Quantification of Total Phenolic and Carotenoid Content in Blackberries (Rubus Fructicosus L.) Using Near Infrared Spectroscopy (NIRS) and Multivariate Analysis.

A rapid method to quantify the total phenolic content (TPC) and total carotenoid content (TCC) in blackberries using near infrared spectroscopy (NIRS) was carried out aiming to provide reductions in analysis time and cost for the food industry. A total of 106 samples were analysed using the Folin-Ciocalteu method for TPC and a method based on Ultraviolet-Visible Spectrometer for TCC. The average contents found for TPC and TCC were 24.27 mg·g-1 dw and 8.30 µg·g-1 dw, respectively. Modified partial least squares (MPLS) regression was used for obtaining the calibration models of these compounds. The RPD (ratio of the standard deviation of the reference data to the standard error of prediction (SEP)) values from external validation for both TPC and TCC were between 1.5 < RPDp < 2.5 and RER values (ratio of the range in the reference data to SEP) were 5.92 for TPC and 8.63 for TCC. These values showed that both equations were suitable for screening purposes. MPLS loading plots showed a high contribution of sugars, chlorophyll, lipids and cellulose in the modelling of prediction equations.

Rapid and Cost-Effective Quantification of Glucosinolates and Total Phenolic Content in Rocket Leaves by Visible/Near-Infrared Spectroscopy.

The potential of visible-near infrared spectroscopy to predict glucosinolates and total phenolic content in rocket (Eruca vesicaria) leaves has been evaluated. Accessions of the E. vesicaria species were scanned by NIRS as ground leaf, and their reference values regressed against different spectral transformations by modified partial least squares (MPLS) regression. The coefficients of determination in the external validation (R²VAL) for the different quality components analyzed in rocket ranged from 0.59 to 0.84, which characterize those equations as having from good to excellent quantitative information. These results show that the total glucosinolates, glucosativin and glucoerucin equations obtained, can be used to identify those samples with low and high contents. The glucoraphanin equation obtained can be used for rough predictions of samples and in case of total phenolic content, the equation showed good correlation. The standard deviation (SD) to standard error of prediction ratio (RPD) and SD to range (RER) were variable for the different quality compounds and showed values that were characteristic of equations suitable for screening purposes or to perform accurate analyses. From the study of the MPLS loadings of the first three terms of the different equations, it can be concluded that some major cell components such as protein and cellulose, highly participated in modelling the equations for glucosinolates.

Application of visible/near-infrared reflectance spectroscopy for predicting internal and external quality in pepper.

BACKGROUND: The characterization of internal (°Brix, pH, malic acid, total phenolic compounds, ascorbic acid and total carotenoid content) and external (color, firmness and pericarp wall thickness) pepper quality is necessary to better understand its possible applications and increase consumer awareness of its benefits. The main aim of this work was to examine the feasibility of using visible/near-infrared reflectance spectroscopy (VIS-NIRS) to predict quality parameters in different pepper types. Commercially available spectrophotometers were evaluated for this purpose: a Polychromix Phazir spectrometer for intact raw pepper, and a scanning monochromator for freeze-dried pepper. RESULTS: The RPD values (ratio of the standard deviation of the reference data to the standard error of prediction) obtained from the external validation exceeded a value of 3 for chlorophyll a and total carotenoid content; values ranging between 2.5 < RPD < 3 for total phenolic compounds; between 1.5 < RPD <2.5 for °Brix, pH, color parameters a* and h* and chlorophyll b; and RPD values below 1.5 for fruit firmness, pericarp wall thickness, color parameters C*, b* and L*, vitamin C and malic acid content. CONCLUSION: The present work has led to the development of multi-type calibrations for pepper quality parameters in intact and freeze-dried peppers. The majority of NIRS equations obtained were suitable for screening purposes in pepper breeding programs. Components such as pigments (xanthophyll, carotenes and chlorophyll), glucides, lipids, cellulose and water were used by modified partial least-squares regression for modeling the predicting equations. © 2015 Society of Chemical Industry.