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• Reflectance, Transmittance, Fluorescence, Raman and integrated imaging is covered. • Instrumentation is discussed with special attention for real-time imaging. • The major steps in hyperspectral data analysis are discussed. • Overview of applications in external and internal quality evaluation. • Review of applications in food safety detection. In the past 20 years, hyperspectral imaging has been widely investigated as an emerging, promising technology for evaluating quality and safety of horticultural products. This technology has originated from remote sensing and joins the domains of machine vision and point spectroscopy to provide superior image segmentation for the detection of defects and contaminations, and to map the chemical composition. Thanks to the advancements in instrumentation and data analysis in the past two decades, hyperspectral imaging technology has evolved into a powerful nondestructive inspection tool and the scope of applications in postharvest quality and safety evaluation has expanded tremendously. In this article, different imaging modes (reflectance, transmittance, fluorescence and Raman) and their combinations, and the potential for real-time acquisition of hyperspectral images at industry relevant speeds are first discussed in terms of their advantages and disadvantages. Next reviewed are different data processing/analysis methods and associated steps from data pre-processing over the spectral and spatial domains to the actual model building and performance evaluation. An overview is then given of hyperspectral imaging applications for external quality and defect evaluation, internal quality and maturity assessment, and food safety detection of horticultural products. Finally, a brief discussion is presented on the challenges and opportunities in future development and application of hyperspectral imaging technology in food quality and safety evaluation of horticultural products. [ABSTRACT FROM AUTHOR]

• Challenges in multivariate calibration of spectroscopic sensors are discussed. • Discussion of methods for quantitative and qualitative calibration. • All methods are illustrated on an example case from the postharvest domain. • Discussion of applications for postharvest quality evaluation. • Special attention is given to spectral preprocessing, careful validation and calibration transfer. Vibrational spectroscopy methods are widely investigated as fast and non-destructive alternatives for postharvest quality evaluation. As these methods measure spectral responses at a large number of wavebands correlated to the quality traits of interest, multivariate calibration equations have to be built to estimate the quality traits from the acquired spectra. This paper provides an overview of the most important multivariate data analysis techniques for exploring spectral data, detecting outliers and building calibration models for predicting the quality traits of interest. Both linear and non-linear calibration methods are discussed for quantitative (continuous) and qualitative (discrete) quality traits. For each of the presented methods the theory is explained, followed by illustration of an example case from the postharvest domain and a discussion of applications of this technique for postharvest quality evaluation based on spectral sensors. As spectral preprocessing, careful validation and calibration transfer are crucial aspects for successful implementation of spectral sensors for postharvest quality evaluation, special attention is given to these aspects. Finally, conclusions are drawn and recommendations are made with respect to the steps to take and points of attention for successful calibration. [ABSTRACT FROM AUTHOR]

'Braeburn' apples are susceptible to internal browning disorders when stored under controlled atmosphere (CA) conditions with unfavorable gas compositions. The progression of CA-related disorders in apple tissues is dynamic, noting a decrease in porosity during early storage due to cellular breakdown and pore flooding, and an increase in porosity in later stages due to structural collapse and cavity formation. Utilizing grating-based X-ray dark-field radiography, which leverages X-ray small-angle scattering to detect microstructural changes below the pixel scale, this study assesses the technique's efficacy in identifying internal disorders in 'Braeburn' apples at both early and later stages. A machine learning approach was applied to compare the diagnostic capabilities of dark-field imaging with those of X-ray absorption radiography at identical image resolutions. Results indicate that for early-stage disordered fruit detection, X-ray dark field radiography is 10 % more accurate than absorption radiography, regardless of the machine learning classifiers that were applied. In the later stage of browning, dark-field imaging performs similarly to absorption imaging. High-resolution micro-computed tomography scans suggested that the distinct detection performance of dark-field imaging may be attributed to the more pronounced microstructural differences between healthy and early-stage defective tissues than those between healthy and later-stage defective tissues. The insights from this work will guide the application of X-ray dark-field systems in fruit quality assurance, particularly in detecting internal disorders. • X-ray dark-field radiography is more suited for detecting low-porosity defects. • X-ray absorption radiography is more effective for identifying high-porosity defects. • Changes in X-ray dark-field image are closely linked with microstructural changes. [ABSTRACT FROM AUTHOR]

Optimization of controlled atmosphere (CA) storage of pome fruit crucially depends on understanding of respiratory gas exchange. Different fruit properties are involved in describing gas transfer and respiration kinetics, which can vary between cultivars, fruit batches and individual fruit. Determination of these properties currently requires a combination of different time-consuming techniques and data analysis procedures. This study introduces a more efficient single method for O 2 gas exchange characterization of fruit based on the non-destructive pathlength-resolved GASMAS (gas in scattering media absorption spectroscopy) technique. GASMAS was used to measure the absolute intercellular O 2 concentration in fruit of different apple cultivars (Malus x domestica Borkh.) with distinct porosity including 'Jonagold', 'Braeburn', and 'Nicoter'. To resolve the ambiguity between variation in pathlength and O 2 concentration inherent to GASMAS, the pathlength travelled through pores cavities was quantified through a second GASMAS measurement at the absorption line of H 2 O vapour. Dynamic experiments were then performed in which the fruit was subjected to varying external O 2 concentrations while measuring the internal O 2 response. The observed dynamic profiles of external and internal O 2 concentration were fitted with a lumped -respiration model to estimate the effective mass transfer coefficient, maximum respiration rate and Michaelis Menten constant of intact fruit. The model showed a good fit (R 2 >0.95) with the measured data and reliable estimates for the model parameters. The proposed method provides a novel and more efficient way to estimate the gas exchange properties of fruit that are essential for optimizing CA storage conditions. Future challenges for the proposed method are with applications to other gasses such as CO 2 and ethylene. • Non-destructive and quantitative internal O 2 measurement of apple using GASMAS. • GASMAS measurement on an intact apple in diffuse transmittance mode. • Fast determination of O 2 exchange and respiration kinetic parameters of apple. [ABSTRACT FROM AUTHOR]

• Bulk optical properties of tissue layers were measured for Satsuma mandarin. • The pigment related μ a and the μ s in juice vesicles increased along harvest time. • Color change was presented in the μ a of flavedo along harvest time. • Influence from fruit size was related to the development stage. • The difference in the μ s of flavedo among cultivars enhanced during maturation. As Satsuma mandarin is a multi-layered fruit, the optical properties of the different tissue layers influence the performance of spectroscopy-based quality detection models. Therefore, the variation in the bulk optical properties (BOP) of the inner (juice vesicles) and outer (flavedo) tissue layer of Satsuma mandarin was investigated for different harvest times, fruit sizes and cultivars. Satsuma mandarin fruit from three different cultivars (Iwasaki, Okitsu and Goku Wase) were harvested at three different times around the recommended harvest date and the BOP of the inner and outer tissue layers were estimated from double integrating spheres measurements. Along the harvest time, the absorption peak related to carotenoids in the bulk absorption coefficient (μ a) spectrum increased in both tissue layers, while the values attributed to chlorophylls decreased in the flavedo. Moreover, a slightly increasing trend over the harvest time was observed in the bulk scattering coefficient (μ s) spectra of juice vesicles, especially at the early stage. The μ a values of both tissue layers and the μ s values of juice vesicles deviated among different fruit sizes, which can be related to the development stage. Smaller fruit presented a higher carotenoids concentration in juice vesicles, an advanced color change in flavedo throughout the maturation stages and higher μ s values in juice vesicles at earlier maturation stages. The μ a differences in pigment absorption among different cultivars were related to the maturation order. Earlier maturing cultivars possessed higher μ a values related to carotenoids absorption in juice vesicles and advanced color changes in flavedo. The μ s values of the flavedo differed among the cultivars and these differences were enhanced during maturation. These insights in the sources of variation in the bulk optical properties of Satsuma mandarin tissues can be used for simulation-based optimal design of an optical measurement configuration and interpretation of the acquired signals in spectroscopy-based quality detection and monitoring. [ABSTRACT FROM AUTHOR]

• Provides an overview of the principles and theory of light transfer in biological materials. • Presents instrumentation and data analysis procedures for emerging optical techniques. • Reviews applications of optical properties for fruit and vegetable quality evaluation. • Discusses issues, challenges and future research needs. This paper provides an overview of the principles and theory of measuring optical properties of biological materials. It then presents the instrumentation and data analysis procedures for implementing several emerging optical techniques, including spatially resolved, time-resolved, and spatial-frequency domain, along with the standard integrating sphere method. Applications of these techniques for optical property measurement, maturity and quality assessment, and defect detection of fruits and vegetables are then reviewed, followed with discussions on issues and challenges that still need to be addressed for these emerging optical techniques. While these optical techniques are overall more sophisticated in instrumentation and computation, they are based on radiative transfer theory or simplified diffusion approximation theory. Hence, measurement of optical absorption and scattering properties has the potential of providing more useful information for quality evaluation of horticultural products. At present, these techniques are still slow in measurement, and prone to errors due to modeling and instrumentation deficiencies. Further research is therefore needed in using a better mathematical modeling approach, improving data acquisition accuracy and speed, and developing more robust inverse algorithms for optical property estimations. [ABSTRACT FROM AUTHOR]

Horticultural products may suffer from surface, subsurface, and internal disorders. These lower the market value and may lead to consumer dissatisfaction. Today's postharvest industry has a high interest in implementing technologies that allow efficient sorting of disordered products to avoid food loss, and to improve market value and consumer appreciation. Inspection by machine vision using RGB imaging and more advanced techniques such as spectral cameras, X-ray and magnetic resonance imaging (MRI), is increasingly implemented to non-destructively analyze disorders in horticultural products. However, for objective, robust and reliable detection of symptoms of disorders that are often even not obvious to detect by human vision, powerful data analysis methods are essential. In recent years, image analysis by artificial intelligence (AI) has evolved from traditional machine learning (ML) to advanced deep learning (DL), which is reaching impressive detection abilities. The aim of this article is to introduce recent developments in AI for extracting information on postharvest disorders from complex image data obtained by modern imaging systems to the non-AI expert. The main progress in AI for postharvest applications is the increasing adoption of available convolutional neural networks (CNNs), usually developed and tested with large open source image datasets elsewhere, to postharvest image data. Challenges in the design of DL models are identified, such as the need for large quantities of (labeled) data, the model explainability, and generalizability. Although proposed innovations often result in excellent detection abilities, their usability in an industrial context should be further considered, where uncontrollable parameters may negatively impact the performance. [Display omitted] • Machine vision is increasingly implemented to non-destructively analyze disorders in horticultural products. • Deep learning aids the successful processing of diverse imaging techniques. • Challenges for DL models are the need for (labeled) data, model explainability and generalizability. [ABSTRACT FROM AUTHOR]

Optical measurement of fruit quality can provide the specific insights into the light absorption (μ a) of chemical compositions and the multiple scattering (μ s ′) by structured tissues, and contributes to their precise evaluation. This work comprehensively explored the bulk optical properties (BOPs) in the wavelength range of 600–1500 nm related to the soluble sugars, pectin constitution and microstructural features (area, perimeter, Feret's diameter, cell roundness, cell solidity and intercellular space) of 'Korla' pear cortex during post-harvest storage. The high correlation between μ a values around 980 nm and 1 485 nm and total sugars and sucrose contents were observed with the r values from 0.74 to 0.99. The μ s ′ of pear tissues were positively corelated to the firmness, cell microstructure parameters in cortex (area, perimeter, Feret's diameter and solidity), whereas negatively correlated to their cell roundness and intercellular properties. Besides, the partial least squares regression models based on the featured BOPs of pear cortex successfully predicted the total sugars and sucrose contents with the determination coefficients (R p 2) from 0.73 to 0.91. Further, the combined BOPs feature models based on the first component (PC1) scores of BOPs provide excellent prediction of firmness (R p 2 = 0.90) and acid soluble pectin (R p 2 = 0.93). Accordingly, this study indicated the optical properties have the possibility to present the sugar composition, firmness, pectin and microstructural characteristics of pear tissues. • Sugars and microstructure of pear tissues are reflected in optical properties (BOPs). • The total sugars and sucrose contribute to assess soluble solids in pears by BOPs. • The acid-soluble pectin and cell solidity are key to assess pear structure by BOPs. • The first component scores on BOPs improved the prediction of pear microstructure. [ABSTRACT FROM AUTHOR]

Hypoxia-related disorders in apple and pears such as browning have been associated with insufficient transport of respiratory gasses inside the fruit during controlled atmosphere (CA) storage. Tissue porosity affects gas exchange and, hence, fruit respiration. It might, therefore, be interesting to adapt the storage conditions to the porosity of the fruit, especially in the case of low-porosity fruit like pears, which are highly susceptible to browning disorders. To improve the current CA storage strategies in that direction, fast, non-destructive measurement of fruit porosity is required. To this end, X-ray CT-based porosity maps and spatially resolved spectroscopy (SRS) were used to characterize respectively the porosity and optical properties of intact pear cultivars (Pyrus communis L.), including 'Thimo', 'Cepuna', and 'Conference'. Thereafter, the link between the fruit porosity and light-scattering properties was investigated. The porosity of the tissue region from the fruit surface down to 3 mm deep as well as the spatially averaged porosity of intact pears from 3 cultivars were found to be linearly correlated to the reduced scattering coefficient (µ s') at 760 nm and 835 nm calculated from SRS measurements. Both 'Cepuna' and 'Conference' pears showed similar porosities and scattering levels, which were slightly higher than those observed for 'Thimo' pears. The presented results suggest the possible application of laser scatter imaging at 760 nm and 835 nm for fast, contactless and non-destructive assessment of pear porosity. • X-ray CT-based porosity mapping of intact pear. • Characterization of BOP of intact pear using SRS. • Relationship between scattering and microstructural properties of pear. • Porosity of intact pear linearly correlated to the µ s ' at 760 nm (R2 =0.66). [ABSTRACT FROM AUTHOR]

Bruises in apples is one of the most important quality factors during postharvest, which needs to be detected early and efficiently during sorting processes. In this study, a step-wise pixel based apple bruise detection system based on line scan hyperspectral imaging (HSI) in the shortwave infrared (SWIR) is demonstrated for three apple cultivars: ‘Jonagold’, ‘Kanzi’ and ‘Joly Red’. The SWIR HSI system performance was tested on apples from the different cultivars bruised at five different impact levels, and monitored from 1 to 36 h after bruising. While glare regions are commonly considered as anomalies and discarded from further analysis, their spectral signatures enabled in this work to distinguish between cultivars with a prediction accuracy up to 96%. Different partial least squares-discriminant analysis (PLS-DA) models were trained to discriminate cultivars and then to discriminate between sound, bruised, glossy and stem regions. Spectral area normalization pre-processing was found to be the most effective for pixel based bruise prediction, resulting in a prediction accuracy up to 90.1%. Post-processing of the binary images by exploiting spatial information further improved the bruise detection accuracy to 94.4%. [ABSTRACT FROM AUTHOR]

A non-destructive methodology was developed to automatically detect and quantify bruise volumes in the equatorial region of apples, using X-ray CT images. Grey level threshold values were calculated to segment bruises in ‘Jonagold’, ‘Joly Red’ and ‘Kanzi’ apple fruit using the multi-level Otsu’s threshold method. Comparisons were made between the CT-based bruise volume estimates and bruise volume estimates that were based on destructive measurements in combination with simple geometric assumptions. Visualisation of the bruises in both 2 and 3D showed that bruises, resulting from a pendulum impact with a spherical impactor, can be highly irregularly shaped which implies that the bruise volume estimations based on simple geometric assumptions cannot deliver accurate results. [ABSTRACT FROM AUTHOR]

A contact force model was developed to model the visco-elastoplastic (VEP) behaviour of apples. The model is based on the elastoplastic Thornton model and has been written in a pressure-based formulation to extend the application of the model to Discrete Element Method (DEM) simulations with arbitrary rounded shapes. The parameters of the new developed VEP contact force model were determined by fitting the experimental data acquired from Jonagold, Joly Red and Kanzi apples impacted by a pendulum. With only one parameter set per cultivar and for a large impact range (impact velocity range: 0.3–1.5 m/s), the VEP-model (R 2 = 0.90 ± 0.13) provides a better description of the force-deformation profiles than the viscoelastic Kono and Kuwabara (KK) model (R 2 = 0.71 ± 0.20). The equivalent Young’s modulus (E * ) was also determined under quasi-static conditions, which resulted in measured E * -values for Jonagold, Joly Red and Kanzi apples of respectively 4.24 ± 0.96 MPa, 5.09 ± 1.27 MPa and 7.82 ± 0.41 MPa. The novel VEP-model has the potential to help predict and understand bruise damage in apples as well as other horticultural products. [ABSTRACT FROM AUTHOR]

Lamb’s lettuce ( Valerianella locusta L.) can be stored up to 28 days without being indistinguishable from fresh material by the human eye. However, due to the prior storage period the shelf life potential is limited and this leads to losses in distribution and a lower quality for the consumer. This work aims to develop a rapid and non-destructive methodology using visible/near infrared (Vis/NIR) reflectance spectroscopy to detect and quantify a prior storage period. Vis/NIR reflectance spectra were linked to the time in storage by partial least squares regression (PLS). Different variable selection techniques (interval PLS, Variable Importance in Projection scores, Genetic Algorithms PLS and Monte Carlo Uninformative Variable Elimination PLS) were combined to improve the accuracy and robustness of the prediction model, while decreasing the number of used wavelengths. The final model used only 10% of the original wavelengths, while the root mean squared error of cross validation decreased from 6.0 to 3.6 days. The final model was tested using 2 external test sets and had a maximum root mean square error of prediction of 3.7 days. Vis/NIR reflectance spectroscopy can be a valuable, rapid and non-destructive method for identifying and quantifying a prior storage period of lamb’s lettuce. [ABSTRACT FROM AUTHOR]

Highlights: [•] The optical properties of Braeburn apples before and after shelf-life were measured with a setup for spatially resolved diffuse reflectance spectroscopy. [•] The estimated absorption spectra showed good correlation with the SSC. [•] The estimated absorption spectra gave better prediction of the soluble solids content and firmness than the scattering spectra. [•] The diffuse reflectance spectra gave comparable prediction accuracies to the μ a spectra. [ABSTRACT FROM AUTHOR]

Abstract: Optical coherence tomography (OCT) has emerged recently as a non-destructive technique to visualize subsurface structures of materials. The objective of this work was to investigate whether OCT is an appropriate method to non-destructively assess the peel structural properties of apple fruit and to compare OCT to confocal microscopy and micro-CT. Peel structural properties of apples from different cultivars (‘Braeburn’, ‘Arlet’, ‘Royal Gala’ and ‘Ida Red’) were measured. The effects of preharvest fertilization treatments and storage duration on calculated structural properties of apple peel from OCT images were investigated. It was found that OCT is a fast, high resolution and high field of view technique that renders 2D and 3D images of apple peel. En-face OCT allows the visualization of the surface topology including cracks in the wax, surface roughness and lenticels. Depth scans with OCT reveal the cellular structure down to a few hundreds of micrometre into the fruit, superior to confocal imaging. Spectral-domain OCT resulted in higher quality images than time-domain OCT. Cuticle, epidermis and hypodermis cells can be resolved in a superior way compared to micro-CT. It was concluded that OCT can be used to visualize peel structural differences between apples, as well as to measure structural changes that occur during storage. OCT is a fast method and allows for combining a high depth resolution with a wide lateral image size. [Copyright &y& Elsevier]

Abstract: The use of diffuse reflectance visible and near infrared (Vis/NIR) spectroscopy was explored as a non-destructive technique to predict ‘Nules Clementine’ mandarin fruit susceptibility to rind breakdown (RBD) disorder by detecting rind physico-chemical properties of 80 intact fruit harvested from different canopy positions. Vis/NIR spectra were obtained using a LabSpec® spectrophotometer. Reference physico-chemical data of the fruit were obtained after 8 weeks of storage at 8°C using conventional methods and included RBD, hue angle, colour index, mass loss, rind dry matter, as well as carbohydrates (sucrose, glucose, fructose, total carbohydrates), and total phenolic acid concentrations. Principal component analysis (PCA) was applied to analyse spectral data to identify clusters in the PCA score plots and outliers. Partial least squares (PLS) regression was applied to spectral data after PCA to develop prediction models for each quality attribute. The spectra were subjected to a test set validation by dividing the data into calibration (n =48) and test validation (n =32) sets. An extra set of 40 fruit harvested from a different part of the orchard was used for external validation. PLS-discriminant analysis (PLS-DA) models were developed to sort fruit based on canopy position and RBD susceptibility. Fruit position within the canopy had a significant influence on rind biochemical properties. Outside fruit had higher rind carbohydrates, phenolic acids and dry matter content and lower RBD index than inside fruit. The data distribution in the PCA and PLS-DA models displayed four clusters that could easily be identified. These clusters allowed distinction between fruit from different preharvest treatments. NIR calibration and validation results demonstrated that colour index, dry matter, total carbohydrates and mass loss were predicted with significant accuracy, with residual predictive deviation (RPD) for prediction of 3.83, 3.58, 3.15 and 2.61, respectively. The good correlation between spectral information and carbohydrate content demonstrated the potential of Vis/NIR as a non-destructive tool to predict fruit susceptibility to RBD. [Copyright &y& Elsevier]

Abstract: The effect of cultivar, season, shelf-life and origin on the accuracy of near infrared (NIR) calibration models for the soluble solids content (SSC) and firmness of apple was studied based on a large spectral data set based on approximately 6000 apple fruit from different cultivars, origins, shelf-life exposure time and seasons. To interpret the variance in the spectra with respect to biological variability, functional analysis of variance (FANOVA) was used. From the FANOVA analysis it was concluded that the effects of cultivar, origin and shelf-life exposure time on the NIR spectra were all significant. The largest differences in the spectra were found around the water absorption peaks (970, 1170 and 1450nm). External validations using independent data sets showed that the accuracy of the models increased considerably when more variability was included in the calibration data set. In general the RMSEP for predictions of the SSC were in the range 0.6–0.8°Brix, while for Magness Taylor firmness it was 5.9–8.8N, depending on the cultivar. It was shown that atypical data can lead to large validation errors. It is, therefore, important to collect a calibration data set which is sufficiently representative for future samples to be analyzed with the developed calibration models and to develop simple procedures for model adaptation during practical use. [Copyright &y& Elsevier]

Abstract: Continuous wave (CW) and time-resolved (TRS) near infrared (NIR) reflectance measurements were carried out on ‘Conference’ pear fruit. While the absorption coefficient spectra obtained from the TRS measurements were dominated by the overtone of the hydroxyl moiety at 975nm, the scattering coefficient spectra were almost flat. The spectral data were used to construct calibration models for the soluble solids content (SSC) and Magness Taylor firmness of ‘Conference’ pear fruit. Reasonable models for SSC (RMSEP=0.44 °Brix) were obtained when the CW spectra in the range 780–1700nm were used, but not when the range was limited to that of the TRS equipment (875–1030nm). No satisfactory calibration model could be established between the TRS absorption coefficient spectrum and SSC. With none of the spectroscopic techniques could significant calibration models for firmness be constructed, although a highly nonlinear relationship between scattering coefficients at 900nm and firmness was observed. [Copyright &y& Elsevier]

Abstract: An overview is given of near infrared (NIR) spectroscopy for use in measuring quality attributes of horticultural produce. Different spectrophotometer designs and measurement principles are compared, and novel techniques, such as time and spatially resolved spectroscopy for the estimation of light absorption and scattering properties of vegetable tissue, as well as NIR multi- and hyperspectral imaging techniques are reviewed. Special attention is paid to recent developments in portable systems. Chemometrics is an essential part of NIR spectroscopy, and the available preprocessing and regression techniques, including nonlinear ones, such as kernel-based methods, are discussed. Robustness issues due to orchard and species effects and fluctuating temperatures are addressed. The problem of calibration transfer from one spectrophotometer to another is introduced, as well as techniques for calibration transfer. Most applications of NIR spectroscopy have focussed on the nondestructive measurement of soluble solids content of fruit where typically a root mean square error of prediction of 1° Brix can be achieved, but also other applications involving texture, dry matter, acidity or disorders of fruit and vegetables have been reported. Areas where more research is required are identified. [Copyright &y& Elsevier]

• GASMAS for pome fruit respiration measurement. • Fruit mimicking model system for GASMAS oxygen sensor validation. • Influence of skin and additional surface coating on gas exchange rate. Pome fruit stored under a controlled atmosphere (CA) often suffers hypoxia due to the mismatch of O 2 level in the storage rooms and the fruit's O 2 consumption. Fruit response-based O 2 sensing and control could be an efficient approach to reduce the hypoxia-related physiological disorders and therefore increase the shelf life of stored fruit. This research aims to validate and evaluate the application of nondestructive gas in scattering media absorption spectroscopy (GASMAS) O 2 sensing in fruit post-harvest. In the first stage, the GASMAS O 2 sensor was validated on a fruit mimicking multilayer model system where a high correlation was observed between the measured and reference O 2 partial pressures (r2 ≥ 0.9). Later, the GASMAS sensor was evaluated on two apple cultivars (Malus x domestica 'Golden delicious', Malus x domestica 'Nicoter') and one pear cultivar (Pyrus communis 'Conference'). The observed GASMAS signal from the 'Golden delicious' apples were nearly 2 times higher than the signal from 'Nicoter' apples and 5 times higher than from the 'Conference' pears. In the next stage, GASMAS measurements were taken on water submerged 'Golden delicious' apple and 'Conference' pear to investigate the difference in O 2 consumption in those fruit. The calculated relative O 2 changes during respiration and evolution of the O 2 partial pressure after nitrogen treatment for both the fruit were found different. It was hypothesized that these findings may be attributed to variations in fruit porosity. And finally, the influence of skin and additional surface coating on the gas exchange was studied by immersing unpeeled, peeled and coated samples in the gaseous nitrogen for 2 h before measurement. The coating was found to reduce the gas exchange compared to the unpeeled samples which already exhibited a lower exchange rate than the peeled samples. [ABSTRACT FROM AUTHOR]

• TRS absorption coefficients are more related to pigment and water of the fruit flesh. • SRS absorption coefficients are strongly affected by pigments in the fruit skin. • Fruit softening was accompanied by increasing values of reduced scattering coefficient. • TRS and SRS capture valuable information on the changes in flesh texture. Bulk optical properties, in terms of absorption (μ a) and reduced scattering coefficients (μ ′ s), can be used for the non-destructive monitoring of fruit quality during ripening. In this study, the performance of time-resolved (TRS) and spatially-resolved (SRS) spectroscopy were compared by analyzing 'Braeburn' apples over a 21 d period of ripening. Nine batches of 20 apples each were measured on the blush side by TRS (540−1064 nm) and SRS (550−1000 nm). Every fruit was analyzed for skin color, texture characteristics, relative internal space volume (RISV), total solid soluble and titratable acidity contents. TRS absorption spectra showed two maxima, the highest at 980 nm (water) and the second at 670 nm (chlorophyll), while in SRS spectra the main peak was measured at 550 nm (anthocyanins) followed by that at 670 nm. The values of μ a 580 SRS and of μ a 670 SRS were much higher than those measured at the same wavelengths by TRS suggesting that TRS and SRS actually explore the apple tissue (skin and/or flesh) in a different way. The values of μ a 980 TRS were higher than those of μ a 980 SRS , probably due to the fact that water content was lower in the skin (mostly probed by SRS) than in the flesh (mostly probed by TRS). No significant correlations were found between μ a 580 SRS and μ a 580 TRS and between μ a 980 SRS and μ a 980 TRS but a low positive relationship was observed between μ a 670 TRS and μ a 670 SRS. On the contrary, high correlations were found between μ a 670 SRS and the spectral index I AD (index of absorbance difference) related to chlorophyll in the skin and between μ a 580 SRS and the spectral index ARI (anthocyanin reflectance index), related to anthocyanin content in the peel, suggesting that μ a 580 SRS is linked to the development of the red color in the peel. Both μ a 670 TRS and μ a 670 SRS decreased during fruit ripening, indicating a decline in chlorophyll in the flesh and skin, respectively. During the shelf life period, apples became soft and mealy, as mechanical and acoustic parameters decreased and RISV increased. Fruit softening was accompanied by increasing values of both μ ′ sTRS and μ ′ sSRS. The μ ′ sTRS and μ ′ sSRS were positively related to each other, were positively correlated to RISV and negatively related to mechanical and acoustic parameters. Both the TRS and SRS technique were able to follow ripening processes in 'Braeburn' apples during the shelf life period, as absorption phenomena were related to changes in pigments present in the fruit flesh and skin, while scattering events mirrored changes in the flesh texture. [ABSTRACT FROM AUTHOR]

• Bulk optical properties of citrus tissues were measured for different species. • Bulk optical properties were compared among tissue layers and fruit sizes. • Scattering coefficient was negatively correlated with the size of the oil glands. • Attenuation coefficient was most fit for the prediction of total soluble solids. • Absorption coefficient was most fit for the prediction of titratable acidity. Vis-NIR spectroscopy and hyperspectral imaging are useful tools for citrus quality evaluation in postharvest grading lines. The bulk optical properties (BOP) of citrus tissues determine the interaction of light with citrus fruit, and thereby influence the measured spectral signal. Therefore, knowledge about the BOP of citrus tissues is important for the improvement of spectral techniques and interpretation of spectral signals. In this study, the BOP of different citrus tissues (flavedo, albedo and juice vesicles) were measured for different fruit types (grapefruit, orange, lemon and lime) and the relationship between the BOP and different quality properties was explored. The bulk absorption coefficient (μ a) spectra in the NIR range were dominated by the absorption peaks of water around 980, 1200 and 1450 nm. For the flavedo tissues, absorption peaks around 480 nm were observed for all the species and an absorption peak around 680 nm was found for lime, which could respectively be attributed to carotenoids and chlorophyll. The differences in the bulk scattering coefficient (μ s) among different tissue layers were obvious: flavedo and albedo had high μ s values, ranging from 25 mm−1 to 35 mm−1, while the μ s values of the juice vesicles were below 3 mm−1 in the whole wavelength range (440 nm–1840 nm). The changes in anisotropy factor (g) with wavelength varied among different tissue layers. The g values for flavedo were relatively flat over the whole wavelength range, while an increasing and slightly decreasing trend could respectively be observed for albedo and juice vesicles. The absorption coefficient spectra for the flavedo tissues of the different species showed different absorption peaks related to the pigments which determine their skin color. The differences in μ s and g between the different species were smaller than the variation among different tissues. The bulk optical properties were then related to the quality properties. A negative correlation was found between the average value of μ s and the diameter of the oil glands in the flavedo. The best prediction models for total soluble solids (TSS) and titratable acidity (TA) were respectively achieved based on the attenuation coefficient (μ t) and μ a of juice vesicles. This study was the first attempt to measure the BOP of citrus tissues and gave a view on the correlation between BOP and quality properties, which made the foundation for further development and optimization of the optical design of quality sensors for citrus fruit. [ABSTRACT FROM AUTHOR]

• Contrast enhanced micro-CT was refined for surface microstructure data of apple. • Reduced scattering coefficient extracted by Hyperspectral Laser Scattering Imagin.g • PLS model built to determine the microstructural properties affecting scattering. • Overall porosity and pore surface density related well with scattering (R2 = 0.89). • Optical determination of subsurface porosity seems feasible. The success of long-term storage of apples under controlled atmosphere (CA) depends, amongst others, on the gas exchange properties of the fruit. As gas exchange is effectively dictated by the microstructure of the fruit, the ability to obtain microstructure data becomes critical to improve storage solutions. The current study complements scattering measurements by means of spatially resolved spectroscopy (SRS) with 3D microstructure data obtained with contrast enhanced X-ray computed micro-tomography (micro-CT). Complementary measurements with both techniques were performed on apples of different cultivars that have different optimal storage conditions and different fleshy microstructure ('Kanzi', 'Braeburn', 'Jonagold' and 'Golden Delicious'). The mean reduced scattering coefficients of the subsurface tissue were calculated from SRS measurements in the 750 nm to 900 nm range at specific equatorial positions on the intact apple. Microstructural parameters such as cell size (equivalent spherical diameter), anisotropy, elongation, flatness, sphericity, object count, porosity as well as pore surface density were quantified and analyzed at the same spot up to 3 mm in depth from the fruit surface. A partial least squares regression model using the microstructural parameters as the different variables to predict the reduced scattering coefficient was built in order to identify the parameters contributing most to this relation. Both mean porosity and pore surface density showed the largest absolute regression coefficients. Furthermore, plotting the reduced scattering coefficient against mean porosity and pore surface density produced a linear relationship between the two parameters with an R2 of 0.89 for both sets of data. The linear relationship suggests that the porosity of individual fruit can be determined via optical SRS measurements. This could allow to sort fruit based on their porosity, thus promoting fine tuning of the storage strategies by reducing variation in the porosity and gas exchange rate of the fruit being stored together. [ABSTRACT FROM AUTHOR]