Location: Physiology and Pathology of Tree Fruits Research
Project Number: 2094-43000-007-000-D
Project Type: In-House Appropriated
Start Date: May 4, 2015
End Date: May 3, 2020
Objective:
The long-term goal of this project is to develop various tools to assist in quality management of deciduous tree fruits. Specifically, during the next five years we will focus on the following objectives.
Objective 1: Integrate pre- and postharvest environment and commercial horticultural management practices with genomic and metabolomic regulation of apple and pear fruit quality.[C1; PS 1.A]
Sub-objective 1A: Determine how fruit position within the tree impacts pear metabolic profile, superficial scald, postharvest quality, and ripening.
Sub-objective 1B: Determine if inconsistent post-storage ripening of 1-
methylcyclopropene (1-MCP) treated d’Anjou pears is relatable to differential
absorbance (DA) value at harvest.
Sub-objective 1C: Determine if pre-storage light exposure impacts apple peel
metabolic responses to postharvest chilling.
Objective 2: Enable new apple, pear and sweet cherry fruit biomarker-based quality management strategies. [C1; PS 1.A]
Sub-objective 2A: Determine if apple aroma volatile production changes when fruit are stored in environments conducive to development of physiological disorders.
Sub-objective 2B: Develop biomarker-based risk monitoring protocols using existing validated gene expression and metabolic biomarkers for early detection of apple and pear peel and cortex storage disorders.
Sub-objective 2C: Determine if sweet cherry fruit pitting, cracking and browning is relatable to fruit epidermis and wax composition.
The two objectives both rely on metabolomic and genomic techniques to investigate field and postharvest factors that impact fruit quality. The link from sub-objective 2B to 1A reflects biomarkers identified in the previous project period to be validated for apple (2B) as well as applied initially for pear (1A, 2B).
Objective 1 is focused on enhancing knowledge of how field horticulture impacts postharvest fruit quality with emphasis on fruit physiological disorders and ripening. The sub-objectives (1A, 1B) are designed to generate new information regarding the impact of pear field horticulture on fruit quality and ripening metabolism, particularly disorder-related metabolomics and genomics.
Sub-objective 1C also is focused on generating disorder-related metabolomic information for apple fruit sun damage originating prior to harvest.
Application of metabolomic and genomic techniques to disorders arising in the postharvest environment is the basis for Objective 2. Can assessment of apple fruit volatiles accumulating during storage in environments known to cause disorders provide a means to avoid disorder development. (2A) Biomarkers identified for apple disorders in the previous project plan will be validated with multiple fruit lots and cultivars (2B). Disorder metabolism of sweet cherries (2C) will be explored using a metabolomic approach.
Approach:
Fruit from commercial orchards will be harvested then stored at ARS-Wenatchee and in commercial CA rooms. Fruit quality, metabolites, and mRNA will be characterized at harvest and after storage using standard methods.
Hypothesis 1A: Fruit position on the tree directly impacts maturation, superficial scald susceptibility, ripening and storability, and associated metabolism. Pears from two extreme light environments within the tree canopy will be grouped based on differential absorbance (DA). Fruit quality and disorders will be assessed at harvest and after storage. Metabolites and mRNA in peel collected from each canopy location/DA group will be analyzed. Results will be mined for metabolites and mRNA associated with physiological disorders.
Hypothesis 1B: Inconsistent post-storage ripening of 1-MCP treated d’Anjou pears is relatable to differential absorbance (DA) value at harvest. Pears will be exposed at harvest to 1-MCP for 16 hours, then stored at 1 degree C. After storage fruit will be evaluated for disorders and fruit quality characterized.
Hypothesis 1C: Apple peel metabolism following cold storage imposition is altered by pre-harvest light exposure. ‘Granny Smith’ apples exposed to direct sunlight will be harvested and sorted by sun damage. Apples will be stored at 1 degree C and after storage, untargeted metabolic profiling of ~800 metabolites will be performed on peel and cortex tissue collected at each sampling date. Multivariate and univariate statistical approaches will be employed to link changes in specific areas of metabolism with sunscald and superficial scald development.
Hypothesis 2A: Apple aroma volatile production changes when fruit are stored in environments conducive to development of physiological disorders. ‘Honeycrisp’ apples stored in controlled atmosphere chambers will be subjected to atmospheres known to cause physiological disorders. Volatile compound samples will be collected after various intervals and after 180 days, fruit will be removed from storage and evaluated for incidence and severity of external disorders.
Hypothesis 2B: Metabolic and gene expression superficial scald based risk assessment can be used to indicate when scald risk in a storage room is elevated.‘Granny Smith’ and ‘Delicious’ apples, and Anjou pears will be stored in CA at 1 degree C. Superficial scald will be evaluated following various lengths of storage. Storage atmospheres will be evaluated for volatile compounds determined to be useful for scald risk assessment.
Hypothesis 2C: Pitting and cracking incidence of sweet cherries is associated with altered epidermal metabolic profile compared with undamaged fruit. ‘Rainier’ sweet cherries will be subjected to uniform bruising using a steel ball dropped onto the fruit. Micro-cracking and stomata/lenticel number will be estimated by staining fresh whole fruit with acridine orange and counting micro-cracks at five random positions on each fruit using florescence microscopy. Waxes extracted from fruit will be analyzed using HPLC-QTOF-MS. Metabolic differences linked with cracking and epidermal defects will be identified using untargeted metabolic profiling methods developed for apple.
