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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1998 Working Papers
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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1998 Working Papers
      • View Item
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      Predicting apple bruising relationships using machine learning

      Holmes, Geoffrey; Cunningham, Sally Jo; Dela Rue, B. T.; Bollen, A. F.
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      Holmes, G., Cunningham, S. J., Dela Rue, B. T. & Bollen, A. F. (1998). Predicting apple bruising relationships using machine learning. (Working paper 98/7). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/1052
      Abstract
      Many models have been used to describe the influence of internal or external factors on apple bruising. Few of these have addressed the application of derived relationships to the evaluation of commercial operations. From an industry perspective, a model must enable fruit to be rejected on the basis of a commercially significant bruise and must also accurately quantify the effects of various combinations of input features (such as cultivar, maturity, size, and so on) on bruise prediction. Input features must in turn have characteristics which are measurable commercially; for example, the measure of force should be impact energy rather than energy absorbed. Further, as the commercial criteria for acceptable damage levels change, the model should be versatile enough to regenerate new bruise thresholds from existing data.

      Machine learning is a burgeoning technology with a vast range of potential applications particularly in agriculture where large amounts of data can be readily collected [1]. The main advantage of using a machine learning method in an application is that the models built for prediction can be viewed and understood by the owner of the data who is in a position to determine the usefulness of the model, an essential component in a commercial environment.
      Date
      1998-04
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      98/7
      Publisher
      University of Waikato, Department of Computer Science
      Collections
      • 1998 Working Papers [18]
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