Mechanizing the harvest and grading of fresh market asparagus while maintaining quality presents a major challenge. Image processing algorithms were tested for detecting asparagus defects. Spreading tips were correctly identified with an 8% error rate, broken tips were detected with a 25% error rate, and scarred or cracked spears were detected with a 42% error rate using multivariate discriminant functions.
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Rigney et al. (1992) studied this question.