TY - JOUR
T1 - Artificial Intelligence in Agro-Food Systems: From Farm to Fork
AU - Aghababaei, Ali
AU - Aghababaei, Fatemeh
AU - Pignitter, Marc
AU - Hadidi, Milad
N1 - Publisher Copyright:
© 2025 by the authors.
Accession Number
WOS:001418571600001
PubMed ID
39942003
PY - 2025/2
Y1 - 2025/2
N2 - The current landscape of the food processing industry places a strong emphasis on improving food quality, nutritional value, and processing techniques. This focus arises from consumer demand for products that adhere to high standards of quality, sensory characteristics, and extended shelf life. The emergence of artificial intelligence (AI) and machine learning (ML) technologies is instrumental in addressing the challenges associated with variability in food processing. AI represents a promising interdisciplinary approach for enhancing performance across various sectors of the food industry. Significant advancements have been made to address challenges and facilitate growth within the food sector. This review highlights the applications of AI in agriculture and various sectors of the food industry, including bakery, beverage, dairy, food safety, fruit and vegetable industries, packaging and sorting, and the drying of fresh foods. Various strategies have been implemented across different food sectors to promote advancements in technology. Additionally, this article explores the potential for advancing 3D printing technology to enhance various aspects of the food industry, from manufacturing to service, while also outlining future perspectives.
AB - The current landscape of the food processing industry places a strong emphasis on improving food quality, nutritional value, and processing techniques. This focus arises from consumer demand for products that adhere to high standards of quality, sensory characteristics, and extended shelf life. The emergence of artificial intelligence (AI) and machine learning (ML) technologies is instrumental in addressing the challenges associated with variability in food processing. AI represents a promising interdisciplinary approach for enhancing performance across various sectors of the food industry. Significant advancements have been made to address challenges and facilitate growth within the food sector. This review highlights the applications of AI in agriculture and various sectors of the food industry, including bakery, beverage, dairy, food safety, fruit and vegetable industries, packaging and sorting, and the drying of fresh foods. Various strategies have been implemented across different food sectors to promote advancements in technology. Additionally, this article explores the potential for advancing 3D printing technology to enhance various aspects of the food industry, from manufacturing to service, while also outlining future perspectives.
KW - agriculture sector
KW - algorithms
KW - artificial neural networks
KW - computer science
KW - food industry
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85217560357&partnerID=8YFLogxK
U2 - 10.3390/foods14030411
DO - 10.3390/foods14030411
M3 - Review
AN - SCOPUS:85217560357
SN - 2304-8158
VL - 14
JO - Foods
JF - Foods
IS - 3
M1 - 411
ER -