Simultaneous Quantification of Fat and Water Content in Cheese by TD-NMR

Combined Relaxation Spectra for the Prediction of Meat Quality: A Case Study on Broiler Breast Fillets with the Wooden Breast Condition

This study evaluated the potential of using combined relaxation (CRelax) spectra within time-domain nuclear magnetic resonance (TD-NMR) measurements to predict meat quality. Broiler fillets affected by different severities of the wooden breast (WB) conditions were used as case-study samples because of the broader ranges of meat-quality variations. Partial least squares regression (PLSR) models were established to predict water-holding capacity (WHC) and meat texture, demonstrating superior CRelax capabilities for predicting meat quality. Additionally, a partial least squares discriminant analysis (PLS-DA) model was developed to predict WB severity based on CRelax spectra. The models exhibited high accuracy in distinguishing normal fillets from those affected by the WB condition and demonstrated competitive performance in classifying WB severity. This research contributes innovative insights into advanced spectroscopic techniques for comprehensive meat-quality evaluation, with implications for enhancing precision in meat applications.

The use of time domain 1 H NMR to study proton dynamics in starch-rich foods: A review

Starch is a major contributor to the carbohydrate portion of our diet. When it is present with water, it undergoes several transformations during heating and/or cooling making it an essential structure-forming component in starch-rich food systems (e.g., bread and cake). Time domain proton nuclear magnetic resonance (TD ¹ H NMR) is a useful technique to study starch-water interactions by evaluation of molecular mobility and water distribution. The data obtained correspond to changes in starch structure and the state of water during or resulting from processing. When this technique was first applied to starch(-rich) foods, significant challenges were encountered during data interpretation of complex food systems (e.g., cake or biscuit) due to the presence of multiple constituents (proteins, carbohydrates, lipids, etc.). This article discusses the principles of TD ¹ H NMR and the tools applied that improved characterization and interpretation of TD NMR data. More in particular, the major differences in proton distribution of various dough and cooked/baked food systems are examined. The application of variable-temperature TD ¹ H NMR is also discussed as it demonstrates exceptional ability to elucidate the molecular dynamics of starch transitions (e.g., gelatinization, gelation) in dough/batter systems during heating/cooling. In conclusion, TD NMR is considered a valuable tool to understand the behavior of starch and water that relate to the characteristics and/or quality of starchy food products. Such insights are crucial for food product optimization and development in response to the needs of the food industry.

Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics

Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in “requeijão cremoso” (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial RC types (traditional, light, lactose-free, vegan, and fiber) were analyzed using longitudinal (T₁) and transverse (T₂) relaxation measurements in a wide bore Halbach magnet (0.23 T) with a 100 mm probe. The T₁ and T₂ analyses were performed using CWFP-T₁ (Continuous Wave Free Precession) and CPMG (Carr-Purcell-Meiboom-Gill) single shot pulses. The scores of the principal component analysis (PCA) of CWFP-T₁ and CPMG signals did not show clustering related to the RC types. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler and predictive partial least squares (PLS) calibration models. The best results were obtained with CWFP-T₁ data, with root-mean-square errors of prediction (RMSEP) of 1.38, 4.71, 3.28, and 3.00% for defatted dry mass, fat in the dry and wet matter, and moisture, respectively. Therefore, CWFP-T₁ data modeled with chemometrics can be a fast method to monitor the quality of RC directly in commercial packages.

Single-Laboratory Validation Study of a Rapid TD-NMR Method for Quantitation of Total Fat in Sunflower Oil Powder

BACKGROUND

A rapid total fat quantitation method for sunflower oil powder was developed using time-domain nuclear magnetic resonance (TD-NMR). Currently, industry has three major methods for the total fat quantitation: gravimetric analysis after ether extraction (AOAC Methods 933.05 and 989.05), gas chromatography with flame ionization detector (GC-FID; AOAC Method 996.06), and High-resolution NMR. The gravimetric analysis method takes a day using highly flammable solvents, and the GC-FID method takes two days requiring harsh chemicals for hydrolyzation, extraction, and methylation. The High-resolution NMR spectroscopy method requires simpler sample preparation and shorter analysis time compared to the other two methods. Often, the only required sample preparation step is to dissolve a sample in a solvent. The acquisition time depends on types of analyzing nuclei and sample. The vegetable oil analysis by 13C NMR takes about 4 h per sample. 1H NMR usually takes less time to analyze. In contrast, the TD-NMR relaxometry method takes only 1 h to prepare and analyze samples if the test is for total fat only. The acquisition time is 40 s per sample, and samples are analyzed "as is". A rapid analysis method in a quality control laboratory is very crucial for laboratory efficiency in releasing products. In this paper, a single-laboratory validation study is described for a rapid TD-NMR method to quantitate total fat in sunflower oil powder.

OBJECTIVE

This validation work is to provide documented evidence for the method validity as well as the method performance.

METHOD

The method used a Bruker minispec mq-20 NMR analyzer® with minispec plus® software. A Hahn echo pulse program was used in the method to collect spin echo signal to determine total fat content.

RESULTS

The linearity/range result from 10 standards (0, 21, 42, 63, 83, 92, 100, 108, 117, and 125%) has coefficients of determination (R2) of 1.0000. The 100% level is 1.2 g-fat in 2.5 g sample, which is targeted fat content in a sunflower oil powder raw material. The method is specific for the quantitation of total fat in sunflower oil powder with no background interference from the matrix. The precision result of the 6 replicate samples at 100% level is 0.3% RSD. The accuracies measured from triplicate analysis of 80, 100, and 120% sample matrices are 100, 100, and 100% average recoveries, respectively. The ruggedness of the test method is 0.4% RSD of 12 analysis from 2 analysts (6 results from each analyst) on the different days.

CONCLUSIONS

The test method is proven to be specific, linear, precise, accurate, rugged, and suitable for the intended use of quantitative analysis for total fat in sunflower oil powder.

HIGHLIGHTS

Traditional methods of gravimetric or GC-FID for total fat analysis of raw materials require lengthy sample preparation and experiment time. Laboratory needs to spend a day to perform gravimetric analysis following ether extraction method and 2 days for the GC-FID method. In addition, these test methods use highly flammable and harsh chemicals that generate hazardous chemical wastes. These hazardous wastes are harmful to analysts and environments. In contrast, the TD-NMR method is safe, environmentally friendly, and fast. Therefore, TD-NMR is a preferred method for quality control laboratories.

Effect of the manufacturing process on Fiore Sardo PDO cheese microstructure by multi-frequency NMR relaxometry

The quality of Fiore Sardo cheese, a traditional Italian dairy product, was analyzed by means of Multi-frequency Nuclear Magnetic (NMR) relaxometry. Specifically, ten cheese wheels were purchased from different production chains, either industrial (N = 5) or artisanal (N = 5) samples. The former came from large scale productions and the latter were produced by shepherds in small quantities and in very small dairy factories. A preliminary interlaboratory proficiency testing of Time Domain - NMR (TD-NMR, 20 MHz) relaxometry by five laboratories, consistently showed that product quality is significantly different in terms of molecular mobility according to their production chain (i.e. industrial or artisanal). More detailed information about cheese microstructure was obtained by Multi-frequency Fast Field Cycling NMR (FFC-NMR) at lower magnetic fields (0.01-10 MHz). According to the interpretative model adopted to describe FFC-NMR data, industrially processed cheeses showed a higher para-casein hydration, higher protein protons to water protons ratio and a higher disorder (lower fractal dimension d_f) than artisanal products. It is suggested that differences between artisanal and industrial cheeses generate from the processing steps preceding cheese maturation, and are clearly reflected in the visual appearance of cheeses. This study shows that NMR relaxometry techniques can successfully discriminate Fiore Sardo cheese from different production chains, and paves the way for their implementation in quality control practices of dairy products.

Milk Authentication: Stable Isotope Composition of Hydrogen and Oxygen in Milks and Their Constituents

This paper summarises the isotopic characteristics, i.e., oxygen and hydrogen isotopes, of Slovenian milk and its major constituents: water, casein, and lactose. In parallel, the stable oxygen isotope ratios of cow, sheep, and goat's milk were compared. Oxygen stable isotope ratios in milk water show seasonal variability and are also 18O enriched in relation to animal drinking water. The δ18Owater values were higher in sheep and goat's milk when compared to cow milk, reflecting the isotopic composition of drinking water source and the effect of differences in the animal's thermoregulatory physiologies. The relationship between δ18Omilk and δ18Olactose is an indication that even at lower amounts (>7%) of added water to milk can be determined. This procedure once validated on an international scale could become a reference method for the determination of milk adulteration with water.

Recent developments in the food quality detected by non-invasive nuclear magnetic resonance technology

Nuclear magnetic resonance (NMR) is a rapid, accurate and non-invasive technology and widely used to detect the quality of food, particularly to fruits and vegetables, meat and aquatic products. This review is a survey of recent developments in experimental results for the quality of food on various NMR technologies in processing and storage over the past decade. Following a discussion of the quality discrimination and classification of food, analysis of food compositions and detection of physical, chemical, structural and microbiological properties of food are outlined. Owing to high cost, low detection limit and sensitivity, the professional knowledge involved and the safety issues related to the maintenance of the magnetic field, so far the practical applications are limited to detect small range of food. In order to promote applications for a broader range of foods further research and development efforts are needed to overcome the limitations of NMR in the detection process. The needs and opportunities for future research and developments are outlined.

The effect of buttermilk or buttermilk powder addition on functionality, textural, sensory and volatile characteristics of Cheddar-style cheese

The influence of buttermilk or buttermilk powder addition to cheese milk or cheese curds respectively on cheese functional properties, free fatty acid profiles and subsequent volatile and sensory characteristics was investigated. Buttermilk addition to cheese milk resulted in a softer cheese compared to other cheeses, with a significantly reduced flowability, while buttermilk powder addition had no influence on cheese firmness but cheese flowability was also reduced compared to the control cheese. Larger pools of free fat, higher levels of free fatty acids, volatile compounds and significant differences in sensory profiles associated with off-flavour were also observed with the addition of buttermilk to cheese milk. Application of light microscopy, using toluidine blue stain, facilitated the visualisation of fat globule structure and distribution within the protein matrix. Addition of 10% buttermilk powder resulted in significant increases in volatile compounds originating from proteolysis pathways associated with roasted, green aromas. Descriptive sensory evaluation indicated few differences between the 10% buttermilk powder and the control cheese, while buttermilk cheeses scored negatively for sweaty, barnyard aromas, oxidized and off flavors, correlating with associated volatile aromas. Addition of 10% buttermilk powder to cheese curds results in cheese comparable to the control Cheddar with some variations in volatile compounds resulting in a cheese with similar structural and sensory characteristics albeit with subtle differences in overall cheese flavor. This could be manipulated to produce cheeses of desirable quality, with potential health benefits due to increased phospholipid levels in cheese.

Applications of NMR in dairy research

NMR is a robust analytical technique that has been employed to investigate the properties of many substances of agricultural relevance. NMR was first used to investigate the properties of milk in the 1950s and has since been employed in a wide range of studies; including properties analysis of specific milk proteins to metabolomics techniques used to monitor the health of dairy cows. In this brief review, we highlight the different uses of NMR in the dairy industry.

A new magnetic resonance imaging approach for discriminating Sardinian sheep milk cheese made from heat-treated or raw milk

The evaluation of milk heat treatment on dairy products via reliable analytical methods is a challenging issue that involves both industrial and fundamental research. We describe a new magnetic resonance imaging (MRI) protocol for discriminating Sardinian sheep milk cheese originating from heat-treated or raw milk. Thirty-six samples (18 pecorino cheeses manufactured from heat-treated milk and 18 Fiore Sardo cheeses made from raw milk) were investigated by means of MRI and bi-exponential signal decay analysis. The protocol is capable of discerning cheeses by virtue of the different distribution of the transversal (T2) relaxation time constant. Cheeses from heat-treated milk showed a significantly higher area fraction (≈70-80%), corresponding to the fast relaxing water protons (T2 ≈ 9 ms), compared with raw milk cheeses, whereas the opposite was observed for the long T2 (T2 ≈ 35 ms) proton population. The MRI protocol described is rapid and nondestructive, and it provides statistically significant discrimination between ewe milk cheeses made from heat-treated and raw milk.