Sugarcane qualitative attributes determination and mapping by spectral sensors

• Grant number: 18/25008-8
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: March 01, 2019
• End date: July 31, 2021
• Field of knowledge: Agronomical Sciences - Agricultural Engineering - Agricultural Machinery and Implements
• Principal Investigator: José Paulo Molin
• Grantee: Lucas de Paula Corrêdo
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil

Abstract

For some agricultural crops the characterization of product quality becomes as important as the measurement of productivity. Sugarcane is an example. The crop profitability is a result association of productivity and quality. Despite the advances in productivity measurement, including the new sensors development in harvesters, quality measurement in real time is still a distant reality. Thus, aim is to evaluate the predicting potential of sugarcane qualitative attributes by different spectroscopy techniques and to analyze this techniques potential for mapping the spatial variability of these attributes in the field. Visible and Near Infrared (visNIR) and X-Ray Fluorescence (XRF) spectroscopy techniques will be used in this work. The sensors readings based on these techniques will be carried out in an industrial quality laboratory parallel to the traditional analyzes for the same samples. In addition, readings will be made for different forms of same sample (stem, fiber and juice). The most suitable sensing techniques (or the combination of these) and sample form for qualitative attributes quantification (Brix, Pol, fibers, purity, sugar reducers and ATR) of sugarcane will be evaluated. Finally, the most appropriate technique will be used to read geo-referenced samples from a commercial field in order to analyze the potential for field application and identification of existing spatial variability for each attribute. (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)

MALDANER, LEONARDO FELIPE; CORREDO, LUCAS DE PAULA; CANATA, TATIANA FERNANDA; MOLIN, JOSE PAULO. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 181, FEB 2021. (18/25008-8)

CORREDO, LUCAS P.; WEI, MARCELO C. F.; FERRAZ, MARCOS N.; MOLIN, JOSE P.. Near-infrared spectroscopy as a tool for monitoring the spatial variability of sugarcane quality in the fields. BIOSYSTEMS ENGINEERING, v. 206, p. 150-161, JUN 2021. (18/25008-8)

CORREDO, LUCAS DE PAULA; CANATA, TATIANA FERNANDA; MALDANER, LEONARDO FELIPE; DE LIMA, JEOVANO DE JESUS ALVES; MOLIN, JOSE PAULO. Sugarcane Harvester for In-field Data Collection: State of the Art, Its Applicability and Future Perspectives. SUGAR TECH, v. 23, n. 1, p. 1-14, FEB 2021. (18/25008-8)

MOLIN, JOSE PAULO; BAZAME, HELIZANI COUTO; MALDANER, LEONARDO; CORREDO, LUCAS DE PAULA; MARTELLO, MAURICIO; CANATA, TATIANA FERNANDA. Precision agriculture and the digital contributions for site-specific management of the fields. REVISTA CIENCIA AGRONOMICA, v. 51, n. SI, 2020. (18/25008-8)

CORREDO, LUCAS DE PAULA; MALDANER, LEONARDO FELIPE; BAZAME, HELIZANI COUTO; MOLIN, JOSE PAULO. Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy. SENSORS, v. 21, n. 6, p. 23-pg., 2021-03-01. (18/25008-8)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

CORRÊDO, Lucas de Paula. Proximal spectroscopy sensing for sugarcane quality prediction and spatial variability mapping. 2021. Doctoral Thesis - Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC) Piracicaba.