Combination of Computational Techniques to Obtain High-Quality Gelatin-Base Gels from Chicken Feet.

José C C Santana,Rosangela M Vanalle,Segundo A V Llanos,Dimitria T Boukouvalas,Felix M C Gamarra,Pedro C Mendoza,Wonder A L Alves,Sidnei A Araujo,Poliana F Almeida,Isabella Vasconcelos,Flavio Guerhardt,Nykael Costa,Ada P B Quispe,Fernando T Berssaneti

doi:10.3390/polym13081289

Abstract

With the increasing global population, it has become necessary to explore new alternative food sources to meet the increasing demand. However, these alternatives sources should not only be nutritive and suitable for large scale production at low cost, but also present good sensory characteristics. Therefore, this situation has influenced some industries to develop new food sources with competitive advantages, which require continuous innovation by generating and utilising new technologies and tools to create opportunities for new products, services, and industrial processes. Thus, this study aimed to optimise the production of gelatin-base gels from chicken feet by response surface methodology (RSM) and facilitate its sensorial classification by Kohonen’s self-organising maps (SOM). Herein, a 22 experimental design was developed by varying sugar and powdered collagen contents to obtain grape flavoured gelatin from chicken feet. The colour, flavour, aroma, and texture attributes of gelatines were evaluated by consumers according to a hedonic scale of 1–9 points. Least squares method was used to develop models relating the gelatin attributes with the sugar content and collagen mass, and their sensorial qualities were analysed and classified using the SOM algorithm. Results showed that all gelatin samples had an average above six hedonic points, implying that they had good consumer acceptance and can be marketed. Furthermore, gelatin D, with 3.65–3.80% (w/w) powdered collagen and 26.5–28.6% (w/w) sugar, was determined as the best. Thus, the SOM algorithm proved to be a useful computational tool for comparing sensory samples and identifying the best gelatin product.

Highlights

The results revealed limitations in the application and interpretation of house of quality (HOQ) within the food industry and that by using the fuzzy set theory, chain information was incorporated in the HOQ, which established good communication between departments
Based on the gelatin that presented the best set of sensory qualities, obtained by the self-organising maps (SOM) algorithm combined with the result obtained by response surface methodology (RSM) optimisation, a range of sugar and collagen contents can be used to obtain high quality gelatines, for example Gelatin
The optimisation indicated that the qualities of gelatin will be maintained if the gelatin is produced with levels between 0.8 and 1 for both the factors, implying the production of gelatines with sugar content ranging 26.5–28.5 g/100 g and collagen content ranging 3.62–3.80 g/100 g [23,33,35]

Summary

Introduction

Many countries have been economically influenced by the trade of chicken and despite the international crisis, the production of chicken increased in 2019 with a global poultry production of approximately 98.5 million tons. The three major world producers are USA, China, and Brazil, with 20.6%, 15.1% and 14.2% production, respectively [1]. Brazil was the second largest producer of chicken in 2015, at 13.5 million tons, but in 2019 it was the third largest producer, at 13.3 million tons and it was estimated to reach 14 million tons in. Brazil is the largest global exporter of chicken meat with 4.2 million tons, with an increase of 2% per year. The people of Brazil have been estimated to consume approximately 97.6 kg per capita of meat, comprising 47.3 kg chicken, 36.3 kg beef, and

Objectives

Methods

Results

Conclusion