Project Number: 3020-43440-009-06-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2018
End Date: Sep 30, 2021
Objectives are to develop application-specific imaging algorithms that extract useful information from single kernels of grain. In one instance imaging will be combined with near infrared spectra of kernels to evaluate chalkiness in rice, in another, to define general kernel morphology (length width, shape, volume) of small grains. These applications will allow integration into automated measurement systems.
Software is needed to assist in the examining of grain for defects and to assess the morphology of single kernels of grain. This will further the understanding of imaging methods that will allow defect detection and measurement of grain morphology related to the plant environment effects. To address this goal,imaging alogorithms will be developed to measure grain morphology and identify factors that allow high-accuracy NIR sorting of haploid kernels and implement high-throughput sorting. This new tool will then be used to evaluate imaging and near infrared methods to determine rice chalkiness and imaging for grain morphology. ARS can then use this information to develop the engineering methods to facilitate high-throughput sorting.