بهینه سازی فرآیند برشته کردن تخمه آفتابگردان در دستگاه برشته‌کن سیلندری با استفاده از سامانه‌های حسگری

نوع مقاله : مقاله پژوهشی

نویسندگان

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

2 گروه مهندسی مکانیک بیوسستم، دانشکده کشاورزی، دانشگاه شهرکرد- ایران

3 گروه مهندسی مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه رازی، کرمانشاه، ایران

چکیده

برشته کردن یک فرآیند حرارتی است و عوامل مختلفی از جمله دما و مدت زمان برشته کردن نقش مهمی در خصوصیات بافتی و حسی محصول دارند. در این تحقیق یک دستگاه برشته‌‌کن برای فرآیند برشته کردن تخمه آفتابگردان طراحی و ساخته شد. با استفاده از بینی الکترونیک، بو و رایحه حاصل از فرآیند برشته شدن نمونه‌‌ها بررسی و با استفاده از روش سطح پاسخ (طرح مرکب مرکزی) در محدوده دمایی 80 تا 160 درجه سلسیوس و محدوده زمانی 10 تا 30 دقیقه بهینه‌‌یابی شد. پاسخ حسگرهای بینی الکترونیک، پارامترهای رنگی شامل (L*، a*، b*، ΔE، BI) و ارزیابی حسی برای توسعه مدل‌‌های پیشگویی و بهینه‌‌سازی فرآیند برشته کردن تخمه آفتابگردان مورد استفاده قرار گرفت. نتایج نشان داد که افزایش دما و مدت زمان برشته‌‌کردن بر روی پاسخ حسگرهای بینی الکترونیک تأثیر معنی‌‌داری دارد. با افزایش دما و مدت زمان برشته شدن مقدار L* روند کاهشی داشت اما a*، b*، ΔE و BI روند افزایشی داشتند، همچنین بیشترین مقدار پذیرش کلی ارزیابان برای نمونه‌‌ی با دمای 120 درجه سلسیوس و مدت زمان 20 دقیقه حاصل شد. نقطه بهینه برای برشته کردن تخمه آفتابگردان با دستگاه ساخته شده دمای 116 درجه سلسیوس و مدت زمان 18 دقیقه به دست آمد. نتایج حاصل از تحقیق نشان دهنده کارایی مفید دستگاه ساخته شده بود و برای مدل‌‌های ارائه شده به روش سطح پاسخ برای پیش‌‌بینی مقادیر متغیرهای وابسته، نتایج بسیار نزدیکی با یافته‌‌های آزمایش به دست آمد. در تمامی ارقام مورد مطالعه (05/0<P) بود که نشان دهنده مناسب بودن مدل‌‌های پیشنهادی بود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Optimizing the sunflower seed roasting process in a cylindrical roaster using instrumental systems

نویسندگان [English]

  • Emad امیری 1
  • Mahdi Ghasemi-Varnamkhasti 1
  • Mojtaba Naderi-Boldaji 2
  • Zahra Izadi 1
  • Esmaeil Mirzaee Ghaleh 3
1 1- Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran
2 Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran
3 5- Department of Mechanical Engineering of Biosystems, Faculty of Agriculture, Razi University, Kermanshah, Iran
چکیده [English]

Roasting is a thermal process and various factors such as temperature and duration of roasting play an important role in the textural and sensory properties of the product. In this research, a roasting machine was designed and fabricated for the process of roasting sunflower seeds. Using an electronic nose, the aroma resulting from the roasting process of the samples were investigated and optimized using the response surface method (Central Compound Design) in the temperature range of 80 to 160 degrees Celsius and the time range of 10 to 30 minutes. The response of electronic nose sensors, color parameters including (L*, a*, b*, ΔE, BI) and sensory evaluation were used to develop prediction models and optimize sunflower seed roasting process. The results showed that increasing the temperature and duration of roasting has a significant effect on the response of electronic nose sensors. With increasing temperature and duration of roasting, the value of L* decreased, but a*, b*, ΔE and BI increased, and the highest overall acceptance value of the human panelist was obtained for the sample with a temperature of 120 degrees Celsius and a duration of 20 minutes. The optimum point for roasting sunflower seeds with the fabricated system was 116 degrees Celsius and a duration of 18 minutes. The results of the research showed the useful efficiency of the fabricated system and for the models presented by the response surface method for predicting the values of the dependent variables, the results were very near to the experimental findings. It was (P<0.05) in all the studied values, which indicated the suitability of the proposed models.

کلیدواژه‌ها [English]

  • Color Parameters
  • Electronic Nose
  • Response Surface Method
  • Roasting
  • Sunflower Seeds

Optimizing the sunflower seed roasting process in a cylindrical roaster using instrumental systems

 

EXTENDED ABSTRACT

Introduction

Sunflower seeds are one of the most popular and widely consumed nuts among nut products, which have a variety of nutrients. Sunflower seeds can be used as raw or roasted. Roasting is a thermal process in which various factors such as roasting method, temperature and duration of roasting play an important role in the texture and sensory characteristics of the product. The high quality of nut products is a basic requirement for consumers. The method of checking and optimizing the process in optimal roasting of nuts and nut products is of great importance. The purpose of this study was to design and fabricate a sunflower seed roasting machine and check and optimize the roasting process with an electronic nose device, color parameters and sensory evaluation using the response surface method.

Materials and methods

In this research, a roasting machine was designed and fabricated using the heat transfer method for roasting sunflower seeds. Using an electronic nose, the aroma resulting from the roasting process of the samples were evaluated. The roasting process was optimized using the Response Surface Method (Central Composite Design) in the temperature range of 80 to 160 degrees Celsius and the time range of 10 to 30 minutes. Response of electronic nose sensors, color parameters including L* (brightness index), a* (redness index), b* (yellowness index), ΔE (overall color change), BI (browning index) and sensory evaluation were considered. The response surface method was used to develop predictive models and optimize the sunflower seed roasting process.

Results and discussion

The results showed that both the factors of temperature and duration of roasting had a significant effect on the response of the electronic nose sensors and the color parameters of the samples, but for sensory evaluation the effect of the factor of duration of roasting was not significant and the interaction of temperature and duration of roasting and their quadratic term had the greatest effect. Increasing the temperature and duration of roasting has a significant effect on the response of electronic nose sensors. With increasing temperature and duration of roasting, the value of L* decreased, but a*, b*, ΔE and BI increased, the average of each of these variables was 83.79, 6.99, 5.13, 21.58 and 2.93, respectively. For the sensory evaluation of roasted sunflower seeds, the interaction effect and the quadratic expression of temperature and roasting time had a very significant effect (P<0.001). the highest score of sensory properties was obtained for the sample at 120°C and a duration of 20 minutes. the results of variance analysis showed that the response of electronic nose sensors, color parameters and sensory evaluation of the samples can be used to check and control the sunflower seed roasting process in the roaster fabricated. The optimal point for roasting sunflower seeds was 116 degrees Celsius and a duration of 18 minutes. In optimal conditions, the roasting operation was performed in three repetitions and the results related to the responses of the dependent variables were compared with the predicted values ​​of the model. In all studied values, it was (P<0.05), which indicates the appropriate models and accuracy of optimization.

Conclusion

The results of the research showed the useful efficiency of the roasting machine. The lack of fit test for all the models obtained from the response level method for the dependent variables was not significant, which indicated the appropriateness of the presented models, and for the models presented to predict the values of the dependent variables. The result was very close to the experimental findings.

 

مراجع

AOAC. (1990). Official methods analyses th Ed., Association of official 14 analytical chemists: Washington. DC. USA.
ASAE. (2000). ASAE Standard S352.2: Moisture measurement-unground grain and kernels in ASAE standards 2000. St. Joseph, MI.
Banerjee, S., & Shrivastava, S. L. (2018). Design and development of mini roaster for cashew nut processing. Journal of Food Process Engineering, 41(1), e12604.
Barea-Ramos, J. D., Cascos, G., Mesías, M., Lozano, J., & Martín-Vertedor, D. (2022). Evaluation of the olfactory quality of roasted coffee beans using a digital nose. Sensors, 22(22), 8654.
Brosnan, T., & Sun, D. W. (2002). Inspection and grading of agricultural and food products by computer vision systems a review. Computers and Electronics in Agriculture, 36(2-3), 193-213.
Butz, P., Hofmann, C., & Tauscher, B. (2005). Recent developments in non-invasive techniques for fresh fruit and vegetable internal quality analysis. Journal of Food Science .70: 131–134.
Cai, J. S., Zhu, Y. Y., Ma, R. H., Thakur, K., Zhang, J. G., & Wei, Z. J. (2021). Effects of roasting level on physicochemical, sensory, and volatile profiles of soybeans using electronic nose and HS-SPME-GC–MS. Journal Food Chemistry, 340, 127880.
Chung, H. S., Kim, J. K., Moon, K. D., & Youn, K. S. (2014). Changes in color parameters of corn kernels during roasting. Food Science and Biotechnology, 23, 1829-1835.
Ghasemi-Varnamkhasti, M., Mohtasebi, S. S., Siadat, M., Lozano, J., Ahmadi, H., Razavi, S. H., & Dicko, A. (2011). Aging fingerprint characterization of beer using electronic nose. Sensors and Actuators B: Chemical, 159(1), 51-59.
Goszkiewicz, A., & Kołodziejczyk, E. (2020). Comparison of microwave and convection method of roasting sunflower seeds and its effect on sensory quality, texture and physicochemical characteristics. Food Structure, 25, 100144.
Hojjati, M., Calín‐Sánchez, Á., Razavi, S. H., & Carbonell‐Barrachina, Á. A. (2013). Effect of roasting on colour and volatile composition of pistachios (P istacia vera L.). International Journal of Food Science & Technology, 48(2), 437-443.
Jia, W., Liang, G., Jiang, Z., & Wang, J. (2019). Advances in electronic nose development for application to agricultural products. Food Analytical Methods, 12(10), 2226-2240.
Kahyaoglu, T. (2008). Optimization of the pistachio nut roasting process using response surface methodology and gene expression programming. LWT-Food Science and Technology, 41(1), 26-33.
Kita, A., & Figiel, A. (2007). Effect of roasting on properties of walnuts. Pol. J. Food Nut. Sci., 57(2), 89- 94.
Kong, F., & Singh, R. P. (2009). Digestion of raw and roasted almonds in simulated gastric environment. Food Biophysics, 4, 365-377.
Kumar, S., Debnath, S., & Hebbar, U. H. (2009). Pulsed infrared roasting of groundnuts and its quality. International Journal of Food Engineering, 5(4).
Leon, K., Mery, D., Pedreschi, F., & Leon, J. (2006). Color measurement in L∗ a∗ b∗ units from RGB digital images. Food research international, 39(10), 1084-1091.
Liu, Z., Wang, W., Huang, G., Zhang, W., & Ni, L. (2016). In vitro and in vivo evaluation of the prebiotic effect of raw and roasted almonds (Prunus amygdalus). Journal of the Science of Food and Agriculture, 96(5), 1836-1843.
Loutfi, A., Coradeschi, S., Mani, G. K., Shankar, P., & Rayappan, J. (2015). Electronic noses for food quality: A review. Journal of Food Engineering, 144, 103-111.
Marzocchi, S., Pasini, F., Verardo, V., Ciemniewska-Zytkiewicz, H., Caboni, M. F., & Romani, S. (2017). Effects of different roasting conditions on physical-chemical properties of Polish hazelnuts (Corylus avellana L. var. Kataloński). LWT-Food Science and Technology, 77, 440-448.
Maskan, M. (2001). Kinetics of colour change of kiwifruits during hot air and microwave drying. Journal of food engineering, 48(2), 169-175.
Olaniyan, A. M., Karim, O. R., Emmanuel, O., & Eromosele, E. O. (2017). Design and development a small-scale peanut roaster. The Journal of the Association of Professional Engineers of Trinidad and Tobago, 45(2), 34-39.
Ozdemir, M. (2001). Mathematical Analysis of Color Changes and Chemical Parameters of Roasted Hazelnuts (PhD Thesis), stanbul Technical University. Institute of Science and Technology, Department of Food Engineering, Istanbul.
Salehi, F., Kashaninejad, M., Asadi, F., & Najafi, A. (2016). Improvement of quality attributes of sponge cake using infrared dried button mushroom. Journal of food science and technology, 53, 1418-1423.
Schlormann, W., Birringer, M., Bohm, V., Lober, K., Jahreis, G., Lorkowski, S., & Glei, M. (2015). Influence of roasting conditions on health-related compounds in different nuts. Food Chemistry, 9, 77-85.
Shakerardekani, A., Karim R, Mohd Ghazali, H., & Chin, N. L. (2011). Effect of roasting conditions on hardness, moisture content and colour of pistachio kernels. International Journal Food Research, 18, 723-729.
Shi, X., Davis, J. P., Xia, Z., Sandeep, K., Sanders, T. H., & Dean, L. O. (2017). Characterization of peanuts after dry roasting, oil roasting, and blister frying. LWT-Food Science and Technology, 75, 520-528.
Soleimanieh, S. M., Eshaghi, M., & Vanak, Z. P. (2015). The effect of roasting method and conditions on physic chemicals and sensory properties of sunflower seed kernels. International Journal of Biosciences, 6(7), 7-17.
Tenyang, N., Ponka, R., Tiencheu, B., Tonfack Djikeng, F., & Womeni, H. M. (2022). Effect of boiling and oven roasting on some physicochemical properties of sunflower seeds produced in Far North, Cameroon. Food Science & Nutrition, 10(2), 402-411. 
Tohidi, M., Ghasemi-Varnamkhasti, M., Ghafarinia, V., Bonyadian, M., & Mohtasebi, S. S. (2018). Development of a metal oxide semiconductor-based artificial nose as a fast, reliable and non-expensive analytical technique for aroma profiling of milk adulteration. International dairy journal, 77, 38-46.
Yam, K.L., & Papadakis, S. E., 2004. A simple digital imaging method for measuring and analyzing color of food surfaces. Journal of Food Engineering, 61, 137-142.
مهندسی بیوسیستم ایران
دوره 54، شماره 4
دی 1402
صفحه 1-17

فایل ها

سابقه مقاله

  • تاریخ دریافت: 28 فروردین 1403
  • تاریخ بازنگری: 24 خرداد 1403
  • تاریخ پذیرش: 04 تیر 1403

هم رسانی

ارجاع به این مقاله

آمار