Year: 2025
Type: article
Abstract: Wide‐spread adoption of proximal sensors in crop health assessment requires understanding of changes in canopy reflectance during the growing season and associations among readings from different sensors. Chlorophyll meter reading (Soil Plant Analysis Development, SPAD), red normalized difference vegetation index (RNDVI), and red‐edge normalized difference vegetation index (RENDVI) were measured for sugarbeet (Beta vulgaris L.), corn (Zea mays), sunflower (Helianthus annuus L.), soybean (Glycine max), and spring wheat (Triticum aestivum) throughout the 2021 growing season. Cumulative growing degree days (GDD) had a significant relationship with SPAD, RNDVI, and RENDVI. The correlation coefficient indicated SPAD was more associated with RENDVI (r = 0.73) than RNDVI (0.50). The R2 values of multiple linear regression of SPAD and GDD with RNDVI and RENDVI were the lowest for spring wheat (0.33 and 0.52, respectively) and the highest for corn (0.94 and 0.95, respectively). For all major five crops grown in the Northern Great Plains, GDD showed a strong relationship with all three indices. For in‐season crop health assessment based on vegetation indices, inclusion of GDD could be a useful predictor variable to develop a single model algorithm applicable for multiple crops at a regional scale.
DOI: 10.1002/cft2.70041
Author: A. Chatterjee
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: bronze
OpenAlex ID: W4409307889