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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Soil Management and Sugarbeet Research » Research » Publications at this Location » Publication #415042
Research Project: Genomic Mining of Sugar Beet Crop Wild Relative Germplasm Resources for New Sources of Disease Resistance

Location: Soil Management and Sugarbeet Research

Title: Standard area diagram for rating Fusarium oxysporum in sugar beet (Beta vulgaris)

Author
item Todd, Olivia
item Hanson, Linda
item Dorn, Kevin

Submitted to: bioRxiv
Publication Type: Pre-print Publication
Publication Acceptance Date: 6/11/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: The Fusarium oxysporum species complex is a group of harmful filamentous fungi that devastate sugar beet. These fungi cause Fusarium Yellows a disease which causes reduced plant growth, low crop yield, and reduced sugar production. To develop better resistant germplasm and manage this disease, scientists and growers need accurate methods to assess disease severity. USDA-ARS scientists from Fort Collins, CO and East Lansing, MI developed a photo-based, novel rating method for Fusarium Wilt in sugar beet that has been statistically proven to be accurate and precise. This tool, referred to as a Standard Area Diagram, allows ease of use in the field regardless of experience level with rating Fusarium diseases using a picture-based method. This Standard Area Diagram is applicable to growers, researchers and seed companies who wish to identify the degree of Fusarium Wilt severity in their fields. The use of this tool supports repeatable and consistent disease screening within USDA prebreeding programs to ensure production of highly resistant germplasm.

Technical Abstract: Members of the Fusarium oxysporum species complex are pathogens of sugar beet (Beta vulgaris L.) that causes Fusarium yellows. Fusarium yellows can reduce plant stand, yield, and extractable sugar. Accurate and precise rating methods are required for breeding programs selecting resistant germplasm and for disease assessment in fields. As part of developing rating methods, two standard area diagram versions using a highly virulent member of the Fusarium oxysporum species complex, Fusarium oxysporum strain F19 were created and tested on up to 18 inexperienced raters. Version 1 raters evaluated 75 images of Fusarium yellows symptoms in sugar beet with 9 category scales and a written description of the symptoms. Version 2 improved upon version 1 for ease of use, and in increasing category availability. There were no statistical differences in Lin’s Concordance Correlation Coefficient (LCCC) values to assess accuracy and precision between the two versions (Cb = 0.99 for both versions, 'c = 0.95 and 0.96 for version 1 and 2 respectively). In addition, five naïve Bayesian machine learning models which used pixel classification as a means to determine disease score were tested for congruency to the human estimates in version 2. Root mean square error was lowest compared to the “true” values for the unweighted model and a model where the necrotic tissue was given a 2x weight (12.4 and 12.6, respectively).