Cow-calf operation management clusters, Argentina.

IF 1.8 Q3 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Translational Animal Science Pub Date : 2025-09-06 eCollection Date: 2025-01-01 DOI:10.1093/tas/txaf110
Vanesa A Vistarop, Alejandro J Larriestra, Claudina Vissio, Federico Demateis Llera, Graciela N Yaful, Carlos J Blanco, Julián A Bartolomé
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引用次数: 0

Abstract

This research was conducted to gain more insight into the productivity and good management practice (GMP) adoption of cow-calf operations in Río Negro Province, Argentina. The objectives were to characterize productivity and management profiles according to GMP adoption, identify herd clusters, and describe the performance and productivity within each specific cluster. A survey sample of 142 out of 1,229 cow-calf and cow-calf to-finish operations from Avellaneda and Pichi Mahuida counties provided data on productivity, herd structure, and GMP adoption. The productivity variables, calves per 100 cows (C/100 c) and calves per 100 ha (C/100 ha), were described statistically using quartiles, and differences by county according to the 3-month breeding season adoption were explored. Moreover, herd structure and GMP-related variables were subjected to multiple correspondence analysis (MCA) with complete-link hierarchical cluster analysis to typify the operations. A total of 127 out of 142 farmers provided productivity data, showing median values of 79.00 C/100 c (Q1 = 67.00; Q3 = 85.00) and 4.58 C/100 ha (Q1 = 2.78; Q3 = 8.00). A Significant difference was found between 3-month and year-round breeding operations for both variables (82.00 C/100 c vs 75.50 C/100 c; P = 0.0006 and 5.60 C/100 ha vs 3.97 C/100 ha; P = 0.0072). Three farm clusters (Cl) were identified: Cl 1 (low adoption), Cl 2 (moderate transition), and Cl 3 (GMP-oriented). Cl 3 showed the highest GMP adoption level, and a significant difference was found in the C/100 c variable (85.00 C/100 c vs. 76.00 and 80.00 for Cl 1 and 2, respectively; P = 0.0233). Cluster profiling enhances our understanding of the cow-calf operation segment and highlights the importance of GMP adoption for improving productivity in cow-calf operations. The results should be interpreted with caution due to the limitations of a cross-sectional study showing correlational associations. Nevertheless, it provides insights for designing science-based and targeted interventions to improve the performance of the beef cattle industry in Río Negro, Argentina, and may be the basis for prospective or interventions studies in the future.

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牛-小牛经营管理集群,阿根廷。
本研究旨在深入了解阿根廷Río内格罗省奶牛养殖业的生产率和良好管理规范(GMP)的采用情况。目标是根据GMP的采用来描述生产力和管理概况,确定牧群集群,并描述每个特定集群内的性能和生产力。在阿韦亚内达县和皮奇马惠达县的1,229家犊牛和犊牛育肥厂中,对142家进行了调查,提供了有关生产力、畜群结构和GMP采用情况的数据。采用四分位数对生产力变量——每100头牛的犊牛数(C/100 C)和每100公顷的犊牛数(C/100 ha)进行了统计描述,并探讨了按3个月繁殖季节采用的县间差异。此外,对畜群结构和gmp相关变量进行了多重对应分析(MCA),并采用全链接层次聚类分析对操作进行了分类。142名农民中有127名提供了生产力数据,显示中位数为79.00 C/100 C (Q1 = 67.00; Q3 = 85.00)和4.58 C/100公顷(Q1 = 2.78; Q3 = 8.00)。3个月和全年的养殖操作在这两个变量之间存在显著差异(82.00℃/100℃vs 75.50℃/100℃,P = 0.0006; 5.60℃/100公顷vs 3.97℃/100公顷,P = 0.0072)。确定了三个农场集群(Cl): Cl 1(低采用率),Cl 2(中等转型)和Cl 3(以gmp为导向)。cl3的GMP采用水平最高,且在C/ 100c变量上存在显著差异(cl1和cl2分别为85.00 C/ 100c和76.00、80.00,P = 0.0233)。集群分析增强了我们对牛-小牛操作部分的理解,并强调了采用GMP对提高牛-小牛操作生产率的重要性。由于显示相关性的横断面研究的局限性,结果应谨慎解释。然而,它为设计基于科学和有针对性的干预措施以改善阿根廷Río Negro肉牛产业的绩效提供了见解,并可能成为未来前瞻性或干预研究的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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