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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Leaf epidermis images for robust identification of plants

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da Silva, Nubia Rosa [1, 2] ; da Silva Oliveira, Marcos William [1, 2] ; de Almeida Filho, Humberto Antunes [2] ; Souza Pinheiro, Luiz Felipe [3] ; Rossatto, Davi Rodrigo [4] ; Kolb, Rosana Marta [3] ; Bruno, Odemir Martinez [1, 2]
Total Authors: 7
[1] Univ Sao Paulo, Inst Math & Comp Sci, Ave Trabalhador Sao Carlense 400, BR-13566590 Sao Paulo - Brazil
[2] Univ Sao Paulo, Sao Carlos Inst Phys, Sci Comp Grp, POB 369, BR-13560970 Sao Carlos, SP - Brazil
[3] Univ Estadual Paulista, Fac Sci & Languages, UNESP, Dept Biol Sci, Ave Dom Antonio 2100, BR-19806900 Sao Paulo - Brazil
[4] Univ Estadual Paulista, Fac Agr & Vet Sci, Dept Appl Biol, UNESP, Via Acesso Prof Paulo Donatto Castellane S-N, BR-14884900 Sao Paulo - Brazil
Total Affiliations: 4
Document type: Journal article
Source: SCIENTIFIC REPORTS; v. 6, MAY 24 2016.
Web of Science Citations: 3

This paper proposes a methodology for plant analysis and identification based on extracting texture features from microscopic images of leaf epidermis. All the experiments were carried out using 32 plant species with 309 epidermal samples captured by an optical microscope coupled to a digital camera. The results of the computational methods using texture features were compared to the conventional approach, where quantitative measurements of stomatal traits (density, length and width) were manually obtained. Epidermis image classification using texture has achieved a success rate of over 96%, while success rate was around 60% for quantitative measurements taken manually. Furthermore, we verified the robustness of our method accounting for natural phenotypic plasticity of stomata, analysing samples from the same species grown in different environments. Texture methods were robust even when considering phenotypic plasticity of stomatal traits with a decrease of 20% in the success rate, as quantitative measurements proved to be fully sensitive with a decrease of 77%. Results from the comparison between the computational approach and the conventional quantitative measurements lead us to discover how computational systems are advantageous and promising in terms of solving problems related to Botany, such as species identification. (AU)

FAPESP's process: 11/01523-1 - Computer vision methods applied to the identification and analysis of plants
Grantee:Odemir Martinez Bruno
Support type: Regular Research Grants
FAPESP's process: 11/21467-9 - Heterogeneous Pattern Recognition and its Applications in Biology and Nanotechnology.
Grantee:Núbia Rosa da Silva
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 11/23112-3 - Leaf anatomy of plants from different vegetation formations
Grantee:Rosana Marta Kolb
Support type: Regular Research Grants