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.     

Determination of Amino Acid Nitrogen in Soy Sauce Using Near Infrared Spectroscopy Combined with Characteristic Variables Selection and Extreme Learning Machine

Amino acid nitrogen (AAN) is one of the most important indicators to assess the quality grade of soy sauce in China. Near infrared (NIR) spectroscopy technique combined with characteristic variable selection and extreme learning machine (ELM) was applied to detect AAN content in soy sauce in this work. First, the optimal spectral intervals were selected by synergy interval partial least square. Then, ELM model based on the optimal spectral intervals was established, called synergy interval extreme learning machine (Si-ELM) model. Support vector machine model based on the optimal intervals was established comparatively. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient ( $ R_{\text{p}}^2 $ ) and root mean square error of prediction (RMSEP) in prediction set. Si-ELM showed excellent performance. The best Si-ELM model was achieved with $ R_{\text{p}}^2 = 0.9657 $ and RMSEP?=?0.0371 in the prediction set. It was concluded that NIR spectroscopy combined with Si-ELM was an appropriate method to detect AAN content in soy sauce.     

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.     

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.     

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).     

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.     

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.     

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.     

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.     

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.     

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.     

Rapid and Simple Determination of Sarafloxacin in Egg by Time-Resolved Chemiluminescence

A new chemiluminescence method for the determination of the fluoroquinolone sarafloxacin is described. The method is based on the measurement of the chemiluminescent (CL) radiation emitted in the reaction of sarafloxacin with Ce (IV) in sulfuric acid medium and in the presence of $ \mathrm{Ru}(\mathrm{bipy})_3^{2+ } $ as sensitizer. Since the method allows the recording of the whole CL intensity-versus-time profile, the use of measurement parameters such as the maximum CL emission is possible, which is proportional to the analyte concentration. The optimum chemical and experimental conditions for the CL emission of the reaction were researched. The calibration graph was lineal in the concentration range from 5.0 to 30.0 mg?L^?1 of sarafloxacin. The limit of detection, according to Clayton et al. (Anal Chem 59:2506–2514, 1987), was 1.17 mg?L^?1. After analyzing a series of ten solutions of 10.0 mg?L^?1 of sarafloxacin, the estimated average concentration was 10.30 mg?L^?1 with a standard deviation of 0.42 mg?L^?1 (confidence level, 95 %). The effect on the sarafloxacin CL signal of some common excipients (sucrose, lactose, and starch) used widely in pharmaceutical preparations was also tested, as well as that of others fluoroquinolones (namely, enrofloxacin and ciprofloxacin). Finally, the proposed method was applied to the determination of sarafloxacin in different spiked egg samples by using the standard addition methodology, obtaining excellent recoveries in all cases (close to 100 %).     

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.     

Freezing Characteristics and Storage Stability of Broccoli (Brassica oleracea L. var. botrytis L.) Under Osmodehydrofreezing and Ultrasound-Assisted Osmodehydrofreezing Treatments

Freezing characteristics (freezing time, latent heat of fusion of ice, and freezable water content) and quality parameters (drip loss, color, firmness, and l-ascorbic acid content) of broccoli (osmodehydrofrozen and ultrasound-assisted osmodehydrofrozen) during frozen storage were investigated. Freezing time, latent heat of fusion of ice, and freezable water content of osmodehydrated samples decreased significantly compared to samples which were not under osmotic dehydration. The changes of drip loss, color, firmness, and l-ascorbic acid content of osmodehydrofrozen and ultrasound-assisted osmodehydrofrozen broccoli during frozen storage were inhibited markedly compared to samples which were not submitted to osmotic dehydration before freezing. Compared to osmotic dehydration, the ultrasound-assisted osmotic dehydration shortened the needed dehydration time and better preserved the firmness and l-ascorbic acid content after osmotic dehydration pretreatment. In addition, the ultrasound-assisted osmotic dehydration minimized the drip loss and loss of l-ascorbic acid content and better maintained the color and firmness when stored at ?25 °C for 6 months. These findings indicate that it is promising to apply ultrasound-assisted osmodehydrofreezing in freezing and frozen storage of food.     

Optimizing Conditions for TEMPO/NaOCl-Mediated Chemoselective Oxidation of Primary Alcohols in Sweet Potato Residue

Sweet potato residue (SPR), a by-product of the sweet potato-based beverage industry, contains health-beneficial dietary fiber, but it has been limited to secondary-use applications due to poor water solubility. The water solubility of polysaccharides in SPR increases following chemoselective oxidation of the primary alcohol group through 2,2,6,6-tetramethyl-1-piperidinyl oxoammonium ion (TEMPO)/sodium hypochlorite (NaOCl)-mediated oxidation. In the present study, a central composite experimental design was used to optimize conditions for chemoselective oxidation of SPR with three variables, including TEMPO concentration (0.05–0.25 mmol, X ₁), NaOCl concentration (4.0–12.0 mmol, X ₂), and pH of the reactants (9.5–11.5, X ₃). The quadratic polynomial model equation describing this relationship was as follows: $ {\text{degree of oxidation}}\left( \% \right) = - {871}.{929} + {975}.{4}0{5}{X_{{1}}} + {2}0.{7181}{X_{{2}}} + {143}.{358}{X_{{3}}}-{12}0.{682}X_1^2-0.{59}0{426}X_2^2-{5}.{78182}X_3^2-{7}.{725}00{X_{{1}}}{X_{{2}}}-{76}.{4}000{X_{{1}}}{X_{{3}}}-0.{55}0000{X_{{2}}}{X_{{3}}}\left( {{R^{{2}}} = 0.{9633}} \right) $ . The maximum degree of oxidation (98.3%) was consistent with the expected value (100%) and was obtained from a TEMPO concentration, NaOCl concentration, and reactant pH of 0.1980 mmol, 9.6236 mmol, and 10.6271, respectively. The introduction of a C6 carboxyl group without oxidation of the secondary alcohols was confirmed by ¹³C nuclear magnetic resonance and Fourier transform infrared spectroscopy. The water solubility of the oxidized products was 99.95%, whereas that of native SPR was <26.45%. The initial velocity of the oxidation showed a strong linear relationship (R ²?=?0.9239) with the degree of oxidation, indicating that initial velocity could be another quantitative index for determining the degree of oxidation and productivity of oxidized SPR. These results suggest that oxidized SPR could be used as a new water-soluble dietary fiber in the food industry.     

Chemometric Models for the Quantitative Descriptive Sensory Properties of Green Tea (<Emphasis Type="Italic">Camellia sinensis</Emphasis> L.) Using Fourier Transform Near Infrared (FT-NIR) Spectroscopy

Multivariable models based on chemometric analyses of the tea infusion sensory data and FT-NIR spectra of 70 “Biluochun” green tea (Camellia sinensis L.) samples were generated aiming to predict the scores of sensory attributes of green tea. Modified BP_AdaBoost algorithm was used to develop the models. The synergy interval partial least square (siPLS) algorithm was applied to select the wavenumbers for the prediction model of sensory properties in order to take only significant spectral intervals into account. Some parameters were optimized by cross-validation in model calibrations. Experimental results showed that the optimal BP_AdaBoost model was achieved with four principal components (PCs), when 184 variables in the combination of four spectral intervals [3 17 19 21] were selected by siPLS. The predicted precision of the best model obtained were as follows: the root mean square error of cross-validation (RMSECV) was 5.0305 and the correlation coefficient (R _c) was 0.8554 in the calibration set; the root mean square error of prediction (RMSEP) was 6.0807, the correlation coefficient (R _p) was 0.7717, and the ratio performance deviation (RPD) was 1.59 in the prediction set. Finally, the BP_AdaBoost model revealed its superior performance when compared with back propagation neural network (BPNN) model. The overall results demonstrate that FT-NIR spectroscopy technique can be successfully used in the evaluation of sensory quality of green tea, and BP_AdaBoost algorithm shows its superiority in model calibration.