Desenvolvimento de um protótipo de baixo custo para análise físico-química do leite cru refrigerado

• Ano de defesa: 2020
• Autor(a) principal: Comachio, Katiane de Oliveira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Medianeira; Brasil; Programa de Pós-Graduação em Tecnologias Computacionais para o Agronegócio; UTFPR
• Palavras-chave em Português: Agricultura de precisão; Leite - Qualidade; Desenvolvimento rural; Precision farming; Milk - Quality; Rural development; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO; Engenharia/Tecnologia/Gestão
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/5398

The requirement with the quality of the food drove the improvementve the improvement of hygiene and control techniques in all stages of obtaining the final product, from the raw material to availability to the final consumer. Regarding the quality of products from bovine milk, in Brazil, the quality of the raw material is improving at a slower pace than expected. Several reasons can be cited, among them the large number of small milk-producing properties, many of which operate in poor hygiene conditions and there is no greater control in post-milking conservation. The objective of this work is to develop a low cost equipment that assesses the physical and chemical characteristics of raw milk. The prototype is composed of sensors capable of detecting some important physical-chemical analyzes for maintaining milk quality, such as pH, temperature and electrical conductivity. Were collected 104 samples of refrigerated raw milk from the truck compartments that arrived at the processing unit during November 11ththrough December 11th, 2019 and the prototype was used to analyze the pH, temperature and electrical conductivity of these samples. The descriptive statistics method, Anderson-Darling normality test and correlation between pH variables were applied to verify the accuracy of the data. It was found that the data did not obey a normal distribution, had a more pronounced curve shape (leptocurtic) and the pH Prototype and pH Dairy variables had a 30% correlation. Even so, it was possible to establish a confidence interval with 5% of significance for the three variables analyzed, being 6.9-7.1 for the mean of the Prototype pH, 20.08-21.14 for the mean of the Temperature and 93.7-108.1 for the average conductivity. The developed equipment achieved the objective of low cost and proved to be promising, but requires improvement.