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بررسی اثر پیشپردازشهای مختلف طیفی بر ارزیابی غیر مخرب کیفیت پرتقال با اسپکتروفتومتری فروسرخ نزدیک (NIRS) | |||||||
| تحقیقات مهندسی صنایع غذایی | |||||||
| مقاله 3، دوره 15، شماره 2، شهریور 1393، صفحه 27-44 اصل مقاله (440.58 K) | |||||||
| نوع مقاله: مقاله پژوهشی | |||||||
| شناسه دیجیتال (DOI): 10.22092/jaer.2014.100188 | |||||||
| نویسندگان | |||||||
| بهاره جمشیدی1؛ سعید مینایی* 2؛ عزالدین مهاجرانی3؛ حسن قاسمیان4 | |||||||
| 1دانشآموخته دکتری تخصصی دانشگاه تربیت مدرس و استادیار موسسه تحقیقات فنی و مهندسی کشاورزی | |||||||
| 2استاد دانشکده کشاورزی دانشگاه تربیت مدرس | |||||||
| 3استاد پژوهشکده لیزر و پلاسما دانشگاه شهید بهشتی | |||||||
| 4استاد دانشکده مهندسی برق و کامپیوتر دانشگاه تربیت مدرس | |||||||
| چکیده | |||||||
| اسپکتروسکوپی فروسرخ نزدیک (NIR) در ترکیب با روشهای شیمیسنجی، شامل پیشپردازشهای طیفی و مدلسازیهای چندمتغیره، یکی از پرکاربردترین روشهای غیر مخرب اندازهگیری ویژگیهای کیفی میوهها و سبزیهاست که در سالهای اخیر بیشتر مد نظر پژوهشگران بوده است. در این پژوهش، توانایی روش اسپکتروسکوپی NIR بازتابی در محدوده طیفی 1650-930 نانومتر بهمنظور پیشبینی غیر مخرب مواد جامد حلشدنی (SSC) و اسیدیته قابل تیتر کردن (TA) پرتقال تامسون، همچنین اثر پیشپردازشهای مختلف طیفی بر دقت مدلهای چندمتغیره پیشبینیکننده بررسی شد. در این راستا، مدلهای واسنجی چندمتغیره حداقل مربعات جزئی (PLS) بر پایه اندازهگیریهای مرجع و اطلاعات طیفهای پیشپردازش شده با ترکیب روشهای مختلف هموارسازی (میانگینگیری متحرک (MA)، ساویتزکی- گولای (SG)، تبدیل موجک (WT))؛ نرمالسازی (تصحیح پراکنش افزاینده (MSC)، توزیع نرمال استاندارد (SNV))؛ و افزایش قدرت تفکیک طیفی (مشتقهای اول و دوم (D1، D2)) برای پیشبینی SSC و TA پرتقالها تدوین شدند. نتایج نشان داد که اسپکتروسکوپی NIR بازتابی، در ترکیب با روشهای شیمیسنجی، توانایی پیشبینی غیر مخرب SSC و TA پرتقال را دارد. همچنین، روشهای پیشپردازش اثر مستقیم بر نتایج مدلهای PLS تدوین شده برای پیشبینی این پارامترهای درونی داشتند و بهترین نتایج پیشبینی برای SSC(430/0RMSEC=، 923/0rc=، 451/0RMSEP=، 936/0rp=، 798/2SDR=) و TA(133/0RMSEC=، 883/0rc=، 177/0RMSEP=، 863/0rp=، 853/1SDR=) بر پایه ترکیب روشهای پیشپردازش MA + SNV بهدست آمد. | |||||||
| عنوان مقاله [English] | |||||||
| Effect of Spectral Pre-Processing Methods on Non-Destructive Quality Assessment of Oranges Using NIRS | |||||||
| چکیده [English] | |||||||
| Near-infrared spectroscopy (NIRS) combined with chemometric methods of spectral pre-processing and multivariate modeling is popular non-destructive method for measuring quality attributes of fruits and vegetables. The present study investigated the feasibility of reflectance NIRS in a spectral range of 930-1650 nm for non-destructive prediction of soluble solids content (SSC) and titratable acidity (TA) in Thomson oranges. The effect of spectral pre-processing methods on the accuracy of multivariate predictor models was also assessed. Partial least squares (PLS) multivariate calibration models were developed using the reference measurements and pre-processed spectra. The following methods were used: smoothing (moving average (MA), Savitzky-Golay (SG), wavelet transform (WT)); normalizing (multiplicative scatter correction (MSC), standard normal variate (SNV)); and increasing the spectral resolution (the first and second derivatives (D1, D2)) to predict the SSC and TA of oranges. The results indicate that reflectance NIRS plus chemometrics gives the potential for non-destructive prediction of SSC and TA in oranges. Pre-processing methods directly affected the results of the PLS models. The best prediction results for SSC (RMSEC = 0.430, rc = 0.923, RMSEP = 0.451, rp = 0.936, SDR = 2.798) and TA (RMSEC = 0.133, rc = 0.883, RMSEP = 0.177, rp = 0.863, SDR = 1.853) were achieved based on a combination of the MA + SNV pre-processing methods. | |||||||
| کلیدواژهها [English] | |||||||
| multivariate analysis, Near-infrared spectroscopy, Non-destructive, Pre-processing methods | |||||||
| مراجع | |||||||
|
Anon, 2005. OOIBase32 Spectrometer Operating Software, Instalation and Operation Manual. Ocean Optics, Inc. USA.
Bokobza, L. 2006. Origin of Near-Infrared Absorption Bands. In: Siesler, H. W., Ozaki, Y., Kawata, S. and Heise, H. M. (Eds.) Near-Infrared Spectroscopy: Principles, Instruments, Applications. 3rd Reprint. Wiley-VCH. Germany.
Camps, C. and Christen, D. 2009. Non-destructive assessment of apricot fruit quality by portable visible-near infrared spectroscopy. LWT-Food Sci. Technol. 42, 1125-1131.
Cayuela, J. A. 2008. VIS/NIR soluble solids prediction in intact oranges (Citrus sinensis L.) cv. Valencia Late by reflectance. Postharvest Biol. Technol. 47, 75-80.
Cayuela, J. A. and Weiland, C. 2010. Intact orange quality prediction with two portable NIR spectrometers. Postharvest Biol. Technol. 58(2): 113-120.
Cen, H. and He, Y. 2007. Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends Food Sci. Technol. 18, 72-83.
Fu, X., Yan, G., Chen, B. and Li, H. 2005. Application of wavelet transforms to improve prediction precision of near infrared spectra. J. Food Eng. 69, 461-466.
Fu, X., Ying, Y., Lu, H., Xu, H. and Yu, H. 2007. FT-NIR diffuse reflectance spectroscopy for kiwifruit firmness detection. Sens. Instrumen. Food Qual. 1, 29-35.
Guthrie, J. A., Walsh, K., Reid, D. J. and Liebensberg, C. J. 2005. Assessment of internal quality attributes of mandarin fruit. 1. NIR calibration model development. Aust. J. Agric. Res. 56, 405-416.
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.
James, C. S. 1998. Analytical Chemistry of Foods. Springer. USA.
Jamshidi, B., Minaei, S., Mohajerani, E. and Ghassemian, H. 2011a. Analysis of citrus peel for non-destructive determination of fruit composition by reflectance Vis/NIR spectroscopy. Proceeding of the XXXIV 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 reflectance Vis/NIR spectra based on wavelet transform for non-destructive and detection of orange color and pH simultaneously. 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 non-destructive 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. 2012c. Reflectance Vis/NIR spectroscopy for nondestructive taste characterization of valencia oranges. Comput. Electron. Agric. 85, 64-69.
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. Prediction of soluble solids in oranges using visible/near-infrared spectroscopy: Effect of peel. Int. J. Food Prop. 17, 1460-1468.
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)
Liu, Y., Sun, X. and Ouyang, A. 2010a. Nondestructive measurement of soluble solids content of navel orange fruit by visible-NIR spectrometric technique with PLSR and PCA-BPNN. LWT-Food Sci. Technol. 43(4): 602-607.
Liu, Y., Sun, X., Zhang, H. and Ouyang, A. 2010b. Nondestructive measurement of internal quality of Nanfeng mandarin fruit by charge coupled device near infrared spectroscopy. Comput. Electron. Agric. 71, s10-s14.
Liu, Y., Sun, X., Zhou, J., Zhang, H. and Yang, C. 2010c. Linear and nonlinear multivariate regressions for determination sugar content of intact Gannan navel orange by Vis-NIR diffuse reflectance spectroscopy. Math. Comput. Model. 51(11-12): 1438-1443.
Liu, Y., Gao, R., Hao, Y., Sun, X. and Ouyang, A. 2012. Improvement of near-infrared spectral calibration models for brix prediction in ‘gannan’ navel oranges by a portable near-infrared device. Food Bioprocess Technol. 5(3): 1106-1112.
Magwaza, L., Opara, U., Nieuwoudt, H., Cronje, P., Saeys, W. and Nicolaï, B. 2012. NIR spectroscopy applications for internal and external quality analysis of citrus fruit-A review. Food Bioprocess Technol. 5(2): 425-444.
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. Int. 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. Biosyst. Eng. 106(3): 295-302.
Nicolaï, B. M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K. I. and Lammertyn, J. 2007. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review. Postharvest Biol. Technol. 46, 99-118.
Pissard, A., Fernández-Pierna, J. A., Baeten, V., Sinnaeve, G., Lognay, G., Mouteau, A., Dupont, P., Rondia, A. and Lateur, M. 2013. Non-destructive measurement of vitamin C, total polyphenol and sugar content in apples using near-infrared spectroscopy. J. Sci. Food Agric. 93(2): 238-244.
Romía, M. B. and Bernàrdez, M. A. 2009. Multivariate Calibration for Quantitative Analysis. In: Sun, D. W. (Ed.) Infrared Spectroscopy for Food Quality Analysis and Control. 1st Ed. Academic Press.
Salguero-Chaparro, L., Baeten, V., Fernández-Pierna, J. A. and Peña-Rodríguez, F. 2013. Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives. Food Chem. 139(1-4): 1121-1126.
Wang, J., Nakano, K. and Ohashi, S. 2011. Nondestructive evaluation of jujube quality by visible and near-infrared spectroscopy. LWT-Food Sci. Technol. 44, 1119-1125.
Xia, J., Li, X., Li, P., Ma, Q. and Ding, X. 2007. Application of wavelet transform in the prediction of navel orange vitamin C content by near-infrared spectroscopy. Agric. Sci. Chin. 6(9): 1067-1073.
Zhu, D., Ji, B., Meng, C., Shi, B., Tu, Z. and Qing, Z. 2007. Study of wavelet denoising in apple's charge-coupled device near-infrared spectroscopy. J. Agric. Food Chem. 55(14): 5423-5428.
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