Determination of Pear Internal Quality Attributes by Fourier Transform Near Infrared (FT-NIR) Spectroscopy and Multivariate Analysis

This paper attempted the feasibility to determine firmness and soluble solid content (SSC) in intact pears using Fourier transform near infrared (FT-NIR) spectroscopy coupled with multivariate analysis. Principal component analysis and independent component analysis were employed comparatively to extract latent vectors from the original spectra data. Extreme learning machine (ELM) was performed to calibrate regression model. Some parameters of ELM model were optimized according to the lowest root mean square error of cross-validation in the calibration set. Moreover, the root mean square error of prediction of the calibration model was finally corrected for making it more closed to the true prediction error due to the effect of reference measurement error existing in the pear sample attribute value on the prediction error of the model. Experimental results showed that the $ R_p^2 $ and ratio performance deviation (RPD) in the prediction set were achieved as follows: $ R_p^2 $ ?=?0.81 and RPD?=?2.28 for the firmness model when ICs?=?6 and $ R_p^2 $ ?=?0.91 and RPD?=?3.43 for the SSC model when ICs?=?5. This study demonstrates that the predictive precision of the calibration model can be effectively enhanced in measurement of firmness and SSC in intact pears by use of FT-NIR spectroscopy combined with appropriate chemometrics methods.     

Enhancing the applicability of near infrared spectroscopy for estimating specific gravity of green timber from Eucalyptus tereticornis by developing composite calibration using both radial and tangential face of wood

Specific gravity is a very important factor in determining the economics of wood and wood products. This study is aimed to apply the near infrared spectroscopy technique with integrating sphere and fiber optic probe accessories for fast prediction of specific gravity of green timber (moisture content 27–30 %) of Eucalyptus tereticornis from 10 to 12 year old plantation. Specific gravity (basic density) was determined by conventional method (oven dry wt/green volume) and correlated with near infrared spectra using partial least square (PLS) regression. Calibrations using radial face, tangential face and composite face (both radial and tangential) were developed and compared. Coefficient of determination of cross validation ( $ {\text{r}}_{\text{cv}}^{ 2} $ ) for radial-longitudinal, tangential-longitudinal solid strips samples and composite face (both radial and tangential) was between 0.74–0.77 and 0.64–0.77 using integrating sphere and fiber optic probe, respectively. The coefficient of determination of prediction ( $ {\text{r}}_{\text{p}}^{ 2} $ ) was between 0.73–0.85 (with integrating sphere) and 0.69–0.83 (with fiber optic probe). The ratio of performance deviation (RPD) ranges from 2.06 to 2.46 for all models. Root mean square error of prediction (RMSEP) was higher than root mean square error of cross validation (RMSECV). For composite models with radial and tangential face $ {\text{r}}_{\text{cv}}^{ 2} $ / $ {\text{r}}_{\text{p}}^{ 2} $ was 0.74/0.76 using integrating sphere and 0.71/0.83 with fiber optic probe with Quant 2 automatic factors optimization process. The results indicate that the composite model is just as good as the radial and tangential face models and can adequately address the problem where it is difficult to obtain perfect radial or tangential surface, particularly in small girth plantation timber or where surface recognition is difficult.     

Moisture movement in wood polypropylene composites

Moisture movement in an extruded wood polypropylene composite was evaluated by exposure to high humidity and immersion of the material in both fresh and seawater. The saturation moisture content was approximately 20 and 19% when exposed to distilled water and seawater, respectively. The moisture diffusion coefficient (D _m) of thin specimens exposed to high humidity was 3.4?×?10^?8?cm² $ / $ s. The D _m of small cubic specimens with extruded surfaces removed submerged in distilled water and seawater were estimated to be 3.1 and 2.3?×?10^?8?cm² $ / $ s, respectively. Use of these diffusion coefficients overestimates the rate of moisture movement in larger extrusion profiles indicating the role of transport phenomenon other than diffusion.     

Turbidimetric Behavior of Colloidal Particles in Beer Before Filtration Process

The effect of colloidal particles and yeast on turbidity of Pilsen beer before the filtration process was studied in this work. The colloidal particles are mainly composed of polysaccharides, representing 96.89 %, in second place proteins with a concentration close to 2 %, and polyphenols less than 0.3 %. There is also a very low concentration of yeast (<0.25 %). The presence of different types of particles in the sample caused multimodal histogram in the particle size distribution and four distinct zones were identified: (1) very small individual particles ( $ \overline D = 0.0{\text{6}}\mu {\text{m}} $ ), (2) yeast ( $ \overline D = {\text{3}}\mu {\text{m}} $ ), (3) colloidal aggregates ( $ \overline D = {\text{17}}\mu {\text{m}} $ ), and (4) a zone with a high dispersion of size, with two $ \overline D $ values (101 and 200 μm). Particles size counts well correlate with both the scanning electron microscopy (SEM) digital image analysis, and the turbidity determination. The fractal dimension (D _f) of the aggregates was determined by analyzing the SEM images with the Variogram method, obtaining D _f?>?2.4 values. Those values are typical of aggregates formed by rapid flocculation or diffusion limited aggregation. Results of this study support the formulation of a model valid for the prediction of colloidal particles concentration in beer.     

aug-MIA-QSPR study of guanidine derivative sweeteners

The sweetness values relative to sucrose (RS) of a series of sweet-tasting guanidine derivatives have been modeled using augmented multivariate image analysis applied to quantitative structure–property relationship (aug-MIA-QSPR). This QSPR approach is based on 2D molecular shape, as well as atomic sizes and colors to encode chemical, physical and biological properties. A predictive model with r ² = 0.955, q ² = 0.731 and $r_{\text{test}}^{2} = 0.571$ r test 2 = 0.571 was used to estimate log(RS) of two novel sweet-tasting guanidine derivatives, which were built from the combination of substructures of the sweetest derivatives along the series. Given the synergistic effect of different substituents to provide new molecules, promising guanidine sweeteners are proposed for further synthesis.     

Rapid measurement of total acid content (TAC) in vinegar using near infrared spectroscopy based on efficient variables selection algorithm and nonlinear regression tools

Total acid content (TAC) is an important index in assessing vinegar quality. This work attempted to determine TAC in vinegar using near infrared spectroscopy. We systematically studied variable selection and nonlinear regression in calibrating regression models. First, the efficient spectra intervals were selected by synergy interval PLS (Si-PLS); then, two nonlinear regression tools, which were extreme learning machine (ELM) and back propagation artificial neural network (BP-ANN), were attempted. Experiments showed that the model based on ELM and Si-PLS (Si-ELM) was superior to others, and the optimum results were achieved as follows: the root mean square error of prediction (RMSEP) was 0.2486 g/100mL, and the correlation coefficient (R(p)) was 0.9712 in the prediction set. This work demonstrated that the TAC in vinegar could be rapidly measured by NIR spectroscopy and Si-ELM algorithm showed its superiority in model calibration.     

Purification and identification of novel antioxidative peptide released from Black-bone silky fowl (Gallus gallus domesticus Brisson)

Papain-treated Black-bone silky fowl (BSF) muscle hydrolysate was subjected to 6 kDa cutoff membrane ultrafiltration, and the resulting BSF peptides (<6 kDa) were purified by two-step reverse-phase high-performance liquid chromatography. The molecular weight (MW) distribution and amino acid composition were investigated for characterization of the BSF peptides. The results showed that the major amino acids of BSF peptides were Glu, Tyr, Lys, Asp, Leu, Ala, Thr and Pro, and the MW was from 281 to 7,982 Da. BSF peptides exhibited a strong antioxidant capacity. At 10 mg/mL, they displayed more powerful $ {\text{O}}_{2}^{ \cdot - } $ , DPPH^· and ABTS^·+ scavenging activity and reducing power than carnosine. The peptide fraction 8 with more hydrophilicity revealed stronger $ {\text{O}}_{2}^{ \cdot - } $ and ABTS^·+ scavenging activity and reducing power than BSF peptides and carnosine. Besides, a peptide, separated from fraction 8 and showed the strongest antioxidant capacity, was purified and identified by LC-ESI-MS/MS to be Glu-Pro-Asp-Arg-Tyr (678 Da).     

近红外结合Si-ELM检测食醋品质指标

为了提高近红外光谱技术检测食醋中可溶性无盐固形物含量(SSFSC)的精度和稳定性,提出采用联合区间偏最小二乘(Si-PLS)筛选光谱特征区间,再利用极限学习机(ELM)算法建立非线性回归模型,并对该方法的优越性进行系统比较;试验通过交互验证优化模型相关参数,以预测时的相关系数(Rp)和预测均方根误差(RMSEP)作为模型的评价指标。结果表明,Si-PLS结合ELM算法(Si-ELM)所建模型最佳,预测结果:Rp=0.973 9,RMSEP=1.232g/100mL。说明利用近红外光谱技术可以快速准确检测食醋中的SSF-SC,Si-ELM的应用可以适当提高该预测模型的精度。     

Effect of Cleaning Treatment on Adhesion of Streptococcus agalactiae to Milking Machine Surfaces

Streptococcus agalactiae is a common subclinical mastitis agent in dairy cattle. In this study, the influence of hygiene procedure time on the adhesion of S. agalactiae to rubber and silicone surfaces used in milking machines was evaluated. The effect of hygiene practices on the thermodynamic and microscopic features of both surfaces was also evaluated. The hydrophobicity of milking machines and bacterial surfaces was investigated by measuring the contact angle with a goniometer 0, 30, 90, and 180 days after a full hygiene procedure simulated using rubber and silicone coupons. As the time of cleaning procedures enhanced, there was a reduction in the adhesion of S. agalactiae to both surfaces. The rubber and silicone surfaces were hydrophobic in all treatments $ \left( {\Delta G_{\text{sws}}^{\text{TOT}}\; < \;0} \right) $ , while the bacterial surface presented hydrophilic behavior $ \left( {\Delta G_{\text{sws}}^{\text{TOT}}\; > \;0} \right) $ , which makes the adhesion process difficult. Photomicrographs showed rapid wear of both surfaces, pointing to damages caused by cleaning agents. However, the silicone was more resistant to cleaning and sanitizing treatments. Thus, this work shows that changes caused by hygiene procedures in the thermodynamic and in the morphology of milking surfaces have an enormous importance in the S. agalactiae adhesion and, consequently, in mastitis transmission between cattle herd.     

Reduction of Acrylamide Formation in Sweet Bread with l-Asparaginase Treatment

Acrylamide, 2-propenamide, has the chemical formula $ \mathrm{CH}2=\mathrm{CH}-\mathrm{CO}-\mathrm{NH}2 $ . It is produced at elevated levels in high temperature fried and baked foods. It has adverse effects on human health and is proven to be neurotoxic, genotoxic, carcinogenic, and toxic to reproductive system. The aim of this paper was to reduce acrylamide formation in bakery products such as sweet bread by enzyme treatment. l-Asparaginase produced from Cladosporium sp. was treated to wheat-based dough at different concentrations (50–300 U). There was no change in the rheological properties of wheat flour and physico-sensory characteristics of bread with l-asparaginase treatment. Moisture, sugars, l-asparagine, acrylamide, and some indicators of Millard reaction (hydroxymethylfurfural (HMF), color, browning) were estimated. With increase in l-asparaginase level the acrylamide formation was reduced. At 300 U, there was 97 % and 73 % reduction of acrylamide formation in the crust and crumb regions of bread, respectively. HMF, a common intermediate product in the Maillard reaction and a genotoxic compound via 5-sulfoxymethylfurfural, also decreased in l-asparaginase-treated bread samples. These results indicated the potential of l-asparaginase enzyme for industrial and domestic applications in reducing harmful Maillard reaction compounds.     

Physical and mechanical properties of oriented strand lumber made from an Asian bamboo (Dendrocalamus asper Backer)

The study was conducted to determine the physical and mechanical properties as follows: modulus of rupture, modulus of elasticity, internal bond, thickness swelling and water absorption of oriented strand lumber (OSL) made from the Asian bamboo Dendrocalamus asper Backer. Thirty-six lab boards were produced from these bamboo strands with two manufacturing parameters varying, i.e., four resin types (MF, MUPF, PF, and pMDI) and three levels of resin content (7, 10, and 13%). The results indicate that OSL made from bamboo strands exhibits superior strength properties compared to the commercial products made from wood for the building sector. The resin type has a?significant effect on board properties. Moreover, all properties of the board improve generally with increasing resin content. With regard to the internal bond, bamboo-based OSL shows less strength than wood-based boards. The best results were obtained by using 13% pMDI content at 750?kg $ / $ m³ density.     

Colour stabilisation of wood composites using polyethylene glycol and melamine resin

Photo-yellowing of native and polyethylene glycol (PEG) modified wood and wood/melamine resin composites was studied by means of FTIR-ATR technique and colourimetry (CIE L^*a^*b^* method). The discolouration $ \mathrm{\Delta } $ E shows a systematic asymptotic trend towards higher values with increasing irradiation time. Yellowing proceeds faster in natural wood compared to wood/melamine resin composites. Nevertheless, long-term irradiation experiments show that the total colour shift is similar for both. Discolouration is significantly reduced by PEG treatment. In comparison to untreated wood, both glycol and melamine resin mainly reduce the irradiation-induced yellow shift. Moreover, PEG also shows an effect on the redness shift. Both effects result in decreased yellowing of the composite surface. An influence of the molecular weight of PEG was detected.     

Reaction Kinetics of Lysine Loss in a Model Dairy Formulation as Related to the Physical State

Sensitive ingredients of food, pharmaceutical products, or bioproducts can be damaged due to inappropriate processing conditions. The knowledge of the kinetics of degradation reactions allows optimizing production processes with regard to the nutritional quality. The essential amino acid lysine is an important nutrient in dairy powders that can be blocked, e.g., due to the Maillard reaction during drying processes. In this study, we showed that lysine loss can be modeled with pseudo-second-order reaction kinetics. The reaction rate constants increased with increasing temperature. At 90 °C, the highest reaction rate constant was found at a water activity of 0.23. This maximum was shifted to higher water activities for lower temperatures. The temperature dependence of the reaction rate constants could be modeled by the Williams–Landel–Ferry equation in the vicinity of the glass transition temperature and in the rubbery state. The glass transition temperature was calculated with the Gordon and Taylor equation. At higher temperatures and water contents, Arrhenius-type behavior was determined. The activation energy E _A and the pre-exponential factor $ k_0^{*} $ of the Arrhenius equation were expressed as a function of the water content. Thus, it is possible to model lysine loss under conditions that are typical of the production of dairy powders as a function of the temperature, water content, and physical state. The established pseudo-second-order reaction kinetics model can be used to minimize lysine loss during the production of milk powder and to ensure a high nutritional quality.     

Predicting mechanical degradation indicators of silver fir wooden strips using near infrared spectroscopy

The management of ecological engineering structures making up a timber structure requires periodical evaluations, including the level of decay of the constituent parts of the timber structure. Methods exist to measure the level of decay in the laboratory or in the field. However, they are rarely suitable for the conditions of ecological engineering structures, or give partial information. The aim of this study was to predict two mechanical degradation indicators (\(Dw_{MOE}\) and \(Dw_{MOR}\)) of silver fir (Abies alba) wooden strips during microbial decomposition using near-infrared spectroscopy (NIRS). For 1.5 years, the degradation of 180 squared wooden strips, 30 mm wide and 500 mm long, buried in a greenhouse near Grenoble, France (Altitude: 200 m) was monitored. \(Dw_{MOE}\) and \(Dw_{MOR}\) were set from the normalized losses in modulus of elasticity (MOE) and modulus of rupture (MOR), two mechanical properties classically used for timber-structure design. A calibration set of 109 samples was selected to build two separate predictive models of \(Dw_{MOE}\) and \(Dw_{MOR}\) using partial least square regression. The NIR-based models applied to a validation set of 47 samples indicated good prediction performance. The model has a root mean square error of prediction (RMSEP) of 0.15 and a coefficient of determination (\(r^2_p\)) of 0.79. The \(Dw_{MOR}\) model has a RMSEP of 0.13 and a \(r^{2}\)-value of 0.91. These results highlight the considerable potential of NIRS in assessing the extension of decay in wooden logs.     

Application of Mid- and Near-Infrared Spectroscopy for the Control and Chemical Evaluation of Brine Solutions and Traditional Sea Salts

Mid- and near-infrared spectroscopy methodologies were explored for the analysis of brine solutions and traditional sea salt samples. Brine solutions from different salt pans, corresponding to different stages of sodium chloride crystallisation, were collected. A total of 61 dried and non-dried traditional sea salts were also analysed. Partial least squares regression with leave-one-out cross-validation strategy was applied for the calibration of inorganic constituents Ca²⁺, Mg²⁺ and K⁺, alkalinity as HCO ₃ ^? , SO ₄ ^2? , NO ₂ ^? and NO ₃ ^? and phosphate in brine solutions. Promising results were obtained with the near-infrared (NIR) methodology for brine solutions with coefficients of determination R ²?>?0.90 for Mg⁺², K⁺, HCO ₃ ^? and SO ₄ ^2? . Using mid-infrared, the calibration for H₂PO ₄ ^? was R ²?=?0.85. In relation to the sea salt samples, the strategy adopted was the re-sampling based cross-validation using different spectral pre-processing treatments. In this case, the calibrations using the two IR methodologies fell bellow acceptable levels for the techniques; however, by comparing the R ² coefficient, the results were slightly better when using the NIR spectra of dried sea samples. In general, these results open a new possibility for the IR applications and also bring an opportunity for continuing with the NIR characterization for dried sea salt samples.     

Application of Time Series Hyperspectral Imaging (TS-HSI) for Determining Water Distribution Within Beef and Spectral Kinetic Analysis During Dehydration

This study was carried out for rapid and noninvasive determination of water distribution within beef during dehydration using time series hyperspectral imaging (TS-HSI). Hyperspectral images (380–1,700 nm) of beef slices were acquired at different periods of dehydration process. The spectra of beef were extracted from the TS-HSI images using image segmentation process. Principal component analysis was conducted to obtain an overview of the systematic spectral variations during dehydration. Instead of the traditional data mining strategies to cope with the large multivariate data structures in the TS-HSI images, the selection of effective wavelengths was conducted for the first time to reduce the computational burden of the TS-HSI data and predigest calibration modeling. On the basis of the effective wavelengths identified by using successive projections algorithm (SPA), three spectral calibration algorithms of partial least squares regression, least squares support vector machines, and multiple linear regression (MLR) were compared. The SPA-MLR model with Spectral Set I was considered to be the best for determining water content of beef slice. The model led to a coefficient of determination ( $ r_V^2 $ ) of 0.953 and root mean square error estimated by cross-validation of 1.280 %. The visualization of water distribution within beef slice during dehydration was finally generated by transferring the quantitative model to each pixel in the image to determine water content in all spots of the beef sample. Kinetic analysis of the TS-HSI images was also conducted for the first time to analyze spectral changes of beef during dehydration. The results demonstrate that TS-HSI has the potential of quantitatively visualizing water content of beef rapidly and noninvasively during dehydration in a reasonable accuracy.     

Possibilities of organic and conventional wines differentiation on the basis of multivariate analysis of their characteristics (EPR,UV–Vis,HPLC and AAS study)

Proving of affiliation of wine sample to either organic or conventional production system and of its geographical origin although important both for consumer safety and food control authorities is still problematic. Characteristics of Slovak and some European wines obtained by spectroscopic methods including atomic absorption spectroscopy, electron paramagnetic resonance spectroscopy (EPR) and ultraviolet–visible spectroscopy in combination with high-performance liquid chromatography and isotachophoresis processed subsequently by multivariate statistics were successfully used to differentiate Slovak organic and conventional wines according to their affiliation to production system and, at the same time, to differentiate the Slovak organic and conventional wine samples from those, produced in other European countries. From totally 74 determined experimental characteristics, concentration of Fe and Cu, ferric-reducing power values, Trolox-equivalent antioxidant capacity values evaluated from ^·DPPH assay by EPR ( \(\tiny \small \text{TEAC}_{{^{\cdot} \text{DPPH(EPR)}}}\) ), ascorbic acid equivalents (AAE), % of radicals scavenged, concentration of citric acid, catechin and epicatechin, but also color values a* and chromaticity were identified by ANOVA, Tukey’s HSD multiple comparison and stepwise discrimination tests as the most promising characteristics for white wines differentiation, whereas Fe content and AAE for the differentiation of red wines. Recognition and prediction ability tests of the Slovak white organic and conventional wines reached 100 %, whereas in case of red wines, correctness of recognition reached 90.5 % and of the prediction ability, 90 %. High correctness of differentiation of organic and conventional samples according to the origin of wine was obtained, reaching 95.8 % for white wines and 80.7 % for red wines, with two Slovak wines misclassified as wines of Czech origin.     

Mathematical models to predict kinetic behavior and aflatoxin production of Aspergillus flavus under various temperature and water activity conditions

Mathematical models were developed to predict fungal growth and aflatoxin production of Aspergillus flavus. Fungal growth and aflatoxin concentrations were measured. The Baranyi model was fitted to fungal growth and toxin production data to calculate kinetic parameters. Quadratic polynomial and Gaussian models were then fitted to μ_max and LPD (lag phase duration) values. The ranges of temperature and a _w values showing a μ_max value increase were 15–35°C and 0.891–0.984, respectively. LPD was only observed when the temperature was 20–35°C with a _w=0.891?0.972. The μ_{max growth} value increased up to 35°C with \(b_w = 0.2\left( {b_w = \sqrt {1 - a_w } } \right)\) , then values declined. LPD_growth values increased as the b _w value increased. The μ_max value for aflatoxins increased up to 25°C, but decreased after 30°C, indicating that the developed models are useful for describing the kinetic behavior of Aspergillus flavus growth and aflatoxin production.