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Modeling multispectral scattering profiles for prediction of apple fruit firmness
- Peng, Y., Lu, R.
- Transactions of the ASAE 2005 v.48 no.1 pp. 235
- apples, raw fruit, fruit quality, firmness, multispectral imagery, nondestructive methods, near-infrared reflectance spectroscopy, light scattering, mathematical models, equations, product grading, prediction
- Nondestructive measurement of fruit firmness would allow the fruit industry to deliver superior, consistent fruit to the marketplace and ensure consumer acceptance and satisfaction. The objective of this research was to develop mathematical models to describe the relationship between fruit firmness and multispectral scattering profiles from apples. Scattering images were acquired from Red Delicious apples using two different multispectral imaging systems at wavelengths 680 nm, 880 nm, 905 nm, and 940 nm with a bandpass of 10 nm. Radial scattering profiles were described accurately by a Lorentzian distribution function with three independent profile parameters. Firmness prediction models were constructed using multilinear regression against twelve Lorentzian parameters for four wavelengths, and they were verified with separate sets of apple fruit. The prediction models gave firmness predictions with the correlation coefficient (r) of 0.82 and the standard error for validation (SEV) of 6.39 N for one set of apple samples, and r = 0.76 and SEV = 6.01 N for another set.