Investigating the effects of simulated transport vibration on tomato tissue damage based on vis/NIR spectroscopy |
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| Institution: | 1. College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, 306 Zhaowuda Road, Hohhot 010018, China;2. Department of Agricultural & Biological Engineering, Purdue University, 225 S. University St., West Lafayette, IN 47907-2093, USA;1. College of Engineering, The University of Georgia, 200 D.W. Brooks Drive, Athens, GA 30602, USA;2. Appalachian Fruit Research Station, USDA-ARS, 2217 Wiltshire Road, Kearneysville, WV 25430, USA;3. Professor Emeritus, University of Georgia, Woodbine, GA 31569, USA;1. Center for Precision and Automated Agricultural Systems, Washington State University, Prosser, WA 99350, USA;2. Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164, USA;1. Department of Plant, Soil and Agricultural Systems, Southern Illinois University, Carbondale, USA;2. Department of Chemistry and Biochemistry, Southern Illinois University, Carbondale, USA;3. Department of Mechanical Engineering, Southern Illinois University, Carbondale, USA;1. College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning, 110034, People’s Republic of China;2. Experimental Teaching Center, Shenyang Normal University, Shenyang, Liaoning, 110034, People’s Republic of China |
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| Abstract: | 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. |
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| Keywords: | Visible and infrared spectroscopy Simulate transport vibration Tissue damage Partial least squares Least squares-support vector machine |
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