Direct NIR spectral determination of genetic improvement, light availability, and their interaction effects on chemically selected yerba-mate leaves

Abstract

Monitoring plant chemical modifications provides useful information about plant genetic variability owing to environmental stresses. This allows determining if the pattern of chemical compounds of interest remains constant. Classically, chemical compounds are monitored through classical analytical procedures that are costly and environmentally harmful. Decaffeinated and high caffeine yerba-mate trees were selected based on their chemical profiles. Their behavior was evaluated at five different shading levels (0%, 40%, 51%, 76%, and 82%), imitating the environmental characteristics of yerba-mate in agroforestry systems. Near-infrared spectroscopy (NIR) fingerprints were obtained for yerba-mate leaves, and ANOVA-simultaneous component analysis (ASCA) models were developed for chemical monitoring. The preprocessing of NIR spectra was assessed with a three-level full factorial design. The best preprocessing set of conditions found was standard normal variate followed by second derivatives, computed according to the Savitzky–Golay method (11-points window and second-degree interpolating polynomial). The ASCA models satisfactorily showed significant differences in chemical behavior for genetic improvement and its interaction with light availibility effects. The genetic improvement effect had a variance of 44.30% over NIR fingerprints, indicating that the chemical differences are maintained at any light level. The interaction effect with 1.84% of the total variance illustrated that the behaviors of decaffeinated and high-caffeinated yerba mate were different when subjected to the same light level. The main absorptions indicated by the ASCA model were the O-H stretching and bending combination band at 1654 nm, and the –CH stretching aromatic 1st overtone at 1675 nm. The ASCA method offered a powerful tool for monitoring chemically selected plants combined with NIR spectroscopy. The method is cheap, fast, environmentally friendly, and can be used for field research.