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采用预测模型监测猪屠宰阶段并关联病原体流行率和指示微生物质量与卫生水平的微生物水平。

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.

机构信息

Graduate Program of Food Technology, Federal University of Technology-Parana, Francisco Beltrão-PR, Londrina-PR, Brazil.

School of Pharmacy, Federal University of Minas Gerais, Belo Horizonte-MG, Brazil.

出版信息

J Food Prot. 2023 Jan;86(1):100034. doi: 10.1016/j.jfp.2022.100034. Epub 2022 Dec 24.

Abstract

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.

摘要

猪肉生产与巴西经济息息相关。养殖和屠宰过程的不同阶段会影响猪肉产品和副产品的微生物质量。微生物分析和危害分析及关键控制点(HACCP)是监测微生物质量指示微生物的工具。预测模型的构建可以协助监测猪肉产品的微生物质量。本研究旨在绘制屠宰阶段图,并开发一种基于过程变量(从农场到屠宰场的距离和需氧嗜温菌)预测沙门氏菌存在或不存在的模型,并分析它们对污染指示微生物的影响。在屠宰过程的九个阶段(放血、烫毛、去毛、燎毛、清洗、内脏处理、检查、最终清洗和冷却)共采集了 810 个样本。二元分类预测模型可用作屠宰阶段的微生物质量预测器。沙门氏菌在所有阶段均有检出,在烫毛和冷却阶段污染水平较低,而在去毛和放血阶段污染水平较高。预测模型对沙门氏菌的准确率约为 85%,是监测猪肉屠宰微生物质量的一种工具。

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