Analysis of Indian post-rainy sorghum multi-location trial data reveals complexity of genotype × environment interaction

Abstract

SUMMARYSorghum [Sorghum bicolor (L.) Moench] grown in India is of two adaptive types: rainy and post-rainy. The post-rainy sorghum is predominantly consumed by humans. While releasing new cultivars through multi-location testing, major emphasis is given to the superiority of new cultivars over existing cultivars, with very little emphasis on the genotype × environment interaction (GEI). To understand the complexity of GEI in post-rainy sorghum testing location trials, the multi-location evaluation data of two post-rainy seasons (2009/10 and 2010/11) under the All India Coordinated Sorghum Improvement Project were analysed. In both years, location explained the highest proportion of total sum of squares followed by the GEI effect and main effect of genotype. Additive main effects and multiplicative interaction (AMMI), stability values (ASV) and genotype + genotype × environment interaction (GGE) instability values recorded high correlation resulting in identification of the best performing cultivars. However, the rank correlations were lower, though still significant. A mixture of crossover and non-crossover GEI was a common occurrence in both years. ‘Which-won-where’ analysis suggested the existence of four possible mega-environments (ME) among post-rainy testing locations, with a few non-informative locations within ME. Mega-environments are characterized by soil type, rainfall pattern and moisture conservation practices. The present study indicated the possibility of reducing the number of test locations by eliminating non-representative highly correlated locations and suggested the need to breed for location-specific genotypes rather than genotypes with wider adaptability.

Yield and nutritional value of biomass sorghum (BRS 716) managed in different row spacing and maturity at harvest in the semiarid region of Brazil

“…In many regions of the world, in recent years, Sorghum [Sorghum bicolor (L.) Moench] has become an increasingly important forage crop (Qu, Liu, Dong, Lu, & Shen, 2014;Amelework, Shimelis, Tongoona, Mark Laing, & Mengistu, 2015;Rakshit et al, 2016;Perazzo et al, 2017;Mwamahonje & Maseta, 2018;Worede, Mamo, Assefa, Gebremariam, & Beze, 2020). This trend is a consequence of the high dry matter yield of sorghum and its ability to adjust to different climatic and soil conditions, which include hot weather, such as in the semiarid region (Perazzo et al, 2017;Mwamahonje & Maseta, 2018;Borges et al, 2019;Ramos et al, 2021;Rigueira et al, 2021), or relatively cold climates, like Canada, Korea (McCaughey, Therrien, & Mabon, 1996;Paradhipta et al, 2019).…”

Assessment of plasticity and stability of grain sorghum varieties on the basis of their grain yield

“…In Russia [1,3,[12][13][14][15][16][17][18] and other countries [11,[19][20][21][22][23][24][25][26], the leading breeders attached great importance to adaptive selection in their studies. Assessment of adaptability, ecological plasticity and stability of varieties by different methods, their application in different climatic conditions is an actual direction of the selection process.…”

Additive main effects and multiplicative interaction and yield stability index for genotype by environment analysis and wider adaptability in Barley

“…The Additive Main Effects and Multiplicative Interaction (AMMI) is a biplot based graphical unique linear-bilinear model and combines both of the above approaches of ANOVA and multiplicative models (Gabriel 1971;Gauch 1988;Yan et al 2007). AMMI model is an efficient method to study stable genotypes and discriminating environments and widely used in several studies (Nurminiemi et al 2002;Mortazavian et al 2014;Sousa et al 2015;Raggi et al 2017;Rakshit et al 2017). It displays main effects, environment (E) main effects, and genotype by environment interaction effects on a biplot and helpful for the plant scientists to see and judge desirable genotypes and environments (Gauch 2006;Gauch et al 2008).…”