Recent Articles

Open access

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

How large-scale foundation models benefit precision livestock farming: A survey

Precision Livestock Farming integrates advanced technologies such as the internet of things (IoT), artificial intelligence (AI), big data and machinery automation into traditional animal husbandry to...

Zero-shot crop segmentation via 3D depth-aware vision pipeline using unsupervised clustering

Pixel-level crop segmentation is essential for precision agriculture yet remains severely constrained by the prohibitive cost and labor intensity of generating large-scale annotated datasets, a critical...

Mix-soil-spectra: Near-infrared spectroscopy combined with contrastive and ensemble learning for accurate prediction of soil organic matter and total nitrogen

Accurate and timely quantification of soil total nitrogen (TN) and organic matter (OM) is critical for sustaining crop growth, improving yield, and supporting smart agriculture. Near-infrared spectroscopy...

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...

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...

STGMAE: A GNSS data-driven pre-training spatiotemporal graph masked autoencoder for agricultural machinery trajectory operation mode identification

Utilizing spatiotemporal features in massive amounts of trajectory data to identify the operation mode of agricultural machinery trajectories is a key task in precision agriculture. Most of the previous...

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...

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...

End-to-end detection of cough and snore based on ResNet18-TF for breeder laying hens: A field study

Cough and snore are the most representative vocalizations for chicken respiratory diseases, which severely restrict poultry health due to highly contagious and lethal characteristics. Nighttime inspection...

Energy-saving and stability-enhancing control for unmanned distributed drive electric plant protection vehicle based on active torque distribution

The distributed drive electric plant protection vehicle (DDEPPV), equipped with a unique four-wheel independent drive system, demonstrates excellent path-tracking capability and dynamic performance...

Two-year remote sensing and ground verification: Estimating chlorophyll content in winter wheat using UAV multi-spectral imagery

Leaf chlorophyll content serves as a critical biophysical indicator for characterizing wheat growth status. Traditional measurement using a SPAD meter, while convenient, is hampered by its localized...

Multi-scale feature alignment network for 19-class semantic segmentation in agricultural environments

To improve environmental perception and ensure reliable agricultural machinery navigation during field transitions under unstructured farm road conditions, this study utilizes high-resolution RGB camera...

SCLFormer: A synergistic convolution-linear attention transformer for hyperspectral image classification of mechanical damage in maize kernels

Classifying mechanical damage in maize kernels using hyperspectral imaging is crucial for food security and loss reduction. Existing methods are constrained by high computational complexity and limited...

Integrating 3D detection networks and dynamic temporal phenotyping for wheat yield classification and prediction

Automated phenotyping of wheat growth stages from 3D point clouds is still limited. The study presents a concise framework that reconstructs multi-view UAS imagery into 3D point clouds (jointing to...

Adaptive compensation method for navigation positioning errors considering the vibration characteristics of a combine harvester

Positioning accuracy directly affects the operational performance and stability of navigation systems. However, in complex field environments, severe vibrations during combine harvester operation can...

SpecColorNet: An interpretable multimodal deep learning approach for predicting SSC of multiple pears

Visible/near-infrared spectroscopy provides a non-destructive approach for evaluating soluble solids content (SSC) of pears (Pyrus pyrifolia Nakai). However, variations among pear cultivars, especially...

Prediction of wheat stem biomass using a new unified model driven by phenological variable under remote-sensed canopy vegetation index constraints

Timely and accurate prediction of stem dry biomass (SDB) is crucial for monitoring crop growing status. However, conventional biomass estimation models are often limited by the influence of crop growth...

LPNet: A lightweight progressive network for calyx-aware apple pose estimation in orchard environments

Robotic apple harvesting has gradually become a critical requirement for modern agriculture. However, complex orchard environments and limited computational resources pose significant challenges for...

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