Study of the Spectroscopic Data Analysis Pretreatments for Enhancing Performance of NIR Calibration Model for Determining the Brix Value of Japanese Pear

##plugins.themes.bootstrap3.article.main##

Karunrat Sakulnarmrat and Piyamart Jannok

Abstract

Spectral pretreatment is one of essential procedures to improve data quality prior to establishment of calibration model and removal of physical interferences from spectra, which could enhance the model accuracy. An evaluation of Japanese Pear (Pyrus pyrifolia) sweetness using Near Infrared (NIR) spectroscopy technique with short wavelength (700 ~ 1100 nm) region and interactance mode was investigated.  Several multivariate calibration techniques were compared and validated by establishing figures of merit. Various pretreatments with truncation were also employed in order to construct the best model of sweetness assessment. This included an individual and combination pretreatments. The best calibration was obtained through combination of multiplicative scatter correction (MSC) and second derivative (MSC+2D). It was characterized as follows: (F = 3), R2 = 0.77, SEC = 0.56°Brix, SEP = 0.64°Brix and bias of -0.10°Brix. The results suggest potential application of NIR technique by food industries to assess pear sweetness that is non-destructive, fast and flexible.

References

Angra, S. K., Dimri, A. K., & Kapur, P. (2009). Nondestructive Brix Evaluation of Apples of Different Origin Using Near Infrared (NIR) Filter Based Reflectance Spectroscopy. Instrum Sci Technol, 37(2), 241-253.

Fan, G., Zha, J., Dub, R., & Gao, L. (2009). Determination of soluble solids and firmness of apples by Vis/NIR transmittance. J Food Eng, 93(4), 416-420.

Jannok, P., Kamitani, Y., & Kawano, S. (2014). Development of a common calibration model for determining the Brix value of intact apple, pear and persimmon fruits by near infrared spectroscopy. J Near infrared Spectrosc, 22(5), 367-373.

Kawano, S., Watanabe, H., & Iwanoto M. (1992). Determination of sugar content in intact peaches by near infrared spectroscopy with fiber optics in interactance mode. J Japan Soc Hort Sci, 61(1), 445-451.

Kawano, S., Abe, H., & Iwamoto, M. (1995). Development of a calibration with temperature compensation for determining the Brix value in intact peaches. J Near Infrared Spec, 3(4), 211-218. http://dx.doi.org/10.1255.jnirs.71

Machado, N. P., Fachinello, J. C., Galarca, S. P., Betemps, D. L., Pasa, M. S., & Schmitz, J. D. (2012). Pear quality characteristics by Vis/Nir spectroscopy. Ann Braz Acad Sci, 84(3), 853-863.


Osborne, B. G., Fearn, T., & Hindle P. H. (1993). Practical NIR Spectroscopy with Applications in Food and Beverage Analysis (2nd ed.). Longman Group: Harlow, England, UK.

Park, B., Abbott, J. A., Lee, K. J., Choi, C. H., & Choi, K. H. (2003). Near-infrared diffuse reflectance for quantitative and qualitative measurement of soluble solids and firmness of Delicious and Gala apples. Trans Amer Soc Agr Eng, 46, 1721– 1731.

Paz, P., Sanchez, M-T., Perez-Marin, D., Guerrero, J-E., & Garrido-Varo, A. (2009). Evaluating NIR instruments for quantitative and qualitative assessment of intact apple quality. J Sci Food Agric, 89(5), 781-790.

Porteous, R., Muir, A., & Wastie, R. (1981). The identification of diseases and defects in potato tubers from measurements of optical spectral reflectance. J Agri Eng Res, 26(2), 151–160.

Sakulnarmrat, K., Shinomiya, T., Jannok, P., Kamitani, Y., & Kawano, S. (2015). A simple method of system response compensation of a near infrared instrument for determining Brix value of Peaches. In 6th Rajamangala University of Technology International Conference (RMUTIC), Green Innovation for a Better Life, 1-3 September 2015, Nakhonratchasima, Thailand: Rajamangala University of Technology Isan.

Saranwong, S., Sornsrivichai, J., & Kawano, S. (2003b). On-tree evaluation of harvesting quality of mango fruit using a hand-held NIR instrument. J Near Infrared Spectrosc, 11(4), 283-293.

Shi, B., Ji, B., Zhu, D., Tu, Z., & Qing, Z. (2008). Study on genetic algorithms-based NIR wavelength selection for determination of soluble solids content in fuji apples. J Food Quality, 31(2), 232-249.

Sirisomboon, P., Tanaka, M., Fujita, S., & Kojima, T. (2007). Evaluation of pectin constituents of Japanese pear by near infrared spectroscopy. J Food Eng, 78(2), 701-707.

Terdwongworakul, A., Nakawajana, N., Teerachaichayut, S., & Janhiran, A. (2012). Determination of translucent content in mangosteen by means of near infrared transmittance. J Food Eng, 109(1), 114-119.

Tsai, C. Y., Chen, H. J., Hsieh, J. F., & Sheng C. T. (2007). Fabrication of a near infrared online inspection system for pear fruit. Int Agric Eng J, 16, 57-70.

Wikipedia. (2014). Pear. Retrieved from http://en.wikipedia.org/wiki/Pyrus_pyrifolia

Ying, Y., Liu, Y., & Fu, X. (2006). Performance of FT-NIR instrument for Brix value measurement of intact pear fruit. Int J Postharv Tech Inn, 1(2). http://dx.doi.org/10.1504/IJPTI.2006.011665

Ying, Y., & Liu, Y. (2008). Nondestructive measurement of internal quality in pear using genetic algorithms and FTNIR spectroscopy. J Food Eng, 84(2), 206-213.

Saranwong, S., Sornsrivichai, J., & Kawano, S. (2003a). Performance of a portable near infrared instrument for Brix value determination of intact mango fruit. J Near Infrared Spectrosc, 11, 175-181.

Keywords
Pear, Near infrared spectroscopy, spectroscopic data analysis, spectral pretreatment
Section
Research Articles

##plugins.themes.bootstrap3.article.details##

How to Cite
AND PIYAMART JANNOK, Karunrat Sakulnarmrat. Study of the Spectroscopic Data Analysis Pretreatments for Enhancing Performance of NIR Calibration Model for Determining the Brix Value of Japanese Pear. Naresuan University Journal: Science and Technology (NUJST), [S.l.], v. 25, n. 2, p. 32-40, may 2017. ISSN 2539-553X. Available at: <http://www.journal.nu.ac.th/NUJST/article/view/1772>. Date accessed: 24 july 2019.