Monitoring the color of coffee leaves using a portable sensor and relationship with the elemental composition obtained using X-ray fluorescence

• Grant number: 23/14932-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): November 01, 2023
• Effective date (End): October 31, 2025
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Acordo de Cooperação: MCTI/MC
• Principal Investigator: Luiz Roberto Guimarães Guilherme
• Grantee: Pedro Lucas Decarlos Gonçalves
• Host Institution: Escola de Ciências Agrárias. 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

Nutritional and physiological state of plants is closely related to the color of the leaves. As an example, adequate levels of N, Mg and chlorophyll correlate with the intensity of the green color in plants. Symptoms of nutritional deficiency in plants are visually diagnosed in the field. Leaf color can be assessed qualitatively using a color chart (e.g., Munsell Color Chart) or more quantitatively through the processing of images obtained with smartphones, drones and satellites. Recently, a small color sensor was launched on the market that connects to smartphones via Bluetooth called Nix" Color Sensor. The sensor allows you to instantly obtain various quantitative color parameters in different systems (e.g., CMYK, CIELab, RGB). Therefore, the aim of this project is to monitor coffee crops using two sensors: Nix" QC Color Sensor and portable X-ray fluorescence equipment (pXRF). In the selected crops and plots, in a random manner, diagnostic coffee leaves representing different ages, cultivars, management, etc., will be analyzed using the Nix and pXRF sensor. After data processing, quantitative color parameters will be used to establish correlations with the elemental composition obtained with pXRF. The hope of this work is to obtain a quick, non-destructive and low-cost protocol, based merely on the color of coffee leaves, for predicting the nutritional status of plants. This may assist soil fertility management practices and foliar fertilization. (AU)