Yield predictions of ‘Del Cerro’ cotton (Gossypium hirsutum L.) germplasm by multispectral monitoring in the north coast of Peru

Abstract

Peruvian cotton (Gossypium hirsutum L.) has great acceptance and demand in the national and international textile market due to the excellent quality of its extra-long fiber, durability and resistance. To evaluate cotton cultivar performance, we need to use tools such as drones + sensors. However, these tools have not been widely used in the Peruvian agricultural area. Here we evaluated seven agro-morphological characters of 21 accessions of Del Cerro cotton cultivar from the National Institute of Agrarian Innovation of Peru with highthroughput phenotyping methods. We employed a Matrice 300 RTK unmanned aerial vehicle (UAV) with the MicaSense Dual Red Edge Blue multispectral sensor to assess plant height, yield, and spectral signature during physiological maturity stage; other morphological characters were manually scored. Multispectral monitoring revealed the phytosanitary status of the crop, which begins to enter senescence after 130 d after sowing (DAS) due to the decrease of the vegetation indices (VI). Pearson correlations between yield and VI showed favorable values, exceeding 0.60 at 94 DAS for normalized difference vegetation index (NDVI), relative vigor index (RVI), and normalized difference red edge index (NDRE). Principal component analysis (PCA) was conducted on the same date, a significant correlation was found between NDVI and yield. Additionally, yield prediction equations were generated with the normalized difference water index (NDWI) showing an R value of 0.74 at 130 DAS. The findings of this study suggest that remote sensing evaluation is suitable for estimating ‘Del Cerro’ cotton yield in infrared (IR) bands, providing a tool for germplasm evaluation that can influence decision-making and better conservation strategies.