Guowei Li

High-Throughput Estimation of Aboveground Peanut Biomass with Optimized Spectral–Textural Features from Unmanned Aerial Vehicle Multispectral Imagery

Liya Hu, Bo Bai, Juntao Yang, Mingxuan Song et autres

cn (code pays fourni par la source)

Chiral of D-type mesoporous silica deliver anti-inflammatory drug with double synergism

Xue Yan, Lu Wang, Zheng Zhang, Xianbao Shi et autres

Chiral drug delivery systems have gained great attention in novel drug delivery applications. To explore their exceptional functions, a series of chiral mesoporous silica xerogel (L-SX, D-SX) was constructed using biomimetic method and another series of chiral mesoporous silica nanoparticles (L-MSNs, D-MSNs) …

cn (code pays fourni par la source)

A novel deep learning framework for High-Throughput peanut seedling identification across diverse germplasm and complex field environments

Jiangtao Zhao, Zhenhai Li, Bo Bai, Xue Kong et autres

• A robust deep learning model (P-YOLOv11s) is proposed for peanut seedling detection. • The model excels across 1025 genotypes and varying field conditions. • UAV flight altitude is the most critical factor for detection accuracy. • The framework enables high-throughput seedling …

cn, Éthiopie (code pays fourni par la source)

Graph Self-Attention Network with Semantic Embedding for Stem-Leaf Separation from 3D Point Clouds

Anhao Yang, Haiyang Wu, Juntao Yang, Zhenhai Li et autres

Abstract. In the context of agricultural modernization, precise 3D organ segmentation has become indispensable for automated extraction of phenotypic traits. In particular, the precise delineation of stem and leaf structures from 3D point clouds is critical for monitoring plant growth and supporting …

cn (code pays fourni par la source)

Integrating Vegetation Indices and Texture Features from UAV multispectral image for Non-destructive Peanut Aboveground Biomass Estimation

Liya Hu, Yi Tan, Dandan Liu, Mingxuan Song et autres

Abstract. High-throughput phenotyping monitoring has become increasingly important in modern agriculture, as it can collect plant images to extract and analyse phenotype data related to growth and yield, thereby reducing crop monitoring costs. Aboveground biomass (AGB) is a key indicator for evaluating …

cn (code pays fourni par la source)

Evaluating the Seedling Emergence Quality of Peanut Seedlings via UAV Imagery

Guanchu Zhang, Qi Wang, Guowei Li, Dunwei Ci et autres

Accurate evaluation of peanut seedling emergence is critical for ensuring agronomic research accuracy and planting benefit efficiency, but traditional manual methods are limited by strong subjectivity and inconsistent batch inspection standards. In order to quickly and accurately evaluate the emergence rate and …

cn (code pays fourni par la source)

Semantic embedding-guided graph self-attention network for plant stem–leaf separation from 3D point clouds

Anhao Yang, Juntao Yang, Haiyang Wu, Guowei Li

cn (code pays fourni par la source)

Above-Ground Biomass Estimation of Peanut by Integrating Spectral, Textural, and Morphological Characteristics from UAV Imagery

Jiayin Liu, Mingxuan Song, Sa Li, Yirou Liu et autres

Above-ground biomass (AGB) is a key parameter to evaluate the growth status of plant population, which is usually expressed by the total mass of vegetation. The accurate measurement of AGB is of great significance in the research and application of precision agriculture. …

cn (code pays fourni par la source)

Regulation of DNA Methylation in Peanut Leaves and Roots: Uncovering the Molecular Mechanisms for Increased Yield After Single‐Seed Sowing

Shi Kai Fan, Jialei Zhang, Fang‐Ji Xu, Zhaohui Tang et autres

Cytosine methylation is a crucial epigenetic modification that responds to various environmental cues, yet the specific mechanisms influencing planting patterns remain incompletely understood. This study reveals significant growth differences between single-seed (SS) precision sowing and double-seed (DS) sowing observed 42 days after …

cn (code pays fourni par la source)

The PROSPECT model in high-throughput phenotyping for peanut leaf parameter estimation: Comparative performance of hyperspectral inversion models

Xue Kong, Jiangtao Zhao, Yirou Liu, Bo Bai et autres

Accurate estimation of leaf biochemical parameters is crucial for understanding crop physiology and monitoring nutritional status. Remote sensing algorithms perform well on limited germplasm, but the transferability to high-throughput phenotyping with diverse genotypes remains unclear. This study estimated leaf chlorophyll content (Cab), …

cn (code pays fourni par la source)

Integration of UAV Multi-Source Data for Accurate Plant Height and SPAD Estimation in Peanut

Ning He, Bo Chen, Xianju Lu, Bo Bai et autres

Plant height and SPAD values are critical indicators for evaluating peanut morphological development, photosynthetic efficiency, and yield optimization. Recent unmanned aerial vehicle (UAV) technology advancements have enabled high-throughput phenotyping at field scales. As a globally strategic oilseed crop, peanut plays a vital …

cn (code pays fourni par la source)

Editorial: Crop abiotic stress: advances in germplasm/gene discovery and utilization

Guowei Li, Hui Song, Ran Hovav, Dayong Cui

a robust framework for identifying superior materials and facilitating the development of breakthrough crop cultivars. This Research Topic focuses on recent advances in germplasm and gene discovery related to abiotic stress management in crops, aiming to enhance our understanding of crop responses …

cn, il (code pays fourni par la source)