Deciphering genotype performance, genotype and environment interaction of seed cotton yield and ginning outturn using GGE biplot for selection of Gossypium hirsutum for rainfed ecosystem

Abstract

Background Cotton is mostly grown under rainfed condition by small and marginal farmers and provides economic livelihood. The assessment of adaptability of a suitable genotype is important and therefore, multilocation evaluation of genotypes was conducted at eight agro-ecologically diverse environments under rainfed ecosystems in India. The data was analyzed for key biometrical traits using pooled ANOVA, LSD test, correlation matrices and regression analysis over two years (2019-20). Additionally, we employed genotype plus genotype by environment interaction (GGE) biplot analysis to identify winning genotypes across different environments. Results The results showed that genotype, environment and their interaction (GEI) significantly (p < 0.01) influenced SCY and GOT%. The GEI showed a high significant impact on SCY (40.46%) and GOT% (48.86%) among genotypes. Correlation analysis revealed positive associations between SCY and major yielding traits such as boll weight, ginning outturn and lint yield. Regression analysis demonstrated that a combination of these traits contributed to high stable yield over the years across the rainfed conditions. The total variation in SCY was 96.61%, composed of PC1 and PC2 values at 92.06% and 4.55%, respectively. GGE biplot analysis identified the genotypes viz., NDLH2057-1, TVH007, and NH615 exhibited high yield potential and ginning outturn and high stability across multilocations. The average environment axis (AEA) of the biplot identified most representative location for the yield and GOT%, respectively. Conclusion The findings identified the use of optimal genotypes for cultivation and use of such genotypes for trait introgression in future breeding and crop improvement, which may facilitate genetic gain of yielding traits and ginning outturn in rainfed environments.