Phyllostachys violascens model optimization for bamboo shoot firmness using near-infrared spectroscopy

Key words: 
• cash forestry /
• NIR spectroscopy /
• biPLS /
• CARS /
• SPA /
• firmness /
• bamboo shoots

Abstract: To develop a calibration model for rapid, accurate and nondestructive determination of bamboo shoots firmness with Phyllostachys violascens by using near infrared spectroscopy （NIRS） technology. The diffuse reflectance spectra of bamboo shoot were obtained in the wavelength range from 800 to 2 632 nm. Different informative variable selection methods were first calculated with the full spectra being pretreated using a standard normal variate （SNV） transformation. Analyses with backward interval partial least squares （biPLS）, synergy interval partial least squares （siPLS）, genetic algorithm （GA）, successive projections algorithm （SPA）, Monte Carlo uninformative variable elimination （MCUVE）, and competitive adaptive reweighed sampling （CARS） were compared. Then CARS and SPA were used on the spectrum to select wavelengths in proper order. The performance of the models were tested using a correlation coefficient for cross-validation of calibration （rcv）, root mean square error for cross-validation of calibration （RMSECV）, the correlation coefficient of prediction （rp）, and the root mean square error of prediction （RMSEP）. Results showed that BiPLS combined with CARS and SPA obtained a total of 25 wavelengths or only 1.6% of the full wavelengths. The rcv, RMSECV, rp, RMSEP by biPLS-CARS-SPA were 0.984, 0.300 Ncm-2, 0.926, 0.625 Ncm-2, respectively. The good performance demonstrated that NIR spectroscopy coupled with the biPLS-CARS-SPA algorithm could be used successfully to analyze bamboo shoot firmness and revealed that the biPLS-CARS-SPA algorithm was superior to other wavelength selection methods. ［Ch, 6 fig. 3 tab. 20 ref.］