ارزیابی روش طیف‌سنجی مرئی- نزدیک فروسرخ موج کوتاه (Vis-SWNIR) برای سنجش رطوبت و غلظت ساکاروز در مواد فیبری متخلخل: مطالعه موردی باگاس نیشکر

نویسندگان

1 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه شهرکرد، شهرکرد، ایران

2 گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه شهرکرد، شهرکرد، ایران

3 موسسه تحقیقات و آموزش نیشکر و صنایع جانبی خوزستان، اهواز، ایران

4 گروه مهندسی بیوسیستم، دانشکده مهندسی زراعی و توسعه روستایی، دانشگاه علوم کشاورزی و منابع طبیعی خوزستان، اهواز، ایران

چکیده

بکارگیری طیف­سنج­های با محدوده طول موج مرئی- نزدیک فروسرخ موج کوتاه (Vis-SWNIR) به عنوان روشی سریع و کم­هزینه­ به منظور اندازه­گیری رطوبت و غلظت قند در مواد غذایی و کشاورزی مورد توجه محققین بوده است. هدف از این مطالعه، ارزیابی طیف‌سنجی بازتابی Vis-SWNIR برای اندازه­گیری رطوبت و غلظت ساکاروز در مواد فیبری متخلخل با مطالعه موردی بر روی باگاس نیشکر می­باشد. به منظور افزایش مساحت در تعامل بین نور و ماده و افزایش نسبت سیگنال به نویز، یک محفظه نورپردازی با دو لامپ هالوژن 50 وات در مقایسه با نورپردازی از طریق لامپ دستگاه طیف­سنج با فیبر نوری در محدوده طول موج 1100-400 نانومتر ساخته و استفاده شد. در گام اول تعداد 48 نمونه با افزودن رطوبت و ساکاروز محلول به کاه گندم آسیاب شده تهیه و اندازه­گیری شد. از روش­ رگرسیونی چند متغیره حداقل مربعات جزیی (PLSR)، برای توسعۀ مدل­های پیش­بینی متغیرهای رطوبت و غلظت ساکاروز نمونه­ها استفاده شد. اعتبارسنجی مدل­ پیش­بینی PLSR  با استفاده از روش نورپردازی لامپ هالوژن، پیش­بینی قوی­تری از درصد رطوبت (88/0 R2=، 3/3 RMSE= و 07/3RPD=) و ساکاروز (78/0 R2=، 95/3 RMSE= و 25/2RPD=) نمونه­های کاه در مقایسه با نورپردازی با فیبر نوری نشان داد که بیانگر قدرت پیشگویی بسیار خوبی می­باشد. نتایج ارزیابی سامانه بر روی 50 نمونه باگاس نیشکر برای درصد رطوبت (69/0 R2=، 26/0 RMSE= و 46/1RPD=) و ساکاروز (44/0 R2=، 27/0 RMSE= و 01/1RPD=) قدرت پیشگویی ضعیف­تری نشان داد که می­تواند به دلیل نایکنواخت بودن بافت نمونه­های باگاس در مقایسه با کاه و دامنه تغییرات محدودتر رطوبت و ساکاروز در نمونه­های باگاس باشد. نتایج این مطالعه نشان داد که محدوده طیف Vis-SWNIR می­تواند بر روی نمونه­های همگن فیبری در صورتی که محدوده تغییرات خصوصیات قابل توجه باشد قدرت پیشگویی مطلوبی داشته باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluation of Visible-short wave near infrared (Vis-SWNIR) spectroscopy for measurement of water content and sucrose concentration in porous fibrous material: Case study on sugarcane bagasse

نویسندگان [English]

  • Ali Farahmandi 1
  • Mojtaba Naderi-Boldaji 2
  • Maral Ajamian 3
  • Mahdi Ghasemi-Varnamkhasti 1
  • Saman Abdanan Mehdizadeh 4
1 Department of Biosystems Engineering, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran
2 Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran
3 Khuzestan Sugarcane and By-products Development Research and Training Institute, Ahvaz, Iran
4 Mechanics of Biosystems Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Iran
چکیده [English]

 The use of spectrophotometers in the range of visible to short-wave near infrared (Vis-SWNIR) is of interest for researchers as a fast and low-cost method to measure moisture and sugar concentration in food and agricultural products. The aim of this study is to evaluate Vis-SWNIR reflectance spectroscopy for measuring moisture content and sucrose concentration in porous fibrous materials with a case study on sugarcane bagasse.  In order to increase the interaction area between the light and sample and to increase the signal-to-noise ratio, a lighting chamber with two 50 W halogen lamps was made and evaluated in comparison with lighting through the spectrophotometer lamp with optical fiber in the wavelength range of 400-1100 nm.  In the first step, 48 samples were prepared and measured by adding different amounts of water-sucrose solution to ground wheat straw. Multivariate partial least square regression (PLSR) method was used to develop prediction models for moisture and sucrose concentration of the samples. Validation of PLSR prediction model using halogen lamp lighting method, showed stronger prediction of moisture content (R2=0.88, RMSE=3.3 and RPD=3.07) and sucrose concentration (R2=0.78, RMSE=3.95 and RPD = 2.25) as compared to lighting with optical fiber. Evaluation results on 50 sugarcane bagasse samples for moisture content (R2=0.69, RMSE=0.26 and RPD=1.46) and sucrose concentration (R2=0.44, RMSE=0.27 and RPD=1.01) showed a weaker predictive power, which could be due to the non-uniform texture of bagasse samples compared to straw and the limited range of moisture and sucrose variations.  The results of this study showed that the spectral range of Vis-SWNIR can have a promising predictive power on homogeneous fiber samples if the range of variations in water content and sucrose concentration to be significant.

کلیدواژه‌ها [English]

  • Porous fibrous materials
  • Short-wave near infrared (Vis-SWNIR)
  • Sugarcane bagasse
  • Sugar concentration

مراجع

Abu-Khalaf, N., and Hmidat, M. (2020). Visible/Near Infrared (VIS/NIR) spectroscopy as an optical sensor for evaluating olive oil quality. Computers and Electronics in Agriculture. 173: 105445. https://doi.org/10.1016/j.compag.2020.105445.
Aghaei Saadi, M., Minaei, S., Jamshidi, B. and Abdullahian Nougabi, M. (2021). Non-destructive measurement of sugar beet grade by combining near infrared spectroscopy (NIR) with chemometric methods. Biosystem Engineering of Iran. 1(49): 9-18. (In Persian). https://doi.org/10.22059/IJBSE.2017.208413.664785.
Aparatana, K., Ishikawa, D., Maraphum, K., Saengprachatanarug, K., Agarie, H., Shikanai, T., and Taira, E. (2022). Non-destructive Laboratory Analysis of the Detection of Unhealthy Sugarcane Stalks Using a Portable Vis-NIR Spectrometer. Engineering in Agriculture, Environment and Food. 15(2): 72-80. https://doi.org/10.37221/eaef.15.2_72.
Bagherpour, H., Mohammadi, M. (2016). Determining the humidity and Brix degree of carrots using near-infrared spectroscopy. Biosystem Engineering Journal of Iran. 1(48): 1-7. (In Persian).  https://doi.org/10.22059/IJBSE.2017.61555.
Blackburn, F. (1950). Sugar cane (translated by Mohammad Reza Rahdar). Shahid Chamran University of Ahvaz: 660pp. (In Persian).
Chen, W., Li, H., Zhang, F., Xiao, W., Zhang, R., Chen, Z., and Du, Y. (2021). Handheld short-wavelength NIR spectroscopy for rapid determination of sugars and carbohydrate in fresh juice with sampling error profile analysis. Infrared Physics & Technology. 115: 103732. https://doi.org/10.1016/j.infrared.2021.103732.
Cortés, V., Blasco, J., Aleixos, N., Cubero, S., and Talens, P. (2019). Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: A review. Trends in Food Science & Technology. 85: 138-148. https://doi.org/10.1016/j.tifs.2019.01.015.
De Whalley, H. C. S. (Ed.). (2013). ICUMSA methods of sugar analysis: official and tentative methods recommended by the International Commission for Uniform Methods of sugar analysis (ICUMSA). Elsevier.
Fan, S., Li, J., Xia, Y., Tian, X., Guo, Z., and Huang, W. (2019). Long-term evaluation of soluble solids content of apples with biological variability by using near-infrared spectroscopy and calibration transfer method. Postharvest Biology and Technology. 151: 79-87. https://doi.org/10.1016/j.postharvbio.2019.02.001.
Forozani, B., Bagherpour, H. and Zabli, Kh. (2019). Detection of protein content and moisture content of wheat grains using non-destructive near-infrared (NIR) method. 11th National Congress of Biosystem Mechanical Engineering and Mechanization. Iran. Hamedan. (In Persian). https://doi.org/10.52547/fsct.17.99.45.
Golic, M., Walsh, K., and Lawson, P. (2003). Short-wavelength near-infrared spectra of sucrose, glucose, and fructose with respect to sugar concentration and temperature. Applied spectroscopy. 57(2): 139-145. https://doi.org/10.1366/000370203321535033.
Hadiwijaya, Y., Putri, I. E., and Munawar, A. A. (2021). Multi-product calibration model for soluble solids and water content quantification in Cucurbitaceae family, using visible/near-infrared spectroscopy. Heliyon. 7(8). https://doi.org/10.1016/j.heliyon.2021.e07677.
Iweka, P., Kawamura, S., Mitani, T., Kawaguchi, T., and Koseki, S. (2020). Online milk quality assessment during milking using near-infrared spectroscopic sensing system. Environmental Control in Biology. 58(1): 1-6. https://doi.org/10.2525/ecb.58.1.
Kim, G. Y., Lee, K. J., Choi, K. H., Son, J. R., Choi, D. S., and Kang, S. W. (2004). Defect and ripeness inspection of citrus using NIR transmission spectrum. Key engineering materials. 270: 1008-1013. https://doi.org/10.4028/www.scientific.net/KEM.270273.100.
Lan, W., Bureau, S., Chen, S., Leca, A., Renard, C. M., and Jaillais, B. (2021). Visible, near-and mid-infrared spectroscopy coupled with an innovative chemometric strategy to control apple puree quality. Food Control. 120: 107546. https://doi.org/10.1016/j.foodcont.2020.107546.
Li, J., Wang, Q., Xu, L., Tian, X., Xia, Y. and Fan, S. (2019). Comparison and optimization of models for determination of sugar content in pear by portable Vis-NIR spectroscopy coupled with wavelength selection algorithm. Food Analytical Methods. 12(1): 12-22. https://doi.org/10.1007/s12161-018-1326-7.
Madsen, L. R., White, B. E., Rein, P. W., Madsen, L. R., White, B. E., and Rein, P. W. (2003). Evaluation of a near infrared spectrometer for the direct analysis of sugar cane. Journal American Society of Sugarcane Technologists, 23(80), e92.
Maraphum, K., Saengprachatanarug, K., Wongpichet, S., Phuphaphud, A., and Posom, J. (2020). In-field measurement of starch content of cassava tubers using handheld vis-near infrared spectroscopy implemented for breeding programmes. Computers and Electronics in Agriculture. 175: 105607. https://doi.org/10.1016/j.compag.2020.105607.
Meade, G. P., and Chen, J. C. P. (1977). Cane sugar handbook: a manual for cane sugar manufacturers and their chemists. John Wiley and Sons.
Naderi-Boldaji, M., Tohidi, M., and Ghasemi-Varnamkhasti, M. (2023). Evaluation of dielectric spectroscopy in fusion with Vis-SWNIR spectroscopy for measurement of sugar concentration on sugarcane stalk samples. Journal of Agricultural Aachinery. (In Persian). https://doi.org/10.22067/JAM.2023.80620.1144.
Nawi, N. M., Chen, G., Jensen, T., and Mehdizadeh, S. A. (2013). Prediction and classification of sugar content of sugarcane based on skin scanning using visible and shortwave near infrared. Biosystems Engineering. 115(2): 154-161. https://doi.org/10.1016/j.biosystemseng.2013.03.005.
O'Shea, M. G., Staunton, S. P., and Burleigh, M. (2010). Implementation of on-line near infrared (NIR) technologies for the analysis of cane, bagasse and raw sugar in sugar factories to improve performance.
Pan, L., Zhu, Q., Lu, R., and McGrath, J. M. (2015). Determination of sucrose content in sugar beet by portable visible and near-infrared spectroscopy. Food chemistry, 167, 264-271. https://doi.org/10.1016/j.foodchem.2014.06.117.
Phuphaphud, A., Saengprachatanarug, K., Posom, J., Maraphum, K. and Taira, E. (2020). Nondestructive and rapid measurement of sugar content in growing cane stalks for breeding programs using visible-near infrared spectroscopy. Biosystems Engineering. 197: 76-90. https://doi.org/10.1016/j.biosystemseng.2020.06.012.
Posom, J., Klaprachan, J., Rattanasopa, K., Sirisomboon, P., Saengprachatanarug, K., and Wongpichet, S. (2020). Predicting marian plum fruit quality without environmental condition impact by handheld visible–near-infrared spectroscopy. ACS omega. 5(43): 27909-27921. https://doi.org/10.1021/acsomega.0c03203.
Rady, A., and Guyer, D. (2015). Utilization of visible/near-infrared spectroscopic and wavelength selection methods in sugar prediction and potatoes classification. Journal of Food Measurement and Characterization. 9: 20-34. https://doi.org/10.1007/s11694-014-9207-2.
Shushtri, M. Ahmadian, S. Asafia, Q. (2008). Sugarcane in Iran. Ayij: 337pp. (In Persian).
Simeone, M. L. F., Parrella, R. A., Schaffert, R. E., Damasceno, C. M., Leal, M. C., and Pasquini, C. (2017). Near infrared spectroscopy determination of sucrose, glucose and fructose in sweet sorghum juice. Microchemical Journal. 134: 125-130. https://doi.org/10.1016/j.microc.2017.05.020.
Soleimani Sodehi, M. (2014). The roadmap for the transformation of the supply chain of the Iranian sugar industry. Commercial Print and Publications: 210 pp. (In Persian).
Tewari, J. C. and Malik, K. (2007). In situ laboratory analysis of sucrose in sugarcane bagasse using attenuated total reflectance spectroscopy and chemometrics. Food Science and Technology. 42: 200-207. https://doi.org/10.1111/j.1365-2621.2006.01209.x.
Wang, J., Wang, J., Chen, Z., and Han, D. (2017). Development of multi-cultivar models for predicting the soluble solid content and firmness of European pear (Pyrus communis L.) using portable vis–NIR spectroscopy. Postharvest Biology and Technology. 129: 143-151. https://doi.org/10.1016/j.postharvbio.2017.03.012.
Williams, P. C., and Norris, K. (2001). Variables affecting near-infrared spectroscopic analysis. Near-infrared technology in the agricultural and food industries. 2: 171-198.
Workman Jr, J., and Weyer, L. (2007). Practical guide to interpretive near-infrared spectroscopy. CRC press. https://doi.org/10.1201/9781420018318.
Xia, Y., Fan, S., Li, J., Tian, X., Huang, W., and Chen, L. (2020). Optimization and comparison of models for prediction of soluble solids content in apple by online Vis/NIR transmission coupled with diameter correction method. Chemometrics and Intelligent Laboratory Systems. 201: 104017. https://doi.org/10.1016/j.chemolab.2020.104017.
Zhang, H., Duan, Z., Li, Y., Zhao, G., Zhu, S., Fu, W., and Hu, J. (2019). Vis/NIR reflectance spectroscopy for hybrid rice variety identification and chlorophyll content evaluation for different nitrogen fertilizer levels. Royal Society open science. 6(10): 191132. https://doi.org/10.1098/rsos.191132.
Zhang, H., Zhan, B., Pan, F., and Luo, W. (2020). Determination of soluble solids content in oranges using visible and near infrared full transmittance hyperspectral imaging with comparative analysis of models. Postharvest Biology and Technology. 163: 111148. https://doi.org/10.1016/j.postharvbio.2020.111148.
مکانیزاسیون کشاورزی
دوره 9، شماره 2
تیر 1403
صفحه 29-44

فایل ها

سابقه مقاله

  • تاریخ دریافت: 06 خرداد 1403
  • تاریخ بازنگری: 24 شهریور 1403
  • تاریخ پذیرش: 15 مهر 1403

هم رسانی

ارجاع به این مقاله

آمار