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Non-destructive image analysis methods for seed quality evaluation

Grant number: 18/01774-3
Support Opportunities:Scholarships in Brazil - Young Researchers
Effective date (Start): February 01, 2018
Effective date (End): July 31, 2023
Field of knowledge:Agronomical Sciences - Agronomy - Crop Science
Principal Investigator:Clíssia Barboza da Silva
Grantee:Clíssia Barboza da Silva
Host Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:17/15220-7 - Non-destructive image analysis methods for seed quality evaluation, AP.JP
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Scientific publications (7)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
OLIVEIRA, NIELSEN MOREIRA; DE MEDEIROS, ANDRE DANTAS; NOGUEIRA, MARINA DE LIMA; ARTHUR, VALTER; MASTRANGELO, THIAGO DE ARAUJO; DA SILVA, CLISSIA BARBOZA. Hormetic effects of low-dose gamma rays in soybean seeds and seedlings: A detection technique using optical sensors. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 187, . (18/03802-4, 18/01774-3, 18/03793-5, 17/15220-7)
DA SILVA, CLISSIA BARBOZA; MARTINS BIANCHINI, VITOR DE JESUS; DE MEDEIROS, ANDRE DANTAS; DUARTE DE MORAES, MARIA HELOISA; MARASSI, AGIDE GIMENEZ; TANNUS, ALBERTO. A novel approach for Jatropha curcas seed health analysis based on multispectral and resonance imaging techniques. INDUSTRIAL CROPS AND PRODUCTS, v. 161, . (18/01774-3, 17/15220-7, 19/04127-1, 18/03802-4)
MARTINS BIANCHINI, VITOR DE JESUS; MASCARIN, GABRIEL MOURA; APARECIDA SANTOS SILVA, LUCIA CRISTINA; ARTHUR, VALTER; CARSTENSEN, JENS MICHAEL; BOELT, BIRTE; DA SILVA, CLISSIA BARBOZA. Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality. PLANT METHODS, v. 17, n. 1, . (18/03807-6, 19/04127-1, 17/15220-7, 18/03802-4, 18/01774-3)
NOVIKOVA, TATYANA P. P.; MASTRANGELO, CLISSIA BARBOZA; TYLEK, PAWEL; EVDOKIMOVA, SVETLANA A. A.; NOVIKOV, ARTHUR I. I.. How Can the Engineering Parameters of the NIR Grader Affect the Efficiency of Seed Grading?. AGRICULTURE-BASEL, v. 12, n. 12, p. 17-pg., . (18/01774-3, 17/15220-7)
GALLETTI, PATRICIA A.; CARVALHO, MARCIA E. A.; HIRAI, WELINTON Y.; BRANCAGLIONI, VIVIAN A.; ARTHUR, VALTER; BARBOZA DA SILVA, CLISSIA. Integrating Optical Imaging Tools for Rapid and Non-invasive Characterization of Seed Quality: Tomato (Solanum lycopersicum L.) and Carrot (Daucus carota L.) as Study Cases. FRONTIERS IN PLANT SCIENCE, v. 11, . (18/24777-8, 18/03807-6, 18/03802-4, 18/03793-5, 18/01774-3, 17/15220-7)
DA SILVA, CLISSIA BARBOZA; OLIVEIRA, NIELSEN MOREIRA; AMARAL DE CARVALHO, MARCIA EUGENIA; DE MEDEIROS, ANDRE DANTAS; NOGUEIRA, MARINA DE LIMA; DOS REIS, ANDRE RODRIGUES. Autofluorescence-spectral imaging as an innovative method for rapid, non-destructive and reliable assessing of soybean seed quality. SCIENTIFIC REPORTS, v. 11, n. 1, . (18/03793-5, 18/03802-4, 17/15220-7, 18/01774-3)
DA SILVA, CLISSIA BARBOZA; NAVES SILVA, ALYSSON ALEXANDER; BARROSO, GEOVANNY; YAMAMOTO, PEDRO TAKAO; ARTHUR, VALTER; MOTTA TOLEDO, CLAUDIO FABIANO; MASTRANGELO, THIAGO DE ARAUJO. Convolutional Neural Networks Using Enhanced Radiographs for Real-Time Detection of Sitophilus zeamais in Maize Grain. FOODS, v. 10, n. 4, . (18/01774-3, 18/03793-5, 18/03807-6, 17/15220-7)

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