{"title":"Artificial intelligence can regulate light and climate systems to reduce energy use in plant factories and support sustainable food production","authors":"Benjamin Decardi-Nelson, Fengqi You","doi":"10.1038/s43016-024-01045-3","DOIUrl":null,"url":null,"abstract":"Plant factories with artificial lighting (PFALs) can boost food production per unit area but require resources such as carbon dioxide and energy to maintain optimal plant growth conditions. Here we use computational modelling and artificial intelligence (AI) to examine plant–environment interactions across ten diverse global locations with distinct climates. AI reduces energy use by optimizing lighting and climate regulation systems, with energy use in PFALs ranging from 6.42 kWh kg−1 in cooler climates to 7.26 kWh kg−1 in warmer climates, compared to 9.5–10.5 kWh kg−1 in PFALs using existing, non-AI-based technology. Outdoor temperatures between 0 °C and 25 °C favour ventilation-related energy use reduction, with outdoor humidity showing no clear pattern or effect on energy use. Ventilation-related energy savings negatively impact other resource utilization such as carbon dioxide use. AI can substantially enhance energy savings in PFALs and support sustainable food production. Plant–environment interactions are examined using artificial intelligence and computational modelling, allowing energy use to be optimized in plant factories with artificial lighting.","PeriodicalId":94151,"journal":{"name":"Nature food","volume":"5 10","pages":"869-881"},"PeriodicalIF":23.6000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature food","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43016-024-01045-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Plant factories with artificial lighting (PFALs) can boost food production per unit area but require resources such as carbon dioxide and energy to maintain optimal plant growth conditions. Here we use computational modelling and artificial intelligence (AI) to examine plant–environment interactions across ten diverse global locations with distinct climates. AI reduces energy use by optimizing lighting and climate regulation systems, with energy use in PFALs ranging from 6.42 kWh kg−1 in cooler climates to 7.26 kWh kg−1 in warmer climates, compared to 9.5–10.5 kWh kg−1 in PFALs using existing, non-AI-based technology. Outdoor temperatures between 0 °C and 25 °C favour ventilation-related energy use reduction, with outdoor humidity showing no clear pattern or effect on energy use. Ventilation-related energy savings negatively impact other resource utilization such as carbon dioxide use. AI can substantially enhance energy savings in PFALs and support sustainable food production. Plant–environment interactions are examined using artificial intelligence and computational modelling, allowing energy use to be optimized in plant factories with artificial lighting.