Skip to main content

Discrimination and identification of morphotypes of Banksia integrifolia (Proteaceae) by an Artificial Neural Network (ANN), based on morphological and fractal parameters of leaves and flowers

Buy Article:

$16.27 plus tax (Refund Policy)

Abstract:

An artificial neural network (back propagation neural network) based on morphological and fractal leaf and flower parameters was developed for the characterization of three Banksia integrifolia subspecies and the identification of nine unnamed morphotypes. Results indicated that the network can be effectively and successfully used to discriminate among morphotypes using simple dedicated instruments, such as a PC and an optical scanner. The new method also as a complementary approach to botanical identification, being capable of separating all the tested Banksia integrifolia accessions and of creating associations between the known subspecies and the unnamed accessions.

Keywords: BPNN; IMAGE ANALYSIS; PLANT IDENTIFICATION; TAXONOMY

Document Type: Research Article

Affiliations: 1: Department of Horticulture, University of Florence, viale delle Idee 30, 50019 Sesto Fiorentino (FI), Italy 2: Department of Horticulture, University of Florence, viale delle Idee 30, 50019 Sesto Fiorentino (FI), Italy, School of Plant Biology, University of Western Australia, 35 Stirling Highway, Crawley, WA 6907, Australia 3: Department of Horticulture, University of Florence, viale delle Idee 30, 50019 Sesto Fiorentino (FI), Italy;, Email: sergio.mugnai@unifi.it 4: School of Plant Biology, University of Western Australia, 35 Stirling Highway, Crawley, WA 6907, Australia

Publication date: August 1, 2009

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Partial Open Access Content
Partial Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more