Development of GLM regression models to predict the consumer acceptability of cooked ham based on analytical
Keshia Broucke1, Stephanie Van Weyenberg1, Anna Twarogowska1
1Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Brusselsesteenweg 370, 9090 Melle, Belgium.
Abstract:
Due to concerns about meat quality, health, sustainability and animal welfare, the typical Belgian meat products such as cooked ham are being threatened by a negative reputation. To address these concerns, an objective quality assessment tool was developed that could predict the consumer acceptability for a range of sensorial descriptors based on analytical parameters. A total of 28 commercial cooked hams were evaluated by a sensorial panel of consumers while simultaneously, a broad range of analytical tests were conducted on the same hams. Per sensorial descriptor, the analytical results and consumer acceptability for all cooked hams were processed by Generalized Linear Modelling (GLM). This holistic approach makes it possible to predict the consumer acceptability of a sensorial descriptor with great reliability and robustness by only using objective analytical parameters. An efficient R&D tool was developed to optimize the sensorial and analytical quality of the cooked ham that meets consumer demands.
More Related Videos
07:34Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
Published on: August 22, 2018
13:54A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
Published on: August 18, 2023
Related Concept Videos
01:11Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
01:19Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...