FeedEfficiencyService: An architecture for the comparison of data from multiple studies related to dairy cattle feed efficiency indices
作者机构：Programa de Pos-Graduacao em Ciencia da ComputacaoUniversidade Federal de Juiz de ForaCampus UniversitarioRua JoseLourenco Kelmers/n-Sao PedroJuiz de ForaMinas Gerais 36036-900Brasil Brazilian Agricultural Research Corporation-EmbrapaAv.Eugenio do Nascimento610-AeroportoJuiz de Fora-MGMinas Gerais 36038-330Brasil
出 版 物：《Information Processing in Agriculture》 (农业信息处理（英文）)
年 卷 期：2022年第9卷第3期
页 面：378-396页
核心收录：
学科分类：090502[农学-动物营养与饲料科学] 0905[农学-畜牧学] 09[农学]
基 金：We would like to thank the researchers who participated in the evaluation,Embrapa and Mr.Rian das Dores Alves for image manipulation.This work was partially funded by UFJF/Brazil,CNPq/Brazil(grant 311595/2019-7) FAPEMIG/Brazil(grant APQ-02685-17),(grant APQ-02194-18)
摘 要：The increased demand for food worldwide,the reduced land availability for livestock pro-duction,the increasing cost of animal feed and the need for mitigating livestock-related greenhouse gas emissions have driven the search for animal feeding systems that proves more *** tackle this problem,we propose the use of computational support to help researchers compare data on feed efficiency,therefore improving economic and environ-mental *** a solution,we present an integrative architecture capable of combining heterogeneous data from multiple experiments related to dairy cattle feed efficiency *** proposed architecture,called FeedEfficiencyService,classifies animals according to feed efficiency indices and allows visualizations through ontologies and inference *** results obtained from a case study with researchers from the Brazilian Agri-cultural Research Corporation–Dairy Cattle(EMBRAPA)demonstrate that this architecture is a supporting tool in their daily work *** researchers highlighted the importance of the proposed architecture as it allows analyzing animal data,comparing experiments,having reliable data analyses,and standardizing and organizing data from *** novelty of our approach is the use of ontologies and inference engines to enable the discovery of new knowledge and new relationships between data from feed efficiency-related *** store such data,relationships,and analyses of results in an inte-grated *** solution ensures unified access to the processing history and data from diverse experiments,including those conducted at external research centers.
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