Monitoring of Pig Slaughter Stages and Correlation in the Prevalence of Pathogens and Levels of Microorganisms That Indicate Microbiological Quality and Hygiene Using a Predictive Model.

Pig production is relevant to the Brazilian economy. Different stages of the raising and slaughtering process influence the microbiological quality of pig products and by-products. Microbiological analysis and hazard analysis and critical control points (HACCPs) are tools for monitoring microbiological quality indicator microorganisms. The construction of predictive models can assist the process of monitoring the microbiological quality of pig products. This study aimed to map the slaughter stages and develop a model to predict the absence or presence of Salmonella based on the process variables (distance from the farm to the slaughterhouse and aerobic mesophilic) and analyze their influence on contamination indicator microorganisms. A total of 810 samples were collected at nine stages of the slaughter process (bleeding, scalding, dehairing, singeing, washing, evisceration, inspection, final washing, and chilling). The binary class predictive model was used as a microbiological quality predictor at the slaughter stages. Salmonella was identified at all process stages, with lower contamination levels at the scalding and chilling stages, whereas the highest levels were found at the dehairing and bleeding stages. The predictive model revealed an accuracy of about 85% for Salmonella being a tool to monitor the microbiological quality of pig slaughter.

Effects of an alternative bleaching method for yerba mate leaves on total phenolic content: evaluation and prediction with soft-computing approaches.

BACKGROUND: The effects of an alternative bleaching method on the total phenolic content (TPC) and antioxidant activity (AA) of yerba mate extracts were evaluated. Traditional bleaching ('zapeco') was compared with submerging the leaves in water followed by a hot air oven-drying process. Seven different approaches, i.e. linear model (LM), response surface model (RSM), Mamdani, Larsen, adaptive neuro-fuzzy inference system (ANFIS) with the product (Prod) and the minimum (Min) operators, and ANFIS with automatically membership functions (Auto), were employed to compare the TPC of yerba mate extracts based on drying temperature and AA assays. RESULTS: The results showed that if leaves were bleached followed by drying at higher temperatures, we obtained higher AA and TPC values. For submerging bleaching treatment, RSM model delivered the best accuracy measures with a mean absolute error (MAE), average absolute percentage error (MAPE), and mean squared error (MSE) of 0.128, 0.006, and 0.028, respectively. The ANFIS Auto model was the best for traditional bleaching treatment, with MAE, MAPE, and MSE of 0.490, 0.013, and 0.612, respectively. CONCLUSION: The results suggest a second-order linear relation between drying temperature, AA assays to TPC, and a high level of relation complexity of drying temperature, AA assays, and TPC. The evaluated soft-computing approaches have the excellent ability to estimate TPC from bleached leaves. © 2022 Society of Chemical Industry.

Antiproliferative activity and energy calculations of a new triterpene isolated from the palm tree Acrocomia totai.

Acrocomia totai Mart (Arecaceae) is a palm tree native to South America, widely studied for biodiesel production. The aim of this work was to perform the first phytochemical study of A. totai leaves, as well as to do biological assays against human cancer cell lines. A new triterpene of the hopane class named totaiol (1), three known triterpenes (2-4), and two phytosteroids (5-6) were identified. The new natural product was characterized using 1 D and 2 D NMR, single crystal X-ray diffraction analises, and high resolution mass spectrometry. The intercontacts in the crystal packing were also analised. Complete stereochemical characterization of compound 1 revealed an unusual positioning pattern for methyl and isopropenyl groups in the polycyclic skeleton. Compounds 1-5 were evaluated for the first time in antiproliferative assays against Ca Ski, MCF-7 and MCF-10 cells. The new natural product was active against Ca Ski cells with IC50 ≤ 6.25 µg mL-1.

A new kinetic model to predict substrate inhibition and better efficiency in an airlift reactor on deammonification process.

A collection of kinetic models to explore the bacteria pathway inhibition by high-ammonia during deammonification process was fitted. The main goal was to determine the substrate concentration to operate the deammonification with efficiency, performance and low impact to ANAMMOX and ammonia-oxidizing bacteria (AOB) by substrate. A new mathematical model was created to describe the deammonification behavior, since the empirical theoretical models showed inconsistent parameters to describe the process. The proposed model showed significant prediction to the estimable parameters and according to it, until 550 mg NH3-N L-1 no inhibitions by ammonia and nitrite were observed. However, concentrations higher than this promote the decrease on specific bacterial activity and nitrite accumulation, since it was not quickly consumed by the bacteria. The proposed model can be applied to predict microorganism affinity and inhibition by substrate over a wide range of ammonia concentrations (<900 mgNH3-N L-1) in reactors treating high-ammonia concentration swine wastewater.