Recent Articles

Open access

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

Hyperspectral estimation of leaf chlorophyll content in wine grape using transfer learning and three-dimensional radiation transfer model

Accurate and timely monitoring of leaf chlorophyll content (LCC) in wine grapes is essential for assessing their photosynthetic status, optimizing management and planting practices, and improving both...

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...

Decoupling tea-bud heap structure from non-imaging hyperspectral spectra for accurate single-bud trace biochemistry retrieval

Accurate, real-time, non-destructive estimation of single-bud biochemistry is critical for managing green-tea quality, yet non-imaging hyperspectral measurements of arbitrarily stacked buds are confounded...

Advancing lightweight and efficient detection of tomato main stems for edge device deployment

Automated pruning and defoliation of tomato plants are essential in modern cultivation systems for optimizing canopy structure, enhancing air circulation, and increasing yield. However, detecting main...

Dual attention guided context-aware feature learning for residual unfilled grains detection on threshed rice panicles

Accurate detection of residual unfilled grains on threshed rice panicles is a critical step in determining a reliable grain-setting rate, and holds significant potential for the development of high-quality...

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...

PlantSegNeRF: A few-shot, cross-species method for plant 3D instance point cloud reconstruction via joint-channel NeRF with multi-view image instance matching

Organ segmentation of plant point clouds is a prerequisite for the high-resolution and accurate extraction of organ-level phenotypic traits. Although the fast development of deep learning has boosted...

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...

Multi-arm robotic system and strategy for the automatic packaging of apples

Packaging is a crucial step in the commercial distribution of apples after harvest. However, achieving fast and accurate automated packaging remains a challenge. This study proposed for the first time...

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...

Optimizing herbicide reduction: A simulation approach using Artificial Intelligence and different nozzle configurations

Targeted application aims to minimize product usage by spraying only where needed. However, there is a lack of tools to evaluate the potential savings and the model's limitations. To address this, we...

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...

Maize phenological stage recognition via coordinated UAV and UGV multi-view sensing and deep learning

Crop phenological stages, marked by key events such as germination, leaf emergence, flowering, and senescence, are critical indicators of crop development. Accurate, dynamic monitoring of these stages...

CTGNN: UAV-satellite cross-domain transfer learning for monitoring oat growth in China’s key production areas

Modern agricultural production necessitates real-time, precise monitoring of crop growth status to optimize management decisions. While remote sensing technologies offer multi-scale observational capabilities,...

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...

Harvesting damage detection in maize ear harvesters based on the Fused Inverted Bottleneck Attention U-Net

Improper operating parameters in maize ear harvesters can cause physical damage to the ears, resulting in grain loss. To address the lack of real-time decision-making support for correcting improper...

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...

YOLOSc-SAM: An acceptable extraction method for farmland regions in remote sensing images using SAM

Farmland is a core spatial unit in agricultural production management, and accurately delineating farmland boundaries is of great significance for agricultural resource surveys and cropland monitoring....

Spatial pose estimation of apples for robotic harvesting

In the apple picking process, the existing robots are unable to accurately estimate the pose of apples. This often leads to damage to the fruits, branches, and even the robot fingers during grasping,...

Decoupling canopy structure effects from vegetation indices for robust assessment of potato plant nitrogen content across growth stages

Accurate monitoring of plant nitrogen concentration (PNC) is essential for precision nitrogen (N) fertilization management at the farm scale. While numerous vegetation indices (VIs) have been proposed...

A hierarchical framework for cotton boll opening rate monitoring using UAV RGB imagery

The cotton boll opening rate (CBOR) is a critical agronomic indicator determining yield and fiber quality. This study developed a hierarchical framework integrating unmanned aerial vehicle (UAV) RGB...

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