Repeatability coefficient for the determination of the optimal number of harvests for the selection of zucchini hybrids

• Autor(a) principal: Maria Elisângela Ferreira de Oliveira
• Data de Publicação: 2022
• Outros Autores: Valter Carvalho de Andrade Júnior, Orlando Gonçalves Brito, Sebastião Márcio Azevedo, Jeferson Carlos de Oliveira Silva, Eduardo Alves da Silva, Alcinei Mistico Azevedo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFMG
• Texto Completo: https://doi.org/10.1590/S1678-3921.pab2022.v57.03016; http://hdl.handle.net/1843/59592; https://orcid.org/0000-0002-8018-6399; https://orcid.org/0000-0002-5010-7725; https://orcid.org/0000-0001-6238-1644; https://orcid.org/0000-0002-2992-5379; https://orcid.org/0000-0002-1411-280X; https://orcid.org/0000-0003-2120-8188; https://orcid.org/0000-0001-5196-0851
• topic: Abobrinha-italiana; Melhoramento genético; Biometria

The objective of this work was to estimate the optimal number of harvests for the reliable selection of zucchini (Cucurbita pepo) hybrids through the repeatability coefficient. The experimental design was randomized complete blocks with 33 treatments (31 experimental hybrids and 2 commercial ones) and four replicates, with six plants per plot. Fifteen harvests were carried out. Seven morphoagronomic fruit characteristics were evaluated, and repeatability coefficients were estimated using four statistical methods. The repeatability coefficients ranged from low to moderate, regardless of the studied characteristic. For a high-precision selection (R2≥90%), a high number of evaluated harvests was required, especially for traits related to fruit yield, as follows: 30 to 54 harvests for selection based on total yield; and 43 to 83 harvests for commercial yield, which varied according to the statistical estimation method. The principal component analysis based on the covariance matrix required the least number of harvests for a satisfactory selection precision. Fifteen harvests are sufficient for a satisfactory selection of all evaluated characteristics, with a precision above 70%.