การศึกษาพฤติกรรมการอบแห้งและการประเมินค่าสีของพริกที่อบแห้งภายในตู้อบแห้งแบบหลายชั้นด้วยเทคนิคการประมวลผลภาพ
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Abstract
Abstract
This paper presents the behavior of chilli drying and the application of image processing technology for analyzing and evaluating color changes of chilli during drying process and the consistency of color in those dried chilli in the multi-layers hot air cabinet dryer. During the experiments, the ambient air was passing through the air heater channel under the condition of constant heat flux at 800 W/m2 using two different air flow velocities namely 2.0 and 4.0 m/s. In addition, the influence of the turning on the heating lamp sets 1, 2, 3 and 4 was used as an auxiliary heating devices and affected the location of the chilli in the cabinet was investigated. The result illustrated that the best drying method occurred when turning on 4 sets of heating lamps at 2.0 m/s of hot air velocity using 8 hours of drying time to reduce the moisture content to less than 13% wet basis. The dried chilli product has an average red, green and blue color were 219, 96 and 65 respectively, and the standard deviations were 13, 16 and 14, respectively.
Keywords: color changes; image processing; chili drying; drying behavior
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References
[2] Kadam, M.D. and Samuel, D.V.K., 2006, Convective flat-plate solar heat collector for cauliflower drying, Biosyst. Eng. 93: 189-198.
[3] Nourhene, B., Mohammed, K. and Nabil, K., 2008, Experimental and mathematical investigations of convective solar drying of four varieties of olive leaves, Food Bioprod. Process. 86: 176-184.
[4] Fudholi, A., Sopian, K., Alghou,l M.A., Ruslan, M.H. and Othman, M.Y., 2015, Performances and improvement potential of solar drying system for palm oil fronds, Renew. Energ. 78: 561-565.
[5] Dina, S.F., Ambarita, H., Napitupulu, F.H. and Kawai, H., 2015, Study on effectiveness of continuous solar dryer integrated with desiccant thermal storage for drying cocoa beans, Case Stud. Therm. Eng. 5: 32-40.
[6] Fudholi, A., Sopian, K., Othman, M.Y. and Ruslan, M.H., 2015, Energy and exergy analyses of solar drying system of red seaweed, Energ. Buildings. 68: 121-129.
[7] Gulcimen, F., Karakaya, H. and Durmus, A., 2016, Drying of sweet basil with solar air collectors, Renew. Energ. 93: 77-86.
[8] Wang, W., Li, M., Hassanien, R.H.E, Wang, Y. and Yang, L., 2018, Thermal performance of indirect forced convection solar dryer and kinetics analysis of mango, Appl. Therm. Eng. 134: 310-321.
[9] Lingayat, A., Chandramohan, V.P. and Raju, V.R.K., 2017, Design, development and performance of indirect type solar dryer for banana drying, Enrgy. Proced. 109: 409-416.
[10] ปราณี อ่านเปื่อง, 2544, หลักการวิเคราะห์อาหารด้วยประสาทสัมผัส, พิมพ์ครั้งที่ 3, สำนักพิมพ์แห่งจุฬาลงกรณ์มหาวิทยาลัย, กรุงเทพฯ, 343 น.
[11] สักกมน เทพหัสดิน ณ อยุธยา, 2555, การอบ แห้งอาหารและวัสดุชีวภาพ, สำนักพิมพ์ท้อป, กรุงเทพฯ, 324 น.
[12] Nadian, M.H, Rafiee, S., Aghbashlo, M., Hosseinpour, S. and Mohtasebi, S.S., 2015, Continuous real-time monitoring and neural network modeling of apple slices color changes during hot air drying, Food Bioprod. Process. 94: 263-274.
[13] 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, Comput. Electron. Agr. 98: 205-213.
[14] Manninen, H., Paakki, M., Hopia, A. and Franzen, R., 2015, Measuring the green color of vegetables from digital images using image analysis, LWT-Food Sci. Technol. 63: 1184-1190.
[15] Liming, X. and Yanchao, Z., 2010, Automated strawberry grading system based on image processing, Comput. Electron. Agr. 71S: S32-S39.
[16] Amjad, W., Crichton, S.O.J., Munir, A., Hensel, O. and Sturm, B., 2018, Hyper spectral imaging for the determination of potato slice moisture content and chromaticity during the convective hot air drying process, Biosyst. Eng. 166: 170-183.
[17] Huang, M., Wanga, Q., Zhang, M. and Zhu, Q., 2014, Prediction of color and moisture content for vegetable soybean during drying using hyperspectral imaging technology, J. Food Eng. 128: 24-30.
[18] ธานินทร์ ศิลป์จารุ, 2557, การวิจัยและวิเคราะห์ข้อมูลทางสถิติด้วย SPSS และ AMOS, พิมพ์ครั้งที่ 15, สำนักพิมพ์ซีเอ็ดยูเคชั่น, กรุงเทพฯ, 576 น.