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 Physiology and Pathology of Tree Fruits Research: Wenatchee, WA
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ARS Home Pacific West Area Wenatchee, Washington Physiology and Pathology of Tree Fruits Research Research





- Rudell, David
- Honaas, Loren
- Leisso, Rachel
- 2023
- 2022
- 2021
- 2020
- Publications
- Plant Diseases (303)
- Product Quality and New Uses (306)

Research Project: Enhancement of Apple, Pear, and Sweet Cherry Quality **Location:
                            Physiology and Pathology of Tree Fruits Research** 2022 Annual Report **Objectives**
                                

The long-term goal of this project is to develop tools for quality management of deciduous tree fruits. Specifically, during the next five years we will focus on the following objectives.

Objective 1:  Resolve production and post-harvest environmental and genetic regulation of apple, pear, and sweet cherry quality.  [NP306, C1, PS1A]  

Sub-objective 1A:  Identify if interactions among storage temperature protocol, controlled atmosphere establishment date, and inhibition of ethylene action impact apple and pear fruit market quality and development of physiological disorders.

Sub-objective 1B: Determine if dynamic control of controlled atmosphere (CA) oxygen concentration can enhance apple fruit post storage volatile production without fruit quality loss.

Sub-objective 1C:  Determine relationship between sweet cherry cutin composition, gene expression, and surface defects caused by sun stress following harvest.

Objective 2:  Use of biomarkers to enhance/assist commercial apple and pear management strategies.  [NP306, C1, PS1A]

Sub-objective 2A:  Determine metabolic and genomic changes related to apple and pear fruit maturation and postharvest chilling.

Sub-objective 2B:  Identify metabolic and genomic changes linked with fruit quality loss and physiological disorder development during cold storage. **Approach**
                                

Fruit from commercial orchards will be harvested then stored at ARS-Wenatchee in controlled atmosphere (CA) chambers. Fruit quality, metabolites, and RNA will be characterized at harvest and after storage using standard methods. Hypothesis 1A:  The manner in which postharvest technologies are imposed results in additive, synergistic, and antagonistic effects on fruit quality and disorder development.  Apple and pear fruit from commercial orchards will be stored continuously at 0.5°C or at 10°C for 7 days, then at 0.5°C.  Fruit will be exposed to 0 or 1 μL L-1 1-MCP for 16 hours, then in air or a CA initiated 1 or 9 days after harvest.  Following 6 to 8 months, fruit will be removed from storage and held 7 days at 20°C to allow post-storage quality loss and disorder development to occur. Hypothesis 1B: The manner in which postharvest technologies are imposed results in additive, synergistic, and antagonistic effects on apple firmness and related gene expression.  Tissues from ‘Gala’ apples stored at various temperatures, in air or CA, with or without 1-MCP treatment will be collected over time. Fruit firmness will be assessed at the same time as tissue harvest for transcriptome analysis plus after 7 at 20°C. Hypothesis 1C: Reciprocity is valid for mean oxygen concentration during CA storage and apple fruit post-storage volatile production and quality.  Honeycrisp’ apples will be CA stored continuously at 5.1% O2 as well as at 2.5% O2 with repeated periods in air to average 5.1% O2 over the storage period. Control fruit will also be held continuously in air. Fruit removed from storage after 4 and 8 months will be assessed for external disorders on the day of removal, then will be held 7 days at 20°C in air. On day 7, volatile compounds emitted from intact fruit will be collected and analyzed. Hypothesis 1D: Cuticle composition and gene expression will be impacted by sunlight exposure.  Sweet cherries will be harvested from the tree periphery and interior or following shading with black cloth.  Fruit peel will be assessed for microcracks using microscopy.  RNA will be collected from peel sections with contrasting cutin deposition patterns using laser microdissection.  Hypothesis 2A: Changes in molecular phenotypes (metabolites and gene activity) can be linked with progression of fruit maturation and low temperatures during storage. Apple and pear cultivars will be harvested over 12 weeks bracketing horticultural maturity.  Fruit maturity, metabolite and RNA content will be assessed using standard methods. Maturity dependent responses to abiotic stress will consist of holding fruit at 20 or 1°C for 48 hours.  Hypothesis 2B: Specific changes in apple and pear cell membrane components are provoked by high carbon dioxide, low oxygen CA leading to higher risk of developing carbon dioxide related storage disorders. Apples treated or not with DPA will be stored in CA at 0.5% O2 and up to 5% CO2. Fruit quality and disorders will be assessed after storage as will fruit metabolites and RNA. **Progress Report**
                                

For Objective 1, research continued on Sub-objective 1A. ‘Fuji’, ‘Gala’, and ‘Granny Smith’ apples were cooled to 34 or 50 degrees F within 24 hours of receipt after harvest. Fruit cooled to 50 degrees F were held 7 days, then cooled to 34 degrees F. At 48 hours after receipt, some fruit at both temperatures were exposed to a controlled atmosphere (CA) containing 1% oxygen and 1% carbon dioxide. After 9 days, additional fruit were exposed to CA. All fruit was held up to 8 months in air or CA, then removed from cold storage and held in air at 68 degrees F for 7 days. As observed in year 1, delayed cooling to 34 degrees F, storage in and delay of CA as well as storage duration impacted development of physiological disorders with the impacts varying with cultivar. Overall delayed cooling with rapid initiation of CA has positive impacts on physiological disorder incidence while lacking negative impacts on fruit quality (sugar and acid content, firmness. For Hypothesis 2, the manner in which postharvest technologies are imposed results in additive, synergistic, and antagonistic effects on apple firmness and related gene expression. ‘Gala’ gene expression patterns relatable to various storage regimes (cooling and CA delay, inhibition of ethylene action or not) identified in year 1 experiments were validated using qPCR. Improved annotation of the ‘Gala’ genome allowed identification of additional genes related to fruit quality changes occurring in the postharvest environment. Research continued for Sub-objective 1B. As in year 1, a simple relationship between average CA oxygen content and post-storage volatile production was not observed due in part to an effect of fruit storage duration. An effect of production season and/or harvest maturity was apparent when year 1 and 2 results were compared. The hypothesis that post-storage volatile production can be manipulated by CA oxygen content without loss of fruit quality (sugar and acid content, firmness, disorders) is supported by these additional results.

In support of Sub-objective 1C, ‘TipTop’ cherry fruit peel analyses identified and validated the presence of compounds previously unreported for sweet cherry. As in year 1, peel composition differed between blush-side and shade-side.
Research continued for Objective 2, Sub-objective 2A. Harvest and gene expression analysis for ‘Granny Smith’ and ‘Delicious’ to validate previous results was completed. Fruit quality both at harvest and during the postharvest period was related to shifts in gene expression across the commercial harvest period with 66 shared genes that had activity correlated with starch clearing and superficial scald risk. ‘d’Anjou’ pear maturity genes previously identified to exhibit differential co-expression were validated. These results confirm gene-to-gene relationships that may be useful biomarkers to predict maturation progression. 

Progress on Sub-objective 2B included storing ‘Fuji’ apples in CA at combinations of 0.1, 0.5, or 1% oxygen (O2) and 0.1, 1, 2, and 5% carbon dioxide (CO2). Internal and external disorders were assessed at 3 and 6 months. Combinations of the lowest O2 and highest CO2 had the worst disorder outcomes. Both peel and cortex samples were taken to compare with existing in-house apple disorder symptom metabolic fingerprints to verify which phytochemicals are most related to CO2 sensitivity. These results support the hypothesis that apple fruit disorders can be diagnosed by analysis of affected tissues, an objective technique that could be useful for industry to assure disorder cause is identified. Multiple lots of d’Anjou pear fruit were treated with crop protectants that control superficial scald and stored under ultra-low or conventional CA (0.5 or 1.5% O2) with high or low CO2 (5 or 0.5%) with the intent of determining whether ethoxyquin or squalane emulsions also control symptoms of peel CO2 sensitivity. No peel disorders were associated with CO2 sensitivity. Black speck, a disorder long suspected to be caused by ultra-low O2 and/or possibly CO2 sensitivity, was most prevalent in more conventional CA conditions. Symptoms were controlled by both ultra-low O2 CA, ethoxyquin, and squalane emulsions indicating similarity with superficial scald. This is another instance where misdiagnosis or incomplete understanding could lead to improper commercial mitigation measures and additional crop losses. **Accomplishments**
                                

1. Apple peel disorders associated with increased orchard temperatures and sun exposure continue to contribute substantially to postharvest losses. In a collaborative project with Washington State University, ARS scientists in Wenatchee, Washington, have developed a fruit sorting protocol to assess sun-related postharvest disorder risk. Using this protocol, sunscald, a sun-related disorder of many important apple cultivars, including highly sensitive ‘Granny Smith’ apples, was predicted at harvest before symptoms developed with over 95% accuracy. Adaptation of this system to existing commercial apple fruit sorting lines or even integration into field sorting lines could nearly eliminate sun-related postharvest disorders and crop loss from apple cold chains. **Review Publications**
                            *Lee, J., Leisso, R.S., Rudell Jr., D.R., Watkins, C.B. 2022. 1-Methylcyclopropene differentially regulates metabolic responses in the stem-end and calyx-end flesh tissues of 'Empire' apple during long-term controlled atmosphere storage. Postharvest Biology and Technology. 192. Article 112018. https://doi.org/10.1016/j.postharvbio.2022.112018.*
                                *Hargarten, H.L., Mattheis, J.P., Honaas, L.A. 2022. Monitoring effects of rootstock genotype and soil treatment strategy on postharvest fruit quality in ‘Gala’ apple. HortScience. 57(7):789–798. https://doi.org/10.21273/HORTSCI16407-21.*
                                *Vieira, M., Argenta, C., Brancher, T.L., de Freitas, S.T., Mattheis, J.P. 2022. Relationship among dry matter content and maturity indexes at harvest and quality of 'Gala' apples after storage. Revista Brasileira de Fruticultura. 44(2). Article e-841. https://doi.org/10.1590/0100-29452022841.*
                                *Argenta, L.C., do Amarante, C.V., de Freitas, S.T., Brancher, T.L., Nesi, C.N., Mattheis, J.P. 2022. Fruit quality of ‘Gala’ and ‘Fuji’ apples cultivated under different environmental conditions. Scientia Horticulturae. 303. Article 111195. https://doi.org/10.1016/j.scienta.2022.111195.*
                                *Mattheis, J.P., Felicetti, D., Rudell Jr, D.R. 2021. ‘d’Anjou’ pear metabolism during ultra-low O2, low CO2 controlled atmosphere storage reflects disorder outcome. Postharvest Biology and Technology. 185. Article 111781. https://doi.org/10.1016/j.postharvbio.2021.111781.*
                                *Hamilton, A.M., Ruiz-Llacsahuanga, B., Mendoza, M., Mattheis, J.P., Hanrahan, I., Critzer, F.J. 2021. Persistence of Listeria innocua on fresh apples during long-term controlled atmosphere cold storage with postharvest fungal decay. Journal of Food Protection. 85(1):133–141. https://doi.org/10.4315/JFP-21-232.*
                                *Hadish, J., Biggs, T., Shealy, B., Bender, M.R., McKnight, C., Wytko, C., Smith, M., Feltus, A.F., Honaas, L.A., Ficklin, S. 2022. GEMmaker: Process massive RNA-seq datasets on heterogeneous computational infrastructure. BMC Bioinformatics. 23. Article 156. https://doi.org/10.1186/s12859-022-04629-7.*


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