{"title":"肉牛补充饲料技术研究进展","authors":"Guilherme Defalque, Ricardo Santos, Marcio Pache, Cristiane Defalque","doi":"10.1016/j.inpa.2023.10.003","DOIUrl":null,"url":null,"abstract":"The increase in the worldwide population reflects the expansion of beef cattle production and exportation. Although pasture is the world’s primary feed source of cattle food, failures in pasture management can endanger the productivity of beef cattle. An option for reducing the issues brought on by a shortage of nutritional resources and maintaining the fodder pasture is to perform the supplementation process on the livestock, even being one of the most costly activities in animal management. To decrease expenses and the need for labor to supplement the herd and improve animal performance, many parameters directly associated with supplementation must be monitored, such as environmental climate, soil and pasture characteristics, animal welfare, weight, and health. With so many parameters that impacts the decision on the quality and quantity of supplement to be supplied to the herd, sensors, remote sensing, and agricultural machinery are essential. The joint usage of these technologies in the supplementation process is complex, and there is a gap in decision-making systems for dynamic supplementation. Therefore, this work aims to carry out a comprehensive literature review that characterizes the main technologies related to the bovine supplementation process, mapping the main processes that involve the use of technological tools in the most diverse application domains. Finally, we propose a new Internet of Things architecture focused on the cattle supplementation process that combines technologies to compose a dynamic supplementation decision-making system capable of estimating the quantity and quality of the supplement that the herd needs in the presence of changes in the environment, pasture, and animals’ conditions parameters to reach production targets.","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"8 1","pages":"0"},"PeriodicalIF":7.7000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A review on beef cattle supplementation technologies\",\"authors\":\"Guilherme Defalque, Ricardo Santos, Marcio Pache, Cristiane Defalque\",\"doi\":\"10.1016/j.inpa.2023.10.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increase in the worldwide population reflects the expansion of beef cattle production and exportation. Although pasture is the world’s primary feed source of cattle food, failures in pasture management can endanger the productivity of beef cattle. An option for reducing the issues brought on by a shortage of nutritional resources and maintaining the fodder pasture is to perform the supplementation process on the livestock, even being one of the most costly activities in animal management. To decrease expenses and the need for labor to supplement the herd and improve animal performance, many parameters directly associated with supplementation must be monitored, such as environmental climate, soil and pasture characteristics, animal welfare, weight, and health. With so many parameters that impacts the decision on the quality and quantity of supplement to be supplied to the herd, sensors, remote sensing, and agricultural machinery are essential. The joint usage of these technologies in the supplementation process is complex, and there is a gap in decision-making systems for dynamic supplementation. Therefore, this work aims to carry out a comprehensive literature review that characterizes the main technologies related to the bovine supplementation process, mapping the main processes that involve the use of technological tools in the most diverse application domains. Finally, we propose a new Internet of Things architecture focused on the cattle supplementation process that combines technologies to compose a dynamic supplementation decision-making system capable of estimating the quantity and quality of the supplement that the herd needs in the presence of changes in the environment, pasture, and animals’ conditions parameters to reach production targets.\",\"PeriodicalId\":53443,\"journal\":{\"name\":\"Information Processing in Agriculture\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Processing in Agriculture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.inpa.2023.10.003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Processing in Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.inpa.2023.10.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
A review on beef cattle supplementation technologies
The increase in the worldwide population reflects the expansion of beef cattle production and exportation. Although pasture is the world’s primary feed source of cattle food, failures in pasture management can endanger the productivity of beef cattle. An option for reducing the issues brought on by a shortage of nutritional resources and maintaining the fodder pasture is to perform the supplementation process on the livestock, even being one of the most costly activities in animal management. To decrease expenses and the need for labor to supplement the herd and improve animal performance, many parameters directly associated with supplementation must be monitored, such as environmental climate, soil and pasture characteristics, animal welfare, weight, and health. With so many parameters that impacts the decision on the quality and quantity of supplement to be supplied to the herd, sensors, remote sensing, and agricultural machinery are essential. The joint usage of these technologies in the supplementation process is complex, and there is a gap in decision-making systems for dynamic supplementation. Therefore, this work aims to carry out a comprehensive literature review that characterizes the main technologies related to the bovine supplementation process, mapping the main processes that involve the use of technological tools in the most diverse application domains. Finally, we propose a new Internet of Things architecture focused on the cattle supplementation process that combines technologies to compose a dynamic supplementation decision-making system capable of estimating the quantity and quality of the supplement that the herd needs in the presence of changes in the environment, pasture, and animals’ conditions parameters to reach production targets.
期刊介绍:
Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining