Evaluating the Effect of a Brewery By-Product as Feed Supplementation on the Quality of Eggs by Means of a Human Panel and E-Tongue and E-Nose Analysis

• Published in: Chemosensors Vol. 9; no. 8; p. 213
• Main Authors: Aguinaga Bósquez, Juan Pablo, Kovacs, Zoltan, Gillay, Zoltán, Bázár, György, Palkó, Csaba, Hingyi, Hajnalka, Csavajda, Éva, Üveges, Márta, Jókainé Szatura, Zsuzsanna, Barbulescu, Iuliana Diana, Begea, Mihaela, Tóth, Tamás
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-08-2021
• Subjects: Aroma compounds; Breweries; By products; Byproducts; chemometric; Consumption; Diet; Dietary minerals; Dietary supplements; Discriminant analysis; Eggs; Electronic noses; Electronic tongues; Feeds; Food; Food quality; Laboratory animals; laying hen; LDA; Organoleptic properties; PCA; Poultry; Principal components analysis; Proteins; Raw materials; Senses; Sensory evaluation; Sensory perception; sensory profile analysis; Vitamin A; zinc
• ISSN: 2227-9040; 2227-9040
• DOI: 10.3390/chemosensors9080213

The objective of our research was to evaluate the possible alteration of the organoleptic properties of eggs produced by hens (Lohmann Brown-Classic) fed with diets containing different doses of an industrial by-product enriched with organic zinc (Zincoppyeast, ZP): Control 0%, ZP 2.5%, and ZP 5.0%. Eggs were collected after 30 days (batch 1) and 60 days (batch 2) of feeding with the experimental diets and subjected to chemical, microbiological, human sensory, e-nose, and e-tongue analyses. There was no significant difference among the microbiological status of eggs of the three groups, but there were significant differences (p < 0.05) in the fat (9.5% vs. 9.3%) and protein contents (12.7% vs. 13.4%) of the Control and ZP 5.0% groups, respectively. Human sensory analysis showed no clear change in the organoleptic characteristics of the eggs. Using linear discriminant analysis (LDA), the e-tongue could recognize the three groups of eggs in batch 1 and batch 2 with 95.9% and 100% accuracy and had a prediction accuracy of 64.8% and 56.2%, respectively. When the eggs were incubating at 50 °C or 80 °C before the e-nose analysis, the groups of eggs could be recognized with 98.0% and 82.7% accuracy, and predicted with 68.5% and 62.2% accuracy, respectively, using principal component analysis-based discriminant analysis (PCA–DA). The aroma compounds and respective sensory descriptors showing changes among the different groups of eggs (batch, storage, and feeding) were identified based on the e-nose analysis. The supplementation of laying hens’ feed with the investigated industrial by-product can be applied without any substantial effect on egg quality, which can, however, be detected with advanced analytical methods.