A5103251275- Remote Sensing in Agriculture
- Leaf Properties and Growth Measurement
- Remote Sensing and LiDAR Applications
- Smart Agriculture and AI
- Plant Water Relations and Carbon Dynamics
- Soil Geostatistics and Mapping
- Supercapacitor Materials and Fabrication
- Crop Yield and Soil Fertility
- Hydrology and Drought Analysis
- Soil Moisture and Remote Sensing
- Spectroscopy and Chemometric Analyses
- Graphene research and applications
- Land Use and Ecosystem Services
- Climate change impacts on agriculture
- Protein Structure and Dynamics
- Computational Drug Discovery Methods
- Aerogels and thermal insulation
- Hydrological Forecasting Using AI
- Greenhouse Technology and Climate Control
- Air Quality Monitoring and Forecasting
- Irrigation Practices and Water Management
- Urban Heat Island Mitigation
- Environmental and Agricultural Sciences
- Advanced Technologies in Various Fields
- Advancements in Battery Materials
Sanya University
2022-2025
Chinese Academy of Agricultural Sciences
2021-2025
Institute of Crop Sciences
2021-2025
Wuhan Institute of Technology
2023-2024
Wuhan University
2021-2024
Institute of Bast Fiber Crops
2024
Jilin University
2023
Guangxi University of Chinese Medicine
2013
Guangxi University
2013
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but using multimodal to estimate LAI, the effect tassels soil background, remain understudied. Our research aims (1) determine how contribute propose a framework based on remote-sensing data, (2) evaluate robustness adaptability an model that uses...
The high proportion of soil background pixels in UAV remote sensing images is an important reason for the uncertainty high-precision leaf area index (LAI) estimation at early growth stages crops. Although traditional method removing from based on canopy coverage (CC) eliminates pure pixels, it can cause spectral saturation and therefore affect accuracy LAI estimation. In this study, a new called reduced contribution (CS) was constructed to improve This be improved by introducing quantitative...
Accurately monitoring the crop water conditions (CWC) is vital for agricultural management. Traditional in situ measurements are limited by inefficiency and lack of spatial information. However, development unmanned aerial vehicle (UAV) applications agriculture now provides a high throughput cost-effective method to obtain field growth Unfortunately, current UAV-based drought indices do not capture time series information, or accuracy limited. This study uses multispectral thermal...
Maize is one of the main grain reserve crops, which directly affects food security country. It extremely important to evaluate growth status maize in a timely and accurate manner. Canopy Chlorophyll Density (CCD) closely related crop health status. A estimation CCD helpful for managers take measures avoid yield loss. Thus, many methods have been developed estimate with remote sensing data. However, relationship between features used these at different stages unclear. In addition, was...
Vertically aligned graphene nanosheet via facile hydrothermal/salt-assisted pyrolysis (HSP) method for high-performance redox supercapacitors.
The accurate estimation of regional crop yields holds significant importance for optimizing subsequent resource allocation and maximizing economic returns in agriculture. Crop yield can be effectively estimated by assessing the overall growth status through long-term remote sensing observations. However, most previous studies have relied on data from one or a few periods estimation, thus lacking comprehensive description entire growth. Furthermore, past algorithms not considered their...
Maize (Zea mays L.), one of the most important agricultural crops in world, which can be devastated by lodging, strike maize during its growing season. lodging affects not only yield but also quality kernels. The identification is helpful to evaluate losses due natural disasters, screen lodging-resistant crop varieties, and optimize field-management strategies. accurate detection inseparable from determination degree helps improve field management crop-production process. An approach was...
Maize is among the most important grain crops. Aboveground biomass (AGB) a key agroecological indicator for crop yield prediction and growth status monitoring, etc. In this study, we propose two new methods, improved algorithm (iCBA) iCBA with piecewise function (iCBA-PF), to estimate maize AGB. Multispectral (MS) images, visible-band (RGB) light detection ranging (LiDAR) data were collected using unmanned aerial vehicles (UAVs). Vegetation indices (VIs) VI-weighted canopy volume model...
Maize leaf spot is a common disease that hampers the photosynthesis of maize by destroying pigment structure leaves, thus reducing yield. Traditional monitoring time-consuming and laborious. Therefore, fast effective method for needed to facilitate efficient management yield safety. In this study, we adopted UAV multispectral thermal remote sensing techniques monitor two types diseases, i.e., southern blight caused Bipolaris maydis Curvularia lutana. Four state-of-the-art classifiers (back...
Two typical flux towers and surrounding 100 km × areas in Northern China. Up-scaling the instantaneous latent heat (LE) to daily-scale is an important step for estimate daily evapotranspiration based on satellite observations. This study evaluated performance three up-scaling methods: constant evaporation fraction (CEF), diurnal LE variation (DLEV) geosynchronous (GS) by using tower observations at site-scale regional scales, respectively. The purpose was improve accuracy of LE. results...
Objective In the context of “internet + medical health” and emphasis on evaluation mechanism for health talents in China, we design an index system doctors online platforms by synthesizing two patterns existing platforms, which is first step to enhance capabilities platforms. Methods Based doctor model integrating information systems success (ISS-DE model) grounded theory, indicators were obtained through expert interviews, offline institutions investigation, literature research, assigned...
Crop growth parameters are the basis for evaluation of crop status and yield. The aim this study was to develop a more accurate estimation model corn combined with multispectral vegetation indexes (VIopt) differential radar information (DRI) derived from SAR data. Targeting plant height (H) BBCH (Biologische Bundesanstalt, Bundessortenamt CHemical industry) phenological parameters, compared accuracies various corresponding VIDRI (vegetation index corrected by DRI) in inverting parameters....
Maize leaf diseases have a significant impact on global industry and food security. Monitoring these large scale with non-destructive remote sensing technology is promising approach to mitigating their impacts. However, monitoring early maize at canopy scales still challenging. Effective disease-specific indices been developed scales, but the differences in planting density cultivars may performance for crop disease scales. Here, we hypothesize that an index sensitive pigments insensitive...
Kernel methods, such as kernel PCA, PLS, and support vector machines, are widely known machine learning techniques in biology, medicine, chemistry, material science. Based on nonlinear mapping Coulomb function, two 3D approaches were improved applied to predictions of the four protein tertiary structural classes domains (all- α , all- β / + ) five membrane types with satisfactory results. In a benchmark test, performances approach compared those neural networks, ensemble algorithm....
To date, the gram-scale production and application of vertically aligned graphene nanosheet arrays (VAGNAs) is limited by established chemical vapor deposition method, which requires expensive instruments additional substrates. Herein, we developed a facile high-quality VAGNAs method named as hydrothermal/salt-assisted pyrolysis (HSP) method. can be fabricated on large scale this HSP from low-cost, green renewable biomass instead fossil gas precursors, no instrument or extra substrate...
Accurately monitoring the crop water status (CWS) will contribute to field agricultural management. Traditional in situ measurements were limited by inefficiency and lack of spatial information. The development unmanned aerial vehicle (UAV) application agriculture provides a high throughput cost-effective method obtain growth However, current UAV-based drought indices can not capture time series information, or accuracy is limited. In this study, three indices: commonly used Normalized...