Location: Sunflower Improvement Research
Project Number: 3060-21000-047-016-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Aug 1, 2023
End Date: Jul 31, 2025
Objective:
(1) Test methods for automated assessment of sunflower seed damage caused by the red sunflower seed weevil, and (2) develop a sensor-based model apparatus for understanding seed weevil infested sunflower and silphium seed separation through combines.
Approach:
The process of breeding crop plants involves repeated scoring of many aspects of plant phenotypes and performance on large numbers of lines. As a result, evaluation of plant traits for which data are collected by scientists or technical support staff is often costly and slow. However, recent research in suggests that technology (e.g., various sensors, artificial intelligence) may be able to perform many phenotyping tasks with improvements to speed or accuracy. As a first step towards improved phenotyping for sunflower breeding applications, various technologies will be evaluated for their utility in different phenotyping tasks. First, varied imaging technologies types including hyperspectral imaging will be assessed versus a traditional, human-aided scoring of samples with damage from a sunflower insect pest. Second, a model apparatus of air column separation, akin to separation in commercial combines, will be developed to better understand separation of seed types of silphium, a sunflower relative, and red sunflower seed weevil infested seeds. This work is intended to complement the current CRIS project (3060-21000-043-000-D) Subobjective 2A “Evaluate susceptibility of sunflowers to insect pests and develop genetic markers for host plant resistance traits.” The results should help determine whether new tools, can accelerate the efficiency of breeding for target traits in sunflower breeding.
