Dataset For Combining Ability of Earliness and Yield in Sweet Corn Using GGE Biplot

Description

Based on analysis of variance (ANOVA) combining ability line x tester, replication, genotypes, line, tester, and line x tester, showed significant results (P> 0.01) for both earlines and yield traits. The emergence of significance in line x tester, indicates a high specific combining ability (SCA). This is influenced by non-additive genes more than additive genes. Furthermore, based on the GGE biplot "Mean vs. Stability" pattern on yield and earlines traits determine pattern ranks genotypes and identifies genotypes that have good combining ability. The highest GCA is the entry located at the end based on the projection direction of the "mean vs stability" biplot. The results showed the highest GCA on character yield were L20, L6, L3, L18, L19, L2, L10. L12. 17, and L15, while the earliness were L15, L3, L14, L5, L4, L9, and L16. Thus, the GGE biplot "Which Won Where" pattern visualizes the interaction between line and tester. This method can show which lines perform best in a specific tester. Good specific combining ability (SCA) is determined based on the location of entries and testers in the same sector based on the appearance of the scatter plot. Genotypes selected based on Specific Combining Ability (SCA) on yield trait are shown by L6xT1, L18xT1, L2xT1, L19xT1, L12xT1, L17xT1, L10xT2, L14xT2, L12xT2, and L20xT2. While the earliness trait is shown by L3xT1, L14 x T1, L4xT1, L9xT1, and L5xT2.

Steps to reproduce

Data collection was conducted by measuring the observation variables, namely earliness and yield. The earliness observation variable was measured by counting the number of days from the time of planting until the plants produce ready-to-harvest cobs, which is when the cobs enter the milk-ripe phase characterized by full seeds, shiny light yellow in color, and when pressed releases a milky liquid. Measurement of yield parameters was carried out by weighing the weight of sweet corn yields in one plot using analytical scales and then converted into units of tons.ha-1. Data analysis of combining ability based on line x tester was described by Singh and Chaudary. Combining ability analysis based on GGE biplot used model equation biplot analysis line x tester based on Yan. Combining ability analysis based on ranking plot. Ranking plot is formed from the average tester coodination (ATC) component which consists of the average tester center, ATC axis and ATC ordinate. The highest GCA is the entry that is located at the end based on the projection direction of the ATC axis. The best SCA can be determined based on the location of entries and testers in the same sector based on the scatter plot display.

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