Rapid evaluation of Curcuma origin and quality based on E-eye, flash GC e-nose, and FT-NIR combined with machine learning technologies - Guo, Qiang; Li, Ming-xuan; Fu, Rao; Wan, Xin; Dong, Wen-hao; Mao, Chun-qin; Bian, Zhen-hua; Ji, De; Lu, Tu-lin; Li, Yu (Food chemistry, 2025)
Keywords: adulterated products; Chromatography, Gas - instrumentation; Chromatography, Gas - methods; Curcuma; Curcuma - chemistry; curcumin; curry; E-eye; Electronic Nose; Flash GC e-nose; flavor; food chemistry; FT-NIR; ingredients; Machine Learning; Origin division; Plant Extracts - chemistry; PLSR; prediction; Quality Control; Quality evaluation; Spectroscopy, Near-Infrared - methods; RMSET; RMSEP; RPD; E-eye; Quality evaluation; Origin division; FT-NIR; R2p; 2D; 1D; SG; R2t; Machine learning; SNV; MSC; Flash GC e-nose; PLSR