FT‐NIR spectroscopy: a rapid method for estimation of moisture content in bael pulp
- 19 April 2011
- journal article
- Published by Emerald in British Food Journal
- Vol. 113 (4), 494-504
- https://doi.org/10.1108/00070701111123970
Abstract
Purpose: The purpose of this paper is to develop FT‐NIR technique for determination of moisture content in bael pulp.Design/methodology/approach: Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 70 to 95 per cent (wb). The prediction models based on partial least squares (PLS) regression, were developed in the near‐infrared region (4,000‐2,500cm‐1). Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre‐processing (vector normalization, minimum‐maximum normalization and multiplicative scatter correction) methods.Findings: The best calibration model was developed with min‐max normalization (MMN) spectral pre‐processing (R2=99.3). The MMN pre‐processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.993 was obtained for the calibration model developed. The developed results indicated that FTNIR spectroscopy could be used for rapid detection of moisture content in bael pulp samples without any sample destruction.Originality/value: The research in this paper is useful for the quick detection of moisture content of bael fruit pulp during processing.Keywords
This publication has 24 references indexed in Scilit:
- A method to quantify organic functional groups and inorganic compounds in ambient aerosols using attenuated total reflectance FTIR spectroscopy and multivariate chemometric techniquesAtmospheric Environment, 2008
- Determination of Kavalactones in Dried Kava (Piper methysticum) Powder Using Near-Infrared Reflectance Spectroscopy and Partial Least-Squares RegressionJournal of Agricultural and Food Chemistry, 2006
- Development of a PLS based method for determination of the quality of beers by use of NIR: spectral ranges and sample-introduction considerationsAnalytical and Bioanalytical Chemistry, 2005
- Classification of apple beverages using artificial neural networks with previous variable selectionAnalytica Chimica Acta, 2004
- Comparison of Combination and First Overtone Spectral Regions for Near-Infrared Calibration Models for Glucose and Other Biomolecules in Aqueous SolutionsAnalytical Chemistry, 2004
- Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopyAnalytica Chimica Acta, 2003
- Dry matter determination in ‘Hass’ avocado by NIR spectroscopyPostharvest Biology and Technology, 2003
- Detection of Brownheart in ‘Braeburn’ apple by transmission NIR spectroscopyPostharvest Biology and Technology, 2002
- Partial Least Squares (PLS): Its strengths and limitationsPerspectives in Drug Discovery and Design, 1993
- Review: Near infra‐red analysis of foodInternational Journal of Food Science & Technology, 1987