Research background and significance
Using drones equipped with hyperspectral imagers to collect cotton data, and using ground spectrometers to collect ground data simultaneously. After data preprocessing, airborne cotton orthophotos were obtained, and the accuracy and reliability of the data were verified by typical spectral characteristic values and first-order differentials, which provided a reference for cotton growth status monitoring. It not only improved the efficiency of cotton planting management, but also provided a scientific basis for cotton pest control, yield and quality evaluation, and promoted the modernization and intelligent development of cotton production.
Equipment application introduction
1. Cotton growth status monitoring: Remote sensing monitoring of cotton by drones equipped with imaging hyperspectral sensors can analyze the spectral data of cotton to obtain information such as nutrient content and growth status of cotton. This method can accurately and quickly obtain this information without destroying crops, which helps to optimize cotton planting management.
2. Cotton pest and disease monitoring: Hyperspectral technology can help monitor cotton pests and diseases by analyzing the spectral characteristics of cotton. For example, by analyzing the changes in the spectral reflectance of cotton leaves, it is possible to identify whether cotton is affected by pests and diseases, so that prevention and control measures can be taken in time.
3. Cotton yield and quality monitoring: Hyperspectral technology can also be used to monitor cotton yield and quality. By analyzing the leaf area index (LAI) of cotton, the yield of cotton can be estimated. At the same time, the quality of cotton can be evaluated by combining the spectral characteristic value and the first-order differential, providing a scientific basis for cotton planting and harvesting.
4. Cotton impurity detection: Hyperspectral cameras were first widely used in cotton impurity detection. By analyzing the spectral characteristics of the cotton surface, impurities in cotton, such as hair, polypropylene yarn, colored thread, etc., can be detected, thereby improving the quality of cotton.
Training site
