Frontiers in Artificial Intelligence | AI in Food, Agriculture and Water

Original Research

Published on 19 Feb 2026

Driving factors of agricultural artificial intelligence adoption intention: an empirical study in Shandong province based on innovation characteristics, technology commitment, and individual heterogeneity

in AI in Food, Agriculture and Water

Kai Cao
Ping Wang
Siyu Kong
Chunzhen Zhang

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1630717

196 views

Original Research

Accepted on 16 Feb 2026

HASPNet: A Hierarchically Attentive Signal-Preserving Network for Papaya Leaf Disease Classification with Explainable Deep Learning

in AI in Food, Agriculture and Water

Sundara Srivasthsan M
Sahnaaz Mariam
Prithivraj S
Lighittha P R
Suchetha M
Preethi S

Frontiers in Artificial Intelligence

Original Research

Accepted on 09 Feb 2026

ZamYOLO-Maize: A YOLOv8n-Based Deep Learning Framework for Automated Detection and Classification of Maize Leaf Diseases in Field Conditions in Zambia

in AI in Food, Agriculture and Water

Prudence Kalunga
Douglas Kunda
Aaron Zimba

Frontiers in Artificial Intelligence

106 views

Original Research

Accepted on 09 Feb 2026

HCA-DBN: A Hill Climbing Optimized Deep Belief Network for Crop Yield Classification Based on Kernel Weight Threshold

in AI in Food, Agriculture and Water

Prakash Sandhya
B Venkataramana

Frontiers in Artificial Intelligence

101 views

Original Research

Accepted on 09 Feb 2026

Classification of Lupinus seeds into sweet and bitter categories using VIS–NIR spectroscopy and machine learning

in AI in Food, Agriculture and Water

Josefa Díaz Álvarez
Francisco A. Galea-Gragera
Francisco Chávez de la O
Pedro A. Salguero-López
Fernando Llera Cid

Frontiers in Artificial Intelligence

Original Research

Published on 09 Feb 2026

Precision cotton disease detection via transformer models applied to leaf imagery

in AI in Food, Agriculture and Water

Nikhil Inamdar
Manjunath Managuli
Ramesh Koti
Jagadish Jakati
Sharanappa P. H.
Prasan Kulkarni

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1743264

873 views

Original Research

Accepted on 03 Feb 2026

Transformer model to determine spatio-temporal relationships of variables, and interpretability for soybean seed yield, oil, and protein prediction

in AI in Food, Agriculture and Water

Timilehin T. Ayanlade
Liza Van der Laan
Qisai Liu
Tryambak Gangopadhyay
Jonathan Shook
Arti Singh
Baskar Ganapathysubramanian
Soumik Sarkar
Asheesh K Singh

Frontiers in Artificial Intelligence

217 views

Original Research

Published on 30 Jan 2026

LeafSightX: an explainable attention-enhanced CNN fusion model for apple leaf disease identification

in AI in Food, Agriculture and Water

Md. Ehsanul Haque
Fahmid Al Farid
Md. Kamrul Siam
Md. Nurul Absur
Jia Uddin
Hezerul Abdul Karim

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1689865

846 views

Original Research

Accepted on 26 Jan 2026

Quantification of feeding intensity and feeding control of largemouth bass based on water surface vibration characteristics

in AI in Food, Agriculture and Water

Yufei Zhang
Andong Liu
Yulei Zhang
Qi Ni
Haigen Zhang
Yong Wang

Frontiers in Artificial Intelligence

200 views

Original Research

Published on 22 Jan 2026

Orchestrating segment anything models to accelerate segmentation annotation on agricultural image datasets

in AI in Food, Agriculture and Water

Leon H. Oehme
Jonas Boysen
Zhangkai Wu
Anthony Stein
Joachim Müller

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1748468

818 views

Original Research

Published on 12 Jan 2026

PotatoLeafNet: two-stage convolutional neural networks for effective Potato Leaf disease identification and classification

in AI in Food, Agriculture and Water

Girigula Durga Bhavani
Mukkoti Maruthi Venkata Chalapathi

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1668839

884 views

Original Research

Published on 04 Dec 2025

Forecasting global monthly cotton prices: the superiority of NNAR models over traditional models

in AI in Food, Agriculture and Water

Rumita Limbu Sanwa
Raksha Khadka
Yeon Nain Chi

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1628744

1,776 views

Editorial

Published on 25 Nov 2025

Editorial: Semantics and natural language processing in agriculture

in AI in Food, Agriculture and Water

Mathieu Roche
Brett M. Drury

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1718114

938 views

Correction

Published on 25 Nov 2025

Correction: Phenology analysis for trait prediction using UAVs in a MAGIC rice population with different transplanting protocols

in AI in Food, Agriculture and Water

Shoji Taniguchi
Toshihiro Sakamoto
Haruki Nakamura
Yasunori Nonoue
Di Guan
Akari Fukuda
Hirofumi Fukuda
Kaede C. Wada
Takuro Ishii
Jun-Ichi Yonemaru

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1725594

704 views

Brief Research Report

Published on 26 Sep 2025

Fluorescent marker prediction for non-invasive optical imaging in bovine satellite cells using deep learning

in AI in Food, Agriculture and Water

Sania Sinha
Aarham Wasit
Won Seob Kim
Jongkyoo Kim
Jiyoon Yi

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1577027

2,027 views

Mini Review

Published on 23 Sep 2025

Data quality challenges of AIGC application in smart agriculture

in AI in Food, Agriculture and Water

Yingxue Ren
Yitong Qu
Runzeng Gao

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1640805

2,521 views

Review

Published on 17 Sep 2025

A bibliometric review of deep learning in crop monitoring: trends, challenges, and future perspectives

in AI in Food, Agriculture and Water

Rui Zhang
Xue Wu
Jing Li
Pengyu Zhao
Qing Zhang
Lige Wuri
Donghui Zhang
Zhijie Zhang
Linnan Yang

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1636898

5,147 views
3 citations

Original Research

Published on 22 Aug 2025

Dairy DigiD: a keypoint-based deep learning system for classifying dairy cattle by physiological and reproductive status

in AI in Food, Agriculture and Water

Shubhangi Mahato
Hanqing Bi
Suresh Neethirajan

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1545247

3,531 views
1 citation

Original Research

Published on 12 Aug 2025

Enhanced plant disease classification with attention-based convolutional neural network using squeeze and excitation mechanism

in AI in Food, Agriculture and Water

S. Karthikeyan
R. Charan
Sathiya Narayanan
L. Jani Anbarasi

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1640549

4,413 views
2 citations

Original Research

Published on 12 Aug 2025

Enhancing AI microscopy for foodborne bacterial classification using adversarial domain adaptation to address optical and biological variability

in AI in Food, Agriculture and Water

Siddhartha Bhattacharya
Aarham Wasit
J Mason Earles
Nitin Nitin
Jiyoon Yi

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1632344

2,256 views
2 citations

Original Research

Published on 06 Aug 2025

Enhancing detection of common bean diseases using Fast Gradient Sign Method–trained Vision Transformers

in AI in Food, Agriculture and Water

Upendo Mwaibale
Neema Mduma
Hudson Laizer
Bonny Mgawe

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1643582

2,339 views

Original Research

Published on 13 May 2025

Deep learning classification of drainage crossings based on high-resolution DEM-derived geomorphological information

in AI in Food, Agriculture and Water

Michael Edidem
Bill Xu
Ruopu Li
Di Wu
Banafsheh Rekabdar
Guangxing Wang

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1561281

2,611 views
1 citation

Original Research

Published on 26 Mar 2025

MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism

in AI in Food, Agriculture and Water

Yuanqi Chen
Aiping Wang
Ziyang Liu
Jie Yue
Enxu Zhang
Fei Li
Ning Zhang

Frontiers in Artificial Intelligence

doi 10.3389/frai.2025.1498025

3,161 views
5 citations

Original Research

Published on 03 Feb 2025

Deep learning and explainable AI for classification of potato leaf diseases

in AI in Food, Agriculture and Water

Sarah M. Alhammad
Doaa Sami Khafaga
Walaa M. El-hady
Farid M. Samy
Khalid M. Hosny

Frontiers in Artificial Intelligence

doi 10.3389/frai.2024.1449329

8,818 views
23 citations

97 articles

articles

Driving factors of agricultural artificial intelligence adoption intention: an empirical study in Shandong province based on innovation characteristics, technology commitment, and individual heterogeneity

HASPNet: A Hierarchically Attentive Signal-Preserving Network for Papaya Leaf Disease Classification with Explainable Deep Learning

ZamYOLO-Maize: A YOLOv8n-Based Deep Learning Framework for Automated Detection and Classification of Maize Leaf Diseases in Field Conditions in Zambia

HCA-DBN: A Hill Climbing Optimized Deep Belief Network for Crop Yield Classification Based on Kernel Weight Threshold

Classification of Lupinus seeds into sweet and bitter categories using VIS–NIR spectroscopy and machine learning

Precision cotton disease detection via transformer models applied to leaf imagery

Transformer model to determine spatio-temporal relationships of variables, and interpretability for soybean seed yield, oil, and protein prediction

LeafSightX: an explainable attention-enhanced CNN fusion model for apple leaf disease identification

Quantification of feeding intensity and feeding control of largemouth bass based on water surface vibration characteristics

Orchestrating segment anything models to accelerate segmentation annotation on agricultural image datasets

PotatoLeafNet: two-stage convolutional neural networks for effective Potato Leaf disease identification and classification

Forecasting global monthly cotton prices: the superiority of NNAR models over traditional models

Editorial: Semantics and natural language processing in agriculture

Correction: Phenology analysis for trait prediction using UAVs in a MAGIC rice population with different transplanting protocols

Fluorescent marker prediction for non-invasive optical imaging in bovine satellite cells using deep learning

Data quality challenges of AIGC application in smart agriculture

A bibliometric review of deep learning in crop monitoring: trends, challenges, and future perspectives

Dairy DigiD: a keypoint-based deep learning system for classifying dairy cattle by physiological and reproductive status

Enhanced plant disease classification with attention-based convolutional neural network using squeeze and excitation mechanism

Enhancing AI microscopy for foodborne bacterial classification using adversarial domain adaptation to address optical and biological variability

Enhancing detection of common bean diseases using Fast Gradient Sign Method–trained Vision Transformers

Deep learning classification of drainage crossings based on high-resolution DEM-derived geomorphological information

MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism

Deep learning and explainable AI for classification of potato leaf diseases