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Proceedings Paper

Neural network classification of sweet potato embryos
Author(s): Enrique Molto; Roy C. Harrell
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Paper Abstract

Somatic embryogenesis is a process that allows for the in vitro propagation of thousands of plants in sub-liter size vessels and has been successfully applied to many significant species. The heterogeneity of maturity and quality of embryos produced with this technique requires sorting to obtain a uniform product. An automated harvester is being developed at the University of Florida to sort embryos in vitro at different stages of maturation in a suspension culture. The system utilizes machine vision to characterize embryo morphology and a fluidic based separation device to isolate embryos associated with a pre-defined, targeted morphology. Two different backpropagation neural networks (BNN) were used to classify embryos based on information extracted from the vision system. One network utilized geometric features such as embryo area, length, and symmetry as inputs. The alternative network utilized polar coordinates of an embryo's perimeter with respect to its centroid as inputs. The performances of both techniques were compared with each other and with an embryo classification method based on linear discriminant analysis (LDA). Similar results were obtained with all three techniques. Classification efficiency was improved by reducing the dimension of the feature vector trough a forward stepwise analysis by LDA. In order to enhance the purity of the sample selected as harvestable, a reject to classify option was introduced in the model and analyzed. The best classifier performances (76% overall correct classifications, 75% harvestable objects properly classified, homogeneity improvement ratio 1.5) were obtained using 8 features in a BNN.

Paper Details

Date Published: 12 May 1993
PDF: 11 pages
Proc. SPIE 1836, Optics in Agriculture and Forestry, (12 May 1993); doi: 10.1117/12.144033
Show Author Affiliations
Enrique Molto, Univ. Politecnica de Valencia (Spain)
Roy C. Harrell, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 1836:
Optics in Agriculture and Forestry
James A. DeShazer; George E. Meyer, Editor(s)

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