Preliminary investigation of the application of Raman spectroscopy to the prediction of the sensory quality of beef silverside

Performance and protein conformation of thermally treated silver carp (Hypophthalmichthys molitrix) and scallop (Argopecten irradians) blended gels

BACKGROUND

The quality of surimi-based products can be improved by combining the flesh of different aquatic organisms. The present study investigated the effects of incorporating diverse ratios of unwashed silver carp (H) and scallop (A) and using various thermal treatments on the moisture, texture, microstructure, and conformation of the blended gels and myofibrillar protein of surimi.

RESULTS

A mixture ratio of A:H = 1:3 yielded the highest gel strength, which was 60.4% higher than that of scallop gel. The cooking losses of high-pressure heating and water-bath microwaving were significantly higher than those of other methods (P < 0.05). Moreover, the two-step water bath and water-bath microwaving samples exhibited a more regular spatial network structure compared to other samples. The mixed samples exhibited a microstructure with a uniform and ordered spatial network, allowing more free water to be trapped by the internal structure, resulting in more favorable gel properties. The thermal treatments comprehensively modified the tertiary and quaternary structures of proteins in unwashed mixed gel promoted protein unfurling, provided more hydrophobic interactions, enhanced protein aggregation and improved the gel performance.

CONCLUSION

The findings of the present study improve our understanding of the interactions between proteins from different sources. We propose a new method for modifying surimi's gel properties, facilitating the development of mixed surimi products, as well as enhancing the efficient utilization of aquatic resources. © 2024 Society of Chemical Industry.

Myofibrillar proteins' intermolecular interaction weakening and degradation: Are they mainly responsible for the tenderization of meat containing l-arginine, l-lysine, or/and NaCl?

This study explored the effects of l-arginine, l-lysine, and NaCl alone and in combination on the tenderness of porcine meat. Arg, Lys, and NaCl alone improved the tenderness, decreased the cooking loss, and increased the myofibrillar fragmentation index (MFI) of porcine meat; Both Arg and Lys cooperated with NaCl to better achieve this effect. Furthermore, Arg/Lys collaborated with NaCl to increase muscle fiber swelling and moisture content of the meat and promoted the extraction of main myofibrillar proteins. FT-IR revealed that Arg, Lys, or NaCl alone or in combination caused changes in protein-water interactions. Western blotting revealed varying degrees of meat protein degradation in all cases, but the results did not well coincide with those of shear force and the MFI. Therefore, the weakening of intermolecular forces between myofibrillar proteins was considered the main reason for meat tenderization under the present study conditions.

Rapid Non-Destructive Detection Technology in the Field of Meat Tenderness: A Review

Traditionally, tenderness has been assessed through shear force testing, which is inherently destructive, the accuracy is easily affected, and it results in considerable sample wastage. Although this technology has some drawbacks, it is still the most effective detection method currently available. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into applying five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of the quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations to guide the future direction of non-destructive, AI-enhanced meat tenderness detection.

A comprehensive study of sous-vide cooked Korat chicken breast processed by various conditions: texture, compositional/structural changes, and consumer acceptance

Korat chicken (KC) is a slow-growing crossbreed renowned for its excellent growth and firm texture. This study investigated the effect of various sous-vide (SV) conditions (60 and 70°C, 1-3 h) on their texture, protein structure and degradation, as well as consumer acceptability, with the traditional boiling served as control. Texture showed significant improvement under all SV conditions compared to the control, as demonstrated by increased water holding capacity (WHC), cooking loss, and decreased shear force, hardness, and chewiness (P < 0.05). These changes corresponded to the higher sensory scores (P < 0.05). Among the SV samples, increased temperatures and longer cooking times led to higher degradation of myofibrils and connective tissue, as evidenced by a decrease in water-, salt-soluble proteins, and soluble collagen (P < 0.05). These findings aligned with the scanning electron microscopy (SEM) results, which showed a looser muscle structure in the meat under more intense cooking conditions. Based on synchrotron radiation-based Fourier transform infrared (SR-FTIR) results, a gradual increase in antiparallel forms within the amide I bands (1,700-1,600 cm-1) of the total spectra with higher temperature and longer cooking times was observed (P < 0.05), while the fluctuations were observed in the changes of α-helix, β-sheet, and β-turn structures. This suggested that the antiparallel structure represented a looser configuration developing during intense SV cooking. Combined with the principal component analysis (PCA) results, the findings indicated that the suitable SV condition for KC breast meat was 70°C for varying durations (1-3 h), as it showed the strongest correlation with sensory scores, particularly in terms of tenderness. In summary, these findings provided a better understanding of molecular changes and discovered SV conditions to enhance the texture quality of the KC meat.

Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review

Muscle foods, valued for their significant nutrient content such as high-quality protein, vitamins, and minerals, are vulnerable to adulteration and fraud, stemming from dishonest vendor practices and insufficient market oversight. Traditional analytical methods, often limited to laboratory-scale., may not effectively detect adulteration and fraud in complex applications. Raman spectroscopy (RS), encompassing techniques like Surface-enhanced RS (SERS), Dispersive RS (DRS), Fourier transform RS (FTRS), Resonance Raman spectroscopy (RRS), and Spatially offset RS (SORS) combined with chemometrics, presents a potent approach for both qualitative and quantitative analysis of muscle food adulteration. This technology is characterized by its efficiency, rapidity, and noninvasive nature. This paper systematically summarizes and comparatively analyzes RS technology principles, emphasizing its practicality and efficacy in detecting muscle food adulteration and fraud when combined with chemometrics. The paper also discusses the existing challenges and future prospects in this field, providing essential insights for reviews and scientific research in related fields.

Effects of microwave processing in comparison to sous vide cooking on meat quality, protein structural changes, and in vitro digestibility

This study investigated the effect of industrial microwave (MW) processing, and sous vide (SV) on goat and lamb biceps femoris, where samples were cooked to the same tenderness. The cooked meat quality and ultrastructure were analyzed along with determining the protein surface hydrophobicity, particle size distribution, secondary structure, and protein digestibility. MW-processing resulted in higher cooking loss and more ultrastructural damage than SV and also induced higher myofibrillar protein surface hydrophobicity. Both processes caused a significant increase (p < 0.05) in the β-sheet and an increase in the random coils with a reduction (p < 0.05) in α-helix and β-turns. Both processes led to different protein hydrolysis patterns (observed through SDS-PAGE), but overall free amino N release after digestion was not significantly different among them. The results suggest that MW and SV modify meat protein structure differently, but with the same meat tenderness level, these processes can lead to similar overall protein digestibility.

Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy

OBJECTIVE

This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle.

METHODS

Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups.

RESULTS

Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm-1, suggests that the content of this amino acid could explain the differences between samples.

CONCLUSION

Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.

Characterization of the physiochemical properties, microstructure, and molecular interactions of a novel rice-pea protein gel

The application of rice and pea proteins in food production is limited due to their undesirable processing performance. The objective of this research was to develop a novel rice-pea protein gel using alkali-heat treatment. This gel had a higher solubility, stronger gel strength, better water retention capacity, and denser bilayer network. This is due to the alkali-heat induced modifications for the secondary structures of proteins (i.e., a decrease in the α-helix, and an increase in the β-sheets) and the interactions between protein molecules. The network structure of gel was more compact by adding 2% and 4% alkali-heat rice protein (AH-RP). This resulted in a stable double-layer network structure of gel. Adding 4% AH-RP significantly improved the hardness and elasticity of gel. This gel will have a good potential use for being the ingredient to produce the functional foods and meat analogs.

Heating temperatures affect meat quality and vibrational spectroscopic properties of slow- and fast-growing chickens

This study determined the effect of water bath cooking (70°C and 90°C for 40 min) and the extreme heat treatment by an autoclave (121°C for 40 min) on the quality of breast meat of a fast-growing chicken, commercial broiler (CB), and slow-growing chickens, Korat chicken (KC), and Thai native chicken (NC) (Leung Hang Khao), by vibrational spectroscopic techniques, including synchrotron radiation-based Fourier transform infrared (SR-FTIR) microspectroscopy and Fourier transform Raman (FT-Raman) spectroscopy. Taste-enhancing compounds, including inosine-5'-monophosphate (IMP) and guanosine-5'-monophosphate (GMP), were better retained in cooked KC and NC meats than in cooked CB meat (P < 0.05). The high heat treatment at 121°C depleted the amount of insoluble collagen in all breeds (P < 0.05). Shear force values of slow-growing chicken meat were not affected by high heating temperatures (P > 0.05). In addition, the high heat treatment increased protein carbonyl (P < 0.05), while no effect on in vitro protein digestibility (P > 0.05). SR-FTIR microspectroscopy performed better in differentiating the meat quality of different chicken breeds, whereas FT-Raman spectroscopy clearly revealed differences in meat qualities induced by heating temperature. Based on principal component analysis (PCA), distinct characteristics of chicken meat cooked at 70°C were high water-holding capacity, lightness (L*), moisture content, and predominant α-helix structure, correlating with Raman spectra at 3,217 cm^-1 (O-H stretching of water) and 1,651 cm^-1 (amide I; α-helix). The high heating temperature at 90°C and 121°C exposed protein structure to a greater extent, as evidenced by an increase in β-sheets, which was well correlated with the Raman spectra at 2,968 and 2,893 cm^-1 (C-H stretching), tryptophan (880 cm^-1), tyrosine (858 cm^-1), and 1,042, 1,020, and 990 cm^-1 (C-C stretching; β-sheet). SR-FTIR and FT-Raman spectroscopy show potential for differentiation of chicken meat quality with respect to breeds and cooking temperatures. The marked differences in wavenumbers would be beneficial as markers for determining the quality of cooked meats from slow- and fast-growing chickens.

Preliminary investigation into the prediction of indicators of beef spoilage using Raman and Fourier transform infrared spectroscopy

The objective of this study was to assess the potential to predict the microbial beef spoilage indicators by Raman and Fourier transform infrared (FT-IR) spectroscopies. Vacuum skin packaged (VSP) beef steaks were stored at 0 °C, 4 °C, 8 °C and under a dynamic temperature condition (0 °C ∼ 4 °C ∼ 8 °C, for 36 d). Total viable count (TVC) and total volatile basic nitrogen (TVB-N) were obtained during the storage period along with spectroscopic data. The Raman and FTIR spectra were baseline corrected, pre-processed using Savitzky-Golay smoothing and normalized. Subsequently partial least squares regression (PLSR) models of TVC and TVB-N were developed and evaluated. The root mean squared error (RMSE) ranged from 0.81 to1.59 (log CFU/g or mg/100 g) and the determination coefficient (R²) from 0.54 to 0.75. The performance of PLSR model based on data fusion (combination of Raman and FT-IR data) is better than that based on Raman spectra and similar to that of FT-IR. Overall, Raman spectroscopy, FT-IR spectroscopy, and a combination of both exhibited a potential for the prediction of the beef spoilage.

Investigating the Effect of Various Sous-Vide Cooking Conditions on Protein Structure and Texture Characteristics of Tilapia Fillet Using Synchrotron Radiation-Based FTIR

The effects of various sous-vide (SV) cooking conditions (50-60℃, 30-60 min) on physicochemical properties related to the texture characteristics, protein structure/degradation, and sensory acceptability of tilapia fillet (Oreochromis niloticus) were investigated. With an increasing temperature and processing time of SV cooking, protein degradation (of both myofibrils and connective tissue) was more pronounced, as evaluated by the decrease in water- and salt-soluble proteins, total collagen, as well as the changes in the ratio of secondary protein structures (α-helix, β-sheet, β-turn, etc.), which were determined by synchrotron-FTIR (SR-FTIR). These degradations were associated with the improvement of meat tenderness, as estimated by shear force and texture profile analyzer (TPA) results. Among all SV conditions, using 60 ℃ for 45 min seems to be the optimal condition for tilapia meat, since it delivered the best results for texture characteristics and acceptability (p < 0.05). Moreover, principal component analysis (PCA) results clearly demonstrated that the highest texture-liking score of this condition was well associated with the intensity of β-sheets, which seem to be the crucial component that affected the texture of SV-cooked tilapia more so than other parameters. The findings demonstrated the potential of SR-FTIR to decipher the biomolecular structure, particularly the secondary protein structure, of SV-cooked tilapia. This technique provided essential information for a better understanding of the changes in biomolecules related to the textural characteristics of this product.

Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review

With the continuous development of economy and the change in consumption concept, the demand for meat, a nutritious food, has been dramatically increasing. Meat quality is tightly related to human life and health, and it is commonly measured by sensory attribute, chemical composition, physical and chemical property, nutritional value, and safety quality. This paper surveys four types of emerging non-destructive detection techniques for meat quality estimation, including spectroscopic technique, imaging technique, machine vision, and electronic nose. The theoretical basis and applications of each technique are summarized, and their characteristics and specific application scope are compared horizontally, and the possible development direction is discussed. This review clearly shows that non-destructive detection has the advantages of fast, accurate, and non-invasive, and it is the current research hotspot on meat quality evaluation. In the future, how to integrate a variety of non-destructive detection techniques to achieve comprehensive analysis and assessment of meat quality and safety will be a mainstream trend.

Preliminary Investigation on the Relationship between Raman Spectra of Beef and Metmyoglobin and Metmyoglobin Reductase Activity

A hand-held Raman spectroscopic device was used as a rapid nondestructive testing device to predict the metmyoglobin (MetMb) and metmyoglobin reductase activity (MRA) values on the surface layer of fresh beef. Longissimus dorsi muscles were from 10 young bulls (Holstein-Friesian) from two different cattle farms (group A = 5 and B = 5). The Raman spectra of 100 samples were correlated with the MetMb and MRA values using partial least squares regression (PLSR). Two groups could be discriminated, and the separate correlation models were better than the joint correlation model for the fresh beef. The coefficients of determination are R 2 = 0.81 (group A) and R 2 = 0.87 (group B) for MetMb and R 2 = 0.80 (group A) and R 2 = 0.85 (group B) for MRA. The results show the usefulness of Raman spectra in predicting the inner traits such as MetMb and MRA during meat storage. In conclusion, it is feasible to determine the MetMb and MRA values by Raman spectroscopy. Color is an important indicator of beef freshness and can vary depending on the age, sex, and breed of the cow. They play a very important role in human nutrition. The color of meat is an important indicator of meat freshness, and many researchers are already investigating the causes of color changes. The research was conducted in this environment.

Toward in-process technology-aided automation for enhanced microbial food safety and quality assurance in milk and beverages processing

Ensuring the safety of food products is critical to food production and processing. In food processing and production, several standard guidelines are implemented to achieve acceptable food quality and safety. This notwithstanding, due to human limitations, processed foods are often contaminated either with microorganisms, microbial byproducts, or chemical agents, resulting in the compromise of product quality with far-reaching consequences including foodborne diseases, food intoxication, and food recall. Transitioning from manual food processing to automation-aided food processing (smart food processing) which is guided by artificial intelligence will guarantee the safety and quality of food. However, this will require huge investments in terms of resources, technologies, and expertise. This study reviews the potential of artificial intelligence in food processing. In addition, it presents the technologies and methods with potential applications in implementing automated technology-aided processing. A conceptual design for an automated food processing line comprised of various operational layers and processes targeted at enhancing the microbial safety and quality assurance of liquid foods such as milk and beverages is elaborated.

Dietary Valine/Isoleucine Ratio Impact Carcass Characteristics, Meat Edible Quality and Nutritional Values in Finishing Crossbred Duroc × Landrace × Yorkshire Pigs With Different Slaughter Weights

The aim of this study was to investigate effects of dietary ratio of valine to isoleucine [R(V/I)] on carcass characteristics and meat quality of finishing pigs and whether slaughter weight influence the effect. We carried out a 2 × 3 factorial trial with two slaughter weight (105 vs. 130 kg) and three R(V/I) (0.58, 1.23, and 2.60 at 75–100 kg body weight, and 0.70, 1.24, and 2.39 at 100–135 kg body weight for L-, N- and H-R (V/I), respectively). Data show that increasing slaughter weight significantly increased meat color (a*_{45 min} and b*_{45 min}), drip loss and shear force (P < 0.05). Meanwhile, increasing slaughter weight reduced sarcomere length, the proportion of protein-bound water, and most kinds of muscular total amino acid contents except for tryptophan and arginine, while increased contents of muscular free lysine, tryptophan, leucine, isoleucine, valine, alanine, and arginine in the M. longissimus thoracis (P < 0.05). Health lipid indices based on fatty acid composition of intramuscular lipid were improved as the slaughter weight increased (P < 0.05). Notably, pigs received N-R (V/I) diet improved carcass traits in terms of thinner backfat thickness and higher fat-free lean index, as well as increased meat flavor-contributing amino acids at the cost of reduced intramuscular fat content and increased shear force of cooked meat compared with the pigs fed L-R (V/I) and H-R(V/I) diets (P < 0.05). H-R (V/I) diet decreased ultimate pH value and sarcomere length of the skeletal muscle but increased the proportion of free water (T₂₃), consequently, increased drip loss and cooking loss of fresh meat in pigs (P < 0.05). In conclusion, both slaughter weight and dietary ratio of valine to isoleucine exerted significant impacts on carcass characteristics, meat quality and nutrition values. In particular, carcass traits and meat color of lighter pigs were more susceptible to the influence of dietary R (V/I) relative to heavier pigs.

Effects of β-alanine and L-histidine supplementation on carnosine contents in and quality and secondary structure of proteins in slow-growing Korat chicken meat

Carnosine enrichment of slow-growing Korat chicken (KRC) meat helps differentiate KRC from mainstream chicken. We aimed to investigate the effects of β-alanine and L-histidine supplementation on the carnosine synthesis in and quality and secondary structure of proteins in slow-growing KRC meat. Four hundred 21-day-old female KRC were used, and a completely randomized design was applied. The chickens were divided into 4 experimental groups: basal diet (A), basal diet supplemented with 1.0% β-alanine (B), 0.5% L-histidine (C), and 1.0% β-alanine combined with 0.5% L-histidine (D). Each group consisted of 5 replicates (20 chickens per replicate). On d 70, 2 chickens per replicate were slaughtered, and the levels of carnosine, anserine, and thiobarbituric acid reactive substances were analyzed. Biochemical changes were monitored using synchrotron radiation-based Fourier transform infrared microspectroscopy; 5 chickens per replicate were slaughtered, and the meat quality was analyzed. Statistical analysis was performed using ANOVA and principal component analysis (PCA). Group D chickens exhibited the highest carnosine meat content, followed by those in groups B and C. However, amino acid supplementation did not affect anserine content and growth performance. Higher carnosine levels correlated with increasing pH_{45 min} and decreasing drip loss, cooking loss, shear force, and lipid oxidation. PCA revealed that supplementation with only β-alanine or L-histidine was related to increased content of β-sheets, β-turns, and aliphatic bending groups and decreased content of α-helix groups. This study is the first to report such findings in slow-growing chicken. Our findings suggest that KRC can synthesize the highest carnosine levels after both β-alanine and L-histidine supplementation. Higher carnosine contents do not adversely affect meat quality, improve meat texture, and alter the secondary structures of proteins. The molecular mechanism underlying carnosine synthesis in chickens needs further study to better understand and reveal markers that facilitate the development of nutrient selection programs.

Prediction of Trained Panel Sensory Scores for Beef with Non-Invasive Raman Spectroscopy

The objective of this study was to investigate Raman spectroscopy as a tool for the prediction of sensory quality in beef. Raman spectra were collected from M. longissimus thoracis et lumborum (LTL) muscle on a thawed steak frozen 48 h post-mortem. Another steak was removed from the muscle and aged for 14 days before being assessed for 12 sensory traits by a trained panel. The most accurate coefficients of determination of cross validation (R2CV) calibrated within the current study were for the trained sensory panel textural scores; particularly tenderness (0.46), chewiness (0.43), stringiness (0.35) and difficulty to swallow (0.33), with practical predictions also achieved for metallic flavour (0.52), fatty after-effect (0.44) and juiciness (0.36). In general, the application of mathematical spectral pre-treatments to Raman spectra improved the predictive accuracy of chemometric models developed. This study provides calibrations for valuable quality traits derived from a trained sensory panel in a non-destructive manner, using Raman spectra collected at a time-point compatible with meat management systems.

Assessment of Bulk Composition of Heterogeneous Food Matrices Using Raman Spectroscopy

Raman spectroscopy (RS) has for decades been considered a promising tool for food analysis, but widespread adoption has been held back by, e.g., high instrument costs and sampling limitations regarding heterogeneous samples. The aim of the present study was to use wide area RS in conjunction with surface scanning to overcome the obstacle of heterogeneity. Four different food matrices were scanned (intact and homogenized pork and by-products from salmon and poultry processing) and the bulk chemical parameters such as fat and protein content were estimated using partial least squares regression (PLSR). The performance of PLSR models from RS was compared with near-infrared spectroscopy (NIRS). Good to excellent results were obtained with PLSR models from RS for estimation of fat content in all food matrices (coefficient of determination for cross-validation (R²_CV) from 0.73 to 0.96 and root mean square error of cross-validation (RMSECV) from 0.43% to 2.06%). Poor to very good PLSR models were obtained for estimation of protein content in salmon and poultry by-product using RS (R²_CV from 0.56 to 0.92 and RMSECV from 0.85% to 0.94%). The performance of RS was similar to NIRS for all analyses. This work demonstrates the applicability of RS to analyze bulk composition in heterogeneous food matrices and paves way for future applications of RS in routine food analyses.

Meat tenderness: advances in biology, biochemistry, molecular mechanisms and new technologies

Meat tenderness is an important quality trait critical to consumer acceptance, and determines satisfaction, repeat purchase and willingness-to-pay premium prices. Recent advances in tenderness research from a variety of perspectives are presented. Our understanding of molecular factors influencing tenderization are discussed in relation to glycolysis, calcium release, protease activation, apoptosis and heat shock proteins, the use of proteomic analysis for monitoring changes, proteomic biomarkers and oxidative/nitrosative stress. Each of these structural, metabolic and molecular determinants of meat tenderness are then discussed in greater detail in relation to animal variation, postmortem influences, and changes during cooking, with a focus on recent advances. Innovations in postmortem technologies and enzymes for meat tenderization are discussed including their potential commercial application. Continued success of the meat industry relies on ongoing advances in our understanding, and in industry innovation. The recent advances in fundamental and applied research on meat tenderness in relation to the various sectors of the supply chain will enable such innovation.

Sensory Analysis and Consumer Research in New Meat Products Development

This review summarises the main sensory methods (traditional techniques and the most recent ones) together with consumer research as a key part in the development of new products, particularly meat products. Different types of sensory analyses (analytical and affective), from conventional methods (Quantitative Descriptive Analysis) to new rapid sensory techniques (Check All That Apply, Napping, Flash Profile, Temporal Dominance of Sensations, etc.) have been used as crucial techniques in new product development to assess the quality and marketable feasibility of the novel products. Moreover, an important part of these new developments is analysing consumer attitudes, behaviours, and emotions, in order to understand the complex consumer–product interaction. In addition to implicit and explicit methodologies to measure consumers’ emotions, the analysis of physiological responses can also provide information of the emotional state a food product can generate. Virtual reality is being used as an instrument to take sensory analysis out of traditional booths and configure conditions that are more realistic. This review will help to better understand these techniques and to facilitate the choice of the most appropriate at the time of its application at the different stages of the new product development, particularly on meat products.

Beneficial effects of Jerusalem artichoke powder and olive oil as animal fat replacers and natural healthy compound sources in Harbin dry sausages

This study aimed to improve the nutritional quality of Harbin dry sausages using natural plant-based Jerusalem artichoke powder (JAP) and olive oil as animal fat replacers. Low-fat Harbin dry sausages were manufactured with 2 different formulations containing JAP and olive oil as pork fat replacers. The texture, rheological properties, microstructure, water holding capacity, muscle protein structure, physicochemical indices, microbiological characteristics, and sensory evaluation of the sausages were analyzed. The result showed that Harbin dry sausages with JAP and olive oil were healthier than control sausages based on the lower fat content and improved fatty acid composition. Scanning electron microscopy showed gel network formation in sausages with a high JAP content. Low-field nuclear magnetic resonance illustrated that the water-holding capacity of the modified sausages was improved, suggesting that the replacers enhanced protein gel formation by changes in C-H stretching and bending vibrations, a reduction in α-helixes, and increases in β-sheets and random coils accompanying the exposure of reactive groups and microenvironment of the tertiary structure. Dynamic rheological and texture tests indicated that the replacers improved the elasticity of sausages. The reduction of fat and addition of replacers significantly enhanced lipid oxidative resistance. Overall, JAP and olive oil improved the fatty acid composition, gel structure, lipid oxidative resistance, and sensory quality of the sausages. These results may contribute to the development of healthy meat products to further reduce animal fat.

Meat quality and Raman spectroscopic characterization of Korat hybrid chicken obtained from various rearing periods

Meat quality attributes vary with chicken age. Understanding the relationship between poultry age and the quality of the meat would be beneficial for efficient poultry farming to meet market needs. The Korat hybrid chicken (KC) is a new crossbred chicken whose meat quality is distinct from that of commercial broiler (CB) chickens and has not been well characterized. In this study, we characterized the physico-chemical properties of KC meat and correlate the findings with Raman spectral data. The protein content of KC breast and thigh meat increased with age. The pH of thigh meat decreased, while the water-holding capacity of breast meat increased as the age of the chickens increased. The amount of cholesterol in breast meat decreased as the rearing period was extended. Inosine 5′-monophosphate and guanosine 5′-monophosphate of breast meat decreased as KC grew older. The shear force values of meat from older birds increased concomitantly with an increase in total collagen. Principle component analysis revealed that the meat quality of CB was greatly different from that of KC meat. High shear force values of KC meat at 20 wk of age were well correlated with an increase in the β-sheet structure (amide I) and amide III of collagen. Raman spectra at 3,207 cm⁻¹ and relative α-helical content were negatively correlated with shear force values of KC breast meat. These could be used as markers to evaluate KC meat quality.

Investigation of Raman Spectroscopy (with Fiber Optic Probe) and Chemometric Data Analysis for the Determination of Mineral Content in Aqueous Infant Formula

This study investigated the use of Raman spectroscopy (RS) and chemometrics for the determination of eight mineral elements (i.e., Ca, Mg, K, Na, Cu, Mn, Fe, and Zn) in aqueous infant formula (INF). The samples were prepared using infant formula powder reconstituted to concentrations of 3%-13% w/w (powder: water) (n = 83). Raman spectral data acquisition was carried out using a non-contact fiber optic probe on the surface of aqueous samples in 50-3398 cm-1. ICP-AES was used as a reference method for the determination of the mineral contents in aqueous INF samples. Results showed that the best performing partial least squares regression (PLSR) models developed for the prediction of minerals using all samples for calibration achieved R2CV values of 0.51-0.95 with RMSECVs of 0.13-2.96 ppm. The PLSR models developed and validated using separate calibration (n = 42) and validation (n = 41) samples achieved R2CVs of 0.93, 0.94, 0.91, 0.90, 0.97, and 0.94, R2Ps of 0.75, 0.77, 0.31, 0.60, 0.84, and 0.80 with RMSEPs of 3.17, 0.29, 3.45, 1.51, 0.30, and 0.25 ppm for the prediction of Ca, Mg, K, Na, Fe, and Zn respectively. This study demonstrated that RS equipped with a non-contact fiber optic probe and combined with chemometrics has the potential for timely quantification of the mineral content of aqueous INF during manufacturing.

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.

Preliminary investigation of the use of Raman spectroscopy to predict beef spoilage in different types of packaging

In this study, pH, meat color analysis, microbial counts and Raman spectroscopic data were obtained from beef steaks stored at 4 °C for up to 21 days using two different packaging methods: vacuum (VP) and modified atmosphere packaging (MAP). Models using partial least square regression (PLSR), indicated that Raman spectroscopy was able to predict total viable counts (TVC) and lactic acid bacteria (LAB) measured at 21d post mortem (TVC in VP: R²_cv = 0.99, RMSEP = 0.61; TVC in MAP: R²_cv = 0.90, RMSEP = 0.38; LAB in VP: R²_cv = 0.99, RMSEP = 0.54; LAB in MAP: R²_cv = 0.75, RMSEP = 0.60). The results of this study demonstrate that Raman spectroscopy may have potential for the rapid determination of meat spoilage.

Physicochemical and sensory properties of carabeef treated with Bacillus subtilis (Ehrenberg) Cohn protease as meat tenderizer

This study investigated the use of Bacillus subtilis protease powder (CTC E-ssentials™ MT-70N) as a carabeef tenderizer. The effect of the bacterial protease on the characteristics of carabeef was determined, and its effectiveness was compared to a commercial meat tenderizer containing papain. Only B. subtilis protease showed significant enzyme activity (80-190 U/g), while the commercial meat tenderizer had no activity (0 U/g). Results from the shear force device revealed that 0.35% B. subtilis protease was the optimal concentration required to induce significant tenderization in carabeef (282 g/cm2) and reduce carabeef toughness by 80%. Proximate analysis showed that carabeef treated with B. subtilis protease had significantly higher crude protein (37%) than the negative control (34%) and carabeef-treated commercial meat tenderizer (31%). Sensory evaluation revealed that carabeef treated with 0.35% B. subtilis protease is more tender than untreated carabeef and those treated with the commercial meat tenderizer. Moreover, the carabeef was not over-tenderized and is palatably acceptable. Hence, B. subtilis protease can be used as a meat tenderizer in place of available commercial tenderizers containing plant-derived proteases.

Predicting the Quality of Meat: Myth or Reality?

This review is aimed at providing an overview of recent advances made in the field of meat quality prediction, particularly in Europe. The different methods used in research labs or by the production sectors for the development of equations and tools based on different types of biological (genomic or phenotypic) or physical (spectroscopy) markers are discussed. Through the various examples, it appears that although biological markers have been identified, quality parameters go through a complex determinism process. This makes the development of generic molecular tests even more difficult. However, in recent years, progress in the development of predictive tools has benefited from technological breakthroughs in genomics, proteomics, and metabolomics. Concerning spectroscopy, the most significant progress was achieved using near-infrared spectroscopy (NIRS) to predict the composition and nutritional value of meats. However, predicting the functional properties of meats using this method-mainly, the sensorial quality-is more difficult. Finally, the example of the MSA (Meat Standards Australia) phenotypic model, which predicts the eating quality of beef based on a combination of upstream and downstream data, is described. Its benefit for the beef industry has been extensively demonstrated in Australia, and its generic performance has already been proven in several countries.

Investigation of chemical composition of meat using spatially off-set Raman spectroscopy

Spatially off-set Raman spectroscopy (SORS) offers non-invasive chemical characterisation of the sub-surface of various biological tissues as it permits the assessment of diffusely scattering samples at depths of several orders of magnitude deeper than conventional Raman spectroscopy. Chemicals such as glycogen, glucose, lactate and cortisol are predictors of meat quality, however detection of these chemicals is limited to the surface of meat using conventional Raman spectroscopy as their concentration is higher within the tissue. Here, we have used SORS to detect spectral bands for glycogen, lactate, glucose and cortisol beneath the surface of meat tissue by spiking. To our knowledge, this is the first report on this method for potential application in meat quality analysis. We further validate our SORS spectral results using chemometric analysis to determine chemical-specific spectral characteristics suitable for chemical identification. The chemometric analysis clearly shows distinction of spiked metabolites into four distinct groups, even for such chemically similar compounds as glucose, glycogen and lactate.

Predicting aged pork quality using a portable Raman device

The utility of Raman spectroscopic signatures of fresh pork loin (1 d & 15 d postmortem) in predicting fresh pork tenderness and slice shear force (SSF) was determined. Partial least square models showed that sensory tenderness and SSF are weakly correlated (R² = 0.2). Raman spectral data were collected in 6 s using a portable Raman spectrometer (RS). A PLS regression model was developed to predict quantitatively the tenderness scores and SSF values from Raman spectral data, with very limited success. It was discovered that the prediction accuracies for day 15 post mortem samples are significantly greater than that for day 1 postmortem samples. Classification models were developed to predict tenderness at two ends of sensory quality as "poor" vs. "good". The accuracies of classification into different quality categories (1st to 4th percentile) are also greater for the day 15 postmortem samples for sensory tenderness (93.5% vs 76.3%) and SSF (92.8% vs 76.1%). RS has the potential to become a rapid on-line screening tool for the pork producers to quickly select meats with superior quality and/or cull poor quality to meet market demand/expectations.

Application of Raman spectroscopy and chemometric techniques to assess sensory characteristics of young dairy bull beef

This work aims to develop a rapid analytical technique to predict beef sensory attributes using Raman spectroscopy (RS) and to investigate correlations between sensory attributes using chemometric analysis. Beef samples (n = 72) were obtained from young dairy bulls (Holstein-Friesian and Jersey×Holstein-Friesian) slaughtered at 15 and 19 months old. Trained sensory panel evaluation and Raman spectral data acquisition were both carried out on the same longissimus thoracis muscles after ageing for 21 days. The best prediction results were obtained using a Raman frequency range of 1300-2800 cm^-1. Prediction performance of partial least squares regression (PLSR) models developed using all samples were moderate to high for all sensory attributes (R²CV values of 0.50-0.84 and RMSECV values of 1.31-9.07) and were particularly high for desirable flavour attributes (R²CVs of 0.80-0.84, RMSECVs of 4.21-4.65). For PLSR models developed on subsets of beef samples i.e. beef of an identical age or breed type, significant improvements on prediction performances were achieved for overall sensory attributes (R²CVs of 0.63-0.89 and RMSECVs of 0.38-6.88 for each breed type; R²CVs of 0.52-0.89 and RMSECVs of 0.96-6.36 for each age group). Chemometric analysis revealed strong correlations between sensory attributes. Raman spectroscopy combined with chemometric analysis was demonstrated to have high potential as a rapid and non-destructive technique to predict the sensory quality traits of young dairy bull beef.

Recent advances in rapid and nondestructive determination of fat content and fatty acids composition of muscle foods

Conventional methods for determining fat content and fatty acids (FAs) composition are generally based on the solvent extraction and gas chromatography techniques, respectively, which are time consuming, laborious, destructive to samples and require use of hazard solvents. These disadvantages make them impossible for large-scale detection or being applied to the production line of meat factories. In this context, the great necessity of developing rapid and nondestructive techniques for fat and FAs analyses has been highlighted. Measurement techniques based on near-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance and hyperspectral imaging have provided interesting and promising results for fat and FAs prediction in varieties of foods. Thus, the goal of this article is to give an overview of the current research progress in application of the four important techniques for fat and FAs analyses of muscle foods, which consist of pork, beef, lamb, chicken meat, fish and fish oil. The measurement techniques are described in terms of their working principles, features, and application advantages. Research advances for these techniques for specific food are summarized in detail and the factors influencing their modeling results are discussed. Perspectives on the current situation, future trends and challenges associated with the measurement techniques are also discussed.