Abderahman Rejeb , Karim Rejeb , Suhaiza Zailani , John G. Keogh , Andrea Appolloni
{"title":"研究人工智能与农业食品行业之间的相互作用","authors":"Abderahman Rejeb , Karim Rejeb , Suhaiza Zailani , John G. Keogh , Andrea Appolloni","doi":"10.1016/j.aiia.2022.08.002","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of AI on agri-food resources and educates practitioners on the significance of knowledge-based and smart agriculture. We utilised bibliometric analysis to investigate the present state of the art and emerging trends in the relationship between AI and the agri-food industry. The research identified three distinct growth phases and the most prevalent AI strategies in the industry. In addition, we analysed key trends and offered researchers and practitioners insightful recommendations for future research. Using resource-based view (RBV) as the theoretical lens, this study established a framework emphasising the long-term effects of AI on various agri-food resources and proposed several research propositions. In addition, AI-related obstacles have been identified and categorised into four major categories. Lastly, the originality of the article lies in its numerous research suggestions and recommendations for advancing the AI field in the agri-food industry.</p></div>","PeriodicalId":52814,"journal":{"name":"Artificial Intelligence in Agriculture","volume":"6 ","pages":"Pages 111-128"},"PeriodicalIF":8.2000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589721722000095/pdfft?md5=d292823287652510cf1b081db68c949d&pid=1-s2.0-S2589721722000095-main.pdf","citationCount":"19","resultStr":"{\"title\":\"Examining the interplay between artificial intelligence and the agri-food industry\",\"authors\":\"Abderahman Rejeb , Karim Rejeb , Suhaiza Zailani , John G. Keogh , Andrea Appolloni\",\"doi\":\"10.1016/j.aiia.2022.08.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of AI on agri-food resources and educates practitioners on the significance of knowledge-based and smart agriculture. We utilised bibliometric analysis to investigate the present state of the art and emerging trends in the relationship between AI and the agri-food industry. The research identified three distinct growth phases and the most prevalent AI strategies in the industry. In addition, we analysed key trends and offered researchers and practitioners insightful recommendations for future research. Using resource-based view (RBV) as the theoretical lens, this study established a framework emphasising the long-term effects of AI on various agri-food resources and proposed several research propositions. In addition, AI-related obstacles have been identified and categorised into four major categories. Lastly, the originality of the article lies in its numerous research suggestions and recommendations for advancing the AI field in the agri-food industry.</p></div>\",\"PeriodicalId\":52814,\"journal\":{\"name\":\"Artificial Intelligence in Agriculture\",\"volume\":\"6 \",\"pages\":\"Pages 111-128\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2589721722000095/pdfft?md5=d292823287652510cf1b081db68c949d&pid=1-s2.0-S2589721722000095-main.pdf\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Intelligence in Agriculture\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589721722000095\",\"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":"Artificial Intelligence in Agriculture","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589721722000095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Examining the interplay between artificial intelligence and the agri-food industry
Artificial intelligence (AI) has advanced at an astounding rate and transformed numerous economic sectors. Nevertheless, a comprehensive understanding of how AI can improve the agri-food industry is lacking. In addition, there is a notable dearth of research on AI that investigates the influence of AI on agri-food resources and educates practitioners on the significance of knowledge-based and smart agriculture. We utilised bibliometric analysis to investigate the present state of the art and emerging trends in the relationship between AI and the agri-food industry. The research identified three distinct growth phases and the most prevalent AI strategies in the industry. In addition, we analysed key trends and offered researchers and practitioners insightful recommendations for future research. Using resource-based view (RBV) as the theoretical lens, this study established a framework emphasising the long-term effects of AI on various agri-food resources and proposed several research propositions. In addition, AI-related obstacles have been identified and categorised into four major categories. Lastly, the originality of the article lies in its numerous research suggestions and recommendations for advancing the AI field in the agri-food industry.