Empirical models to correlate the basic physical and chemical indices of modified rice bran and mustard oil

Modified rice bran oil (RBO) and modified mustard oil (MO) were prepared by adding oleic acid and oxidized oil separately. The physical and chemical indices like dielectric constant, viscosity, peroxide value (PV), acid value (AV), free fatty acids (FFA), iodine value (IV), and saponification value (SV) of pure and modified RO and MO were determined and correlated. Dielectric constant and viscosity were found to decrease in a non-linear fashion with increase in temperature (30°C–75°C). The dependence of dielectric constant and viscosity with temperature was investigated using model empirical equations. The dielectric variation was studied using Akerlof and Oshry’s model equations, which exhibited high dependency of R² ranges from 0.99 to 0.997. The behaviour of viscosity with temperature was studied with Wright’s equation and the correlation coefficient (R²) was found to be 0.998. Model equations were developed, which relates dielectric constant with IV, SV, and PV with the regression coefficients R² = 0.955, 0.936, and 0.994, respectively. The developed equations can be used in processing, pipelining, and to predict the parameters at a desired temperature. On comparing the correlations between the physical and chemical properties of the oil samples, RBO and its modified forms exhibited more oxidative stability than modified MO.     

Dielectric Properties of Sweet Potato Purees at 915 MHz as Affected by Temperature and Chemical Composition∗

A process for rapid sterilization and aseptic packaging of sweet potato puree using a continuous flow microwave system operating at 915 MHz has been successfully developed. In microwave processing, dielectric properties have a major role in determining the interaction between purees and the electromagnetic energy. The objective of this research was to determine how dielectric properties are affected by temperature and chemical composition of purees derived from thirteen sweet potato cultivars with varying flesh colors. Results indicated that temperature, moisture, sugar and starch content had a pronounced effect (p < 0.001) on dielectric properties measured from 15°C to 145°C at 915 MHz. Dielectric constant decreased with increasing temperature, while dielectric loss factor increased quadratically. Power penetration depth of all cultivars decreased with increasing temperature. Predictive equations were developed for dielectric constant (R²?=?0.82) and dielectric loss factor (R²?=?0.90) as a function of temperature, moisture, sugar, and starch. The predictive equations would be useful in determining the dielectric properties of sweet potato purees for the microwave processing technology.     

Modular Feed Forward Networks to Predict Sugar Diffusivity from Date Pulp Part I. Model Validation

In Tunisia, some 15,000 tons of fructose could be produced annually from second quality dates presently being left to rot. Extraction is the first step in producing sugar from these dates, and sugar diffusivity from the date paste governs the process. The objective of this project was therefore to measure in the laboratory, the sugar diffusivity of three date varieties (Manakher, Lemsi, and Alligue) under three different temperatures (50, 65 and 80°C), and from this data, develop an artificial neural network (ANN) model to predict sugar extraction. For each date variety, the laboratory procedure consisted of soaking a layer of date paste in water at one of the three temperatures and observing water sugar concentration at 20 mm from the date layer, every 15 min over a period of 240 min. This experimental data was then used to develop the ANN model, where several configurations were evaluated. Date sugar concentration with time was found to be significantly influenced by temperature and variety. The Lemsi variety allowed for the highest sugar extraction of 75% at 80°C. The optimal ANN model was found to be a network with two hidden layers and seven neurones in both the upper and lower levels of each hidden layers. This optimal model was capable of predicting sugar diffusivity from the different date varieties with a mean square error of 0.0037 and an 8.0% Error. The results show very good agreement between the predicted and the desired values of sugar diffusivity (R² = 0.98). The coefficient of determination was also very good (R² > 0.95), due to a small prediction error.     

Hydration properties and proton exchange in aqueous sugar solutions studied by time domain nuclear magnetic resonance

Proton NMR relaxation rates (R₁ and R₂) were measured in aqueous solutions of sucrose, d-glucose and d-fructose with increasing concentration. The measurements were carried out using Bruker PC 20 NMR Process Analyzer. Inversion recovery and CPMG pulse sequences are used for the measurement of relaxation rates. Results show that the values of relaxation rate increase as the concentration of the sugar is increased. The relaxation rate appears to be higher for sucrose solutions as compared to glucose or d-fructose solutions. These results were discussed on the basis of molecular association between sugar and water molecules through hydrogen bonding. The water self diffusion coefficient was measured in these sugar solutions by using pulse field gradient NMR method. As expected, the water self-diffusion coefficient was reduced with increased sugar concentrations. The results of translational mobility exhibited a higher mobility for fructose than glucose or sucrose in aqueous solutions.     

Rapid detection and quantification of soya bean oil and common sugar in bovine milk using attenuated total reflectance–fourier transform infrared spectroscopy

Attenuated total reflectance–Fourier transform infrared spectroscopy, along with chemometrics, were used to detect and quantify soya bean oil (SO) and sugar (CS) adulteration in milk. Bovine milk was artificially adulterated with SO (0.2–2.0%; v/v) and CS (1–10%; w/v) separately. Spectra revealed significant differences in specific wavenumber regions (SO: 1450–1250 cm^?1; CS: 1200–900 cm^?1). Soya bean oil adulteration was best predicted in wavenumber range of 1262–1164 cm^?1, using partial least square regression (coefficient of determination (R²: 0.90 and 0.88 for calibration and validation, respectively). Common sugar adulteration was best predicted in wavenumber range of 1010–910 cm^?1 (R²: 0.99 for calibration and validation) using partial least square.     

Preliminary investigation on the relationship of Raman spectra of sheep meat with shear force and cooking loss

A prototype handheld Raman system was used as a rapid non-invasive optical device to measure raw sheep meat to estimate cooked meat tenderness and cooking loss. Raman measurements were conducted on m. longissimus thoracis et lumborum samples from two sheep flocks from two different origins which had been aged for five days at 3–4 °C before deep freezing and further analysis. The Raman data of 140 samples were correlated with shear force and cooking loss data using PLS regression. Both sample origins could be discriminated and separate correlation models yielded better correlations than the joint correlation model. For shear force, R² = 0.79 and R² = 0.86 were obtained for the two sites. Results for cooking loss were comparable: separate models yielded R² = 0.79 and R² = 0.83 for the two sites. The results show the potential usefulness of Raman spectra which can be recorded during meat processing for the prediction of quality traits such as tenderness and cooking loss.     

利用图像分析和深度学习预测油菜籽中总酚含量

目的 建立了一种结合图像分析和深度学习的油菜籽中总酚含量的快速预测方法。方法 利用VGG19网络进行油菜籽图像籽粒特征的提取,通过多个卷积层来学习油菜籽图像的特征,并建立了回归模型用于预测油菜籽的总酚含量。共收集了100种油菜籽样本,将油菜籽样本按照3:1的比例划分为训练集和测试集,利用均方损失函数(MSELoss)和决定系数(r2)评估模型预测准确性。结果 测试集MSELoss=0.0085、r2=0.9914,表明该预测模型具有一定的准确性和实用性。结论 本研究提出了一种快速、准确的评估油菜籽总酚含量的方法,为油菜籽的总酚测定提供一种快速、准确的智能化检测方法。     

Goat farm variability affects milk Fourier-transform infrared spectra used for predicting coagulation properties

Driven by the large amount of goat milk destined for cheese production, and to pioneer the goat cheese industry, the objective of this study was to assess the effect of farm in predicting goat milk-coagulation and curd-firmness traits via Fourier-transform infrared spectroscopy. Spectra from 452 Sarda goats belonging to 14 farms in central and southeast Sardinia (Italy) were collected. A Bayesian linear regression model was used, estimating all spectral wavelengths' effects simultaneously. Three traditional milk-coagulation properties [rennet coagulation time (min), time to curd firmness of 20 mm (min), and curd firmness 30 min after rennet addition (mm)] and 3 curd-firmness measures modeled over time [rennet coagulation time estimated according to curd firmness change over time (RCT_eq), instant curd-firming rate constant, and asymptotical curd firmness] were considered. A stratified cross validation (SCV) was assigned, evaluating each farm separately (validation set; VAL) and keeping the remaining farms to train (calibration set) the statistical model. Moreover, a SCV, where 20% of the goats randomly taken (10 replicates per farm) from the VAL farm entered the calibration set, was also considered (SCV₈₀). To assess model performance, coefficient of determination (R²_VAL) and the root mean squared error of validation were recorded. The R²_VAL varied between 0.14 and 0.45 (instant curd-firming rate constant and RCT_eq, respectively), albeit the standard deviation was approximating half of the mean for all the traits. Although average results of the 2 SCV procedures were similar, in SCV₈₀, the maximum R²_VAL increased at about 15% across traits, with the highest observed for time to curd firmness of 20 mm (20%) and the lowest for RCT_eq (6%). Further investigation evidenced important variability among farms, with R²_VAL for some of them being close to 0. Our work outlined the importance of considering the effect of farm when developing Fourier-transform infrared spectroscopy prediction equations for coagulation and curd-firmness traits in goats.     

Sun drying of figs: an experimental study

In this work, the sun drying behaviour of figs was investigated. Drying experiments were conducted for figs (Ficus carica) grown in Iskenderun-Hatay, Turkey. The constant rate period is absent from the drying curve. The drying process took place in the falling rate period. The drying data were fitted to the different mathematical models such as Lewis, Henderson and Pabis, Page, Logarithmic, Two-term, Two-term exponential, Verma et al. and Wang and Singh models. The performance of these models was investigated by comparing the determination of coefficient (R²), reduced chi-square (χ²) and root mean square error (RMSE) between the observed and predicted moisture ratios. The results showed that the Verma et al. model was found to satisfactorily describe the sun drying curve of figs with a R² of 0.9944, χ² of 0.000483 and RMSE of 0.062857.     

Evaluation of the robustness of the enzymatic hydrolysis in batch and continuous mode by a central composite design

The main purpose of this work is to study the ability of the enzymatic reaction. For the performance of the experiment, it is desirable to control variations so that they are minimized to the maximum extend and therefore an optimum operating point can be maintained. To achieve this target, the central composite design takes into account all interaction effects that may be useful for creating a mathematical model in agreement with the validity criteria. The model showed to be more suitable for the saccharification experiments in batch mode than in continuous mode. In batch mode, a correlation coefficient close to unity (R² = .98) was obtained. Moreover, the resulting mathematical model was satisfactory in accordance with the validation criteria. For continuous mode, the coefficient value obtained was R² = .83 indicating that the model to study the ability of the enzymatic reaction was inferior than the batch mode conditions of the analysis.

Practical applications

• The ability of the enzymatic reaction to maintain its performance at small experimental condition variations was studied.
• The central composite design conformed to criterion validity.
• A correlation coefficient close to unity (R² = .98) was obtained.

     

An improved model of the seeded batch crystallization of glucose monohydrate from aqueous solutions

The current research has produced an accurate model of the non-nucleating seeded batch crystallization of glucose monohydrate which includes complex phenomena including crystal growth rate dispersion and the effect of the mutarotation reaction. The model is able to predict the population density of crystals in the batch as a function of particle size and batch time, n=n(L,t) as well as total glucose concentration in the mother liquor and the fraction of glucose in the α-d-glucopyranose form. A previous model of similar systems was limited by considering only systems with monosize seed crystals, and where growth rate dispersion had a negligible effect on the particle size distribution. Because of the nature of the ‘common history’ crystals that are produced by the growth of glucose monohydrate, the modifications required to the model to account for these additions to the model are remarkably simple. By predicting the full population density the model produces an accurate mass balance for the crystallization process, since the second moment of the crystal size distribution (CSD) may be calculated analytically at every point in the simulation. This enables the competitive kinetics between the rate of crystal mass deposition of α-glucose and the rate of production of α-glucose via the mutarotation reaction to be more accurately accounted for, and hence the significance of the mutarotation reaction on the crystal growth to be more accurately predicted.     

Modelling the influence of temperature on the recovery ofListeria monocytogenesfrom heat injury

The ability ofListeria monocytogenesScott A to recover from heat injury, as monitored by repair of salt-tolerance, was modelled as a function of temperature and extent of cell injury. A modification to the equation of Hills and Mackey ((1995) Food Microbiology, 12, 333-346), which included parameters for the maximum rate of recovery (R_r), and the decreasing rate of recovery (a_r), and eliminated the parameter describing the increasing rate of recovery (b_r), was used to model the recovery from injury. Lag phase duration (LPD) and R_rwere well predicted by models including both temperature and extent of injury (R²=0.99 and 0.92 for LPD and R_rrespectively), while the growth rate (R_g) was influenced by temperature alone (R²=0.96). The degree to which cells had recovered salt-tolerance at the end of the lag phase (i.e. proportion of cells capable of growth on agar containing 5% ((w/v) NaCl) was found to be related to the initial extent of injury. The results suggest that loss of salt-tolerance may not be the most important site of injury, and that alternative models are needed to adequately account for the contribution of sub-populations of cells to growth after repair of heat injury.     

Application of Mid-infrared Spectroscopy for the Measurement of Several Quality Parameters of Alcoholic Beverages, Wine and Raki

Mid-infrared (IR) spectroscopy, which is a rapid and relatively small amount of waste producing technique, was used to predict several quality parameters of two types of alcoholic beverages, wine and raki. Mid-infrared spectra of red, rose and white wines and a traditional aniseed alcoholic beverage, raki were collected and relations were established between measured chemical parameters (pH, brix, total phenol content, anthocyanin content, titratable acidity, sugar content, electrical conductivity and some colour parameters) of these beverages and their infrared spectra using chemometric techniques. Partial least square regression provided excellent prediction of total phenol (R ²?=?0.97) and anthocyanin contents (R ²?=?0.98) of wine samples and a good prediction of pH (R ²?=?0.9), brix (R ²?=?0.92) and colour intensity (R ²?=?0.93) values were obtained. Brix, total phenol and sugar content of raki samples were also estimated very successfully (R ²?=?0.99) for raki and good prediction was obtained with pH value. Mid-IR spectroscopy in combination with chemometrics could be a promising technique for determination of several quality parameters of alcoholic beverages simultaneously and rapidly.     

Optimization of the basic formulation of a traditional baked cassava cake using response surface methodology

The optimum formulation for production of a Malaysian traditional baked cassava cake was determined using response surface methodology (RSM). Effects of amount of ingredients such as sugar (10-30%) and coconut milk (15-35%) on the textural characteristics (hardness and chewiness) and sensory qualities (colour, firmness, cassava flavour and overall acceptability) of cakes were investigated. Significant regression models which explained the effects of different percentages of sugar and coconut milk on all response variables were determined. The coefficients of determination, R² of all the response variables were higher than 0.8. Based on the response surface and superimposed plots, the basic formulation for production of Malaysian traditional baked cassava cake with desired sensory quality was obtained by incorporating with 25% of sugar and 20% of coconut milk.     

Determination of degree of substitution of carboxymethyl starch by Fourier transform mid-infrared spectroscopy coupled with partial least squares

The degree of substitution (DS) markedly affects the properties of carboxymethyl starch (CMS). The conventional methods for the DS determination are time-consuming and not environment friendly. Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with partial least squares (PLS) regression is applied to determine the DS of CMS in the present study. Calibration models with direct titration as the reference method were optimised by cross validation. A PLS regression model with a coefficient of determination (R²) of 0.9593 and root-mean-square error of cross validation (RMSECV) of 0.0141 was obtained in the spectral range from 500 to 4000 cm⁻¹. The prediction set gave a coefficient of determination (R²) and root-mean-square error of prediction (RMSEP) of 0.9368 and 0.0228, respectively. The results obtained in this study indicate that FT-MIR spectroscopy can be used as an easy, rapid, and novel tool to quantitatively predict the DS of CMS.     

Non-destructive determination of water-holding capacity in fresh beef by using NIR hyperspectral imaging

This study was carried out for post-mortem non-destructive prediction of water holding capacity (WHC) in fresh beef using near infrared (NIR) hyperspectral imaging. Hyperspectral images were acquired for different beef samples originated from different breeds and different muscles and their spectral signatures were extracted. Both principal component analysis (PCA) and partial least squares regression (PLSR) models were developed to obtain an overview of the systematic spectral variations and to correlate spectral data of beef samples to its real WHC estimated by drip loss method. Partial least squares modeling resulted in a coefficient of determination (R_CV²) of 0.89 and standard error estimated by cross validation (SECV) of 0.26%. The PLSR loadings showed that there are some important absorption peaks throughout the whole spectral range that had the greatest influence on the predictive models. Six wavelengths (940, 997, 1144, 1214, 1342, and 1443 nm) were then chosen as important wavelengths to build a new PLS prediction model. The new model led to a coefficient of determination (R_CV²) of 0.87 and standard error estimated by cross validation (SECV) of 0.28%. Image processing algorithm was then developed to transfer the predicting model to each pixel in the image for visualizing drip loss in all portions of the sample. The results showed that hyperspectral imaging has the potential to predict drip loss non-destructively in a reasonable accuracy and the results could be visualised for identification and classification of beef muscles in a simple way. In addition to realize the difference in WHC within one sample, it was possible to accentuate the difference in samples having different drip loss values.     

Statistical optimization of desugarization process parameters of liquid whole egg using response surface methodology

The glucose is considered to affect the quality of the dried egg products; therefore the statistical optimization of desugarization process parameters of Liquid whole egg (LWE) was carried out in this study. The fermentation of Liquid whole egg (LWE) was done using compressed baker’s yeast. A polynomial model was regressed between reducing sugar & desugarization conditions. The coefficient of determination (R²) of 0.998 (P < 0.0001) for the regressed model indicated about the adequacy of the model, which implies the model was significant to predict reducing sugar content at different fermentation conditions. Optimum conditions for complete desugarization of Liquid whole egg (LWE) were found to be time 6.49 h, temperature 28 °C, pH 6.40 and yeast concentration 3.8 g/L and confirmed by conducting actual experiments at these conditions.     

Variable selection in visible and near-infrared spectra: Application to on-line determination of sugar content in pears

Informative variable (or wavelength) selection plays an important role in quantitative analysis by visible and near-infrared (Vis-NIR) spectroscopy. Four different variable selection methods, namely, stepwise multiple linear regression (SMLR), genetic algorithm-partial least squares regression (GA-PLS), interval PLS (iPLS), and successive projection algorithm-multiple linear regression combined with GA (GA-SPA-MLR), were studied to determine the sugar content of pears. The results derived by these techniques were then compared. The calibration model built using GA-SPA-MLR on 18 selected wavelengths (2% of the total number of variables) exhibited higher coefficient of determination (R²) = 0.880 and root mean square error of prediction (RMSEP) = 0.459°Brix for the validation set. Results show that the accuracy of the quantitative analysis conducted by Vis-NIR spectroscopy can be improved through appropriate wavelength selection. Despite the RMSEP value of GA-SPA-MLR was a slightly higher than that of GA-PLS, considering that this model was simpler and easier to interpret, GA-SPA-MLR can be used for industrial applications.     

Modeling changes in rheological properties of potatoes during storage under constant and variable conditions

The changes in rheological properties of potatoes stored at 5, 15, 25 °C and variable (fluctuating) temperature for 16 or 26 weeks were evaluated in terms of elasticity and viscosity parameters using axial compression and creep tests. Cylindrical test specimens (15 mm diameter and 30 mm long) were used. A third-degree polynomial best fitted the force-deformation curves in axial compression test (R²=0.98-0.99) whereas a four-element (Burgers) mechanical model adequately described the creep response of potatoes (R²=0.95-0.99). The tangent modulus of elasticity in axial compression and elasticity and viscosity parameters in creep tests in general decreased significantly (P<0.05) with increase in storage time both under constant and variable storage conditions. The changes in rheological properties of potatoes stored under constant storage condition were sufficiently described by a modified exponential model (R²=0.89-0.96) except for the viscosity parameter of the Maxwell component of the four-element model. The logarithm of degradation rate constant, k, and the constant, n, were linearly related to storage temperature. For the variable storage condition, a bulk mean temperature (T_bm) was calculated to account for a series combination of storage time and temperature to which the potatoes were subjected. The changes in rheological properties due to variable storage temperature were then described as a function of T_bm and storage time, t_s, using stepwise multiple regression. The result indicated that except the viscosity parameter of the Maxwell component of the four-element model, it was possible to describe the changes in rheological properties as a function of T_bm and t_s (R²=0.84-0.99).