Evaluating Wheat Nitrogen Status with Canopy Reflectance Indices and Discriminant Analysis

TLDR

Nitrogen deficiency reduces wheat yield, and remote sensing of leaf chlorophyll a offers a cost‑effective way to estimate crop nitrogen status. The study aimed to evaluate whether remote sensing of wheat chlorophyll a could rapidly estimate nitrogen status. Researchers measured canopy reflectance under five fertilization levels throughout the growth cycle, tested indices such as R550, R680, red‑edge parameters, PSR, NPCI, and performed discriminant analysis on selected indices to classify nitrogen status. Significant correlations were found between chlorophyll a and R550, R680, and red‑edge indices; NPCI and PSR distinguished treatments over time, and discriminant analysis successfully assigned spectra to distinct nitrogen status classes, demonstrating the potential of optical methods for wheat nitrogen assessment.

Abstract

Nitrogen deficiencies can seriously reduce yield and economic returns for farmers. Remote sensing could provide inexpensive, largearea estimates of N status and be used to monitor N status since leaf chlorophyll (Chi) A content is mainly determined by N availability. The objective was to determine if remote sensing of wheat ( Triticum aestivum L.) Chi A content would provide a rapid estimation of wheat N status. We measured the reflectance of a wheat crop submitted to five different fertilization treatments throughout the growth cycle. We tested several empirical reflectance indices of pigment content: reflectance at 550 nm (R550), reflectance at 680 nm (R680), three parameters of the red edge [wavelength (λ re ), amplitude in the first derivative of the reflectance spectra (dR re ), and sum of amplitudes between 680 and 780 nm in the first derivative of the reflectance spectra (ΣdR 680–780nm )], and pigment simple ratio (PSR) and normalized pigment chlorophyll index (NPCI) (indices of carotenoid/Chl ratio). We also measured leaf Chi A and N content, and leaf area index. There were significant correlations between canopy Chi A content and R550, R680, and all the red edge parameters. The NPCI and PSR followed phenological evolution of the carotenoids/Chl A ratio and separated the different treatments. By discriminant analysis based on the pigment indices reflectance at 430 nm (R430), R550, R680, λ re , dR re , and NPCI, each reflectance spectrum can be assigned to a different N status class. Thus, the use of these optical techniques offers a potential for assessing N status of wheat.