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Abstract
This study aimed to investigate the contributions of intercepted photosynthetically active radiation (IPAR), radiation use efficiency (RUE), and harvest index (HI) to nitrogen(N)-induced yield loss in cotton and to predict the aforementioned traits using UAV-based RGB and multispectral imagery. The experiment was conducted with five N application rates in a randomized complete block design in Georgia, USA during the 2021 and 2022 growing seasons. Physiological measurements along with UAV-based imagery were collected. Results indicated that light interception by the canopy was the primary contributor to N-induced yield loss, and boll density was the primary yield component governing N-induced variation in lint yield. Furthermore, certain vegetation indices derived from UAV-based imagery in integration with growing degree days (GDD) explained more than 90% of variation in canopy light interception. The developed models were able to predict some yield-driving parameters in response to nitrogen.