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Selection of Stable Cultivars Using Phenotypic Variances

Dep. of Agronomy and Soils and Alabama Agric. Exp. Stn., Auburn Univ., AL 36849-5412

^* Corresponding author (jmosjidi{at}ag.auburn.edu).

Genotype-environment interactions reduce the correlation between phenotype and genotype and decrease selection progress. Type 1 stability measures (simple variance across environments S²_i and related coefficient of variability CV_i) are biased because they do not distinguish the effects of locations and years. We propose the unbiased estimate of phenotypic variance (V_p) and phenotypic coefficient of variability (PCV_i) as an alternative to S²_i. The V_p, unlike S²_i and Type 4 stability measure MS Y/L (years-within-location mean square), includes location, year within location, and error variance components from analysis of variance based on a linear model. The F-test can be used to classify cultivars into location unstable, year unstable, or both location and year unstable, or vice versa. The actual model used in data analyses was based on the mean across replications in each environment (P_ij.) because the plot (replication) data were not available. Hence, the corresponding V_p and PCV_i were denoted as V^'_P and PCV^'_i. The V^'_P underestimates V_p. Monte Carlo simulation was used to evaluate the performance of V^'_P and S²_i . A wheat (Triticum aestivum L.) data set was used to demonstrate the calculation of the above parameters. The results from rank correlation showed that V^'_P was correlated to MS Y/L, the regression coefficient (b_i), PCV^'_i , and S²_i (P < 0.05). The V^'_P was not correlated to the residual mean square of deviation from the regression (#x03B4;²_i). The V^'_P and S²_i had similar sampling errors. When less than 18 locations and 6 years are used, V_e is particularly useful since S²_i is biased.

Received for publication March 10, 1995.

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