4.7 Article

Investigating the effects of simulated transport vibration on tomato tissue damage based on vis/NIR spectroscopy

Journal

POSTHARVEST BIOLOGY AND TECHNOLOGY
Volume 98, Issue -, Pages 41-47

Publisher

ELSEVIER
DOI: 10.1016/j.postharvbio.2014.06.016

Keywords

Visible and infrared spectroscopy; Simulate transport vibration; Tissue damage; Partial least squares; Least squares-support vector machine

Funding

  1. National Natural Science Foundation of China [61265011]
  2. Inner Mongolia Natural Science Foundation [2012MS0915]
  3. Research Fund for the Doctoral Program of Higher Education [20111515120004]
  4. Research Fund for the Doctoral Program of Inner Mongolia Agricultural University [BJ09-18]

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Visible and near infrared (vis/NIR) spectroscopy combined with chemometrics were investigated to evaluate the effects of simulated transport vibration levels on damage of tomato fruit. A total of 280 tomato samples were randomly divided into 5 groups; each group was subjected to vibration at different acceleration levels. A total of 230 samples (46 from each group) were selected as a calibration set; whereas 50 samples (10 from each group) were selected as a prediction set. Raw spectra, differentiation (the first derivative) spectra, extended multiplicative scatter correction (EMSC) processed spectra and standard normal variant combined with detrending (SNV-DT) processed spectra were used for calibration models. SNV-DT processed spectra had the best performance using for partial least squares (PLS) analysis. The PLS analysis was implemented to calibrate models with different wavelength bands including visible, short-wave near infrared (SWNIR) and long-wave near infrared (LWNIR) regions. The best PLS model was obtained in the vis/NIR (600-1600 nm) region. Using a grid search technique and radial basis function (RBF) kernel, four least squares support vector machine (LS-SVM) models with different latent variables (7, 8, 9, and 10 LVs) were compared. The optimal model was obtained with 9 LVs and the correlation coefficient (r), root mean square error of prediction (RMSEP) and bias for the best prediction by LS-SVM were 0.984, 0.137 and 0.003, respectively. The results showed that vis/NIR spectroscopy could be applied as a reliable and rapid method for predicting the effect of vibration levels on tissue damage of tomato fruit. (C) 2014 Elsevier B.V. All rights reserved.

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