Prediction of Rice Starch Quality Parameters by Near-Infrared Reflectance Spectroscopy

ABSTRACT: A rapid predictive method based on near-infrared spectroscopy (NIR), was developed to measure rice starch quality parameters. A calibration set of 100 samples and validation set of 62 samples of rice flour of Chinese genotypes was used. Results of partial least squares modeling indicated that NIR was reasonably accurate in predicting apparent amylose content (AAC) (standard error of prediction [SEP] = 1.39 percentage units, coefficient of determination [R²] = 0.91); pasting parameters of setback (SB) (SEP = 13.6 RVU, R²= 0.92), and breakdown (BD) (SEP = 10.2 RVU, R²= 0.88); and gelatinization peak temperature (T_p) (SEP = 1.33 °C, R²= 0.89). Gel consistency (GC), cool paste viscosity (CPV), gelatinization onset temperature (T_o), and textural properties of chewiness, hardness and gumminess, were modeled less well with R2 between 0.75 and 0.86. NIR analysis is sufficiently accurate for routine screening of large numbers of samples in early generation selection in rice breeding programs.     

A Rapid FTIR Spectroscopic Method for Estimation of Caffeine in Soft Drinks and Total Methylxanthines in Tea and Coffee

ABSTRACT: A rapid Fourier Transform infrared (FTIR) spectroscopic method was developed to estimate caffeine in a variety of soft drinks and total methylxanthine content in tea and coffee using a single calibration model. FTIR spectrum of pure caffeine was characterized, and the 2 spectral regions of 1500 to 1800 cm^-1 and 2800 to 3000 cm^-1 were used for quantitative estimation using Partial least square (PLS) and principal component regression (PCR). FTIR spectroscopy with chemometrics using the PLS-First derivative spectra could predict the caffeine content accurately up to an R² value greater than 0.99 and a standard error of prediction (SEP) of less than 3.2 with 5 factors in the model.     

Nondestructive Prediction of Moisture and Sodium Chloride in Cold Smoked Atlantic Salmon (Salmo salar)

ABSTRACT: Salt and moisture contents in cold-smoked salmon were determined using short-wavelength near-infrared (SW-NIR) reflectance spectroscopy (600 to 1100 nm). Partial least square (PLS) regression models yielded the best results among 3 linear regression methods tested. Back-propagation neural networks (BPNN) exhibited a somewhat better capability to model salt and moisture concentrations (Salt: R²= 0.824, RMS = 0.55; Moisture: R²= 0.946, RMS = 2.44) than PLS (Salt: R²= 0.775, RMS = 0.63; Moisture: R²= 0.936, RMS = 2.65). Selection of samples from different axial locations on a fish did not affect the prediction error for salt or WPS but affected the prediction error for moisture.     

Detection of sublethal thermal injury in Salmonella enterica serotype typhimurium and Listeria monocytogenes using Fourier transform infrared (FT-IR) spectroscopy (4000 to 600 cm(-1))

ABSTRACT:  Fourier transform infrared (FT-IR) spectroscopy (4000 to 600 cm⁻¹) was utilized to detect sublethally heat-injured microorganisms: Salmonella enterica serotype Typhimurium ATCC 14028, a Gram-negative bacterium, and Listeria monocytogenes ATCC 19113, a Gram-positive bacterium. A range of heat treatments ( N = 2) at 60 °C were evaluated: 0 D (control), 2 D , 4 D , 6 D , and 8 D using a D _{60 °C} ( S . enterica serotype Typhimurium ATCC 14028 = 0.30 min, L . monocytogenes ATCC 19113 = 0.43 min). The mechanism of cell injury appeared to be different for Gram-negative and Gram-positive microbes as observed from differences in the 2nd derivative transformations and loadings plot of bacterial spectra following heat treatment. The loadings for PC1 and PC2 confirmed that the amide I and amide II bands were the major contribution to spectral variation, with relatively small contributions from C-H deformations, the antisymmetric P==O stretching modes of the phosphodiester nucleic acid backbone, and the C-O-C stretching modes of polysaccharides. Using soft independent modeling of class analogy (SIMCA), the extent of injury could be predicted correctly at least 83% of the time. Partial least squares (PLS) calibration analysis was constructed using 5 latent variables for predicting the bacterial counts for survivors of the different heat treatments and yielded a high correlation coefficient ( R = 0.97 [ S . enterica serotype Typhimurium] and 0.98 [ L. monocytogenes ]) and a standard error of prediction ( SEP = 0.51 [ S . enterica serotype Typhimurium] and 0.39 log₁₀ CFU/mL [ L. monocytogenes ]), indicating that the degree of heat injury could be predicted.     

Modeling the Growth Rate of Listeria Monocytogenes Using Absorbance Measurements and Calibration Curves

ABSTRACT:  The influence of environmental conditions (temperature and pH) on the relationship between growth data expressed by absorbance (ABS) and data transformed to cell count (CC) measurements was studied, using calibration curves for predicting Listeria monocytogenes growth rate. With this aim, 19 calibration curves at different stress conditions were performed. A shift in the calibration curves was observed for the most stringent conditions, which affected cell viability. Subsequently, a Baranyi model was fitted to ABS and CC data to obtain growth rate (GR_ABS and GR_CC) and a linear regression was performed. Absorbance was found to be a reliable technique for measuring microbial growth, as a strong relationship between GR_ABS and GR_CC (R²= 0.9717) was observed. Furthermore, 2 different response surface models were developed to link GR_ABS and GR_CC data with temperature, citric acid, and ascorbic acid. The goodness of fit of both ABS and CC models to the data was observed (RMSE = 0.0223 and 0.0221; SEP [%]= 29 and 25, respectively). Mathematical validation was carried out by calculating bias and accuracy factors, providing reasonably acceptable values for both absorbance and cell count models (B_f= 1.11 and 1.09, A_f= 1.44 and 1.41, respectively). Predictions for GR_CC were compared to data taken from Growth Predictor software at different temperatures and pH. Response surface model predictions showed that a suitable combination of preservative factors can inhibit L. monocytogenes growth. These results highlight accurate predictions of growth parameters of L. monocytogenes .     

THE PSYCHOPHYSICS OF POURING, SPREADING AND IN-MOUTH VISCOSITY

The sensory viscosity of low calorie viscoelastic syrups in the mouth, while pouring out of a bottle, and spreading over a flat surface was satisfactorily estimated from the fundamental physical properties of these fluids. Appropriate sensory perception mechanisms were identified and linked to the operating conditions of each sensory test through psychophysical models. Oral sensory viscosity correlated with the shear stress in the mouth (R²= 0.96) (Kokini et al. 1977); pouring sensory viscosity correlated with the cross sectional area filled by the fluid at the neck of the bottle (R²= 0.86); and spreading sensory viscosity correlated inversely with the radial growth of the spreading fluid puddle (R²= 0.96).     

Effect of Postharvest Treatments on Amaranthus Betacyanin Degradation Evaluated by Visible/Near-Infrared Spectroscopy

ABSTRACT: A visible/near-infrared spectrophotometric method was developed for betacyanin and moisture content in Amaranthus samples. A standard error of prediction (SEP) of 0.25 mg/g for betacyanins ( r ²= 0.97) and 2.18% for moisture ( r ²= 0.99) was obtained on the validation sample set. Effect of 5 postharvest treatments on betacyanin degradation was assessed. Freeze-drying and -18°C frozen storage gave over 97% pigment retention, compared to natural air (52.8%), solar drying (63.5%), air oven drying (61.9 to 83.1%), and 14°C storage (78.3%). Air-drying gave the lowest degradation rate and longest half-life among the solar and oven-drying treatments for 8 h. Dried samples showed good pigment stability with 28.6 mo half-life at 25°C.     

Correlation between Cheese Meltability Determined with a Computer Vision Method and with Arnott and Schreiber Tests

ABSTRACT: Meltability of different brands of Cheddar and Mozzarella cheeses was determined with a novel computer vision method as well as with 2 traditional methods, that is, the Arnott and Schreiber tests. Correlation between the results of these methods was analysed and it showed that the meltability determined with a computer vision system was significantly (P < 0.0001) interrelated with the Arnott (R²= 0.69) and Schreiber (R²= 0.88) meltabilities. The computer vision method provided an accurate quantitative account of the physical changes in cheese during melting, and thus was capable of revealing meltability differences of cheese that were difficult to distinguish by the traditional methods. The new approach was also applicable to a wide range of cheeses.     

基于可见-近红外漫反射光谱技术的葡萄贮藏期间可溶性固形物定量预测

利用可见-近红外漫反射光谱技术,建立不同品种葡萄贮藏期间可溶性固形物含量定量预测的通用模型。以10 ℃贮藏的玫瑰香葡萄、马奶葡萄、红提葡萄的混合光谱为定标材料,探讨不同化学计量学建模方法、不同光谱预处理方法、间隔点、平滑数以及不同特征波长区间选择对建模效果的影响及模型的品种适用性。结果显示,采用改进偏最小二乘法,16 点平滑,间隔点数16 点,结合二阶导数、去散射的处理方法,在波长范围408～1 092.8 nm内建立的模型效果最优,其交互验证误差和交互验证判定系数R2CV分别为0.308 7、0.980 2。由3 种葡萄混合组成的预测集对模型进行评价,预测标准差0.354、预测判定系数Rp2为0.980 8、验证相对分析误差为6.22、预测残差平方和为7.993。模型对单一品种预测Rp2均达到0.94以上。因此,葡萄果实可溶性固形物含量的近红外预测模型具有可行性,可同时适用于多种葡萄品种。     

Piezoelectric Flow Injection Analysis Biosensor for the Detection of Salmonella Typhimurium

ABSTRACT: Piezoelectric biosensors have the potential to provide direct detection of food contaminants, such as pathogens. In this study, Protein A antibody immobilization was used for the activation of the piezoelectric biosensor to detect Salmonella typhimurium. The overall system consisted of a new design for a flow cell and flow injection analysis system. The flow cell made possible a baseline stability of ± 1 Hz out of 5 MHz for hours. The sensor had responses of 5 to 65 Hz in 30 min with R²= 0.95 for S. typhimurium concentrations of 10⁷to 10⁹ CFU/ml under continuous flow, and 3 to 75 Hz in 40 min with R²= 0.96 for S. typhimurium concentrations of 10⁶ to 10¹⁰ CFU/ ml under stop flow. Cross-reactivity tests were performed with nonpathogenic Escherichia coli, Escherichia coli O157:H7, Listeria monocytogenes , and Vibrio parahaemolyticus and showed less than 10% response.     

Determination of cholesterol in dairy products using infrared techniques: 1. FTIR spectroscopy

A Fourier transformed infrared (FTIR) spectroscopic method is described to estimate cholesterol after a single step extraction instead of the conventional colorimetric method. FTIR spectrum of pure cholesterol was characterized and the region between 2800 and 3200 cm⁻¹ was used for quantitative estimation. Partial least square (PLS) and principal component regression (PCR) analysis were used for quantitative analysis. FTIR spectroscopy with chemometrics could predict the cholesterol content accurate to an r ² greater than 0.99 and a standard error of prediction (SEP) of less than 0.98. The developed model was successfully applied to predict cholesterol in commercial dairy products and validated with standard method and recovery studies. Results indicate that FTIR spectroscopy can determine the cholesterol content in dairy products in approximately 5 min.     

EFFECT OF ULTIMATE pH ON THE QUALITY CHARACTERISTICS OF PORK

A study was conducted to characterize the relationship between Longissimus thoracis ultimate pH(LTpH) and pork quality. Animals (n = 47) were selected based on LTpH measured at 24 h postmortem. Data were analyzed using regression procedures with ultimate pH as the independent variable, and relationships were determined to be linear (L), quadratic (Ql or cubic (C). Ultimate pH explained 79% (C) of the variation in subjective color, which increased as pH increased. Drip loss, purge loss and L* value decreased as LTpH increased (R²= 0.57C, 0.77 Q and 0.68 Q, respectively). Shear force decreased and sensory juiciness increased as LTpH increased (R²= 0.26Q and 0.46C, respectively). However, of flavor intensity increased as LTpH fell below pH 5.2 or exceeded 6.1(R²=0.52C). Increasing LTpH, up to a point, will improve fresh pork quality and processed meat properties, whereas, above approximately 6.1, of-flavor may increase.     

High-performance liquid chromatographic determination of arbutin in skin-whitening creams and medicinal plant extracts

A high-performance liquid chromatographic method was developed for quantitative analysis of arbutin. The arbutin was separated on an ODS Hypersil^® C18 column with a mobile phase of water: methanol: 0.1 M hydrochloric acid (89:10:1, v/v/v). The level of arbutin was measured by means of UV detection at 222 nm. The optimum conditions for arbutin quantitative analysis were investigated. The calibration curve was found to be linear up to 1000 μg/ml^-1 of arbutin concentration, and the working calibration curve for arbutin determination over the range 0.5–30.0 μg/ml^-1 of arbutin ( r ² = 0.9999) was established. The relative standard deviations for intraday and interday were found to be 0.98% and 1.15%, respectively. A detection limit (3σ) and quantitation limit (10σ) of 0.02 μg/ml^-1 and 0.2 μg/ml^-1, respectively, and a mean percentage recovery of the spiked arbutin of 99.88 ± 1.12% were obtained. The proposed method has been applied to the determination of arbutin in commercial skin-whitening creams (Arbuwhite^® cream, Super Whitening^® cream, and Shiseido^® cream) with average contents of 7.60, 5.30, and 57.90 mg/g^-1, respectively. It was also applied to the determination of arbutin in medicinal plant extracts from Betula alnoides Buch. Ham., Clerodendrum petasites S. Moore, Curculigo latifolia Dryand. Var. latifolia, and Hesperethusa crenulata (Roxb.) Roem, levels of which were found to be 3.50, 1.50, 1.10, and 0.12 μg/g^-1, respectively (no article reported in the literature about arbutin analysis). The proposed HPLC method is rapid, simple, and selective for routine analysis.     

基于中波近红外光谱构建生鲜鸡肉胆固醇定量分析模型

通过采集市售生鲜鸡肉样品在中波近红外区的光谱信息,采用偏最小二乘法构建胆固醇定量分析模型,并评价模型的预测准确性。在建模过程中,讨论异常样品剔除与组合预处理方法等优化措施对模型的影响。参模样品经2 次异常样本剔除并以SG（Savitzky-Golay）一阶导数、SG平滑及去趋势校正进行预处理后,获得了最佳生鲜鸡肉胆固醇定量分析模型,其中：校正标准差（standard error of calibration,SEC）为4.534 8、校正集相关系数为0.919 7、预测标准差（standard error of prediction,SEP）为7.437 5、验证集相关系数为0.812 0、范围误差比为2.844 7、相对预测标准差为9.44%、主因子数为5、SEP/SEC为1.640 1。对检验集样品预测的结果表明,基于中波近红外光谱构建的胆固醇定量分析模型的预测性能较好（P＞0.05）,特别是在60～100 mg/100 g含量区间,可应用于对市售生鲜鸡肉及产品胆固醇的检测。     

Using near infrared spectroscopy for the determination of total solids and protein content in cheese curd

In-line or on-line monitoring requires fast and reliable methods for determining composition or processing variables. A near infrared spectroscopic method for the determination of solids and protein content in cheese curd has been developed. Based on approximately 250 curd samples, calibration models were built using partial least squares regression. The calibration models resulted in coefficients of determination of R² = 0.994 for total solids and R² = 0.985 for protein content for unhomogenized curd, which improved only slightly after subjecting the curd to homogenization. As confirmed by results that were obtained from a validation set, this suggests that near infrared spectroscopy is a potential and powerful method for the rapid monitoring of curd composition.     

Rapid Fruit Extracts Antioxidant Capacity Determination by Fourier Transform Infrared Spectroscopy

ABSTRACT: The antioxidant content of fruits have made them a desirable component of the human diet. Several wet chemistry techniques, including the oxygen radical absorbance capacity (ORAC_FL) assay, have been reported for measuring the antioxidant activities of fruit. In this study, we investigated the use of Fourier transform infrared spectroscopy (FTIR) to measure fruit antioxidant activity. Flavonoid-rich extracts from 5 blueberry, 5 grape, and 6 blackberry genotypes were obtained by methanol-water-formic acid (60:37:3, v/v/v) solvent. The total antioxidant capacities of the fruit extracts were determined by the ORAC_FL assay, and the FTIR spectra of the fruit extracts were collected. Partial least squares (PLS) regressions with cross-validation was conducted on 128 spectra of extracts and their corresponding ORAC_FL values to obtain a calibration model for predicting the antioxidant activity of the extracts. Spectra from an additional 16 extracts were used as an external validation set for the model. A good calibration model ( R ²= 0.97) for antioxidant activity was obtained with satisfactory predictive ability (root mean standard error [RMSE] = 5.35) using the spectral region 2000/cm to 900/cm. Cross-validation procedures indicated good correlations ( R ²= 0.94) between ORAC_FL assay values and FTIR estimates. The ratio of the standard deviation of the data to the standard error of validation (RPD) values were above 5.0 for blueberry, grapes, and the combined extracts in the external validation set indicating that the calibration model was suitable for quantifying fruit extracts antioxidant activities. This study shows that an FTIR technique would be suitable for rapidly measuring fruit extract antioxidant activity.     

Determination of chloride, nitrate and calcium ions in sugar with ion selective-electrodes

Chloride, nitrate, and calcium ion-selective electrodes were tested and found satisfactory for the determination of the corresponding ions in highly refined white sugar, molasses and other impure sugar samples at different stages of sugar manufacturing or refining. The interferences by Br⁻ and I⁻ ions in Cl⁻ determination were eliminated by oxidation with 3 M HNO₃ and passing air to remove the free Br₂ and I₂ formed. The Cl⁻ concentration was then determined with a chloride-selective electrode against a calibration curve. Chloride should not be determined by ashing sugar, since this causes high losses of Cl⁻. It was found that NO₃⁻ and free Ca²⁺ ions could be determined directly in the sugar solution against corresponding calibration curves. Total calcium was determined after ashing of sugar samples. The ash was dissolved in 0.1 M HCl and passed through an anion exchange resin to remove PO³⁻₄ and SiO₂₋₃ ions, and Ca²⁺ was determined as before. Bound calcium was obtained by subtracting values of free from total calcium. Determination of bound calcium was useful to monitor the process of liming. For comparison, the three ions were also determined with acceptable precision without removing interfering ions using the method of standard addition and Gran's plot. The errors of determination for both direct and standard addition techniques were 3% for Cl⁻ and NO⁻₃ and 1–5% for Ca²⁺.     

MODELING THERMAL SOFTENING KINETICS OF POTATOES USING FRACTIONAL CONVERSION OF RHEOLOGICAL PARAMETERS

Texture degradation in potatoes was investigated during heating of cylindrical test samples, 15 mm diameter and 30 mm long, in water at 60, 70, 80 and 90C by mechanical testing. The rheological parameters obtained from the axial and radial compression, creep and stress relaxation tests decreased exponentially with an increase in heating duration and temperature approaching steady levels corresponding to the remaining texture after prolonged heating. A single first-order kinetic model described the changes in various rheological parameters due to thermal softening of potatoes using fractional conversion technique indicating very high values of the coefficient of determination (R² > 0.97). In general, the visco-elastic test parameters were relatively more sensitive to texture degradation in potatoes in comparison with the quasi-static test parameters. Overall comparison showed that elasticity and viscosity parameters in Kelvin component of the 4-element model (E₂ and η₂) from creep tests and elasticity moduli from axial and radial compression tests (E_a and E_r) best presented the texture degradation kinetics in potatoes with R² ranging from 0.98 to 0.99.     

Rheological Characterization of Rice Flour-Based Batters

ABSTRACT: The flow behavior and the applicability of rheological models to predict the viscosity of rice flour-based batter (RFBB) for deep-fat frying at 5,15, and 25 °C were investigated. The Herschel-Bulkley model was found to be the best fit for all RFBBs formulated with different ratios of rice to corn flour, oxidized corn starch, and methylcellulose (R²= 0.85–0.99). Rheological parameters depended on RFBB compositions, temperature, and shear rate. The relationship between temperature and RFBB apparent viscosity can be predicted within shear rate range between 30 to 132 s⁻¹. Correlation coefficient (r) of model validation decreased as temperature increased.     

Degree of correlation between total light interception and whole-canopy net CO2 exchange rate in two grapevine growth systems

This paper shows the degree of precision by which measurement of total canopy light interception (TCLI) can estimate whole-canopy net CO₂ exchange rate (NCER). The test vines comprised a single 35° NE-SW oriented hedgerow, with vertically shoot positioned grapevine canopies at either a low shoot density (10 shoots/metre of row) or a high shoot density (20 shoots/metre of row). TCLI was measured on different dates and at various times on each date (during the 2001 growing season) by a multiple line sensor equipped with 64 phototransistors (35 mm spacing). Each sensor had a spectral sensitivity in the 300–1100 nm waveband and the line of sensors was moved horizontally in steps of 10 cm. Whole-canopy NCER was recorded over successive clear days using an enclosure method. TCLI and canopy NCER were highly correlated on a seasonal basis for both the low shoot density treatment ( R²= 0.97) and the high shoot density treatment ( R²= 0.94). The correlation became less precise ( R²= 0.80 and 0.79 for low and high, respectively), when data taken at various times of day were treated separately. Canopy NCER derived from single TCLI readings taken at solar noon tended to be under-estimated, while NCER derived from single TCLI readings taken later in the afternoon tended to be over-estimated. Nevertheless, for a given training system, our method was sufficiently precise to predict seasonal increase of canopy NCER as well as the total leaf area at which NCER approached a maximum thus setting a value above which additional leaf area resulted in mutual shading without enhancing carbon assimilation.