نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، گروه مهندسی مکانیک بیوسیستم، دانشگاه رازی، کرمانشاه، ایران

2 دانشجوی دکتری ، گروه مهندسی مکانیک بیوسیستم ، دانشگاه محقق اردبیلی، اردبیل، ایران

3 دانشیار، گروه مهندسی مکانیک بیوسیستم ، دانشگاه محقق اردبیلی، اردبیل، ایران

10.22055/agen.2024.45563.1704

چکیده

نان به عنوان مهم‌ترین منبع کالری و پروتیئن در تغذیه کشور نقش و اهمیت خاصی دارا می‌باشد و ارزان بودن آن سبب شده است که در سال‌های اخیر جانشین سایر مواد خوارکی در جیره غذایی گردد. نان مسطح بیشترین آمار مصرف را بـین نان‌هـای دیگـر در ایران را به خود اختصاص داده است. نان بربری دومـین نان پرمصرف پس از نان لـواش در ایران است. بنابراین سلامت و کیفیت نان بربری مصرفی از اهمیت ویژه‌ای برخوردار است. به همین منظور این مطالعه با هدف بررسی اثر دما بر زمان نگهداری نان‌ بربری براساس ویژگی بو با استفاده از سامانه ماشین بویایی انجام شد. بردار ویژگی‌ها از سیگنال پاسخ حسگرها به ترکیبات فرار و بوی نان بربری، استخراج و به‌ عنوان ورودی مدل تشخیص الگو استفاده شد. برای طبقه‌بندی ویژگی‌های استخراج ‌شده از روش‌ تحلیل تفکیک خطی (LDA) و تحلیل تفکیک درجه دوم (QDA) استفاده شد. نتایج تحلیل مؤلفه‌های اصلی با دو مؤلفه‌ی PC1 و PC2، برای نان بربری در دمای اتاق (داخل سفره و داخل نایلون)، دمای یخچال و دمای فریزر به ترتیب 95، 90، 86 و 85 درصد به دست آمد. نتایج به‌دست آمده از تحلیل QDA برای تشخیص کیفیت نان بربری در دمای °C 4 به مدت 9 روز، در دمای اتاق (داخل نایلون و داخل سفره) به مدت5 روز و در دمای فریزر (°C 18-) به مدت 15 روز نگهداری به ترتیب با دقت طبقه بندی 52/98، 96، 100 و 35/97 درصد به دست آمد. نتایج تحلیل LDAبرای سیگنال‌های حاصل از ماشین بویایی، در طبقه‌بندی مدت نگهداری نان بربری در دمای یخچال، دمای اتاق (داخل سفره و داخل نایلون) و دمای فریزر به ترتیب با دقت طبقه بندی 26/79، 33/85، 67/78 و 22/75 درصد حاصل شد. براساس نتایج نمودارهای خطی لودینگ و نمودار رادار، بوی نان بربری بیش‌ترین و کم‌ترین تأثیر را به ترتیب بر روی حسگر MQ9 و حسگر TGS813 دارد. نمودار رادار نشان داد که حسگر MQ9 در میان حسگرهای دیگر، بیشترین نقش را در طبقه‌بندی داشت.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The effect of storage time of Barbari bread on the odor characteristic using olfactory machine system

نویسندگان [English]

  • Esmaeil Mirzaee- Ghaleh 1
  • Fardin Aayri Samlhe 2
  • Amir Hossein Afkari Sayyah 3

1 Associate Professor, Mechanical Engineering of biosystems Department, Faculty of Agriculture, Razi University, Kermanshah, Iran

2 PhD Student, Mechanical Enginnering of Biosystems Department, Faculty of Agriculture, University of Mohaghegh Ardabili , Ardabil-Iran

3 Associate Professor, Mechanical Engineering of Biosystems Department, Faculty of Agriculture, University of Mohaghegh Ardabili, Ardabil, Iran

چکیده [English]

Introduction As the most important source of calories and protein, bread has a special role and importance in the nutrition of the country, and its cheapness has caused it to replace other food items in the diet in recent years. The increase in bread consumption in the low-income and vulnerable groups has been more intense due to the low volume of supply of other food products and the excessive and continuous increase in the price of other alternative products. Flat bread has the highest consumption statistics among other breads in Iran. One of their types is Barbari bread, which is the second most consumed bread after lavash bread in Iran. Therefore, the health and quality of consumed Barbari bread is of particular importance. For this purpose, this study was conducted with the aim of the effect of storage time of Barbari bread based on the characteristic of smell using the olfactory machine system based on eight metal oxide semiconductor sensors.
Materials and Methods An odor machine system based on eight MOS sensors was carried out in order to investigate the effect of bread storage time based on odor characteristics. Designed system includes data acquisition system, sensors, shield of sensors, sample container, power supply, connections, electric valves, air pump and air filter. The sensor array was consisted of the 8 MOS sensors that each one reacts to specific volatile compounds. These sensors are widely used in olfactory machines because of their high chemical stability, high durability, low response to moisture and affordable prices. These are the most commonly used sensors in electronic nose system. Sensors are the main components of an electronic nose system therefor it is necessary to select the able sensors to detect differences among samples. In order to carry out the test, the sample was placed in sample container and in the baseline correction step (150 seconds), clean air was passed through the sensors to transmit the response of sensor array to steady state. At the injection step (180 seconds), the sample headspace was transmitted and passed through sensors chamber. Output voltage of each sensor depends on the type of sensor and its sensitivity. At the cleaning step (150 seconds) the clean air was passed through sensors to get the sensor array responsive to a stable state. Also, at this step the pump removed the odor remaining inside the sample container and system is prepared for the next test. The signals obtained from the sensors were recorded and then pre-processed.
Results and Discussion The olfactory machine system based on eight metal oxide semiconductor (MOS) sensors was investigated with the PCA pattern recognition method due to the storage time of Barbari bread at four different temperatures. The data obtained from the signals processing with fractional method were used as input of PCA. The results of principal component analysis with two components PC1 and PC2 are 95, 90, 86 and 85%, respectively, for Barbari bread that is stored at room temperature (in the table), refrigerator temperature (4°C), room temperature (in foil) And the temperature of the freezer was placed, it showed. The results obtained from the QDA analysis to determine the quality of Barbari bread at 4 °C for 9 days, at room temperature (in foil) and (on the table) for 5 days and Barbari bread at the freezer temperature of the refrigerator (-18 °C) for 15 days of storage with classification accuracy of 98.52, 96, 100 and 97.35% respectively. The results of LDA analysis for the signals obtained from the olfactory machine, in the classification of the duration of storage of Barbari bread at refrigerator temperature, room temperature (in the table), room temperature (in foil) and refrigerator freezer temperature, respectively, with classification accuracy of 79.26 and 85.33, 78.67 and 75.22 percent were obtained. Also, according to the output obtained from the loading linear graphs and the radar graph, the smell of Barbari bread has the most and the least effect on the MQ9 sensor and the TGS813 sensor, respectively
Conclusion. An olfactory machine system based on eight metal oxide semiconductor (MOS) sensors was investigated for the Barbari bread time retention effect at four different temperatures. The results of principal component analysis with two components PC1 and PC2, for Barbari bread at room temperature (the table), refrigerator temperature, room temperature (in foil) and It showed that they were exposed to freezing temperatures. The results obtained from QDA analysis to detect the quality of Barbari bread at 4°C in room temperature (in foil) and (in the table) and refrigerator freezer temperature respectively. The results of LDA analysis for the classification of Barbari bread at refrigerator temperature, room temperature (in the table), room temperature (in foil) and freezer temperature of the refrigerator. The was obtained. Also, according to the output obtained from the loading linear graphs and the radar graph, the smell of Barbari bread has the most and the least effect on the MQ9 sensor and the TGS813 sensor, respectively.

کلیدواژه‌ها [English]

  • Barbari bread
  • Olfactory machine
  • Sensor
  • Classification
  • Odor
  • Temperature