title: Application of Rapid Visco Analyser (RVA) viscograms and chemometrics for maize hardness characterisation.
abstract: It has been established in this study that the Rapid Visco Analyser (RVA) can describe maize hardness, irrespective of the RVA profile, when used in association with appropriate multivariate data analysis techniques. Therefore, the RVA can complement or replace current and/or conventional methods as a hardness descriptor. Hardness modelling based on RVA viscograms was carried out using seven conventional hardness methods (hectoliter mass (HLM), hundred kernel mass (HKM), particle size index (PSI), percentage vitreous endosperm (%VE), protein content, percentage chop (%chop) and near infrared (NIR) spectroscopy) as references and three different RVA profiles (hard, soft and standard) as predictors. An approach using locally weighted partial least squares (LW-PLS) was followed to build the regression models. The resulted prediction errors (root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP)) for the quantification of hardness values were always lower or in the same order of the laboratory error of the reference method.
authors.affiliation: Department of Food Science, Stellenbosch University, Private Bag X1, Matieland (Stellenbosch) 7602, South Africa. Electronic address: 12356832@sun.ac.za.
authors.forename: Anina
authors.initials: A
authors.lastname: Guelpa
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", P.le Aldo Moro 5, Rome I-00185, Italy. Electronic address: marta.bevilacqua@uniroma1.it.
authors.forename: Marta
authors.initials: M
authors.lastname: Bevilacqua
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", P.le Aldo Moro 5, Rome I-00185, Italy. Electronic address: federico.marini@uniroma1.it.
authors.forename: Federico
authors.initials: F
authors.lastname: Marini
authors.affiliation: Essential Foods, Division of Pioneer Foods (Pty.) Ltd., PO Box 9149, Huguenot 7645, South Africa. Electronic address: Kim.O'Kennedy@pioneerfoods.co.za.
authors.forename: Kim
authors.initials: K
authors.lastname: O'Kennedy
authors.affiliation: Department of Food Science, Stellenbosch University, Private Bag X1, Matieland (Stellenbosch) 7602, South Africa; Institute of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences, Skogsmarksgränd, 90183 Umeå, Sweden. Electronic address: Paul.Geladi@slu.se.
authors.forename: Paul
authors.initials: P
authors.lastname: Geladi
authors.affiliation: Department of Food Science, Stellenbosch University, Private Bag X1, Matieland (Stellenbosch) 7602, South Africa. Electronic address: mman@sun.ac.za.
authors.forename: Marena
authors.initials: M
authors.lastname: Manley
mesh_terms: D004044:Dietary Proteins / Q000032:analysis; D005511:Food Handling; D006244:Hardness; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D010316:Particle Size; D025341:Principal Component Analysis; D019265:Spectroscopy, Near-Infrared; D003313:Zea mays / Q000737:chemistry*
chemical_list: D004044:Dietary Proteins
keywords: Chemometrics; Conventional hardness methods; Locally weighted partial least squares (LW-PLS) regression; Maize hardness; Milling quality; Rapid Visco Analyser (RVA); White maize