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Dec 15, 2021 · In general, this study proposes a machine learning framework based on UAV remote sensing data instead of traditional manual yield measurements for cotton yield prediction, which can accurately predict cotton yields and obtain a high-resolution yield map.
- Establishing a Model to Predict The Single Boll Weight of Cotton in Northern Xinjiang by Using High Resolution UAV Remote Sensing Data
The efficient prediction of the single boll weight in a...
- Estimating Grain Yield of Maturing Rice Canopies Using High Spectral Resolution Reflectance Measurements
The yield samples were air-dried, and ttigh Resolution...
- Estimating Smallholder Crops Production at Village Level From Sentinel-2 Time Series in Mali's Cotton Belt
Theoretically, using a full VI seasonal integral (rather...
- Developing a Machine Learning Based Cotton Yield Estimation Framework Using Multi-Temporal UAS Data
An accurate prediction of cotton yield and replacing human...
- Establishing a Model to Predict The Single Boll Weight of Cotton in Northern Xinjiang by Using High Resolution UAV Remote Sensing Data
Jun 24, 2024 · Abstract: The United States cotton industry is devoted to sustainable production strategies that reduce water, land, and energy consumption while enhancing soil health and cotton yield. Climate-smart agricultural solutions are being developed to increase yields and reduce operational costs.
This study used a multisource dataset to create an explainable and accurate predictive model for cotton yield prediction over the continental United States (CONUS). A recently proposed glass-box method called explainable boosting machine (EBM), which provides transparency, reliability, and ease of interpretation, was implemented.
The method for yield predictions by combining two deep learning models including convolution neural network (CNN) model and gated recurrent unit (GRU) model, was introduced to predict yield in cotton and this combination achieved RMSE of 247 (8.9 %) (Feng et al., 2023).
The results demonstrate how a simple and robust model can be developed and utilized to help cotton climate-smart efforts. INDEX TERMS Cotton Yield Prediction, Climate Change Effect, Smart...
Aug 1, 2022 · The model predicted that the long-term adoption of hairy vetch ( Vicia villosa ), a legume cover crop, has the potential to increase cotton yield. Among the climate variables, cotton lint yield was most impacted by average maximum temperature and precipitation during flowering to open boll period.
Jun 14, 2022 · Yield monitoring is an important parameter to evaluate cotton productivity during cotton harvest. Nondestructive and accurate yield monitoring is of great significance to cotton production. Unmanned aerial vehicle (UAV) remote sensing has fast and repetitive acquisition ability.
