Project Number: 2094-43000-007-05-A
Project Type: Cooperative Agreement
Start Date: Oct 1, 2010
End Date: Jul 31, 2015
1. Discover and validate diagnostic biomarkers that predict, diagnose, and/or distinguish apple postharvest physiological disorders. 2. Compile sets of biomarkers that could be used to predict, diagnose, or distinguish apple postharvest browning disorders and test their efficacy by classifying/reclassifying browning disorders based on new metabolic/genetic information. 3. Actively facilitate transfer of new biomarker-based technology for immediate implementation using current platforms and development of new tailored platforms utilizing biomarker-based technology.
Conduct an advisory panel, industry, and academic query that will assess current needs, scope, and understanding of diagnosis and non-chemical management of postharvest browning disorders, representing a variety of similar disorders occurring in multiple ecomically important cultivars, have been selected for this study. Employ experimental strategies that ulilize susceptable cultivars along with chemical and cultural controls that both control the selected disorders while accentuating metabolic differences and differences in gene expression between healthy apples and disorder-prone apples. Comprehensive metabolic and gene-expression profiling will be employed to discover disorder-specific diagostic biochemical and genetic biomarkers. Metabolic and gene-expession evaluations will be screened by the bioinformatics cooperators. Metabolic and gene expression profiles will be statistically modeled and mined by statistics/modeling cooperator to determine disorder-related metabolic changes and select biomarkers that best predict whether an apple will develop a certain disorder of differential that distinguish from others. Biomarkers associated with individual disorder will be compiled and compared to select those that will be the bases of discrimination of postharvest browning disorders. An economic study will validate cost-effectiveness biomarker-based management strategies and platforms. New tools will be used to classify or re-classify disorders using the new metabolic information. Diagnostic/prediction biomarkers and tools will be presented to fruit producers, retailers, and agricultural service companies in extension, industry, and scientific meeting to determine the best means for pilot testing and implementation of this new storage management and quality assurance technology.