Skip to main content
ARS Home » Pacific West Area » Wenatchee, Washington » Physiology and Pathology of Tree Fruits Research » Research » Research Project #436626

Research Project: Non-Destructive Detection of Sun Stress Compromised Apples

Location: Physiology and Pathology of Tree Fruits Research

Project Number: 2094-43000-008-07-A
Project Type: Cooperative Agreement

Start Date: May 1, 2019
End Date: Jan 1, 2022

Objective:
Sun stress results in significant annual loss, not only due to injury in the orchard, but also those that appear during the cold chain including sunscald and lenticel blotch. Detection of these disorders before they enter the cold chain could afford producers the capacity to segregate fruit for removal, immediate marketing, or different storage strategy to eliminate injured fruit. Our earlier work has identified fruit compounds present prior to symptom development that may be detected non-destructively. Two non-destructive techniques, near infrared spectroscopy and near UV reflectance, have been tested and show promise, and at least one other technique may also have utility. We will use the same destructive chemical analysis techniques used to identify fruit compounds associated with peel disorder risk to validate the accuracy of the non-destructive techniques. Then, we will validate the use of the non-destructive technique(s) by identifying symptomless, yet sun stressed, apples prior to storage, and then wait for symptoms to develop during storage. The goal of this project will be development of a means for sorting symptomless sun stressed fruit from fruit that will not develop sun stress disorders therefore minimizing or eliminating sun-related postharvest disorders from the cold chain and retail. Objectives: 1. Determine best non-destructive methods to segregate sun stress compromised fruit. 2. Validate accuracy of non-destructive method for detecting chemistries associated with solar stress. 3. Test if non-destructive sorting improves storage outcome for different sun stress related disorders.

Approach:
We propose to find UV and vis-NIR reflectance regions that could be used to sort apples according to degree of solar stress. We will use a combination of UV-vis hyperspectral imaging and vis-NIR spectroscopy coupled with spectral processing and deconvolution to determine the best combination of spectral regions for discriminating solar stress. We will use our in-house metabolic profiling protocols to determine links between spectroscopy/imaging and target metabolites known to be associated with solar stress. Finally, we will use our non-destructive sorting analysis to sort apples from 2 cultivars to determine how effectively they assessed risk for postharvest peel disorders (sunscald and lenticel blotch) at harvest.