Abstract

Due to environmental diversity, genotype performance for yield and stability is essential for crop improvement. The GGE biplot, and 11 parametric and non-parametric stability models were employed to evaluate 23 wheat (Triticum aestivum L.) genotypes, tested in randomized complete block trials across two contrasting fields (sandy and loamy) and four seasons. The sandy field yielded half compared to the loamy field, reflecting relatively low- and high-input environments, respectively. Analysis of variance showed significant differences between genotypes for grain yield and crossover genotype ranking across environments; the loamy field was more representative of an overall genotype performance. The stability models resulted in diverse genotype classification and were distinguished into two separate groups. The first group comprised measures that consider both G and GE focusing on the agronomic aspect of stability and high-yielding ability. The second group included tools that consider only GE focusing on the static aspect of stability and characterized most of the high-performing genotypes as undesirable. The GGE biplot highlighted genotypes that were characterized as either desirable or undesirable following most models in both groups. Therefore, the GGE biplot presented an effective statistical tool for assessing wheat genotypes in terms of general and specific adaptation without overlooking yielding ability. It is suggested the preference of favorable experimental conditions and application of the GGE model to identify genotypes that are more promising for stable performance across wide agroecosystems.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call