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Highlights • Plum tomato oil-in-water emulsions reduce pancreatic lipase activity. • Release of carotenoids into oil droplets is affected by oil content and HPH pressure. • Raman spectroscopy is a rapid method for determination of carotenoids in oil droplets. Abstract Carotenoids are lipophilic compounds that are digested and absorbed along with lipids. Emulsions based on a mixture of plum tomato and red sweet pepper, with 5% or 10% rapeseed oil, were obtained by high pressure homogenization, and the concentration of carotenoids in the emulsion oil droplets was quantified. The fraction of lycopene and beta-carotene released from the plant matrix into the oil droplets was highest in the 10% emulsion, which had larger oil droplets than the 5% emulsion. Xanthophylls were easily released into oil droplets in both 5% and 10% emulsions. The results suggest that the release of carotenoids made available for intestinal absorption depends on carotenoid type and can be significantly improved by increasing the homogenization pressure and oil content. However, in vitro gastrointestinal digestion indicated the presence of constituents or structures in the emulsions, originating from tomato, that reduced pancreatic activity, which may delay micellarization and uptake of carotenoids. [ABSTRACT FROM AUTHOR]

Calanus finmarchicus is a crustacean currently used as a source of marine lipid. The lipids are extracted by enzymatic protein hydrolysis, while the remaining peptide fraction is regarded as a byproduct. In the present work, ten different commercial proteases and endogenous C. finmarchicus proteases were used to produce a set of 63 protein hydrolysates. Protease concentration and hydrolysis time were varied. Hydrolysates were characterized using size-exclusion chromatography and 1H nuclear magnetic resonance spectroscopy. Addition of commercial proteases had unremarkable effect on the yield and molecular weight distribution. This was attributed to the strong impact of endogenous enzymes dominating the hydrolysis process. However, multivariate classification based on 1H NMR spectra revealed subtle variations in composition of hydrolysates produced using different enzymes. The hydrolysates were further evaluated for DPP-IV inhibition and antioxidant activity. The hydrolysates showed significantly higher bioactivity than the unhydrolyzed control. A representative hydrolysate (CaFi55) was fractionated using semipreparative size-exclusion chromatography. A fraction consisting of short peptides with an average chain length of five amino acids (F2) , was identified as a major contributor to the DPP-IV inhibitory activity (IC 50 = 0.70 ± 0.07 mg/mL). [Display omitted] • A total of 63 Calanus finmarchicus hydrolysates were produced and characterized. • SEC and NMR revealed characteristic short peptides and known marine metabolites. • Hydrolysates inhibited DPP-IV enzyme (36–72%) and showed good antioxidant activity. • Low molecular weight fraction inhibited DPP-IV with IC 50 of 0.70 ± 0.07 mg/mL. • Endogenous enzymes were efficient in hydrolysis and yielding bioactive peptides. [ABSTRACT FROM AUTHOR]

[Display omitted] • Processing conditions influence the bioactive properties of protein hydrolysates. • FTIR and SEC fingerprints are correlated with bioactivities of protein hydrolysates. • PLSR models predicted ACE-1 inhibition and DPPH radical scavenging activity. • FTIR-based models were observed to be more robust than SEC-based models. Characterization of protein hydrolysates is a vital step in developing peptide-based bioactive ingredients. Multivariate correlation of chemical fingerprints and bioactivity of poultry by-product protein hydrolysates is explored as a potential analytical strategy for characterization and quality control. Chemical fingerprints of sixty hydrolysates were acquired using Fourier-transform infrared spectroscopy (FTIR) and size exclusion chromatography (SEC). Bioactivities (2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and angiotensin-1-converting enzyme (ACE-1) inhibition) were measured in vitro. Partial least squares regression models based on FTIR fingerprints or SEC chromatograms showed a better prediction performance for ACE-1 inhibition (coefficients of determination (R2) = 0.91, root mean square error of prediction (RMSECV) = 2.8; R2 = 0.85, RMSECV = 3.5, respectively) than for DPPH radical scavenging (R2 = 0.74, RMSECV = 0.3; R2 = 0.75, RMSECV = 0.3, respectively). Such models are promising tools for rapid prediction of bioactivities and as a quality control technology in production of bioactive peptides. [ABSTRACT FROM AUTHOR]

[Display omitted] • The role of thermal inactivation in collagen solubilization during EPH was studied. • Two protases with very different mode of action towards collagen were included. • 180 hydrolysates from different poultry by-products were produced. • Heat assisted solubilization of partly hydrolyzed collagen was assessed. • Sediment removal prior to thermal inactivation is a strategy to tailor hydrolysates. Enzymatic protein hydrolysis (EPH) is an invaluable process to increase the value of food processing by-products. In the current work the aim was to study the role of standard thermal inactivation in collagen solubilization during EPH of poultry by-products. Hundred and eighty hydrolysates were produced using two proteases (stem Bromelain and Endocut-02) and two collagen-rich poultry by-products (turkey tendons and carcasses). Thermal inactivation was performed with and without the sediment to study the effect of heat on collagen solubilization. A large difference in molecular weight distribution profiles was observed when comparing hydrolysate time series of the two proteases. In addition, it was shown that 15 min heat treatment, conventionally used for inactivating proteases, is essential in solubilizing collagen fragments, which significantly contributes to increasing the protein yield of the entire process. The study thus demonstrated the possibility of producing tailored products of different quality by exploiting standard heat inactivation in EPH. [ABSTRACT FROM AUTHOR]

Highlights: [•] Resolution and resolving power are often defined in opposing ways. [•] Resolution is the theoretical ability of the detector. [•] Distinguishability is the ability of the detector achieved in practice. [•] The distinguishability of a detector cannot be better than its resolution. [Copyright &y& Elsevier]

Abstract: In this investigation, the effect of NaCl, KCl and MgSO4 on bovine meat was studied, where the salts were used in standard marinades in 5.5% concentration. The effect of salts on secondary structure of the myofibrillar proteins, protein–water interactions, WHC, and sensory properties of the meat was followed by carrying out FTIR and NIR measurements, cooking loss and sensory analysis. The information obtained by spectroscopic analysis was integrated by using CPCA. This revealed that MgSO4 increased ratio of α-helices and C O and NH groups (followed by FTIR) that are involved in H-bonding with surrounding water molecules (followed by NIR). This was also supported by increased WHC. Conversely, KCl reduced WHC of meat and was correlated to non-hydrogenated C O and NH groups. Furthermore, the sensory analysis confirmed that MgSO4 was acceptable only when the share of this salt in the mixture was one third. [Copyright &y& Elsevier]

Abstract: In this paper a combination of NIR spectroscopy and FTIR and Raman microspectroscopy was used to elucidate the effects of different salts (NaCl, KCl and MgSO4) on structural proteins and their hydration in muscle tissue. Multivariate multi-block technique Consensus Principal Component Analysis enabled integration of different vibrational spectroscopic techniques: macroscopic information obtained by NIR spectroscopy is directly related to microscopic information obtained by FTIR and Raman microspectroscopy. Changes in protein secondary structure observed at different concentrations of salts were linked to changes in protein hydration affinity. The evidence for this was given by connecting the underlying FTIR bands of the amide I region (1700–1600cm−1) and the water region (3500–3000cm−1) with water vibrations obtained by NIR spectroscopy. In addition, Raman microspectroscopy demonstrated that different cations affected structures of aromatic amino acid residues differently, which indicates that cation–π interactions play an important role in determination of the final structure of protein molecules. [Copyright &y& Elsevier]

Abstract: In this paper, we extend the concept of cross model validation (CMV) to multiple X and Y variables where different spectroscopic techniques serve as X and Y data in a regression context. For the first dataset on marzipan samples the main objective was to find significant regions in the spectral data, and to discuss the issue of false discovery, i.e. combinations of variables that erroneously are found to be significant. A permutation test within the framework of CMV showed that no regression coefficients in the partial least squares regression (PLSR) model between FT-IR and VIS/NIR spectra show significance at the 5% level. We believe the reason is that the CMV acts as strong filter towards spurious correlations. Corresponding CH- and OH-bands between FT-IR and NIR spectra gave significant regions. For the second dataset, the results from CMV are interpreted more in detail with chemical background knowledge in mind. Most of the significant regions found between the Raman and NIR spectra could be interpreted from the chemical composition of the oil mixtures. Some regions were more difficult to interpret, which could be due to systematic baseline effects in the NIR data. [Copyright &y& Elsevier]

• Non-destructive determination of SSC and sugars in apples by Raman spectroscopy. • Apple analysis at three steps: intact apples, apples without skins and juices. • Measurements thought skin were possible at least 1.0 cm in deep. • Regression coefficients highlighted identifiable Raman bands related to the target sugars. This study reports the feasibility of using Raman spectroscopy for quantification of soluble solids and individual sugars in apples. Six different commercial apple varieties were measured by Raman spectroscopy at three different steps: 1) Intact apples with skin, 2) apples without skin and 3) juices obtained from apples. Results indicated that it is possible to measure Raman signals to a depth of 8 mm into the apple with a wide area Raman probe. Multivariate calibration models were established to evaluate how well Raman spectra can be used to estimate the quality parameters SSC (%), total sugars, glucose, fructose and sucrose. Estimation accuracy for SSC was comparable with what is achievable with near-infrared spectroscopy: Root mean square error of cross-validation (RMSECV) = 0.66, 0.46 and 0.72 % and coefficients of determination (R2) = 0.70, 0.85 and 0.63 for intact apples, apples without skin and juices, respectively. Sucrose and glucose were well estimated with RMSECV of 2.8, 1.9, 2.1 mg/mL for glucose and 5.8, 3.9 and 3.7 mg/mL for sucrose, for the three sample cases, respectively. Coefficient of determination was higher than 0.82 for all models. Regression coefficients for all calibration models highlighted identifiable Raman bands that could be related to the target sugars. [ABSTRACT FROM AUTHOR]

• New SEC -based method was applied for estimation of protein digestibility. • SEC enables quantitative comparisons of protein digestibility in different foods. • The method gives insight into protein solubilization and breakdown during digestion. • The proposed SEC based methodology is reproducible and easy to perform. While the harmonized INFOGEST model provides a physiologically relevant platform for simulated digestion, it needs to be combined with adequate analytical methods to enable quantification and comparison of protein digestibility in different food matrices. We have shown that size exclusion chromatography (SEC) can be used to estimate the proportion of small peptides potentially available for uptake. Combined with determination of total dissolved protein, the % of small peptides per total protein was calculated as a physiologically relevant estimate of protein digestibility (D SEC). Values for D SEC differed for casein (87.6%), chicken mince (72.6%), heated pea protein concentrate (67.8%), bread (63%), beef entrecote (57.7%) and pea protein concentrate (57.8%). In contrast to existing methods (TCA soluble protein, free NH 2 -groups), the proposed SEC based method gives separate insight into the two fundamental processes during protein digestion (solubilization and break-down), while maintaining the ability to rank digestibility of very different food proteins. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to investigate if Raman spectra recorded at the exact same position as drip loss measurements could improve prediction of drip loss in pork. One ventral and one dorsal cylindrical plug, cut from a standardized slice from Longissimus lumborum , were used to determine drip loss by EZ-DripLoss method and to collect Raman spectra, while ultimate pH was measured at another location. Partial least squares regression models were developed using spectra from each plug individually or averaged spectra from both plugs. The best models used spectra from the ventral plug, resulting in r cv 2=0.75, root mean square error of cross-validation (RMSECV) = 1.27% and ratio of prediction to deviation (RPD) =2.0 for EZ-DripLoss and r cv 2=0.72, RMSECV = 0.05 and RPD = 2.0 for ultimate pH. Results indicate that Raman spectroscopy can be used for rough screening of drip loss and pH in pork, and that the location chosen for collection of spectra can be very important for successful predictions. [ABSTRACT FROM AUTHOR]

• DH% and M w were monitored during enzymatic protein hydrolysis of dairy proteins. • Intercorrelation of DH% vs M w were studied for 60 milk protein hydrolysates. • A PLSR model was developed for prediction of DH% based on molecular weight distribution profiles. • A multivariate model based on dry-film FTIR was developed for dual prediction of DH% and M w. Fourier-transform infrared (FTIR) spectroscopy was applied to predict the degree of hydrolysis (DH%) and weight-average molecular weight (M w) in milk protein hydrolysates. Both DH% and M w are important quality parameters of protein hydrolysates. Measuring these parameters and following their development during proteolytic reactions is therefore essential for process control and optimization in industry. In the present study the intercorrelation and the complimentary nature of these parameters were investigated and a partial least squares regression (PLSR) model was developed for the prediction of DH% from molecular weight distributions. Finally, we developed PLSR models based on dry-film FTIR spectroscopy for the prediction of both DH% and M w. Here spectral changes in the amide region were found to be important for the two calibration models, underlining the advantage of dry-film FTIR measurement. This shows that dry-film infrared spectroscopy is a promising tool for dual prediction of DH% and M w. [ABSTRACT FROM AUTHOR]

Highlights • A rapid method for color quality measurement in paprika was developed. • Raman spectroscopy with a 785 nm laser excitation was applied in paprika powder. • Non-adulterated samples were discriminated from Sudan I adulterated samples by PLS-DA. Abstract The aim of this study was developing a non-destructive method for the determination of color in paprika powder as well as for detecting possible adulteration with Sudan I. Non-destructive Raman spectroscopy was applied directly to paprika powder employing a laser excitation of 785 nm for the first time. The fluorescence background was estimated, by fitting a polynomial to each spectrum, and then subtracted. After preprocessing the spectra, some peaks were clearly identified as characteristic from pigments present in paprika. The preprocessed Raman spectra were correlated with the ASTA color values of paprika by partial least squares regression (PLSR). Twenty-five paprika samples were adulterated with Sudan I at different levels and the PLSR model was also obtained. The coefficients of determination (R2) were 0.945 and 0.982 for ASTA and Sudan I concentration, respectively, and the root mean square errors of prediction (RMSEP) were 8.8 ASTA values and 0.91 mg/g, respectively. Finally, different approaches were applied to discriminate between adulterated and non-adulterated samples. Best results were obtained for partial least squares – discriminant analysis (PLS-DA), allowing a good discrimination when the adulteration with Sudan I was higher than 0.5%. [ABSTRACT FROM AUTHOR]

Industries are continuously looking for dedicated sensor solutions for evaluating the chemical composition of products that can provide valuable insights into process control, process optimization, and product quality. A rapid and robust analytical method, Fourier-Transform Infrared (FTIR) spectroscopy, holds significant potential in this regard as it provides detailed compositional values of food nutrients. The main aim of the present study was to use dry film FTIR spectroscopy as an analytical tool to characterize products from an industrial enzymatic protein hydrolysis process and link this to understand industrial process variations. For this purpose, 463 protein hydrolysate samples were obtained from an industrial enzymatic protein hydrolysis plant. In the same period, systematic variations in process parameters such as raw material composition, enzyme type, and water addition, were performed. All samples were analyzed using dry film FTIR spectroscopy. Two subsets containing 200 and 68 hydrolysate samples were chosen for measuring average molecular weight (AMW) and collagen content respectively, providing reference data for constructing calibration models based on partial least squares regression (PLSR). The percentage of low molecular weight constituents was derived from the molecular weight distribution of size exclusion chromatograms of protein hydrolysates and also used in the modeling. Calibration models for the prediction of AMW, low molecular weight constituents, and collagen content were obtained with a good fit and lower estimation errors. Principal component analysis (PCA) of protein hydrolysates' FTIR spectra effectively differentiated process variations (enzyme types and raw materials) without extensive reference analysis. One-factor analysis of variance (ANOVA) tests was used to observe the impact of process variation on product quality. FTIR proved to be a sensitive method for liquid protein analysis and process control with a significant potential in process optimization approaches. To the authors' knowledge, this is the first time dry film FTIR spectroscopy has been used to evaluate an industrial bioprocess with designed process variations. [Display omitted] • Dry film FTIR was used to evaluate an industrial bioprocess with process variations. • Dry film FTIR can be used to characterize industrial protein hydrolysate quality. • FTIR calibration models were built with low estimation errors for three parameters. • FTIR spectroscopy was successfully used to comprehend industrial process variations. [ABSTRACT FROM AUTHOR]

[Display omitted] • Raw material and protease have major effects on product composition and quality, but impact vary with product quality studied. • Protein yield, proximate composition and bioactivity are more affected by protease than by raw material variations. • Raw material variations affect peptide size distribution and amino acid composition in protein fractions, exemplified by EAA values. The aim of this study was to investigate the role of compositional variations in side-streams from the chicken and turkey industry on product characteristics after enzymatic protein hydrolysis (EPH). Variation was obtained using four raw materials, namely chicken and turkey carcasses, and mechanically deboned chicken and turkey residues. Alcalase 2.4 L, Corolase 2TS and Flavourzyme, three commercial proteases with different specificities, were used to investigate impact of protease choice on product characteristics. Besides protein yield, effects on product characteristics such as nutrient and amino acid composition, size distribution of peptides, degree of hydrolysis (DH%), rheological properties, and angiotensin-I-converting enzyme (ACE) inhibition, were investigated. Results show that choice of protease and industrially relevant variations in poultry raw material composition both have major effect on product composition and the other quality parameters studied. Protein yield, proximate composition, and bioactivity were more affected by protease than raw material variation. Raw material variation had a bigger impact on quality parameters such as peptide size distribution and amino acid composition, exemplified by the sum of essential amino acids. This means that raw material variation should be handled and accounted for to realize the true potential that exists in tailor-making EPH products with specified properties for targeted applications. [ABSTRACT FROM AUTHOR]

Abstract According to European food safety authorities, one of the major control parameters for mechanically separated meat is calcium content, which is an indicator of residual bone. Residual bone in mechanically separated meat can also be measured as total ash content. Despite the need to measure both ash and/or calcium content of mechanically separated meat, there is no rapid analytical technique that can be used in an industrial environment. In the current study, we are presenting the first application of Raman spectroscopy as a rapid tool for estimating calcium and ash contents in bone and meat mixtures from mechanical deboning of chicken meat. Raman-based partial least squares regression models were developed for prediction of both ash and calcium content in 79 samples gathered from four different production days. Two different data pre-processing methods, i.e., polynomial background fitting and extended multiplicative scatter correction with polynomial extension, were applied to the raw Raman data and the prediction models were compared. The prediction model based on EMSC treated data afforded the lowest root mean square error of cross-validation (RMSECV = 0.333 g/100 g for calcium and RMSECV = 0.634 g/100 g for ash) and the highest coefficient of determination (R2 = 0.775 for calcium and R2 = 0.894 for ash). Highlights • Raman study of residual bone minerals in mechanically deboned chicken meat. • Calcium and ash content of samples from mechanical chicken deboning were studied. • Raman-based PLSR models were developed for prediction of calcium and ash content. • Prediction models were compared for two pre-processing strategies. [ABSTRACT FROM AUTHOR]