Sensors associated with the internet of things to connect the environment, genetics and processing to the chemical and sensory profile of specialty coffees

• Grant number: 23/00474-4
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: February 01, 2023
• Status: Discontinued
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Analytical Chemistry
• Agreement: MCTI/MC
• Principal Investigator: Cleiton Antônio Nunes
• Grantee: Yhan da Silva Mutz
• 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
• Associated scholarship(s): 24/13645-4 - Solutions based on near-infrared (NIR) spectroscopy, computer vision, and NIR hyperspectral imaging (NIR-HSI) for the understanding of specialty coffee quality, BE.EP.PD

Abstract

Coffee productivity and quality depend on the interaction among several factors, such as genetic characteristics of the plant cultivars, environmental conditions, management techniques and technologies from the beginning of development to the beverage production. We intend to understand such relationships using the "Internet of Things" to process data and find patterns related to the highest quality of the drink "in the cup". The candidate is expected to: evaluate, by digital image processing, the quality of the coffee harvest, determining the proportion of ripe x green beans; evaluate, through sensors and digital images, the drying conditions of the grains with humidity, temperature and intensity of sunlight; evaluate controlled fermentation conditions using sensors during the development of metabolites in specialty coffees; measure roasted and ground grain quality parameters, such as organic acid, volatile compounds, through sensors, chromatography, electronic nose and other techniques; understand how parameters related to agricultural inputs, soil, harvested and processed beans impact the sensory quality of the coffee beverage and consumer perception; collaborate with graduate students; discussion of data and writing of reports, patents and scientific articles. (AU)

Scientific publications

(5)

(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)

DE CARVALHO, ISABELLA MARQUES; DA SILVA MUTZ, YHAN; MACHADO, AMANDA CRISTINA GOMES; DE LIMA SANTOS, AMANDA APARECIDA; MAGALHAES, ELISANGELA JAQUELINE; NUNES, CLEITON ANTONIO. Exploring Strategies to Mitigate the Lightness Effect on the Prediction of Soybean Oil Content in Blends of Olive and Avocado Oil Using Smartphone Digital Image Colorimetry. FOODS, v. 12, n. 18, p. 13-pg., 2023-09-01. (23/00474-4)

DE OLIVEIRA, MAISA AZARIAS; RIBEIRO, MICHELE NAYARA; VALENTE, HENRIQUE MURTA; MUTZ, YHAN DA SILVA; PINHEIRO, ANA CARLA MARQUES; NUNES, CLEITON ANTONIO. Feasibility of Using Reflectance Spectra from Smartphone Digital Images to Predict Quality Parameters of Bananas and Papayas. FOOD ANALYTICAL METHODS, v. 17, n. 1, p. 9-pg., 2023-11-28. (23/00474-4)

LIMA, JUCELINO DE SOUSA; ANDRADE, OTAVIO VITOR SOUZA; DOS SANTOS, LEONIDAS CANUTO; DE MORAIS, EVERTON GERALDO; MARTINS, GABRYEL SILVA; MUTZ, YHAN S.; NASCIMENTO, VITOR L.; MARCHIORI, PAULO EDUARDO RIBEIRO; LOPES, GUILHERME; GUILHERME, LUIZ ROBERTO GUIMARAES. Soybean Plants Exposed to Low Concentrations of Potassium Iodide Have Better Tolerance to Water Deficit through the Antioxidant Enzymatic System and Photosynthesis Modulation. PLANTS-BASEL, v. 12, n. 13, p. 19-pg., 2023-07-01. (23/00474-4)

PIRES, FABIANA DE CARVALHO; MUTZ, YHAN DA SILVA; DE CARVALHO, THAIS CRISTINA LIMA; LORENZO, NATASHA DANTAS; PEREIRA, ROSEMARY GUALBERTO FONSECA ALVARENGA; DA ROCHA, RONEY ALVES; NUNES, CLEITON ANTONIO. Feasibility of using colorimetric devices for whole and ground coffee roasting degrees prediction. Journal of the Science of Food and Agriculture, v. 104, n. 9, p. 7-pg., 2024-02-21. (23/00474-4, 21/06968-3)

MUTZ, YHAN S.; MAROUM, SAMARA MAFRA; TESSARO, LETICIA L. G.; SOUZA, NATALIA DE OLIVEIRA; DE BEM, MIKAELA MARTINS; ALVES, LOYANE SILVESTRE; FIGUEIREDO, LUISA PEREIRA; DO ROSARIO, DENES K. A.; BERNARDES, PATRICIA C.; NUNES, CLEITON ANTONIO. Effectiveness of an E-Nose Based on Metal Oxide Semiconductor Sensors for Coffee Quality Assessment. CHEMOSENSORS, v. 13, n. 1, p. 16-pg., 2025-01-01. (23/00474-4, 21/06968-3)