In-depth analysis of serum metabolomics, meat quality spectroscopic and imaging data

• Grant number: 23/02311-5
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: May 01, 2023
• End date: August 29, 2023
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Animal Production
• Principal Investigator: Nara Regina Brandão Cônsolo
• Grantee: Eduardo Solano Pina dos Santos
• Supervisor: Yash Dixit
• Host Institution: Faculdade de Zootecnia e Engenharia de Alimentos (FZEA). Universidade de São Paulo (USP). Pirassununga , SP, Brazil
• Institution abroad: AgResearch, Grasslands, New Zealand
• Associated to the scholarship: 22/07950-3 - Plasma metabolomics characterization of bovines raised in the Pantanal area, BP.IC

Abstract

The use of metabolomics in animal production has provided a deep knowledge of the molecular bases that integrate several lines of research. Considering the increase in the number of animals on the extinction list registered each year, it becomes essential to investigate the preservation of cataloged species with high risk of extinction, especially species endemic to Brazil. In this context, aiming to expand the scope of knowledge about the breeds adapted to the Pantanal biome, the present study proposes the creation of the first metabolomics database of the Pantaneiro and Curraleiro breeds. The results of the present will be analyzed in partnership with AgResearch, NZ, during the period of Internship and Research Abroad (BEPE). These results will increase the knowledge of the molecular basis associated with these breeds and will allow the exploration of metabolomic pathways correlated to resistance characteristics, adaptability and origin of these animals. Associated with the analysis of data from the project in Brazil, the present proposal for a research internship abroad plans to investigate the quality of meat in mixture with viscera through hyperspectral imaging. In general, meat and viscera are rich sources of nutrients and their formulation needs for meat products, which we believe in this, the great opportunity for joint research data to understand and highlight such nutritional quality and provide better acceptance by the consumer. However, because meat is a highly heterogeneous substrate varying between cuts and within cuts, the hypothesis suggests that there is an association between nutrient concentration and meat particles and viscera. Advanced data analysis based on multiblock modeling will be applied to the hyperspectral data to validate this idea. The data set to test this hypothesis is being collected through hyperspectral imaging (HSI) camera and chemical data, considered standard analysis, (fat, fatty acids, moisture, vitamins and mineral content) from 33 samples of ground beef prepared from 3 different animals, 6 cuts and 5 muscle + viscera mixtures. The images will be analyzed in order to segment the particle distribution in the products. Then, multi-block modeling will be applied to investigate the association between the nutrient profile and the spectral data in the segmented regions, thus identifying correlations between the particle distribution and the nutrient profiles. (AU)