Protein based evaluation of meat species by using laser induced breakdown spectroscopy

Fresh Meat Classification Using Laser-Induced Breakdown Spectroscopy Assisted by LightGBM and Optuna

To enhance the accuracy of identifying fresh meat varieties using laser-induced breakdown spectroscopy (LIBS), we utilized the LightGBM model in combination with the Optuna algorithm. The procedure involved flattening fresh meat slices with glass slides and collecting spectral data of the plasma from the surfaces of the fresh meat tissues (pork, beef, and chicken) using LIBS technology. A total of 900 spectra were collected. Initially, we established LightGBM and SVM (support vector machine) models for the collected spectra. Subsequently, we applied information gain and peak extraction algorithms to select the features for each model. We then employed Optuna to optimize the hyperparameters of the LightGBM model, while a 10-fold cross-validation was conducted to determine the optimal parameters for SVM. Ultimately, the LightGBM model achieved higher accuracy, macro-F1, and Cohen's kappa coefficient (kappa coefficient) values of 0.9370, 0.9364, and 0.9244, respectively, compared to the SVM model's values of 0.8888, 0.8881, and 0.8666. This study provides a novel method for the rapid classification of fresh meat varieties using LIBS.

High-throughput identification of meat ingredients in adulterated foods based on centrifugal integrated purification-CRISPR array

Rapid, accurate, and sensitive analytical methods for the detection of food fraud are now an urgent requirement in the global food industry to ensure food quality. In response to this demand, a centrifugal integrated purification-CRISPR array for meat adulteration (CIPAM) was established. In detail, CIPAM system combines microneedles for DNA extraction and RAA-CRISPR/Cas12a integrated into a centrifugal microfluidic chip for the detection of meat adulteration. The RAA-CRISPR/Cas12a reaction reagents were pre-embedded into the different reaction chambers on the microfluidic chip to achieve the streamline of operations, markedly simplifying the detection process. The whole reaction was completed within 30 min with a detection limit of 0.1 % (w/w) in pig, chicken, duck, and lamb products. Referring to the results of the standard method, CIPAM system achieved 100 % accuracy. The automatic multiplex detection process implemented in the developed CIPAM system met the needs of food regulatory authorities.

Understanding the Role of Filamentous Actin in Food Quality: From Structure to Application

Actin, a multifunctional protein highly expressed in eukaryotes, is widely distributed throughout cells and serves as a crucial component of the cytoskeleton. Its presence is integral to maintaining cell morphology and participating in various biological processes. As an irreplaceable component of myofibrillar proteins, actin, including G-actin and F-actin, is highly related to food quality. Up to now, purification of actin at a moderate level remains to be overcome. In this paper, we have reviewed the structures and functions of actin, the methods to obtain actin, and the relationships between actin and food texture, color, and flavor. Moreover, actin finds applications in diverse fields such as food safety, bioengineering, and nanomaterials. Developing an actin preparation method at the industrial level will help promote its further applications in food science, nutrition, and safety.

Relative quantification of pork and beef in meat products using global and species-specific peptide markers for the authentication of meat composition

We used global and species-specific peptide markers for a relative quantitative determination of pork and beef in raw and processed meat products made of the two meat species. Four groups of products were prepared (i.e., minced raw meats, sausages, raw and fried burgers) in order to represent products with different extents of food processing. In each group, the products varied in the pork/beef proportions. All products were analysed by multiple reaction monitoring mass spectrometry (MRM-MS) for the presence/concentration of pork- and beef-specific peptide markers, as well as global markers - peptides widely distributed in muscle tissue. The combined MRM-MS analysis of pork-specific peptide HPGDFGADAQGAMSK, beef-specific peptide VLGFHG and global marker LFDLR offered the most reliable validation of declared pork/beef compositions across the whole range of meat products. Our work suggests that a simultaneous analysis of global and species-specific peptide markers can be used for composition authentication in commercial pork/beef products.

Visual Detection of Chicken Adulteration Based on a Lateral Flow Strip-PCR Strategy

The aim of this study was to develop an accurate, easy-to-use, and cost-effective method for the detection of chicken adulteration based on polymerase chain reaction (PCR) and lateral flow strip (LFS). We compared six DNA extraction methods, namely the cetyltrimethylammonium bromide (CTAB) method, salt method, urea method, SDS method, guanidine isothiocyanate method, and commercial kit method. The chicken cytb gene was used as a target to design specific primers. The specificity and sensitivity of the PCR-LFS system were tested using a self-assembled lateral flow measurement sensor. The results showed that the DNA concentration obtained by salt methods is up to 533 ± 84 ng µL⁻¹, is a suitable replacement for commercial kits. The PCR-LFS method exhibits high specificity at an annealing temperature of 62 °C and does not cross-react with other animal sources. This strategy is also highly sensitive, being able to detect 0.1% of chicken in artificial adulterated meat. The results of the test strips can be observed with the naked eye within 5 min, and this result is consistent with the electrophoresis result, demonstrating its high accuracy. Moreover, the detection system has already been successfully used to detect chicken in commercial samples. Hence, this PCR-LFS strategy provides a potential tool to verify the authenticity of chicken.

Critical review and recent advances of 2D materials-Based gas sensors for food spoilage detection

Many people around the world are concerned about meat safety and quality, which has resulted in the ongoing advancement of packaged food technology. Since the emergence of graphene in 2004, the number of studies on layered two-dimensional materials (2DMs) for applications ranging from food packaging to meat quality monitoring has been expanding quickly. Recently, scientists have been working hard to develop a novel class of 2DMs that keep the good things about graphene but don't have zero bandgaps at room temperature. Much work has been done on layered transition metal dichalcogenides (TMDCs) like different metal sulfides and selenides for meat spoilage gas sensors. This review looks at (i) the main indicators of meat spoilage and (ii) the detection methods that can be used to find out if meat has been spoiled, such as chemiresistive, electrochemical, and optical methods. (iii) the role of 2DMs in meat spoilage detection and (iv) the emergence of advanced methods for selective classification of target analytes in meat/food spoilage detection in recent years. Thus, this review demonstrates the potential scope of 2DMs for developing intelligent sensor systems for food and meat spoilage detection with high viability, simplicity, cost-effectiveness, and other multipurpose tools.

Identification of meat species in processed meat products by using protein based laser induced breakdown spectroscopy assay

The detection of meat fraud and mislabeling in processed meat products is a raising concern for consumers. The aim of this study was to develop and demonstrate the potential of protein-based laser induced breakdown spectroscopy (LIBS) method to be used for the identification of beef, chicken, and pork in fermented sausage and salami products. In this respect, bulk protein and protein fractions rich in sarcoplasmic and myofibrillar protein of sausage and salami products were obtained and subjected to LIBS analysis. LIBS spectrum was evaluated with chemometric methods to classify meat species and determine adulteration ratio by using principal component analysis and partial least square analysis, respectively. Limit of detection values for chicken and pork adulteration in beef sausage were found as 3.68 and 3.83% for myofibrillar fraction, while those values in beef salami were found as 3.80 and 3.47% for sarcoplasmic fraction, respectively.