Handheld near infrared spectrometer and machine learning methods applied to the monitoring of multiple process stages in industrial sugar production
- 1 February 2022
- journal article
- research article
- Published by Elsevier in Food Chemistry
- Vol. 369, 130919
Abstract
No abstract availableKeywords
Funding Information
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (573894/2008-6)
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (465768/2014-8)
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (BCT-0291-3.06/17)
- Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (APQ-0721-3.06/16)
- Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (APQ-0346-1.06/14)
- University of Cambridge
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2014/50951-4)
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2008/57808\u20131)
- Johns Hopkins University
This publication has 35 references indexed in Scilit:
- Spatial mapping of Brix and moisture content in sugarcane stalk using hyperspectral imagingJournal of Near Infrared Spectroscopy, 2020
- Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithmTalanta, 2018
- Practical comparison of sparse methods for classification of Arabica and Robusta coffee species using near infrared hyperspectral imagingChemometrics and Intelligent Laboratory Systems, 2015
- Soft sensors in bioprocessing: A status report and recommendationsBiotechnology Journal, 2012
- Variable selection in regression—a tutorialJournal of Chemometrics, 2010
- Soft-sensor for industrial sugar crystallization: On-line mass of crystals, concentration and purity measurementControl Engineering Practice, 2010
- Support Vector Machines for classification and regressionThe Analyst, 2009
- Data-driven Soft Sensors in the process industryComputers & Chemical Engineering, 2009
- Application of Mid Infrared/Near Infrared Spectroscopy in Sugar IndustryApplied Spectroscopy Reviews, 2003
- Handling intrinsic non-linearity in near-infrared reflectance spectroscopyChemometrics and Intelligent Laboratory Systems, 1999