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

Published: 5 February 2024| Version 2 | DOI: 10.17632/5dkk9gjsth.2
Contributors:
Fakhri Nasharul Syihab,
, Ade Ismail,
,
,
,
,
,

Description

The data can be used to analyse both general and specific combine ability based on line x tester analysis. Set data include raw data, Table of analysis of variance (ANOVA) for combining ability and Figure of GGE biplots for lines and hybrids of both earlines and yield traits. Thus, genotypesto be selected based on Specific Combining Ability (SCA) on both yield and earliness were also shown.

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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.

Institutions

  • Universitas Padjadjaran Fakultas Pertanian

Categories

Agricultural Science, Crop Science, Plant Breeding, Biometrics in Plant Breeding

Funders

  • Academic Leadership Grant of Universitas Padjadjaran
    Grant ID: 1549/UN6.3.1/PT.00/2023

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