Stability and Adaptability of Sorghum Hybrids Elucidated With Genotype–environment Interaction Biplots

Abstract

This study was conducted to compare the performance of ten sorghum hybrids at two locations (Maize and Millets Research Institute, Yusafwala, Sahiwal, MMRI) & Sorghum Research Sub-Station, Dera Gazi Khan, D.G. Khan) for two consecutive years (2015 and 2016), i.e. in a total of four environments (MMRI-15, MMRI-16, DG Khan-15 and DG Khan-16). The experiment was conducted in a Randomized Complete Block Design with a plot size of 4 × 0.75 × 2 m. In all four environments the crop was sown in July and harvested in December. Five plants were selected randomly from each plot for data collection. The following ranges were determined in the investigated traits; grain yield (2858.34-5266.33 kg ha-1), fodder yield (28663-45667 kg ha-1), days to 50% anthesis (76-81 days) and Brix value (8.28-18.42). Analysis of variance (ANOVA) estimates, generated by the biplot software were used for data interpretation. It was found that the influence of genotype, environment and G × E interaction was significant (P<0.05) for all traits in all environments. The data for all traits except Brix value were useful for further study. For grain yield and fodder yield, hybrid YSH-95 was the most suitable due to its higher yield and better stability. Sorghum Research Sub-Station Dera Gazi Khan (DG Khan), a non-discriminating location, were considered suitable for generally adapted hybrids and Maize and Millets Research Institute, Yusafwala, Sahiwal (MMRI), a more discriminating location, were considered best for specifically adapted hybrids. The results of which-won-where biplots showed that Lasani was the best general hybrid at both locations, whereas YSH-95 was the best hybrid for the specific environmental conditions at MMRI.

Evaluation of genotype × environment relationship in silage maize genotypes using biplot analysis and stability index

“…Comparison biplot model have been used to determine the optimal genetypes for adaptation studies. Similar results using the GGE Biplot model have been reported by several other researchers (Dehghani et al, 2006;Kaya et al, 2006;Akcura et al, 2011;Jalata, 2011;Rakhsit et al, 2012;Karimizade et al, 2013;Kendal and Sayar, 2016;Oral et al, 2018;Muntaz 2019).The stability of the genotypes in dry matter yield was assessed using the biplot (Figure 17). The ASV indicated variations in dry matter yield stability among five maize hybrids (Table 6).…”

“…The study conducted in the same environment for six years showed that the years were different from each other in terms of herbage yield of maize genotypes ( Figure 6). The effect of this method on the environment is different from each other (Yan and Tinker 2006;Putto et al, 2008;Ahmadi et al, 2012;Muntaz et al, 2019).…”

“…The first mega environment is the ideal test environment for the DKC7221 genotype and the second mega environment is ideal for the herbage yield of PR31Y43, Burak and SAMADA07 maize hybrids (Figure 7). A similar approach for the mega environment identification and specific adaptation were used by Yan et al (2000), Yan and Rajcan (2002), Yan and Tinker (2006), Putto et al (2008); Ahmadi et al (2012) and Muntaz et al (2019).…”

Effects of Heat Stress on Growth, Physiology of Plants, Yield and Grain Quality of Different Spring Wheat (Triticum aestivum L.) Genotypes

“…Therefore, these two clusters could be used in hybridization programs to broaden the genetic basis of germplasm, and top entries from cluster-2 could be directly resealed for general cultivation if their performance in multilocation trials remains as good as in this experiment. Several researchers used cluster and biplot analysis to characterize genotypes under the different environmental conditions and found these tools quite useful [42,43].…”

Stability Analyses for Interpreting Genotype by Environment Interaction of Selected Oriental Tobacco Landraces

“…In addition to classical methods, different stability analyzes such as multivariate analysis (Westcoff, 1987), cluster analysis (Crossa et al, 1991), regression analysis (Gauch, 1988), additive main effects and multiplicative interaction model (Gauch, 1992) are used to explain the genotype x environment interaction. The most powerful and optimal technique recently used is the genotype x environment biplot technique owing to providing a visual presentation of the interactions (Yan et al, 2001;Dehghani et al, 2006;Mumtaz et al, 2019). Tobacco selection in the natural population do not allow to obtain a new genotype, only an existing individual is highlighted.…”