TY - JOUR
T1 - Recent advances in artificial intelligence towards the sustainable future of agri-food industry
AU - Nath, Pinku Chandra
AU - Mishra, Awdhesh Kumar
AU - Sharma, Ramesh
AU - Bhunia, Biswanath
AU - Mishra, Bishwambhar
AU - Tiwari, Ajita
AU - Nayak, Prakash Kumar
AU - Sharma, Minaxi
AU - Bhuyan, Tamanna
AU - Kaushal, Sushant
AU - Mohanta, Yugal Kishore
AU - Sridhar, Kandi
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/7/30
Y1 - 2024/7/30
N2 - Artificial intelligence has the potential to alter the agricultural and food processing industries, with significant ramifications for sustainability and global food security. The integration of artificial intelligence in agriculture has witnessed a significant uptick in recent years. Therefore, comprehensive understanding of these techniques is needed to broaden its application in agri-food supply chain. In this review, we explored cutting-edge artificial intelligence methodologies with a focus on machine learning, neural networks, and deep learning. The application of artificial intelligence in agri-food industry and their quality assurance throughout the production process is thoroughly discussed with an emphasis on the current scientific knowledge and future perspective. Artificial intelligence has played a significant role in transforming agri-food systems by enhancing efficiency, sustainability, and productivity. Many food industries are implementing the artificial intelligence in modelling, prediction, control tool, sensory evaluation, quality control, and tackling complicated challenges in food processing. Similarly, artificial intelligence applied in agriculture to improve the entire farming process, such as crop yield optimization, use of herbicides, weeds identification, and harvesting of fruits. In summary, the integration of artificial intelligence in agri-food systems offers the potential to address key challenges in agriculture, enhance sustainability, and contribute to global food security.
AB - Artificial intelligence has the potential to alter the agricultural and food processing industries, with significant ramifications for sustainability and global food security. The integration of artificial intelligence in agriculture has witnessed a significant uptick in recent years. Therefore, comprehensive understanding of these techniques is needed to broaden its application in agri-food supply chain. In this review, we explored cutting-edge artificial intelligence methodologies with a focus on machine learning, neural networks, and deep learning. The application of artificial intelligence in agri-food industry and their quality assurance throughout the production process is thoroughly discussed with an emphasis on the current scientific knowledge and future perspective. Artificial intelligence has played a significant role in transforming agri-food systems by enhancing efficiency, sustainability, and productivity. Many food industries are implementing the artificial intelligence in modelling, prediction, control tool, sensory evaluation, quality control, and tackling complicated challenges in food processing. Similarly, artificial intelligence applied in agriculture to improve the entire farming process, such as crop yield optimization, use of herbicides, weeds identification, and harvesting of fruits. In summary, the integration of artificial intelligence in agri-food systems offers the potential to address key challenges in agriculture, enhance sustainability, and contribute to global food security.
KW - Artificial intelligence
KW - Food and agricultural sector
KW - Food quality
UR - http://www.scopus.com/inward/record.url?scp=85187196574&partnerID=8YFLogxK
U2 - 10.1016/j.foodchem.2024.138945
DO - 10.1016/j.foodchem.2024.138945
M3 - Review article
C2 - 38461725
AN - SCOPUS:85187196574
SN - 0308-8146
VL - 447
JO - Food Chemistry
JF - Food Chemistry
M1 - 138945
ER -