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ARS Home » Pacific West Area » Corvallis, Oregon » Horticultural Crops Production and Genetic Improvement Research Unit » Research » Research Project #449457

Research Project: Identifying Key Factors and Developing Screening Protocols for High-Quality Raspberry Fruits

Location: Horticultural Crops Production and Genetic Improvement Research Unit

Project Number: 2072-21000-060-025-A
Project Type: Cooperative Agreement

Start Date: Sep 1, 2026
End Date: Dec 31, 2029

Objective:
The Cooperator seeks to identify factors that contribute to premium raspberry fruit quality and develop an efficient method for breeders to assess this important trait. The Cooperator will evaluate factors contributing to both individually quick frozen (IQF) fruit qualty and fresh fruit quality. Specific objectives include: 1) Identify fruit characteristics that contribute to high quality IQF and fresh market raspberry. 2) Develop and validate an efficient, lab-scale phenotyping protocol for evaluating IQF and fresh market fruit quality. 3) Disseminate project information to the caneberry industry and breeding community. This project directly contributes to red raspberry industry priorities: Developing cultivars that are summer-bearing, high-yielding, winter hardy, machine harvestable, disease resistant, virus resistant, and have superior fresh and processed fruit quality.

Approach:
The Cooperator will evaluate fruit quality features in 15-20 raspberry cultivars representing a range of quality, including fruit surface features (e.g., style remnants or “hairs”), drupelet height, depth, number, and cohesion, receptacle cavity size, pit weight, and cell wall structure using light and electron microscopy. Fruit weight, firmness, volume, overall shape (conical or round), and tissue nutrient content with particular attention to calcium will also be recorded. Perform impact testing to measure effects of harvest forces on quality features. Resulting data will guide the development of a lab-scale tool that mimics commercial harvest and freezing conditions. Generalized linear regression modeling and standard model selection procedures will be used to determine what fruit variables most significantly contribute to IQF and fresh fruit quality.