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Organic fertilizers --- Organic fertilizers --- Slurry --- Slurry --- nitrogen cycle --- nitrogen cycle --- Environmental impact --- Environmental impact --- plant requirements --- plant requirements --- Low input agriculture --- Low input agriculture --- Fertilizer distributors --- Fertilizer distributors --- Injection --- Injection --- Optimization methods --- Optimization methods --- computer applications --- computer applications --- Measurement --- Measurement

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In the agro-food industry, there is an increasing demand for non-destructive, fast and cost-efficient methods for the objective determination of product quality. Several parameters influence the quality of a product, while the importance of each of these parameters may vary amongst people. Optical measurement techniques are often used because of their non-destructive nature. However, the robust determination of both chemical and physical quality attributes remains difficult. In this work, a non-destructive determination of quality was performed using laser scatter imaging. This technique allows to obtain more information on both the absorption and scattering of light, by retrieving spatial information. The bulk optical properties (bulk absorption coefficient, bulk scattering coefficient and scattering anisotropy factor) are used to characterize absorption and scattering properties.^ The absorption of light is related to the chemical composition of a product, like present pigments, water or sugars. Scattering of light is more related to the physical structure, possibly allowing to retrieve more information on physical quality attributes, like firmness, tenderness or porosity. Optical properties of light were derived from the obtained scatter images using a data-based modelling technique, possibly allowing a better prediction of product quality. This approach was tested in two case studies, apples and bovine meat, selected because of their economic importance for Belgium.First, a hyperspectral laser scatter imaging (HLSI) system was developed. A combination of a supercontinuum laser with monochromator was used to illuminate samples with monochromatic light in the 550 nm to 1000 nm range, while a CCD camera was used to take images of the diffuse reflectance glow spots.^ From this glow spots, a diffuse reflectance profile with the light intensity relative to the distance from the point illumination was obtained. Models were constructed to optimize the detector size and the source-detector distance, estimating different quality parameters of Braeburn apples. A detector size of 0.82 mm was found to be adequate for the estimation of all parameters, including the starch value, firmness, SSC and Streif index. Different source-detector distances were found to be of importance for predicting different quality traits. Photons exiting the sample closer to the point illumination, which have interacted less with the sample, were more important for SSC prediction, while the prediction of physical parameters like firmness relied on photons which had more interaction with the sample. Moreover, using variable selection, the wavelength regions of pigment and water absorption were found to be most informative.^ A classification of apples into ripeness classes based on these models was possible, with a misclassification rate of 12.5%. Nevertheless, these models still used mixed information, including both the effects of absorption and scattering.Using the double integrating spheres (DIS), the golden standard method for determining bulk optical properties (BOP), the interaction of light with both apple and bovine meat samples was studied. Both the apple skin and cortex were studied separately during maturation of bi-colored (Braeburn and Kanzi) and green cultivars (Greenstar). The bulk absorption coefficient µa of the skin showed features of anthocyanins at 550 nm, chlorophyll at 678 nm and water at 970 nm, 1200 nm and 1450 nm, while the µa of the cortex showed an overall lower absorption attributed to carotenoids, chlorophyll and water.^ During maturation of apples, an increase in the absorption by anthocyanins was observed in the red cultivar’s skin, while a decrease in absorption by chlorophyll was observed in the cortex. Both the bulk scattering coefficient µs and anisotropy factor g of the skin were significantly higher in comparison to the cortex. Both skin and cortex were found to be highly forward scattering with anisotropy factors above 0.9 in the entire wavelength range between 500 nm and 1850 nm. During maturation, no clear evolutions in the anisotropy factor were observed, while µs decreased in the fruit cortex. It was hypothesized that the shape and size of the scattering particles hardly changed during maturation.The DIS analysis showed changes in the optical properties of apple during maturation. This indicates that the non-destructive estimation of BOP could be beneficial in determining apple quality.^ To go from scatter images towards an estimation of the optical properties, a data-based model was used. To train this model, a set of optical phantoms with known optical properties was measured using the HLSI system. These diffuse reflectance measurements, in combination with the BOP from the DIS, were used as an input for a metamodel, linking the BOP to diffuse reflectance profiles. The metamodel showed a good performance for a set of validation phantoms, with an R2V of 0.9977 and 0.957 in combination with an RMSEV of 0.20 cm-1 and 3.21 cm-1, for respectively µa and µs’. Nevertheless, at wavelengths with extreme BOP values, the predictions were less accurate. The prediction of apple BOP showed an expected course for the µa spectra, with absorption features of anthocyanin, chlorophyll and water. However, an incomplete separation between µa and µs’ was obtained, as µs’ still showed some distinct absorption features.^ Nevertheless, at wavelengths with low absorption, the estimation of µs’ was according to expectations. In addition, the same evolutions in BOP as found with the DIS setup were also found with the non-destructive HLSI technique. Though, no clear relation was obtained between apple quality and the estimated BOP. Possibly, the low variability of both SSC and firmness during maturation, together with a high variability amongst apples from the same harvest day, could have complicated the prediction models. Moreover, still mostly information on the changes of apple pigments was used in the models.Next, two bovine muscles were measured using the DIS as well. Both the longissimus lumborum (LL) and the biceps femoris (BF) were considered, while the BF was further divided into an outer and inner part, due to two-toning. Clear absorption features of myoglobin, mainly oxymyoglobin at 544 nm and 582 nm, and water were found in the µa spectra.^ A higher absorption of myoglobin was found in the BF samples, while also a higher µs and a lower g was found in this muscle compared to the LL. The inner and outer BF showed significant scattering differences, possibly related to an increased degree of protein denaturation in the inner BF. During wet aging, when meat tenderness increases, a decrease in the measured g was noticed in both muscle samples.When measuring muscle samples using spatially resolved spectroscopy, anisotropic light scattering by the present muscle fibers should be accounted for. By measuring muscle samples with different initial fiber orientations, it was shown that muscle fibers can change the shape of the diffuse reflectance glow spots from circular to a rhombus shape. This effect was mainly present in the samples with the muscle fibers running parallel to the measurement surface. Moreover, the rhombus’ major axis orientation was related to the distance from the point of illumination.^ Close to the point illumination the major axis orientation was found to be perpendicular to the muscle fibers, while at larger distance a 90° shift occurred, aligning the major axis with the muscle fibers. In these samples with muscle fibers parallel to the measurement surface, the fiber orientation could be predicted based on the fitted rhombuses, with an R2P of 0.993 and RMSEP of 3.95°. These results show the importance of the 3D fiber orientation when measuring diffuse reflectance signals. Moreover, this 3D fiber orientation could possibly be determined using the obtained diffuse reflectance signals.The prediction of muscle BOP values using the metamodel also showed similarities with the DIS measurement. Clear absorption features of oxymyoglobin and water were present, while the absorption by metmyoglobin was observed as well, related to the ticker samples measured using HLSI.^ A thicker sample allows a gradient of myoglobin forms to exist, relative to different depths inside the sample. Again, larger µa and µs’ values were observed for the inner BF samples, while both the outer BF and LL samples showed lower values for µs’. During wet aging, a significant increase was obtained for the µs’ of the LL muscle. Moreover, due to the non-destructive nature of HLSI, measurements were possible through the plastic vacuum pack. Due to the lack of oxygen inside the vacuum pack, mainly deoxymyoglobin with an absorption peak around 557 nm was present. Measurements on the exact same sample during wet aging, through the vacuum pack, also showed an increase in µs’ of the LL muscle.^ As the changes in meat tenderness were most prominent in the LL muscle, it was suggested that the increase in meat tenderness could explain the observed increase in µs’ for this muscle.Finally, a limited number of wavelengths were selected to design a multispectral hand-held measurement device. Four laser diode modules emitting at wavelengths of 533.3 nm, 674 nm, 800.7 nm and 981.1 nm, were selected and mounted around a CCD camera. Using shutters, the laser light of the different modules was guided onto the sample sequentially. Again, a metamodel was built by measuring a set of liquid optical phantoms with a wide range of both µa and µs’. In validation, the metamodel showed an R2V of 0.9724 and 0.9377 in combination with an RMSEV of 0.56 cm-1 and 5.13 cm-1 for µa and µs’ respectively.^ However, for the prediction of apple and pear samples, with and without the skin, an incomplete separation between absorption and scattering properties was obtained, mainly at wavelengths with high absorption values. Nevertheless, the est

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Food quality is an important aspect for the food industry which refers to the production of safe, high nutritional as well as tasty food products. To meet consumer requirements food manufacturers would like to have fast, accurate and non-destructive quality control techniques. Visible (Vis) and Near Infrared (NIR) spectroscopy has been extensively applied as non-destructive quality inspection technique. Traditionally, the quality attributes are predicted based on statistical relations between the acquired spectra and the properties of interest, which are established through the use of multivariate calibration methods. Although these multivariate statistical methods have been extensively used for non-destructive prediction of quality attributes, in complex biological materials such as food these data-based models often prove not to be robust, due to the complex interaction of incident light with food involving both absorption and scattering of the light. Inability of conventional Vis/NIR spectroscopy to separate scattering and absorption information contained in the spectra limits its robustness for prediction of the chemical composition and its usefulness for determination of the microstructure of foods. To overcome the limitations of classical Vis/NIR spectroscopy this PhD research aimed to separate the information on the scattering and absorption properties of food samples by combining multiple diffuse reflectance measurements which are resolved in space. For this purpose, a setup for contactless spatially resolved spectroscopy (SRS) in the 500-960 nm range has been elaborated by combining a focused broadband light beam for the illumination with a hyperspectral line-scan camera for contactless acquisition of SRS profiles. To estimate the absorption coefficient and the reduced scattering coefficient from the SRS profiles acquired at every wavelength, an iterative estimation has been implemented around a data based light propagation model. This metamodel was trained and validated by means of liquid and solid phantoms covering a wide range of optical properties relevant for food products. The reference optical properties of these phantoms were calculated from double integrating spheres (DIS) measurements, the reference technique for bulk optical properties measurement on turbid samples. The forward and inverse validation of the metamodeling approach on the optical phantoms showed good prediction accuracy. This indicates that this combination of hyperspectral scatter imaging with an inverse light propagation model can provide a fast and accurate estimation of the bulk optical properties of turbid samples, such as foods. This technique was then used to estimate the bulk optical properties of different model foods: sugar foams with the same composition, but different microstructures induced by different foaming times, crispy breads produced with different extruder settings, and Braeburn apples stored for a longer period under controlled atmosphere (CA) conditions and exposed to shelf-life. The estimated optical properties were then used to evaluate the food quality attributes by relating them to the composition and microstructure for better understanding the structure-property relations. Finally, the estimated scattering properties of these food samples were correlated with destructive measurements: X-ray micro-CT (sugar foam), universal texture analyzer (crispy breads and Braeburn apples) for non-destructive estimation of the microstructure parameters of the aforementioned samples. Clear relations were observed between the estimated bulk optical properties (scattering property) and microstructure of the sugar foams and crispy bread samples. These results support the potential of hyperspectral scatter imaging to provide an indirect estimation of the food composition and texture parameters in a rapid and non-contact way. This makes it a very interesting technique for online quality inspection and process monitoring in the food industry. While good results were reported for the model foods, the results for apple fruit with its more complex microstructure were inconclusive with respect to the potential of hyperspectral scatter imaging for non-destructive assessment of the consumption quality. The estimated absorption coefficient spectra of the Braeburn apple fruits clearly showed the changes in chemical composition of the apples during CA storage over a longer period (up to 6 months) and shelf-life exposure (14 days). Mainly, these changes were observed as a decrease in the absorption coefficient values around 670 nm which was due to the degradation of chlorophyll during storage. Also, a clear decrease in the scattering properties of the apples was observed after 14 days of shelf-life exposure. However, no clear differences were observed in the optical properties estimated for the apples which had been stored under optimal and brown inducing CA storage conditions. This was explained by the fact that hyperspectral scatter imaging only probes the outer layers of the fruit, while the browning typically starts at the center of the fruit. Quantitative prediction of the internal apple quality in terms of soluble solids content (SSC) and fruit firmness (FF) based on respectively the bulk absorption coefficient and the reduced scattering coefficient did not result in higher prediction accuracy than prediction based on single point Vis/NIR reflectance spectra. The overall results clearly support a strong potential of the combination of the line-scanning hyperspectral scatter imaging technique with the computationally fast and accurate inverse metamodeling approach for fast, contactless and non-destructive optical properties estimation of food products to separate the information on the microstructure from that on the chemical composition.

664.017 --- Academic collection --- Properties of preserved foods and foodstuffs. Food quality --- Theses --- 664.017 Properties of preserved foods and foodstuffs. Food quality

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Quality assessment and process monitoring are essential for today's fruit industry sector and the world's economy. From picking fruit in orchards, to transport and handling practices, to storage and packaging, each step will influence the quality of the end-product when presented to the consumers. The appearance, consisting of the shape, size, colour or absence of any damage are essential criteria relevant to consumers, and influence their will on buying. It is therefore essential to provide a fast, consistent quality assessment of each fruit to match the expectations of the market. To remain competitive to this demand at low cost, fast and efficiently, non-destructive automated quality sorting lines are needed. Among the different defects affecting fruit quality, bruises are one of the most problematic industrial losses. The detection of bruises in fruit such as apples during handling is therefore required.^ The browning process of bruises results in progressive apple tissue softening and colour changes. As this natural process takes time before it becomes visible, there is a gap of a few days between the mechanical damage causing the bruise and the consequent visible brown spots, which lower the price of apples. It is therefore important to detect bruises on each apple as early as possible after damaging to limit consequent economical losses.Light is the fastest known information carrier. In ambient conditions, it is also harmless for fruit or the surrounding workers, and a cheap technology. Among the different non-destructive and non-invasive techniques, the usage of light and the analysis of the information it can carry is therefore the most promising path. By shining light onto apples, and observing the absorbed, reflected and scattered light, bruises may be detected non-destructively at high speed.^ Among the most recent technologies reported, hyperspectral imaging (HSI), being the combination of the machine vision and spectroscopy fields, is showing promising paths. More particularly, the short-wave infra-red (SWIR) range has been demonstrated to promote successful detection of bruises in apples at early stages. However, there are still limiting factors when using SWIR HSI prior its success in industry. Among them, the most predominant are high noise levels arising from the detectors, non-uniform illumination, specular reflections and real-time HSI data handling. This research aims to tackle those problems be first describing and modelling the different components consisting of a SWIR HSI sorting system being the illumination and the imager, and further optimizes their configuration for better image quality. Those building blocks are further put together combined with improved data handling more robust and efficient usage of SWIR HSI in industry.^ This research is split into 10 chapters.Chapter 1 covers the current practices in image based fruit sorting, with a stronger emphasis on hyperspectral imaging. It further compares visible and near infra-red (Vis-NIR) to SWIR HSI and where are the additional challenges when using SWIR over Vis-NIR. The chapter then describes the relevance of apples in industry and why early bruise detection. The chapter ends with the outline of this thesis.Chapter 2 describes the state-of-the-art in light, its interaction with matter, with a focus on polarisation and vibrational spectroscopy. The browning bio-chemical process of apples is further described. The algorithms used to process light spectral information, also referred to multivariate data analysis which are applied within this research are then described.Chapter 3 is focused on characterising the noise and sensitivity of a SWIR hyperspectral imager, to quantify the signal to noise ratio (SNR).^ To quantify the pixel-to-pixel variation or the detector’s response, a radiometric calibration method is proposed which dynamically removes the detector noise. This approach removed 6% further noise compared to conventional sequential noise sampling methods. The average detector noise or dark current evolution through time is then shown, which was noted to vary non-linearly, with a sub-linear trend one hour after start-up to stabilize after 3 hours, with up to 12% of the imager’s dynamic range. Contrast of each spectral image is also described using a novel custom-made checkerboard calibration rig. The following showed a ratio per wavelength up to 15000 versus 1 raw values with 100-1700 nm.^ The checkerboard also enabled accurate spatial calibration using a thin lens model.Chapter 4 describes how to measure, model analytically and using non-sequential ray-tracing software the spectral and angular distribution of halogen tungsten (HT) spots, considered as the standard in SWIR HSI illumination. The far field angular distribution was modelled with a Gaussian distribution with an R² of 0.99, while the spectra using a Plank based 5th order polynomial with and R² of 0.98. The modelled spectra enabled to convert photometric measurements into radiometric units, and estimate the energy contribution of the spots in the SWIR spectral range, with up to 63% of the total spectral power. Further, near-field spot distribution is measured and modelled within the ray-tracing software, comparing irradiance distributions when using or not diffusers.^ It was shown that the irradiance patterns could be reproduced with a peak relative error of 12% when using diffusers, while up to 30% without.Conventional illumination distribution and light beam shaping are non-linear problems, which often are solved using iterative methods such as simplex or simulated annealing (SA) optimization algorithms, which can result in sub-optimal solutions or time consuming searches. Chapter 5 introduces novel constrained non-linear global optimization algorithms which can handle more efficiently such problems while simultaneously offering information on the sensitivity of a configuration near its optimum. A design is proposed using 4 HT spots placed around a flat target, using the source models from chapter 4. The two proposed optimization methods are referred to as Design of Computer Experiments with Design Augmentation (DACEDA) and Design of Computer Experiments with Simplex post-optimization (DACES).^ A 2 variables analytical version of the problem using isotropic source models enabled to compare DACES and DACEDA’s modelled design space with an overall average relative error of 2%, with a peak up to 10% at the corners of the design space. The SNR of ray-traced near-field sources modelled in chapter 4 is quantified using the Rose model, setting the stop criterion of the proposed optimization algorithms. The simulated irradiance distribution uniformity is then optimized for a 2 and 5 variables case studies with DACES, DACEDA, simplex and SA. In the 2D case, it was shown that DACES performed best after 30 simulations while in the 5D case, DACEDA performed best after 65 simulations.^ Both algorithms were further used in a case study with DACEDA for tolerance analysis, and DACES for optimization of a configuration for apples, which was used within the remaining of the thesis.Among the main challenges when using SWIR HSI for fruit quality inspection, are the glossy regions observed from their arbitrary deformed toroidal shape and waxy surface. Therefore, this research further aimed at reducing the influence of those specular reflections, both numerically and optically.In chapter 6, a first proposed approach is to use chemometrics tools combined with image analysis to reduce or remove those artefacts, using a multiclass classifier or a stepwise approach. The proposed method using iterative steps to remove progressively automatically unwanted regions resulted in 6% higher prediction accuracy than a multi-class partial least-squares discriminant analysis (PLS-DA) classifier. Appropriate wavelength selection using interval PLS-DA enabled to improve further by 4%.^ Furthermore, the stepwise algorithm enabled to detect for multiple cultivars up to 80% six hours after bruising.Chapter 7 uses the multi-class PLS-DA classifier from chapter 6 on a real-time case study of one cultivar, and compare pixel based calibration models to conventionally used region based ones. Pixel based models, encountering for variations described in chapter3, improved prediction accuracy at the pixel level up to 2%. With a cultivar based model built for 2 hours after damage, using area normalization as spectral pre-processing and image post-processing, a pixel-based prediction of accuracy of 95.6% was obtained, while up to 98% at the sample level.^ The following was demonstrated on a real-time SWIR HIS sorting system at a rate of 200 ms per apple at a scanning speed of 0.3 m/s.To further improve those results, chapter 8 aims at quantifying the degree of glossiness for apples as a function of the light geometrical path, also referred to as surface scatter properties or bi-directional scatter distribution function (BSDF). It was shown that apples have a Gaussian gloss trend around the specular angle, and are Lambertian outside the glossy region.Moreover, polarization properties of apples are then investigated in chapter 9, in the aim to remove optically gloss arising from apples using a cross-polarized imaging system.^ It was shown that gloss could be removed for multiple cultivars using cross-polarization, and that the resulting scattered reflected light was Lambertian, thus improving the image uniformity and bruise-sound contrast region.Finally, the combination of the conclusions drawn from the different chapters and future research perspectives are given in chapter 10. It can be concluded that near-field ray-traced sources with diffusers are the best choice for SWIR illumination, which can be optimized using DACES or DACEDA for improved uniformity. It was shown in this research that real-time SWIR HSI is possible, and using broad spectral has significant added value. It was shown that using the knowledge of

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Light consists of photons, tiny particles, that each have a specific wavelength. The wavelengths of the photons in the light determine its color. White lights consists of photons of all wavelengths in the visible light range and is emitted from a source such as the sun or a lamp. On its trajectory, light bumps into objects. Mostly, light is not directly reflected by the object but rather enters the object. Inside, the light will collide with the molecules in the object until it eventually exits the object. Not all of the incident light eventually leaves: some of it is absorbed. The chemical composition of an object determines the intensity by which photons of different wavelengths are absorbed. This phenomenon causes apples to appear red and bananas to appear yellow.In traditionally photography, the pixels of the photograph summarize the incoming light into color information. This is sufficient for the image to be displayed or printed but ignores a large part of the chemical information that the light contains. This thesis regards the analysis of hyperspectral images. The pixels in a hyperspectral image carefully record the intensity of the incoming photons per wavelength. This information is then translated into absorbance spectra from which the chemical composition of an object can be determined. Example uses of hyperspectral images are the detection of counterfeit medication or the identification of bruises in apples.This work focusses on MCR-ALS, a method to recover the concentration of molecules from absorbance spectra. Furthermore, MCR-ALS determines the pure absorption spectra for the molecules. A pure absorption spectrum conveys how the light would be absorbed if the object would consist solely of one type of molecule. The first chapter reviews some of alternatives to MCR-ALS and motivates our choice for this algorithm.The second chapter considers the initial value problem. MCR-ALS requires an initial guess of either the concentrations or the pure absorba...