Editor’s Choice Articles

Published 06 May, 2026

Deep learning-based classification, detection, and segmentation of tomato leaf diseases: A state-of-the-art review

June 2025

Aritra Das | Fahad Pathan | Jamin Rahman Jim | Md Mohsin Kabir | M.F. Mridha

The early identification and treatment of tomato leaf diseases are crucial for optimizing plant productivity, efficiency and quality. Misdiagnosis by the farmers poses the risk of inadequate treatments, harming both tomato plants and agroecosystems. Precision of disease diagnosis is essential…

 

Advancing precision agriculture: A comparative analysis of YOLOv8 for multi-class weed detection in cotton cultivation

June 2025

Ameer Tamoor Khan | Signe Marie Jensen | Abdul Rehman Khan

Effective weed management plays a critical role in enhancing the productivity and sustainability of cotton cultivation. The rapid emergence of herbicide-resistant weeds has underscored the need for innovative solutions to address the challenges associated with precise weed detection. This paper investigates…

 

AI-driven aquaculture: A review of technological innovations and their sustainable impacts

September 2025

Hang Yang | Qi Feng | Shibin Xia | Zhenbin Wu | Yi Zhang

The integration of artificial intelligence (AI) in aquaculture has been identified as a transformative force, enhancing various operational aspects from water quality management to genetic optimization. This review provides a comprehensive synthesis of recent advancements in AI applications…

 

Comprehensive review on 3D point cloud segmentation in plants

June 2025

Hongli Song | Weiliang Wen | Sheng Wu | Xinyu Guo

Segmentation of three-dimensional (3D) point clouds is fundamental in comprehending unstructured structural and morphological data. It plays a critical role in research related to plant phenomics, 3D plant modeling, and functional-structural plant modeling. Although technologies for plant point cloud segmentation (PPCS) have advanced rapidly…

 

An efficient strawberry segmentation model based on Mask R-CNN and TensorRT

June 2025

Anthony Crespo | Claudia Moncada | Fabricio Crespo | Manuel Eugenio Morocho-Cayamcela

Currently, artificial intelligence (AI), particularly computer vision (CV), has numerous applications in agriculture. In this field, the production and consumption of strawberries have experienced great growth in recent years, which makes meeting the growing demand a challenge that producers must face. However, one of the main problems regarding the cultivation of this fruit is…

 

Research on an orchard row centreline multipoint autonomous navigation method based on LiDAR

June 2025

Chen Zhenyu | Dou Hanjie | Gao Yuanyuan | Zhai Changyuan | Wang Xiu | Zou Wei

Orchard intelligent equipment must perform autonomous navigation tasks along fruit tree row centrelines and headlands according to established operational requirements. The tree canopy obstructs satellite signals, limiting the accuracy and stability of the GNSS-based autonomous navigation system. This paper presents a multipoint autonomous navigation method…

 

A review on enhancing agricultural intelligence with large language models

December 2025

Hongda Li | Huarui Wu | Qingxue Li | Chunjiang Zhao

This paper systematically explores the application potential of large language models (LLMs) in the field of agricultural intelligence, focusing on key technologies and practical pathways. The study focuses on the adaptation of LLMs to agricultural knowledge, starting with foundational concepts such as architecture design, pre-training strategies, and fine-tuning techniques…

 

End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality

September 2025

Tingting Zhang | Jing Li | Jinpeng Tong | Yihu Song | Li Wang | Renye Wu | Xuan Wei | Yuanyuan Song | Rensen Zeng

Seeds are essential to the agri-food industry. However, their quality is vulnerable to biotic and abiotic stresses during production and storage, leading to various types of deterioration. Real-time monitoring and pre-sowing screening offer substantial potential for improved storage management, field performance, and flour quality. This study investigated…

 

Technical study on the efficiency and models of weed control methods using unmanned ground vehicles: A review

December 2025

Evans K. Wiafe | Kelvin Betitame | Billy G. Ram | Xin Sun

As precision agriculture evolves, unmanned ground vehicles (UGVs) have become an essential tool for improving weed management techniques, offering automated and targeted methods that obviously reduce the reliance on manual labor and blanket herbicide applications. Several papers on UGV-based weed control methods have been published…

 

Prediction of sugar beet yield and quality parameters using stacked-LSTM model with pre-harvest UAV time series data and meteorological factors

 June 2025

Qing Wang | Ke Shao | Zhibo Cai | Yingpu Che | Haochong Chen | Shunfu Xiao | Ruili Wang | Yaling Liu | Baoguo Li | Yuntao Ma

Accurate pre-harvest prediction of sugar beet yield is vital for effective agricultural management and decision-making. However, traditional methods are constrained by reliance on empirical knowledge, time-consuming processes, resource intensiveness, and spatial-temporal variability in prediction accuracy. This study presented a plot-level approach that…

 

Application of artificial intelligence in insect pest identification - A review

March 2026

Sourav Chakrabarty | Chandan Kumar Deb | Sudeep Marwaha | Md. Ashraful Haque | Deeba Kamil | Raju Bheemanahalli | Pathour Rajendra Shashank

The increasing danger of insect pests to agriculture and ecosystems calls for quick, and precise diagnosis. Conventional techniques that depend on human observation and taxonomic knowledge are frequently labour-intensive and time-consuming. Incorporating artificial intelligence (AI) into detection has emerged as an effective approach in agriculture, including entomology. AI-based detection methods use…

 

Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques

September 2025

Rabiu Aminu | Samantha M. Cook | David Ljungberg | Oliver Hensel | Abozar Nasirahmadi

To reduce damage caused by insect pests, farmers use insecticides to protect produce from crop pests. This practice leads to high synthetic chemical usage because a large portion of the applied insecticide does not reach its intended target; instead, it may affect non-target organisms and pollute the environment. One approach to mitigating…

 

Multi-camera fusion and bird-eye view location mapping for deep learning-based cattle behavior monitoring

December 2025

Muhammad Fahad Nasir | Alvaro Fuentes | Shujie Han | Jiaqi Liu | Yongchae Jeong | Sook Yoon | Dong Sun Park

Cattle behavioral monitoring is an integral component of the modern infrastructure of the livestock industry. Ensuring cattle well-being requires precise observation, typically using wearable devices or surveillance cameras. Integrating deep learning into these systems enhances…

 

Development of an enhanced hybrid attention YOLOv8s small object detection method for phenotypic analysis of root nodules

March 2026

Ya Zhao | Wen Zhang | Liangxiao Zhang | Xiaoqian Tang | Du Wang | Qi Zhang | Peiwu Li

Nodule formation and their involvement in biological nitrogen fixation are critical features of leguminous plants, with phenotypic characteristics closely linked to plant growth and nitrogen fixation efficiency. However, the phenotypic analysis of root nodules…

 

Automatic body temperature detection of group-housed piglets based on infrared and visible image fusion

March 2026

Kaixuan Cuan | Feiyue Hu | Xiaoshuai Wang | Xiaojie Yan | Yanchao Wang | Kaiying Wang

Rapid and accurate measurement of body temperature is essential for early disease detection, as it is a key indicator of piglet health. Infrared thermography (IRT) is a widely used, convenient, non-intrusive, and efficient non-contact temperature measurement technology. However, the activities and clustering of group-housed piglets make it challenging to…

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