Accurate Non-Destructive Prediction of Peach Fruit Quality


Available for Licensing
TRL: 6

IP Status

PCT Patent Pending: WO 2022/060983


Ioannis S. Minas

At A Glance

Researchers at Colorado State University have developed an accurate non-destructive prediction tool to assess peach fruit internal quality and physiological maturity with a single scan using near infrared spectroscopy (NIRS).

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Licensing Director

Jillian Lang

Reference No.:  2021-005


Peach consumption per capita has been in constant decline in the United States and Europe in recent decades and has continued to drop even with the availability of numerous new cultivars and improved quality traits.  Surveys indicate that this trend is due to immature, overripe and/or tasteless fruit as well as a variety of textural problems associated with interrupted ripening, due to postharvest physiological disorders at the time of consumption.  For increased rates of fresh peach consumption, optimization of fruit quality is a necessity.

Internal quality of peach fruit cannot be improved during postharvest handling, only maintained. Thus, for significant improvement of peach consumer quality, non-destructive, reliable, and accurate models that evaluate the effect of preharvest factors are needed.  These models can help commercial growers and large-scale farmers determine proper harvest time for optimized internal quality, inherently increasing consumer demand for peaches.

  • Hand-held portable device (can be used in the field)
  • Accurate non-destructive prediction
  • Assessment of true orchard impact on peach quality (e.g., crop loads, canopy position, etc.)
  • Assessment of internal quality and maturity simultaneously
  • Method uses precise and reliable single scan (NIRS)
  • Commercial scalability
  • Commercial assessment of peach quality
  • Assessment of fruit and vegetable crops for maturity and quality

Minas, Ioannis S., et al. “Accurate Non-Destructive Prediction of Peach Fruit Internal Quality and Physiological Maturity with a Single Scan Using near Infrared Spectroscopy.” Food Chemistry, Elsevier, 25 July 2020,

Last updated: April 2022

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