Potentiality of front-face fluorescence and mid-infrared spectroscopies coupled with partial least square regression to predict lipid oxidation in pound cakes during storage

Non-destructive Detection of Fatty Acid Content of Camellia Seed Based on Hyperspectral

As a unique traditional vegetable oil in China, camellia seed oil has very high edible value. Camellia seed kernel is mainly composed of fatty acids, which not only determines the oil yield of camellia seed, but also exert an important impact on the storage performance of camellia seed. In order to quickly and accurately determine the fatty acid content of camellia seed, this paper took camellia seed as the research object, used hyperspectral technology to determine the fatty acid content of camellia seed, and establishes a spectral model. 8 pretreatment methods, such as Savitzky-Golay smoothing, normalization, baseline correction, multivariate scattering correction, standard normal variable transformation, detrending algorithm, first derivative and second derivative, were adopted in this paper. The spectral prediction model of fatty acid content in camellia seed was established by combining 4 modeling methods: principal components regression (PCR), partial least square regression (PLSR), back propagation neural network (BP), radial basis function neural network (RBF). The optimal prediction model was selected by comparing the coefficient of determination (R²) and root mean square error (RMSE) of various models. The results showed that the spectral sensitive bands with high correlation coefficients (r) were 410-420 nm, 450-460 nm, 490-510 nm, 545-580 nm, 845-870 nm and 905-925 nm, respectively. The r obtained by MSC pretreatment of spectral data was the largest. The data obtained by 8 different pretreatment methods combined with RBF neural network model was the best, in which the average value of coefficient of determination (R_C²) in the calibration set was 0.8654, and the root mean square error of calibration (RMSEC) was 0.0777; the average value of coefficient of determination (R_P²) and root mean square error of prediction (RMSEP) in the prediction set model were 0.8437 and 0.0827, respectively. It could be seen that the best accuracy could be achieved by MSC pretreatment combined with RBF neural network modeling. This paper can provide reference for rapid nondestructive detection of fatty acid content in camellia seed by hyperspectral technology.

Use of mid-infrared spectroscopy for quality monitoring and the prediction of physicochemical parameters of dry fermented chicken sausages enriched with sesame flour

BACKGROUND

This study aimed to investigate the effects of the supplementation of sesame flour in fermented chicken sausages ('S1' containing 800 g kg^-1 chicken fillet, 180 g kg^-1 veal fat and 20 g kg^-1 sesame flour and 'S2' containing 800 g kg^-1 chicken fillet, 160 g kg^-1 veal fat and 40 g kg^-1 sesame flour) compared with control sausages (containing 800 g kg^-1 chicken fillet and 200 g kg^-1 veal fat) on the physico-chemical characteristics, texture, and structure during the fermentation stage.

RESULTS

The physicochemical parameters of samples belonging to the control, S1, and S2 batches were significantly affected by the addition of sesame flour and the fermentation stage. For instance: (i) the lowest protein content was observed for control samples on day 1 (61.4 ± 6.52 g kg^-1 ) whereas the highest level was noted for S2 samples on day 15 (327.5 ± 22.2 g kg^-1 ), and (ii) an inverse trend was observed for the fat content because the lowest content was observed for samples in the S2 batch on day 1 (129.0 ± 5.30 g kg^-1 ) whereas the highest fat content was noted for samples belonging to control batch on day 15 (332.0 ± 1.29 g kg^-1 ). The application of statistical methods to mid-infrared spectroscopy allowed clear discrimination between control, S1, and S2 batches. The addition of sesame flour in the recipes induced some modification in the secondary structure because β-turn levels ranged from 39.30 to 34.50, 36.76 to 34.70, and 38.93 to 34.70 for control, S1, and S2 batches, respectively, throughout the fermentation stage. Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) showed a similar protein profile pattern in the three batches on days 1 and 5, but on day 10 control and S2 batches showed the most intense degradation of myofibrillar proteins.

CONCLUSION

The results demonstrated that mid-infrared spectroscopy coupled with chemometric tools could be used as a rapid screening tool to assess and monitor the quality of dry chicken sausages enriched with sesame flour throughout the fermentation stage. © 2022 Society of Chemical Industry.

Use of front face fluorescence spectroscopy coupled with multivariate data analysis for monitoring biscuits' quality during aging

In this study, the potentiality of front face fluorescence spectroscopy (FFFS) for the evaluation of the quality of biscuits manufactured with butylated hydroxytoluene and pomegranate peel extract during aging was investigated. By using the principal component analysis, vitamin A and tryptophan spectra allowed a clear discrimination between biscuit samples according to the nature of antioxidants, while fluorescent Maillard reaction products spectra showed clear differentiation between samples according to the storage time. Clear differentiation between biscuits according to the used antioxidants and storage time was achieved by using common components and specific weights analysis. Using partial least-squares regression, excellent prediction of water activity (R 2 = 0.95), and L* values (R 2 = 0.92), and approximate prediction of hardness (R 2 = 0.78), b* values (R 2 = 0.74), and moisture content (R 2 = 0.74) were shown. However, the FFFS failed to predict a* values, primary and secondary oxidation products (R 2 < 0.6).

Texture staling of pound cakes assessed by front face fluorescence spectroscopy in tandem with chemometric analysis

Two vegetal oils have been selected for the formulation of pound cakes, rapeseed oil (RO) and palm oil (PO). The freshness of these products has been monitored during 58 days of storage. The RO pound cakes of 58 days as well as PO pound cakes presented higher values (p < .05) of hardness (N), Young's modulus (N.cm^-2 ) and compressive stress (N.cm^-2 ) than those aged of 5 days. For both vitamin A and tryptophan spectra, the maximum of fluorescence intensity varied according to the aging period. For both RO and PO recipes, lipid oxidation indicators (peroxide value, para-anisidine value, and total oxidation value [TOTOX]) were interestingly correlated to Young's modulus (R²  = 0.99) as well as compressive stress (R²  = 0.99), using polynomial model. The application of partial least squares regression to the vitamin A spectra provided excellent predictive results for both compressive stress (R²  = 0.99) and TOTOX (R²  = 0.99). Good results were observed for tryptophan spectra for the prediction of TOTOX (R²  = 0.77). Thus, the use of front face fluorescence spectroscopy may provide rapid and accurate results for the monitoring of pound cakes freshness throughout storage.

Assessing the quality of dry sausages using fluorescence spectroscopy, physico-chemical and dynamic testing rheology: A preliminary study

The viscoelastic and the structure properties of three brands of dry sausages (Auvergne, Beef-poultry, and Galbanetto) were studied using dynamic rheology and fluorescence spectroscopy. The storage and the loss modulus of sausage samples showed a viscoelastic character. The principal component analysis (PCA) carried out on the normalised rheological and physico-chemical parameters allowed to differentiate the sausage samples into 3 groups according to their brands. This trend was confirmed by the factorial discriminant analysis (FDA) where 74.44% of correct classification was obtained. The emission spectra acquired after excitation set at 290, 340, and 360 nm and excitation spectra scanned after emission set at 410 nm allowed clear differentiation between the three brand samples. The obtained results were confirmed following the application of partial least squares regression (PLSR) to the fluorescence and physico-chemical parameters since an excellent prediction of moisture content was obtained from the excitation spectra set at 340 nm (R²  = 0.99) and 360 nm (R²  = 0.99). The protein content of dry sausages was well predicted after excitation set at 290 and 340 nm with R² of 0.96 and 0.97, respectively, while the fat level was well estimated after excitation set at 340 and 360 nm and emission set at 410 nm (R²  = 0.96, 0.96 and 0.94, respectively). The obtained results showed the potential use of fluorescence spectroscopy as a rapid technique for evaluating the quality of dry sausages. This article is protected by copyright. All rights reserved.

Front-face synchronous fluorescence spectroscopy for rapid and non-destructive determination of free capsanthin, the predominant carotenoid in chili (Capsicum annuum L.) powders based on aggregation-induced emission

Capsanthin is the major natural carotenoid pigment in red chili pepper possessing important bioactivity. Its conventional determination method is high performance liquid chromatography (HPLC) with complex and tedious sample pretreatment. In this study, synchronous front-face fluorescence spectroscopy (FFFS) was applied for the fast and non-invasive detection of free capsanthin in chili powders. Although capsanthin was only weak fluorescent in solution state, it showed strong fluorescence in two separated regions in front-face geometry which could also be clearly observed in chili powders. The mechanisms of these emissions are revealed to be aggregation-induced emission (AIE) and J-aggregate formation (JAF). The free capsanthin in 85 chili powder samples were determined by HPLC as in the range of 0.6-3.0 mg/g. The total synchronous FFFS spectra of these samples were scanned. Simple first-order models were built by partial least square regression (PLSR), and were validated by 5-fold cross-validation and external validation. The coefficients of determination (R²) were higher than 0.9, and the root mean square errors (RMSE) were less than 0.2 mg/g. The relative error of prediction (REP) was 9.9%, and the residual predictive deviation (RPD) was 3.7. The method was applied for the estimation of free capsanthin in several real-world samples with satisfactory analytical results. The average relative error to HPLC reference values was -11.8%.

Characterization of the Lipid Oxidation Process of Robusta Green Coffee Beans and Shelf Life Prediction during Accelerated Storage

The lipid oxidation process of Robusta green coffee beans was characterized during accelerated storage for 20 days at 40 °C, 50 °C, and 60 °C. The conventional oxidation indexes and fatty acid compositions were evaluated, and the shelf life of the green coffee beans was predicted using the Arrhenius model. The acid value, iodine value, peroxide value, total oxidation value, thiobarbituric acid reactive substances, and free fatty acid content increased throughout storage, while the moisture content, p-anisidine value, and unsaturated fatty acid content decreased, which suggests that lipid oxidation occurred during accelerated storage. The predicted shelf life of green coffee bean samples were 57.39 days, 44.44 days, and 23.12 days when stored at 40 °C, 50 °C, and 60 °C, respectively. This study provided scientific evidence of the impact of lipid oxidation on the loss of quality during the accelerated storage of green coffee beans.

Bovine Milk Fats and Their Replacers in Baked Goods: A Review

Milk fats and related dairy products are multi-functional ingredients in bakeries. Bakeries are critical local industries in Western countries, and milk fats represent the most important dietary lipids in countries such as New Zealand. Milk fats perform many roles in bakery products, including dough strengthening, textural softeners, filling fats, coating lipids, laminating fats, and flavor improvers. This review reports how milk fats interact with the ingredients of main bakery products. It also elaborates on recent studies on how to modulate the quality and digestibility of baked goods by designing a new type of fat mimetic, in order to make calorie- and saturated fat-reduced bakery products. It provides a quick reference for both retailers and industrial manufacturers of milk fat-based bakery products.