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In this research, a non-destructive and low-cost approach based on Vis/NIR spectroscopy was developed for rapid measurement of nitrate concentrations in cucumbers and screening of the samples based on maximum limit of nitrate accumulation. Vis/NIR spectra of intact cucumbers including both field and greenhouse samples with different concentrations of nitrate were analyzed. PLS models were developed based on the pre-processed spectra and reference measurements. Moreover, PCA-DA classification models with different methods of linear, quadratic and Mahalanobis were developed to discriminate the samples based on maximum limit of nitrate accumulation according to Iranian National Standardization Organization (INSO) and World Health Organization (WHO), as well as based on the type. The best PLS model for prediction of nitrate concentrations in the cucumbers was achieved using D 2 pre-processing method (r p =0.87, SEP=60.92 mg kg−1, RPD=2.07). It was concluded that Vis/NIR spectroscopy is adequate for screening the cucumbers based on their nitrate concentrations. The results also confirmed that this technology combined with PCA-DA is appropriate (accuracy=72.22%, sensitivity=76.74%, specificity=54.55%) and fairly suitable (accuracy=64.81%, sensitivity=59.26%, specificity=70.37%) for screening of the cucumbers based on maximum limit of nitrate accumulation according to INSO and WHO, respectively. It was excellent technology for classification of the cucumbers based on their type (accuracy=94.44%, sensitivity=93.55%, specificity=95.65%). Consequently, the proposed spectroscopic approach can be used for safety assessment of cucumbers as a rapid method with easy and out-of-laboratory usability. • Non-destructive measurement of nitrate concentrations in cucumbers is possible using Vis/NIRS. • Non-destructive and rapid screening of cucumbers based on maximum limit of nitrate is possible. • Vis/NIRS can be used for developing a portable system for safety assessment of cucumbers. [ABSTRACT FROM AUTHOR]

The present study investigated the feasibility of visible near-infrared (Vis-NIR) spectroscopy method as a low-cost, quick and reliable method for the prediction of qualitative characteristics (fruit juice percentage, soluble solids, acidity, taste index and vitamin C) of an export variety of Persian pomegranate. For this purpose, pomegranate samples were first analyzed by Vis-NIR spectroscopy, followed by destructive reference methods for quality determination. Subsequently, the data from Vis-NIR were evaluated with different pre-processing methods, among which the combination of the Savitzky–Golay (SG) smoothing model and standard normal variation (SNV) normalization model, generates the best outcomes in predicting six desired qualitative characteristics by partial least square regression (PLSR) model. Fruit juice percentage and pH presented the best prediction models with a correlation coefficient (r P) of 0.98 for both, and root mean square errors of prediction (RMSEP) equal to 0.036 and 0.041, respectively. The values of r p for all desired parameters in this study were higher than 0.95, which pointed to the excellent accuracy of the PLSR models in the prediction of pomegranate qualitative features. It can be concluded from the present study that, Vis-NIR spectroscopy using the PLSR model as a non-destructive functional approach is capable of verifying the quality of Persian export variety pomegranate as an online technique with the aim of grading products before the export phase in order to augment the product marketability. [Display omitted] • Twelve quality parameters of fruit determined through destructive tests. • The most important quality parameters were selected for non-destructive prediction. • Vis-NIR was able to predict selected quality parameters with excellent accuracy. • The fruit juice percentage was predicted for the first time as a quality parameter. • The proposed method can be utilized in the grading stage prior to the export phase. [ABSTRACT FROM AUTHOR]