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Proceedings Paper

Broccoli/weed/soil discrimination by optical reflectance using neural networks
Author(s): Federico Hahn
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Paper Abstract

Broccoli is grown extensively in Scotland, and has become one of the main vegetables cropped, due to its high yields and profits. Broccoli, weed and soil samples from 6 different farms were collected and their spectra obtained and analyzed using discriminant analysis. High crop/weed/soil discrimination success rates were encountered in each farm, but the selected wavelengths varied in each farm due to differences in broccoli variety, weed species incidence and soil type. In order to use only three wavelengths, neural networks were introduced and high crop/weed/soil discrimination accuracies for each farm were achieved.

Paper Details

Date Published: 6 April 1995
PDF: 10 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205126
Show Author Affiliations
Federico Hahn, Instituto Tecnologico de la Laguna (Mexico)

Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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