Location: Quality and Safety Assessment Research Unit
Project Number: 6040-42440-001-005-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2022
End Date: Oct 1, 2025
Objective:
To develop hyperspectral imaging technology and mechanical models with integrated machine learning algorithms to non-destructively evaluate commercially important traits in agricultural commodities such as myopathies in chicken breast meat and firmness/internal bruising in blueberries in order to provide tools for better quality management.
Approach:
To fulfill this research goal, we will develop methodologies to test and validate hyperspectral imaging and mechanical models at both the macro- and micro-scale to correlate quality factors with spectral features of agricultural commodities such as chicken and blueberries at both the intact product and cellular levels. A series of experiments will be conducted based on the following procedures: 1) analyze the spectral features of commodities with hyperspectral imaging; 2) develop machine learning models to understand external and internal spectral characteristics of commodities; 3) develop methods for product classification (occurence of myopathies in chicken breast meat and firmness/internal bruising in blueberries) that can be used for better quality control; and 4) build mechanical models to study the internal bruising patterns of blueberries during the harvesting process.
