Measurement of SSC in processing tomatoes (Lycopersicon esculentum Mill.) by applying Vis-NIR hyperspectral transmittance imaging and multi-parameter compensation models

Processing tomato (Lycopersicon esculentum Mill.) is a very important horticultural product all over the world. Soluble solid content (SSC) as a key quality assessment parameter of processing tomato directly affects quality and cost of processing tomato products such as tomato paste. This study proposes an analytical method for quantitatively assessment of SSC in processing tomatoes by using the visible and near-infrared (Vis-NIR) hyperspectral transmittance imaging technique and multi-parameter compensation models. Monte-Carlo outlier detection method was applied to optimize sample set. The competitive adaptive reweighted sampling (CARS) algorithm was used to identify the optimal wavelengths from transmittance spectra. Two characteristic parameters including area (size) and weight of samples were measured and different models including conventional PLS/LS-SVM models and multi-parameter compensation PLS/LS-SVM models were established, respectively. The results obtained by comparing all the established models showed that the multi-parameter (spectrum, area, and weight) compensation CARS-LS-SVM model with 47 important wavelengths had the best assessment ability of SSC in processing tomatoes. The prediction accuracies of the optimal model are r(cal) = 0.95 and RMSEC = 0.16 for calibration set, and r(pre) = 0.94, RMSEP = 0.17 and RPD = 2.94 for prediction set, respectively. Research results indicated that the newly proposed Vis-NIR hyperspectral transmittance imaging combining with multi-parameter compensation LS-SVM model would be potential as a noninvasive technique to quantitatively evaluate the SSC in processing tomatoes. Practical applications Fast assessment of soluble solid content (SSC) in processing tomatoes has significant value for tomato processing in practical application. High quality processing tomatoes can reduce the processing cost and raise product prices. The newly proposed SSC measurement technique integrated both Vis-NIR hyperspectral transmittance imaging and multi-parameter compensation models. This technique can effectively overcome some disadvantageous influences from size and weight of processing tomatoes in the assessment process of SSC. Use of transmittance technology further improved the acquisition capability of effective spectral information from the tested object. This work was valuable for setting up the fast multispectral inspection system that can be used for SSC measurement of processing tomatoes in practical on-line grading applications.