کاربرد بینی الکترونیک در طبقه بندی فلفل خوراکی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی بیوسیستم، دانشکده کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران

2 گروه مهندسی مکانیک بیوسیستم، دانشگاه رازی، کرمانشاه، ایران

3 استاد دانشکده کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل

4 گروه مهندسی بیوسیستم، دانشگاه محقق اردبیلی، اردبیل، ایران

10.22034/jess.2022.333771.1745

چکیده

در بازارهای میوه و تره بار جوامع مدرن، به طور تقریبی تمامی میوه ها و سبزی ها به صورت سورت و لیبل گذاری شده عرضه می شوند و این امر سبب تشخیص آسان تر کیفیت محصول توسط مشتری شده و توزیع و عرضه منظم تری را به دنبال خواهد داشت، که این امر سبب تسهیل بسته بندی اولیه و حمل و نقل محصول نیز شده و ارزش افزوده بیشتری نصیب کشاورزان خواهد کرد. بنابراین، توسعه ماشین های سورتینگ متناسب با سطح تکنولوژی موجود که از نظر قیمت نهایی ماشین مقرون به صرفه بوده و کاربرد آن آسان باشد، الزامی و ضروری است. با توجه به نوظهور بودن فن آوری بینی الکترونیک می توان از آن در سیستم های کنترل کیفی مواد غذایی استفاده نمود. در این پژوهش فلفل پادرون(Padrón) با نام علمی Capsicum annuum L. تهیه شده و مورد ارزیابی قرار میگیرد. در میان هر 20 میوه یکی از آن ها تند است و بقیه طعم ملایمی دارند. در این پژوهش برای طبقه بندی فلفل های شیرین و تند از روشهای PCA، QDA و MDA استفاده شد. روش PCA بر حسب دو مولفه اول 96 درصد واریانس داده ها را تشخیص داد. در روش های QDA و MDA دقت طبقه بندی برابر 100 درصد به دست آمد. این روش به عنوان یک راه کاری مطمئن برای تفکیک فلفل های شیرین از تند به کمک پارامتر بو میتواند مورد توجه و بررسی قرار گیرد و برای اولین بار بر حسب ویژگی بو ماشین های سورتینگ توسعه داده شوند

کلیدواژه‌ها


عنوان مقاله [English]

Application of electronic nose in the classification of edible peppers

نویسندگان [English]

  • Mansour Rasekh 1
  • Hamed Karami 2
  • Yousef Abbaspour-Gilandeh 3
  • mansour ahmadi-pirlou 4
1 University of Mohaghegh Ardabili, Ardabi, Iran
2 Mechanical engineering of biodystems, Razi university, Kermanshah, Iran
3 Professor, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
4 Department of Biosystem Engineering, University of Mohaghegh Ardabili , Ardabil, Iran
چکیده [English]

Abstract
Introduction
Pepper (Capsicum annuum L.) is one of the most consumed vegetables in the world, containing a large amount of vitamins C and A, as well as minerals. Therefore, the consumption of about 60 to 80 g of pepper per day can provide 100 and 25% of the recommended daily amount of vitamin C and A, respectively. In addition, this horticultural product contains considerable levels of other health-promoting substances with antioxidant activity, including carotenoids, flavonoids, and other polyphenols.
The quality of fresh pepper depends primarily on consumer acceptance, which is determined primarily by color, pungency, and aroma. Aroma plays an essential role in determining the sensory characteristics of these products. Volatile organic compounds (VOCs) are generally associated with the taste and aroma of foods and are important factors in assessing consumer acceptance or rejection. Consequently, food quality, originality, purity, and origin can be evaluated by determining VOC.
Because it is important to distinguish hot peppers from sweet ones, we used an electronic nose to determine food quality in this study. Research has shown that the electronic nose is able to discriminate between products.

Methodology
The variety used in this study was Padrón, a very popular species in Spain. The peppers can be harvested when they reach a length of 2.5 to 4 cm. One fruit out of 20 has a spicy flavor, while the rest has a mild taste. The green fruits showed no signs of ripening or discoloration and remained completely green.
The peppers weighed an average of 12 ± 2 g when fresh. The weights for the sweet and spicy varieties were determined by weighing 30 fruits each. The fruits to be examined were evaluated by electronic nose.
In this research, an electronic nose made in the Department of Biosystem Engineering of Mohaghegh Ardabili University was used. This device uses 9 low-power metal oxide (MOS) semiconductor sensors.
The sample chamber was connected to the electronic nose and data collection was performed. The data collection was done by first passing clean air through the sensor chamber for 100 seconds to clear the sensors of odors and other gases. The sample odor was then sucked out of the sample chamber by the pump for 100 seconds and directed to the sensors, and finally fresh air was injected into the sensor chamber for 100 seconds to prepare the device for repetition and subsequent tests. 30 replicates were considered for each sample.
The study began with the chemometrics method with principal component analysis (PCA) to detect the output response of the sensors and reduce the data dimension. In the next step, Quadratic detection analysis and Mahalanobis detection analysis (QDA and MDA) were used to classify 2 group of pepper. 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 with each other.
Quadratic detection analysis and Mahalanobis detection analysis (QDA and MDA) are the most common monitored technique for separating samples into predetermined categories. This technique selects independent data variables to differentiate the sample that is to follow the normal distribution. The QDA and MDA are based on linear classification functions in which intergroup variance is maximized and intragroup variance is minimized.


Conclusion
Principal component analysis diagram shows the total variance of the data equal to PC-1 (90%) and PC-2 (6%), respectively, and the first two principal components constitute 96% of the total variance of the normalized data. When the total variance is above 90%, it means that the first two PCs are sufficient to explain the total variance of the data set. two group of pepper are well differentiated by PCA method. Therefore, it can be concluded that e-Nose has a good response to the smell of 2 group of pepper and they can be distinguished from each other, which shows the high accuracy of the electronic nose in detecting the smell of different products.
The correlation loadings plot diagram can show the relationships between all variables. The loading diagram shows the relative role of the sensors for each principal component. The inner ellipse shows 50% and the outer ellipse shows 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, the sensors located on the outer circle have a greater role in data classification and it is clear that the three sensors MQ4, MQ9 and TGS822 have played an important role in identifying 2 group of pepper.
The correlation loadings plot diagram can show the relationships between all variables. The loading diagram shows the relative role of the sensors for each principal component. The inner ellipse shows 50% and the outer ellipse shows 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, the sensors located on the outer circle have a greater role in data classification and it is clear that the three sensors MQ4, MQ9 and TGS822 have played an important role in identifying 2 group of pepper. Unlike the PCA method, the LDA method can extract multi-sensor information to optimize resolution between classes. Therefore, this method was used to detect 2 group of pepper based on the output response of sensors. The results of detection of cultivars were equal to 100%.
The electronic nose has the ability to be used and exploited as a fast and non-destructive method to distinguish sweet and hot pepper from leaf odor. Using this method in identifying sweet and hot pepper will be very useful for consumers, especially processing units and food industries in order to select appropriate cultivars. Since the detection of pepper using an electronic nose has not yet been researched, the promising results of this study can be widely applied in the sorting industry.

کلیدواژه‌ها [English]

  • Sweet and hot pepper
  • Sorting
  • electronic nose
  • Classification