| Full text | |
| Author(s): |
Pereira, Danillo Roberto
[1]
;
Papa, Joao Paulo
[2]
;
Rosalin Saraiva, Gustavo Francisco
[1]
;
Souza, Gustavo Maia
[3]
Total Authors: 4
|
| Affiliation: | [1] Univ Oeste Paulista, Sao Paulo - Brazil
[2] Univ Estadual Paulista, Sao Paulo - Brazil
[3] Univ Fed Pelotas, Pelotas, RS - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 145, p. 35-42, FEB 2018. |
| Web of Science Citations: | 6 |
| Abstract | |
In plants, there are different types of electrical signals involving changes in membrane potentials that could encode electrical information related to physiological states when plants are stimulated by different environmental conditions. A previous study analyzing traits of the dynamics of whole plant low-voltage electrical showed, for instance, that some specific frequencies that can be observed on plants growing under undisturbed conditions disappear after stress-like environments, such as cold, low light and osmotic stimuli. In this paper, we propose to test different methods of automatic classification in order to identify when different environmental cues cause specific changes in the electrical signals of plants. In order to verify such hypothesis, we used machine learning algorithms (Artificial Neural Networks, Convolutional Neural Network, Optimum-Path Forest, k-Nearest Neighbors and Support Vector Machine) together Interval Arithmetic. The results indicated that Interval Arithmetic and supervised classifiers are more suitable than deep learning techniques, showing promising results towards such research area. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/19403-6 - Energy-based learning models and their applications |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 14/16250-9 - On the parameter optimization in machine learning techniques: advances and paradigms |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |