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Table 5 Results of calibration and prediction models for classifying mature bamboo fractions

From: Rapid determination of chemical composition and classification of bamboo fractions using visible–near infrared spectroscopy coupled with multivariate data analysis

Wavelength (nm) Sample sets Parameters B I K M O
400–780 (n = 100) Calibration R 2 0.96 0.88 0.81 0.93 0.93
SEC 0.08 0.14 0.17 0.11 0.11
Validation R 2 0.90 0.77 0.69 0.71 0.83
SEV 0.13 0.19 0.23 0.21 0.17
Factors 13 13 13 13 13
780–2500 (n = 100) Calibration R 2 0.98 0.94 0.93 0.97 0.97
SEC 0.05 0.10 0.10 0.08 0.07
Validation R 2 0.93 0.76 0.76 0.85 0.90
SEV 0.11 0.20 0.20 0.16 0.13
Factors 16 16 16 16 16
400–2500 (n = 100) Calibration R 2 0.98 0.98 0.96 0.97 0.96
SEC 0.06 0.06 0.08 0.07 0.08
Validation R 2 0.94 0.95 0.87 0.90 0.91
SEV 0.10 0.09 0.14 0.13 0.12
Factors 15 15 15 15 15
  1. Three regions of wavelength were selected to establish models, and these spectra came from original data. The number of sample sets was 100. (B bamboo branch, I bamboo yellow, K bamboo node, M bamboo timber, O bamboo green)