Evaluating Moisture Content in Immersion Vacuum-Cooled Sausages with Citrus Peel Extracts Using Hyperspectral Imaging.

The moisture content of immersion vacuum-cooled sausages with modified casings containing citrus fruit extracts under different storage conditions was studied using hyperspectral imaging (HSI) associated with chemometrics. Different pre-processing combinations were applied to improve the robustness of the model. The partial least squares regression model, employing the full reflectance spectrum with pre-treatment of the standard normal variate, showed calibration coefficients of determination (Rc2) of 0.6160 and a root mean square error of calibration (RMSEC) of 2.8130%. For the first time, prediction maps developed via HSI visualized the distribution of moisture content in the immersion vacuum-cooled sausages with unique modified casings in response to fluctuating storage conditions. The prediction maps showed exact parts with high water content, which will help us to monitor and prevent mold growth. The combination of HSI with multivariate analysis not only quantifies changes in moisture content but also visually represents them in response to various casing treatments under different storage conditions, illustrating the significant potential for real-time inspection and early mold detection in sausages within the processed meat industry.

Assessment of adenosine triphosphate content in sausages stuffed in different modified casing treatments added with orange extracts, utilising hyperspectral imaging combined with multivariate analysis.

Introduction: An investigation was conducted using a hyperspectral imaging (HSI) system to non-invasively estimate adenosine triphosphate (ATP) content in vacuum packaged sausages in different modified casing treatments added with orange extracts after a year of storage at 4°C. Methods: Various pre-processing combinations were applied to the spectra to enhance the performance of partial least squares regression (PLSR). Results and discussion: PLSR models, utilising the full absorbance spectrum with pre-treatment of standard normal variate combined with 1st derivative,exhibited prediction coefficients of determination (Rp2) reaching up to 0.6629. A distribution map developed through MATLAB was employed to display the location and concentration of ATP content in these unique sausages for the first time. The integration of HSI and multivariate analysis not only quantifies but also visually represents the changes in ATP content response to the different casing treatments, demonstrating the significant potential for real-time inspection in the processed meat industry.

Microwave-Assisted Extraction of Polyphenols from Bitter Orange Industrial Waste and Identification of the Main Compounds.

In this work, the extraction of phenolic compounds from orange waste (OW) obtained after the industrial extraction of neohesperidin from bitter oranges (Seville oranges) was assayed by microwave-assisted extraction (MAE) and Soxhlet extraction (SE). The extraction agents were ethanol and acetone. For SE, aqueous solutions of both extraction agents were used at 50%, 75%, and 100% (v/v). For MAE, a design of experiments was applied to determine the conditions that maximize the extraction yield. The independent variables were temperature (from 20 to 75 °C), process time (between 10 and 20 min), and percentage of extraction agent (v/v) in the extraction solution (50%, 75%, and 100%). Following that, the extracts were analyzed by ultra-high-performance liquid chromatography to identify the main phenolic compounds extracted. Results showed that 50% (v/v) ethanol or acetone was the extraction agent concentration that maximized the extraction yield for both SE and MAE, with the yields of MAE being higher than those of SE. Thus, the highest extraction yields on a dry basis achieved for MAE were 16.7 g/100 OW for 50% acetone, 75 °C, and 15 min, and 20.2 g/100 OW for 50% ethanol, 75 °C, and 10.8 min, respectively. Finally, the main phenolic compounds found in the orange waste were naringin, hesperidin, neohesperidin, and naringenin (i.e., flavonoids).

Hyperspectral Imaging Combined with Chemometrics Analysis for Monitoring the Textural Properties of Modified Casing Sausages with Differentiated Additions of Orange Extracts.

The textural properties (hardness, springiness, gumminess, and adhesion) of 16-day stored sausages with different additions of orange extracts to the modified casing solution were estimated by response surface methodology (RSM) and a hyperspectral imaging system in the spectral range of 390-1100 nm. To improve the model performance, normalization, 1st derivative, 2nd derivative, standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied for spectral pre-treatments. The raw, pretreated spectral data and textural attributes were fit to the partial least squares regression model. The RSM results show that the highest R2 value achieved at adhesion (77.57%) derived from a second-order polynomial model, and the interactive effects of soy lecithin and orange extracts on adhesion were significant (p < 0.05). The adhesion of the PLSR model developed from reflectance after SNV pretreatment possessed a higher calibration coefficient of determination (0.8744) than raw data (0.8591). The selected ten important wavelengths for gumminess and adhesion can simplify the model and can be used for convenient industrial applications.

Evaluation of pH in Sausages Stuffed in a Modified Casing with Orange Extracts by Hyperspectral Imaging Coupled with Response Surface Methodology.

The pH values of sausages stuffed in natural hog casings with different modifications (soy lecithin, soy oil, orange extracts (OE) from waste orange peels, lactic acid in slush salt, and treatment time) after 16-day 4 °C storage were evaluated for the first time by hyperspectral imaging (350−1100 nm) coupled with response surface methodology (RSM). A partial least squares regression (PLSR) model was developed to relate the spectra to the pH of sausages. Spectral pretreatment, including first derivative, second derivative, multiplicative scatter correction (MSC), standard normal variate (SNV), normalization, and normalization, with different combinations was employed to improve model performance. RSM showed that only soy lecithin and OE interactively affected the pH of sausages (p < 0.05). The pH value decreased when the casing was treated with a higher concentration of soy lecithin with 0.26% OE. As the first and second derivatives are commonly used to eliminate the baseline shift, the PLSR model derived from absorbance pretreated by the first derivative in the full wavelengths showed a calibration coefficient of determination (R2) of 0.73 with a root mean square error of calibration of 0.4283. Twelve feature wavelengths were selected with a comparable R2 value compared with the full wavelengths. The prediction map enables the visualization of the pH evolution of sausages stuffed in the modified casings added with OE.

Optimizing Procedures of Ultrasound-Assisted Extraction of Waste Orange Peels by Response Surface Methodology.

The simultaneous effects of three continuous factors: solvent concentration (50−100%), treated times (25−85 min), treated temperatures (25−55 °C), and two categorical factors: type of solvents (methanol or ethanol) and ultrasonic frequency (28 kHz or 40 kHz) on ultrasonic-assisted extraction yield from waste orange peels were evaluated and optimized by response surface methodology. Fourier Transform Infrared (FTIR) spectroscopy with a wavelength of 500 cm−1 to 4000 cm−1 was employed to rapidly identify the orange extracts. The significant polynomial regression models on crude extraction, sediments after evaporation, and precipitation yield were established (p < 0.05). Results revealed that solvent concentration affected crude extraction and precipitation yield linearly (p < 0.01). The optimal and practical ultrasound-assisted extraction conditions for increasing the precipitation yield were using 61.42% methanol with 85 min at 55 °C under 40 kHz ultrasonic frequency. The spectra of extracts showed a similar fingerprint of hesperidin.

Quality Evaluation and Mathematical Modelling Approach to Estimate the Growth Parameters of Total Viable Count in Sausages with Different Casings.

The growth kinetics for the total viable count (TVC) in sausages with modified hog casings (treated by surfactant solutions and slush salt with lactic acid), natural hog casings and sheep casings as a function of the storage time (up to 50 days) were studied for the first time. The growth of TVC was fitted by the Baranyi model, and the maximum specific growth rate, lag time and initial and final cell populations were estimated via DMFit. The coefficient of determination of the Baranyi model reached 0.94, 0.77 and 0.86 for sausages stuffed in modified hog casings (MHC), control hog casings (CHC) and natural sheep casings (NSC), respectively. The experimental data for the initial populations were 4.69 ± 0.10 log cfu/g for MHC, 4.79 ± 0.10 log cfu/g for CHC and 3.74 ± 0.14 log cfu/g for NSC, whilst the predicted initial cell populations for MHC, CHC and NSC were 4.81 ± 0.20 log cfu/g, 5.19 ± 0.53 log cfu/g and 3.74 ± 0.54 log cfu/g, respectively. Their shelf lives can also be predicted. The results show that the average pH value of MHC samples (6.96 ± 0.01) was significantly lower than that of CHC (7.09 ± 0.01) and NSC (7.05 ± 0.02) samples at day 50 (p < 0.05). Sausages with CHC possessed a significant higher water holding capacity (99.48 ± 0.14%) at d 29 than those with MHC (97.40 ± 0.46%) and NSC (98.55 ± 0.17%) (p < 0.05). On the last day, the average moisture content for samples with NSC (38.30 ± 3.23%) was significantly higher than that for those with MHC (29.38 ± 2.52%) and CHC (29.15 ± 1.16%) (p < 0.05).

Terahertz spectroscopy technology as an innovative technique for food: Current state-of-the-Art research advances.

With the dramatic development of source and detector components, terahertz (THz) spectroscopy technology has recently shown a renaissance in various fields such as medical, material, biosensing and pharmaceutical industry. As a rapid and noninvasive technology, it has been extensively exploited to evaluate food quality and ensure food safety. In this review, the principles and processes of THz spectroscopy are first discussed. The current state-of-the-art applications of THz and imaging technologies focused on foodstuffs are then discussed. The advantages and challenges are also covered. This review offers detailed information for recent efforts dedicated to THz for monitoring the quality and safety of various food commodities and the feasibility of its widespread application. THz technology, as an emerging and unique method, is potentially applied for detecting food processing and maintaining quality and safety.

Hyperspectral Imaging Coupled with Multivariate Analysis and Image Processing for Detection and Visualisation of Colour in Cooked Sausages Stuffed in Different Modified Casings.

A hyperspectral imaging system was for the first time exploited to estimate the core colour of sausages stuffed in natural hog casings or in two hog casings treated with solutions containing surfactants and lactic acid in slush salt. Yellowness of sausages stuffed in natural hog casings (control group, 20.26 ± 4.81) was significantly higher than that of sausages stuffed in casings modified by submersion for 90 min in a solution containing 1:30 (w/w) soy lecithin:distilled water, 2.5% wt. soy oil, and 21 mL lactic acid per kg NaCl (17.66 ± 2.89) (p < 0.05). When predicting the lightness and redness of the sausage core, a partial least squares regression model developed from spectra pre-treated with a second derivative showed calibration coefficients of determination (Rc2) of 0.73 and 0.76, respectively. Ten, ten, and seven wavelengths were selected as the important optimal wavelengths for lightness, redness, and yellowness, respectively. Those wavelengths provide meaningful information for developing a simple, cost-effective multispectral system to rapidly differentiate sausages based on their core colour. According to the canonical discriminant analysis, lightness possessed the highest discriminant power with which to differentiate sausages stuffed in different casings.

Estimation of adenosine triphosphate content in ready-to-eat sausages with different storage days, using hyperspectral imaging coupled with R statistics.

A hyperspectral imaging (HSI) system (380-1000 nm) was investigated for non-invasively estimating adenosine triphosphate (ATP) content in ready-to-eat sausages during 5 days storage at 35 °C. A set of pretreated combinations were carried out on preprocessing the spectra to improve the performance of partial least squares regression (PLSR). According to the regression coefficient values, ten important wavelengths (385, 390, 395, 505, 580, 670, 745, 780, 855, and 955 nm) were selected in this study. PLSR models developed using full wavelengths and optimal wavelengths showed the prediction coefficient of determination (rp2) up to 0.8324 and 0.8606, respectively. The concentration and location of the ATP content in sausages were for the first time displayed via chemical imaging developed by R statistics. Combining HSI and multivariate analysis can quantify and visualize ATP dynamic changes during storage and a great potential in the processed meat industry for real-time inspection.

Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions.

The potential of hyperspectral imaging with wavelengths of 380 to 1000 nm was used to determine the pH of cooked sausages after different storage conditions (4 °C for 1 d, 35 °C for 1, 3, and 5 d). The mean spectra of the sausages were extracted from the hyperspectral images and partial least squares regression (PLSR) model was developed to relate spectral profiles with the pH of the cooked sausages. Eleven important wavelengths were selected based on the regression coefficient values. The PLSR model established using the optimal wavelengths showed good precision being the prediction coefficient of determination (Rp2 ) 0.909 and the root mean square error of prediction 0.035. The prediction map for illustrating pH indices in sausages was for the first time developed by R statistics. The overall results suggested that hyperspectral imaging combined with PLSR and R statistics are capable to quantify and visualize the sausages pH evolution under different storage conditions. PRACTICAL APPLICATION: In this paper, hyperspectral imaging is for the first time used to detect pH in cooked sausages using R statistics, which provides another useful information for the researchers who do not have the access to Matlab. Eleven optimal wavelengths were successfully selected, which were used for simplifying the PLSR model established based on the full wavelengths. This simplified model achieved a high Rp2 (0.909) and a low root mean square error of prediction (0.035), which can be useful for the design of multispectral imaging systems.

Real-time prediction of pre-cooked Japanese sausage color with different storage days using hyperspectral imaging.

BACKGROUND: Redness can greatly influence the freshness of sausages. A precise, rapid and noncontact analytical method or tool is needed to quantify the color. Hyperspectral imaging (HSI) is an emerging technique that integrates spectroscopy and imaging to obtain the spectral and spatial information simultaneously. In the present study, the redness of cooked sausages stored up to 57 days was predicted using HSI in tandem with multivariate data analysis. The mean spectra of the sausages were extracted from the hyperspectral images. Partial least squares regression (PLSR) and forward stepwise multiple regression (FSMR) models were used to develop the relavent spectral profiles with the redness of the cooked sausages. RESULTS: Ten important wavelengths were selected based on the regression coefficient values from the PLSR model. The PLSR model established using the full wavelengths presented a good performance, with Rc of 0.934 and a root mean square error of calibration of 0.642 (redness ranged between 14.99 and 21.48). The prediction maps for demonstrating evolution of redness in sausages were developed for the first time using R statistics (R Foundation for Statistical Computing) and Matlab (MathWorks Inc., Natick, MA, USA). CONCLUSION: HSI combined with PLSR and FSMR can be used to quantify and visualize evolution of sausage redness under different storage days. © 2017 Society of Chemical Industry.

Physical Properties and Volatile Composition Changes of Cooked Sausages Stuffed in a New Casing Formulation Based in Surfactants and Lactic Acid During Long-Term Storage.

The objective of this research was to investigate the effects of different modified casings and storage time on the quality attributes of cooked sausages using principal component analysis (PCA) and discriminant analysis. The effects of modifying different casing treatments on sausages' color (L* , a* , b* ), pH, and texture (hardness, springiness, cohesion, gumminess, chewiness) after 36-d storage were estimated by PCA. According to the PCA, lightness at day 36 was correlated to sample stuffed in casing with treatment 2 (T2; soy lecithin concentration: 1:27.5, soy oil concentration: 1.25%, lactic acid concentration: 19.5 mL/kg NaCl [solid], residence time: 75 min). T2 sample can be distinguished from control sample at days 1, 8, 15, and 36 according to electronic nose system. DA was performed to determine possible different sample groups according to selected variables. Results showed that chewiness was the best discriminator for differentiating sausages stored for 15 d from other days. Chewiness and gumminess were able to discriminate sausages stuffed in casing with T2 from control sample. The relationships between modified concentrations and quality attributes of cooked sausages after 36-d storage were also established.

Effects of processing parameters on immersion vacuum cooling time and physico-chemical properties of pork hams.

The effects of agitation (1002 rpm), different pressure reduction rates (60 and 100 mbar/min), as well as employing cold water with different initial temperatures (IWT: 7 and 20°C) on immersion vacuum cooling (IVC) of cooked pork hams were experimentally investigated. Final pork ham core temperature, cooling time, cooling loss, texture properties, colour and chemical composition were evaluated. The application for the first time of agitation during IVC substantially reduced the cooling time (47.39%) to 4.6°C, compared to IVC without agitation. For the different pressure drop rates, there was a trend that shorter IVC cooling times were achieved with lower cooling rate, although results were not statistically significant (P>0.05). For both IWTs tested, the same trend was observed: shorter cooling time and lower cooling loss were obtained under lower linear pressure drop rate of 60 mbar/min (not statistically significant, P>0.05). Compared to the reference cooling method (air blast cooling), IVC achieved higher cooling rates and better meat quality.