Rapid Determination of Vitamin C by NIR Spectroscopy Coupled With CARS ‐ PLS

ABSTRACT

Vitamin C (VC) is a crucial nutritional indicator in fruits, yet its rapid and non‐destructive determination remains challenging. This study proposed a competitive adaptive reweighted sampling coupled with partial least squares (CARS‐PLS) approach for quantifying VC content in “Jinhuang” mango using near‐infrared (NIR) spectroscopy. NIR spectra (1000–2500 nm) of 154 mango samples were acquired, and VC contents were determined by titration. The CARS algorithm selected informative wavelengths, and the CARS‐PLS model was compared with full‐spectrum PLS and three other wavelength selection methods. Results showed that CARS retained 1078 wavelengths from 1557 variables with a 30.8% reduction while substantially improving predictive accuracy. The CARS‐PLS model achieved excellent performance with R ² _P of 0.954 and RMSE _P of 0.282 mg/100 g, significantly outperforming full‐spectrum PLS with R ² _P of 0.884 and RMSE _P of 0.442 mg/100 g. The selected wavelengths were predominantly located in spectral regions associated with carbon‐hydrogen (CH) and oxygen‐hydrogen (OH) stretching overtones, specifically between 1100 and 1300 nm, 1600 and 1800 nm, and 2200 and 2400 nm. These findings demonstrate that CARS‐PLS provides a robust, parsimonious tool for rapid, non‐destructive mango VC assessment, with potential applications in quality control and postharvest management.