Monitoring growth and predicting crop yield through UAV-mounted spectral camera analysis of the interplay between soil compaction and vegetation index

This paper aims to introduce a prediction of crop yield based on relationship between soil compaction and vegetation index. The soil compaction increasingly with depth, which was calculated manuallyunevenly distributed in the field. The NDVI/NDRE was conducted by aerial spectral images taken by the UAV. To figure out connection, the Pearson's correlation test was applied to analyze the correlation between factors. These research results show that the NDVI/NDRE in WS and SA crops increased and decreased steadily after reaching the maximum values (0.85 +/- 0.02/ 0.38 +/- 0.02 and 0.8 +/- 0.02/ 0.28 +/- 0.02) during the reproductive stage. The NDVI/NDRE had a high relationship with the plant height, tiller number, yield components of rice. WS and SA networks were built and tested according to the training algorithm in the Matlab software for predicting rice yield with high reliability. The developed models showcase promising results in forecasting rice yield, underscoring the potential applicability of this methodology in agricultural yield prediction.