شناسایی و تفکیک برنج خالص و ناخالص به کمک بینی الکترونیک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه محقق اردبیلی

2 دانشگاه محقق اردبیلی، اردبیل، ایران

10.22034/jess.2022.147669

چکیده

برنج به عنوان یکی از مهمترین محصولات زراعی دنیا، در سراسر جهان در بخش‌های وسیعی کشت می‌شود و غذای اصلی بیش از نیمی از مردم جهان است. لازمه تعیین و ارزیابی دقیق بو در برنج، شناسـایی مواد مؤثر در بو به موازات توسـعه روش‌هـای تعیـین مقدار آن‌هاست. بیش از 3 دهه از آغاز مطالعات مربوط به شناخت عوامل ایجاد کننده و مـؤثر در عطـر بـرنج می‌گـذرد. در این بین بینی الکترونیک می‌تواند ترکیبات فرار برنج را تشخیص دهد و ماشین بویایی می‌تواند کارایی بالا در طبقه‌بندی و تشخیص رقم، اصالت و مدت انبارداری داشته باشد. این پژوهش با هدف به کارگیری بینی الکترونیکی به همراه یکی از روش های کمومتریکس PCA به عنوان یک روش ارزان، سریع و غیر مخرب برای تشخیص ارقام اصلی و تقلبی برنج انجام شد. در این تحقیق از بینی الکترونیک مجهز به 9 سنسور نیمه هادی اکسید فلزی (MOS) با مصرف برق کم استفاده شد. بر اساس نتایج به دست آمدهPCA با دو مؤلفه اصلیPC1 و PC2، 99% واریانس مجموعه‌ی داده‌ها را برای نمونه‌های مورد استفاده توصیف کردند.

کلیدواژه‌ها


عنوان مقاله [English]

Recognition and classification of pure and adulterated rice using the electronic nose

نویسندگان [English]

  • Vali Rasooli Sharabiani 1
  • Ali Khorramifar 2
1 Department of Biosystem Engineering, Faculty of Agriculture,, University of Mohaghegh Ardabili
2 University of Mohaghegh Ardabili , Ardabil , Iran
چکیده [English]

Introduction
Annual herbaceous rice, standing, rooted, shallow, strong, and white, belongs to the Oryza family, belonging to the Oryzeae family. Rice is the staple food of about 2.5 billion people, which is about 20 percent of the energy needed, and provides protein for 15 percent of the world's population. In general, tropical and subtropical countries Burma, Thailand, Vietnam, Laos, Indonesia, Philippines, Pakistan, India, USA, Japan, Italy, Egypt, China, Brazil, Cuba, Mexico, and Australia are the main rice producers in the world. Among them, Sadri, Tarom, and Hashemi cultivars are among the best and most high-quality rice cultivars native to Iran, and the most productive cultivars of this country can be Caspian, Speedroad, Sahel, Kadous, Shafaq, Darfak, Gohar and Neda pointed out. Accurate determination and evaluation of odor in rice require identification of substances affecting odor in parallel with the development of methods for determining their amount. More than 3 decades have passed since the beginning of studies related to recognizing the creative and effective factors in rice aroma. Much research has been done in the field of using more efficient and faster methods in identifying rice volatiles and identifying the main causes. Of the more than 100 known compounds in rice, a few are effective in creating its aroma and aroma. In the meantime, the electronic nose can detect volatile compounds in rice. The electronic nose has been used in extensive research to identify and classify food and agricultural products. Pandan leaf aroma of rice is a special feature and is used to differentiate the quality of rice. Quality determines whether it has a certain percentage of cleanliness and purity or not. Aromatic rice is usually preferred by consumers due to its good quality, which includes delicacy, shape, colour, aroma, taste, and consumers use aromatic rice for celebrations and occasions due to high demand and use good quality. The quality of aromatic rice is influenced by various factors such as cultivation location, climatic conditions, genetic activities and post-harvest. Important issues in the rice industry include quality control, incorrect labelling, grading and fraud in different types of rice. For this reason, the rice industry uses standard grades based on market criteria to identify grain. Due to these factors, quality control and fraud are the main issues that are wrong labelling and grading are the main problems. The use of human expert panels is the most common technique used to evaluate the quality of aromatic rice. They distinguish rice based on its aroma. With the rapid and rapid advancement of computer technology and sensor technology, the application of the bionic electronic nose, including a semiconductor gas-sensitive sensor and a pattern recognition system as a means of detection, offers a new method for rapid classification and digit recognition. Give. The electronic nose has also introduced a new method for classifying and detecting rough rice in a non-destructive and fast way. The aim of this study was to evaluate the ability and accuracy of the electronic noses using one of the chemometrics methods to distinguish pure rice cultivars from 3 gross cultivars.

Methodology
First, 4 rice cultivars were prepared from the Iranian Rice Research Center located in Rasht. These 4 cultivars included 1 high-quality rice cultivar named Hashemi and 3 substandard rice cultivars named Neda, Khazar, and Sahel. Therefore, in the experiments, one genuine rice cultivar (Hashemi) and three non-genuine or counterfeit cultivars (mixture of Caspian, Neda, and Sahel cultivars with Hashemi cultivars) were prepared, so that the counterfeit cultivars each contained 80% of Hashemi cultivars and 20% of substandard cultivars. After preparing and mixing the cultivars, first, the samples were placed in a closed container (sample container) for 1 day to saturate the container with the aroma of rice, then the sample containers were used for data collection with an electronic nose. Were located. In this research, an electronic nose made in the Department of Biosystem Engineering of Mohaghegh Ardabili University was used. In this device, 9 low-power metal oxide (MOS) semiconductor sensors are used, which are given in Table 1 of the sensor specifications. The sample chamber was connected to the electronic nasal device and data collection was performed. The data collection was done by first passing clean air through the sensor chamber for 150 seconds to clear the sensors of odours and other gases. The sample odor was then sucked out of the sample chamber by the pump for 150 seconds and directed to the sensors, and finally, fresh air was injected into the sensor chamber for 150 seconds to prepare the device for repetition and subsequent tests. 22 replicates were considered for each sample. The study started with the chemometrics method with principal component analysis (PCA) to detect the output response of the sensors and reduce the data dimension. Principal component analysis (PCA) is one of the simplest multivariate methods and is known as an unsupervised technique for clustering data by groups. It is usually used to reduce the size of the data and the best results are obtained when the data are positively or negatively correlated. Another advantage of PCA is that this technique reduces the size of multidimensional data while eliminating additional data without losing important information.

Conclusion
The scores diagram (Figure 1) showed the total variance of the data equal to PC-1 (99%) and PC-2 (0%), respectively, and the first two principal components constitute 99% of the total variance of the normalized data. When the total variance is greater than 90%, it means that the first two PCs are sufficient to explain the total variance of the data set. According to the shape of Hashemi's main cultivar (a) on the left side of the chart and 3 fake cultivars (b, c, and d) are visible, which are well separated by the PCA method. Therefore, it can be concluded that e-Nose has a good response to rice odor and it is possible to distinguish between original and counterfeit rice cultivars, which shows the high accuracy of electronic nose in detecting the smell of different products. The correlation loadings plot diagram can show the relationships between all variables. The loading diagram (Figure 2) shows the relative role of the sensors for each principal component. The inner ellipse represents 50% and the outer ellipse represents 100% of the total variance of the data. The higher the loading coefficient of a sensor, the greater the role of that sensor in identifying and classifying. Therefore, sensors mounted on the outer circle have a greater role in data classification. According to the figure, it is clear that all sensors have played an important role in identifying rice cultivars, including the role of sensors No. 1 and 9, which are the same sensors MQ9 (to detect carbon dioxide, combustible gases) and MQ3 (to detect). Alcohol, methane, natural gases) were slightly less than the other sensors, which can be reduced by removing these two sensors to reduce the cost of making the olfactory device (to detect genuine and counterfeit rice) and save costs. In this study, an electronic nose with 9 metal oxide sensors was used to identify and distinguish between original and counterfeit rice cultivars. PCA chemometrics method for qualitative and quantitative analysis of complex data, an electronic sensor array was used. PCA was used to reduce the data and with 99 main components PC1 and PC2, it described 99% of the variance of the data set and provided a preliminary classification. The electronic nose has the ability to be used and exploited as a fast and non-destructive method to detect genuine and counterfeit rice cultivars. Using this method in identifying rice cultivars will be very useful for consumers, especially in restaurants and halls, in order to select pure and high-quality cultivars.

کلیدواژه‌ها [English]

  • rice
  • chemometrics
  • Purity
  • electronic nose