Project Number: 6040-42440-001-005-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2022
End Date: Oct 1, 2024
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.
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.