热带干旱林条件下生长的UN cotovovaya (Carica papaya L.)品种的形态多样性

Ruby Alejandra Loaiza Ruiz, Julián David Otalvaro Gutiérrez, José Régulo Cartagena Valenzuela, Carlos Felipe Barrera Sanchez, Oscar de Jesús Córdoba Gaona
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摘要

本工作旨在描述联合国cotovovaya品种的形态多样性,以识别可用于获得新的地方栽培品种的优秀植物。选取18个个体,采用多元非分层聚类技术对数据进行分析。采用多项式回归模型描述生长作为生长度天数的函数。方差分析发现,大多数形态变量在植物之间存在显著差异。Pearson相关性呈线性相关;各变量均与株高呈高度相关(> 0.82)。霍普金斯和Gap的统计数据确定了两种聚类:从所有参数来看,发展程度较高的“D”组和发展程度较低的“A”组。对株高的拟合效果最好的是二阶多项式模型,其余的均为三阶模型。评价变量的非线性函数模型不显著,“缺乏拟合”值大于0.05。研究结果可为木瓜选育提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Morphological diversity of the UN Cotové papaya (Carica papaya L.) variety grown under tropical dry forest conditions
This work aimed to describe the morphological diversity of the UN Cotové papaya variety to identify outstanding plants that can be used to obtain a new local cultivar. 18 individuals were selected, and the multivariate non-hierarchical cluster technique analyzed data. A Polynomial regression model was carried out to describe growth as a function of growing degree days. The ANOVA identified significant differences between plants for most morphological variables. The Pearson correlation showed linear dependence; all the variables had a high correlation (higher than 0.82) with plant height. The Hopkins and Gap statistic determined two clusterings: Gropu "D" with higher development and group "A" with less development for all parameters. Second-order polynomial model were the best fit for the plant height, and third-order models were the best fit for the others. The non-linear functional models were not significant for the evaluated variables, presenting "Lack of Fit" values greater than 0.05. The results provided information for selecting plants with outstanding characteristics that can be used in the papaya breeding program.
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