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Spectroscopy in the visible near-infrared spectral (Vis-NIRS) range combined with imaging techniques (hyperspectral imaging, HSI) allows assessment of chemical composition, texture, and meat structure. The use of HSI in the meat and food industry has observed a significant growth in the last decade, yet its use for assessment of meat it is not optimal yet. The application of HSI for assessment of meat is reviewed with focus on its ability to capture meat unique chemical and structural characteristics. While HSI is widely used for assessment of chemical composition, a limited number of evidences on its ability to handle the effect of different sources of variation on the assessment is found. The use of spatially resolved spectroscopy has been able to detect structural information related to animal background, muscle type, rigor process and ageing. Similarly the use of texture features seem to capture unique characteristics of meat., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The bulk optical properties (BOP) of two bovine muscles were studied in the 500nm to 1850nm wavelength range. Over a two-week period of wet aging, the BOP of the biceps femoris (BF) and longissimus lumborum (LL) were determined and related to moisture content, tenderness and cooking loss. The absorption by myoglobin and reduced scattering coefficient were higher in the BF compared to the LL. The scattering anisotropy factor was relatively high (>0.95 for LL), representing dominant forward scattering. Two-toning effects in the BF could be attributed to significant scattering differences, as no differences in absorption properties were observed. During wet aging, the anisotropy factor decreased, while tenderness increased. It was hypothesized that this might be related to proteolysis of cytoskeletal proteins. The results show the potential use of BOP to monitor tenderization and the cause of color differences in beef muscles. Moreover, this information could be used to develop and optimize optical sensors for non-destructive meat quality monitoring., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

A global optimizer has been developed, capable of computing the optimal configuration in a probe for spatially resolved reflectance spectroscopy (SRS). The main objective is to minimize the number of detection fibers, while maintaining an accurate estimation of both absorption and scattering profiles. Multiple fibers are necessary to robustify the estimation of optical properties against noise, which is typically present in the measured signals and influences the accuracy of the inverse estimation. The optimizer is based on a robust metamodel-based inverse estimation of the absorption coefficient and a reduced scattering coefficient from the acquired SRS signals. A genetic algorithm is used to evaluate the effect of the fiber placement on the performance of the inverse estimator to find the bulk optical properties of raw milk. The algorithm to find the optimal fiber placement was repeatedly executed for cases with a different number of detection fibers, ranging from 3 to 30. Afterwards, the optimal designs for each considered number of fibers were compared based on their performance in separating the absorption and scattering properties, and the significance of the differences was tested. A sensor configuration with 13 detection fibers was found to be the combination with the lowest number of fibers which provided an estimation performance which was not significantly worse than the one obtained with the best design (30 detection fibers). This design resulted in the root mean squared error of prediction (RMSEP) of 1.411 cm(-1) (R(2) = 0.965) for the estimation of the bulk absorption coefficient values, and 0.382 cm(-1) (R(2) = 0.996) for the reduced scattering coefficient values., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The size of colloidal particles in food products has a considerable impact on the product's physicochemical, functional and sensory characteristics. Measurement techniques to monitor the size of suspended particles could, therefore, help to further reduce the variability in production processes and promote the development of new food products with improved properties. Visible and near-infrared (Vis/NIR) spectroscopy is already widely used to measure the composition of agricultural and food products. However, this technology can also be consulted to acquire microstructure-related scattering properties of food products. In this study, the effect of the fat globule size on the Vis/NIR bulk scattering properties of milk was investigated. Variability in fat globule size distribution was created using ultrasonic homogenization of raw milk. Reduction of the fat globule size resulted in a higher wavelength-dependency of both the Vis/NIR bulk scattering coefficient and the scattering anisotropy factor. Moreover, the anisotropy factor and the bulk scattering coefficients for wavelengths above 600 nm were reduced and were dominated by Rayleigh scattering. Additionally, the bulk scattering properties could be well (R(2) ≥ 0.990) estimated from measured particle size distributions by consulting an algorithm based on the Mie solution. Future research could aim at the inversion of this model to estimate the particle size distributions from Vis/NIR spectroscopic measurements., (Copyright © 2015 Elsevier B.V. All rights reserved.)