Emirates Journal of Food and Agriculture 36: 1-10, doi: 10.3897/ejfa.2024.118256
Monitoring growth and predicting crop yield through UAV-mounted spectral camera analysis of the interplay between soil compaction and vegetation index
Bui Van Huu‡, Ngo Quang Hieu‡, Luu Trong Hieu‡‡ Can Tho University, Can Tho, Vietnam
Corresponding author: Luu Trong Hieu ( luutronghieu@ctu.edu.vn ) Academic editor: Abdul Jaleel © Bui Van Huu, Ngo Quang Hieu, Luu Trong Hieu. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Citation:
Huu BV, Hieu NQ, Hieu LT (2024) Monitoring growth and predicting crop yield through UAV-mounted spectral camera analysis of the interplay between soil compaction and vegetation index. Emirates Journal of Food and Agriculture 36: 1-10. https://doi.org/10.3897/ejfa.2024.118256 |  |
Abstract
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.
Keywords
soil compaction, UAV, spectral aerial images, Pearson’s correlation, NDVI/NDRE, crop yield