بررسی تأثیر فرآیند خشک ‌کردن بر ویژگی های رنگی گلبرگ زعفران با استفاده از ماشین بینایی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی مکانیک بیوسیستم،دانشکده کشاورزی، دانشگاه تربیت مدرس،تهران

2 استاد گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه تربیت مدرس، تهران

3 استادیار گروه علوم باغبانی، دانشکده کشاورزی، دانشگاه تربیت مدرس، تهران

10.22048/jsat.2018.91656.1241

چکیده

خشک کردن یکى از روش‌هاى رایج براى افزایش ماندگارى گیاهان دارویی و محصولات کشاورزى است. در این پژوهش، فرآیند خشک کردن گلبرگ‌های زعفران با خشک کن هوای داغ لایه نازک در پنج سطح دمای 40، 60، 80، 100 و 120 درجه سلسیوس و سه سرعت هوای 5/0، 1 و 5/1 متر بر ثانیه و تأثیرات آن‌ها بر پارامتر‌های رنگی (مقادیر G ,R و B) مورد بررسی قرار گرفت. به کمک سامانه ماشین بینایی، تصاویر رنگی از نمونه‌های خشک شده گلبرگ زعفران، دریافت و با استفاده از الگوریتم‌های پردازش تصویر، مورد پردازش قرار گرفت. ویژگی-های رنگی (RGB) آن‌ها نیز استخراج گردید. از سوی دیگر میزان آنتوسیانین به روش pH افتراقی و ویژگی‌هایL*a*b* نمونه‌ها به منظور تعیین شرایط مناسب خشک کردن اندازه‌گیری شدند. داده‌های حاصل با استفاده از آزمایش فاکتوریل در قالب طرح کاملا تصادفی مورد تجزیه و تحلیل آمـاری قرار گرفتنـد. نتایج بررسی نشان داد بیشترین مقادیرRGB مربوط به محدوده‌ دمای 80 تا 100 درجه سلسیوس است که نشان دهنده‌ی بیشترین نسبت و شدت رنگ‌های قرمز، سبز و آبی می‌باشد. همچنین در این بازه دمایی بیشترین میزان آنتوسیانین (21/482 میلی‌گرم بر لیتر) و کمترین مقدار تغییرات رنگ (∆E) بدست آمد که مطلوبیت نسبی این بازه برای خشک کردن گلبرگ‌های زعفران را نشان می‌دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Effect of the drying process on saffron petals color Features using the vision machine

نویسندگان [English]

  • Sedigheh Kasali 1
  • Saeed Minaei 2
  • Mahdi Ayyari 3
1 MSc student, Biosystems Engineering, Faculty of Agriculture, Tarbiat Modares University, Tehran
2 Professor of Biosystems Engineering, Faculty of Agriculture, Tarbiat Modares University, Tehran
3 Assistant Professor of Horticultural Science, Faculty of Agriculture, Tarbiat Modares University, Tehran
چکیده [English]

Iran is the largest producer of saffron and more than 90 percent of Iran's saffron is produced in Iran.Drying is one of the methods commonly used to increase the shelf life of medicinal plants and agricultural products. In this study, drying process of saffron petals with thin layer hot air dryer at five levels at 40, 60, 80, 100 and 120 ° C and three air flow of 0.5, 1 and 1.5 m/s and their impacts of on colored parameter (amounts R, G and B) have been studied. By using vision machine system, color images of the saffron dried petals were taken, and analyzed using image processing algorithms, Features colored (RGB) were also obtained. In addition, the anthocyanin content, (using differential pH method) and L*a*b* characteristics were measured in order to determine the proper drying conditions of the samples. The data were analyzed using factorial experiment based on randomized complete design. The results showed that maximum RGB values were at the temperature range of 80 to 100°C, representing the greatest ratio and intensity of red, green and blue colors. Also in this temperature range, the highest anthocyanin content (482.21mg/l) and lowest color changes (ΔE) were obtained which was a relative desirability of this range for drying saffron petals.

کلیدواژه‌ها [English]

  • Saffron
  • color changes
  • L * a * b *
  • vision machine
  • Anthocyanins
Aghaee, Z., Jafari, S, M., Ghorbani, M., and Hemmati, KH. 2014. Effect of different drying methods on anthocyanin extracted from saffron petals. 22 National Congress of Food Science and Technology. Gorgan University of Agricultural Sciences, 30-31 August 2014.  (In Persian).
Arabhosseini, A., Huisman, W., Van Boxtel, A., and Müller, J. 2007. Long-term effects of drying conditions on the essential oil and color of tarragon leaves during storage. Journal of Food Engineering 79: 561-566.
Arabhosseini, A ., Padhye, S., Huisman, W., van Boxtel, A., and Müller, J. 2011. Effect of drying on the color of tarragon (Artemisia dracunculus L.) leaves. Food and Bioprocess Technology 4: 1281-1287.
Basti, A.A., Moshiri, E., Noorbala, A.A., Jamshidi, A.H., Abbasi, S.H., and Akhondzadeh, S. 2007. Comparison of petal of Crocus sativus L. and fluoxetine in the treatment of depressed outpatients: a pilot double-blind randomized trial. Progress in Neuro-Psychopharmacology and Biological Psychiatry 31: 439-442.
Chen, Q., Zhang, D., Pan, W., Ouyang, Q., Li, H., Urmila, K., and Zhao, J. 2015. Recent developments of green analytical techniques in analysis of tea's quality and nutrition. Trends in Food Science and Technology 43: 63-82.
Du, C.-J., and Sun, D. W. 2005. Comparison of three methods for classification of pizza topping using different colour space transformations. Journal of Food Engineering 68: 277-287.
Fatehi, M., Rashidabady, T., and Fatehi Hassanabad, Z. 2003. Effects of Crocus sativus petals’ extract on rat blood pressure and on responses induced by electrical field stimulation in the rat isolated vas deferens and guinea-pig ileum. Journal of Ethnopharmacology 84: 199-203.
Gabel, M.M., Pan, Z., Amaratunga, K., Harris, L.J., and Thompson, J.F. 2006. Catalytic infrared dehydration of onions. Journal of Food Science 71: E351-E357.
Giusti, M.M., and Wrolstad, R.E. 2001. Characterization and measurement of anthocyanins by UV‐visible spectroscopy. Current Protocols in Food Analytical Chemistry. John Wiley and Sons, Inc
Hassini, L., Azzouz, S., Peczalski, R., and Belghith, A. 2007. Estimation of potato moisture diffusivity from convective drying kinetics with correction for shrinkage. Journal of Food Engineering 79: 47-56.
Heydari, S., Rezaeiii, R., and Haghayeghi, G.H. 2014. Effect of drying processes on stability of anthocyanin extracts from saffron petal. Evolving Trends in Engineering and Technology 2: 13-18.
Hemmati, A., Hosseini, K.D.,  and Rahimy, S.K. 1994. Search and anthocyanin extract of saffron petals Khorasan and stability in a beverage model, a research project, the Institute of Food Science and Technology, Mashhad.  (In Persian).
Hosseinzadeh, H., and Younesi, H.M. 2002. Antinociceptive and anti-inflammatory effects of Crocus sativus L. stigma and petal extracts in mice. BMC pharmacology 2 (7): 1472-2210.
Kafi, M. 2006. Saffron (Crocus sativus): Production and Processing. Science Publishers.
Larraín, R., Schaefer, D.,  and Reed, J. 2008. Use of digital images to estimate CIE color coordinates of beef. Food Research International 41: 380-385.
Lee, J., Durst, R.W., and Wrolstad, R.E. 2005. Determination of total monomeric anthocyanin pigment content of fruit juices, beverages, natural colorants, and wines by the pH differential method: collaborative study. Journal of AOAC International 88: 1269-1278.
Lee, J., Rennaker, C., and Wrolstad, R.E. 2008. Correlation of two anthocyanin
quantification methods: HPLC and spectrophotometric methods. Food Chemistry 110 (3):  786-782.
Maskan, M. 2001. Kinetics of colour change of kiwifruits during hot air and microwave drying. Journal of Food Engineering, 48: 169-175.
Mahdavi Khazaei, K., Jafari, S., Ghorbani, M., and Kakhki, A.H. 2016. Optimization of anthocyanins extraction from saffron petals with response surface methodology, Food Anal. Methods 9: 1993–2001.
Mahdavi Khazaei, N.B., Tavakoli, T., Ghassemian, H., Khoshtaghaza, M.H., and Banakar, A. 2013. Applied machine vision and artificial neural network for modeling and controlling of the grape drying process. Computers and Electronics in Agriculture 98: 205-21. (In Persian).
Mendoza, F., and Aguilera, J. 2004. Application of image analysis for classification of ripening bananas. Journal of Food Science 69:  E471–E477.
Mendoza, F., Dejmek, P., and Aguilera, J.M. 2006. Calibrated color measurements of agricultural foods using image analysis. Postharvest Biology and Technology 41: 285-295.
Nobbs, J., and Connolly, C. 2000. Camera-based colour inspection. Sensor Review 20: 14-20.
Shafiee, S., Minaei, S., Moghaddam-Charkari, N., and Barzegar, M. 2014. Honey characterization using computer vision system and artificial neural networks. Food Chemistry 159: 143-150.
Shahabi, M., Rafiee, S., Mohtasebi, S.S., and Hosseinpour, S. 2014. Image analysis and green tea color change kinetics during thin-layer drying. Food Science and Technology International 20: 465-476.
Sliwinska, M., Wisniewska, P., Dymerski, T., Namiesnik, J.,  and Wardencki, W. 2014. Food analysis using artificial senses. Journal of Agricultural and Food Chemistry 62: 1423-1448.
Stintzing, F.C., and Carle, R. 2004. Functional properties of anthocyanins and betalains in plants, food, and in human nutrition. Trends in Food Science and Technology 15: 19-38.
Taghadomi-Saberi, S., Omid, M., Emam-Djomeh, Z., and Ahmadi, H. 2013.Development of an intelligent system to determine sour cherry's antioxidant activityand anthocyanin content during ripening. International Journal of Food Properties 48-735-741.
Tahmasbpour, M., Dehghannia, G., Sayedlo haris, S.S., and Ghanbarzadeh, B. 2014. Modeling color changes during drying grapes are pre-treated with ultrasound and carboxymethyl cellulose and its organoleptic characteristics. Journal of Food Technologies 1: 61-79. (In Persian).
Williams, C.A., Harborne, J.B., and Goldblatt, P. 1986. Correlations between phenolic patterns and tribal classification in the family Iridaceae. Phytochemistry 25: 2135-2154.
Wlazly, A., and Targonski, Z. 2000. Polyphenol oxidase and beta-glucosidase in selected berry fruit. Journal of Zywnosc 7: 122-132.
Yagiz, Y., Balaban, M.O., Kristinsson, H.G., Welt, B.A., and Marshall, M.R. 2009. Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon. Journal of the Science of Food and Agriculture 89: 728-730.