建立西部牧场野火烟雾与成品肉牛性能指标之间的关系。

IF 1.3 Q3 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Translational Animal Science Pub Date : 2024-03-04 eCollection Date: 2024-01-01 DOI:10.1093/tas/txae022
Arturo Macias Franco, Aghata Elins Moreira da Silva, Graham Holton, Tio Brody, Mozart Alves Fonseca
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引用次数: 0

摘要

因果关系的识别非常复杂。研究人员通常会忽略关系背后的因果关系,从而产生误导性关联。在此,我们仔细研究了内华达州里诺市两年内野火烟雾暴露与动物表现和行为指标之间的参数关系和因果关系。2020 年烟雾季节的动物是谷物饲养(n = 12)和草饲养(n = 12),而 2021 年烟雾季节的动物采用相同的日粮饲养,但使用激素植入物(n = 9)或不使用激素植入物(n = 9)。数据集包括饲料摄入量(FI)、体重(BW)、饮水量(WI)、平均日增重(ADG)和饮水行为(饮水时间 [TSD];饮水事件 [WIE];无饮水事件 [NWIE])的每日记录。利用可变树长贝叶斯加性回归树(BART)研究空气质量指数(AQI)、空气中 2.5 μm 颗粒物(PM2.5)和 10 μm 颗粒物(PM10)、空气中二氧化氮(NO2)、二氧化硫(SO2)、臭氧(Ozone)和一氧化碳(CO)水平(传感器 P2.5(P 2)、CO 和 PM10(P 2))之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishing the relationship between wildfire smoke and performance metrics on finished beef cattle in Western Rangelands.

Identifying causal relationships is complicated. Researchers usually overlook causality behind relationships which can generate misleading associations. Herein, we carefully examine the parametric relationship and causality between wildfire smoke exposure and animal performance and behavior metrics over a period of 2 yr in Reno, Nevada. The animals in the 2020 smoke season were grain-finished (n = 12) and grass-finished (n = 12), whereas the animals during the 2021 season were fed under the same diet but finished with either a hormonal implant (n = 9), or without (n = 9). The dataset included daily records of feed intake (FI), body weight (BW), water intake (WI), average daily gain (ADG), and WI behavior (time spent drinking [TSD]; water intake events [WIE]; no-WIE [NWIE]). Variable tree length Bayesian additive regression trees (BART) were utilized to investigate the relationships between air quality index (AQI), particulate matter 2.5 μm (PM2.5) and 10 μm (PM10), NO2, SO2, Ozone, and CO levels in the air (sensors < 1.6 km from animals) with the animal data. Additionally, linear mixed models with a 7-d lag were used to evaluate parametric relationships among the same variables. All statistical analyses were performed on R Statistical Software (R Core Team 2023). Under the linear mixed model with a 7-d lag, significant positive and negative associations were found for all parameters examined (P < 0.05). Negative associations were found between FI, WI, ADG, BW, WIE, NWIE, TSD, and PM2.5 (P < 0.05) for at least one animal group. Positive linear associations between wildfire smoke parameters and the metrics evaluated were more variable and dependent on year, treatment, and smoke parameters. When examining the credible intervals and the variable importance in the BART, relationships were more difficult to identify. However, some associations were found for Ozone, AQI, NO2, CO, and PM10 (P < 0.05). Overall, our results carefully examine the relationship between smoke parameters and cattle performance and present interesting pathways previously unexplored that could guide early culling/finishing of animals to avoid economic losses associated with performance decrease in response to wildfire smoke exposure. Though interesting associations are found under linear mixed models, causality is difficult to establish, which highlights the need for controlled exposure experiments.

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来源期刊
Translational Animal Science
Translational Animal Science Veterinary-Veterinary (all)
CiteScore
2.80
自引率
15.40%
发文量
149
审稿时长
8 weeks
期刊介绍: Translational Animal Science (TAS) is the first open access-open review animal science journal, encompassing a broad scope of research topics in animal science. TAS focuses on translating basic science to innovation, and validation of these innovations by various segments of the allied animal industry. Readers of TAS will typically represent education, industry, and government, including research, teaching, administration, extension, management, quality assurance, product development, and technical services. Those interested in TAS typically include animal breeders, economists, embryologists, engineers, food scientists, geneticists, microbiologists, nutritionists, veterinarians, physiologists, processors, public health professionals, and others with an interest in animal production and applied aspects of animal sciences.
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