Recent Articles

Open access

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

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

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,...

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

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...

Application of artificial intelligence in insect pest identification - A review

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...

A perspective analysis of imaging-based monitoring systems in precision viticulture: Technologies, intelligent data analyses and research challenges

This paper presents a comprehensive review of recent advancements in intelligent monitoring systems within the precision viticulture sector. These systems have the potential to make agricultural production...

Multivariate stacked regression pipeline to estimate correlated macro and micronutrients in potato plants using visible and near-infrared reflectance spectra

The ability to sense nutrient status in potato plants using spectroscopy has several merits including the ability to proactively respond to deficiencies of certain elements. While research so far has...

YOLO-light-pruned: A lightweight model for monitoring maize seedling count and leaf age using near-ground and UAV RGB images

Maize seedling count and leaf age are critical indicators of early growth status, essential for effective field management and breeding variety selection. Traditional field monitoring methods are time-consuming,...

Application of navigation technology in agricultural machinery: A review and prospects

With the rapid advancement of information technology, the intelligent and unmanned applications of agricultural machinery and equipment have become a central focus of current research. Navigation technology...

Early detection of wheat powdery mildew: A multi-source in situ remote sensing approach enabled by stacked ensemble learning

Powdery mildew seriously hinders photosynthesis and nutrient accumulation in wheat, and its early detection holds the key to enhancing control efficacy. In this research, solar-induced chlorophyll fluorescence...

A comprehensive review of obstacle avoidance for autonomous agricultural machinery in multi-operational environment

As automation becomes increasingly adopted to mitigate labor shortages and boost productivity, autonomous technologies such as tractors, drones, and robotic devices are being utilized for various tasks...

Multi-stage fusion of dual attention mask R-CNN and geometric filtering for fast and accurate localization of occluded apples

In unstructured orchard environments, factors such as complex lighting, fruit occlusion, and fruit clustering significantly reduce the accuracy of apple detection and 3D localization in robotic harvesting...

A lightweight model based on knowledge distillation for free-range chickens detection in complex commercial farming environments

Side-view imaging for monitoring free-range chickens on edge devices faces significant challenges due to complex backgrounds, occlusions, and limited computational resources, which particularly affect...

A lightweight keypoint detection model-based method for strawberry recognition and picking point localization in multi-occlusion scenes

Strawberries grown on elevated stands usually suffer from fruit occlusion issues, which severely limit the implementation of strawberry recognition and picking point localization, and the embedded devices...

Advancing UAV-based wheat phenology monitoring: A dual-mode framework integrating time-series reconstruction, noise augmentation, and deep learning for robust BBCH estimation

Precise monitoring of wheat phenology (BBCH scale) is essential for agricultural optimization, yet UAV-based single-phase monitoring encounters spectral ambiguities where multiple vegetation indices...

Inversion of plant functional traits from hyperspectral imagery enhances the distinction of wheat stripe rust severity

Wheat stripe rust can cause yield losses of up to 40 % during severe outbreaks, underscoring the importance of timely and accurate detection for effective management. Traditional hyperspectral methods...

Utilizing interpretable machine learning algorithms and multiple features from multi-temporal Sentinel-2 imagery for predicting wheat fusarium head blight

Wheat Fusarium head blight (FHB) severely affects wheat yields, and predicting its occurrence and spatial distribution is essential for safeguarding crop production. This study presents an interpretable...

PlaneSegNet: A deep learning network with plane attention for plant point cloud segmentation in agricultural environments

Accurately extracting plant point clouds from complex agricultural environments is essential for high-throughput phenotyping in smart farming. However, existing methods face significant challenges when...

Smart agriculture technology: Real-time generation method of local soil property distribution maps based on WGAN-GPM

With the advancement of smart agriculture, precision variable-rate seeding requires high-resolution soil information. However, existing methods still fall short in generating localized soil property...

Improved YOLOv8 for multi-colored apple fruit instance segmentation and 3D localization

Robotic apple harvesting requires precise instance segmentation and 3D localization, especially for multi-colored apples under complex orchard conditions with occlusions and variable lighting. Current...

Transfer learning-based soybean LAI estimations by integrating PROSAIL, UAV, and PlanetScope imagery

Accurate Leaf Area Index (LAI) estimations at the soybean plot scale is achievable using high-resolution Unmanned Aerial Vehicle (UAV) imagery and field measurement samples. However, the limited coverage...

Organ3DNet: A deep network for segmenting organ semantics and instances from dense plant point clouds

Worldwide food shortage has put the plant phenotyping research to the spotlight because phenotyping enhances crop yield under limited land use by accelerating the cycle of modern breeding. The prerequisite...

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...

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...

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...

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....

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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