Verifying origin claims on dairy products using stable isotope ratio analysis and random forest classification.

Scientifically underpinning geographic origin claims will improve consumer trust in food labels. Stable isotope ratio analysis (SIRA) is an analytical technique that supports origin verification of food products based on naturally occurring differences in isotopic compositions. SIRA of five relevant elements (C, H, N, O, S) was conducted on casein isolated from butter (n = 60), cheese (n = 96), and whole milk powder (WMP) (n = 41). Samples were divided into four geographic regions based on their commercial origin: Ireland (n = 79), Europe (n = 67), Australasia (n = 29) and USA (n = 22). A random forest machine learning model built using δ13C, δ2H, δ15N, δ18O and δ34S values of all products (n = 197) accurately (88% model accuracy rate) predicted the region of origin with class accuracy of 95% for Irish, 84% for European, 71% for Australasia, and 94% for US products.

Effect of different botanically-diverse diets on the fatty acid profile, tocopherol content and oxidative stability of beef.

BACKGROUND: Beef from pasture-fed animals is viewed as a healthier and more welfare-friendly alternative to concentrate-fed beef. Botanically-diverse pastures consisting of numerous plant species may alter the fatty acid (FA) profile and the tocopherol content of beef, as well as the oxidative stability of the meat. In the present study, steers were assigned to one of three botanically-diverse diets: perennial ryegrass (PRG), perennial ryegrass + white clover (PRG + WC) or multi-species (MS), all with a finishing diet of the respective botanically-diverse silages plus a cereal-based concentrate, consistent with production systems in Ireland. The FA profile, tocopherol content, oxidative stability and colour of meat during storage were measured. RESULTS: Compared to the other diets, the MS diet resulted in higher proportions of linolenic acid (C18:3n-3c), linoleic acid (C18:2n-6c) and total polyunsaturated fatty acids (PUFA), with higher PUFA:saturated fatty acid and n-6:n-3 ratios in the meat. α-Tocopherol concentrations were lowest in the meat of animals from the MS diet. In uncooked meat, lipid oxidation and colour values were affected by storage time across all diets, whereas the MS diet led to higher hue values only on day 14 of storage. When cooked, meat from animals on PRG + WC and MS diets had higher lipid oxidation on days 1 and 2 of storage than meat from animals on the PRG diet. CONCLUSION: Feeding steers on a botanically-diverse diet consisting of six plant species can improve the n-3 FA and PUFA concentration of beef, affecting the susceptibility of cooked, but not uncooked, beef to oxidation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Isolation of casein for stable isotope ratio analysis of butter, cheese, and milk powder.

RATIONALE: Stable isotope ratio analysis (SIRA) is commonly used for the authentication of dairy commodities, providing evidence to support the geographical origin and production background of products. We set out to optimise methods for the isolation of a common constituent (casein) from three dairy commodities, which would permit easier inter- and intra-commodity comparisons following SIRA. METHODS: Three published methods for isolation of protein (from cheese, milk, and butter) were adapted to yield protein (casein) fractions from commercial cheddar cheese, whole milk powder (WMP), and butter samples with a high degree of purity for subsequent SIRA. The casein fractions isolated underwent elemental analysis (H, C, and N), protein determination, and some also underwent SIRA of O and S. Two-way analysis of variance and Tukey post hoc comparisons tested differences between methods. RESULTS: For each product, an optimised casein isolation method was chosen based on the C/N ratio and protein content. An optimum solvent lipid extraction (petroleum spirit-diethyl ether (2:1)) and casein precipitation method was chosen for cheddar cheese casein. A final solvent lipid extraction (heptane-isopropanol (3:2)) was necessary for WMP and butter casein extraction. δ13 C and δ2 H values validated the methods' abilities to remove contaminating lipid and isolate pure casein. CONCLUSIONS: Casein of high purity, for subsequent SIRA, can be isolated from cheddar cheese, WMP, and butter following modifications of previously published methods.

Does Finishing at Pasture Influence the Colour of Muscle from Suckler Bulls and Can Colour Be Used to Authenticate Their Pre-Slaughter Diet?

The primary objective of this study was to compare the colour of muscle from bulls finished at pasture or indoors on a high concentrate diet. The ancillary objectives were to identify possible explanations for any differences in the colour observed and the potential of muscle colour to discriminate between bull beef from different production systems. Growth, longissimus muscle colour, fibre type composition and metabolic profile were measured in late-maturing breed sired suckler bulls slaughtered at 19 months of age after 199 days at pasture (G0), 100 days indoors after 98 days at pasture (G0AL) and indoors for 199 days (AL). When compared to bulls finished indoors and offered a high concentrate ration, the carcass weight of G0 bulls was lower, their carcasses were leaner, and their longissimus muscle was similar in lightness but less red and had a lower glycolytic metabolism. The temperature at which the longissimus muscle reached pH 6.0 was lower (19.7 °C) for G0 than for G0AL (29.9 °C) and AL (31.6 °C), which did not differ. Co-variate adjustment for this variable removed the differences in redness. Adjusting the chill settings appears to be a practical strategy for abattoirs to minimise early post-mortem differences in muscle colour between lighter grass-fed and heavier concentrate-fed carcasses. The preliminary results demonstrate the potential of both L*, a*, b* values and the visible reflectance spectra of muscle to discriminate between grass- finished and concentrate-finished bull beef, but further refinement and validation of the models is required.

Prediction of Warner-Bratzler shear force, intramuscular fat, drip-loss and cook-loss in beef via Raman spectroscopy and chemometrics.

Rapid prediction of beef quality remains a challenge for meat processors. This study evaluated the potential of Raman spectroscopy followed by chemometrics for prediction of Warner-Bratzler shear force (WBSF), intramuscular fat (IMF), ultimate pH, drip-loss and cook-loss. PLS regression models were developed based on spectra recorded on frozen-thawed day 2 longissimus thoracis et lumborum muscle and validated using test sets randomly selected 3 times. With the exception of ultimate pH, models presented notable performance in calibration (R2 ranging from 0.5 to 0.9; low RMSEC) and, despite variability in the results, promising predictive ability: WBSF (RMSEP ranging from 4.6 to 9 N), IMF (RMSEP ranging from 0.9 to 1.1%), drip-loss (RMSEP ranging from 1 to 1.3%) and cook-loss (RMSEP ranging from 1.5 to 2.9%). Furthermore, the loading values indicated that the physicochemical variation of the meat influenced the models. Overall, results indicated that Raman spectroscopy is a promising technique for routine quality assessments of IMF and drip-loss, which, with further development and improvement of its accuracy could become a reliable tool for the beef industry.

Laser-induced breakdown spectroscopy (LIBS) for rapid analysis of ash, potassium and magnesium in gluten free flours.

Gluten free (GF) diets are prone to mineral deficiency, thus effective monitoring of the elemental composition of GF products is important to ensure a balanced micronutrient diet. The objective of this study was to test the potential of laser-induced breakdown spectroscopy (LIBS) analysis combined with chemometrics for at-line monitoring of ash, potassium and magnesium content of GF flours: tapioca, potato, maize, buckwheat, brown rice and a GF flour mixture. Concentrations of ash, potassium and magnesium were determined with reference methods and LIBS. PCA analysis was performed and presented the potential for discrimination of the six GF flours. For the quantification analysis PLSR models were developed; R2cal were 0.99 for magnesium and potassium and 0.97 for ash. The study revealed that LIBS combined with chemometrics is a convenient method to quantify concentrations of ash, potassium and magnesium and present the potential to classify different types of flours.

Quantification of copper content with laser induced breakdown spectroscopy as a potential indicator of offal adulteration in beef.

Laser induced breakdown spectroscopy (LIBS) is an emerging technique in the field of food analysis which provides various advantages such as minimal sample preparation, chemical free, rapid detection, provision of spatial information and portability. In this study, LIBS was employed for quantitative analysis of copper content in minced beef samples spiked with beef liver over three independent batches. Copper content was determined with graphite furnace atomic absorption spectroscopy (GFAAS) in order to obtain reference values for modelling. Partial least square regression (PLSR) was performed to build a calibration and validation model. A calibration model with a high Rcv2 of 0.85 and a RMSECV of 43.5ppm was obtained, confirming a good fit for the model. The validation model showed a good prediction accuracy with a high Rp2 of 0.85 and RMSEP of 36.8ppm. Moreover, on a further study to evaluate the spatial capabilities, LIBS was able to successfully map copper content within a pellet, indicating the suitability of LIBS to provide spatial information and therefore potential use on heterogeneous samples. Overall, it can be concluded that LIBS combined with chemometrics demonstrates potential as a quality monitoring tool for the meat processing industry.

Multipoint NIR spectroscopy for gross composition analysis of powdered infant formula under various motion conditions.

Powdered infant formula (PIF) is a worldwide, industrially produced, human milk substitute. Manufacture of PIF faces strict quality controls in order to ensure that the product meets all compositional requirements. Near-infrared (NIR) spectroscopy is a rapid, non-destructive and well-qualified technique for food quality assessments. The use of fibre-optic NIR sensors allows measuring in-line and at real-time, and can record spectra from different stages of the process. The non-contact character of fibre-optic sensors can be enhanced by fitting collimators, which allow operation at various distances. The system, based on a Fabry-Perot interferometer, records four spectra concurrently, rather than consecutively as in the "quasi-simultaneous" multipoint NIR systems. In the present study, a novel multipoint NIR spectroscopy system equipped with four fibre-optic probes with collimators was assessed to determine carbohydrate and protein contents of PIF samples under static and motion conditions (0.02, 0.15 and 0.30m/s) to simulate possible industrial scenarios. Best results were obtained under static conditions providing a R(2) of calibration of 0.95 and RMSEP values of 1.89%. Yet, considerably low values of RMSEP, for instance 2.70% at 0.15m/s, were provided with the in-motion predictions, demonstrating the system's potential for in/on-line applications at various levels of speed. The current work also evaluated the viability of using general off-line calibrations developed under static conditions for on/in-line applications subject to motion. To this end, calibrations in both modes were developed and compared. Best results were obtained with specific calibrations; however, reasonably accurate models were obtained with the general calibration. Furthermore, this work illustrated independency of the collimator-probe setup by characterizing PIF samples simultaneously recorded according to their carbohydrate content, even when measured under different conditions. Therefore, the improved multipoint NIR approach constitutes a potential in/on-line tool for quality evaluation of PIF over the manufacturing process.

Multipoint near-infrared spectrometry for real-time monitoring of protein conformational stability in powdered infant formula.

Powdered infant formula (PIF) can be the sole source of nutrition for babies and infants. Monitoring conformational changes in protein during manufacture of PIF is critical in order to maintain its nutritional value. This study presents the development of a calibration model for monitoring conformational changes in PIF protein by applying a novel multipoint near-infrared (NIR) spectrometry. NIR spectra were collected for PIF and PIF proteins, casein and whey protein isolate, before and after heat treatment. Results show that principal component analysis showed discrimination between native protein at room temperature and protein conformational changes caused at elevated temperature. Partial least squares regression analysis showed good calibration models with correlation coefficients ranging between 87% and 99% for the prediction of protein quality. This novel multipoint NIR spectrometry could serve as a simple in-line tool to rapidly monitor protein quality during processing stages, contributing to product nutritional value.