Estimation of Specific Leaf Area and Nitrogen Concentration in Sweet Corn and Snap Bean Using Narrowband Reflectance Spectroscopy and Partial Least Square Regression.

Non-destructive measurements of leaf nitrogen (N) concentration and specific leaf area are needed for N simulation model development and calibration, as well as improved in-season N management. Many reflectance-based techniques for N concentration require calibration across species, cultivars, growing stages, and cultural practices.  Reflectance spectroscopy (i.e., hyperspectral data), in combination with partial least square regression (PLSR) models, may offer improved performance over vegetation indices derived from step linear regression analysis with simple ratios or combined formulas. Limited research on this technique has been conducted for sweet corn and snap bean. The objective of this study was to test the performance of reflectance spectroscopy (λ=450-2500 nm) and PLSR analysis to evaluate their use for predicting specific leaf area and leaf N content in sweet corn and snap bean. The results indicate that PLSR is a promising method to estimate real-time N status in sweet corn and snap bean across growth stages and different N management in the field.