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

Systematic Review

Published on 20 Apr 2026

Maize yield prediction using machine learning: a systematic literature review

in AI in Food, Agriculture and Water

Jabulani Nyengere
Frank Tchuwa
Harineck Mayamiko Tholo
Lucius Malalu
Allena Laura Njala
Petros Kachulu
Rodney Maganga
Brenda Matewere
Lackson Jamu
Clement Nyirenda

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1735157

127 views

Original Research

Published on 17 Apr 2026

Fusing appearance and vein morphology using dual-branch deep networks for accurate medicinal plant identification

in AI in Food, Agriculture and Water

Chembon Rajeendran Karthik
Parthiban Maheswari Adithya
Naveen Nidadavolu
Ananthakrishnan Balasundaram
Ayesha Shaik

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1771431

187 views

Original Research

Accepted on 14 Apr 2026

Classification of Coffee Leaf Nutrient Deficiencies using Hybrid Feature Aggregation with Hierarchical Localized Attention and MobileNet

in AI in Food, Agriculture and Water

Alden Jenish S
Karthik R
Keerthana S
Sudhakaran G

Frontiers in Artificial Intelligence

Original Research

Published on 10 Apr 2026

Performance evaluation of machine learning algorithms for estimating reference evapotranspiration based on NASA POWER weather data: a case study in Nigeria

in AI in Food, Agriculture and Water

Oluwaseun Temitope Faloye
Grace Awotoye
Oluwadamilare Oluwasegun Eludire
Oluwatobi Solomon Olaleye
Ayoola Olamitomi Oluwadare
Oluwafemi E. Adeyeri
Laemthong Laokhongthavorn
Viroon Kamchoom

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1801981

215 views

Original Research

Accepted on 09 Apr 2026

Federated Learning with Dynamic Weighted Aggregation for Multi-Crop Disease Detection: A Hybrid CNN-Transformer Approach

in AI in Food, Agriculture and Water

Bhavadharini R M
Shashank Ragoor

Frontiers in Artificial Intelligence

Original Research

Published on 26 Mar 2026

Portable electrochemical impedance biosensing with DRT-enabled machine learning for detecting E. coli O157:H7 in poultry meat

in AI in Food, Agriculture and Water

Yang Tian
Ziyu Liu
Chaitanya Pallerla
Siavash Mahmoudi
Ramesh Bahadur Bist
Yiting Xiao
Terry Howell
Jeyamkondan Subbiah
Dongyi Wang

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1741144

252 views

Original Research

Published on 25 Mar 2026

LeafFusionNet: a hybrid deep learning approach for robust plant disease detection

in AI in Food, Agriculture and Water

Srijani Das
G. Prethija
C. Sudha

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1773329

354 views

Original Research

Published on 20 Mar 2026

HASPNet: a hierarchically attentive signal-preserving network for papaya leaf disease classification with explainable deep learning

in AI in Food, Agriculture and Water

M. Sundara Srivathsan
Suchetha Manikandan
S. Preethi
P. R. Lighittha
S. Prithivraj
Sahnaaz Mariam

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1734865

256 views

Original Research

Published on 13 Mar 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
Hongqiao Song
Yong Wang
Xiaoyan Cheng

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1656290

370 views

Original Research

Published on 12 Mar 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

doi 10.3389/frai.2026.1742033

278 views

Original Research

Published on 27 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

doi 10.3389/frai.2026.1745720

498 views

Original Research

Published on 26 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
Johnathon Shook
Arti Singh
Baskar Ganapathysubramanian
Soumik Sarkar
Asheesh K. Singh

Frontiers in Artificial Intelligence

doi 10.3389/frai.2026.1750108

677 views

Original Research

Published on 25 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

doi 10.3389/frai.2026.1764283

629 views

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

633 views

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

1,081 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

1,191 views
2 citations

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

1,148 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

1,221 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

2,143 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

801 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

1,082 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

2,158 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

2,764 views
1 citation

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

5,995 views
6 citations

104 articles

articles

Maize yield prediction using machine learning: a systematic literature review

Fusing appearance and vein morphology using dual-branch deep networks for accurate medicinal plant identification

Classification of Coffee Leaf Nutrient Deficiencies using Hybrid Feature Aggregation with Hierarchical Localized Attention and MobileNet

Performance evaluation of machine learning algorithms for estimating reference evapotranspiration based on NASA POWER weather data: a case study in Nigeria

Federated Learning with Dynamic Weighted Aggregation for Multi-Crop Disease Detection: A Hybrid CNN-Transformer Approach

Portable electrochemical impedance biosensing with DRT-enabled machine learning for detecting E. coli O157:H7 in poultry meat

LeafFusionNet: a hybrid deep learning approach for robust plant disease detection

HASPNet: a hierarchically attentive signal-preserving network for papaya leaf disease classification with explainable deep learning

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

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

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

ZamYOLO-maize: a YOLOv8n-based deep learning framework for automated detection and classification of maize leaf diseases in field conditions in Zambia

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

Precision cotton disease detection via transformer models applied to leaf imagery

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

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

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

Editorial: Semantics and natural language processing in agriculture

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