Identification of stable lentil genotypes through genotype by environment interactions on yield potential in Morocco

Asmae Baggar; Amal Safi; Fatima Gaboun; Mona Taghouti; Nadia Benbrahim

doi:10.14719/pst.1814

Authors

Asmae Baggar Faculty of Sciences and Technology of Mohammedia, Hassan II University of Casablanca https://orcid.org/0000-0002-7303-2041
Amal Safi Departement of biology, Laboratory of Biochemistry, Hassan II University of Casablanca, Faculty of sciences and technology of Mohammedia, Morocco. https://orcid.org/0000-0001-5891-5391
Fatima Gaboun Regional center of agricultural research, National Institute of Agronomic Research, (INRA) Rabat, Morocco https://orcid.org/0000-0003-2018-8031
Mona Taghouti Regional center of agricultural research, National Institute of Agronomic Research, (INRA) Rabat, Morocco https://orcid.org/0000-0001-6721-2778
Nadia Benbrahim Regional center of agricultural research, National Institute of Agronomic Research, (INRA) Rabat, Morocco https://orcid.org/0000-0002-2263-9329

DOI:

https://doi.org/10.14719/pst.1814

Keywords:

Lentil, grain yield, G×E interaction, AMMI-GGE, biplot analysis

Abstract

Genotype by environment (G×E) interaction study becomes essential for selecting high and stable yielding genotypes. Altogether 64 lentil genotypes representing improved varieties, landraces and advanced lines were evaluated under 6 environments for green cover, phenological characters, grain yield and 1000 seed weight. Variance analysis revealed highly significant effects of genotype, environment and genotype by environment interaction for all studied traits. The environment had the greatest effect with 75.7% of the total sum of squares. AMMI-GGE biplot identified 3 mega-environments where Z32 advanced lines were performed in the first one (E1, E4 and E5); Z33 was the best in the second mega-environment (E2 and E3), of which E2 (SAD18) was characterized as discriminating and representative environment for selecting adaptable genotypes. While VR4 and LR4 were the winning genotypes in the third mega-environment represented by E6. According to 7 stability methods, Z33, Z32, Z31, Z13 and G03 lines were the most stable and resilient in all environments. In addition, five landraces (PA6, LR4, LR10, LR6 and PA1) showed a high yielding potential that could be used as a source of genotype candidates to develop novel resilient varieties of lentils. Varieties VR9 was recommended for both favorable and unfavorable environments, VR6 for unfavorable and VR3 for favorable environment. Otherwise, genotypes were grouped into 3 clusters with 90% of similarity. The third one gathered the highest yielding genotypes (Z33 and Z32), which were the most stable that could be promoted for developing resilient varieties for climatic changing environments.

Downloads

Download data is not yet available.

References

Kumar S, Rajendran K, Kumar J, Hamwieh A, Baum M. Current knowledge in lentil genomics and its application for crop improvement. Front Plant Sci. 2015;6(FEB):1-13. https://doi.org/10.3389/fpls.2015.00078

Dhuppar P, Biyan SC, Chintapalli B, Sarveshwara Rao D. Lentil Crop Production in the Context of Climate Change: An Appraisal. Indian Res J Ext Educ Spec Issue. 2012.

FAOSTAT. Food and Agriculture Organization of the United Nations [Internet]. 2020 [cited 2010 Jun 16]. Available from: http://www.fao.org/faostat/en/#compare

Sarker A, Kumar S. Lentils in production and food systems in West Asia and Africa. 2011;(56):56-58. https://hdl.handle.net/20.500.11766/7913

Urbano G, Porres JM, Frías J, Vidal-valverde C. Chapter 5 Nutritional Value. Lentil an Anc Crop Mod times. 2007;3:47-93. https://doi.org/10.1007/978-1-4020-6313-8_5

Joshi M, Timilsena Y, Adhikari B. Global production, processing and utilization of lentil: A review. J Integr Agric [e-book]. 2017 Dec 1 [cited 2010 Jun 15]: 16(12):2898-913. Available from: http://dx.doi.org/10.1016/S2095-3119(17)61793-3

Rawal V, Kalamvrezos Navarro D. The Global Economy of Pulses. Food and A. Rome: FAO. 2019; 190 p. https://agris.fao.org/agris-search/search.do?recordID=XF2020000786

Benayad A, Taghouti M, Benali A, Benbrahim N, Aboussaleh Y. Development and nutritional, technological, microbiological, cooking and sensory characterization of durum wheat couscous partially enriched with lentil semolina. Food Bios. 2021;42(January):101062. https://doi.org/10.1016/j.fbio.2021.101062

Carbonaro M, Nardini M, Maselli P, Nucara A. Chemico-physical and nutritional properties of traditional legumes (lentil, Lens culinaris L. and grass pea, Lathyrus sativus L.) from organic agriculture: an explorative study. Org Agric. 2015;5(3):179-87. https://doi.org/10.1007/s13165-014-0086-y

Dissanayaka DMSB, Rankoth LM, Gunathilaka WMND, Prasantha BDR, Marambe B. Utilizing food legumes to achieve iron and zinc nutritional security under changing climate. J Crop Improv. 2021;00(00):1-22. https://doi.org/10.1080/15427528.2021.1872754

Zakir M. Review on genotype X environment interaction in plant breeding and agronomic stability of crops. J Biol Agric Healthc. 2018;8(12):14-21. https://www.iiste.org/Journals/index.php/JBAH/article/view/43065

Neac?u A. Grain protein concentration and its stability in a set of winter wheat cultivars, grown in diverse environments and management practices. Rom Agric Res. 2011;(28):29-36. https://www.incda-fundulea.ro/rar/nr28/rar28.5.pdf

Sabaghnia N, Sabaghpour SH, Dehghani H. The use of an AMMI model and its parameters to analyse yield stability in multi-environment trials. J Agric Sci. 2008;146(5):571-81. https://doi.org/10.1017/S0021859608007831

Smith MF, Gauch HG. Effects of noise on ammi and hierarchical classification analyses. South African Stat J. 1992;26:121-42. https://doi.org/10.15835/nsb529067

Karimizadeh R, Mohammadi M, Sabaghni N, Mahmoodi AA, Roustami B, Seyyedi F et al. GGE biplot analysis of yield stability in multi-environment trials of lentil genotypes under rainfed condition. Not Sci Biol. 2013;5(2):256-62. https://doi.org/10.15835/nsb529067

Jeberson MS, Shashidhar KS, Wani SH, Singh AK, Dar SA. Identification of stable lentil ( Lens culinaris Medik ) genotypes through GGE biplotand AMMI analysis for North Hill Zone of India. India: Agricultural Research Communication Centre. 2019;42(4):467-72. https://doi.org/10.18805/LR-3901

Hugh G. Gauch J. Model Selection and Validation for Yield Trials with Interaction. International Biometric Society Stable. Biometrics. 1988;44(3):705-15. http://www.jstor.org/stable/2531585 https://doi.org/10.2307/2531585

Yan W, Hunt LA, Sheng Q, Szlavnics Z. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 2000;40(3):597-605. https://doi.org/10.2135/cropsci2000.403597x

Eberhart SA, Russell WA. Stability parameters for comparing varieties 1. Crop Sci. 1966;6(1):36-40. https://doi.org/10.2135/cropsci1966.0011183X000600010011x

Lin CS, Binns MR. A method of analyzing cultivar x location x year experiments: a new stability parameter. Theor Appl Genet. 1988;76(3):425-30. https://doi.org/10.1007/BF00265344

Nassar R, Hühn M. Studies on estimation of phenotypic stability?: Tests of significance for nonparametric measures of phenotypic stability. International Biometric Society. Biometrics. 1987;43(1):45-53. http://www.jstor.org/stable/2531947 https://doi.org/10.2307/2531947

Hühn M, Nassar R. On tests of significance for nonparametric measures of phenotypic stability. International Biometric Society. 1989;45(3):997-1000. https://www.jstor.org/stable/2531698 https://doi.org/10.2307/2531698

Pinthus MJ. Estimate of Genotypic Value?: Euphytica. 1973;22:121-23. https://doi.org/10.1007/BF00021563

Perkins JM, Jinks JL. Environmental and genotype-environmental components of variability IV. Non-linear interactions for multiple inbred lines. Heredity (Edinb). 1968;23(4):525-35. https://doi.org/10.1038/hdy.1968.71

Mohebodini M, Dehghani H, Sabaghpour SH. Stability of performance in lentil (Lens culinaris Medik) genotypes in Iran. Euphytica. 2006;149(3):343-52. https://doi.org/10.1007/s10681-006-9086-7

Rahman MM, Islam MM, Ahmed B. Performance of different lentil genotypes in southern belt of Bangladesh. J Environ Sci Nat Resour. 2015;7(1). https://doi.org/10.3329/jesnr.v7i1.22162

Kumar V. Genetic variability and character association among the yield and yield attributing components in lentil (Lens culinaris Medik.). Bangladesh J Bot. 2020;49(2):305-12. https://doi.org/10.3329/bjb.v49i2.49311

Hamdi A, Ali MMA, Shaaban M, Ezzat ZM. Agronomic, seed protein and quality characters of the most promising lentil genotypes in Egypt. World Appl Sci J. 2012;20(1):70-79. https://doi.org/10.5829/idosi.wasj.2012.20.01.2812

Mondal MMA, Puteh AB, Malek MA, Roy S, Yusop MR. Contribution of morpho-physiological traits on yield of lentil (Lens culinaris Medik). Aust J Crop Sci. 2013;7(8):1167-72. https://search.informit.org/doi/10.3316/informit.409387567528788

Al-Naggar AMM, Shafik MM, Musa RYM. Ammi, Gge biplot analyses for yield stability of nineteen maize ammi and gge biplot analyses for yield stability of nineteen maize genotypes under different nitrogen and irrigation levels. Plant Archives. 2020. http://www.plantarchives.org/20-2/4431-4443 (6172).pdf

RD. AMMI Biplot analysis for genotype X environment interaction on yield trait of high Fe content lentil genotypes in Terai and Mid-Hill Environment of Nepal. Ann Agric Crop Sci. 2017;2(1). https://doi.org/10.26420/annagriccropsci.2017.1026

Ajay BC, Bera SK, Singh AL, Kumar N, Gangadhar K, Kona P. Evaluation of genotype × environment interaction and yield stability analysis in peanut under phosphorus stress condition using stability parameters of AMMI model. Agric Res. 2020;9(4):477-86. https://doi.org/10.1007/s40003-020-00458-3

Abbas G, Asghar MJ, Shahid M, Hussain J, Akram M, Ahmad F. Yield performance of some lentil genotypes over different environments. Agrosystems, Geosci Environ. 2019;2(1):1-3. https://doi.org/10.2134/age2018.10.0051

Rashid A, GRH, NJ, MSN, GMA. Genotype X environment interaction and stability analysis in mustard. Asian J Plant Sci. 2002;1(5):591-92. https://doi.org/10.3923/ajps.2002.591.592

Hoyos-Villegas V, Wright EM, Kelly JD. GGE biplot analysis of yield associations with root traits in a mesoamerican bean diversity panel. Crop Sci. 2016;56(3):1081-94. https://doi.org/10.2135/cropsci2015.10.0609

Bhartiya A, Aditya JP, Kumari V, Kishore N, Purwar JP, Agrawal A et al. Stability analysis of soybean [Glycine max (L.) Merrill] genotypes under multi-environments rainfed condition of North Western Himalayan hills. Indian J Genet Plant Breed. 2018;78(3):342-47. https://doi.org/10.31742/IJGPB.78.3.6

Negash K, Tumsa K, Amsalu B, Gebeyehu S. Grouping of environments for testing Navy Bean in Ethiopia Common Bean is one of the grain legume crops grown in Ethiopia and is being. 2017;27(2):111-30. https://www.ajol.info/index.php/ejas/article/download/156185/145803

Yan W, Rajcan I. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Sci. 2002;42(1):11-20. https://doi.org/10.2135/cropsci2002.1100

Yan W, Tinker NA. Biplot analysis of multi-environment trial data: Principles and applications. Can J Plant Sci. 2006;86(3):623-45. https://doi.org/10.4141/P05-169

Kang MS. Genotype-environment interaction?: Progress and prospects progress and prospects. Dep Agron Louisiana State Univ Bat Rouge, LA 70803-2110;2002. https://doi.org/10.1079/9780851996011.0221

Reza M, Rad N, Ghasemi A, Arjmandinejad A. Study of limit irrigation on yield of lentil (Lens culinaris) genotypes of national plant gene bank of Iran by drought resistance indices. Taylor & Francis Group. 2012;7(2):238-44.