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QUANTIFICATION OF FLOWERING AND FRUIT MATURATION BY DIGITAL IMAGE TO ANALYZE AND PREDICT COFFEE HARVEST

Grant number: 22/11209-7
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): September 01, 2022
Effective date (End): August 31, 2023
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Cooperation agreement: MCTI/MC
Principal researcher:Antonio Chalfun Junior
Grantee:Francisco Eron Cordeiro Carvalho
Home Institution: Pró-Reitoria de Pós-Graduação. Universidade Federal de Lavras (UFLA). Ministério da Educação (Brasil). Lavras , SP, Brazil
Associated research grant:21/06968-3 - From seed to cup: internet of things technology in the quality coffee production chain, AP.TEM

Abstract

The project aims to elaborate an automated methodology for flowering and fruit ripening analyses in coffee by massive image capture, light manipulation and development of a program (algorithm/software) for digitization and data analysis. The desired results are quantitative, seeking to establish numerical patterns of floral proportion and ripening distribution in plants from the output data of an algorithm developed for this goal. Applications of the project extend to data capture and support field corrective practices, in other words, focused on precision agriculture. At the end of the project we hope to offer a tool capable of quantifying the number of annual flowers, determining the homogeneity of flowering and estimating the production of fruits and its maturation. These data will compose a database that will be updated annually and with prospect of use, along with artificial intelligence and machine learning algorithms, to create an inde that anticipates and improve productivity forecasting. Thus, we hope that the new tool will be of great interest in the field of biotechnology and agroeconomics. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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