Stability and adaptability of grain sorghum hybrids in the off-season

Abstract

ABSTRACT. We analyzed productivity data obtained from experiments on grain sorghum conducted in 7 locations of its cultivation in Brazil. A total of 25 hybrids were analyzed, of which 22 were pre-commercial and 3 were cultivars. The Wricke and Purchase et al. methods were highly consistent in identifying individuals with low contributions to genotype x environment interactions. The Lin and Binns method proved to be easily applicable and interpretable but it was not efficient in detecting individuals with specific adaptations. An additive main effect and multiplicative interaction (AMMI) model indicated the suitability of cultivar 1G282 for the cities of Guaíra, Sete Lagoas, and Vilhena, and hybrids 0307087 and 0307091 for the southeast of Goiás. The associations of the Eberhart and Russell method with AMMI indicated that 0307071, 0307131, 0307511, 7627Grain sorghum hybrids stability and adaptability ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 13 (3): 7626-7635 (2014) and 0307651 showed adaptability to favorable environments. Hybrid 0009061 stood out as the most adaptable and stable cultivar.

Genotype-Environment Interaction: Trade-Offs between the Agronomic Performance and Stability of Dual-Purpose Sorghum (Sorghum bicolor L. Moench) Genotypes in Senegal

“…This indicates that these genotypes responded differently to environments, thereby confirming phenotypic diversity among the genotypes assessed. These results are in agreement with previous findings on sorghum [25][26][27][28]. In general, yields were higher for sowing date 1 than for sowing date 2, showing the potential importance of a longer cycle time and the existence of a photoperiod response of several of the sorghums studied, as already demonstrated in West Africa [29].…”

Genetic Variability and Yield Performance of Sorghum

“…Furthermore, the GxE was also very highly significant (p≤ 0.0001), showing inconsistencies in the performance of sorghum genotypes across locations which shows difference in the response of sorghum genotypes at different environments. This outcome is in agreement with the findings of (Kenga et al, 2003;Asfaw, 2007;Almeida et al, 2014;Abiy and Firew, 2016). The result of the combined variance components showed that the total variation in yield was attributed to location (86.4%), genotype (1.9%) and GxE (10.9%) effects (Table 4).…”

“…This indicates that the high diversity of the growing conditions in the three locations and the small variability in the genotypes for grain yield performance. Significant effect of location on yield of sorghum varieties was reported by (Asfaw, 2007;Maposa et al, 2010;Almeida et al, 2014;Abiy and Firew, 2016;Lyle et al, 2016). Furthermore, the GxE was also very highly significant (p≤ 0.0001), showing inconsistencies in the performance of sorghum genotypes across locations which shows difference in the response of sorghum genotypes at different environments.…”

Identification of sorghum hybrids with high phenotypic stability using GGE biplot methodology

“…This makes it difficult to recommend cultivars, since those adapted to growth under a specific condition do not exhibit superior performance under different environmental conditions. This differential response of genotypes in different environments is known as the genotype x environment interaction (GE), and when recommending sorghum cultivars in the face of GE, it is necessary to annually test a large number of genotypes in different environments before the final recommendation and multiplication is made (Almeida Filho et al, 2014). However, despite its importance, the simple GE interaction analysis does not provide complete and accurate information about the behavior of each genotype in various environmental conditions.…”