YOLO-GPP: End-to-end prediction of the grasp position and pose on tomato peduncle for robotic harvesting
June 2026
A high fresh fruit harvesting success rate relies on the real-time and precise determination of the optimal grasping position and pose of the target fruit. This study proposes an end-to-end grasp pose...
Computer vision in smart agriculture and precision farming: Techniques and applications
September 2024
The transformation of age-old farming practices through the integration of digitization and automation has sparked a revolution in agriculture that is driven by cutting-edge computer vision and artificial...
Can generative AI make farming decisions? Current status and future pathways – A case study in row crop production with ChatGPT
June 2026
The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key...
Recent advances in crop pest detection, forecasting and early warning: A review
June 2026
Crop insect pests are critical biotic stressors disrupting plant physiological functions. Their infestations not only cause direct yield losses but also threaten global food security and agricultural...
PII-CNN-LSTM: A multi-modal deep learning framework integrating novel pollination importance index for predicting optimal apple pollination windows
June 2026
Pollination optimization in apple orchards faces increasing challenges from climate variability and declining pollinator populations, necessitating precision timing strategies. This study introduces...
Application of artificial intelligence in insect pest identification - A review
March 2026
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...
Integrating hyperspectral radiation transfer modeling and deep transfer learning to estimate nitrogen density in winter wheat canopies
June 2026
Nitrogen is a core element that regulates winter wheat yield and quality, and its precise monitoring is crucial for sustainable agricultural development. Traditional empirical methods and physical inversion...
Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides
2020
Agriculture plays a significant role in the economic sector. The automation in agriculture is the main concern and the emerging subject across the world. The population is increasing tremendously and...
Automation and digitization of agriculture using artificial intelligence and internet of things
2021
The growing population and effect of climate change have put a huge responsibility on the agriculture sector to increase food-grain production and productivity. In most of the countries where the expansion...
Deep learning-based classification, detection, and segmentation of tomato leaf diseases: A state-of-the-art review
June 2025
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,...
A comprehensive review on automation in agriculture using artificial intelligence
June 2019
Agriculture automation is the main concern and emerging subject for every country. The world population is increasing at a very fast rate and with increase in population the need for food increases...
MA-UQNet: A multi-modal uncertainty quantification neural network for remote sensing-based wheat aboveground biomass estimation
June 2026
Accurate aboveground biomass estimation with quantified uncertainty is essential for precision agriculture, enabling risk-aware decision-making and strategic model improvement. Existing approaches predominantly...
Optimized modular transfer learning framework integrating PROSAIL and UAV-based hyperspectral reconstruction for cotton canopy water and nitrogen content retrieval
June 2026
Optimizing water and fertilizer management is crucial for improving cotton yield and quality. However, reliable and generalizable models for quickly and accurately estimating cotton canopy leaves water...
Fruit ripeness classification: A survey
March 2023
Fruit is a key crop in worldwide agriculture feeding millions of people. The standard supply chain of fruit products involves quality checks to guarantee freshness, taste, and, most of all, safety....
A review on enhancing agricultural intelligence with large language models
December 2025
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...
Application of artificial intelligence in cattle disease diagnosis: A comprehensive review
Available online 27 June 2026
Cattle diseases severely threaten the global agricultural economy. Traditional disease management, heavily reliant on manual observation, is inherently delayed and subjective. Artificial intelligence...
Evaluation of Multi-Object Detection models for automated goat behavior identification in intensive farming facilities
June 2026
Computer vision offers significant potential for the continuous, stress-free, and cost-effective monitoring of animal behavior, yet its application in goat farming remains limited. In this study, a...
Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review
2020
An e-nose or an e-tongue is a group of gas sensors or chemical sensors that simulate human nose or human tongue. Both e-nose and e-tongue have shown great promise and utility in improving assessments...
Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments
September 2024
Instance segmentation, an important image processing operation for automation in agriculture, is used to precisely delineate individual objects of interest within images, which provides foundational...
Comparison of CNN-based deep learning architectures for rice diseases classification
September 2023
Although convolutional neural network (CNN) paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures, few studies have focused on the performance comparison...
AI-driven aquaculture: A review of technological innovations and their sustainable impacts
September 2025
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....
Transformer-based cross-view LiDAR–orthomosaic fusion for geo-localization and digital modeling in apple orchards
June 2026
Precision agriculture increasingly relies on accurate large-scale localization and digital modeling for autonomous tasks in orchards. However, map drift and localization uncertainty under GNSS-limited...
Toward autonomous agriculture: Integrating computer vision and large language models for intelligent weed management
Available online 30 May 2026
Weed diagnosis and management in agricultural fields still rely heavily on manual observation and expert knowledge, resulting in limited efficiency, accessibility, and decision interactivity. Although...
DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes
March 2024
Rice stands as a crucial staple food globally, with its enduring sustainability hinging on the prompt detection of rice leaf diseases. Hence, efficiently detecting diseases when they have already occurred...
AgriMAPO: A multimodal automatic prompt optimization approach for crop disease classification using large language models
June 2026
Accurate identification of crop diseases is a core challenge in promoting precision agriculture and reducing yield losses. Current deep learning-based recognition methods heavily rely on large-scale...
