用形态测量法预测墨西哥本土鹦鹉的体重

Pub Date : 2020-04-01 DOI:10.12706/itea.2020.003
Rodrigo Portillo-Salgado, F. Cigarroa-Vázquez, J. Herrera-Haro, Ignacio Vázquez-Martínez
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引用次数: 1

摘要

本研究的目的是利用分类和回归树分析(CART)对墨西哥本土瓜罗特(NMG)的形态测量(MM)和形态指标进行体重预测。对来自普埃布拉州、恰帕斯州和坎佩切州的244名新移民采取了措施。采集体重和10 MM,对体重(MAS)、粗度(STK)和体况(CON) 3个形态学指标进行估计。对各变量进行描述性统计和Pearson相关(r)分析,并采用CART方法构建回归树。MM的变异系数<20%,MAS为13.50%,STK为111.12%,CON为16.81%。体重与MM的相关性从中等到高度不等(r = 0.35 ~ r = 0.91;P < 0.0001)。在标准化重要性分析中,CON是得分最高的变量(100%),其次是MAS(79.2%)和胸围(52.8%)。最优回归树图共形成13个节点,其中7个为终端节点,说明CON足以预测NMG的BW。本研究定义了一个包含CON、体高和翼宽的预测模型,其观测解释方差为86.4%,可为生产者可靠地预测NMG体重提供依据
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Predicción del peso corporal de guajolotes nativos mexicanos a través de medidas morfométricas
The aim of this study was to evaluate the prediction of body weight (BW) of the native Mexican guajolote (NMG) from morphometric measurements (MM) and morphological indices using classification and regression tree analysis (CART). Measures were taken of 244 NMG from the states of Puebla, Chiapas and Campeche. The BW and ten MM were collected, and three morphological indices were estimemated: massiveness (MAS), stockiness (STK) and body condition (CON). The descriptive statistics and Pearson’s correlation (r) of the variables were analyzed and a regression tree was constructed using the CART method. Coefficients of variation <20% were obtained in the MM, an MAS of 13.50%, STK of 111.12% and the CON of 16.81%. Correlations between BW and MM ranged from moderate to high (r = 0.35 to r = 0.91; P < 0.0001). The CON was the variable with the best score (100%) in the normalized importance analysis, followed by MAS (79.2%) and thoracic perimeter (52.8%). The optimal regression tree diagram formed a total of 13 nodes, of which 7 were terminal nodes, demonstrating that the CON is sufficient to predict the BW of NMG. This study allowed to define a prediction model with an observed explained variance of 86.4% and included the CON, body height and wing width, which can be applied by producers to reliably predict body weight of NMG
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