Cotton yield estimation using several vegetation indices

Abstract

Accurate yield estimation before harvest is important for farmers and researchers to optimize field management and increase productivity. The purpose of this study is to develop efficient cotton plant productivity using field studies and satellite imagery. Nitrogen (N) fertilizer is an important nutrient in plant development, and when suboptimal amounts are applied, it can cause yield reductions. Different vegetation indices were employed to analyze the dynamics and yield of cotton plants, with a primary focus on the Red, Near-Infrared (NIR), and Red Edge bands derived from satellite imagery. The objective was to assess the nitrogen content in the plants. The present study involved a comparative analysis of various vegetation indicators in relation to cotton plant production. The productivity of the cotton plant was assessed by employing the indices that exhibited the most influence. The analysis revealed that the MCARI index exhibited the worst weaknesses, while the CLRE index demonstrated the main performance. The productivity of each index was computed, and it was observed that the CLRE index exhibited the closest proximity to the average productivity of 34.48 cents per hectare (cent/ha). Similar results have been observed in other indices. The MCARI index exhibits a distinct value of 32.08 in comparison to the others indices. The results of this study illustrate the potential of satellite imaging in monitoring cotton yield, hence offering valuable theoretical and technological assistance for estimating cotton production in agricultural areas.

Keywords

• Cotton
• Yield
• Vegetation indices
• Biomass
• Satellite images

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