Hyperspectral imaging for the determination of potato slice moisture content and chromaticity during the convective hot air drying process

Hyperspectral imaging (HSI) was utilised for the determination of moisture content of potato slices with three thicknesses (5 mm, 7 mm, 9 mm) at three drying temperatures (50 °C, 60 °C, 70 °C) during convective drying in a laboratory hot air dryer. The Page, thin-layer drying model was found better to explain the drying kinetics with a fitting accuracy of R2 (0.96–0.99) and lowest reduced Chi-square (0.00024–0.00090), Root mean square errors (RMSE) (0.014–0.026), and relative percentage error (1.5%–5.1%) under the used drying conditions. Spectral data were analysed using partial least squares regression (PLS) analysis, a multivariate calibration technique, alongside Monte Carlo Uninformative Variable Elimination (MCUVE-PLS) and competitive adaptive reweighted sampling (CARS-PLS). The feasibility of both moisture content and CIELAB prediction with a reduced wavelength set from the Visible near-infrared (VNIR) region (500–1000 nm) was investigated with these three models. The PLS model (R2 = 0.93–0.98, RMSE = 0.16–0.36 and the lowest number of optimal wavelengths = 6, for all drying conditions) was found suitable to implement for the moisture visualisation procedure. Potato chromaticity was also shown to be predictable during drying using a similar number of wavelengths, with PLS models for CIELAB a* performing well (R2 = 0.91–0.65, RMSE = 0.61–1.78). PLS Models for CIELAB b* more variably (R2 = 0.91–0.62, RMSE = 2.16–4.42) due to potato colour mainly varying along this axis. The current study showed that hyperspectral imaging was a useful tool for non-destructive measurement and visualisation of the moisture content and chromaticity during the drying process.

[1]  E. Akoy.  Experimental characterization and modeling of thin-layer drying of mango slices. , 2014 .

[2]  Alan M. Lefcourt,et al.  A novel integrated PCA and FLD method on hyperspectral image feature extraction for cucumber chilling damage inspection , 2004 .

[3]  Hartwig Schulz,et al.  Application of near Infrared Spectroscopy for the Quantification of Quality Parameters in Selected Vegetables and Essential Oil Plants , 1998 .

[4]  W. P. Silva,et al.  Mathematical models to describe thin-layer drying and to determine drying rate of whole bananas , 2014 .

[5]  Zhu Zhou,et al.  Nondestructive Detection of Blackheart in Potato by Visible/Near Infrared Transmittance Spectroscopy , 2015 .

[6]  Jasper G. Tallada,et al.  NIR Hyperspectral Imaging for Measurement of Internal Quality in Strawberries , 2005 .

[7]  P. Cârlescu,et al.  Convective Air Drying Characteristics for Thin Layer Carrots , 2013 .

[8]  Da-Wen Sun,et al.  Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review , 2012, Critical reviews in food science and nutrition.

[9]  V. Chelladurai,et al.  Detection of infestation by Callosobruchus maculatus in mung bean using near-infrared hyperspectral imaging , 2013 .

[10]  H. Martens,et al.  Variable Selection in near Infrared Spectroscopy Based on Significance Testing in Partial Least Squares Regression , 2000 .

[11]  Min Zhang,et al.  Detection of insect-damaged vegetable soybeans using hyperspectral transmittance image , 2013 .

[12]  Jolana Tarkosova,et al.  Determination of Carbohydrate Content in Bananas during Ripening and Storage by near Infrared Spectroscopy , 2000 .

[13]  A. Hurlbert,et al.  Moisture content measurement in dried apple produce through visible wavelength hyperspectral imaging , 2015 .

[14]  Bart Nicolai,et al.  Prediction of optimal cooking time for boiled potatoes by hyperspectral imaging , 2011 .

[15]  İbrahim Doymaz,et al.  Convective drying kinetics of strawberry , 2008 .

[16]  Aoife Gowen,et al.  Prediction of white button mushroom (Agaricus bisporus) moisture content using hyperspectral imaging , 2009 .

[17]  G. Xanthopoulos,et al.  Evaluation of Thin-Layer Models for Mushroom (Agaricus bisporus) Drying , 2007 .

[18]  Ning Wang,et al.  Studies on banana fruit quality and maturity stages using hyperspectral imaging , 2012 .

[19]  E. Akpinar,et al.  Thin layer drying of red pepper , 2003 .

[20]  W. Horwitz.  Official Methods of Analysis , 1980 .

[21]  Da-Wen Sun,et al.  Recent Progress of Hyperspectral Imaging on Quality and Safety Inspection of Fruits and Vegetables: A Review. , 2015, Comprehensive reviews in food science and food safety.

[22]  I. L. Pardeshi,et al.  Thin-Layer Drying of Green Peas and Selection of a Suitable Thin-Layer Drying Model , 2009 .

[23]  Robert H. Driscoll,et al.  The thin-layer drying characteristics of garlic slices , 1996 .

[24]  R. K. Goyal,et al.  Thin-layer Drying Kinetics of Raw Mango Slices , 2006 .

[25]  S. Simal,et al.  Mathematical modelling of the drying curves of kiwi fruits: influence of the ripening stage , 2005 .

[26]  C. Ertekin,et al.  Mathematical modeling of thin layer solar drying of sultana grapes , 2001 .

[27]  Daniel E. Guyer,et al.  Evaluation of Sugar Content of Potatoes using Hyperspectral Imaging , 2015, Food and Bioprocess Technology.

[28]  K. Górnicki,et al.  Evaluation of drying models of apple (var. McIntosh) dried in a convective dryer. , 2010 .

[29]  R. Hartmann,et al.  NIR determination of potato constituents , 1998, Potato Research.

[30]  M. Ngadi,et al.  Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry , 2007 .

[31]  M. Mehrubeoglu,et al.  Determination of total reducing sugars in potato samples using near-infrared spectroscopy , 1997 .

[32]  İbrahim Doymaz,et al.  The kinetics of forced convective air-drying of pumpkin slices , 2007 .

[33]  Barbara Sturm,et al.  Thermodynamic analysis of drying process in a diagonal-batch dryer developed for batch uniformity using potato slices , 2016 .

[34]  İbrahim Doymaz,et al.  Convective air drying characteristics of thin layer carrots , 2004 .

[35]  Ning Wang,et al.  Water Content and Weight Estimation for Potatoes Using Hyperspectral Imaging , 2005 .

[36]  Henry Jaeger,et al.  DRYING TECHNOLOGIES IN FOOD PROCESSING , 2014 .

[37]  Di Wu,et al.  Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications , 2013 .

[38]  Xiuqin Rao,et al.  Detection of common defects on oranges using hyperspectral reflectance imaging , 2011 .

[39]  L. Diamante,et al.  Short communication A new mathematical model for thin layer drying of fruits , 2010 .

[40]  W. Cai,et al.  A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra , 2008 .

[41]  Kuanglin Chao,et al.  Development and Application of Multispectral Algorithms for Defect Apple Inspection , 2012 .

[42]  Qing-Song Xu,et al.  libPLS: An integrated library for partial least squares regression and linear discriminant analysis , 2018 .

[43]  Douglas Fernandes Barbin,et al.  Grape seed characterization by NIR hyperspectral imaging , 2013 .

[44]  A. Hurlbert,et al.  Use of hyperspectral imaging for the prediction of moisture content and chromaticity of raw and pretreated apple slices during convection drying , 2018 .

[45]  Jean-Michel Roger,et al.  Combination of optical and non-destructive mechanical techniques for the measurement of maturity in peach , 2012 .

[46]  Moon S. Kim,et al.  Detection of cuticle defects on cherry tomatoes using hyperspectral fluorescence imagery , 2013 .

[47]  M. Scanlon,et al.  Quality evaluation of processing potatoes by near infrared reflectance , 1999 .

[48]  Hongdong Li,et al.  Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. , 2009, Analytica chimica acta.