统计分析替代方案,以验证血液参数在热带条件下的乳制品

R. Campos, Mauricio Vélez, K. García, Adriana Correa, Angela Lizeth Ordoñez
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引用次数: 0

摘要

在6项试验研究的基础上,对热带条件下放牧奶牛的血液参数进行了分析。主要目标是确定可用于研究生理、环境或遗传变异的统计分析方法。分析的参数是红细胞压积、血红蛋白浓度和多形核细胞(即嗜酸性粒细胞、嗜碱性粒细胞、中性粒细胞和淋巴细胞)的计数。最初分析了972头成年奶牛的数据,这些奶牛的产量在当地乳制品生产中被认为是中高的。经过信息滗析过程,使用了415条记录。这些数据对应于从产犊前30天到产后105天的采样期,每两周进行一次测定。每两周采集一次血液,每一刻被定义为一个周期。在搜索中应用了不同的分析技术,以便从数据中提取最佳信息,以便将来重用。最佳的分析类型对应于随机森林(RF)技术、聚类和方差分析。分析了能量代谢指标(非酯化脂肪酸)和蛋白质代谢指标(总蛋白)在10个采集期、3个品种组和3种营养管理方式下对血液指标的影响。使用多元相关和机器学习方法从数据中提取信息。结果表明,近距离干牛、过渡期和泌乳第一阶段的血液学行为发生了变化。各变量间无显著正相关或负相关。红细胞压积和血红蛋白水平可以通过与代谢指标和血液成分相关的变量来估计。需要进一步的研究来阐明奶牛在过渡时期的血液行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical analysis alternatives to validate hematic parameters in dairy under tropical conditions
The hematic parameters of cows selected for milk production in grazing under tropic conditions were analyzed based on six experimental studies. The major objective was to determine statistical analysis alternatives that could be used in the study of physiological, environmental or genetic variations. The parameters analyzed were hematocrit, hemoglobin concentrations and counts of polymorphonuclear cells (i.e., eosinophils, basophils, neutrophils and lymphocytes). Initially 972 data from adult cows with productions considered medium-high in the context of local dairy production were analyzed. After the information decanting process, 415 records were used. These data corresponded to a sampling period from 30 days before calving to day 105 postpartum, with determinations made fortnightly.  Blood collection was made every two weeks and each moment was defined as a period. Different analytical techniques were applied in searching to extract the best information from the data and that could be reused in the future. The best type of analysis corresponded to the Random Forest (RF) technique, clustering, and analysis of variance.The effect of an indicator of energy metabolism (non-esterified fatty acids - NEFA), an indicator of protein metabolism (total protein - TP) of 10 collection periods, three breed groups and three types of nutritional management given to the animals on the blood variables were analyzed. Multivariate correlation and machine learning methods were used to extract information from the data. Results indicated that hematological behavior change throughout close up dry cow, transition period and first phase of lactation. No high direct or inverse correlation were found among variables. Hematocrit and hemoglobin levels can be estimated from variables associated with metabolic indicators and blood components. Further studies are required to elucidate the hematic behavior of dairy cows during the transition period.
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