Genetic parameters, stability and selection of lentil genotypes under rainfed conditions for autumn planting using BLUP, WAASB and AMMI methods

Document Type : Original Article

Authors

1 Assistant Professor, Crop and Horticultural Science Research Department, Lorestan Agricultural and Natural Resources Research and Education Center ( AREEO), Khorramabad, Iran

2 Researcher, Dryland Agricultural Research Institute, Sararood Branch, Agricultural Research, Education and Extension (AREEO), Kermanshah, Iran

3 Assistant Professor, Ilam Agricultural and Natural Resources Research and Education Center,( AREEO), Ilam, Iran

10.22034/plant.2024.141328.1105

Abstract

ABSTRACT
The integration of the two stability assessment methods of the best linear unbiased predictions (BLUP) and AMMI in multi- environment experiments based on the stability index of weighted average absolute scores (WAASB) helps to better evaluate plant genotypes. In the present study, the seed yield stability of 13 advanced lentil genotypes was evaluated in a multi-environment trials in three locations including; Khoramabad, Ilam and Kermanshahn in 2019-2022 cropping seasons. The experimental design was randomized complete block design with three replications. In order to evaluate genotype × environment interaction, AMMI and BLUP methods were combined by introducing WAASB and WAASBY indicators and the yield stability was evaluated by drawing various graphs. Considering the significant G×E interaction based on the results of the relative likelihood test (LRT), it was possible to perform BLUP analysis on the data. The highest predicted seed yield by BLUP method belonged to genotype no. 12 followed by genotypes no. 6, 4, 3, 5 and 9 which had higher than average predicted seed yield. To enable simultaneous selection based on both seed yield and yield stability, by combining seed yield (Y) and WAASB, a new index “WAASBY” was created. Considering 50% contribution of each of the two components of seed yield and yield stability, seven genotypes showed above average WAASBY. Genoypes no. 3, 6, 5 and 2 had considerably higher WAASBY when compared with other genotypes and was identified .

Keywords

References

Abbas, G., Asghar, M. J., Shahid, M., Hussain, J., Akram, M., & Ahmad, F. (2019). Yield performance of some lentil genotypes over different environments. Agrosystems, Geosciences & Environment, 2(1), 1-3.
Abo-Hegazy, S. R. E., Selim, T., &Ashrie, A. A. M. (2013). Genotype× environment interaction and stability analysis for yield and its components in lentil. Journal Plant Breed. Crop Science, 5(5), 85-90.
Akbari, S., Akbarpour, O., &Pezeshkpour, P. (2021). Evaluation of grain yield stability of lentil genotypes using non-parametric methods. Plant Genetic Researches, 8(1), 95-114. (In Persian).
Akıncı, C., Biçer, B. T., Kızılgeçi, F., Albayrak, Ö., &Yıldırım, M. (2018). Stability parameters in lentil genotypes. El-Cezeri, 5(2), 287-291.
Azam, M. G., Iqbal, M. S., Hossain, M. A., & Hossain, M. F. (2020). Stability investigation and genotype× environment association in chickpea genotypes utilizing AMMI and GGE biplot model. Genetics and Molecular Research, 19(3), 1-15.
Barrios, A., Aparicio, T., Rodríguez, M. J., de la Vega, M. P., &Caminero, C. (2016). Winter sowing of adapted lines as a potential yield increase strategy in lentil (Lens culinarisMedik.). Spanish Journal of Agricultural Research, 14(2), e0702-e0702.
Barbosa, M.H., Ferreira, A., Peixoto, L. A., Resende, M.D., Nascimento, M.,& Silva. F.F. (2014). Selection of sugar cane families by using BLUP and multi-diverse analyses for planting in the Brazilian savannah. Genetics and Molecular Research. 13, 1619-1626.
Baretta, D., Nardino, M., Carvalho, I. R., Oliveira, A. D., Souza, V. D.,&   Maia, L. D. (2016). Performance of maize genotypes of Rio Grande do Sul using mixed models. Científica, 44(3), 403-411.
Bermejo, C., Cazzola, F., Maglia, F., &Cointry, E. (2020). Selection of parents and estimation of genetic parameters using BLUP and molecular methods for lentil (Lens culinarisMedik.) breeding program in Argentina. Experimental Agriculture, 56(1), 12-25
Branković-Radojčić, D., Babić, V., Girek, Z., Živanović, T., Radojĉić, A., Filipović, M., &Srdić, J. (2018). Evaluation of maize grain yield and yield stability by AMMI analysis. Genetika, 50(3), 1067-1080.
Chen, C., Etemadi, F., Franck, W., Franck, S., Abdelhamid, M. T., Ahmadi, J., Mohammed, Y. A., Lamb, P., Miller, J., Carr, P. M., & McPhee, K. (2022). Evaluation of environment and cultivar impact on lentil protein, starch, mineral nutrients, and yield. Crop Science, 62(2), 893-905.
Dehghani, H., Sabaghpour, S. H., &Sabaghnia, N. (2008). Genotype× environment interaction for grain yield of some lentil genotypes and relationship among univariate stability statistics. Spanish Journal of Agricultural Research, 6(3), 385-394.
Elias, A. A., Robbins, K. R., Doerge, R. W., &Tuinstra, M. R. (2016). Half a century of studying genotype × environment interactions in plant breeding experiments. Crop Science, 58, 2090-2105.
Gan, Y., Hamel, C., Kutcher, H. R., & Poppy, L. (2017). Lentil enhances agroecosystem productivity with increased residual soil water and nitrogen. Renewable Agriculture and Food Systems,32(4), 319-30.
Holland, J. B. (2006). Estimating genotypic correlations & their standard errors using multivariate restricted maximum likelihood estimation with SAS Proc MIXED. Crop science, 46(2), pp.642-654
Jeberson, M. S., Shashidhar, K. S., Wani, S. H., Singh, A. K.,& Dar, S. A. (2019). Identification of stable lentil (Lens culinaris Medik) genotypes through GGE biplotand AMMI analysis for North Hill Zone of India. Environment. 2(22.7432), 11-3716.
Laffont, J.L., Hanafi, M.,& Wright, K. (2007). Numerical and graphical measures to facilitate the interpretation of GGE biplots. Crop Science, 47(3), 990-996.
Karaköy, T., Erdem, H., Baloch, F.S., Toklu, F., Eker, S., Kilian, B.,&Özkan, H. (2012). Diversity of macro- and micronutrients in the seeds of lentil landraces. The Scientific World Journal, 1-9.
Karimizadeh, R., SafikhaniNasimi, M., Mohammadi, M., Seyyedi, F., Mahmoodi, A. A.,& Rostami, B. (2008). Determining Rank and Stability of Lentil Genotypes in Rainfed Condition by Nonparametric Statistics. JWSS-Isfahan University of Technology. 43(1), 93 -103 (In Persian).
Karimizadeh, R., & Mohammadi, M. (2010). AMMI adjustment for rainfed lentil yield trials in Iran. Bulgarian Journal of Agricultural Science, 16(1), 66-73.
Karimizadeh, R., Mohammadi, M. &Sabaghnia, N. (2013). Site regression biplot analysis for matching new improved lentil genotypes into target environments. Journal of Plant Physiology and Breeding, 3(2), 51-65.
Karimizadeh, R., Pezeshkpour, P., Barzali, M., Mehraban, A. & Sharifi, P. (2020). Evaluation the mean performance and stability of lentil genotypes by combining features of AMMI and BLUP techniques. Journal of Crop Breeding. 12(36), 160-170. (In Persian).
Karimizadeh, R., Pezeshkpour, P.,&Mirzaii, A. (2021). Evaluation of grain yield stability of rainfed lentil genotypes by parametric and non-parametric methods. Applied Field Crops Research, 34(3), 155-140. (In Persian).
Muehlbauer, F.J., Cubero, J.I., & Summerfield, R.J. (1985). Lentil (Lens culinaris Medic. In Grain Legume Crops; Summerfield, R.J., Roberts, E.H., Eds.; Collins: London, UK. pp. 266–311.
Namdari, A., Pezeshkpour, P., Mehraban, A., Mirzaei, A.,&Vaezi, B. (2022). Evaluation of genotype× environment interaction of advanced rainfed lentil genotypes by multivariate GGE biplot method. Journal of Crop Production, 15, 2.203-218. (In Persian).
Maicon, N., Diego, B., Ivan, R. C., Tiago, O., Diego, N. F., Vincius, J. S., &Velci, Q. D. S. (2016). Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) for analyzing the agronomic performance of corn. African Journal of Agricultural Research, 11(48), 4864-4872.
Olivoto, T. (2019). Metan: multi environment trials analysis. R package version 1.1.0. https://github.com/TiagoOlivoto/metan.
Olivoto, T., Lúcio, A. D., da Silva, J. A., Marchioro, V. S., de Souza, V. Q., &Jost, E. (2019). Mean performance and stability in multi‐environment trials I: combining features of AMMI and BLUP techniques. Agronomy Journal,111(6), 2949-2960.
Olivoto, T., &Lúcio, A. D. C. (2020). metan: An R package for multi‐environment trial analysis. Methods in Ecology and Evolutio, 11(6), 783-789.
Piepho, H.P., Mohring, J., Melchinger, A.E., &Buchse, A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 161, 209–228.
Pawar, I. S., & Singh, S. (2010). Theory and Application of Biometrical Genetics. CBS Publisher and Distributors Pvt. Ltd. Softcover, 1st edition. New Delhi, IND.
Pezeshkpour, P., Karimizadeh, R., Mirzaei, A., &Barzali, M. (2021). Analysis of yield stability of lentil genotypes using AMMI Method. Journal of Crop Breeding, 13(37), 132-145. (In Persian).
Resende, M. D. V. D. (2016). Software Selegen-REML/BLUP: a useful tool for plant breeding. Crop Breeding and Applied Biotechnology, 16(04), 330-339.
Ruisi, P., Amato, G., Badagliacca, G., Frenda, A.S., Giambalvo, D., & Di Miceli, G. (2017). Agro-ecological benefits of faba bean for rainfed Mediterranean cropping systems. Italian Journal of Agronomy, 12(3), 1459-66.
Sa’diyah, H., &Hadi, A. F. (2016). AMMI Model for yield estimation in multi-environment trials: A comparison to BLUP. Agriculture and Agricultural Science Procedia,  9, 163-169.
Sandhu, J.S., & Singh, S. (2007). History and origin. Lentil: An ancient crop for modern times.1-9.
Sarker, A., & Kumar, S. (2011). Lentils in production and food systems in West Asia and Africa. International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria. Grain Legumes,57, 46–48.
Sarker, A., Erskine, W., & Singh, M. (2003). Regression models for lentil seed and straw yields in Near East. Agricultural and forest meteorology,116(1-2), 61-72.
Sellami, M.H., Pulvento, C., Aria, M., Stellacci, A.M., &Lavini, A. (2019). A systematic review of field trials to synthesize existing knowledge and agronomic practices on protein crops in Europe. Agronomy, 9(6), p.292.
Sellami, M. H., Pulvento, C.,&Lavini, A. (2021). Selection of suitable genotypes of lentil (Lens culinaris Medik.) under rainfed conditions in south Italy using multi-trait stability index (MTSI). Agronomy. 11(9), 1807-1820.
Sharifi, P. (2020). Application of multivariate analysis methods in agriculturalsciences. Rasht branch, Islamic Azad University Press. 288 P. (In Persian).
Shobeiri, S., SadeghzadehAhari, D., Pezeshkpour, P.,&Azimi, M. (2021). Stability analysis of grain yield of Lens culinaris L. lentil genotypes in dryland conditions by GGE biplot method. Journal of Crop Breeding,13(40), 1-10.
Singh, D., Singh, C.K., Kumari, S., Singh Tomar, R.S., Karwa, S., Singh, R., Singh, R.B., Sarkar, S.K.,& Pal, M. (2017). Discerning morpho-anatomical, physiological and molecular multiformity in cultivated and wild genotypes of lentil with reconciliation to salinity stress. PLoS One, 12(5), p.e0177465.
Smith, A. B., Cullis, B. R.,& Thompson, R. (2005). The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches. The Journal of Agricultural Science. 143(6), 449-462.
Smirnov, N. (1948). Table for estimating the goodness of fit of empirical distributions. The annals of mathematical statistics, 19(2), 279-281.
Subedi, M., Khazaei, H., Arganosa, G., Etukudo, E., & Vandenberg, A. (2021). Genetic stability and genotype× environment interaction analysis for seed protein content and protein yield of lentil. Crop Science, 61(1), 342-356.
Tadesse, T., Sefera, G., Asmare, B., &Tekalign, A. (2021 a). AMMI analysis for grain yield stability in lentil genotypes tested in the highlands of Bale, southeastern Ethiopia. Journal of Plant Sciences, 9(1), 9-12.
Tadesse, T., Tekalign, A., &Asmare, B. (2021 b). Identification of Stable Lentil Genotypes Using AMMI Analysis for the Highlands of Bale, Southeastern Ethiopia. Chemical and Biomolecular Engineering, 6(4), 74-79.
Thennarasu, K. (1995). On Certain Non-parametric Procedures for Studying Genotype-Environment Inertactions and Yield Stability." PhD diss., IARI, Division of Agricultural Statistics, New Delhi.
Tullu, A., Diederichsen, A., Suvorova, G.,& Vandenberg, A. (2011). Genetic and genomic resources of lentil: status, use and prospects. Plant Genetic Resources, 9(1),19-29.
Wright, K. & J. L. Laffont. (2018). Package ‘GGE’. https://github.com/kwstat/gge/issues.
Yadav, N. K., Ghimire, S. K., Sah, B. P., Sarker, A., Shrestha, S. M., & Sah, S. K. (2016). Genotype x environment interaction and stability analysis in lentil (Lens culinarisMedik.). International Journal of Environment, Agriculture and Biotechnology, 1(3), 238539.
Yan, W., & Tinker, N. A. (2006). Biplot analysis of multi-environment trial data: Principles and applications. Canadian Journal of Plant Science, 86(3), 623-645.
Zaccardelli, M., Lupo, F., Campanile, F., Infantino, A., & Et, A., (2010). Leguminoseminori (cece, lenticchia, cicerchia, fava). Progetto di ricerca per potenziare la competitività di orticole in aree meridionali.73pp.
 
Plant Production and Genetics
Volume 5, Issue 2 - Serial Number 8
November 2024
Pages 183-200

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