A novel and enhanced approach for the assessment of the total carotenoid content of foods based on multipoint spectroscopic measurements

Applications of Visible Spectroscopy and Color Measurements in the Assessments of Carotenoid Levels in Foods

The color of the food can be evaluated visually or instrumentally. The instrumental measurement allows to measure the color objectively and can be carried out by different techniques, most of them fast, cheap, and simple. Carotenoids are responsible for the color of many plants and foods. The measurement of color can be an effective tool to determine indirectly the concentration of carotenoids in plants and foods. In this chapter, we describe both traditional and recent methodologies for color measurement.

Quality, stability, carotenoids and chromatic parameters of commercial Sacha inchi oil originating from Peruvian cultivars

Sacha inchi oil is a high-quality product with market potential and a wealth of bioactive compounds beneficial for food and health. The main objective of this work was to evaluate three quality parameters, stability, chromatic parameters and total carotenoids of commercial oils obtained from Sacha inchi seeds. The free acidity and peroxide value of all samples studied were in ranges of 0.16-1.86 (% α-linolenic acid) and 1.87-17.47 (meq O₂/kg), respectively. While K₂₃₂ value for the samples ranged from 1.96 to 2.29, the K₂₇₀ value was between 0.08 to 0.20 and ∆K in the range of - 0.005 to 0.005. Regarding color, Sacha inchi oils showed high h _ab and low C ab ∗ values, and the L ^* values were from 91 to near 100 units. Samples were located in the second quadrant of the CIELAB a ^* b ^*-color diagram. These characteristics corresponds to low-vivid light-yellow colors. Carotenoid content of Sacha inchi oils was 0.31-9.10 mg/kg. The oxidative stability using Rancimat (100 °C, 20 L/h air flow rate) of these oils presented an average value of 5.6 h. Pearson's coefficients indicate a very high correlation coefficient between the values of Car (carotenoid) versus b ^* (yellow area) (r = 0.991). The results of this study provide better understanding of the quality, stability, chromatic intensities and carotenoid contents of Sacha inchi oil that is marketed in Peru.

A rapid and effective approach for on-site assessment of total carotenoid content in wolfberry juice during processing

BACKGROUND

Carotenoid content analysis in wolfberry processed products has mainly focused on the determination of zeaxanthin or zeaxanthin dipalmitate, which cannot indicate the total carotenoid content (TCC) in wolfberries.

RESULTS

We have exploited an effective approach for rapid extraction of carotenoid from wolfberry juice and determined TCC using UV-visible spectrophotometry. Several solvent mixtures, adsorption wavelengths of carotenoid extracts and extraction procedures were investigated. The optimal solvent mixture with broad spectrum polarity was hexane-ethanol-acetone (2:1:1) and optimal wavelength was 456 nm. There was no significant difference of TCC in wolfberry juice between direct extraction and saponification extraction.

CONCLUSION

The developed method for assessment of TCC has been successfully employed in quality evaluation of wolfberry juice under different processing conditions. This measurement approach has inherent advantages (simplicity, rapidity, effectiveness) that make it appropriate for obtaining on-site information of TCC in wolfberry juice during processing.

Simplified method for the screening of technological maturity of red grape and total phenolic compounds of red grape skin: application of the characteristic vector method to near-infrared spectra

Characteristic vector analysis has been applied to near-infrared spectra to extract the main spectral information from hyperspectral images. For this purpose, 3, 6, 9, and 12 characteristic vectors have been used to reconstruct the spectra, and root-mean-square errors (RMSEs) have been calculated to measure the differences between characteristic vector reconstructed spectra (CVRS) and hyperspectral imaging spectra (HIS). RMSE values obtained were 0.0049, 0.0018, 0.0012, and 0.0012 [log(1/R) units] for spectra allocated into the validation set, for 3, 6, 9, and 12 characteristic vectors, respectively. After that, calibration models have been developed and validated using the different groups of CVRS to predict skin total phenolic concentration, sugar concentration, titratable acidity, and pH by modified partial least-squares (MPLS) regression. The obtained results have been compared to those previously obtained from HIS. The models developed from the CVRS reconstructed from 12 characteristic vectors present similar values of coefficients of determination (RSQ) and standard errors of prediction (SEP) than the models developed from HIS. RSQ and SEP were 0.84 and 1.13 mg g(-1) of skin grape (expressed as gallic acid equivalents), 0.93 and 2.26 °Brix, 0.97 and 3.87 g L(-1) (expressed as tartaric acid equivalents), and 0.91 and 0.14 for skin total phenolic concentration, sugar concentration, titratable acidity, and pH, respectively, for the models developed from the CVRS reconstructed from 12 characteristic vectors.