Semantic Scholar Open Access 2023 121 sitasi

Artificial Intelligence: Implications for the Agri-Food Sector

Akriti Taneja Gayathri Nair Manisha Joshi Somesh Sharma Surabhi Sharma +6 lainnya

Abstrak

Artificial intelligence (AI) involves the development of algorithms and computational models that enable machines to process and analyze large amounts of data, identify patterns and relationships, and make predictions or decisions based on that analysis. AI has become increasingly pervasive across a wide range of industries and sectors, with healthcare, finance, transportation, manufacturing, retail, education, and agriculture are a few examples to mention. As AI technology continues to advance, it is expected to have an even greater impact on industries in the future. For instance, AI is being increasingly used in the agri-food sector to improve productivity, efficiency, and sustainability. It has the potential to revolutionize the agri-food sector in several ways, including but not limited to precision agriculture, crop monitoring, predictive analytics, supply chain optimization, food processing, quality control, personalized nutrition, and food safety. This review emphasizes how recent developments in AI technology have transformed the agri-food sector by improving efficiency, reducing waste, and enhancing food safety and quality, providing particular examples. Furthermore, the challenges, limitations, and future prospects of AI in the field of food and agriculture are summarized.

Penulis (11)

A

Akriti Taneja

G

Gayathri Nair

M

Manisha Joshi

S

Somesh Sharma

S

Surabhi Sharma

A

A. Jambrak

E

Elena Roselló-Soto

F

Francisco J. Barba

J

J. M. Castagnini

N

N. Leksawasdi

Y

Yuthana Phimolsiripol

Format Sitasi

Taneja, A., Nair, G., Joshi, M., Sharma, S., Sharma, S., Jambrak, A. et al. (2023). Artificial Intelligence: Implications for the Agri-Food Sector. https://doi.org/10.3390/agronomy13051397

Akses Cepat

Lihat di Sumber doi.org/10.3390/agronomy13051397
Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Total Sitasi
121×
Sumber Database
Semantic Scholar
DOI
10.3390/agronomy13051397
Akses
Open Access ✓