A5077319306- Smart Agriculture and AI
- Spectroscopy and Chemometric Analyses
- Remote Sensing in Agriculture
- Plant Pathogenic Bacteria Studies
- Plant tissue culture and regeneration
- Weed Control and Herbicide Applications
- Pesticide and Herbicide Environmental Studies
- Insurance and Financial Risk Management
- Crop Yield and Soil Fertility
- Nematode management and characterization studies
- Gold and Silver Nanoparticles Synthesis and Applications
- Advanced Data Processing Techniques
- Plant Pathogens and Fungal Diseases
- CRISPR and Genetic Engineering
- Identification and Quantification in Food
- Educational and Technological Research
- Reliability and Maintenance Optimization
- Statistical Distribution Estimation and Applications
- Legume Nitrogen Fixing Symbiosis
- Artificial Intelligence in Healthcare
- Software Reliability and Analysis Research
- Genetically Modified Organisms Research
- Genetic Mapping and Diversity in Plants and Animals
- Spectroscopy Techniques in Biomedical and Chemical Research
Zhejiang University
2022-2024
Hefei University
2024
Ministry of Agriculture and Rural Affairs
2022
Anhui Normal University
2019
The object detection method based on deep learning convolutional neural network (CNN) significantly improves the performance of wheat head images obtained from near ground. Nevertheless, for different stages, high density, and overlaps captured by aerial-scale unmanned aerial vehicle (UAV), existing learning-based methods often have poor effects. Since receptive field CNN is usually small, it not conducive to capture global features. visual Transformer can information an image; hence we...
The non-judicious use of pesticides in agro-food poses a severe threat to food safety and human health. As an emerging chromatographic fingerprint provider, surface-enhanced Raman spectroscopy analysis (SERS) sheds bright light on sensitive nondestructive detection pesticide residues. This research proposed novel strategy detect three-pesticide residues (thiabendazole, carbendazim, chlorpyrifos) tomato peel based the flexible sticky SERS substrate. After selecting best commercial adhesive...
Bacterial blight poses a threat to rice production and food security, which can be controlled through large-scale breeding efforts toward resistant cultivars. Unmanned aerial vehicle (UAV) remote sensing provides an alternative means for the infield phenotype evaluation of crop disease resistance relatively time-consuming laborious traditional methods. However, quality data acquired by UAV affected several factors such as weather, growth period, geographical location, limit their utility...
Hyperspectral imaging technique combined with machine learning is a powerful tool for the evaluation of disease phenotype in rice disease-resistant breeding. However, current studies are almost carried out lab environment, which difficult to apply field environment. In this paper, we used visible/near-infrared hyperspectral images analysis severity bacterial blight (BB) and proposed novel index construction strategy (NDSCI) application. A designed long short-term memory network attention...
Glyphosate is one of the most widely used non-selective herbicides, and creation glyphosate-resistant cultivars solves problem limited spraying area. Therefore, it great significance to quickly identify resistant without destruction during development superior cultivars. This work took maize seedlings as experimental object, spectral indices leaves were calculated construct a model with good robustness that could be in different experiments. Compared no transfer strategies, transferability...
Abstract Developing herbicide resistant cultivars is one of the effective methods to solve safety problem caused by use herbicide. In this study, hyperspectral image was used develop more robust leaf chlorophyll content (LCC) prediction model based on different datasets finally analyze response LCC glyphosate-stress. Chlorophyll a fluorescence (ChlF) dynamically monitor photosynthetic physiological transgenic glyphosate-resistant and wild glyphosate–sensitive maize seedlings, applying...
This paper studies the application of Bayesian model in construction personalized learning platform for Internet education. Aiming at and assessment courseware course, this presents a method to calculate passing rate knowledge relation between based on results course organization evaluation. First all, by organizing pre-class comprehensive test, pre-school quiz post-school three main evaluation methods establish corresponding statistical model, Bayes formula deduce most suitable students...
In this paper, a real-time monitoring method of portfolio risk measurement based on likelihood ratio is proposed through the research paradigm intelligent simulation analysis. The value data mined with idea green simulation, and theoretical model built to realize fixed length time, that is, can always be obtained after certain period time when market state given at current moment. Using large loss probability as measure investment risk, path corresponding each are according nested Monte...
Abstract Background Transgenic glyphosate-resistant maize has emerged as a way to expand the use of glyphosate for weed control. Studying microbiome in transgenic plant and rhizosphere soil is vital understanding mechanism optimizing design crops. Results In our study, modification did not affect initial bacterial community leaf, stem, root maize, but promoted healthier soil. After stimulation, recruited more beneficial bacteria regulate biocontrol, N fixation P solubilization both tissues...
Glyphosate is a widely used nonselective herbicide. Probing the glyphosate tolerance mechanism necessary for screening and development of resistant cultivars. In this study, hyperspectral image was to develop more robust leaf chlorophyll content (LCC) prediction model based on different datasets finally analyze response LCC glyphosate-stress. Chlorophyll fluorescence (ChlF) dynamically monitor photosynthetic physiological transgenic glyphosate-resistant wild glyphosate-sensitive maize...