A DIAGNOSTIC TOOLBOX FOR MANAGEMENT OF APPLE POSTHARVEST NECROTIC DISORDERS
Plant, Soil and Nutrition Research
2013 Annual Report
1a.Objectives (from AD-416):
Fruit tree stakeholders have identified the need for effective, consistent control measures for apple postharvest physiological disorders and the development of additional control and management tools to replace or amend existing programs. Metabolic and genetic biomarker-based tools that are cost-effective will be developed under this project to predict, diagnose, and distinguish postharvest necrotic disorders to assure that high quality, disorder-free product remain available across the supply chain. Implementation of biomarker-based diagnostic tools represents a pragmatic, technology-driven shift from the treatment-based apple storage of the present to more economically feasible, sustainable, management-based systems, similar to those effectively applied in orchard systems such as integrated pest management.
1b.Approach (from AD-416):
Our scientific approach applies metabolic and gene expression profiling to discover biomarkers that can be used to predict, diagnose, and distinguish economically significant apple postharvest physiological disorders. We will use this information to develop prototype predictive and diagnostic storage management tools and to re-evaluate prior understanding of disease classification based on distinguishing biomarkers. To demonstrate the economic feasibility of biomarker-based disorder management, the costs and benefits of biomarker-based tools will be compared with treatment-based tools alone or in combination. Long-term net benefits of each system will be simulated under various regional and policy environments to provide a range of plausible economic outcomes for stakeholders across the supply chain.
This project is part of a broader multi-institutional effort directed toward eventual development of diagnostic tools for predicting apple fruit storage disorders negatively impacting fruit appearance or quality so that decisions can be made regarding optimal use of specific apple storage lots. For example, apple storage lots showing markers for late term apple fruit disorders might be targeted for early fresh use or sent to the processing stream if stored for a longer period so as to recover maximal product benefit. Specific activities under this project include testing of candidate gene expression patterns that may serve as early warning markers for various storage regimes and pre-storage treatments that might impact later development of fruit storage disorders. In the current year, we have mined whole genome transcriptome profiling data of apple fruit under various storage conditions and selected a number of candidate marker genes. These were then confirmed via qPCR analysis and then tested on secondary tissue lots stored under the same conditions. The same data was used for comparative genomics with tomato to identify homologous apple genes corresponding to defined and characterized tomato genes.