حامد کرمی

Coffee is a common drink which is obtained from the roasted and ground beans of the coffee plant. Coffee beverages are widely consumed as a stimulant, a property largely attributed to the presence of caffeine, which is the most active pharmaceutical ingredient consumed worldwide. When the fruit of the coffee plant ripens, the coffee beans are harvested, processed, and finally dried. Dried coffee beans are roasted to different degrees and graded depending on the desired aroma and taste. It is very important to detect natural and unnatural impurities and adulteration in coffee.

An odor machine system based on eight MOS sensors was used to investigate the effect of bread storage time based on odor characteristics. The designed system includes a data acquisition system, sensors, sensor shield, sample container, power supply, connections, electric valves, air pump, and air filter. The sensor array consisted of 8 MOS sensors, including MQ136, TGS822, MQ9, MQ3, TGS813, TG2620, TG2602, and MQ135, each reacting 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. They are the most commonly used sensors in electronic nose systems. Sensors are the main components of an electronic nose system; therefore, it is necessary to select sensors able to detect differences among samples. In this research, the use of electronic nose technology and artificial intelligence was evaluated to detect common adulteration in Arabica coffee (Medium Dark). Robusta coffee samples with weight percentages of 10, 40, 30, 20, and 50% were used for experiments and adulteration. An electronic nose equipped with eight metal oxide sensors was used to carry out experiments related to odor. The data received from 8 sensors was first recorded and stored as raw data. In this research, the fractional method was used to normalize the data. Preprocessed data were used as the input matrix for multivariate analytical methods. The unsupervised multivariate principal component analysis (PCA) method was used to analyze the data. The LDA method was used to reduce classification differences and expand the differences between different groups. The artificial neural networks (ANN) method was used for classification. All calculations and analyses were done using Excel 2016, Unscrambler x10.4, and MATLAB software. Model evaluation criteria are used to evaluate algorithm performance in supervised learning. To analyze the system's performance, common criteria including Specificity, Recall, Precision, Accuracy, Area Under the Curve (AUC), and F-score were used.

The results of PCA showed that 87% of the total variance of the data was explained by PC1, and 8% by PC2, and the two main components constituted 95% of the total variance of the normalized data. Based on the results, pure Robusta coffee (B) was located on the right side of the PCA diagram and completely separate from other levels of adulteration. Also, pure Arabica coffee (A) was placed in the vicinity of counterfeit samples, and all counterfeit samples showed the same behavior as Arabica coffee, which is very difficult to distinguish. The loading diagram was examined to determine the role of sensors in separating the groups. Based on the loading diagram for coffee adulteration detection, the sensors that had the highest value on the principal component were MQ9, TGS822, and MQ136. Other sensors also showed a high correlation with the smell of the samples. In other words, other sensors could be neglected. The models of artificial neural networks analysis were evaluated by the correct classification rate (CCR), root mean square error (RMSE), and coefficient of determination (R2). According to the results obtained for 7 different coffee groups, the 7-8-8 structure had the best results. This structure has 8 neurons in the input layer (number of sensors), a hidden layer with 8 neurons, and 7 neurons in the output layer (7 groups). The average values of the class obtained from the ANN model for the parameters of accuracy, precision, recall, specificity, area under the curve (AUC), and F-score were equal to 0.984, 0.952, 0.943, 0.990, 0.971, and 0.942, respectively. Also, the ANN method showed higher accuracy than the LDA method.

The electronic nose showed that it is a fast and effective tool for detecting adulteration substances in coffee.

Medicinal plants are widely used in many fields around the world. Medicinal plants are an integral part of daily life and the increase in demand for these plants leads to fraud and reduced quality in the final product. Therefore, authentication is vitally important for consumers. Mint is valuable because of its medicinal properties and its essential oil, which is used in the food, pharmaceutical, cosmetic and health industries. In this research, the use of electronic nose to detect the age of mint plant by the odor emitted from its leaves was investigated. The main branches of mint plant with different ages of one to five years were taken from the distance of 4 to 5 cm from the ground. An electronic nose equipped with 8 metal oxide sensors was used to carry out experiments. To analyze the data, PCA, LDA and QDA analyzes were used. PCA results showed that 95% of the total variance of the data was explained by PC1 and 4% by PC2, and the two principal components expressed accounted for 99% of the variance of the normalized data. Also, the QDA method was 100% accurate in determining the age of the mint plant. The electronic nose has shown that it is a fast and effective tool to detect the quality parameters of plants and agricultural products.

Potato is an important vegetable that grows all over the world and is considered as an important product in developing and developed countries for human diet as a source of carbohydrates, proteins, and vitamins. This product is native to South America and its origin is from Peru, and after wheat, rice and corn, it is the fourth product in the food basket of human societies. According to the statistics of the Food and Agriculture Organization of the United Nations, the area under cultivation of this crop in Iran in 2017 was 161 thousand hectares and the crop harvested from this area is about 5.1 million tons. Traditional methods of determining potato varieties were based more on morphological features, but with the production of new products, there was a need for methods that were faster and more recognizable. Meanwhile, the high-performance artificial neural network can be used to classify cultivars. An artificial neural network can classify and detect cultivars, is flexible and is used in most agricultural products. Azizi conducted a study on 120 potatoes in 10 different cultivars using a visual and image processing machine with a MATLAB R2012 software toolbox to detect texture, shape parameters and potato cultivars. First, potato cultivars were classified usithe ng LDA method, which obtained 66.7% accuracy. This method also erred in distinguishing the two cultivars Agria and Savalan and also classified the two cultivars Fontane and Satina in other classes. They also used artificial neural networks to classify potato cultivars, in which the network was 82.41% accurate with one hidden layer and 100% accurate with two hidden layers. In this study, it was found that different types of potatoes can be identified and identified with a very high level of accuracy using the three color characteristics, textural and morphological features extracted by the visual machine and the use of a non-linear classifier artificial neural network. Categorized.In another study that was conducted using neural networks and image processing on 5 sweet potato cultivars, the researchers showed that this method was successful and could classify sweet potato cultivars with 100% accuracy.By determining and examining the existing relations between the force and the deformation of agricultural products up to the point of surrender, the range of forces harmful to fruit can be determined so that harvesting and transportation machines are designed in such a way that the forces from them do not exceed this range. On the other hand, one of the ways to determine the degree of ripeness of the fruit is to touch and press it with the thumb, which is an experimental way and depends on the skill of the person touching it. The mechanical penetration test of the fruit can be an indicator to check the ripeness of the fruit by quantifying this diagnosis and using this diagnosis to determine the optimal harvest time.Several types of research have been conducted on the physical and mechanical properties of agricultural products in Iran and other countries. In a research conducted by Ali Mohammadi and Rasakh to determine some mechanical properties of lime fruit under quasi-static loading, the results showed that the effect of loading speed, loading direction and size of a lime on the breaking force of lime is significant. As the size of the lemon decreases, the breaking force and deformation decrease, and also with increasing loading speed, the braking force increases. In another research conducted by Mohd Nejad and Khosdada, the effect of size, speed and direction of loading on the mechanical properties of lime was investigated and the results showed that the interaction of loading speed and size on fracture energy and toughness and the main effects of size, loading speed and The loading direction is significant on the modulus of elasticity, but none of the effects on the rupture force is significant.

First, 5 different varieties of potatoes (Agria, Spirit, Sante, Marfona and Jelly) were prepared from Ardabil Agricultural Research Center immediately after harvest. After preparing the varieties, 21 samples of each potato variety were prepared using a cutting cylinder and then data collection was done with santam machine.To measure the rupture energy of potato samples, santam device (available in the Biosystem Engineering Department of Mohaghegh Ardabili University) was used. For this purpose, each potato variety was subjected to a compressive force at three loading speed levels (10, 40 and 70 mm/min) with 7 repetitions. Then, using the amount of rupture force and deformation (surface area under the force-deformation curve), the amount of rupture energy was calculated. The data obtained from the experiment were analyzed statistically with Minitab 18 software.

Conclusion:

 The amount of rupture energy in 5 different varieties of potato was obtained using santam device and equation 1. The values obtained for 5 potato cultivars were analyzed using Minitab18 software and the results are given in Table (1).The results of the analysis of variance for the firmness of 5 different potato cultivars were significant at the 1% level and the coefficient of variation was 9.6. In Figure 2, you can see the average results.According to Figure 2, it is clear that the lowest amount of rupture energy is related to the Agria variety and the highest is related to the Jali variety. Also, it can be found that with a loading speed of 10 mm/min, the highest amount of rupture energy is obtained in all figures.In this research, the firmness level for 5 different potato cultivars was calculated using the santam machine available at Mohaghegh Ardabili University and the area under the force-deformation curve. The amount of calculated rupture energy has the ability to be used as a method for the proper selection of different potato cultivars. The use of this method in potato cultivars will be very useful for factories such as chips factories and processing units, and it is also expected that similar methods related to mechanical properties such as crispness and hardness and with the help of different statistical methods to optimize production and The processing of agricultural products can be used in the food industry, which leads to more customer-friendliness and can also reduce agricultural waste.

Introduction:

 Potato with scientific name Solanum tuberosum. L is a plant that is cultivated as an important crop in all countries and is known as a source of carbohydrates, proteins, and vitamins in the human diet. This is a native product of South America and its origin is from Peru. After wheat, rice and corn, potato is the fourth product in people's food basket, which in Iran sometimes takes the place of rice and takes second place, which shows its importance in meeting people's food needs. According to the reports of the Food and Agriculture Organization of the United Nations, the area under potato cultivation in Iran in 2019 was more than 164 thousand hectares and the harvested product from this area was about 32.5 million tons. In the food industry, this product is transformed into various products such as baked potatoes, fried potatoes, potato chips, potato starch, dry fried potatoes, etc.Agria, Sante, Arinda, Marfona, Jelli, Born, Satina, Milva, Banba, Fontane, Ramos and Esprit varieties are among the most common potato varieties in Iran. Due to the increasing expectations for food products with high quality and safety standards, it is necessary to accurately, quickly and purposefully determine the characteristics of food products. In the apple-potato product, quality assessment after the harvest stage is necessary to provide a reliable and uniform product to the market, because potatoes, like many other products, have uneven quality and handling during the harvest stage. - Be At the same time, the safety and desirability of food play an important role in the food industry and are directly related to people's health. In addition, a huge part of the potatoes used in the processing industry is stored, so considering the importance of this food item and the demand of the people throughout the year, it is possible to meet the needs of the applicants only through long-term storage with optimal conditions was responsible. Potatoes for the processing industry must have some requirements such as low sugar content, high dry matter and specific weight, high antioxidants, light skin color and no sprouting. Storage conditions after harvesting can cause changes in the chemical composition and quality of the product.The nutritional and chemical composition of potatoes differs from each other depending on the variety, storage period, growing season, soil type and pre-harvest nutrition. In general, potatoes contain 70-80% water and 16-24% starch and contain small amounts (less than 4%) of protein, fat, anthocyanins, minerals, etc.Storage conditions after harvesting can cause many changes in the chemical composition of potato tubers and as a result, change the quality characteristics of the final product. Sugar and starch are the main components that are affected by metabolism after harvesting in the potato tuber and may ultimately affect their texture, sensory and cooking properties.The quality of potatoes and, consequently, the quality of processed products, significantly depends on the variety and environmental conditions, both during the growing season and during the storage period.Although the quality of raw potatoes is determined primarily by the size, shape, color and attractiveness of the tuber, its quality is mainly determined by examining the quality of the final product. The quality of processed potato products is evaluated in terms of color, flavor and texture, and most of their quality depends on the quality of raw potatoes.By analyzing the relationship between the color of chips, dry solids, sucrose, reducing sugar, ascorbic acid, protein and storage temperature data, Meza showed that dry solids, reducing sugar and sucrose in determining the color of fresh potato chips and reducing sugar, tuber temperature and sucrose content are very important in determining the color of stored tuber chips, and the relative importance of each of these parameters changes with the variety and age of potato tubers.

different varieties of potato were prepared from Arallo Agricultural Research Center (Ardebil Province) immediately after harvest. Then, data collection was done from different samples and cultivars (measurement of carbohydrate content) as explained below.The carbohydrate content of the samples was extracted using the equipment available in the central laboratory of Mohaghegh Ardabili University. This process was carried out by the Schlegel method, in which carbohydrates were extracted using 95% ethanol based on the sulfuric acid method in each sample. The amount of light absorption of each sample was obtained from a nano-spectrophotometer device (Nanodrop) with a volume of 1000 microliters (Figure 1) using a cuvette (made by Termo scientific company from the USA) and the amount of extracted carbohydrates were obtained based on micrograms per millilitre from the standard curve.Glucose was used to prepare the standard curve. Serial dilution of glucose was prepared and color development at 490 nm was controlled for different concentrations of glucose and one millilitre of distilled water was used as a blank. This standard curve was used to calculate the concentration of total carbohydrates in the samples. The standard curve had a coefficient of determination of 0.9955.For each sample, data collection was done in three repetitions and the amount of absorption wavelength and then the amount of carbohydrate was calculated.

In order to obtain the number of carbohydrates, the number of the absorption wavelength was placed in the relationship obtained from the standard curve, and the number of carbohydrates was obtained in micrograms per millilitre. The results of the analysis of the variance of the effect of cultivar on potato carbohydrate content can be seen in Table 1. According to the analysis of the variance table, the effect of variety on potato carbohydrate content was significant at the 1% probability level.As you can see, Sante and Esprit cultivars have more carbohydrates than other cultivars. Also, the carbohydrate content of the Marfona variety was the lowest.According to the data and results of the research, it was observed that the amount of carbohydrates in different potato cultivars is different, and Sante and Esprit cultivars had more carbohydrates at the time of harvest. Also, according to the resulting graphs, it was observed that the amount of carbohydrates of the Marfona cultivar is lower than other cultivars. It is recommended to choose a more suitable variety according to the type of consumption and the importance of quality characteristics for consumption and processing, according to the storage conditions and time.

The use of plant-derived compounds is common in medicine and preventive health care, while the scope of use of some substances is steadily increasing. The mint family, with more than 200 genera and 3000 species, is very important economically and medicinally. The mint genus contains 25 to 30 species that grow in different temperate regions of Asia, Europe, Australia and South Africa. There is a great diversity in terms of chemical composition among the species of the mint genus. Peppermint essential oil (Mentha spicata L.) is rich in carvone, which produces the special aroma of mint. The yield of essential oil of Sentha spicata is lower than that of Mentha piperita. Carvone is the main component of Mentha spicata and Mentha longlifolia, while Carvone is absent in Mentha piperita, Mentha aquatic, Mentha arvensis and Mentha pulegium. Peppermint essential oil and extract are used in the pharmaceutical, cosmetic and food industries all over the world. Mentha spicata essential oil and leaves have therapeutic uses and its general properties are analgesic, tonic, stomach tonic, antitussive, anticonvulsant, astringent, analgesic and sedative. Peppermint oil has been used since ancient times for medicinal purposes, mostly to treat headaches, colds and neuralgia. It can also relieve skin irritations and digestive problems and has antispasmodic effects. Although, there is mixed information about the chemical composition of Mentha spicata essential oil, many studies have confirmed carone and limonene as its main components. Carvone is responsible for the smell of peppermint essential oil. The high price of carvone in the market has pushed breeders to improve mint varieties with high carvone. Different chemotypes are characterized by specific odors and biological activities, which indicate different applications in the aromatic and pharmaceutical industries. For example, Europeans enjoy the scent of Carvone. The use of medicinal plants in the food and pharmaceutical industries depends on the amount of biologically active substances and their chemical composition. Changes in the concentration of volatile compounds of mint during drying also depend on several factors, including drying conditions (temperature, air speed), humidity, variety and age of the plant, climate, soil and harvesting method. The drying process and storage conditions of the dried plant can have an adverse effect on the medicinal properties of the essential oil. Drying is one of the efficient methods to preserve agricultural products and maintain food quality. Drying, as an important food preservation technique, is used in the food industry. Drying is required to reduce the water activity of the product to suppress the growth of microorganisms and inhibit chemical reactions to increase the shelf life of the product at room temperature. In addition, drying lightens shipping weight and reduces storage space. Conventional drying methods include hot air drying (HAD), vacuum drying (VD), vacuum freeze drying (VFD), and microwave-hot air alternating drying (MW-HAD). HAD is the most common method that dries food in an oven with a constant flow of hot air. As an optimal approach for drying raw vegetable food, this method has easy operation and low cost, but it requires a long drying time and has low energy consumption.

After the drying process, the essential oil was extracted from the dried product, and for this purpose, a Clonger machine was used using the water distillation method. Distillation with water is a method of extracting essential oils. This method is cheap because it mostly uses water as a solvent. Qualitative GC-MS analysis of the extracted essential oils was performed using an HP 6890 gas chromatograph coupled to an HP 5973 mass-selective detector (Agilent Technologies, Foster City, CA, USA) operating at 70 eV mode. The electronic nose consists of three parts: (1) a sample transport system (2) a detection system consisting of a set of gas sensors with partial characteristics and (3) an odor data processing system. The e-nose instrument can detect the presence of VOCs in various molecular structures with high accuracy and reliability regardless of more or less odor. Samples were analyzed using a portable e-nose, which consists of a multiple gas sensor array, a signal acquisition unit, and pattern recognition software. Essential oil samples (1 mL) were placed in a 10 mL sealed glass vial and equilibrated at 40 °C for 30 min under stirring. Clean ambient air was used as the carrier gas to transport the volatiles in the headspace of the sealed glass vials to the temperature and humidity controlled sensing chamber. The conductivity change in the sensor array is expressed by the normalized response of the sensor. Each measurement cycle lasted 100 seconds, which allows the sensor to reach a steady state, and the data collection interval using a computer was 1 second. Between measurement cycles, the sensor was purged for 200 s with purge gas filtered through activated charcoal to return the sensor signal to baseline. 15 measurements were made for each sample of peppermint essential oil. Data obtained from GC-MS analysis were first processed by in-house MSD Chemstation and structural identification was performed through NIST 2014 library research along withretention index (RI) validation. The dataset consists of pre-processed signals from 9 MOS gas sensors obtained in the e-nose during 120 measurements corresponding to 8 independent samples evaluated with 15 repetitions. The performance of e-nose for evaluating peppermint essential oil samples was evaluated using three supervised statistical methods, namely QDA, MDA and ANN.

Drying is the most suitable method used to preserve the natural products of plants. Choosing a special drying method is one of the important costs in the production and commercialization of medicinal plants. This study determined the effect of different drying methods on the quantity and quality of peppermint essential oil. The results showed that the highest yield of essential oil was in the HAD1A drying method and the lowest yield was related to the sun drying method. Also, the obtained compounds of the essential oil were determined by the GC-MS method, and in the HAD drying method, 18 compounds were determined, and the content of some of them decreased significantly with the increase of the drying temperature. In the dried samples, the main components were Carvone (64.30-7.45%), Limonene (24.21- 6.59%) and Carveol (18.34-1.92%). Also, the aroma characteristics of mint essential oil were evaluated with the help of an E-nose. Three classification algorithms QDA, MDA and ANN were used, and the highest percentage of classification related to QDA and MDA methods was 100%, and the accuracy of the ANN method was also 0.967%. The findings of this study provide a theoretical basis for the development of hot air thin layer drying process for medicinal plants and improving their sensory quality and related products. The future perspective is to continuously improve the in situ drying technique for medicinal plants and develop a suitable monitor system to control the sensory quality of the final products based on the findings of the current study.

Maize (Zea mays. L) is one of the most important crops acrossthe world that ranks third in terms of acreage behind wheat and rice. As this crop can adapt to different climatic conditions, it is of great importance and has a large area under cultivation.Therefore, maize is one of the major products of temperate, warm-temperate, subtropical, and humid regions. After wheat, rice, and barley, this plant is the main crop in Iran with the largest cultivated area.There are different types of maizeseeds, so their classification is essential to ensure quality. A key component of sustainable agriculture is quality assurance. On the one hand, techniques such as drying, cooling, and edible coating must be used to maintain the quality of agricultural products. On the other hand, effective and efficient methods should be developed to evaluate and classify their quality, which is used in seed and seedling processing centers, silos, and mechanized warehouses.The detection of various varieties of crop seeds using instrumental methods has been the subject of extensive research. As a non-destructive and rapid inspection method for the recognition and classification of cereal seed varieties, the visual machine is available. Machine vision-based automated methods can have a positive impact on food processing. In other words, this tool is the process of preparing and analyzing images of a real scene using a computer to obtain information or control a process. The features of images can be extracted using this machine to recognize and identify the quality of different types of products. To identify the types of plants, their growth patterns, and the effects of the environment on them to obtain more and superior products, machine vision occupies a special place and is one of the most important research areas. Inspection and quality control of factory output products is an important application of machine vision.Advances in image processing technology have opened up a wide range of machine vision applications in agriculture. The development of powerful microcomputers and specialized software has led to the use of image processing for the inspection of fruits and agricultural products, especially for quality control and sorting. Many agricultural products sorting systems used to separate fruits or crops based on color, shape, size, the extent of damage, crushing, bursting, spotting, etc., now rely on visual machines and image processing functions.Images of products moving on the conveyor system are taken by a CCD camera, transmitted to a computer for processing, and in these systems, the necessary data are extracted from them. Depending on the information obtained, commands are then issued to activate or deactivate a mechanical part so that the product can be removed from or allowed to cross the main path. Sorting is a common practice in many industries. Compared to mechanical systems, machine vision technology offers the highest accuracy and quality at the lowest cost and with the lowest error rate, so it can be considered the most effective solution to this problem. The agricultural industry is one of the areas where sorting and grading systems based on machine vision are urgently needed.The core elements of machine vision are image processing and analysis used together with new methods and classifiers such as neural networks, backup vector machines, fuzzy logic, etc. to perform classifications and required measurements. This study aimed to identify seeds of three maize varieties using macroscopic imaging techniques, evaluate the morphological and chromatic features in maize grains, and discriminate varieties using a stepwise method and remove some variables using LDA and ANN.

Three seed varieties of single cross 703,single cross 704, and single cross 705 were provided by the Agricultural and Natural Resources Research Centre of Ardabil Province in Pars Abad Moghan. The seeds were then taken to the Biophysical Properties Laboratory of the Department of Biosystems and Mechanical Engineering, MohagheghArdabili University.Three samples (20 g) of each variety were stored in a laboratory oven at 105 °C for 24 h to determine the initial moisture content of maize grains. According to the dry weight of grains, the initial moisture content of them was calculated by 10.50%. To distinguish 3 maize varieties, 180 samples were analyzed as single seeds (30 replicates in the anterior direction and 30 replicates in the posterior direction) for each variety with 60 replicates. In addition, 9 more samples were used in bulk with 3 replicates for each variety.Thus, we imaged a total of 189 samples. In addition, a digital scale with an accuracy of 0.001 g was used to measure the weight of the grains. Computer vision systems consist of five main components: lighting chamber, camera, analogue-digital card (for digitization), computer, and computer software. Images were taken using a Canon IXY DIGITAL 510 IS digital camera. A dome-shaped chamber was used to reduce noise and control ambient light. The system was illuminated with four fluorescent lamps and two rows of LED lamps, one white and one yellow. While the camera was pointed perpendicular to the imaging surface, it provided images with a resolution of 12.1 megapixels.In this case, the images were processed using MATLAB software. First, 10 maize seeds were randomly sampled from the first variety (single cross 703) and weighed using a digital balance. Then, parameters such as the large and small diameters and thickness of each grain were measured using a caliper of 0.02 mm. Then, these grains were placed at appropriate distances from each other on a plate of red cardboard in the opposite direction to be imaged. Finally, 30 maizeseeds were imaged in both directions and 60 images were taken as single seed. In total, we obtained 180 images of all three varieties as single seeds. To prepare the mass, first, some seeds of the first variety were placed in a cylindrical container (1.5 cm high, 4.2 cm in basal diameter, and 70.62174 cm2 in volume) so that the container was filled. After weighing, the mass of grains with a certain volume was poured onto the red plate in a circular pattern. In the end, the camera was placed on the bulk sample and the image was taken, just like the single grain image.The same procedure was repeated twice more on two more bulk samples of the first variety. Similarly, three bulk samples of two more varieties were imaged. In this way, a total of nine images were obtained. After each imaging, we measured and recorded the dimensions and weight of 10 randomly selected seeds from the imaged bulk. In the end, 189 images were obtained, including 180 single-grain and 9 bulk images.In the single sample feature extraction step using the bwlabel function, all samples were labeled and the grain morphological features were extracted. Then, the set of Regionprop functions was used to determine eight parameters, including area, perimeter, major principal axis, minor principal axis, integrity, irregularity, convex area, and equivalent diameter. An artificial neural network (NAA) and a statistical linear discriminant analysis (LDA) method were used to identify maize varieties based on their morphological and color characteristics. The data were normalized before analysis. LDA is a statistical method for classifying objects based on independent variables. The analysis was carried out using SPSS software. The diagnostic analysis includes stepwise analysis, principal component analysis, and elimination of recursive features. In this study, the stepwise method was used. In the usual method, all variables are included in the analysis. However, in the stepwise method, some variables were removed and only the variables with the greatest influence on the model were included. To classify the maize varieties, a network consisting of three layers: input, output, and hidden layers was used.

We performed image processing to classify three maize varieties based on the results obtained. A linear diagnostic analysis method was used in this study. A total of 16 predictor variables were used with an accuracy of 70.6%. Some variables were eliminated by a stepwise method. In addition, eight other predictor variables were analyzed with the same accuracy of 70.6%. Thus, although the number of predictor variables was reduced, the detection accuracy remained constant. Moreover, the highest accuracy of diagnosis (80%) was associated with the first variety (single cross 703). Additionally, the accuracy of the methods of ANN with 16 and 8 predictor variables was 75.6% and 72.2%, respectively. These values were higher than that of LDA.Predictive variables included areas, perimeter, major principal diameters, minor principal diameters, irregularities, concave areas, equivalent diameters, color indices (red, green, and blue) resulting from maize grain sample processing, weight, and grain size. The following factors were the most important predictors of varietal discrimination: thickness, major principal axis, minor principal axis, irregularity, equivalent diameter, integrity, red color index, and green color index. According to the results, the length and width of individual grains had no significant effect on variety classification.Our finding demonstrated thatmachine vision technology can be used in seed and seedling processing centers, silos, mechanized warehouses, and other places where maize seed crops need to be identified and separated in a non-destructive manner.

Potato with the scientific name (Solanum tuberosum. L.) is a plant that is cultivated as an important product in all countries and is known as a source of carbohydrates, proteins, and vitamins in the human diet. This is a native product of South America and its origin is from Peru. After wheat, rice and corn, potato is the fourth product in people's food basket, which in Iran sometimes takes the place of rice and takes second place, which shows its importance in meeting people's food needs. According to the reports of the Food and Agriculture Organization of the United Nations, the area under potato cultivation in Iran in 2019 was more than 164 thousand hectares and the harvested product from this area was about 32.5 million tons. In the food industry, this product is transformed into various products such as baked potatoes, fried potatoes, potato chips, potato starch, dry fried potatoes, etc.Since the expectations for food products with appropriate quality and safety standards have increased, it seems necessary to determine the characteristics of food products. In the meantime, in the potato product, quality evaluation after the harvest stage is necessary to provide a reliable and uniform product to the market, because potatoes, like many other products, have uneven quality and handling in It is the harvesting stage. At the same time, the safety and desirability of food play an important role in the food industry and are directly related to people's health. Potatoes for the processing industry must have some requirements such as low sugar content, high dry matter and specific weight, high antioxidants, light skin color and no sprouting. Stored potatoes may suffer from sweetening, rotting, water loss and sprout growth during storage. Storage conditions after harvesting can cause changes in the chemical composition and quality of the product. Therefore, the management of potato tubers in all stages of production and storage is very important.The quality of this product and its processed products depends on the variety and environmental conditions (both during the growing season and during the storage period). By analyzing the relationship between chips color, dry solids, sucrose, reducing sugar, ascorbic acid, protein and storage temperature data, Meza showed that dry solids, reducing sugar and sucrose in determining the color of fresh potato chips and reducing sugar, tuber temperature and sucrose content are very important in determining the color of stored tuber chips and the relative importance of each of these parameters changes with the type of tuber variety and storage.The amount of potato sugar significantly depends on the variety and storage temperature and it happens quickly in cold weather. In potato tubers during the storage period, starch is gradually hydrolyzed and turned into sugar (glucose). In unripe tubers and potatoes that are stored for a long time at low temperatures, there are more amounts of glucose, this feature is considered an anti-quality feature for the potato product in the industry, why? The increase of regenerating sugars causes the produced chips to turn brown and bitter. Storing potatoes for more than 7 months can cause ageing or old sweetness, and storage at a temperature of fewer than 10 degrees Celsius can cause sweetness caused by cold. Although potato storage at low temperatures can have beneficial results such as reducing respiration rate, reducing physiological ageing, inhibiting germination, reducing evaporative water loss and reducing microbial pathogens. But sugars accumulate when the balance between starch degradation and breakdown is not established and there is carbohydrate respiration. Therefore, potatoes that are kept at a lower temperature have a lot of sugar. Researchers reported that when potatoes are stored at zero degrees Celsius, there will be a complete stop in th accumulation of sugar.

First, 5 different varieties of fresh potatoes (Spirit, Agria, Sante, Jelli and Marfona) were prepared from Ardabil Agricultural Research Center (Arallo District). It should be noted that these potatoes were prepared immediately after harvesting so that there are no changes in the amount of sugar due to the time interval after harvesting.The amount of sugar in each sample was measured in three replicates using a liquid refractometer model BPTR100 (Middle East Control System Company, brand name Prisma Tech, made in Iran) available at Mohaghegh Ardabili University (Figure 1). For this, first, some water was taken from the samples and after pouring it into a microtube, it was placed inside a refrigerated centrifuge (top speed) of the LISA France model, and after rotating at a speed of 1800 rpm for 2 minutes, the impurities at the bottom settled and separated the pure liquid (pure potato juice). After reaching the ambient temperature, the said liquid was placed on the refractometer and its sugar content was read in terms of Brix.

The results of the analysis of the variance of cultivar effect on potato sugar content are shown in Table 1. According to the analysis of the variance table, the effect of variety on potato sugar level was significant at 1% probability level. You can see the changes in the amount of sugar of different potato cultivars in Figure 2. The difference in the amount of sugar in different cultivars is due to the difference in their starch hydrolysis (the main compound of potato-potato tubers) which occurs as a result of the respiration of the product, and it is in this way that the higher the amount of starch in If one variety is less, that variety has less sugar, and it is important to note that the chemical composition depends on the potato variety, soil, climate, and agricultural factors. In general, it can be said that potatoes with more sugar are suitable for the chips industry, and potatoes with medium sugar are suitable for frying. According to Figure 2, the highest amount of sugar is related to the Esprit variety and the lowest amount is related to the Jelly variety. The reason for the difference in the amount of sugar between different cultivars is mainly related to the type of soil, fertilizer and poison used. According to the data and the results of the research, it was observed that the amount of sugar in different varieties of potato is different, in the meantime, the jelly variety generally has a lower amount of sugar at the time of harvesting, and the variety of Esprit has the highest amount of sugar at the time of harvesting. Was. It is recommended to choose a more suitable variety according to the conditions according to the type of consumption and the importance of quality characteristics for consumption and processing, of course, physical characteristics are also involved in this relationship, which should be taken into consideration.

Foodstuff adulteration involves replacing expensive ingredients with low-cost substances to decrease the production cost and reach the maximum profit. In recent years, the issue of food adulteration has reached an alarming stage. The detection methods currently available for this problem are often costly, time-consuming, and require high technical expertise. Lemon juice has repeatedly been the victim of fraud attempts by manufacturers to lower the price of products. Electronic noses are used in many fields, including the beverage industry, for classification and quality control. The process involves detecting and differentiating volatile organic compounds (VOCs) released from food. This study used an electronic nose equipped with 8 metal oxide sensors to evaluate pure lemon juice and 11 counterfeit samples (water, lemon pulp, and wheat straw) to detect fraud through VOC analysis. The response patterns of the sensors were analyzed using chemometric methods, specifically Quadratic Discriminant Analysis (QDA) and Mixture Discriminant Analysis (MDA). According to the results obtained from the QDA and MDA methods, the total variance was 100% and 98.89%, respectively, for the classification of samples. Hence, it can be concluded that the electronic nose based on metal oxide semiconductor sensors combined with chemometric methods can be an effective tool with high efficiency for rapid and non-destructive classification of pure lemon juice and its counterfeits.

Walnut is an important economic and commercial product all over the world. The smell can be one of the key factors in determining the ripening time of the fruit and it depends on the content of the chemical compounds of the fruit and its skin. Crunchyness and easy peeling are the main features that affect the level of satisfaction of walnut consumers.The complexity of food odor makes it difficult to analyze them with conventional analytical techniques such as gas chromatography. However, sensory analysis by experts is a costly process and requires trained people who can only work for a relatively short period of time. Problems such as the human subjectivity of the response to smell and the variation between people should also be considered. Hence, there is a need for a tool such as an electronic nose with high sensitivity and correlation with human sensory panel data for specific applications in food control. Due to its easy construction, cheapness and the need for little time for analysis, the electronic nose is becoming an automatic non-destructive method to describe the smell of food.An olfactory machine can recognize the fragrance composition by estimating its concentration or determining some of its intrinsic properties, which the human nose is hardly able to do. In general, the human olfactory system is a five-step process including smelling, receiving the scent, evaluating, detecting and erasing the effect of the scent. The olfactory phenomenon begins with inhaling the intended smell and ends with breathing fresh air to remove the effect of the scent. The human olfactory system, with all its unique capabilities, also has disadvantages that limit its use in quality control processes, including subjectivity, low reproducibility (for example, results depending on time, people's health, analysis before the presence of odor and fatigue is variable), time-consuming, high labor cost, adaptation of people (less sensitivity when exposed to odor for a long time). In addition, it cannot be used to evaluate dangerous odors.The purpose of this research was to evaluate the ability of the electronic nose using chemometrics methods to detect the ripening time of walnuts with the help of its volatile compounds during the ripening period.

In each process of investigation (including 5 courses and intervals were determined as one week), premature walnut samples plus its ripe samples (in the last period) from one of the gardens around Ardebil (located in the village September) It was prepared and with an electronic data nose.In this study, the electronic nose was made in the Biosystem Engineering Department of Mohaghegh Ardebili University. The device uses 9 metal oxide semiconductor sensors (MOS) with low power consumption. The data is that the clean air was first passed through the sensor chamber for 150 seconds to clean the sensors from the smell and other gases. The sample smell was then sucked for 150 seconds by the pump from the sample chamber and directed to the sensors, and finally, clean air was injected into the sensor chamber for 150 seconds to prepare the device for recurring and subsequent tests. 20 repetitions are intended for each sample. During the above steps, the output voltage of the sensors was changed due to exposure to gases emitted from the sample (walnut aroma) and their smell response was collected and recorded by data collection cards.The Chemometrics method in this study will begin with the analysis of the main components (PCA) to discover the sensor output response and reduce the data dimension. The next step is to classify the time of walnut proceedings using artificial neural network analysis (ANN).

The scores chart (Figure 2) showed the total variance of the total data to PC-1 (98%) and PC-2 (1%), respectively, and the first two main components make up 99%of the total variance of normal data. When the total variance is above 90 %, it means that the first two PCSs are sufficient to explain the total variance. So it can be concluded that E-nose has a good response to peach smell and can be distinguished from peach figures, which indicates the high accuracy of the electronic nose in identifying the smell of different products. These results are highly compatible with the results obtained by XU et al., In a study conducted on class 6 rice digits, the PCA method was 99.5% accurate. The artificial neural network method was also used to identify and differentiate peaches based on the output of the sensors. The results of the diagnosis of walnut proceedings were obtained by 99% (Figure 3), which was the same as the PCA method.Aimin Li and colleagues, using an electronic nose with GC-MS tests, identified Chinese maca (MacA) at macroscopic and microscopic levels, concluding that there was a direct relationship between the Maca smell and chemical compounds (LI ET AL, 2019). Min Yee Lim and colleagues also achieved good results with the PCA method (Lim et al, 2020). They used the electronic nose to grade the quality of the Chinese commercial mum and were able to classify their quality with 94.3% accuracy, with the results of their PCA method in accordance with our research results. Arun Jana et al. (Jana et al, 2011) also used the olfactory machine with Ann, PCA and LDA to detect aromatic and non-aromatic rice, with the accuracy of the results used for the methods used, respectively: 93%, 96.5% and 80%. The results of our research were far more accurate than this study, which could be due to the presence of different volatile compounds in grape leaves.In this study, an olfactory machine with 9 metal oxide sensors was used to handle walnuts using their smell. Chemometrics, including PCA and ANN, were used for qualitative and quantitative data analysis of electronic sensor arrays. PCA was used to reduce data and, with two main components of PC1 and PC2, described 99% of the variance of the data set and provided an initial classification, as well as the artificial neural network capable of identifying and accurately classifying grape figures with grape cultivars the accuracy was 99%. The olfactory machine has the ability to use and operate as a rapid and non -destructive way to detect walnuts from their smell. Using this method will be very useful in identifying proper harvesting time for gardeners and manufacturers, especially processing units and food industries.

Potato is an important vegetable that grows all over the world and is considered as an important product in developing and developed countries for the human diet as a source of carbohydrates, proteins, and vitamins. This product is native to South America and its origin is from Peru, and after wheat, rice and corn, it is the fourth product in the food basket of human societies. According to the statistics of the Food and Agriculture Organization of the United Nations, the area under cultivation of this crop in Iran in 2017 was 161 thousand hectares and the crop harvested from this area is about 5.1 million tons. Traditional methods of determining potato varieties were based more on morphological features, but with the production of new products, there was a need for methods that were faster and more recognizable. Meanwhile, the high-performance artificial neural network can be used to classify cultivars. An artificial neural network can classify and detect cultivars, is flexible and is used in most agricultural products. Azizi conducted a study on 120 potatoes in 10 different cultivars using a visual and image processing machine with a MATLAB R2012 software toolbox to detect texture, shape parameters and potato cultivars. First, potato cultivars were classified use the ng LDA method, which obtained 66.7% accuracy. This method also erred in distinguishing the two cultivars Agria and Savalan and also classified the two cultivars Fontane and Satina in other classes. They also used artificial neural networks to classify potato cultivars, in which the network was 82.41% accurate with one hidden layer and 100% accurate with two hidden layers. In this study, it was found that different types of potatoes can be identified and identified with a very high level of accuracy using the three color characteristics, textural and morphological features extracted by the visual machine and the use of a non-linear classifier artificial neural network. Categorized.In another study that was conducted using neural networks and image processing on 5 sweet potato cultivars, the researchers showed that this method was successful and could classify sweet potato cultivars with 100% accuracy.By determining and examining the existing relations between the force and the deformation of agricultural products up to the point of surrender, the range of forces harmful to fruit can be determined so that harvesting and transportation machines are designed in such a way that the forces from them do not exceed this range. On the other hand, one of the ways to determine the degree of ripeness of the fruit is to touch and press it with the thumb, which is an experimental way and depends on the skill of the person touching it. The mechanical penetration test of the fruit can be an indicator to check the ripeness of the fruit by quantifying this diagnosis and using this diagnosis to determine the optimal harvest time.Several types of research have been conducted on the physical and mechanical properties of agricultural products in Iran and other countries. In a research conducted by Ali Mohammadi and Rasakh to determine some mechanical properties of lime fruit under quasi-static loading, the results showed that the effect of loading speed, loading direction and size of a lime on the breaking force of lime is significant. As the size of the lemon decreases, the breaking force and deformation decrease, and also with increasing loading speed, the braking force increases. In another research conducted by Mohd Nejad and Khosdada, the effect of size, speed and direction of loading on the mechanical properties of lime was investigated and the results showed that the interaction of loading speed and size on fracture energy and toughness and the main effects of size, loading speed and The loading direction is significant on the modulus of elasticity, but none of the effects on the rupture force is significant.

First, potatoes in 5 different varieties (Agria, Esprit, Sante, Marfona and Jelli) were prepared at Ardabil Agricultural Research Center and stored at 4-10 degrees Celsius. One day after preparing the varieties, 21 samples of each potato variety were prepared using a cutting cylinder and then data collection was done. The data collection included mechanical properties.To determine the toughness of the samples, the santam machine available in the mechanical properties laboratory of the biosystem engineering department of Mohaghegh Ardabili University was used. Each potato variety was subjected to a compressive force at three loading speed levels of 10, 40 and 70 mm/min and with 7 repetitions. Then, using the amount of braking force, deformation and sample volume, the toughness was calculated according to equation (1).
These experiments were carried out in 5 storage periods (at 2-week intervals).

The toughness of different cultivars showed different behavior during the storage period so no changes were observed in the Marfona cultivar for toughness during the storage period, and in the Sante cultivar, the toughness level was almost the same at the beginning and end of the period and only in the middle of the storage period the value There was a slight increase. But in the case of Agria, Sprit and Jali cultivars, it should be said that the changes in toughness do not follow a specific trend and are unpredictable. Also, according to Figure 3, it is quite clear that in all figures, the lower the loading speed, the greater the toughness obtained, and the reason for this is that at a lower loading speed, the breaking force occurs in high values. Falls, and as a result, according to relation 1, the toughness value also increases.According to Figure 3, during the storage period, the two varieties of Jelli and Marfona (especially the Marfona variety) did not change much in terms of toughness and considering this issue, it is recommended to use these two varieties for some purposes, including frying.In this research, firmness was calculated for 5 different varieties of potatoes in 5 storage periods using the santam machine available at Mohaghegh Ardabili University and with the help of equation 1. The results showed that Jali and Marfona cultivars maintained their firmness during the storage period, and hence they are recommended for uses such as chips.

The most essential function of governments, whether theological or secular, as a living organ is to survive in the area under its rule, & the public wealth of each country provides the resources to meet the needs of this living organ. In today's society, the administration of justice in the areas of distribution, allocation & elimination of discrimination is an undeniable necessity for the survival of governments. Indeed, the greater amount of these resources, if properly managed or consumed, it will lead to the growth of sustainable government development & ensure the survival of governance. The first step in managing & exploiting public wealth is to identify all types & instances of public wealth. So far, only the tangible aspects of public wealth have been considered in Iranian public law, & the intangible aspects of public wealth have been neglected due to the lack of recognition of this type of wealth, both in the field of identification & in the field of management or consumption. Human capital as intangible public wealth is the most valuable part of a country's public wealth, which has been considered by governments in macroeconomics since the beginning of the present century. This article seeks to expand the conceptual space of the subject & express its problematic aspect & examine the various dimensions & aspects of public wealth, especially intangible public wealth, & in a word, to substantiate the concept of intangible public wealth.

Peach, as an edible fruit with an acceptable economic advantage, is mainly produced in the Mediterranean region and Central Asia and consumed all over the world. Flavor is one of the key factors in fruit quality, and it largely depends on the content of soluble sugars and organic acids. Sweetness, which is determined by the level of soluble sugars, is one of the main characteristics that affect consumer satisfaction. In the mature peach fruit, sucrose constitutes more than 54% of the total soluble sugars, which are mainly stored in the vacuole and occupy up to 90% of the total cell. However, the underlying mechanisms of sugar accumulation in peach fruit remain largely unknown.The complexity of food odor makes it difficult to analyze them with conventional analytical techniques such as gas chromatography. However, sensory analysis by experts is a costly process and requires trained people who can only work for a relatively short period of time. Problems such as the human subjectivity of the response to smell and the variation between people should also be considered. Hence, there is a need for a tool such as an electronic nose with high sensitivity and correlation with human sensory panel data for specific applications in food control. Due to its easy construction, cheapness and the need for little time for analysis, the electronic nose is becoming an automatic non-destructive method to describe the smell of food.An olfactory machine can recognize the fragrance composition by estimating its concentration or determining some of its intrinsic properties, which the human nose is hardly able to do. In general, the human olfactory system is a five-step process including smelling, receiving the scent, evaluating, detecting and erasing the effect of the scent. The olfactory phenomenon begins with inhaling the intended smell and ends with breathing fresh air to remove the effect of the scent. The human olfactory system, with all its unique capabilities, also has disadvantages that limit its use in quality control processes, including subjectivity, low reproducibility (for example, results depending on time, people's health, analysis before the presence of odor and fatigue is variable), time-consuming, high labor cost, adaptation of people (less sensitivity when exposed to odor for a long time). In addition, it cannot be used to evaluate dangerous odors.The purpose of this research was to evaluate the ability and accuracy of the electronic nose using chemometrics methods to detect and differentiate peach cultivars using their volatile compounds.

First, 5 varieties of peaches were prepared. After preparing different varieties of peaches, first, the samples were placed in a closed container (sample compartment) for 1 day to saturate the space of the container with the aroma and smell of peach fruit, and then the sample compartments were used for data collection with an odor machine.In this research, the electronic nose made in the Biosystems Engineering Department of Mohaghegh Ardabili University was used. In this device, 9 metal oxide semiconductor (MOS) sensors with low power consumption are used, which are listed in Table1.The sample chamber was connected to the electronic nose device and data collection was done. This data collection was done in such a way that first, clean air was passed through the sensor chamber for 100 seconds to clean the sensors from thepresence of odors and other gases. Then the smell of the sample was sucked from the sample chamber by the pump for 100 seconds and directed to the sensors, and finally, clean air was injected into the sensor chamber for 100 seconds to prepare the device for repetition and subsequent tests. 30 repetitions were considered for each sample.The chemometrics method in this research, started with principal component analysis (PCA) to discover the output response of the sensors and reduce the dimension of the data. In the next step, linear discriminant analysis (LDA) was used to classify 5 peach cultivars.Principal component analysis (PCA) is one of the simplest multivariate methods and is known as an unsupervised technique for clustering data according to groups. It is usually used to reduce the dimensionality of the data and the best results are obtained when the data are highly correlated, positively or negatively.

The scores chart (Figure 2) showed that the total variance of the data is equal to PC-1 (89%) and PC-2 (7%), respectively, and the first two principal components account for 96% of the total variance of the normalized data. When the total variance is higher than 90%, it means that the first two PCs are sufficient to explain the total variance of the data set. So it can be concluded that the e-Nose has a good response to the smell of peaches and it is possible to distinguish peach cultivars, which shows the high accuracy of the electronic nose in identifying the smell of different products.The LDA method was also used to identify and distinguish peach cultivars based on the output response of the sensors. Unlike the PCA method, the LDA method can extract multi-sensor information to optimize the resolution between classes. Therefore, this method was used to detect 5 varieties of peach based on the output response of the sensors. The results of the identification of cultivars were equal to 90% (Figure 3).
In this research, an olfactory machine with 9 metal oxide sensors was used to identify and differentiate peach cultivars using their scent. Chemometrics methods including PCA and LDA were used for qualitative and quantitative analysis of complex data from the electronic sensor arrays. PCA was used for data reduction and with two principal components PC1 and PC2, it described 96% of the variance of the data set and provided an initial classification, while LDA was able to accurately identify and classify grape cultivars. It became 90%. The scent machine has the ability to be used and exploited as a quick and non-destructive method to identify peach cultivars based on their smell. The use of this method in identifying peach cultivars will be very useful for consumers, especially processing units and food industries, in order to choose suitable cultivars.

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.

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.

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.

Abstract;Right to work (employment) is one of the most important right, classified in the second generation of human right, has been emphasized in article 23 of the universal declaration of human right and has been recognized as one of the economic, social and culeural right in article 20of Islamic republic of Iran constitution.The necessity of equal terms in employment also has been mentioned in article 28 of Islamic republic of Iran constitution.Therefore lack of unreasonable diversity of employment contract is one of the issues discussed in hiring systems. Due to this matter, employment form change is one of the most emportant issues in employment law and a prerequisite for job safety and right to employment.This research, which has been conducted through an analytical-descriptive approach, aims to analyze the regulations of employing corporate employees and changing their type to officially employed. It also answers the question of whether all corporate employees are entitled to petition to have their type changed to officially employed.The answer is that the government is required to officially employ those corporate employees who are liable to clause 21 of the general law of serving war veterans and have been hired during the period when the fifth five-years-long development plan was in practice,according to the stipulated terms in the article and clause 44 of the aforementioned law and the subsequent revisions.This possibility has been predicted in article of cluse 87 of the law of the sixth five-years-long development plan.Keywords:Corporate employees,Formal employment,Status change,Employment, Court of Administrative Justice.

The Court of Administrative Justice is a judicial institution that protects the rights and legal freedoms of the people against the institutions and executive bodies. In order to protect the martyrs, the legislator has provided facilities and privileges in the laws and regulations. Enjoying the privilege of a higher education degree is one of the privileges in order to apply it by the executive bodies, several lawsuits have been filed in the court. The issue under discussion is the scope of the devotees' enjoyment of this privilege; According to the explicit text of the laws, the authorities are obliged to consider a higher level of education for martyrs, veterans, freedmen and children of martyrs. There is ambiguity about the children of veterans, whether they can also use the privileges of a higher education or not? In order to answer this question, the lawsuit issued by the primary branch of the court will be reviewed and analyzed.

The quality of contemporary urban squares based on indigenous lessons is one of the topics considered by the designers and the concerns of the present study. Assuming that the pattern language of historical squares in Yazd region can be recognized, this study aims to apply the pattern language theory to design these squares not only for morphological description, but also for exploring the application in the design of squares as well as redesigning of historical squares. Therefore, using theoretical perspectives and practical experiences on pattern language theory, this article aims to develop a method for recognizing design patterns and use it in extracting design patterns as well as the relationship between patterns to form a network of a pattern language. The basis for recognizing patterns is the historical squares of Yazd region (seven squares including Amirchakhmaq square, Shah square, Khan square, Vaqt al-Sa'eh square, Qala square, Lord Fahadan square and Shah Nematullah Vali Taft square) which are completely Iranian squares. These seven squares have been selected in different scales and functions and from different historical periods, including the Timurid, Safavid and Qajar periods. Six squares are located in the historical context of Yazd and one square is located in the historical context of Taft. The present research is applied-development and has been done by qualitative and historical-comparative method. In the process of reviewing the applied model, including four steps for extracting and recognizing design patterns have been developed. The first step is to experimentally observe and extract field similarities in different contexts. In the second step, the words of the pattern language or design patterns are extracted and the components and levels of the patterns as well as the functional and structural patterns of each are described. The third step is to formulate the relationships between the patterns or the rules of the pattern language, and the fourth step is to formulate general rules for designing urban squares. The most important output patterns include empty courtyard pattern, one-level and two-level color system, enclosed space, rectangular geometry, stepped composition, repetitive element of five- and seven-week arches, orientation, hierarchy, balance and contrast, entrance enclosures are spatial coherence and functional convergence. The result of this research is the development of thirteen rules for designing squares that include unity, hierarchy, proportions, ecology, spatial orientation, balance, spatial contrast, continuity, diversity, identity, universality, populism and simplicity.

Potato is an important vegetable that grows all over the world and is considered as an important product in developing and developed countries for human diet as a source of carbohydrates, proteins, and vitamins. This product is native to South America and its origin is from Peru, and after wheat, rice and corn, it is the fourth product in the food basket of human societies. According to the statistics of the Food and Agriculture Organization of the United Nations, the area under cultivation of this crop in Iran in 2017 was 161 thousand hectares and the crop harvested from this area is about 5.1 million tons. Traditional methods of determining potato varieties were based more on morphological features, but with the production of new products, there was a need for methods that were faster and more recognizable. Meanwhile, high-performance artificial neural network can be used to classify cultivars. Artificial neural network can classify and detect cultivars, is flexible and is used in most agricultural products. Azizi conducted a study on 120 potatoes in 10 different cultivars using a visual and image processing machine with a MATLAB R2012 software toolbox to detect texture, shape parameters and potato cultivars. First, potato cultivars were classified using LDA method, which obtained 66.7% accuracy. This method also erred in distinguishing the two cultivars Agria and Savalan and also classified the two cultivars Fontane and Satina in other classes. They also used artificial neural networks to classify potato cultivars, in which the network was 82.41% accurate with one hidden layer and 100% accurate with two hidden layers. In this study, it was found that different types of potatoes can be identified and identified with a very high level of accuracy using the three color characteristics, textural and morphological features extracted by the visual machine and the use of a non-linear classifier artificial neural network. Categorized.By determining and examining the existing relations between the force and the deformation of agricultural products up to the point of surrender, the range of forces harmful to fruit can be determined so that harvesting and transportation machines are designed in such a way that the forces from them do not exceed this range. On the other hand, one of the ways to determine the degree of ripeness of the fruit is to touch and press it with the thumb, which is an experimental way and depends on the skill of the person touching. The mechanical penetration test of the fruit can be an indicator to check the ripeness of the fruit by quantifying this diagnosis and using this diagnosis to determine the optimal harvest time.

First, 5 different potato cultivars were prepared from Ardabil Agricultural Research Center and kept at a temperature of 4-10 ° C. One day later, 21 samples of each potato cultivar were prepared using a cutting cylinder and then data were collected. To determine the toughness of the samples, the Centam device available in Mohaghegh Ardabili University was used. Each potato cultivar was subjected to compressive force at three levels of loading speed of 10, 40 and 70 mm / min with 7 repetitions. Then the amount of toughness was calculated according to Equation (1). Then linear diagnostic analysis (LDA) and artificial neural networks (ANN) were used to classify potato cultivars. LDA is a supervised method used to find the most distinctive special vectors, maximizing the ratio of variance between class and within the class, and being able to classify two or more groups of samples. ANN and pattern recognition were used to find similarities and differences in the classification of potato cultivars. For this, 1 neuron was considered for the input layer, the hidden layer with the optimal number of neurons will be considered and five output neurons with Depending on the number of output classes the target will be considered. In network training, the logarithmic sigmoid transfer function and Lunberg-Marquardt learning method were used (Figure 4), and the error value was calculated using the mean square error. For learning (70%), testing (15%) and validation (15%) all data were randomly selected. Training data was provided to the network during the training and the network was adjusted according to their error. Validation was used to measure network generalization and completion of training. Data testing had no effect on training and therefore provided an independent measurement of network performance during and after training. All of the calculations and matrix classification were performed using MATLAB R2018a and X 10.4 Unscrambler software.Toughness in 5 different potato cultivars was obtained using Centam machine and Equation 1. The values obtained for the toughness of 5 potato cultivars were analyzed using Mstatc software. The results of analysis of variance were significant for the toughness of 5 different potato cultivars at the level of 1% and its coefficient of variation was 2.28. LDA and ANN methods were used to detect potato cultivars based on the values calculated for toughness. Detection results of cultivars using LDA were equal to 70.48% (Figure 6). Also, the accuracy of ANN method according to the perturbation matrix was equal to 72.4% (Figure 7).

In this study, the amount of toughness for 5 different potato cultivars was calculated using Centam machine available in Mohaghegh Ardabili University with the help of Equation 1. Chemometrics methods including LDA and ANN were used for qualitative and quantitative analysis of data to identify and classify potato cultivars. Thus, LDA and ANN were able to identify and accurately classify different potato cultivars with an accuracy of over 70%. The obtained toughness has the ability to be used as a method to distinguish different potato cultivars. The use of this method in identifying potato cultivars will be very useful for factories such as chips factory and processing units, and it is also expected that similar methods related to mechanical properties such as crispness and stiffness with the help of chemometrics methods to optimize production and The processing of agricultural products should be used in the food industry, which has led to more customer friendliness and, in addition, can reduce agricultural waste.

Grape is a creeping plant that has ivy in front of some of its leaves. France, Italy and Germany are among the most important grape producing countries in Europe, and Iran is one of the most important centers for grape production and cultivation in the world due to its favorable geographical and climatic conditions. Grape fruit is divided into two types, seeded and seedless, each of which is found in different colors of red, yellow, black and almost green. In areas where the maximum temperature is not more than 40 degrees Celsius and the minimum temperature is not less than 15 degrees Celsius below zero, grape fruit grows better. Grapes are made from raisins, jellies, raisins, jams, vinegar and juice, and various products are made from grape seeds. This product is a good source of potassium, fiber and a variety of vitamins and other minerals. Is. According to available reports, there are about 800 to 1000 grape cultivars in Iran, and some of these cultivars are of great economic importance, especially for fresh consumption and preparation of raisins. In Iran, edible grapes are of the genus Winifra, and in addition, there are two types of Labrosca grapes, which are scattered in the north of the country, and wild grapes of the subspecies Westeris in the northern forests and wetlands of the Zagros Mountains. Grapes are widely distributed in terms of climate and have recently been cultivated in temperate and tropical regions in all parts of the world. By recognizing grape cultivars before fruit growth, it is an effective step in determining the purpose and use of the harvest product, in the meantime, the type of grape cultivar can be identified using new post-harvest technologies. One of these methods is to use an electronic nose to identify volatile compounds in grape leaves and to identify its cultivar. Electronic nose has been used in extensive research to identify and classify food and agricultural products.

First, 3 varieties of grape leaves were obtained from vineyards located in Bonab city of West Azerbaijan province. These 3 cultivars were: Jovini, Aq Shaliq and Qara Shaliq. 200 grams of each of these leaves were prepared. After preparing leaves from different grape cultivars, first the samples were placed in a closed container (sample container) for 1 day to saturate the container space with the aroma of grape leaves, then the sample containers were used for data collection with the case of the 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, linear detection analysis (LDA) and support vector machine (SVM) were used to classify 3 grape cultivars. 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.Linear Detection Analysis (LDA) is 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 LDA is based on linear classification functions in which intergroup variance is maximized and intragroup variance is minimized.

The scores diagram (Figure 2) shows the total variance of the data equal to PC-1 (82%) and PC-2 (11%), respectively, and the first two principal components constitute 93% 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. Grape cultivars are well differentiated by PCA method. Therefore, it can be concluded that e-Nose has a good response to the smell of grape leaves and grape cultivars 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 (Figure 3) 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 TGS2620, TGS822 and TGS813 have played an important role in identifying grape cultivars from their leaf aroma.LDA and SVM methods were used to identify and differentiate grape cultivars based on the output response of sensors. Unlike the PCA method, the LDA method can extract multi-sensor information to optimize resolution between classes. Therefore, this method was used to detect 3 grape cultivars based on the output response of sensors. The results of detection of cultivars were equal to 100% and also the accuracy of SVM method for detection of 3 grape cultivars was equal to 83.33% (Figures 4 and 5).In this study, an electronic nose with 9 metal oxide sensors was used to identify and differentiate grape cultivars using their leaf aroma. Chemometrics methods including PCA, LDA and SVM were used for qualitative and quantitative analysis of complex data using electronic sensor array. The electronic nose has the ability to be used and exploited as a fast and non-destructive method to distinguish grape cultivars from leaf odor. Using this method in identifying grape cultivars will be very useful for consumers, especially processing units and food industries in order to select appropriate cultivars.

By examining the category of social security, Challenges like how to manage SSO, or how to determine the duties of the main trustee, its administrative and financial independence have also been discussed. However, in designing social security management system, the participation and supervision of employers and the insured can and should be used. The main purpose of this study is to explain the extent of the government’s intervention in the SSO, by emphasising its administrative and financial independence. Based on descriptive-analytical studies, the present results of the research show that the main structure of social security laws and regulations, has emphasized the participatory structure of the Social Security Administration, but over time, there have been changes in the selection, number and functions of these pillars. Meanwhile, what is quite noticeable, especially after the victory of the Islamic Revolution, is the government’s presence in the field of social security and its increasing role in the field of security and welfare. Also for some reason, despite the explicit text of the law, the administrative and financial independence of the organization is violated by the government and is sometimes ignored. This issue is due to the existence of defects in the laws and regulations related to the administrative and financial independence of the organization, as well as the existence of problems and challenges in the implementation of some laws by the government. Therefore, the organization is in a situation that needs to restore administrative and financial independence.

Changes in the social and economic conditions of the country and the relocation of labor in different areas of work have made it necessary to transfer insurance records between the Social Insurance Pension Fund, which serves different segments of the work. Transfer from one pension fund to another, either voluntarily or involuntarily, has many implications that can be seen in terms of employees' employment rights and the interests of the bureaucracy. In this area, in addition to legal texts, the review of the rulings of the Court of Administrative Justice is of particular importance. The main purpose of this study is legal analysis of the possibility of changing the pension fund in the Iranian administrative system by looking at the procedure of the Administrative Court of Justice. Due to the special nature of legal studies in this article, a descriptive analytical method has been used. The results of the research show that due to different legal conditions, the transfer of insurance records from one fund to another is faced with limitations and obstacles. Examining the scattered laws and regulations in the field of transferring insurance records and looking at the procedure of the Administrative Court of Justice shows that the main issue in this field is the possibility or impossibility of transferring insurance records. In various texts, what is considered as the initial state in changing the pension fund is a forced change as a result of matters such as changing the service device, and in limited and exceptional cases, the voluntary possibility of change has been recognized. Another important point in this regard is the determination of the person responsible for paying the difference in insurance premiums that are transferred between the two funds, which is doubly important due to its importance. This task is in some cases the responsibility of the beneficiary and in some cases the responsibility of the government. In view of the above-mentioned points, it seems necessary for the legislator to adopt a unified procedure regarding the transfer of insurance records in a way that solves the problems of the insured and the funds.

Today, social capital is a major part of intangible public wealth, and the protection of public wealth requires good governance (as one of the components of soft power), a form of governance largely by the institution. International and developed countries have entered the literature of sustainable development and it has been interpreted as the proper management of a country's resources in a flexible, transparent, responsive, fair and responsive way to the needs of its citizens, which can, while protecting Social capital will increase the level of soft power. Therefore, according to the thematic documents presented in this research, the research method is descriptive-analytical and the data collection method is library. The article raises the question: What is the relationship between good governance (as a component of soft power) and public wealth? In other words, how can good governance affect social capital? In response, it can be assumed that: "The relationship between good governance and social capital is an interactive and two-way relationship in which good governance can create conditions in which social capital flourishes and social capital flourishes. It paves the way for good governance and increases soft power. ”The result is that social capital has positive effects on the dimensions of good governance, including transparency, oversight, balance, democracy and solidarity, and good governance also increases and The level of social capital will rise.

The outbreak of coronavirus has caused c psychological insecurity for all citizensVarious agencies and institutions have put a wide range of measures on the agenda to deal with this deadly virus. One of these important institutions is the Social Security organization, the purpose of the present study is the policiesof the Social Security Organization to protect the insured against the effects of coronavirus. Research Method In this research, the analytical method is descriptive. In this article, first the concepts of Social Security Organization, Corona virus and the insured are discussed, then  theoretical foundations of the Social Security Organization's entry to deal with the effects of Corona virus are discussed, and finally the actions of the Social Security Organization to deal with the effects of this virus on insurance. The victims have been examined. The results show that the Social Security Organization, in order to achieve high human goals, including, creating security and tranquility in life and with the tasks that it has to improve the living standards and social welfare of society, In order to reduce and deal with the effects of the corona virus, the current corona situation can be an example of the state of emergency subject to Article 79 of the Constitution and is also included in the crisis situation of the crisis management law, several measures have been put on the agenda in order to control the spread of the disease and break the chain of transmission.

The drying process plays an important role in the treatment of medicinal plants, in order to maintain the quantity and quality of the essential oil extracted from the plant. Because Medicinal herbs containing essential oils If they are not dried immediately or their essence is not extracted, they will lose their active ingredients and volatile compounds.The aim of this study is design a hybrid dryer to drying medicinal plants and comparison their results with traditional drying methods (sun and shade).The effects of different drying methods (hybrid dryer, oven and shade drying) on the essential oil content and chemical composition of thyme were studied. The essential oils from each organ type were extracted by hydrodistillation and the chemical components were analyzed by GC/MS systems. Mathematical modeling results showed that the Midilli model can fit the drying curves with high accuracy. The highest essential oils yield of 2.4 % (v/w) was obtained by a hybrid dryer. Results indicated that hybrid dryer could keep the 24 Kinds of volatile compounds of Thymus while these values were 10 and 6 for oven and shadow methods, respectively. The main components of the essential oils in different drying methods were including alpha and beta pinene, caryophyllene, caryophyllene oxide, carotol, thymol, thymol methyl ether, terpinene-4-ol, gama-terpinene, p-cymene.In general, hybrid drying method is recommended as the best method for post-harvest thyme processing.

One of the types of employment in executive organizations is through the buying service contract. The terms and conditions governing on this contract and how to employment situation transform are considered issues of employment law in Iran. Higher Salaries, Benefits, and Job Stability Formal Employment and Contractual Provide Highly craze for Contract Employees in transforming the employment situation. Therefore, one of the most repeated cases in the Administrative Justice Court is this issue. This Article analyzes the rules and regulations of the Buying Service Contract, after reviewing sources such as books and legal articles, acts and regulations, and the judgments of the Administrative Justice Court. And it has answered the question that can anyone who is employed as a buy in service apply for employment situation transform? The answer that can be made is that the situation can be changed only for those who have been employed in accordance with the "Coordination Guidelines for the Use of Human Services Required by the State Apparatus". And in other cases where people have been hired to buying service, it is not possible to turn the situation into contractual employment.

The term “National Monuments” is a familiar title for today’s citizens. However, this term is not as old as nine decades. The first time, this term has been mentioned in the books of intellectual authors in the Qajar era. After the establishment of Pahlavi, special legal rules have been passed in 1930.

For present study, the analytical-descriptive approach has been chosen.
Ethical Considerations: All ethical considerations as well as authenticity of the texts have been observed.

In laws and regulations related to national monuments, we cannot consider a comprehensive definition in this regard. Similar concepts such as cultural possessions, historical property, artistic property, antique treasures, national treasures, and natural monuments overlap with this concept.

According to the current legal order in the field of national monuments, spending one hundred years is necessary for the description of the cultural - historical monuments.