Source: CORNELL UNIVERSITY submitted to NRP
PRE AND POSTHARVEST PHYSIOLOGY AND ETIOLOGY OF PHYSIOLOGICAL DISORDERS IN ‘HONEYCRISP’ APPLES
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
1032703
Grant No.
2024-67023-42846
Cumulative Award Amt.
$300,000.00
Proposal No.
2023-08086
Multistate No.
(N/A)
Project Start Date
Aug 15, 2024
Project End Date
Aug 14, 2026
Grant Year
2024
Program Code
[A1601]- Agriculture Economics and Rural Communities: Small and Medium-Sized Farms
Recipient Organization
CORNELL UNIVERSITY
(N/A)
ITHACA,NY 14853
Performing Department
(N/A)
Non Technical Summary
'Honeycrisp' apple is a highly profit cultivar because of its flavor and texture. However, the cultivar is susceptible to a wide range of physiological disorders during storage and shelf life. The most important are bitter pit, which is considered a warm temperature storage disorder, and soft scald which is a chilling injury. The recommendation for postharvest management of this cultivar is to condition fruit at 10 ?C for 1 week before transferring them to 3 C to avoid the development of soft scald. However, the conditioning treatment exacerbates bitter pit with associated economic losses. We have observed a strong negative correlation between soft scald and bitter pit development over several years. The physiology and etiology behind this association is not well understood. Our hypothesis is that fruit are either susceptible to bitter pit or soft scald, and in some exceptions to the two disorders. The objective of this research is to study the effects of different pre and postharvest factors on bitter pit and soft scald susceptibility. The effects of different factors on the postharvest physiological disorder development in 'the cultivar will be investigated in relation to rootstock cultivar, nutritional and hormonal balance of the fruit during fruit development, at harvest, and during storage. The results will contribute to the development of new cultivars with resistance to both disorders. Our results will help the apple industry mange the two disorders during storage to reduce the total loss of apples throughout the supply chain and thereby improve sustainable agricultural production.
Animal Health Component
80%
Research Effort Categories
Basic
10%
Applied
80%
Developmental
10%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
20311101020100%
Goals / Objectives
Objective 1Experimentally determine how specific rootstocks alter physiological disorders and how physiological disorders in turn alter fruit quality. (Year 1)Our first objective focuses on understanding the relationship between rootstocks, environment, fruit quality, and physiological disorder development in the apple cultivar 'Honeycrisp'.Rational. In contrast to research on bitter pit, the rootstock effect on soft scald development have not been addressed except for our preliminary study from this year. Our hypothesis that rootstock is the main driver of scion mineral nutrient concentrations, affecting vigor and yield and importantly fruit susceptibility to physiological disorders. We expect that rootstocks with high bitter pit susceptibility will have lower soft scald incidence during storage.Sub objective A. Study the effects of different Geneva, Malling and Budagovsky rootstocks on the interaction between bitter pit and soft scald.Subobjective B. Study the regional effects of rootstocks on bitter pit and soft scald interaction.Objective 2Understand the mechanisms of bitter pit and soft scald development in relation to endogenous hormones and minerals balance. (Year 1)Rational. The effects of mineral nutrient profile and balance in relation to rootstock and the interaction between soft scald and bitter pit has not yet been explored. Some research examining the effects of different rootstocks on the scion hormones concentration were investigated by the Co-PIs Robinson and Fazio in previous work. However, the relationship between hormone concentration at different stages of fruit development and physiological disorder development during storage remain has not been studied. We hypothesize that the influence of rootstock on hormone concentrations, such as abscisic acid (ABA), may reduce bitter pit and enhance soft scald development or vice versa. In addition, mineral nutrient balance in the fruit as influenced by rootstock could contribute to development of both physiological disorders.Subobjective A. Understand the effects of mineral balance in relation to rootstock on the interaction between bitter pit and softs scald.Subobjective B. Study the effects of the hormonal balance during fruit development starting from fruit set until harvest in relation to rootstock and physiological disorder development in the field and during storage.Objective 3Characterize the variation in fruit physiological disorders and model the relationships among environments, orchard management, storage temperature manipulation, and fruit quality. (Year 2). Rationale: Prediction models for both bitter pit and soft scald based on their interaction are needed but such relationships have not yet been studied in relation to pre and postharvest factors. No studies have identified the interaction between the two disorders in 'Honeycrisp' fruit and their mechanisms through the different fruit development stages and through postharvest storage. An integrative model to predict bitter pit and soft scald. Based on our preliminary data and results of the first objective, we will build a preliminary model to predict bitter pit and soft scald during storage based on their interaction of rootstock genotype and abiotic factors.
Project Methods
Growers, undergraduate students, agricultural stakeholders, storage operators, women in agriculture, scientists, plant physiologists, and extension educators. Sample collection, fruit maturity, quality, and physiological disorder assessment. Fruit will be collected from the various 'Honeycrisp': rootstock combinations 3 weeks before anticipated harvest (typically Sept 15) to predict bitter pit based on the passive and peel sap analysis methods. Another set of fruit will be harvested at commercial harvest and will be transported to the postharvest laboratory at Cornell campus in Ithaca. The occurrence of fruit physiological disorders will also be assessed in the field at harvest. In addition, fruit maturity indices will be measured including internal ethylene concentration (IEC), fruit firmness, soluble sugar content (SSC), titratable acidity (TA) starch patter index (SPI) and IAD value index to measure the chlorophyll content. Clean fruit with no external disorders will be stored at 3°C for 4 months plus 4 days at 20°C. During storage, bitter pit, soft scald, and any other external disorder will be assessed monthly. After storage, fruit quality and internal and external physiological disorders will be assessed.will be used from rootstock duplicate field trials run by Co-PI Robinson in Western NY at Geneva and in the Champlain Valley NY. Results will be analyzed in relation to the weather data in the two regions to understand the effects of the environment and rootstock on physiological disorder development at harvest and during storage.Weather data: Weather data will be collected from the closest weather stations to the orchards in the two regions starting from full bloom until harvest. Primary attention will be given to temperature, precipitation, and sunshine duration, but we will also collect windspeed/direction, humidity, and temperature range daily. We will use these to calculate growing degree days (GDD): a standard measure of cumulative temperature effect on fruit development.We will collect apples from trees featuring apple rootstocks with known contrasting ability to generate bitter pit in 'Honeycrisp' trees (G.210, M.9 consistently high levels and G.969, G.214, and B.9 consistently low levels of the K/Ca ratio to predict the incidence of bitter pit in individual apple fruit. Samples will be collected monthly at different stages of fruit development starting from fruit set until harvest and during four months of cold storage. Four replicate samples of 5 fruit from each of the rootstocks will be collected at fruit set, and at three weeks before anticipated harvest and at commercial harvest for analysis of macro and micro minerals.Mineral analyses. XRF instrument (Bruker Tracer 5i) will be used to monitor potassium (K) and calcium (Ca) non-destructively. In addition, mineral nutrient concentrations in fruits will be measured to include tissues from the fruit peel taken from the entire 5 fruit per replicate because soft scald might be developed at any part of the peel whereas bitter pit is usually found in the calyx end of the fruit. The results will be expressed as g•kg-1 on a dry weight basis.Hormone analysis. Xylem exudates will be extracted biweekly starting from fruit set until harvest, from two one-year-old branches on two trees per replicate using a pressure chamber (600 EXP Super Chamber, PMS Instrument Company, Albany, Oregon, USA). Samples from each replicate will be pooled to produce an experimental unit and will be stored at −80 °C until further use. The identification and quantification of the hormones will be measured by UPLC ESI-MS/MS at Cornell Biotechnology Institute.Based on our preliminary data and results of the first objective, we will build a preliminary model to predict bitter pit and soft scald during storage based on their interaction of rootstock genotype and abiotic factors.Data analysis. Field trials data will be analyzed by analysis of variance (ANOVA) followed by mean comparisons using Tukey's honest significant difference (HSD) and Student's t-test at the 5% confidence level in a randomized complete block design. The correlation between bitter pit, soft scald, mineral nutrient levels, hormone concentrations, and weather data will be assessed using neural network and partitioning prediction models. The Variable Importance in Projection (VIP) method will be used. A value of 0.8 is considered to be a small VIP. Nonlinear iterative partial least squares (NIPALS) models will be used based on the VIP. Partial least squares regression (PLS) will be used. All statistical analyses will be carried out using the JMP statistical program (JMP Pro 17.INK).