1a.Objectives (from AD-416):
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. Transfer of new biomarker-based technology for immediate implementation adapting existing laboratory-based and field-based analytical platforms.
1b.Approach (from AD-416):
Previous results indicate postharvest experiments designed to produce necessary contrasts can be used to develop viable biomarkers for physiological disorder prediction, diagnosis, and differentiation. Until recently, metabolic and gene expression evaluation approaches have focused on one or a few pathways with known associations to a particular disorder. While focused approaches were insightful, these approaches have not allowed development of new tools for superficial scald control or the discovery of physiological bases of other apparently unrelated physiological disorders. Our proposed research relies instead on comprehensive analytical approaches that avoid preconception of disorder-related metabolic/genetic processes. This allows discovery of prospective biomarkers not previously associated with superficial scald and other disorders.
This project relates to objective 1 of the associated in-house project which seeks to identify factors that influence postharvest fruit quality and development of market limiting physiological disorders. Chemical changes within apple peel and cortex can be exploited to indicate whether there will be significant storage losses due to different browning disorders before those losses occur as well as distinguish similar looking browning disorders. Major storage trials of 3 major US apple varieties and 4 economically significant storage disorders have been completed. Evaluation of peel and cortex chemistry under conditions that may lead to disorder development has yielded candidate biomarkers that may be used to assess risk for these disorders. The work of chemical and gene expression analysis and mathematical analysis of the large datasets is ongoing. An assessment of the impact biomarker based tools may have on apple production is ongoing. It is expected that the knowledge gained from this project will enhance our understanding of these disorders to improve how apple producers store fruit, develop new apple varieties with less likelihood of developing these disorders, and provide advanced tools to assess disorder risk. Biomarker based tools for assessing plant health is a relatively novel concept that mirrors medical diagnostics technology and has widespread potential promoting food quality and agricultural sustainability.