Abstract
Genotype × Environment (G×E) interaction and stability performance were investigated on paddy yield of eighteen rice genotypes and twelve locations using two well renowned statistical models; genotype main effect and G×E Biplot analysis (GGE) and additive main effects and multiplicative interaction (AMMI) analysis. The aim of this study was to elucidate the performance of some advance rice lines/genotypes at multiple locations in multi environment trials (METs) using GGE biplot and AMMI analyses. The results of GGE biplot and AMMI analyses performed over the data of paddy yield at multiple locations of two years 2014 and 2015 indicated that G×E interaction plays a crucial role in determining the performance of genetic material in METs. The results declare that GGE and AMMI not only provide easy and affective evaluation of genotypes into environment interactions in a number of locations but also a comprehensive understanding of the variability of the target locations. AMMI analyses for data of both years indicated that RRI 7 was the highest priority selected genotype for six locations, NIAB 1175 for four and RRI 3 for three locations. Dhokri and Kala Shah Kaku were the highest yielding, while Faisalabad and Dhokri were the most stable environments in 2014. Likewise, Faisalabad and PARC Islamabad were the highest yielding as well as most stable environments in 2015. Basmati 515 and PS 2 were the most favorable genotypes in 2014 and 2015, respectively for their high paddy yield and stability at all locations. The results further suggested that both models were useful and presented similar interpretations about MET data. Key words: Genotype main effect and G × E biplot analysis (GGE), additive main effects and multiplicative interaction (AMMI) analysis, rice, fine type, multiple locations.
Highlights
Rice is being used as staple food by more than three billion of world population which represents 50 to 80% of their daily calorie intake (Khush, 2005; Amirjani, 2011)
Genotype × Environment (G×E) interaction and stability performance were investigated on paddy yield of eighteen rice genotypes and twelve locations using two well renowned statistical models; genotype main effect and G×E Biplot analysis (GGE) and additive main effects and multiplicative interaction (AMMI) analysis
The results of GGE biplot and AMMI analyses performed over the data of paddy yield at multiple locations of two years 2014 and 2015 indicated that G×E interaction plays a crucial role in determining the performance of genetic material in multi environment trials (METs)
Summary
Rice is being used as staple food by more than three billion of world population which represents 50 to 80% of their daily calorie intake (Khush, 2005; Amirjani, 2011). In Pakistan, rice was grown on approximately 2.89 million hectares with a total production of 7.01 million tonnes and earned a foreign exchange of worth US$ 1.53 billion. With the passage of time, due to drastic climatic changes, there are developing vast differences in agro-climatic conditions among different locations of Pakistan These phenomena make new developing rice varieties more unstable when grown under diverse environmental conditions and results in poor yield (Duncan, 1955)
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