A DIAGNOSTIC TOOLBOX FOR INTEGRATED MANAGEMENT OF APPLE POSTHARVEST NECROTIC DISORDERS
Project Number: 5350-43000-006-14
Start Date: Sep 30, 2010
End Date: Sep 29, 2014
1. Improve prediction and diagnosis of familiar and novel storage disorders to direct treatment and storage management decisions (focus areas 3 and 4).
2. Improve fruit quality assurance and reduce agrichemical input and environmental impact (focus areas 3, 4, and 5).
3. Integrated biomarker-based diagnostic protocols with existing protocols (focus area 4).
1. Discover and validate diagnostic biomarkers that predict, diagnose, and/or distinguish apple postharvest physiological disorders (Scientific objective).
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. (Scientific and outreach objective).
3. Estimate the economic impact (both benefits and costs) to the apple industry of utilizing biomarker-based diagnostic tools to manage apple postharvest physiological disorders. (Scientific and outreach objective).
4. Actively facilitate transfer of new biomarker-based technology for immediate implementation using current platforms and development of new tailored platforms utilizing biomarker-based technology (Outreach objective).
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 from a nation-wide industrial standpoint. Distinct postharvest browning disorders, representing a variety of similar disorders occurring in multiple economically important cultivars, have been selected for this study. Employ experimental strategies that utilize susceptible 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 diagnostic biochemical and genetic biomarkers. Metabolic and gene-expression evaluations will be team-based according to the disorder(s) evaluated. Gene expression data 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 or differentiate that disorder 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 meetings to determine the best means for pilot testing and implementation of this new storage management and quality assurance technology. Specialty Crops Research Initiative. In kind matching funds will coming from Universities, Industry, and International collaborators (Katholieke Universiteit Leuven, Belgium). Documents Reimbursable with NIFA. Log 41039. Formerly 5350-43000-005-24R (7/10).