Recent Articles

Open access

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

PII-CNN-LSTM: A multi-modal deep learning framework integrating novel pollination importance index for predicting optimal apple pollination windows

Pollination optimization in apple orchards faces increasing challenges from climate variability and declining pollinator populations, necessitating precision timing strategies. This study introduces...

Integrating hyperspectral radiation transfer modeling and deep transfer learning to estimate nitrogen density in winter wheat canopies

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...

Optimized modular transfer learning framework integrating PROSAIL and UAV-based hyperspectral reconstruction for cotton canopy water and nitrogen content retrieval

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...

YOLO-GPP: End-to-end prediction of the grasp position and pose on tomato peduncle for robotic harvesting

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...

MA-UQNet: A multi-modal uncertainty quantification neural network for remote sensing-based wheat aboveground biomass estimation

Accurate aboveground biomass estimation with quantified uncertainty is essential for precision agriculture, enabling risk-aware decision-making and strategic model improvement. Existing approaches predominantly...

Transformer-based cross-view LiDAR–orthomosaic fusion for geo-localization and digital modeling in apple orchards

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...

Evaluation of Multi-Object Detection models for automated goat behavior identification in intensive farming facilities

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...

Can generative AI make farming decisions? Current status and future pathways – A case study in row crop production with ChatGPT

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...

Leveraging artificial intelligence and evolutionary algorithms for optimising cow supplementation and milk production

Efficient allocation of grain-based concentrate is essential for maximising milk yield and improving profitability in dairy farming. This study optimised concentrate allocation for dairy cows by integrating...

Empowering Chinese medicinal agriculture through AI-driven technologies: A comprehensive review

Traditional Chinese medicine, with its rich history and profound influence on healthcare, is deeply rooted in medicinal plants, which serve as the foundation for Chinese herbal medicines (CHMs). However,...

AgriMAPO: A multimodal automatic prompt optimization approach for crop disease classification using large language models

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...

Distributed crop disease detection with deep Q-network agent decision-making in a compressed state space

Crop disease detection is vital for reducing agricultural losses. Traditional centralized methods face challenges with data privacy and model performance. Distributed learning offers a promising alternative,...

An integrated time series modeling and computer vision framework for predictive structure characterization of extruded plant-based meat products

Plant-based meat extrusion is a complex multi-stage process involving dynamic interactions among raw materials, operational parameters, and resulting product structure. Maintaining consistent product...

Multimodal remote sensing combination for maize LAI estimation: Stacking model development and phenology-specific feature sensitivity analysis

Leaf Area Index (LAI) is a key biophysical parameter for characterizing canopy structure, playing a critical role in precision agricultural monitoring and management. However, traditional optical remote...

Optimization and evaluation of weed control performance in variable-rate patch spraying in field: Small-scale prescription operation

Weed management is an important means to ensure crop production, and the extensive use of herbicides destroys the ecological balance of farmland and enhances weed resistance. In this paper, an intelligent...

Recent advances in crop pest detection, forecasting and early warning: A review

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...

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...

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