Hyperspectral reflectance-based partial least squares regression models for predicting cotton leaf physiological traits

Alterations in the mechanistic drivers of photosynthesis have the potential to improve crop productivity, but their measurement is inherently time-consuming using traditional methods. High-throughput approaches to estimate photosynthesis using hyperspectral reflectance could be developed by leveraging variation in cotton (Gossypium hirsutum L.) leaf traits generated through nitrogen management, synthetic growth regulation strategies, and leaf position within the canopy. Currently, no such models exist for cotton, and interactions among the aforementioned factors are relatively unexplored for cotton leaf traits.  This study aimed to (1) evaluate the effects of N application rate, mepiquat chloride (MC) management, and leaf position within the canopy on photosynthesis and its components, and (2) develop and validate hyperspectral reflectance-based partial least squares regression (PLSR) models for predicting cotton leaf physiological traits. N rate and leaf position interac..., , # Hyperspectral reflectance-based partial least squares regression models for predicting cotton leaf physiological traits ## PLSR Model Coefficients for Cotton Leaf Traits This folder contains Partial Least Squares Regression (PLSR) model coefficients and jackknife coefficient files for estimating cotton leaf traits from reflectance spectra (500–2400 nm). ## File Naming Convention * **[Trait]PLSR_Coefficients[#comp].csv** Standard coefficients for estimating traits using the specified number of PLSR components. * **[Trait]_Jackkife_PLSR_Coefficients.csv** Jackknife coefficients used to estimate the uncertainty (standard deviation and confidence intervals) of trait predictions. **Example:** * `A_PLSR_Coefficients_15comp.csv` * `A_Jackkife_PLSR_Coefficients.csv` ## Column Descriptions To assist users unfamiliar with spectral modeling, below is a description of the variables (column headers) in the CSV files: ### 1. Standard Coefficients Files (`[Trait]PLSR_Coefficients[#comp]...,