Utilization of multi-locational pigeonpea performance data for determination of stability parameters

Multi-locational data on medium duration pigeonpea varieties in Eastern and Southern Africa was analyzed for genotype performance. The objective was to utilize multi-locational data to identify superior genotypes. The study also aimed at ranking the pigeonpea varieties using different yield based stability parameters. The relationship between temperature and performance of these varieties was also evaluated. Data were obtained from trials conducted at research stations in Kenya, Uganda, Tanzania, Malawi and Mozambique by the International Crops Research Institute for the Semi-Arid Tropics. Seven common genotypes were selected from data collected between 1997/98 to 2009/2010 crop seasons to constitute 22 environments. Analysis of variance, Eberhart and Russell, AMMI and GGE biplot models were used to evaluate genotype by environmental interactions. In addition, analysis was done to test the relationship between crop performance visà-vis mean maximum and minimum temperature during crop growth period. Analysis of variance showed that genotype by environmental interaction was significant (p<0.001). Different stability parameters gave different genotype rankings. Eberhart and Russell model ranked genotypes ICEAP 00550 as the most stable genotypes, AMMI model ranked ICP 6927 as the most stable genotype while ICEAP 00068 was ranked as the most stable genotype by GGE biplot. Considering ranking by the three models the three most stable genotypes were found to be ICEAP 00550, ICP 12734 and ICP 6927. Temperature, showed a significant relationship with crop performance(p<0.001). Recommendations were that stable genotypes should be subjected to on farm national performance trials for adoption. Temperature could be considered by scientists when predicting duration from planting to flowering and maturity.