P. Fayyaz; S. S. Mohtasebi; A. Jafari; A. Masoudi
Abstract
Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like. Most of the methods that are used to detect and to distinguish essential oils are based on chromatographic ...
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Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like. Most of the methods that are used to detect and to distinguish essential oils are based on chromatographic methods. However, these analytical methods are time consuming and require expert operators to work with required devices. Moreover, it is necessary to prepare the samples. An electronic nose is known as a tool for mimicking the sense of smell. This tool usually consists of an array of sensors which are used to identify and to isolate a variety of complex odors at a low cost. Since there has been no research on the usage of an electronic nose system for detection and separation of essential oils, the purpose of this study is to develop and to evaluate an electronic nose system for identification and classification of various types of commercial lemon essential oils (synthetic types). Materials and Methods The proposed system consists of a sensor chamber, a sample chamber, an array of MOS sensors, electro valves, a pump, a data acquisition cart and, a processor. Essential oils used in this study includes eight types of synthetic commercial lemon essential oils that were prepared by ((Avishan Khane Tabiat Sabz)) Company located in chemistry and chemical engineering research center of Iran. One gram sample of each essential oil was prepared to be placed in the sample chamber. Each experiment was carried out in 9 replicates and in three stages of 1- Baseline correction (250 s) 2- Sample smell injection (400 s) and 3- Sensors chamber cleaning (200 s). Data received from the sensors signals were initially preprocessed and normalized and then three methods of principal component analyses (PCA), linear discriminant analyses (LDA) and artificial neural network (ANN) were used to process the data. Both PCA and LDA methods were run using the Unscramble x10.4 software and the artificial neural network was used with the help of NeuroSolution 5 software. In ANN, the classification was carried out using a multilayer perceptron (MLP) and Leave-one-out technique. Leave-one-out is an acceptable method for evaluating the performance of the classification algorithms when the number of samples is low. Results and Discussion In order to analyze the data obtained from the sensor array, first, the principal components analysis (PCA) method was used. In this method, the first two principal components of PC 1 and PC 2 totally covered 99% of the data variance. Another plot called as loading plot was used to determine the effects of each sensor responses in pattern recognition analyzes. According to this plot, all sensors had high loading coefficients. In case of distinguishing the lemon essential oils, the results of the linear discriminant analysis (LDA) method showed that this method can distinguish eight types of lemon essential oils with an accuracy of %98. The artificial neural network (ANN) also separated the essential oils with the accuracy of the above %91. Conclusion An Electronic nose system based on semiconductor metal oxide sensors is a powerful tool that can be used as a substitute for traditional methods. In general, this study showed that the electronic nose system based on MOS sensors has the ability to detect and to distinguish commercial lemon essential oils. Considering the wide ranges and economical nature of the essential oils, it is suggested that applications of the electronic nose can be more expanded in the subject of the essential oils of different products.
J. Habibi Asl; L. Behbahani; A. Azizi
Abstract
Introduction Many vegetables such as mint are highly seasonal in nature. They are available in plenty at a particular period of time in specific regions that many times result in market glut. Due to perishable nature, huge quantity of vegetables is spoiled within a short period. The post-harvest loss ...
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Introduction Many vegetables such as mint are highly seasonal in nature. They are available in plenty at a particular period of time in specific regions that many times result in market glut. Due to perishable nature, huge quantity of vegetables is spoiled within a short period. The post-harvest loss in vegetables has been estimated to be about 30-40% due to inadequate post-harvest handling, lack of infrastructure, processing, marketing and storage facilities. Therefore, the food processing sector can play a vital role in reducing the post-harvest losses and value addition of vegetables which will ensure better remuneration to the growers. Drying is a common technique for preservation of food and other products; including fruits and vegetables. The major advantage of drying food products is the reduction of moisture content to a safe level that allows extending the shelf life of dried products. The removal of water from foods provides microbiological stability and reduces deteriorate chemical reactions. Also, the process allows a substantial reduction in terms of mass, volume, packaging requirement, storage and transportation costs with more convenience. Sun drying is a well known traditional method of drying agricultural products immediately after harvest. However, it is plagued with in-built problems, since the product is unprotected from rain, storm, windborne dirt, dust, and infestation by insects, rodents, and other animals. It may result in physical and structural changes in the product such as shrinkage, case hardening, loss of volatiles and nutrient components and lower water reabsorption during rehydration. Therefore, the quality of sun dried product is degraded and sometimes become not suitable for human consumption. For these reasons, to utilize renewable energy sources, reduce vegetable losses and increase farmers income, the current project has been conducted in the Agricultural Engineering Department of Khuzestan Agricultural Research Center during the years 2011-2013. Materials and Methods In this research an indirect cabinet solar dryer with three trays and grooved collector was constructed. To improve air convection, a chimney was mounted above the dryer. The dryer performance was evaluated by drying mint leaves in three levels of mass density of 2, 3, and 4 kg m-2 at two drying manners of natural and forced convection and compared with drying mint leaves in shade as the traditional method. Results and Discussion The results showed that total drying time required in different solar drier treatments was 3.5 to 15 h, while it was about 5 days in traditional method. Drying time in upper trays was more as the air flow decreased due to increase in mass density. Mean required drying time in forced convection was 29.7% less than that of natural convection. Maximum essences with 0.80% and 0.76% were belonged to "natural convection and 3kg m-2 mass density" and "forced convection and 4 kg m-2 mass density" treatments respectively, while minimum one with 0.30% was for "forced convection and 2 kg m-2 mass density" treatment. Also, the highest and lowest chlorophyll content with 8.51 and 4.18 mg ml-1 were measured in "natural convection and 3 kg m-2 mass density" and "forced convection and 4 kg m-2 mass density" treatments respectively. According to obtained results, 3 and 4 kg m-2 mass density can be suggested for natural and forced convection solar drying of mint leaves in Khuzestan condition respectively. Conclusion In order to reduce vegetable losses and increase Khuzestan vegetable producers income, indirect cabinet solar dryer for drying mint leaves in winter season, could be an appropriate option. For natural and forced convection drying methods, mass density of 3 and 4 kg m-2 is recommended respectively.
