Artificial Intelligence to Improve the Food and Agriculture Sector
Rayda Ben Ayed, Mohsen Hanana
Abstract
The world population is expected to reach over 9 billion by 2050, which will require an increase in agricultural and food production by 70% to fit the need, a serious challenge for the agri-food industry. Such requirement, in a context of resources scarcity, climate change, COVID-19 pandemic, and very harsh socioeconomic conjecture, is difficult to fulfill without the intervention of computational tools and forecasting strategy. Hereby, we report the importance of artificial intelligence and machine learning as a predictive multidisciplinary approach integration to improve the food and agriculture sector, yet with some limitations that should be considered by stakeholders.
Topics & Concepts
AgricultureContext (archaeology)Multidisciplinary approachScarcityFood securityPopulationBusinessFood processingWorld populationPandemicFood industryNatural resource economicsComputer scienceEnvironmental resource managementCoronavirus disease 2019 (COVID-19)EconomicsEconomic growthGeographyDeveloping countryPolitical scienceMicroeconomicsEnvironmental healthArchaeologyInfectious disease (medical specialty)PathologyDiseaseLawMedicineSmart Agriculture and AIFood Supply Chain Traceability