Non-Destructive Evaluation of Sugar content Using a Combination of Near-Infrared Spectroscopy (NIRS) and Chemometrics Methods

Document Type : Research Paper

Authors

1 University of Tarbiat Modares

2 Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization (AREEO),Karaj

3 Agricultural Research and Education Organization, Sugar Beet Research Institute

Abstract

In this research, the ability of the reflectance near-infrared (NIR) spectrometry was investigated for non-destructive assessment of the sugar content of sugar beet roots. To this end, spectrometry of 120 samples of sugar beet was performed in the interactance measurement mode within the spectral range of 350-2500 nm using a contact probe. Spectral data obtained from the spectrophotometer included unwanted information and noise in addition to the information about the samples. In order to arrive at accurate analytical models, pre-processing of the spectral data was required prior to regression model simulation. For this purpose, multivariate calibration models of partial least squares (PLS) were developed based on the reference measurements and the information of the preprocessed spectra. A combination of different methods for assessment and prediction of sugar content was employed: smoothing, normalizing as well as increasing the spectral resolution. Prediction of the sugar content of intact samples with the PLS model based on SG + D2, had the best discrimination ability. Thus, SG+D2 preprocessing (R_C^2=0.973, RMSEC = 0.306, R_P^2= 0.977, RMSEP = 0.265) is suitable for predicting beet root sugar content with high accuracy (SDR= 6.660).

Keywords

Main Subjects

References

Bagherpour, H., Minaei, S., Abdollahian, N. M., and  Khorasani Fardvani, M. E. (2015). Non-Destructive Determination of Sugar Content in Root Beet by Near Infrared Spectroscopy (NIRS). Iranian Journal of Food Science and Technology, 12(46), 219-228.
Birth, G. S., Dull, G. G., Renfroe, W. T. and Kays, S. J. (1985). Nondestructive spectrophotometric determination of dry matter in onions. Journal of the American Society for Horticultural Science, 110(2), 297–303.
Butz, P., C. Hofmann, and B. Tauscher. (2005). Recent developments in noninvasive techniques for fresh fruit and vegetable internal quality analysis. Journal of Food Science. 70 (9), 131-141.
Cen, H., and He, Y.(2007). Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science & Technology, 18(2), 72-83.
Clark, C. J., McGlone, V. A. and Jordan, R. B. (2003). Detection of brownheart in ‘Braeburn’ apple by transmission NIR spectroscopy. Postharvest Biology and Technology, 28(1), 87- 96.
Fu, X., Ying, Y., Lu, H., Xu, H. and Yu, H. (2007). FT-NIR diffuse reflectance spectroscopy for kiwifruit firmness detection. Sensing and Instrumentation for Food Quality and Safety, 1(1), 29-35.
Heise, H. M. and Winzen, R. (2006). Chemometrics in Near-Infrared Spectroscopy. In: Siesler, H. W., Ozaki, Y., Kawata, S. and Heise, H. M. (Eds.) Near-Infrared Spectroscopy: Principles, Instruments, Applications. 3rd Reprint. Wiley-VCH. Germany.
Jamshidi, B., Minaei, S., Mohajerani, E. and Ghassemian, H. (2011a). Analysis of citrus peel for nondestructive determination of fruit composition by reflectance Vis/NIR spectroscopy. Proceeding of theXXXIV CIOSTA CIGR V Conference on Efficient and Safe Production Processes in Sustainable Agriculture and Forestry. June 29 - July 1. Vienna. Austria.
Jamshidi, B., Minaei, S., Mohajerani, E. and Ghassemian, H. (2012a). Multivariate analysis of reflectanceVis/NIR spectra based on wavelet transform for non-destructive and detection of orange color and pHsimultaneously. Proceeding of the 7th National Congress on Agricultural Machinery Engineering and Mechanization. Sep. 4-6. Shiraz. Iran. (in Farsi)
Jamshidi, B., Minaei, S., Mohajerani, E. and Ghassemian, H. (2012b). Vis/NIR spectroscopy for nondestructive classification of orange varieties. Proceeding of the 7th National Congress on Agricultural Machinery Engineering and Mechanization. Sep. 4-6. Shiraz. Iran. (in Farsi)
Jamshidi, B., Minaei, S., Mohajerani, E. and Ghassemian, H. (2013). Linear multivariate model based on NIR spectroscopy for non-destructive internal quality prediction of orange. Proceeding of the 19th Iranian Conference on Optics and Photonics, and 5th Iranian Conference on Photonics Engineering. Jan. 22-24. Zahedan. Iran. (in Farsi)
Jamshidi, B., Minaei, S., Mohajerani, E. and Ghassemian, H. (2014). Effect of Spectral Pre-Processing Methods on Non-Destructive Quality Assessment of Oranges Using NIRS. Journal of Agricultural Engineering Research. 15(2), 27- 44. (in Farsi)
Jamshidi, B., Minaei, S., Mohajerani, E., Ghassemian, H. and Afkhami Ardakani, H. (2011b). Reflectance spectra analysis of citrus by Vis/NIR spectroscopy for nondestructive determining of inner chemical compositions. Proceeding of the 17th Iranian Conference on Optics and Photonics, and 3rd Iranian Conference on Photonics Engineering. Feb. 8-10. Kerman. Iran. (in Farsi)
Lammertyn, J., Nicolaï, B. M., Ooms, K., De Smedt, V. and De Baerdemaeker, J. (1998). Non-destructive measurement of acidity, soluble solids, and firmness of Jonagold apples using NIR spectroscopy. American Society of Agricultural and Biological Engineers, 41(4), 1089–1094.
Magana, C., Núñez-Sánchez, N., Fernández-Cabanás, V. M., García, P., Serrano, A., Pérez-Marín, D., and Alcalde, E. (2011). Direct prediction of bioethanol yield in sugar beet pulp using Near Infrared Spectroscopy. Bioresource Technology, 102(20), 9542-9549.
Mehinagic, E., Royer, G., Symoneaux, R., Bertrand, D. and Jourjon, F. (2004). Prediction of the sensory quality of apples by physical measurements. Postharvest Biology and Technology, 34(3), 257–269.
Mireei, S. A., Mohtasebi, S. S., Massudi, R., Rafiee, S. and Arabanian, A. S. (2010). Feasibility of near infrared spectroscopy for analysis of date fruits. International Agrophysics, 24, 351-356.
Moghimi, A., Aghkhani, M. H., Sazgarnia, A. and Sarmad, M. (2010). Vis/NIR spectroscopy and chemometrics for the prediction of soluble solids content and acidity (pH) of kiwifruit. Biosystems Engineering, 106(3), 295-302.
Nicolar, B. M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K. I. and Lammertyn, J. (2007a). Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review. Postharvest Biology and Technology, 46(2), 99-118.
Nicolar, B. M., Theron, K. I. and Lammertyn, J. (2007b). Kernel PLS regression on wavelet transformed NIR spectra for prediction of sugar content of apple. Chemometrics and Intelligent Laboratory Systems, 85(2), 243–252.
Nikbakht, A. M., Tavakkoli Hashtjin, T., Malekfar, R., and  Ghobadian, B. (2011). Nondestructive determination of tomato fruit quality parameters using Raman spectroscopy. Journal of Agricultural Science and Technology, 13(4), 517-526.
Pan, L., Lu, R., Zhu, Q., McGrath, J. M., and Tu, K. (2015b). Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy. Postharvest Biology and Technology, 102, 42-50.
Pan, L., Zhu, Q., Lu, R., and McGrath, J. M. (2015a). Determination of sucrose content in sugar beet by portable visible and near-infrared spectroscopy. Journal of Agriculture and Food Chemistry, 167, 264-271.
Roggo Y., Duponchel, L., and Huvenne, J.P. (2004). Quality Evaluation of Sugar Beet (Beta vulgaris) by Near-Infrared Spectroscopy. Journal of Agriculture and Food Chemistry, 52(5), 1055-1061.
Roy, S., Anantheswaran, R., Shenk, J., Westerhaus, M. O. and Beelman, R. (1993). Determination of moisture content of mushrooms by VIS-NIR-spectroscopy. Journal of the Science of Food and Agriculture, 63(3), 355–360.
 
Iranian Journal of Biosystems Engineering
Volume 49, Issue 1
April 2018
Pages 9-18

Files

History

  • Receive Date: 07 August 2016
  • Revise Date: 10 August 2017
  • Accept Date: 23 September 2017

Share

How to cite

Statistics