Molecular genetic methods for identifying raw materials in meat products: Diversity, opportunities and prospects

In the current economic situation, after easing the Covid pandemic restrictions, almost all laboratories, which are focused on evaluation of the conformity of food products, have faced issues in supplying for their laboratories. In this regard, in the last years many laboratories have been forced to validate new approaches and introduce new methods for assessing conformity of the food products. Very often it is not possible to use only one method to resolve the issue of the food product ingredients, especially for the purpose of traceability of their names and the used raw materials, listed on the label. Survey of the raw food materials to determine whether they correspond to the type name is a simpler task, in contrast to survey of the multicomponent food product. Many researchers have to estimate the opportunities and feasibility of application of various methodologies in their workplaces. Therefore, this review is relevant for the researchers in this field, as it focuses on aspects and special features of similar methodologies. The prospect of molecular genetic methods for identification of the raw materials used for manufacturing of meat products is presented below. This review also represents characteristics of methods for identification of the sources of raw materials used for the manufacturing of the meat products, based on the recognition of species-specific sections within the nucleic acids structures. The variety of methods (hybridization methods, polymerase chain reaction, different types of isothermal amplifications, methods using CRISPR/Cas systems), the principles of their implementation, and achieved analytical characteristics are considered. The capacities and competitive potential of various methods are discussed, as well as approaches being developed to overcome the existing limitations.In the current economic situation, after easing the Covid pandemic restrictions, almost all laboratories, which are focused on evaluation of the conformity of food products, have faced issues in supplying for their laboratories. In this regard, in the last years many laboratories have been forced to validate new approaches and introduce new methods for assessing conformity of the food products. Very often it is not possible to use only one method to resolve the issue of the food product ingredients, especially for the purpose of traceability of their names and the used raw materials, listed on the label. Survey of the raw food materials to determine whether they correspond to the type name is a simpler task, in contrast to survey of the multicomponent food product. Many researchers have to estimate the opportunities and feasibility of application of various methodologies in their workplaces. Therefore, this review is relevant for the researchers in this field, as it focuses on aspects and special features of similar methodologies. The prospect of molecular genetic methods for identification of the raw materials used for manufacturing of meat products is presented below. This review also represents characteristics of methods for identification of the sources of raw materials used for the manufacturing of the meat products, based on the recognition of species-specific sections within the nucleic acids structures. The variety of methods (hybridization methods, polymerase chain reaction, different types of isothermal amplifications, methods using CRISPR/Cas systems), the principles of their implementation, and achieved analytical characteristics are considered. The capacities and competitive potential of various methods are discussed, as well as approaches being developed to overcome the existing limitations

Influence Distribution Training Data on Performance Supervised Machine Learning Algorithms

Almost all fields of life need Banknote. Even particular fields of life require banknotes in large quantities such as banks, transportation companies, and casinos. Therefore Banknotes are an essential component in carrying out all activities every day, especially those related to finance. Through technological advancements such as scanners and copy machine, it can provide the opportunity for anyone to commit a crime. The crime is like a counterfeit banknote. Many people still find it difficult to distinguish between a genuine banknote ad counterfeit Banknote, that is because counterfeit Banknote produced have a high degree of resemblance to the genuine Banknote. Based on that background, authors want to do a classification process to distinguish between genuine Banknote and counterfeit Banknote. The classification process use methods Supervised Learning and compares the level of accuracy based on the distribution of training data. The methods of supervised Learning used are Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and Naïve Bayes. K-NN method is a method that has the highest specificity, sensitivity, and accuracy of the three methods used by the authors both in the training data of 30%, 50%, and 80%. Where in the training data 30% and 50% value specificity: 0.99, sensitivity: 1.00, accuracy: 0.99. While the 80% training data value specificity: 1.00, sensitivity: 1.00, accuracy: 1.00. This means that the distribution of training data influences the performance of the Supervised Machine Learning algorithm. In the KNN method, the greater the training data, the better the accuracy

International Marketing

International Marketing, a compilation of open educational resources and Lynn Library-licensed material, discusses how organizations market goods and services internationally, and how the scope of marketing subsequently broadens as it interacts with other dimensions like national culture and countries’ political, legal, and economic systems. The text reveals how, when marketing across national boundaries, organizations must decide what it is going to sell, what markets to target, and what marketing mix (product, place, promotion, price, and people) to embrace. Course: MKT 392https://spiral.lynn.edu/ludp/1012/thumbnail.jp