Multi-user equipment approved in grant 2017/15220-7: imaging system VideoMeterLab

• Grant number: 18/03802-4
• Support Opportunities: Multi-user Equipment Program
• Duration: April 01, 2018 - March 31, 2025
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Clíssia Barboza Mastrangelo
• Grantee: Clíssia Barboza Mastrangelo
• 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
• EMU web page: http://www.esalq.usp.br/departamentos/lpv/labimagem/Plano%20de%20Gestão_Videometer.pdf
• Type of equipment: Processos Biológicos - Caracterização - Leitores de fluorescência (imageamento, placas); Caracterização de Materiais - Imageamento - Fluorescência (in vivo)
• Manufacturer: Videometer
• Model: VideometerLab VML

Abstract

The growing demand for seeds in Brazil, especially regarding to crops of economic importance, requires the constant improvement of the parameters for quality evaluation, aiming maximizing production and the performance of the agricultural sector in the economy, both national and international. Therefore, the evaluation of seed quality using nondestructive image analysis techniques is of great interest, since objective information can be achieved, in a relatively short period of time, with less human interference and with great portability potential. Following through with the "Thematic Project" - Seed Imaging Analysis in Seed Technology Research - financed by FAPESP (Grant number: 06/57900-0), the objective of this research project is to continue studies on non-destructive methods for seed quality evaluation with the use and improvement of recent techniques of X-rays and Magnetic Resonance, as well as the introduction and the establishment in Brazil of imaging techniques based on multispectral analysis and chlorophyll fluorescence. The expected results of this project are to find patterns optical images by using advanced techniques which can characterize the quality patterns of carrot, tomato, physic nut (Jatropha curcas L.) and peanut seeds in continuation of previous studies on "Seed Imaging Analysis" that our team has been working in recent years, and with that, to strengthen and expand innovative approaches that include new lines of research with inter-institutional and international collaborations. (AU)

Scientific publications

(12)

(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)

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, JAN 26 2021. (18/03807-6, 19/04127-1, 17/15220-7, 18/03802-4, 18/01774-3)

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, MAR 2021. (18/01774-3, 17/15220-7, 19/04127-1, 18/03802-4)

FRANCA-SILVA, FABIANO; QUEIROZ REGO, CARLOS HENRIQUE; GUILHIEN GOMES-JUNIOR, FRANCISCO; DUARTE DE MORAES, MARIA HELOISA; DE MEDEIROS, ANDRE DANTAS; DA SILVA, CLISSIA BARBOZA. Detection ofDrechslera avenae(Eidam) Sharif [Helminthosporium avenae(Eidam)] in Black Oat Seeds (Avena strigosaSchreb) Using Multispectral Imaging. SENSORS, v. 20, n. 12, JUN 2020. (17/15220-7, 18/03802-4)

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, AUG 2021. (18/03802-4, 18/01774-3, 18/03793-5, 17/15220-7)

MASTRANGELO, THIAGO; DA SILVA, FABIANO FRANCA; MASCARIN, GABRIEL MOURA; DA SILVA, CLISSIA BARBOZA. Multispectral imaging for quality control of laboratory-reared Anastrepha fraterculus (Diptera: Tephritidae) pupae. Journal of Applied Entomology, v. 143, n. 10, p. 8-pg., 2019-11-27. (18/03802-4, 17/15220-7)

MASTRANGELO, THIAGO; DA SILVA, FABIANO FRANCA; MASCARIN, GABRIEL MOURA; DA SILVA, CLISSIA BARBOZA. Multispectral imaging for quality control of laboratory-reared Anastrepha fraterculus (Diptera: Tephritidae) pupae. Journal of Applied Entomology, NOV 2019. (18/03802-4, 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, DEC 21 2020. (18/24777-8, 18/03807-6, 18/03802-4, 18/03793-5, 18/01774-3, 17/15220-7)

FABIANO FRANÇA-SILVA; SILVIO MOURE CICERO; FRANCISCO GUILHIEN GOMES-JUNIOR; ANDRÉ DANTAS MEDEIROS; JOSÉ DE BARROS FRANÇA-NETO; DENISE CUNHA FERNANDES SANTOS DIAS. Quantification of chlorophyll fluorescence in soybean seeds by multispectral images and their relationship with physiological potential. JOURNAL OF SEED SCIENCE, v. 44, 2022-07-08. (18/03793-5, 18/03802-4)

GOMES, WINSTON PINHEIRO CLARO; GONCALVES, LUIS; SILVA, CLISSIA BARBOZA DA; MELCHERT, WANESSA R.. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 198, p. 9-pg., 2022-07-01. (17/15220-7, 18/24029-1, 18/03802-4)

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, SEP 8 2021. (18/03793-5, 18/03802-4, 17/15220-7, 18/01774-3)

REGO, CARLOS HENRIQUE QUEIROZ; FRANCA-SILVA, FABIANO; GOMES-JUNIOR, FRANCISCO GUILHIEN; DE MORAES, MARIA HELOISA DUARTE; DE MEDEIROS, ANDRE DANTAS; DA SILVA, CLISSIA BARBOZA. Using Multispectral Imaging for Detecting Seed-Borne Fungi in Cowpea. AGRICULTURE-BASEL, v. 10, n. 8, p. 12-pg., 2020-08-01. (18/03802-4, 17/15220-7)

FRANCA-SILVA, FABIANO; GOMES-JUNIOR, FRANCISCO GUILHIEN; REGO, CARLOS HENRIQUE QUEIROZ; MARASSI, AGIDE GIMENEZ; TANNUS, ALBERTO. Advances in imaging technologies for soybean seed analysis. JOURNAL OF SEED SCIENCE, v. 45, p. 16-pg., 2023-01-01. (18/03802-4, 15/24008-6, 18/13139-0)