Bart Nicolai

NON-DESTRUCTIVE MEASUREMENT OF ACIDITY, SOLUBLE SOLIDS, AND FIRMNESS OF JONAGOLD APPLES USING NIR-SPECTROSCOPY

In this study the potential of visible and near infrared spectroscopy (380-1650 nm) as a non-destructive measurement technique for measuring quality characteristics of Jonagold apples is evaluated. A relation has been established between the reflectance spectra recorded with a bifurcated optical fibre and fruit parameters such as the pH, the soluble solids content, the stiffness factor and other texture parameters such as the elastic modulus of the flesh. The data were analyzed with multivariate calibration techniques such as principal component analysis (PCA), principal component regression (PCR) and partial least squares analysis (PLS). The impact of the data preprocessing on the prediction performance has also been investigated. The prediction models indicate a good to excellent prediction performance. The best pH model has a standard error of prediction (SEP) of 0.068 and a correlation between predicted and measured values (r) of 0.93. The proposed model for the stiffness factor has a SEP of 2.49 and an r-value of 0.90. For the soluble solids content model a SEP of 0.61 and an r-value of 0.82 is obtained. It has been shown that the pH model has a physico-chemical background. The prediction performance of the model for the elastic modulus, however, was not yet satisfactory (SEP = 0.26, r = 0.75).

Three-Dimensional Gas Exchange Pathways in Pome Fruit Characterized by Synchrotron X-Ray Computed Tomography

Our understanding of the gas exchange mechanisms in plant organs critically depends on insights in the three-dimensional (3-D) structural arrangement of cells and voids. Using synchrotron radiation x-ray tomography, we obtained for the first time high-contrast 3-D absorption images of in vivo fruit tissues of high moisture content at 1.4-μm resolution and 3-D phase contrast images of cell assemblies at a resolution as low as 0.7 μm, enabling visualization of individual cell morphology, cell walls, and entire void networks that were previously unknown. Intercellular spaces were always clear of water. The apple (Malus domestica) cortex contains considerably larger parenchyma cells and voids than pear (Pyrus communis) parenchyma. Voids in apple often are larger than the surrounding cells and some cells are not connected to void spaces. The main voids in apple stretch hundreds of micrometers but are disconnected. Voids in pear cortex tissue are always smaller than parenchyma cells, but each cell is surrounded by a tight and continuous network of voids, except near brachyssclereid groups. Vascular and dermal tissues were also measured. The visualized network architecture was consistent over different picking dates and shelf life. The differences in void fraction (5.1% for pear cortex and 23.0% for apple cortex) and in gas network architecture helps explain the ability of tissues to facilitate or impede gas exchange. Structural changes and anisotropy of tissues may eventually lead to physiological disorders. A combined tomography and internal gas analysis during growth are needed to make progress on the understanding of void formation in fruit.

NIR Spectroscopy Applications for Internal and External Quality Analysis of Citrus Fruit—A Review

The global citrus industry is continually confronted by new technological challenges to meet the ever-increasing consumer awareness and demand for quality-assured fruit. To face these challenges, recent trend in agribusiness is declining reliance on subjective assessment of quality and increasing adoption of objective, quantitative and non-destructive techniques of quality assessment. Non-destructive instrument-based methods are preferred to destructive techniques because they allow the measurement and analysis of individual fruit, reduce waste and permit repeated measures on the same item over time. A wide range of objective instruments for sensing and measuring the quality attributes of fresh produce have been reported. Among non-destructive quality assessment techniques, near-infrared (NIR) spectroscopy (NIRS) is arguably the most advanced with regard to instrumentation, applications, accessories and chemometric software packages. This paper reviews research progress on NIRS applications in internal and external quality measurement of citrus fruit, including the selection of NIR characteristics for spectra capture, analysis and interpretation. A brief overview on the fundamental theory, history, chemometrics of NIRS including spectral pre-processing methods, model calibration, validation and robustness is included. Finally, future prospects for NIRS-based imaging systems such as multispectral and hyperspectral imaging as well as optical coherence tomography as potential non-destructive techniques for citrus quality assessment are explored.

Optical properties of apple skin and flesh in the wavelength range from 350 to 2200 nm.

Optical measurement of fruit quality is challenging due to the presence of a skin around the fruit flesh and the multiple scattering by the structured tissues. To gain insight in the light-tissue interaction, the optical properties of apple skin and flesh tissue are estimated in the 350-2200 nm range for three cultivars. For this purpose, single integrating sphere measurements are combined with inverse adding-doubling. The observed absorption coefficient spectra are dominated by water in the near infrared and by pigments and chlorophyll in the visible region, whose concentrations are much higher in skin tissue. The scattering coefficient spectra show the monotonic decrease with increasing wavelength typical for biological tissues with skin tissue being approximately three times more scattering than flesh tissue. Comparison to the values from time-resolved spectroscopy reported in literature showed comparable profiles for the optical properties, but overestimation of the absorption coefficient values, due to light losses.

Food process modelling.

Part 1 Principles of modelling: Fundamental approaches: Power and pitfalls of deductive modelling Problem decomposition Kinetic modelling Modelling of heat and mass transfer Combined discrete/continuous modelling. Part 2 Principles of modelling: Empirical approaches: Power and pitfalls of inductive modelling Data mining Modelling and prediction in an uncertain environment. Part 3 Applications: Agricultural production: Yield and quality prediction of vegetables Modelling and management of fruit production Dairy production Beef cattle production. Part 4 Applications: Processing technologies: Use of models in process development: the case of fermentation processes Improving modified atmosphere packaging through conceptual models Modelling thermal processes: cooling and freezing Modelling thermal processes: heating. Part 5 Applications: Safety and quality in the food chain: Modelling food quality Modelling microbiological safety Modelling use of time-temperature indicators in distribution and stock rotation Modelling the management of distribution centres Concepts of chain management and chain optimisation.

Genotype effects on internal gas gradients in apple fruit

A permeation-diffusion-reaction model was applied to study gas exchange of apple fruit (Kanzi, Jonagold, and Braeburn) as effected by morphology and respiratory metabolism. The gas exchange properties and respiration parameters of the fruit organ tissues were measured. The actual internal tissue geometry of the fruit was reconstructed from digital fruit images and the model was solved over this geometry using the finite element method. The model was validated based on measurements of internal gas concentrations and the gas flux of the fruit to its environment. Both measurements and an in silico study revealed that gradients of metabolic gases exist in apple fruit, depending on diffusion properties and respiration of the different cultivars. Macroscale simulation confirmed that Jonagold has large potential for controlled atmosphere (CA) storage while low diffusion properties of cortex tissue in Braeburn indicated a risk of storage disorder development. Kanzi had less O(2) anoxia at CA storage compared with Braeburn.

A continuum model for metabolic gas exchange in pear fruit.

Exchange of O2 and CO2 of plants with their environment is essential for metabolic processes such as photosynthesis and respiration. In some fruits such as pears, which are typically stored under a controlled atmosphere with reduced O2 and increased CO2 levels to extend their commercial storage life, anoxia may occur, eventually leading to physiological disorders. In this manuscript we have developed a mathematical model to predict the internal gas concentrations, including permeation, diffusion, and respiration and fermentation kinetics. Pear fruit has been selected as a case study. The model has been used to perform in silico experiments to evaluate the effect of, for example, fruit size or ambient gas concentration on internal O2 and CO2 levels. The model incorporates the actual shape of the fruit and was solved using fluid dynamics software. Environmental conditions such as temperature and gas composition have a large effect on the internal distribution of oxygen and carbon dioxide in fruit. Also, the fruit size has a considerable effect on local metabolic gas concentrations; hence, depending on the size, local anaerobic conditions may result, which eventually may lead to physiological disorders. The model developed in this manuscript is to our knowledge the most comprehensive model to date to simulate gas exchange in plant tissue. It can be used to evaluate the effect of environmental stresses on fruit via in silico experiments and may lead to commercial applications involving long-term storage of fruit under controlled atmospheres.

Logistic regression analysis of factors influencing core breakdown in 'Conference' pears

Core breakdown of ‘Conference’ pears (Pyrus communis L.) is characterised by softening and browning of tissue near the core and is associated with the development of cavities. The disorder causes large economic losses of ‘Conference’ pears in Belgium, stored under controlled atmospheres. Factors that influence development of the disorder, CO2 and O2 concentration, the size and weight of the pear, the picking date and the storage temperature, were investigated. Multiple logistic regression was used to establish prediction and classification models for both internal browning and cavity development. Over-mature fruit was more susceptible to core breakdown during storage. It was also found that pears with a large weight had a higher probability of developing brownheart. R 2 values from 0.7 to 0.92 were obtained between the predicted and measured percentages of brownheart and cavities. The models classified up to 86% of the pears correctly. In a final analysis, the time sequence of the symptoms occurring during core breakdown disorder development was modelled with a generalized logits model.

Predictive microbiology in a dynamic environment: a system theory approach☆

The main factors influencing the microbial stability of chilled prepared food products for which there is an increased consumer interest-are temperature, pH, and water activity. Unlike the pH and the water activity, the temperature may vary extensively throughout the complete production and distribution chain. The shelf life of this kind of foods is usually limited due to spoilage by common microorganisms, and the increased risk for food pathogens. In predicting the shelf life, mathematical models are a powerful tool to increase the insight in the different subprocesses and their interactions. However, the predictive value of the sigmoidal functions reported in the literature to describe a bacterial growth curve as an explicit function of time is only guaranteed at a constant temperature within the temperature range of microbial growth. As a result, they are less appropriate in optimization studies of a whole production and distribution chain. In this paper a more general modeling approach, inspired by system theory concepts, is presented if for instance time varying temperature profiles are to be taken into account. As a case study, we discuss a recently proposed dynamic model to predict microbial growth and inactivation under time varying temperature conditions from a system theory point of view. Further, the validity of this methodology is illustrated with experimental data of Brochothrix thermosphacta and Lactobacillus plantarum. Finally, we propose some possible refinements of this model inspired by experimental results.

Treatment of missing values for multivariate statistical analysis of gel‐based proteomics data

The presence of missing values in gel‐based proteomics data represents a real challenge if an objective statistical analysis is pursued. Different methods to handle missing values were evaluated and their influence is discussed on the selection of important proteins through multivariate techniques. The evaluated methods consisted of directly dealing with them during the multivariate analysis with the nonlinear estimation by iterative partial least squares (NIPALS) algorithm or imputing them by using either k‐nearest neighbor or Bayesian principal component analysis (BPCA) before carrying out the multivariate analysis. These techniques were applied to data obtained from gels stained with classical postrunning dyes and from DIGE gels. Before applying the multivariate techniques, the normality and homoscedasticity assumptions on which parametric tests are based on were tested in order to perform a sound statistical analysis. From the three tested methods to handle missing values in our datasets, BPCA imputation of missing values showed to be the most consistent method.