Interrelationship among and repeatability of seven stability indices estimated from commercial cotton (Gossypium hirsutum L.) variety evaluation trials in three Mediterranean countries

Abstract

Multi-environment trial data are required, to obtain variety stability performance parameters as selection tools for effective cultivar evaluation. The interrelationship among seven stability parameters and their association with mean yield, along with the repeatability of these parameters across consecutive years was the objective of this study. Cottonseed yield data of 31 cotton cultivars, proprietary of Delta and Pine Land Co and other companies, evaluated in 20 locations over the 1999-2005 year period in Greece, Spain and Turkey were used for combined analysis of variance in four datasets. Across locations in a single evaluation year (dataset A), across locations in each of two single consecutive evaluation year (dataset B), across locations and two consecutive years (dataset C) and across locations and three consecutive years (dataset D). For each dataset, cultivar phenotypic variance (sigma(2)(p)) was appropriately partitioned in its components and the h(2) and sigma(2)(ge) component estimated. Furthermore, following the appropriate stability analysis b(i); sd(i)(2), sigma(2)(i); YS(i) and AMMI1 along with the GGE Biplot distance (GGED) and instability (GGEIN) parameters were obtained. The interrelationship among the parameters and their association with mean yield based on Spearman rank correlation was studied in each of the seven single evaluation years (dataset A). Rank correlation coefficients were also used as estimates of the repeatability of these stability parameters across consecutive year combinations (dataset B, C and D). The parameters GGED and YS(i) were consistently highly correlated with each other and mean yield in five out of seven single evaluation years. The data provided evidence that single year evaluation across locations might be sufficient to reliably rank cotton cultivars, based on mean yield along with GGED and YS(i). Combined analysis across two consecutive years (dataset C) was more effective as compared to single year evaluation. GGED was relatively more repeatable than YS(i) and mean yield in single (dataset B) and 2-year comparisons (dataset C). Although GGED is an index depended and proportional to yield, provides a superior way to integrate mean performance and stability into a single measure, which can be assessed visually on biplots. Regarding the other stability parameters, the results were contradicting and of low repeatability across single years and two consecutive years. Cultivar evaluation combined across locations in 3 years did not improve the repeatability of cultivar variance effects but resulted in very high repeatability of GGED, YS(i) and mean yield.