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Correlation and Regression Analysis of Temperature of Chicken Carcasses in an Industrial Cooling Process
Author(s) -
Belledeli Bernardo D.,
Silveira Christian L.,
Soares Monica B.A.,
Treichel Helen,
Mazutti Marcio A.
Publication year - 2014
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.12076
Subject(s) - process (computing) , polynomial regression , regression analysis , mathematics , variables , statistics , correlation , computer science , operating system , geometry
In this work, correlation analysis was employed in order to determine how the process variables are associated with the temperature of chicken carcasses after the cooling process by immersion. Based on the correlation analysis, a second‐order polynomial model was proposed to predict the temperature of chicken carcasses given the values for the independent variables. The correlation analysis showed to be an important tool to be applied industrially because it enabled the choice of the variables that truly affect the cooling process of chicken carcasses. In addition, the correlation analysis demonstrated that first‐order interaction and quadratic terms of independent variables also affect the process and should be considered in the model. From these findings, a quadratic model capable of explaining about 45% of the variation of cooling process was proposed. This model can be used as a tool for making quick decisions in the industry or for quickly predicting the behavior of the cooling process given some specific conditions. Practical Applications This work describes a simple and practical procedure for statistical analysis of industrial process data, guiding the development of a quadratic model that can be further used for control and optimization purposes, improving the process quality of chicken carcasses as well as process profitability.