Artificial Intelligence to Improve the Food and Agriculture Sector | Zendy

Rayda Ben Ayed | Zendy; Mohsen Hanana | Zendy

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Artificial Intelligence to Improve the Food and Agriculture Sector

Author(s) -

Rayda Ben Ayed,

Mohsen Hanana

Publication year - 2021

Publication title -

journal of food quality

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.568

H-Index - 43

eISSN - 1745-4557

pISSN - 0146-9428

DOI - 10.1155/2021/5584754

Subject(s) - agriculture , context (archaeology) , multidisciplinary approach , scarcity , food security , population , business , food processing , world population , pandemic , food industry , natural resource economics , computer science , environmental resource management , covid-19 , economics , economic growth , geography , developing country , political science , microeconomics , environmental health , medicine , archaeology , law , disease , pathology , infectious disease (medical specialty)

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.

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