L. Parrenin, Christophe Danjou, B. Agard, R. Beauchemin
{"title":"有机制粉的未来趋势:人工智能的作用","authors":"L. Parrenin, Christophe Danjou, B. Agard, R. Beauchemin","doi":"10.3934/agrfood.2023003","DOIUrl":null,"url":null,"abstract":"The milling of wheat flour is a process that has existed since ancient times. In the course of history, the techniques have improved, the equipment modernized. The interest of the miller in charge of the mill is still to ensure that a mill is functional and profitable, as well as to provide a consistent quality of flour. The production of organic flour means that methods of adding chemicals and unnatural agents are not possible. In organic flour production, it is necessary to work with the raw material. A grain of wheat is a living material, and its quality varies according to a multitude of factors. Challenges are therefore present at each stage of the value chain. The use of artificial intelligence techniques offers solutions and new perspectives to meet the different objectives of the miller. A literature review of artificial intelligence techniques developed at each stage of the value chain surrounding the issues of quality and yield is conducted. An analysis of a large number of variables, including process factors, process parameters and wheat grain quality from data collected on the value chain enables the development and training of artificial intelligence models. From these models, it is possible to develop decision support tools and optimize the wheat flour milling process. Several major research directions, other than constant quality, are to be studied to optimize the process and move towards a smart mill. This includes energy savings, resource optimization and mill performance.","PeriodicalId":44793,"journal":{"name":"AIMS Agriculture and Food","volume":"1 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Future trends in organic flour milling: the role of AI\",\"authors\":\"L. Parrenin, Christophe Danjou, B. Agard, R. Beauchemin\",\"doi\":\"10.3934/agrfood.2023003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The milling of wheat flour is a process that has existed since ancient times. In the course of history, the techniques have improved, the equipment modernized. The interest of the miller in charge of the mill is still to ensure that a mill is functional and profitable, as well as to provide a consistent quality of flour. The production of organic flour means that methods of adding chemicals and unnatural agents are not possible. In organic flour production, it is necessary to work with the raw material. A grain of wheat is a living material, and its quality varies according to a multitude of factors. Challenges are therefore present at each stage of the value chain. The use of artificial intelligence techniques offers solutions and new perspectives to meet the different objectives of the miller. A literature review of artificial intelligence techniques developed at each stage of the value chain surrounding the issues of quality and yield is conducted. An analysis of a large number of variables, including process factors, process parameters and wheat grain quality from data collected on the value chain enables the development and training of artificial intelligence models. From these models, it is possible to develop decision support tools and optimize the wheat flour milling process. Several major research directions, other than constant quality, are to be studied to optimize the process and move towards a smart mill. This includes energy savings, resource optimization and mill performance.\",\"PeriodicalId\":44793,\"journal\":{\"name\":\"AIMS Agriculture and Food\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIMS Agriculture and Food\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3934/agrfood.2023003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIMS Agriculture and Food","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3934/agrfood.2023003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Future trends in organic flour milling: the role of AI
The milling of wheat flour is a process that has existed since ancient times. In the course of history, the techniques have improved, the equipment modernized. The interest of the miller in charge of the mill is still to ensure that a mill is functional and profitable, as well as to provide a consistent quality of flour. The production of organic flour means that methods of adding chemicals and unnatural agents are not possible. In organic flour production, it is necessary to work with the raw material. A grain of wheat is a living material, and its quality varies according to a multitude of factors. Challenges are therefore present at each stage of the value chain. The use of artificial intelligence techniques offers solutions and new perspectives to meet the different objectives of the miller. A literature review of artificial intelligence techniques developed at each stage of the value chain surrounding the issues of quality and yield is conducted. An analysis of a large number of variables, including process factors, process parameters and wheat grain quality from data collected on the value chain enables the development and training of artificial intelligence models. From these models, it is possible to develop decision support tools and optimize the wheat flour milling process. Several major research directions, other than constant quality, are to be studied to optimize the process and move towards a smart mill. This includes energy savings, resource optimization and mill performance.
期刊介绍:
AIMS Agriculture and Food covers a broad array of topics pertaining to agriculture and food, including, but not limited to: Agricultural and food production and utilization Food science and technology Agricultural and food engineering Food chemistry and biochemistry Food materials Physico-chemical, structural and functional properties of agricultural and food products Agriculture and the environment Biorefineries in agricultural and food systems Food security and novel alternative food sources Traceability and regional origin of agricultural and food products Authentication of food and agricultural products Food safety and food microbiology Waste reduction in agriculture and food production and processing Animal science, aquaculture, husbandry and veterinary medicine Resources utilization and sustainability in food and agricultural production and processing Horticulture and plant science Agricultural economics.