JCU Connect Partner with us Our Technologies Rapid Assessment Technology for Fruits, Vegetables and Seafoods

Rapid Assessment Technology for Fruits, Vegetables and Seafoods

Background

Problem

Most producers struggle with delivering adequate and consistent quality because current post‑harvest technology cannot detect all internal defects reliably or effectively, and manual quality checks are costly, time‑consuming and destructive. More efficient and cost-efficient systems are needed to improve grading and automated assessment of quality to ensure consistency of supply, enable new marketing opportunities and ensure customer satisfaction.

Solution

We have developed a new method for non-invasive, non-destructive testing method on our automated grading/sorting machine with different produce, incl. but not limited to apples, tomatoes, kiwi fruits, mangoes, avocados, pineapples, chilies, and prawns.

Designed for processing and packaging facilities, our system can assist to determine damage, shelf-life, taste and other eating qualities of fruits, vegetables and seafood without having to cut them open. This enables sorting according to customer preferences and adjustable settings, for example into classes such as "Premium", "Firsts", "Seconds", "Thirds" and "Rejects". Since the quality can be guaranteed, the highest quality produce can be sold at a premium price, delivering higher profit margins to the business. At the same time the technology reduces time and wage costs due to the automated grading and sorting process.

Our proof-of-concept includes our in-house, custom-developed software, near-infrared cameras and suitable hardware to run trials which have proven the reliability and accuracy of our software models that can determine the "internal" qualities, which are generally not detectable from the outside.

We can, for example, detect bruises and rot susceptibility as an indication of shelf-life using non-destructive evaluation of impact damage and rot susceptibility of whole avocado fruit.

The technology uses our custom-built software to analyse the incoming data from near infrared spectroscopy (NIR) sensors which enables high-speed and non-invasive grading of produce. The NIR light is absorbed by by chemical bonds (e.g. O-H, N-H, C-H, ...) so the this technology can probe the chemical composition, and determine several key properties of the produce, incl. taste and bruises.

The operational unit is based on an optical platform using the following components:

  • Visible/NIR Camera(s), spectrometers;
  • Visible/NIR Lighting Platforms;
  • Image Capture/Processing/Item tracking software;
  • Statistical software for analysis and algorithmic computation;
  • PC for running software; and
  • System housing to control component temperature and contamination.

The optical platform is combined with a proprietary database and an interface system that provides parameters to the in-line conveyor system and associated drop points for product grading categories.

The technology is based on a secondary method of determination and is dependent on combining visual and physical wet chemistry analysis to develop and maintain the operating parameters (algorithms/calibration model). As the number of records in database increase and encompasses seasonal, product and producer variances over time, the overall accuracy and robustness improves.

Recent Publications

Wedding, B. B., Wright, C. , Grauf, S. , Gadek, P. and White, R. D. (2018), The application of FT‐NIRS for the detection of bruises and the prediction of rot susceptibility of ‘Hass’ avocado fruit. J. Sci. Food Agric.. doi:10.1002/jsfa.9383

Compared with wet chemistry, this technology has the advantage of no or minimal sample preparation, and the potential to test every single fruit, vegetable or seafood item in an inline setting using an accurate multi‑analytic method.

Advantages include:

  • detect internal and eating qualities (dry matter content, susceptibility to rot, etc.)
  • non-invasive/non-destructive method
  • predict shelf-life (which produce will rot or deteriorate before a certain date)
  • fully automated grading/sorting based on adjustable parameters
  • high assessment speed of 20 pieces (e.g. of fruit) per second
  • flexible software model - independent from a particular product, produce or variety
  • calibration enables the underlying model to embrace seasonal and regional variations
  • proven reliability and accuracy for certain produce (contact us for more information)
  • automated quality control and grading of produce
  • value-adding through guarantee of quality
  • suitable for fruits, vegetables, and certain sea foods, such as prawns
  • suitable for on-farm, export and packaging facilities
  • determine suitability for shipping method/logistics

After 10 years o R&D, the university are now seeking partners to finalise the development and roll-out the technology. They are looking for suitable key partners who are interested in one or more of the following activities:

  • Ultimately: commercialisation of the technology
  • facilitation of additional trials, either in our lab or on-site
  • further R&D to adopt the technology to other produce and varieties
  • miniaturisation of the existing footprint
  • lowering costs to increase adoption
  • increase the processing speed to enable higher throughput for commercial applications

Seeking:

  • Development partner
  • Commercial partner
  • Licensing
  • Know-how based
  • Copyright

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