Animal Husbandry Risk Assessment Based on Data Analytics

Abstract

This paper presents an approach and model for data integration and risk analysis in animal husbandry production. The proposed model for data integration and its components are described in detail, including the organization of the workflow, the modules, and their connections used for data exchange. Based on the presented workflow, experiments were conducted using statistical data on the population of domestic animals.  The analysis of the results from these experiments reveals trends in the risk associated with animal husbandry risk analysis in livestock production and in particular disease risk assessment in cattle because of ingestion of chemical substances during forage cultivation. Based on year-by-year studies and quantitative metrics, it has been established that the model for processing and analyzing statistical data to assess the risk of cattle diseases from ingesting soil-borne chemical compounds is applicable in the field of animal husbandry. This model enables the tracking of trends in the use of artificial fertilizers and chemicals over a specified period, based on pre-collected statistical data.