[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2684":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"view_count":30,"doi":31,"paper":32,"created_at":50},2684,"Predictors of economic performance of sheep meat farms","https:\u002F\u002Fdoi.org\u002F10.5424\u002Fsjar\u002F2026242-21226","The sheep sector is suffering an important decline in recent years and it is necessary to ensure its economic viability in order to guarantee its continuity. The main objective of this work was to determine the structural, technical and economic variables that best predicted the economic performance of a sample of sheep farms. Assuming that there were different types of farms, a typification was also carried out to find out whether the predictor variables differed between the groups. Eleven structural, technical and economic variables were studied in a sample of 126 Aragonese farms (Spain) over the period 1993-2016, and several statistical analyses were carried out: Factor Analysis, Cluster Analysis and Multiple Linear Regression. From the result of the typification, three groups of farms were obtained that can define three production systems differentiated mainly by the productive structure, and the degree of intensification of production. It was observed that different farm management could lead to the same economic results. Labour intensification followed by the number of lambs sold per ewe per year were the indicators with the highest positive predictive power on economic results, while feed cost per ewe was the variable with the highest negative predictive power, in all cases with no differences between groups.","近年来，养羊业正经历显著衰退，为确保其持续发展，必须保障其经济可行性。本研究的主要目标是确定最能预测样本羊场经济表现的结构性、技术性和经济性变量。考虑到存在不同类型的养殖场，本研究还进行了类型划分，以探究预测变量在不同组别之间是否存在差异。研究对西班牙阿拉贡地区126个养殖场在1993—2016年期间的11个结构性、技术性和经济性变量进行了分析，并开展了多项统计分析：因子分析、聚类分析和多元线性回归。类型划分的结果得到了三组养殖场，可据此定义三种生产体系，其主要区别在于生产结构和生产集约化程度。研究观察到，不同的养殖管理方式可能导致相同的经济结果。劳动力集约化程度，其次是每只母羊每年售出的羔羊数，是对经济结果正向预测能力最强的指标，而每只母羊的饲料成本则是负向预测能力最强的变量，在所有情况下各组之间均无差异。",null,"Spanish Journal of Agricultural Research","2026-09-15T00:00:00Z","论文",10,false,65,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,20,16,13,1,"基于西班牙126个羊场27年数据的实证研究，方法扎实、结论明确，对肉羊产业经济可持续性有参考价值，但属区域样本研究，公共影响有限。",[24],{"name":10,"url":6},[26,27,28,29],"农业经济","农场管理","肉羊养殖","养殖经济效益",0,"10.5424\u002Fsjar\u002F2026242-21226",{"doi":31,"openalex_id":33,"authors":34,"venue":10,"cited_by_count":30,"oa_url":42,"card":43,"direction":47,"ingested_from":49},"W7213292528",[35,37,40],{"name":36,"orcid":9},"Louiza Chekmam",{"name":38,"orcid":39},"María T. Maza","https:\u002F\u002Forcid.org\u002F0000-0002-2266-4655",{"name":41,"orcid":9},"L. Pardos","https:\u002F\u002Fsjar.revistas.csic.es\u002Findex.php\u002Fsjar\u002Farticle\u002Fdownload\u002F21226\u002F6753",{"tldr":44,"method":45,"finding":46,"direction":47,"opportunity":48},"分析西班牙绵羊场结构、技术与经济变量，找出预测经济绩效的关键指标。","对126个农场1993-2016年11个变量做因子、聚类与多元线性回归。","劳动集约度和每羊年售羔数正向预测经济绩效，每羊饲料成本负向预测，且各组一致。","农业人工智能与决策模型","可构建跨区域绵羊场经济绩效预测模型，并引入物联网实时数据优化饲料与劳动管理。","openalex","2026-09-16T23:30:58.240541Z"]