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Banana and its dried products are one of the most common foods consumed all over the world. Quality attributes of dried banana slices are typically evaluated using time-consuming and labor intensive methods which do not allow to evaluate each individual slice. Replacement of the current destructive methods for quality evaluation of dried banana slices by fast, non-destructive methods would provide large added value to the food industry. Therefore, the aim of this study was to monitor the moisture content, texture and color of banana slices during the drying process in a fast and non-destructive way. VNIR hyperspectral reflectance imaging in the 400–1000 nm range was selected for this purpose. Thanks to a cross-polarized configuration the effects of glare or specular reflection on the banana slice surfaces in the hyperspectral diffuse reflectance images was largely reduced. Reference quality attributes for all the slices (moisture content, texture and color ( L*, a*, b* values) obtained using conventional destructive methods and colorimeter were predicted from their corresponding average reflectance spectra extracted from the hyperspectral images by means of partial least squares regression (PLSR). The PLSR calibration models were validated on samples which had not been used for model calibration. The results were very good for water content ( R 2 P  = 0.97, RMSEP  = 0.05 kg water/kg DM), quite good for and b* value ( R 2 P  = 0.83, RMSEP  = 1.95), and reasonable for texture ( R 2 P  = 0.66, RMSEP  = 11.8 N), a* value ( R 2 P  = 0.53, RMSEP  = 1.32) and L* value ( R 2 P  = 0.61, RMSEP  = 5.92). Subsequently, these calibration models were used to predict those quality attributes at pixel level for the validation slices to visualize the spatial distribution of these quality parameters at different stages during the drying process. The obtained results clearly indicate the potential of cross-polarized hyperspectral reflectance imaging for non-destructive monitoring of the quality attributes of banana slices during drying. [ABSTRACT FROM AUTHOR]

Insight in the transmission of light through intact fruit is important to optimize and interpret the signals acquired with spectroscopy methods such as tunable diode laser absorption spectroscopy (TDLAS). To this end, we quantified the bulk optical properties (BOP) of skin, outer cortex, inner cortex, and core tissue of three pear (Pyrus communis) cultivars (Thimo , Cepuna , and Conference) using double integrating spheres measurements in combination with the inverse adding doubling method. Similar trends and values were observed for the bulk optical properties of the three cultivars. A clear chlorophyll-a absorption feature was present in the bulk absorption coefficient (μ a) at 690 nm for the skin samples. At 761 nm, the bulk scattering coefficient (μ s) decreased from the skin towards the core region, for example from 256 ± 34 cm−1 to 146 ± 22 cm−1 for Conference pears. The observed anisotropy factor (g) of the skin was lower than these of the other tissue layers (0.87 ± 0.026 vs. 0.94 ± 0.08 for Conference). Next, Monte Carlo voxelized media (MCVM) simulations were performed based on these BOP values and validated against measurements with a TDLAS setup for gas in scattering media absorption spectroscopy (GASMAS) at 761 nm. In these experiments, the sample thickness was reduced by sequentially slicing the pear from the skin towards the center. Light transmittance through an intact pear at the height of the core region was found to be very low (1.9 × 10−4 ± 8.5 × 10−5%) and exponentially increased around 100-fold when the sample thickness decreased from 64 mm to 24 mm. The simulated transmittance profiles based on the measured BOP values at 761 nm followed the same trend as the measured GASMAS transmittance as a function of the fruit thickness. This shows that simulations based on these measured BOP values can be used to optimize the measurement configuration for O 2 monitoring in intact pear fruit with GASMAS. • The bulk optical properties of pear tissue layers: skin, outer cortex, inner cortex, and core. • 3D Monte Carlo simulation of diffuse transmittance through an intact pear. • Comparison of simulated and measured diffuse transmittance vs pear sample thicknesses. • Simulations provided a valuable tool for optimizing the amplification of GASMAS detectors in diffuse transmittance mode. [ABSTRACT FROM AUTHOR]

Abstract: In the presented research three measurement strategies of Fourier transform infrared (FT-IR) spectrometry (horizontal- and micro-attenuated total reflection (HATR and μATR, respectively) and a novel high throughput transmission (HTT)) in combination with extensive chemometric approach have been applied for analysis of beer. Fifty Belgian beer samples were analyzed: lager and white beers, dark and blonde ales, lambic and Trappist beers. Partial least square (PLS) regression was used for prediction of different physicochemical parameters of beer based on mid-IR data, modified with different spectral preprocessing and variable selection algorithms for higher prediction performance. It was found that HATR and μATR have the same prediction capability with a slight advantage of μATR and excellent correlations between spectra and reference values were demonstrated for original (R 2 0.95), apparent (R 2 0.89) and real (R 2 0.95) extracts, real and apparent degrees of fermentation (R 2 0.91 and 0.89), alcohol content (R 2 0.94) and energetic value (R 2 0.95). Good results (R 2 0.83) were obtained from the HTT experiments for prediction of real extract and allow measurement of large sample numbers in short time (1 sample/minute) with further potential increase in a sample throughput and has the possibility for automation. The obtained results indicate that mid-IR spectrometry in combination with advanced pre-processing and variable selection methods is a valuable analytical tool for high throughput measurement of beer quality attributes and thus has potential for use in product development and quality control. [Copyright &y& Elsevier]

To facilitate the design of new optical measurement systems for biological systems, the knowledge of light propagation properties is essential. Therefore, the bulk optical properties of skin and cortex of three apple cultivars were studied during maturation, in the 500 nm–1850 nm range. A clear absorption signature was observed with absorption peaks which can be related to present anthocyanins, chlorophyll, carotenoids and water. During maturation, the skin absorption at 550 nm increased in the bicolored cultivars ‘ Braeburn ’ and ‘ Kanzi ’, while the absorption at 680 nm decreased in the cortex. Both the bulk scattering coefficient and the anisotropy factor were larger for the skin compared to the cortex tissue. Also during maturation, the skin scattering increased in the two bicolored cultivars, while a general decrease was seen in the apple cortex. Physiological changes during maturation, like cell growth, the formation/degradation of pigments and the formation of a cuticle layer on the skin, may explain the observed evolutions. As a result, using the bulk optical properties, these physiological changes can be monitored and linked to the maturity stage in the orchard, supporting the selective harvest of apples. [ABSTRACT FROM AUTHOR]

Highlights: [•] Vis/NIR spectroscopy can be successfully used to detect flaws in hazelnut. [•] Features were selected within the 550–600nm and 1150–1650nm spectral bands. [•] Features correspond to overtones of O H and C H stretches and deformations. [Copyright &y& Elsevier]

Abstract: The potential of near infrared (NIR) reflectance spectroscopy over the range 780–1690nm was investigated to measure the soluble solids content (SSC) and firmness of bell pepper fruit. Partial least squares (PLS) calibration models were constructed based on a calibration dataset which included data from two cultivars (Solution and Ferrari) and two harvest times (2005 and 2006). The effect of Savitzky–Golay second derivative preprocessing and extended multiplicative signal correction (EMSC) on the accuracy of the calibration models was investigated and the best results were obtained with the former. The SECV were equal to 5.9N and 0.59°Brix for firmness and SSC, respectively. When the model was applied to an external data set including data from cv. Solution and a different harvest season, the satisfactory SEP values of 4.49N and 0.7°Brix were obtained, but for firmness a bias of 5.6N was observed. From these results it can be concluded that NIR spectroscopy can be used as a non-destructive technique for measuring the SSC in bell pepper, but that further research is needed to make it robust for firmness prediction. [Copyright &y& Elsevier]

The cooking time of common beans is influenced by genotype and storage conditions. This study aimed to use near-infrared (NIR) spectra of milled, freshly harvested (fresh) beans to predict their cooking times and their susceptibility to develop the storage-induced, hard-to-cook (HTC) defect. The physical characteristics of bean accessions, from two different seasons, were evaluated. The cooking times and susceptibility to HTC (determined by aging under standard adverse conditions) of the aforesaid beans were correlated to NIR spectra to develop calibrations using variable selection and partial least squares regression. The beans exhibited diverse physical characteristics, cooking times and susceptibility to HTC. The models predicting cooking times of fresh beans sufficiently overcame genotype and seasonal differences (R2 P = 0.73, RMSEP = 4 min). The susceptibility of fresh beans to HTC was also successfully predicted (R2 CV = 0.8, RSECV = 64%). NIR spectroscopy has high potential to rapidly identify beans with short cooking times and low susceptibility to HTC at harvest. • Bean type had a significant effect on the physical characteristics of the accessions. • Cooking times of fresh beans were predicted from NIR spectra of their flours. • PLS-R models were robust against phenotypic and seasonal variations of the beans. • Susceptibility to develop HTC was predicted from NIR spectra of milled, fresh beans. [ABSTRACT FROM AUTHOR]

The interaction of visible and near-infrared light with citrus tissues is of great importance for the design of new optical sensors for fruit quality inspection. In this study, the light propagation through citrus fruit was simulated using the Monte Carlo multi-layered (MCML) technique based on the bulk optical properties (BOP) of citrus tissues. Comparison of the diffuse reflectance profiles from MCML and from the laser scatter images confirmed the accuracy of the simulations. Simulation results indicated that most of the light was diffusely reflected or absorbed in the flavedo. Only a small fraction around 800 nm was transmitted through the three layers. Flavedo and albedo were found to contribute mostly to the diffuse reflectance spectra at 800 nm and their contributions respectively decreased and increased with source-detector distance. Although the contribution of juice vesicles increased with distance, the maximal diffuse reflectance intensity contributed by juice vesicles was located within 0.56 cm. Based on these results, the combination of the power intensity and the source-detector distance can be optimized to obtain more information about the layer of interest, which lays the foundations for designing new quality detection sensors for citrus fruit. • Light propagation in citrus fruit was simulated by Monte Carlo multi-layered model. • Good agreement of simulated and measured diffuse reflectance profiles. • Light was mainly absorbed by flavedo and diffusely reflected. • Flavedo and albedo contributed mostly to the diffuse reflectance spectra. [ABSTRACT FROM AUTHOR]

The cooking time of beans is an important quality indicator which can change considerably during ageing. Therefore, this study investigated the potential of near-infrared spectroscopy to rapidly predict cooking times of aged common beans. Four bean varieties were aged under different storage conditions, resulting in a range of samples for each of these varieties. The cooking kinetics of the aged beans were determined by finger pressing and modelled using logistic regression to obtain the times it took to cook 95% of the beans. The cooking times obtained were predicted from the NIR spectra of milled raw bean samples. This was done using partial least squares regression, after carrying out wavelength selection. Model performance was improved up to an average prediction error of 8 min by de-hulling the beans and reducing the number of varieties included. In conclusion, NIR spectroscopy has high potential to predict the cooking times of aged beans. • Cooking times of beans were predicted from NIR spectra of milled raw beans. • De-hulling beans prior to NIR measurements improved prediction accuracy. • NIR spectra of aged beans clustered into groups according to variety. • Variety-specific calibrations more accurately predict cooking times of aged beans. [ABSTRACT FROM AUTHOR]