ATR-FTIR spectroscopy and chemometrics as a quick and simple alternative for discrimination of SARS-CoV-2 infected food of animal origin.

Alternative routes such as virus transmission or cross-contamination by food have been suggested, due to reported cases of SARS-CoV-2 in frozen chicken wings and fish or seafood. Delay in routine testing due to the dependence on the PCR technique as the standard method leads to greater virus dissemination. Therefore, alternative detection methods such as FTIR spectroscopy emerge as an option. Here, we demonstrate a fast (3 min), simple and reagent-free methodology using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy for discrimination of food (chicken, beef and fish) contaminated with the SARS-CoV-2 virus. From the IR spectra of the samples, the "bio-fingerprint" (800 - 1900 cm-1) was selected to investigate the distinctions caused by the virus contamination. Exploratory analysis of the spectra, using Principal Component of Analysis (PCA), indicated the differentiation in the data due to the presence of single bands, marked as contamination from nucleic acids including viral RNA. Furthermore, the partial least squares discriminant analysis (PLS-DA) classification model allowed for discrimination of each matrix in its pure form and its contaminated counterpart with sensitivity, specificity and accuracy of 100 %. Therefore, this study indicates that the use of ATR-FTIR can offer a fast and low cost and not require chemical reagents and with minimal sample preparation to detect the SARS-CoV-2 virus in food matrices, ensuring food safety and non-dissemination by consumers.

CLASSIFICATION OF FOOD MENU AND GROUPING OF FOOD POTENTIAL TO SUPPORT THE FOOD SECURITY AND NUTRITION QUALITY

The Movement for Diverse, Nutritious, Balanced, and Safe Diet, in this article called by B2SA is a program from the Indonesian government to improve resilience and nutritional quality in line with one of the Sustainable Development Goals, especially during the Coronavirus Disease (COVID-19) pandemic. In this article, classification and grouping methods are carried out to determine the development of supporting the B2SA program in Indonesia, such as the classified menu arrangement and the potential for grouped foodstuffs, especially in East Java, which is one of the provinces with a high COVID-19 spread rate and contributes greatly to food security in Indonesia. The application of the classification method in this study is to compare the performance of logistic regression and random forest. In addition, the clustering method is applied by comparing the performance of Single Linkage and K-Means. The results of this study are the category of food menu recommended by the population of East Java, which turned out to be 49.3% not meeting the B2SA standard. As for the results of the grouping, there are four groups for potential food categories of staple foods and side dishes, two groups for the category of fruits and vegetables. These results are expected to be a recommendation for the government in supporting the stability of food security to strengthen the resilience of the food industry in Indonesia because it is a region that has food potential in Indonesia. © 2022 the author(s).

Fuzzy Clustering Methods to Identify the Epidemiological Situation and Its Changes in European Countries during COVID-19.

The main research question concerned the identification of changes in the COVID-19 epidemiological situation using fuzzy clustering methods. This research used cross-sectional time series data obtained from the European Centre for Disease Prevention and Control. The identification of country types in terms of epidemiological risk was carried out using the fuzzy c-means clustering method. We also used the entropy index to measure the degree of fuzziness in the classification and evaluate the uncertainty of epidemiological states. The proposed approach allowed us to identify countries' epidemic states. Moreover, it also made it possible to determine the time of transition from one state to another, as well as to observe fluctuations during changes of state. Three COVID-19 epidemic states were identified in Europe, i.e., stabilisation, destabilisation, and expansion. The methodology is universal and can also be useful for other countries, as well as the research results being important for governments, politicians and other policy-makers working to mitigate the effects of the COVID-19 pandemic.