| Grant number: | 18/03802-4 |
| Support Opportunities: | Multi-user Equipment Program |
| Start date: | April 01, 2018 |
| End date: | 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 |
| As informações de acesso ao Equipamento Multiusuário são de responsabilidade do Pesquisador responsável | |
| 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)
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