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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.)

A novel approach for Jatropha curcas seed health analysis based on multispectral and resonance imaging techniques

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Author(s):
da Silva, Clissia Barboza [1] ; Martins Bianchini, Vitor de Jesus [2] ; de Medeiros, Andre Dantas [3] ; Duarte de Moraes, Maria Heloisa [4] ; Marassi, Agide Gimenez [5] ; Tannus, Alberto [5]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Ctr Nucl Energy Agr, Lab Radiobiol & Environm, Av Centenario 303, BR-13416000 Piracicaba, SP - Brazil
[2] Univ Sao Paulo, Coll Agr Luiz de Queiroz, Dept Crop Sci, Piracicaba, SP - Brazil
[3] Univ Fed Vicosa, Dept Agron, Vicosa, MG - Brazil
[4] Univ Sao Paulo, Coll Agr Luiz de Queiroz, Dept Plant Pathol & Nematol, Piracicaba, SP - Brazil
[5] Univ Sao Paulo, Ctr Magnet Resonance Imaging & Vivo Spect, Phys Inst Sao Carlos, Sao Carlos, SP - Brazil
Total Affiliations: 5
Document type: Journal article
Source: INDUSTRIAL CROPS AND PRODUCTS; v. 161, MAR 2021.
Web of Science Citations: 2
Abstract

Innovative methods have been developed in the state-of-the-art technologies based on robust spectral-spatial sensors for modern seed industry. In this study we proposed a novel approach based on multispectral imaging combined with machine learning algorithm to classify Jatropha curcas seed health. Furthermore, we present for the first time a methodology based on magnetic resonance imaging (MRI) to identify anatomical changes in J. curcas seeds infected with different pathogenic fungi. First, seeds were artificially inoculated with Lasiodiplodia theobromae, Colletotrichum siamense and Colletotrichum truncatum, and multispectral images were acquired after 24, 48, 72, 96, 120, 144 and 168 h of incubation. The MRI method was applied using incubated seeds for 168 h. Our results showed that the multispectral imaging technique combined with statistical models has the potential to distinguish different fungal species in J. curcas seeds after 48 h of incubation, with high accuracy (>80 %). The proposed MRI methodology allowed the identification of different damage patterns in the endosperm tissues infected with L. theobromae, C. siamense and C. truncatum. Therefore, multispectral imaging and MRI can be useful tools for rapid and accurate detection of different fungal species in J. curcas seeds. (AU)

FAPESP's process: 17/15220-7 - Non-destructive image analysis methods for seed quality evaluation
Grantee:Clíssia Barboza da Silva
Support type: Research Grants - Young Investigators Grants
FAPESP's process: 19/04127-1 - Application of analytical techniques of magnetic resonance imaging and multispectral image to evaluate Jatropha curcas L. seeds
Grantee:Vitor de Jesus Martins Bianchini
Support type: Scholarships in Brazil - Scientific Initiation
FAPESP's process: 18/01774-3 - Non-destructive image analysis methods for seed quality evaluation
Grantee:Clíssia Barboza da Silva
Support type: Scholarships in Brazil - Young Researchers
FAPESP's process: 18/03802-4 - Multi-user equipment approved in grant 2017/15220-7: imaging system VideoMeterLab
Grantee:Clíssia Barboza da Silva
Support type: Multi-user Equipment Program