{"title":"High-performance simulation of disease outbreaks in growing-finishing pig herds raised by the precision feeding method","authors":"","doi":"10.1016/j.compag.2024.109335","DOIUrl":null,"url":null,"abstract":"<div><p>Perturbations always affect livestock during the breeding process, including harmful diseases. Researching the impact of disease outbreaks on pig herds is extremely important so that disease control measures can be applied early. However, conducting practical experiments on disease outbreaks is extremely expensive. Precision feeding systems (PFS) for pigs use data on the animal’s own feed intake to calculate the appropriate amount of feed for each individual. This helps increase productivity and product quality while contributing to reducing waste generation in the environment. Daily feed intake (DFI) and cumulative feed intake (CFI) data can be automatically collected and estimated from the PFS, which can help detect or predict disease outbreaks. In this article, we introduce an advanced simulation model of the PFS for pigs and the integration of disease outbreak models into this system. A disease outbreak simulation application within the pig herd raised by the precision feeding method is also developed for running high-performance experimental simulations. The results of the simulation scenarios are analyzed and compared with data from a real-world experiment to assess the accuracy of the application. The correlation coefficient values of DFI in all scenarios fall within the range of 0.25 to 0.5, suggesting almost no correlation between simulated DFI and actual DFI. The overall average correlation coefficient of CFI for all scenarios is 0.764, falling within the strong correlation range. It can be concluded that the simulation accurately represents CFI values compared to reality.</p></div>","PeriodicalId":50627,"journal":{"name":"Computers and Electronics in Agriculture","volume":null,"pages":null},"PeriodicalIF":7.7000,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Electronics in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168169924007269","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Perturbations always affect livestock during the breeding process, including harmful diseases. Researching the impact of disease outbreaks on pig herds is extremely important so that disease control measures can be applied early. However, conducting practical experiments on disease outbreaks is extremely expensive. Precision feeding systems (PFS) for pigs use data on the animal’s own feed intake to calculate the appropriate amount of feed for each individual. This helps increase productivity and product quality while contributing to reducing waste generation in the environment. Daily feed intake (DFI) and cumulative feed intake (CFI) data can be automatically collected and estimated from the PFS, which can help detect or predict disease outbreaks. In this article, we introduce an advanced simulation model of the PFS for pigs and the integration of disease outbreak models into this system. A disease outbreak simulation application within the pig herd raised by the precision feeding method is also developed for running high-performance experimental simulations. The results of the simulation scenarios are analyzed and compared with data from a real-world experiment to assess the accuracy of the application. The correlation coefficient values of DFI in all scenarios fall within the range of 0.25 to 0.5, suggesting almost no correlation between simulated DFI and actual DFI. The overall average correlation coefficient of CFI for all scenarios is 0.764, falling within the strong correlation range. It can be concluded that the simulation accurately represents CFI values compared to reality.
期刊介绍:
Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.