (2007) Marker-assisted selection in maize: current status, potential, limitations and perspectives from the private and public sectors. Food and Agriculture Organization of the United Nations (FAO): FAO
Ray DK, Mueller ND, West PC, Foley JA (2013) Yield trends are insufficient to double global crop production by 2050. PLoS One 8(6):e66428. https://doi.org/10.1371/journal.pone.0066428
Rebetzke GJ, Jimenez-Berni J, Fischer RA, Deery DM, Smith DJ (2019) Review: high-throughput phenotyping to enhance the use of crop genetic resources. Plant Sci 282:40–48
Reckling M, Döring TF, Bergkvist G, Stoddard FL, Watson CA, Seddig S, Chmielewski FM, Bachinger J (2018) Grain legume yields are as stable as other spring crops in long-term experiments across northern Europe. Agron Sustain Dev 38:63. https://doi.org/10.1007/s13593-018-0541-3
Romano G, Zia S, Spreer W, Sanchez C, Cairns J, Araus JL, Müller J (2011) Use of thermography for high throughput phenotyping of tropical maize adaptation in water stress. Comput Electron Agric 79:67–74
Roorkiwal M, Rathore A, Das RR, Singh MK, Jain A, Srinivasan S, Gaur PM, Chellapilla B, Tripathi S, Li Y, Hickey JM, Lorenz A, Sutton T, Crossa J, Jannink J-L, Varshney RK (2016) Genome-enabled prediction models for yield related traits in chickpea. Front Plant Sci 7:1666. https://doi.org/10.3389/fpls.2016.01666
Roorkiwal M, Jain A, Kale SM, Doddamani D, Chitikineni A, Thudi M, Varshney RK (2018) Development and evaluation of high-density Axiom®CicerSNP Array for high-resolution genetic mapping and breeding applications in chickpea. Plant Biotechnol J 16:890–901
Rutkoski J, Singh RP, Huerta-Espino J, Bhavani S, Poland J, Jannink JL, Sorrells ME (2015) Efficient use of historical data for genomic selection: a case study of stem rust resistance in wheat. Plant Genome 8:1. https://doi.org/10.3835/plantgenome2014.09.0046
Sadhukhan A, Kobayashi Y, Kobayashi Y, Tokizawa M, Yamamoto YY, Iuchi S, Koyama H, Panda SK, Sahoo L (2014) VuDREB2A, a novel DREB2-type transcription factor in the drought-tolerant legume cowpea, mediates DRE-dependent expression of stress-responsive genes and confers enhanced drought resistance in transgenic Arabidopsis. Planta 240:645–664
Samineni S, Sen M, Sajja SB, Gaur PM (2019) Rapid generation advance (RGA) in chickpea to produce up to seven generations per year and enable speed breeding. Crop J. https://doi.org/10.1016/j.cj.2019.08.003
Sanderson LA, Caron CT, Shen Y, Liu R, Bett KE (2019) KnowPulse: a web-resource focussed on diversity data for pulse improvement. Front Plant Sci 10:965
Sarker A, Singh M (2015) Improving breeding efficiency through application of appropriate experimental designs and analysis models: a case of lentil (Lens culinarisMedikus subsp. culinaris) yield trials. Field Crops Res 179:26–34
Sawardekar SV, Mhatre NK, Sawant SS, Bhave SG, Gokhale NB, Narangalkar AL, Katageri IS, Kumar PA (2012) Agrobacterium mediated genetic transformation of pigeonpea [Cajanuscajan (L.) Millisp] for pod borer resistance: optimization of protocol. Indian J Genet 72:380–383
Saxena KB, Kumar RV, Latha M, Dalvi VA (2006) Commercial pigeonpea hybrids are just a few steps away. Indian J Pulses Res 19:7–16
Saxena RK, Saxena KB, Pazhamala LT, Patel K, Parupalli S, Sameerkumar CV, Varshney RK (2015) Genomics for greater efficiency in pigeonpea hybrid breeding. Front Plant Sci 6:793. https://doi.org/10.3389/fpls.2015.00793
Saxena K, Saxena R, Hickey L, Varshney R (2019) Can a speed breeding approach accelerate genetic gain in pigeonpea? Euphytica 215. https://doi.org/10.1007/s10681-019-2520-4
Scheben A, Edward D (2017) Genome editors take on crops. Science 355(6330):1122–1123
Siddique KHM, Erskine W, Hobson K, Knights EJ, Leonforte A, Khan TN, Paull JG, Redden R, Materne M (2013) Cool-season grain legume improvement in Australia—use of genetic resources. Crop Pasture Sci 64:347–360
Siva N, Thavarajah P, Kumar S, Thavarajah D (2019) Variability in prebiotic carbohydrates in different market classes of chickpea, common bean, and lentil collected from the American local market. Front Nutr 6:38. https://doi.org/10.3389/fnut.2019.00038
Sivashakthi S, Thudi M, Tharanya M, Kale SM, Kholova J, Halime MH, Jaganathan D, Baddam R, Thirunalasundari T, Gaur PM, Varshney RK, Vadez V (2018) Plant vigour QTLs co-map with an earlier reported QTL hotspot for drought tolerance while water saving QTLs map in other regions of the chickpea genome. BMC Plant Biol 18:29
Slinkard AE, Solh MB, Vandenberg A (2000) Breeding for yield: the direct approach. In: Knight R (ed) Linking research and marketing opportunities for pulses in the 21st century. Current plant science and biotechnology in agriculture, vol 34. Springer, Dordrecht
Smith AB, Cullisi BR, Thompson R (2005) The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches. J Agric Sci 143:449–462
Smýkal P, Coyne CJ, Ambrose MJ, Maxted N, Schaefer H, Blair MW, Berger J, Greene SL, Nelson MN, Besharat N, Vymyslický T, Toker C, Saxena RK, Roorkiwal M, Pandey MK, Hu J, Li YE, Wang LX, Guo Y, Qiu LJ, Redden RJ, Varshney RK (2015) Legume crops phylogeny and genetic diversity for science and breeding. Crit Rev Plant Sci 34:43–104
Stringer JK, Cullis BR (2002) Joint modelling of spatial variability and interplot competition. In: Australasian Plant Breeding Conference, Perth. Proceedings: CSIRO, pp 614–619
Suripeddi RK, Ghanti KK, Ghanti S, Kumar B, Nataraja K, Reddy K, Rao S, Kishor P (2011) Heterologous expression of P5CS gene in chickpea enhances salt tolerance without affecting yield. Biol Plant 55:634–640
Talbot M (1984) Yield variability of crop varieties in the UK. J Agric Sci 102:315–321
Tanksley SD, McCouch SR (1997) Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277:1063–1066
Tanksley SD, Young ND, Paterson AH, Bonierbale MW (1989) RFLP mapping in plant breeding: new tools for an old science. Biotechnology 7:257–264
Thavarajah D, Thavarajah P, Wejesuriya A, Rutzke M, Glahn RP, Combs GF Jr, Vandenberg A (2011) The potential of lentil (Lens culinaris L.) as a whole food for increased selenium, iron, and zinc intake: preliminary results from a 3-year study. Euphytica 180:123–128
Tilman D, Clark M (2015) Global diets link environmental sustainability and human health. Nature 515:518–522
Tittonell P, Giller KE (2013) When yield gaps are poverty traps: the paradigm of ecological intensification in African smallholder agriculture. Field Crops Res 143:76–90
Upadhyaya HD, Ortiz R (2001) A mini core subset for capturing diversity and promoting utilization of chickpea genetic resources in crop improvement. Theor Appl Genet 102:1292–1298
Upadhyaya HD, Dronavalli N, Dwivedi SL, Kashiwagi J, Krishnamurthy L, Pande S, Sharma HC, Vadez V, Singh S, Varshney RK, Gowda CLL (2013) Mini core collection as a resource to identify new sources of variation. Crop Sci 43:2506–2517
Ustun A, Allen FL, English BC (2001) Genetic progress in soybean of the US Midsouth. Crop Sci 41:993–998
van Eeuwijk FA, Bustos-Korts D, Millet EJ, Boer MP, Kruijer W, Thompson A, Malosetti M, Iwata H, Quiroz R, Kuppe C, Muller O, Blazakis KN, Yu K, Tardieu F, Chapman SC (2019) Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding. Plant Sci 282:23–39
Varshney RK, Thudi M, Nayak SN, Gaur PM, Kashiwagi J, Krishnamurthy L, Jaganathan D, Koppolu J, Bohra A, Tripathi S, Rathore A, Jukanti AK, Jayalakshmi V, Vemula A, Singh SJ, Yasin M, Sheshshayee MS, Viswanatha KP (2014) Genetic dissection of drought tolerance in chickpea (Cicer arietinum L.). Theor Appl Genet 127:445–462
Varshney RK, Thudi M, Pandey MK, Tardieu F, Ojiewo C, Vadez V, Whitbread AM, Siddique KHM, Nguyen HT, Carberry PS, Bergvinson D (2018) Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy. J Exp Bot 69:3293–3312
Varshney RK, Ojiewo C, Monyo E (2019) A decade of tropical legumes projects: development and adoption of improved varieties, creation of market-demand to benefit smallholder farmers and empowerment of national programmes in sub-Saharan Africa and South Asia. Plant Breed 138:379–388
Velazco JG, Rodríguez-Álvarez MX, Boer MP, Jordan DR, Eilers PHC, Malosetti M, van Eeuwijk FA (2017) Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model. Theor Appl Genet 130:1375–1392
Verkaart S, Munyua GB, Mausch K, Michler DJ (2016) Welfare impacts of improved chickpea adoption: a pathway for rural development in Ethiopia? Food Policy 66:50–61
Viguiliouk E, Glenn AJ, Nishi SK, Chiavaroli L, Seider M, Khan T, Bonaccio M, Iacoviello L, Mejia SB, Jenkins DJA, Kendall CWC, Kahleová H, Raheli D, Salas-Salvadó J, Sievenpiper JL (2019) Associations between dietary pulses alone or with other legumes and cardiometabolic disease outcomes: an umbrella review and updated systematic review and meta-analysis of prospective cohort studies. Adv Nutr 10:S308–S319
Vincent H, Wiersema J, Kell SP, Fielder H, Dobbie S, Castañeda-Álvarez NP, Guarino L, Eastwood R, Leόn B, Maxted N (2013) A prioritized crop wild relative inventory to help underpin global food security. Biol Conserv 167:265–275
Wang E, van Oosterom E, Meinke H et al (2003) The new APSIM-Wheat Model—performance and future improvements. In: Solutions for a better environment. Proceedings of the 11th Australian Agronomy Conference, 2–6 Feb 2003, Geelong, Victoria. Australian Society of Agronomy
Wang Y, Cheng X, Shan Q, Zhang Y, Liu J, Gao C, Qiu JL (2014) Simultaneous editing of three homoeoalleles in hexaploid bread wheat confers heritable resistance to powdery mildew. Nat Biotechnol 32:947–951
Wang H, La Russa M, Qi LS (2016) CRISPR/Cas9 in genome editing and beyond. Annu Rev Biochem 85:227–264
Watson C, Reckling M, Preissel S, Bachinger J, Bergkvist G, Kuhlman T, Lindström K, Nemecek T, Topp C, Vanhatalo A, Zander Z, Murphy-Bokern D, Stoddard F (2017) Grain legume production and use in European agricultural systems. Adv Agron 144:235–303
Whitaker D, Williams ER, John JA (2001) CycDesigN: a package for the computer generation of experimental designs. CSIRO Forestry and Forest Products, CSIRO, Canberra
Wijnker E, de Jong H (2008) Managing meiotic recombination in plant breeding. Trends Plant Sci 13:640–646
Win MM, Shwe T, Gaur PM (2014) An overview of chickpea breeding programs in Myanmar. Legume Perspect 3:62–64
Windhausen VS, Atlin GN, Hickey JM, Crossa J, Jannink JL, Sorrells ME, et al. (2012). Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments. G3 2:1427–1436
Wright S (1920) The relative importance of heredity and environment in determining the piebald pattern of Guinea pigs. Proc Natl Acad Sci 6:320–332
Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407
Yabe S, Iwata H, Jannink J (2017) A simple package to script and simulate breeding schemes: the breeding scheme language. Crop Sci 57:1–8
Yigezu AY, Alwang J, Rahman MW, Mollah MBR, El-Shatera T, Aw-Hassan A, Sarker A (2019a) Is DNA fingerprinting the gold standard for estimation of adoption and impacts of improved lentil varieties? Food Policy 83:48–59
Yigezu AY, El-Shater T, Boughlala M, Bishaw Z, Niane AA, Maalouf F, Degu WT, Wery J, Boutfiras A, Aw-Hassan A (2019b) Legume-based rotations have clear economic advantages over cereal monocropping in dry areas. Agron Sustain Dev 39:58. https://doi.org/10.1007/s13593-019-0602-2
Yin X, Goudriaan J, Lantinga EA, Vos J, Spiertz JHJ (2003) A flexible sigmoid function of determinate growth. Ann Bot 91:361–371
Zhang Y, Malzahn AA, Sretenovic S, Qi Y (2019) The emerging and uncultivated potential of CRISPR technology in plant science. Nat Plants 5:778–794
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Kumar, S., Gupta, P., Choukri, H., Siddique, K.H.M. (2020). Efficient Breeding of Pulse Crops. In: Gosal, S.S., Wani, S.H. (eds) Accelerated Plant Breeding, Volume 3. Springer, Cham. https://doi.org/10.1007/978-3-030-47306-8_1
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