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ISSN: 2589-7217
CN: 10-1795/S
p-ISSN: 2097-2113

Fast extraction of navigation line and crop position based on LiDAR for cabbage crops

This paper describes the design, algorithm development, and experimental verification of a precise spray perception system based on LiDAR were presented to address the issue that the navigation line...

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Decoding canola and oat crop health and productivity under drought and heat stress using bioelectrical signals and machine learning

Abiotic stresses, such as heat and drought, often reduce crop yields by harming plant health. Plants have evolved complex signaling networks to mitigate environmental impacts, making monitoring in-situ...

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Accurate Orah fruit detection method using lightweight improved YOLOv8n model verified by optimized deployment on edge device

The replacement of personal computer terminal with edge device is recognized as a portable and cost-effective potential solution in solving equipment miniaturization and achieving high flexibility of...

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Multi-scale cross-modal feature fusion and cost-sensitive loss function for differential detection of occluded bagging pears in practical orchards

In practical orchards, the challenges posed by fruit overlapping, branch and leaf occlusion, significantly impede the successful implementation of automated picking, particularly for bagging pears....

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ADeepWeeD: An adaptive deep learning framework for weed species classification

Efficient weed management in agricultural fields is essential for attaining optimal crop yields and safeguarding global food security. Every year, farmers worldwide invest significant time, capital,...

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Picking point localization method based on semantic reasoning for complex picking scenarios in vineyards

In the complex orchard environment, precise picking point localization is crucial for the automation of fruit picking robots. However, existing methods are prone to positioning errors when dealing with...

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

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...

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An autonomous navigation method for field phenotyping robot based on ground-air collaboration

High-throughput phenotyping collection technology is important in affecting the efficiency of crop breeding. This study introduces a novel autonomous navigation method for phenotyping robots that leverages...

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MSNet: A multispectral-image driven rapeseed canopy instance segmentation network

Precise detection of rapeseed and the growth of its canopy area are crucial phenotypic indicators of its growth status. Achieving accurate identification of the rapeseed target and its growth region...

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A review on enhancing agricultural intelligence with large language models

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...

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

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...

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Rapid detection and visualization of physiological signatures in cotton leaves under Verticillium wilt stress

Verticillium wilt poses a severe threat to cotton growth and significantly impacts cotton yield. It is of significant importance to detect Verticillium wilt stress in time. In this study, the effects...

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A new tool to improve the computation of animal kinetic activity indices in precision poultry farming

Precision Livestock Farming (PLF) emerges as a promising solution for revolutionising farming by enabling real-time automated monitoring of animals through smart technologies. PLF provides farmers with...

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Improving accuracy and generalization in single kernel oil characteristics prediction in maize using NIR-HSI and a knowledge-injected spectral tabtransformer

Near-infrared spectroscopy hyperspectral imaging (NIR-HSI) is widely used for seed component prediction due to its non-destructive and rapid nature. However, existing models often suffer from limited...

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EU-GAN: A root inpainting network for improving 2D soil-cultivated root phenotyping

Beyond its fundamental roles in nutrient uptake and plant anchorage, the root system critically influences crop development and stress tolerance. Rhizobox enables in situ and nondestructive phenotypic...

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FGPointKAN++ point cloud segmentation and adaptive key cutting plane recognition for cow body size measurement

Accurate and efficient body size measurement is essential for health assessment and production management in modern animal husbandry. In order to realize the segmentation of the point clouds at the...

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Recognizing and localizing chicken behaviors in videos based on spatiotemporal feature learning

Timely acquisition of chicken behavioral information is crucial for assessing chicken health status and production performance. Video-based behavior recognition has emerged as a primary technique for...

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PWM offline variable application based on UAV remote sensing 3D prescription map

Precision application in orchards enhancing deposition uniformity and environmental sustainability by accurately matching nozzle output with canopy parameters. This study provides a pipeline for creating...

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

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....

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

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...

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Stereo vision based broccoli recognition and attitude estimation method for field harvesting

At present, automatic broccoli harvest in field still faces some issues. It is difficult to segment broccoli in real time under complex field background, and hard to pick tilt-growing broccoli for the...

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Boosting grapevine phenological stages prediction based on climatic data by pseudo-labeling approach

Predicting grapevine phenological stages (GPHS) is critical for precisely managing vineyard operations, including plant disease treatments, pruning, and harvest. Solutions commonly used to address viticulture...

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Unveiling the drivers contributing to global wheat yield shocks through quantile regression

Sudden reductions in crop yield (i.e., yield shocks) severely disrupt the food supply, intensify food insecurity, depress farmers' welfare, and worsen a country's economic conditions. Here, we study...

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

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...

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Navigating challenges/opportunities in developing smart agricultural extension platforms: Multi-media data mining techniques

Agricultural Extension (AE) research faces significant challenges in producing relevant and practical knowledge due to rapid advancements in artificial intelligence (AI). AE struggles to keep pace with...

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