Near Infrared Reflectance spectroscopy to analyse texture related characteristics of sous vide pork loin

Effect of different atmospheric and subatmospheric cooking techniques on physical and chemical qualitative properties of pork loin

In this paper, the effects of four cooking procedures were evaluated, two occurring in atmospheric (in ventilated and steam oven) and two in subatmospheric (vacuum and sous vide cooking) conditions on pork Longissimus lumborum. The main objective of the study was to compare and evaluate the physical and chemical characteristics. Samples were cooked in four independent trials namely Oven (O), Steaming (ST), Vacuum Cooking (VC) and Sous Vide (SV). The analyses included temperature, cooking effect, percentage weight loss, texture (cutting and double compression tests), colour (superficially and inside the sample), microstructure (optical microscopy) and fibres shortening analysis. To assess cooking effects on significant nutritional constituents, the fatty acid composition and the content of B vitamins were analysed. Volatile profiles of samples were also compared using solid-phase microextraction. SV cooking resulted in the less favourable meat texture, presenting the highest hardness and chewiness. Moreover, high hardness values measured on SV samples is also related to the high weight loss. The technique of oven cooking (O) demonstrated superior results in terms of mechanical properties, which are closely associated with the cooking values. Specifically, the cook value C0 was significantly higher in the case of oven cooking compared to SV, VC, and ST. Mild temperature conditions and cooking times of the four considered cooking techniques did not induce significant variations in the fatty acid composition and volatile profile. Conversely, SV and VC allowed the highest amount of vitamin B retention in cooked meat. This work suggests that some differences emerged on the effects due to sub-atmospheric and atmospheric cooking compared to traditional ones.

Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?

This study involved a comprehensive examination of sensory attributes in dry-cured Bísaro loins, including odor, androsterone, scatol, lean color, fat color, hardness, juiciness, chewiness, flavor intensity and flavor persistence. An analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveiled distinct peaks associated with significant components, such as proteins, lipids and water. Support vector regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization and the radial base kernel (non-linear SVR model). This process involved partitioning the data into calibration (67%) and prediction (33%) subsets using the SPXY algorithm. The model parameters were optimized via a hybrid algorithm based on particle swarm optimization (PSO) to effectively minimize the root-mean-square error (RMSECV) derived from five-fold cross-validation and ensure the attainment of optimal model performance and predictive accuracy. The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616-0.9955) and low RMSE values (0.0400-0.1031). The prediction set's relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig meat aroma, hardness, fat color and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment. Such advancements have the potential to benefit both the research community and the meat industry by closely aligning their practices with consumer preferences and expectations.

Influence of Sous Vide Cooking on Ground Beef Patties

With rising consumer demand for fast-food options, quick-service restaurants are constantly developing new menu items to attract consumers. Sous vide cookery has become popular for the in-home and fine dining consumer but has not been considered the first cooking option for quick service applications. Therefore, ground beef patties were manufactured to measure the influence of sous vide cooking time on the patty characteristics of moisture, color, and objective tenderness. Patties were randomly assigned a sous vide cooking time of 30, 60, or 90 min and then grilled to an internal temperature of 71.1 °C. Patties sous vide cooked for 30 min exhibited the greatest (p < 0.05) cook loss, Allo-Kramer Shear Force (AKSF) and were darker (L*) than patties sous vide cooked for 60 or 90 min. Additionally, neither internal redness, calculated spectral values of chroma, hue angle, or red-to-brown differed (p > 0.05) regardless of sous vide cooking time. Sous vide cooking duration prior to grilling the ground beef patties altered the moisture, color, and objective texture characteristics of ground beef patties.

Determination of beef tenderness based on airflow pressure combined with structural light three-dimensional (3D) vision technology

The main factor affecting beef quality, consumer satisfaction, and purchase decisions is beef tenderness. In this study, a rapid nondestructive testing method for beef tenderness based on airflow pressure combined with structural light 3D vision technology was proposed. The structural light 3D camera was used to scan the 3D point cloud deformation information of the beef surface after the airflow acted on it for 1.8 s. Six deformation characteristics and three point cloud characteristics of the beef surface depression region were obtained by using denoising, point cloud rotation, point cloud segmentation, point cloud descending sampling, alphaShape, and other algorithms. A total of nine characteristics were mainly concentrated in the first five principal components (PCs). Therefore, the first five PCs were put into three different models. The results showed that the Extreme Learning Machine (ELM) model had a comparatively higher prediction effect for the prediction of beef shear force, with a root mean square error of prediction (RMSEP) of 11.1389 and a correlation coefficient (R) of 0.8356. In addition, the correct classification accuracy of the ELM model for tender beef achieved 92.96%. The overall classification accuracy reached 93.33%. Consequently, the proposed methods and technology can be applied for beef tenderness detection.

Dry-cured loin characterization by ultrasound physicochemical and sensory parameters

The aim of this study was to evaluate the ability of ultrasound inspection and quality determinations to characterize two commercial categories of dry-cured pork loin, labelled as green (GL) and red (RL). For this objective, ultrasound inspection was carried out for two different frequencies (500 and 1000 kHz), considering parameters of ultrasonic pulse velocity (UPV), frequency components related to the fast Fourier transform (FFT), and variables related to the attenuation. Physicochemical (moisture and fat content, water activity, instrumental color), instrumental texture (TPA) and sensory analyses (QDA) were also carried out. Moreover, quality and ultrasonic parameters were subjected to a correlation analysis (Pearson). Several physicochemical, instrumental texture and sensory parameters allowed to discriminate the dry-cured loin category. Moreover, high significant correlations were found among quality and acoustics parameters. Thus, ultrasound inspection can determine quality parameters indirectly without the limitations of traditional methodologies, postulating as a tool for characterizing dry-cured loin samples of different category with a promising predictive nature. This work has showed new findings for dry-cured meat products that may be of interest to the meat industry.

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.

Monitoring Thermal and Non-Thermal Treatments during Processing of Muscle Foods: A Comprehensive Review of Recent Technological Advances

Muscle food products play a vital role in human nutrition due to their sensory quality and high nutritional value. One well-known challenge of such products is the high perishability and limited shelf life unless suitable preservation or processing techniques are applied. Thermal processing is one of the well-established treatments that has been most commonly used in order to prepare food and ensure its safety. However, the application of inappropriate or severe thermal treatments may lead to undesirable changes in the sensory and nutritional quality of heat-processed products, and especially so for foods that are sensitive to thermal treatments, such as fish and meat and their products. In recent years, novel thermal treatments (e.g., ohmic heating, microwave) and non-thermal processing (e.g., high pressure, cold plasma) have emerged and proved to cause less damage to the quality of treated products than do conventional techniques. Several traditional assessment approaches have been extensively applied in order to evaluate and monitor changes in quality resulting from the use of thermal and non-thermal processing methods. Recent advances, nonetheless, have shown tremendous potential of various emerging analytical methods. Among these, spectroscopic techniques have received considerable attention due to many favorable features compared to conventional analysis methods. This review paper will provide an updated overview of both processing (thermal and non-thermal) and analytical techniques (traditional methods and spectroscopic ones). The opportunities and limitations will be discussed and possible directions for future research studies and applications will be suggested.

Monitoring Thermal Treatments Applied to Meat Using Traditional Methods and Spectroscopic Techniques: a Review of Advances over the Last Decade

Thermal treatments are often applied during processing or preparation of muscle foods aiming to both improve the palatability and organoleptic properties and to ensure the safety of the treated food. However, the application of inappropriate or severe thermal treatments can lead to undesirable changes in the sensory and nutritional quality of heat-processed products, and especially so for foods that are sensitive to thermal treatments, such as meat and meat products. The impact of traditional and new heat processing technologies (e.g. microwaving, ohmic, and radio frequency heating) on meat quality has been widely assessed by a wide range of conventional methods, such as sensory, microbiological, and physicochemical methods. Due to the destructive nature and the time required to perform these assessments, alternative online methods are highly needed in order to achieve continuous monitoring through online applications. In this review paper, both traditional and new heat processing methods and their impact on the quality of meat will be first briefly presented. The methods and techniques that have been applied to monitor changes induced by application of thermal treatments will be then discussed. The main focus will be put on the application of spectroscopic techniques, as rapid and non-destructive methods compared to most conventional techniques. Finally, future trends and possible applications and research directions will be suggested.