Research Article
P. Fayyaz; S. S. Mohtasebi; A. Jafari; A. Masoudi
Abstract
Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like. Most of the methods that are used to detect and to distinguish essential oils are based on chromatographic ...
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Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like. Most of the methods that are used to detect and to distinguish essential oils are based on chromatographic methods. However, these analytical methods are time consuming and require expert operators to work with required devices. Moreover, it is necessary to prepare the samples. An electronic nose is known as a tool for mimicking the sense of smell. This tool usually consists of an array of sensors which are used to identify and to isolate a variety of complex odors at a low cost. Since there has been no research on the usage of an electronic nose system for detection and separation of essential oils, the purpose of this study is to develop and to evaluate an electronic nose system for identification and classification of various types of commercial lemon essential oils (synthetic types). Materials and Methods The proposed system consists of a sensor chamber, a sample chamber, an array of MOS sensors, electro valves, a pump, a data acquisition cart and, a processor. Essential oils used in this study includes eight types of synthetic commercial lemon essential oils that were prepared by ((Avishan Khane Tabiat Sabz)) Company located in chemistry and chemical engineering research center of Iran. One gram sample of each essential oil was prepared to be placed in the sample chamber. Each experiment was carried out in 9 replicates and in three stages of 1- Baseline correction (250 s) 2- Sample smell injection (400 s) and 3- Sensors chamber cleaning (200 s). Data received from the sensors signals were initially preprocessed and normalized and then three methods of principal component analyses (PCA), linear discriminant analyses (LDA) and artificial neural network (ANN) were used to process the data. Both PCA and LDA methods were run using the Unscramble x10.4 software and the artificial neural network was used with the help of NeuroSolution 5 software. In ANN, the classification was carried out using a multilayer perceptron (MLP) and Leave-one-out technique. Leave-one-out is an acceptable method for evaluating the performance of the classification algorithms when the number of samples is low. Results and Discussion In order to analyze the data obtained from the sensor array, first, the principal components analysis (PCA) method was used. In this method, the first two principal components of PC 1 and PC 2 totally covered 99% of the data variance. Another plot called as loading plot was used to determine the effects of each sensor responses in pattern recognition analyzes. According to this plot, all sensors had high loading coefficients. In case of distinguishing the lemon essential oils, the results of the linear discriminant analysis (LDA) method showed that this method can distinguish eight types of lemon essential oils with an accuracy of %98. The artificial neural network (ANN) also separated the essential oils with the accuracy of the above %91. Conclusion An Electronic nose system based on semiconductor metal oxide sensors is a powerful tool that can be used as a substitute for traditional methods. In general, this study showed that the electronic nose system based on MOS sensors has the ability to detect and to distinguish commercial lemon essential oils. Considering the wide ranges and economical nature of the essential oils, it is suggested that applications of the electronic nose can be more expanded in the subject of the essential oils of different products.
Research Article
Design and Construction
H. Dehghan-Hesar; D. Kalantari
Abstract
Introduction Optimizing the energy consumption in mechanized agriculture is becoming more important due to the limited energy sources in the world. In this regard, optimization of the cutting blades is presented in this study by modifying the geometric form of the blade to reduce the forage cutting energy. ...
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Introduction Optimizing the energy consumption in mechanized agriculture is becoming more important due to the limited energy sources in the world. In this regard, optimization of the cutting blades is presented in this study by modifying the geometric form of the blade to reduce the forage cutting energy. Hence, two new blades, inspired by the geometric profiles of front claws of mole crickets and teeth of grasshoppers were designed and built using the biomimetic method (the method for transferring biological solutions to the engineering ones). Finally, the new biomimetic blades were tested and compared with two other conventional blades (flat and bent blades) by cutting 8 different types of crops and weeds. Materials and Methods The main idea of building one of the blades was inspired by the geometric forms of mole crickets' scissors-like front legs and lower teeth of grasshoppers. Therefore, five adult mole crickets and five grasshoppers were collected from a farm in Kalat-e Naderi, Khorasan Razavi Province. In the next step, different images were captured from the front leg of mole cricket and tooth of grasshopper using the stereomicroscope (Nikon, SMZ-U, Japan). In the next step, the images were transferred to the image analysis software (Image J) and the boundary lines of images were selected. Then, the selected boundary lines were imported to SolidWorks software and the points on the selected curve were extracted. The obtained points were drawn in Matlab software and several fitting curves for the points were examined, e.g., Fourier function, Gaussian function, and polynomial function. According to the obtained results, the Gaussian profile was selected to design the blade with the highest correlation coefficient (R2=0.99), see Fig. 1d. To design the desired blade, a section of the Gaussian curve between points A and B were used. Finally, the biomimetic blade of the mole cricket and grasshopper were drawn in SolidWorks software (Fig. 1e). After designing the blades in the SolidWorks software, the biomimetic blades were built by a CNC machine. Results and Discussion In all the treatments, a significant difference was observed between the biomimetic blades and the conventional flat and bent blades according to the results of Tukey's test at the level of 5%. The obtained results showed that there was no significant difference between the mole cricket and grasshopper blades at the level of 5% for cutting. According to the results obtained in this study, there was a significant difference at the level of 5% between the grasshopper and flat blades for cutting alfalfa, clover, amaranth, orach, and poaceae; as well as between the grasshopper and bent blades for cutting alfalfa, clover, nutsedge, and amaranth, also between mole cricket and flat blades for cutting alfalfa, clover, purslane, amaranth, orach, paddy, and poaceae and finally between mole cricket and flat blades in cutting alfalfa, clover, nutsedge, amaranthus, and paddy. In this regard, no significant difference at the level of 5% was observed between the flat and bent blades for all cutting treatment. The batches containing 6 stems were used for cutting the soft stems with low shear stress and the batches containing 4 stems were used for cutting thick stems with high shear stress. Conclusion The results obtained in this study indicated that the geometrical form of the blade has a significant influence on the amount of required shear energy. The mole cricket biomimetic blade reduced the cutting energy compared to the flat blade by 23.37% to 52.51% (with the mean of 39.11%) and compared to the bent blade by 10.46% to 52.46% (with the mean of 32.8%). The grasshopper biomimetic blade also reduced the cutting energy compared to the flat blade by 15.78% to 53.82% (with the mean of 33.59%) and compared to the bent blade by 2% to 46.29% (with the mean of 27.87%). According to the results of this study, the mole cricket biomimetic blade showed better performance in comparison with the grasshopper biomimetic blade for cutting the plants and as a final result could be recommended to build the plant cutting blades.
Research Article
Design and Construction
H. Biabi; S. Abdanan Mehdizadeh; M. Nadafzadeh; M. Salehi Salmi
Abstract
Introduction Leaf color is usually used as a guide for assessments of nutrient status and plant health. Most of the existing methods that examined relationships between chlorophyll status and carotenoid of leaf color were developed for particular species. Different methods have been developed to measure ...
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Introduction Leaf color is usually used as a guide for assessments of nutrient status and plant health. Most of the existing methods that examined relationships between chlorophyll status and carotenoid of leaf color were developed for particular species. Different methods have been developed to measure chlorophyll status and carotenoid. However, the high cost and difficulty to use have restricted their application, whereas the handheld chlorophyll meters such as the SPAD has become popular in the last decade for non-destructive measurement of chlorophyll content. SPAD meter readings have found to be related to the plant’s nutrition status, seed protein content, types of nodulation, and photosynthetic rates of leaves. Digital color (RGB) image analysis, another nondestructive technique is becoming increasingly popular with its potential in phenotyping various parameters of plant health status. The development of low-cost digital cameras that use charged-couple device (CCD) arrays to capture images offers an advantage of low-cost real-time monitoring process over optical sensor based SPAD meter. Gupta et al. (2012) estimated chlorophyll content, using simple leaf digital analysis procedure in parallel to a SPAD chlorophyll content meter. The chlorophyll content as determined by the SPAD meter was significantly correlated to the RGB values of leaf image analysis (RMSE = 3.97). The aim of this research is developing a new inexpensive, hand-held and easy-to-use technique for detection of chlorophyll and carotenoid content in plants based on leaf color. This method provides rapid analysis and data storage at minimal cost and does not require any technical or laboratory skills. Materials and Methods Sample collection In this research, 15 leaves were randomly selected from six types of plants (Shoeblackplant, Vitex, Spiderwort, Sacred fig, Vine and Lotus). Afterwards, the chlorophyll content of the leaf was measured in 3 different ways: 1) using a SPAD instrument; 2) using machine vision system (non-destructive method), and 3) laboratory test using a spectrophotometer. Chlorophyll and carotenoid content The chlorophyll content of the leaf was measured and recorded using SPAD chlorophyll meter (Hansatech, model CL-01, Japan) and spectrometer as explained by Dey et al. (2016). Furthermore, to measure the carotenoid content method described by Gitelson et al. (2006) was utilized. Image processing For estimation of chlorophyll using the image processing algorithm, sample images were taken using CCD (CASIO, model Exilim EX-ZR700, Japan) and transferred to the computer. The camera was mounted perpendicular to the horizontal plane at a fixed distance of 25 cm from the samples. In a consequence histogram of leaf, images were equalized and the average of each color channels from RGB, Lab, HSV, and I1I2I3 were extracted using Matlab 2016. Decision tree regression (DTR) algorithm To develop a regression model to predict chlorophyll and carotenoid content, two decision tree were constructed. The average of each color channels from RGB, Lab, HSV, and I1I2I3 become the predictor variables or feature vector and the real known chlorophyll and carotenoid content become the target variable or the target vector of each regression tree. To develop the regression models, dataset (90 observations) was split into training (60 observations) and test (30 observations) data. Results and Discussion According to the obtained results, a high correlation of 0.92 for chlorophyll and 0.85 for carotenoid was achieved, respectively, between the image processing method and the values measured by the spectrometer. Therefore, it can be said that the proposed image processing method has a desirable and acceptable performance for prediction of both chlorophyll content and carotenoid. The review points out a need for fast and precise leaf chlorophyll measurement technique. With this in mind, Dey et al. (2016) used image processing techniques to measure chlorophyll content. For the purpose of analysis of the proposed model, the model outcome was compared with the LEAF+ chlorophyll meter reading. Regression analysis proofed that there was a strong correlation between the proposed image processing technique and chlorophyll meter reading. Thus, it appears that the proposed image processing technique of leaf chlorophyll measurement will be a good alternative for measuring leaf chlorophyll rapidly and with ease. Conclusion In this research, collections of images from six divers plants (Shoeblackplant, Vitex, Spiderwort, Sacred fig, Vine and Lotus) were analyzed to predict chlorophyll and carotenoid content at different color spaces (RGB, Lab, HSV, and I1I2I3). Based on the results, it was shown that there were high correlations of 0.92 for chlorophyll content as well as 0.85 for carotenoid between the image processing method and the values measured by the spectrometer. Therefore, in general, it can be concluded that the proposed image processing method has a desirable and acceptable performance for prediction of chlorophyll content as well carotenoid.
Research Article
Image Processing
A. Jahanbakhshi; K. Kheiralipour
Abstract
Introduction Carrot is one of the most important agricultural products used by millions of people all over the world. Quality assessment of agricultural products is one of the most important factors in improving the marketability of agricultural products. In the market, carrots with irregular shapes ...
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Introduction Carrot is one of the most important agricultural products used by millions of people all over the world. Quality assessment of agricultural products is one of the most important factors in improving the marketability of agricultural products. In the market, carrots with irregular shapes are not commonly picked by customers due to their appearance. This causes to remain those carrots in the market for a long time and then decay. Therefore, adopting an appropriate method for sorting and packaging this product can increase its desirability in the market. Packaging and sorting of carrots by workers bring about many problems such as high cost, product waste, etc. Image processing systems are modern methods which have different applications in agriculture including sorting of different products. The aim of this study was to implement a machine vision system to classify carrot based on their shape using image processing. Materials and Methods In this study, 135 carrot samples with different shapes (56 regulars and 79 irregulars) were selected and their images were obtained through an imaging system. First, an expert divided the carrots into, two categories according to their shapes. The carrots which had irregular shape were those with double or triple roots, cracked carrots, curved carrots, damaged carrots, and broken ones and those with upright shapes were considered as regular shape carrot. After imaging, image processing was started by an algorithm programmed in Matlab R2012a medium. Then some shape features such as length, width, breadth, perimeter, elongation, compactness, roundness, area, eccentricity, centroid, centroid non-homogeneity, and width non-homogeneity were extracted. After the selection of efficient features, artificial neural networks and support vector machine were used to classify the efficient features. Results and Discussion The number of neurons in the hidden layers of artificial neural network models were varied to find the optimal model. The highest percentage of the correct classification rate (98.50%) belonged to the structure of 2-10-16, which in fact has 16 neurons in the input layer, 10 neurons in the hidden layer and 2 neurons in the output layer. This model has also the lowest mean squared error and the highest correlation coefficient of the test data, 0.90 and 2.52, respectively. This network was a feed forward back propagation error type and the activation functions in hidden and output layers were Tansig and Perlin, respectively. The correct classification rate of the support vector machine method was 89.62%. The confusion matrix of support vector machine method showed that out of 56 usual samples, 42 specimens were correctly identified but 14 samples were mistakenly classified as unusual carrots. All 79 carrots with unusual shapes were correctly classified. The results obtained from the comparison of the performance of the two methods, the neural network method has a good superiority than the support vector machine for classification. Conclusion In this research, the classification of carrots was based on its appearance. At first the physical characteristics and appearance attributes of the carrot samples were extracted and processed using image processing. Image analysis was included the classification of samples into two usual and unusual shapes, which to classify the extracted properties two methods were used: the artificial neural network (ANN) and support vector machine (SVM). The classification accuracy of the ANN method was higher than SVM. It can be said that the image processing method can be used to improve the traditional method for grading the carrot product in new ways. So, the marketability of the product will be increased, and thus its losses will be reduced. Also, the image processing technique can be used as a simple, fast and non-destructive alternative to other methods of extracting geometric properties of agricultural products. Finally, it can be stated that image processing method and machine vision are effective ways for improving the traditional sorting techniques for carrots.
Research Article
Image Processing
A. Heidari; J. Amiri Parian
Abstract
Introduction Lack of water resources, increasing demands for food, the optimal use of water and land, and food security are of the most important reasons for the development of greenhouses in the country. The benefits of greenhouse cultivation consisted of the possibility to produce off-season, increase ...
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Introduction Lack of water resources, increasing demands for food, the optimal use of water and land, and food security are of the most important reasons for the development of greenhouses in the country. The benefits of greenhouse cultivation consisted of the possibility to produce off-season, increase harvest period, reduce the production costs, increase economic efficiency and etc. Regarding the conditions of the greenhouse, in terms of temperature and humidity, a site is susceptible to contamination with various pests and diseases, which can cause a lot of damages to the products. So, for a high-quality product, identification and timely control of pests are necessary. The need for spraying in a timely manner, with a sufficient number of times, is to have accurate information on the population of pests in a greenhouse environment at different times. Whiteflies, thrips, and aphids are among the most commonly known harmful insects in the world, causing severe damages to greenhouse plants. Materials and Methods Twenty yellow sticky cards were randomly selected in different parts of the greenhouse of cucumbers in the Amzajerd district of Hamadan. From each card, 45 photos were taken with Canon IXUS 230HS digital camera with a resolution of 12.1 Megapixels at a distance of 20 centimeters. Before each image processing, trapped insects were initially identified and counted by three entomologists. At this stage, three types of insects (two harmful insects, whitefly and thrips and non-harmful insect) were identified. Then the images were transferred to Matlab software. The algorithm of identifying and counting the whitefly was the following six steps: Step 1: Convert the original image to the gray level image Step 2: Correcting the effects of non-uniform lighting Step 3: Determine the optimal threshold and convert the gray level image to the binary image Step 4: Remove objects smaller than Whitefly Step 5: Fill the holes in the image Step 6: Counting broken segments The algorithm of identifying and counting the thrips was the following eight steps: Step 1: Convert the original image to the gray level image Step 2: Correcting the effects of non-uniform lighting Step 3: Determine the optimal threshold and convert the gray level image to the binary image Step 4: Prepare image negatives Step 5: Remove objects smaller than the thrips Step 6: Remove the thrips and isolate the rest of the objects Step 7: Split the thrips Step 8: Count the thrips Results and Discussion Relative accuracy, root mean square error (RMSE) and Coefficient of variation of the RMSE of Whitefly counting in image processing system were 94.4%, 15.3 and 5.5% respectively. The results of the T-test between two methods indicated that there was no significant difference between them. The mean relative accuracy, root mean square error (RMSE) and Coefficient of variation of the RMSE of the thrips count in the image processing system were 87.4%, 18 and 5.9% respectively. There was no significant difference between the two methods. Conclusion The proposed image processing algorithm was able to detect whiteflies and thrips with a relative accuracy of 94.5% and 87.4%, respectively. In addition to simplicity, this method has the ability to adapt to different conditions. Also, with some changes in the proposed algorithm, the system will also be able to identify other pests. In order to design an intelligent spray system in the greenhouse, the population of pests needs to be monitored frequently, so the identification and counting of pests will be necessary for the intelligent spray system.
Research Article
S. Rahnama; M. Maharlooei; M. A. Rostami; H. Maghsoudi
Abstract
Introduction Date palm is one of the most valuable horticultural products in Iran, which includes 16% of non-oil exports to the world. Kerman province has the second rank for the cultivation area of date palm in Iran. Having information about the exact cultivated area has gained importance for further ...
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Introduction Date palm is one of the most valuable horticultural products in Iran, which includes 16% of non-oil exports to the world. Kerman province has the second rank for the cultivation area of date palm in Iran. Having information about the exact cultivated area has gained importance for further decision makings. To determine the cultivated area, organizations usually use census which has the disadvantages of high cost, wasting time and labor intensive. The aim of this research was to study the feasibility of using Landsat 8 OLI images to identify and classify the area under date palm cultivation. To accomplish this purpose, four supervised classification methods were evaluated. Materials and Methods The study area was in Bam region located at 200 km southeast of Kerman province. In this research, a total of 14 images of Landsat8 OLI satellite from the study area during fall and winter were downloaded from Landsat official web page. After preliminary inspections for interested classes (Date palm gardens, Lands covered with bare soil and forage crop fields), one of the images that was taken on Jan 14, 2017, was selected for further analysis. After initial corrections and processing, 32 images of alfalfa farms, 32 images of date palm gardens and 32 images of lands covered with bare soil, were selected using GPS data points collected in study area scouting. Shape files of all selected fields were created and utilized for supervised classification training set. The same process was also done for the unsupervised classification method. To evaluate the classification methods confusion matrix and Kappa coefficient were used to determine the true and miss-classified area under date palm cultivation. It is worth mentioning that these factors alone cannot identify the most powerful method for classification and they just give us a general overview to choose acceptable methods among all available methods. To identify the most powerful method among selected methods, confusion matrix and investigating the pixel transfers between classes is the crucial method. Results and Discussion Results of classifications revealed that the overall classification accuracy by using NN, MLC, SVM, MDC, and K-Means were 99.10% (kappa 0.973), 98.77% (kappa 0.975), 98.66% (kappa 0.973), 98.52% (kappa 0.97), and 52.66% (kappa 0.31) respectively. Concerning the confusion matrix in the NN method, the percentage of producer accuracy error in date palm class was 0% and in user, accuracy error was 1.44%. In the review of other methods, the lowest producer accuracy error value in date palm class obtained by NN and SVM methods was 0% and the highest producer accuracy error belonged to MLC method which was 1.35%. Checking the recognition power of other classes showed that in the soil class, the highest producer accuracy error was 2.32% by MDC method and the least one was 0.64% by MLC. For forage class, the highest producer accuracy error was calculated 37.07% by SVM and the least accurate one was 4.92% by MDC. Although the K-Means method with Kappa Coefficient of 0.31 did not have a good classification quality, concerning classes and samples, it successfully could identify date palm according to selective samples with 100% accuracy. Results of calculated date palm area using supervised classification methods versus actual area measurements showed that NN and SVM methods with the coefficient of determination (R2) of 0.9995% and 0.9986% had the highest coefficients. K-Means method with R-square of 0.9228% had a good correlation. In general, all supervised classification methods obtained acceptable results for distinguishing between date palm classes and two other classes. NN and SVM methods could successfully recognize date palm class. K-Means method also could recognize date palm class but the recognition included some errors such as dark clay soil textures which were classified as the date palm. Conclusion In general, overall accuracy and kappa Coefficient alone cannot identify the most powerful method for classifying and these methods just give us a general overview to choose an acceptable percentage of accuracy coefficients among available methods. After the initial selection, to identify the most powerful method of classification the pixel transfer calculations in a confusion matrix would be an acceptable technique.
Research Article
F. Jannatdost; P. Ahmadi Moghaddam; F. Sharifian
Abstract
Introduction Fruits and vegetables play an important role in food supply and public health. This group of agricultural products due to high humidity are perishable and most of them (5 to 50 percent) waste during post-harvest operation. Decreasing and minimizing such waste as "hidden harvest" could be ...
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Introduction Fruits and vegetables play an important role in food supply and public health. This group of agricultural products due to high humidity are perishable and most of them (5 to 50 percent) waste during post-harvest operation. Decreasing and minimizing such waste as "hidden harvest" could be an effective way to save food and increase profitability. Despite the surplus of the fruit production in the country, our position in terms of exportation is not commensurate with production, so measurements and grading on the basis of qualitative parameters such as firmness, taste, color, and shape can influence the marketing and export of fruit. In this research, application of an acoustic test is considered to achieve an effective and economic technology in the field to determine the stiffness of kiwifruit in post-harvest step. The aim of this study is to investigate the stiffness index of kiwifruit and provide a classification algorithm in the post-harvest step by using the non-destructive method of processing impact acoustic signals. Materials and Method In this research, an acoustic-based intelligent system was developed and the possibility of using the acoustic response to classify kiwifruit into soft, semi-soft and stiff categories was studied. 150 samples of Hayward variety of Kiwifruit was used during the 18 days shelf life in controlled conditions of temperature and humidity. Analyses were done in 9 sets per two days. In each analysis, an acoustic test was done by 48 samples in both free fall condition and fall from a conveyor belt. The feature extraction of acoustic signals in both the time domain and frequency domain has done, then the classification of samples was done by using the Artificial Neural Network. After getting the impact signals of stiff, semi-soft and soft samples, stiffness of kiwifruits identification has done by using acoustic features. The stiffness of kiwifruit samples in this study was measured to be 15.9±4.9 (N) by using the Magnes- Taylor test. Finally, samples were classified into stiff, semi-soft and soft by comparison of maximum force and flux of signals amplitude. Results and Discussion The results showed that the features of CF and maximum amplitude in the time domain have high accuracy in kiwifruit classification. The frequency resonances as environmental noises or impact position are out of control in the time domain which causes a decrease in accuracy. So, the ANN by features of time domain has not the acceptable capability to identify the semi-soft samples. The identification of semi-soft samples is not easy because of having same properties of stiff and soft samples. Extracted features of frequency domain have the most capability of correct detection. The optimal network has five neurons in the hidden layer and 0.014782 of mean square error. The accuracy of correct detection of the optimal network was 93.3, 91.3 and 78.3 percent for stiff, semi-soft and soft samples, respectively. Because of using more features in the frequency domain, the classification of all categories was acceptable and identification of semi-soft samples was as good as stiff and soft samples. The results of combined features of time and frequency domain showed that the artificial neural network has less efficiency in comparison with the other two attitudes. The accuracy of identification and classification was decreased by adding the extracted features of the time domain. So achieving the most accuracy in classification is accomplishable just by using the features of the frequency domain. By comparing the results of both free fall and online tests, it is claimed that this research can be industrialized. Conclusion Comparison of all results shows that there was no significant difference in the capability of ANN for identification and classification of the sample in three categories. After all, we can use this method in online sorting of kiwifruits by controlling the vector and position of impaction.
Research Article
S. Khodamoradi; E. Ahmadi
Abstract
Introduction Grape fruit set its fruits and shortly after planting and due to high nutritious value and excellent food quality has been welcomed by many people in the world, but considering its soft tissue and high softening velocity and sensitivity to fungi attack it is known as an extensively vulnerable ...
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Introduction Grape fruit set its fruits and shortly after planting and due to high nutritious value and excellent food quality has been welcomed by many people in the world, but considering its soft tissue and high softening velocity and sensitivity to fungi attack it is known as an extensively vulnerable fruit. One of the most important ways to maintain fruit quality, decrease vulnerably and assist more appropriate storage, is the use of coating method and proper packing of agricultural products and combining these procedures to decrease damages in storage. Edible coatings provide a replacement and fortification of the natural layers at the product surface to prevent moisture losses, gas aromas, and solute movements out of the food, while selectively allowing for controlled exchange of important gases, such as oxygen, carbon dioxide, and ethylene, which are involved in fruit respiration. Chitosan is the most common polysaccharide-based coatings. Chitosan films have been successfully applied as edible material in films and coatings for the quality preservation of different fruit. In this study, the effects of the application of chitosan edible coatings and storage time on some physical, chemical, mechanical and rheological properties of grape were investigated during storage. Materials and Methods Grape fruits were screened for physical damages, fungal infections, and size homogeneity after harvesting from the farm. Then fruits were divided into without coating and fruits with coating. Fruits being coated, prepared in chitosan emulsion and submerged for two minutes and kept at 20°C for one hour for drying the surface coating via airflow. In order to calculate the weight loss, three containers of each grape fruits (treatment and control) collected and after weighing and averaging weight loss were compared to initial weight during storage expressed as a percent. Color intensities were determined using colorimeter samples. In order to determine soluble solids from each sample, refract meter was used and pH amount of each sample was determined. Mechanical traits and fruit stiffness were measured through penetration test using materials test machine Zowick/ Roell having 500 N loadcell in line with the small diameter with concave probe (5 mm diameter), the penetration depth of 2 mm and loading rate of 10 mm s-1. Mechanical traits including stiffness and elasticity module calculated from the force-deformation curve. Viscoelastic materials have the properties of both viscous and elastic materials and can be modeled by combining elements that represent these characteristics. A viscoelastic model, called the Maxwell model which can predict behavior was evaluated. Results and Discussion In this current study, the application of chitosan coating significantly reduced the fresh grape decay. Fruit decay of grape increased with storage time, but the coating reduced the rate of decay with the length of storage. According to the results, the application of these coatings has a positive impact on yield stress and energy of rupture product texture during the storage. Results of variance analysis showed that temperature, coating and storage time has a significant effect (1% level) on some of the engineering properties of the grape. Storage time has a significant effect on elasticity, while the coating does not have a significant effect on this parameter. Finally, results showed that the application of chitosan coating has an effect on relaxation time and stress. So during storage of coated samples these parameters decreased compared to uncoated. Conclusion Edible films and coatings may reduce the moisture transfer, the rate of oxidation and respiration which are considered important to prolong the shelf-life of these products. This investigation showed that the chitosan coatings are effective for grape shelf life extension and retarded the senescence process compared with control. The coat has been as a physical barrier for the gas exchange between the fruit and the environment. It was demonstrated that the coating reduced the loss of firmness and delayed the softening of fruit and texture change.
Research Article
H. R. Gazor; A. Moumeni
Abstract
Introduction High energy consumption and non-uniformity drying in conventional batch type dryer are the common problems in paddy dying industry. Non-uniformity drying causes to kernel breaking chance in the milling process. Using new dryers with better performance can solve the drying problem and energy ...
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Introduction High energy consumption and non-uniformity drying in conventional batch type dryer are the common problems in paddy dying industry. Non-uniformity drying causes to kernel breaking chance in the milling process. Using new dryers with better performance can solve the drying problem and energy saving. In this research, the operation of a re-circulating batch dryer was compared with a fixed bed batch dryer (conventional dryer) for paddy drying. Materials and Methods This research was done in a paddy milling factory in Ferydonkenar and deputy of Rice Research Institute of Iran, in Amol, Mazandaran province. Both re-circulating dryer and conventional batch type dryer were made by Khazar Electric Company in Amol- Iran and they had 5 tonnes capacity. In the re-circulating dryer, ambient air was warmed in the furnace and blown to drying zone inside of grain bin. Natural Gas (NG) was used for air warming in dryers. Warm air absorbed paddy moisture and pushed away from the dryer. Drying temperature ranges for re-circulating dryer and conventional dryer was 48-50 °C and 38-52°C, respectively. The paddy variety was one of the Iranian rice varieties as Tarom and initial moisture content of grains was 21% (w.b), it was decreased using drying to 8-9% (w.b) for milling process. Paddy moisture content was measured each 60-120 min by SUNCUE TD-6 portable moisture tester-Taiwan. Energy consumption calculated by fuel and electrical energy summation in each experiment. Natural Gas and electrical power consumption were measured by Gas and electric counters respectively. Drying time, paddy moisture change trend and energy consumption were investigated for paddy drying in each dryers. Also, milling ratio, breaking percent, whitening degree, and elongation rate after cooking were studied after the milling process for rice dried using national standard methods and deputy of Rice Research Institute facilities in Amol. Experimental samples were 150 g and husker (SATAKE THU35B), a whitener (SATAKE TMU05) and KETT C-100 were used for husking, whitening and whiteness degree, respectively. All Experiments were done with three replication and data analyzed using T- student method in 5% probability. Results and Discussion Results showed that re-circulating dryer caused to reduce 54.12 percent in drying time and energy saving in paddy drying in compare with conventional paddy dryers. The trend of moisture content changes was longer and over-drying occurred in lower layers in conventional batch type dryer compared to re-circulating dryer. Paddy drying was 20 hours more in batch type than the re-circulating dryer. It caused wasting time and energy consumption. Specific energy consumption for water evaporating in the re-circulating batch dryer was 3.9 MJ/kg water and it was 76.25 percent less than fixed bed batch dryer. After the drying process in both dryers, paddy moisture content was in range 8-9 percent (% w.b). Using re-circulating dryer did not have a significant effect on milling yield but it had a significant effect on broken rice. Broken rice decreased by 5 percent after the milling process when paddy dried by re-circulating. Uniformity of layers drying and normal heat stress in rice kernels in re-circulating dryer reduced broken rice in the milling process. Whiteness degree of rice dried using fixed bed dryer was 2.4 percent more than the re-circulating batch dryer. Also, rice dried had more elongation rate about 6.2 percent after cooking when paddy dried by conventional dryer. Conclusion Results of this paper showed that using of re-circulating dryer would decrease time and modify energy consumption in paddy drying. The costs of installation for the re-circulating batch dryer was about 5.3 times more than fixed bed batch dryer. It seems too expensive at first but considering energy and time-saving in the drying process and suitable effect on decreasing grain breakage in paddy milling, using of the re-circulating batch dryer is recommendable in rice milling factories.
Research Article
M. Ghasemi-Nejad Raeini; E. Bougari; F. Azadshahraki
Abstract
Introduction Rice is one of the most important cereal grains in the world. Milling is one of the most important phases of the paddy processing that affects the quality and quantity of the product. Postharvest losses include threshing, drying, transportation and milling contains about 30–40% of ...
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Introduction Rice is one of the most important cereal grains in the world. Milling is one of the most important phases of the paddy processing that affects the quality and quantity of the product. Postharvest losses include threshing, drying, transportation and milling contains about 30–40% of total produced rice in developing country. Parboiling increases the mailing efficiency of rice from 51% to 80%, protein, fat and ash content. Champa variety is one of the most important varieties of rice in the southwest of Iran and has low milling quality in spite of its flavor and aroma. This study was conducted to assess increasing the quality of Champa rice milling phase by parboiling method. Materials and Methods This study was conducted to assess the increasing quality of Champa rice milling phase by parboiling method in the growing season of 2016 in Lordegan city. Paddies were prepared from a rice farm in Lordegan city. Parboiling treatments consisted of three soaking temperatures (35, 55 and 75°C) and two steaming times (15 and 25 minutes) at a steam temperature of 110 °C. This study was performed in a factorial experiment based on a completely randomized design in three replications. Parboiling process included soaking, steaming, drying and whitening. Bain Marie was used to keep the water temperature constant in two phases of soaking and steaming. Samples were placed in a oven to decrease the humidity in the drying phase. Breakage percentage, loss of solid material, milling efficiency, whiteness degree and the ratio of length to width were measured in raw and baked rice in all samples. Results and Discussion Breakage in control treatment (non-parboiling) was 19.38%. The lowest breakage percentage (4.03%) was obtained in parboiling treatment (soaking temperature of 55 °C and a steaming time of 15 minutes). Parboiling improved milling efficiency and reduced loss of solid materials. Highest milling efficiency (67.11%) was obtained in a soaking temperature of 55 °C and steaming time of 25 minutes. The lowest amount of loss of solid materials (1.74%) was obtained in a soaking temperature of 75 °C and steaming time of 25 minutes. The highest ratio of length to width (2.46) and the highest whiteness degree (76.54%) was obtained in no parboiling treatment. There was no significant difference in water absorption parameter between parboiling treatment and non-parboiling treatment. Conclusion Champa rice variety has a very good flavor and aroma but did not have good appearance and its breakage percentage is not good. Parboiling reduces the breakage and improves the appearance in raw and baked rice. Parboiling had a lot of positive effects on the milling quality of this rice cultivar. The best treatment (soaking temperature of 55 °C and steaming time of 25 minutes) reduced breakage percentage (by 79%) and loss of solid materials (by 37%) and increased milling efficiency (by 2%) in comparison with control treatment (non-parboiling). Overall, parboiling reduced rice streaking during baking by improving the quality attributes of paddies and finally improved the rice shape.
Research Article
G. Khoobbakht
Abstract
Introduction The researchers have been currently focused on replacing fossil fuels by biofuels to reduce dependence on fossil fuels. Biofuels provide low greenhouse emissions with the reduction of oil import. The biofuels can play an important role economically becomes more clear when their ...
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Introduction The researchers have been currently focused on replacing fossil fuels by biofuels to reduce dependence on fossil fuels. Biofuels provide low greenhouse emissions with the reduction of oil import. The biofuels can play an important role economically becomes more clear when their relatively developed agricultural sector is taken into account. Bioethanol, biodiesel and to a lesser extent pure vegetable oils are recently considered as most promising biofuels. Since 19 century, ethanol has been used as a fuel for the diesel engines. The cost of bio-diesel for IC engine is slightly greater than that of diesel oil. The specific fuel consumption, a function of the engine speed, is higher in bio-diesel than in diesel oil. The results previously of Bench-test indicated that the average value of SFC for bio-diesel was 17% greater than that of diesel oil. As for the properties of biodiesel, the lower heating value, higher density and higher viscosity play a primary role in engine fuel consumption for biodiesel. Most of the authors, who agreed that fuel consumption increased for biodiesel compared to diesel, contributed to the loss in the heating value of biodiesel. Of course, some authors only explained the increased fuel consumption as the result of the higher density of biodiesel, which causes a higher mass injection for the same volume at the same injection pressure. Materials and Methods The equipment and instruments used in the present research were a diesel engine (OM 314), a dynamometer, a dynamometer control panel and a fuel tank. A four-cylinder direct injection diesel engine, model OM 314, made by Idem Company, Tabriz, Iran, was used to conduct the experiments. The fuel used in the present research was from waste oil. Ethanol was also used to feed the engine. The blends of diesel–ethanol–biodiesel were prepared on a volumetric basis. The experiments were conducted based on the response surface methodology and using Central Composite Rotatable Designs (CCRD). The response surface methodology, as one of the best methods to optimize processes and determine the effect of different variables on the responses, has special popularity among researchers. Applied research design in this study was CCRD that has the most application among other designs of the method. Independent variables were different ratios of ethanol, biodiesel, and diesel, engine load, and engine rotational speed and responses were included engine brake specific fuel consumption. Results and Discussion The P-values for both total and prediction models of specific fuel costs were less than 0.01. This result showed that the models statistically have high abilities to predict the impacts of independent variables on specific fuel costs at 1% probability level. The linear, quadratic and interaction of the overall model had a P-value less than 0.05 that indicated their statistical validity. The specific fuel costs decreased for all blends by increasing the engine load. The reduction of specific fuel costs was more aggressively observed in low loads. With increasing engine rotational speed, the specific fuel costs were increased at low loads and at middle and high loads it was decreased and then increased. The increasing of volume ratio of biodiesel in the blended fuels, specific fuel costs were increased. By increasing the volumetric ratio of ethanol and biodiesel, specific fuel costs were increased due to lower calorific value and the direct relationship of this variable with brake power compared to that of diesel fuel in all test conditions and all fuel blends. By increasing of biodiesel ratio in the blended fuels, the specific fuel costs were increased at the low percentage of ethanol ratio. But by the increase of ethanol ratio the specific fuel consumption firstly was increased and then slightly decreased at high levels of biodiesel. Conclusion The minimum of the specific fuel costs (580 R kW-1h-1) occurred at full load and engine rotational speed of 2139 rpm for pure diesel (B0E0D100). Also, the maximum of specific fuel consumption was obtained by 9951 R kW-1h-1 at 20% engine load and rotational speed of 2800 rpm and for a fuel blend containing 0.8 l biodiesel, 0.4 l ethanol and 1l diesel (B45.2E36.6D18.2).
Research Article
A. Vaysi; A. Rohani; M. Tabasizadeh; R. Khodabakhshian; F. Kolahan
Abstract
Introduction In recent years, with development of industrial products with complex and precise systems, the demand for CNC machines has been increasing, and as its technology has been progressed, more failure modes have been developed with complex and multi-purpose structures. The necessity of CNC machines’ ...
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Introduction In recent years, with development of industrial products with complex and precise systems, the demand for CNC machines has been increasing, and as its technology has been progressed, more failure modes have been developed with complex and multi-purpose structures. The necessity of CNC machines’ reliability is also more evident than ever due to its impact on production and its implementation costs. Aiming at reducing the risks and managing the performance of the CNC machine parts in order to increase the reliability and reduce the stop time, it is important to identify all of the failure modes and prioritize them to determine the critical modes and take the proper cautionary maintenance actions approach. Materials and Methods In this study, conventional and fuzzy FMEA, which is a method in the field of reliability applications, was used to determine the risks in mechanical components of CNC lathe machine and all its potential failure modes. The extracted information was mainly obtained by asking from CNC machine experts and analysts, who provided detailed information about the CNC machining process. These experts used linguistic terms to prioritize the S, O and D parameters. In the conventional method, the RPN numbers were calculated and prioritized for different subsystems. Then in the fuzzy method, first the working process of the CNC machine and the mechanism of its components were studied. Also, in this step, all failure modes of mechanical components of the CNC and their effects were determined. Subsequently, each of the three parameters S, O, and D were evaluated for each of the failure modes and their rankings. For ranking using the crisp data, usually, the numbers in 1-10 scale are used, then using linguistic variables, the crisp values are converted into fuzzy values (fuzzification). 125 rules were used to control the output values for correcting the input parameters (Inference). For converting input parameters to fuzzy values and transferring qualitative rules into quantitative results, Fuzzy Mamdani Inference Algorithm was used (Inference). In the following, the inference output values are converted into non-fuzzy values (defuzzification). In the end, the fuzzy RPNs calculated by the fuzzy algorithm and defuzzified are ranked. Results and Discussion In conventional FMEA method, after calculating the RPNs and prioritizing them, the results showed that this method grouped 30 subsystems into 30 risk groups due to the RPN equalization of some subsystems, while it is evident that by changing the subsystem, the nature of its failure and its severity would vary. Therefore, this result is not consistent with reality. According to the weaknesses of this method, fuzzy logic was used for better prioritization. In the fuzzy method, the results showed that, in the 5-point scale, with the Gaussian membership function and the Centroid defuzzification method, it was able to prioritize subsystems in 30 risk groups. In this method, gearboxes, linear guideway, and fittings had the highest priority in terms of the criticality of failure, respectively. Conclusion The results of the fuzzy FMEA method showed that, among the mechanical systems of CNC lathe machine, the axes components and the lubrication system have the highest FRPNs and degree of criticality, respectively. Using the fuzzy FMEA method, the experts' problems in prioritizing critical modes were solved. In fact, using the linguistic variables enabled experts to have a more realistic judgment of CNC machine components, and thus, compared to the conventional method, the results of the prioritization of failure modes are more accurate, realistic and sensible. Also, using this method, the limitations of the conventional method were reduced, and failure modes were prioritized more effectively and efficiently. Fuzzy FMEA is found to be an effective tool for prioritizing critical failure modes of mechanical components in CNC lathe machines. The results can also be used in arranging maintenance schedule to take corrective measures, and thereby, it can increase the reliability of the machining process.
Research Article
H. Rahmanian- Koushkaki; S. H. Karparvarfard
Abstract
Introduction Pneumatic conveying is a continuous and flexible material handling method which uses positive or negative air pressure to convey materials in pipe. This conveying system is generally divided into two groups of dilute and dense phase. The purpose of this research was to create spiral grooves ...
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Introduction Pneumatic conveying is a continuous and flexible material handling method which uses positive or negative air pressure to convey materials in pipe. This conveying system is generally divided into two groups of dilute and dense phase. The purpose of this research was to create spiral grooves inside horizontal pipes which transfer granular materials under dense phase. Also, the performance of these pipes was compared with control pipes. Finally, friction factors obtained in this research were compared to the previous study. Materials and Methods To create spiral grooves inside the pipes, a broaching machine was designed and developed. Then, by connecting the broached pipes to a pneumatic conveying test- rig of granular materials, the performance of these pipes was compared with control pipes. The specifications of the broaching machine and test-rig were as follow. Broaching machine: The machine included chassis, an electromotor with one hp power, a reduction gearbox, a ball screw for converting rotational motion to linear motion, a spiral shaft, a guide with three bolls, broaches and inverter. Cutting operations and creating grooves inside the pipes were done using broaches. These broaches had two angles, attack angle of 15 degrees and a clearance angle of 10 degrees. The spiral angle of broaches was 30 degrees, the spiral pitch was 260 mm, the width of each groove was 1.5 mm, and a number of teeth were 20. Test- rig: The main components of the test- rig were the air compressor, blow tank, conveying pipes, solid discharge control valve (SDCV), receiving hopper, orifice plate flow meter, pressure transducers, and single point load cell. The compressor was a piston- type, the air flow rate was 405 L min-1 and maximum pressure was 12 bar. For a continuous flow of air and material mixture into conveying pipes, a blow tank was used. To transfer material from blow tank to pipes, a 90-degree bend with a radius of 250 mm and an inner diameter of 40 mm was used. The inner diameter of pips was 40 mm, the thickness was 5 mm and was selected from ABS. In order to measure static pressure of air along the pipes, 10 holes of one mm diameter were drilled on the surroundings of the pipes at intervals of one meter. Then, on each of these holes, a polyethylene bushing was placed. Pressure transducers were threaded on the top of these bushings. A solid discharge control valve was placed at the end of the flow line to control the flow of materials in a dense and continuous phase and to prevent material acceleration. The materials were introduced into the receiving hopper after leaving the valve. To measure the volume flow rate of air, an orifice plate with D and D/2 tapping was used. The pressure transducers were Hogller. For measuring the mass of the materials entering the receiving hopper, a single point load cell (Zemic L6G) was installed under the hopper. A data acquisition system based on ARM microcontroller was used to record output signals from transducers. The treatments were four levels of groove depth (0, 0.35, 0.55 and 0.9 mm), three levels of air pressure (1, 2 and 3 bar) and three levels of pipe length (3, 6 and 9 m). The transferred material was considered as mung bean. Results and Discussion The results of ANOVA showed that the main effects of groove depth, pipe length, and air pressure were significant on the mass flow rate of transmitted mung bean and solid friction factor at 1% probability level. The results indicated that the maximum mass flow rate and minimum friction factor were observed at a pipe length of 3 m, the groove depth of 0.90 mm and air pressure of 3 bar. Minimum mass flow rate and maximum friction factor were observed at pipe length of 9 m, the groove depth of 0 mm (smooth pipe) and air pressure of 1 bar. Conclusion The results showed that the existence of spiral grooves within horizontal conveying pipes would increase the mass flow rate of the mung bean and reduce the solid friction factor of the mung bean and inner wall of pipes.
Research Article
F. Akhavan; S. Kamgar; A. A. Golneshan
Abstract
Introduction Pollinating elevated date palms has been a challenging problem for many years. A few types of equipment have been designed and manufactured in the last fifty years, using either low pressure or compressed air to overcome this problem. However traditional pollination is still the most popular ...
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Introduction Pollinating elevated date palms has been a challenging problem for many years. A few types of equipment have been designed and manufactured in the last fifty years, using either low pressure or compressed air to overcome this problem. However traditional pollination is still the most popular method in none-mechanized and small date farms. In the present research, a light portable electrical pollen-duster has been developed and tested. Materials and Methods A powerful ducted fan, equipped with a speed controller and a servo tester was made and installed on the top of a 6 -7.7m long carbon fiber boom, to provide a high volume rate of air flow for pollination. A small part of air flow is conducted through a by-pass tube to hit the pollen/pollen-flour blend in the pollen bin and suspend it. The rest of air flow, passing through a venturi, is responsible to provide a relative vacuum at the opening of pollen bin to pull up the suspended pollen and throw it toward the date palm crown. Although plain flour is traditionally used as filler in mechanical pollinators, however, SEM imaging showed that pasta flour particles are bigger than plain flour particles and are closer in size to pollen particles. Also, Repose angle of date pollen was measured as 38º where plain flour and pasta flour showed 44.9º and 40.7º respectively (figures 6 and 7). So, Pasta flour was used instead of plain flour to make a blend. To provide a low-weight pollen-duster, wires extending from ducted fan to its actuating equipment (battery, servo tester, and speed controller) were selected to be a combination of 2.5mm2 (3 meters) and 1.5mm2 (3 meters) types in the standard boom. This lowered the applied force on the operator’s hand by 33% (Figure 5 and equations 4 and 5). Evaluation of the pollen-duster has been performed in Khoor town in Isfahan province of Iran. Eighteen trees of Kabkab variety were pollinated in a completely random test with 6 treatments (five mechanical treatments compared with traditional treatment). Mechanical treatments were using 0.5, 1.5 and 2.5g pure pollen and 2 and 6g pollen-flour blend (in 1:3 ratio) in each of the three weekly repetitions. After 8 weeks, in kimri stage, normal, abnormal (non- pollinated), and dropped fruits on some randomly selected strands were counted to determine pollination as well as fruit setting efficiencies. Fruits weight in each treatment was measured on some random fruits in the Tamar stage. A new index; called "pollen consumption index", was introduced to provide a measure of pollen consumption rate in order to prevent redundant pollen consumption which has no sensible effect on the yield. Results and Discussion Calculated pollination and fruit setting efficiencies did not show a significant difference in all treatments, convincing that the traditional method could be replaced by pollen-duster without any yield difference. It offers benefits of lower pollen consumption; more trees pollinated in a day and also safer pollination due to reducing number of trees climbing. It was also shown that a tree could be pollinated properly with 0.5g pollen, so each hectare of date farm (120 trees) needs almost 180g pollen for all three replications, almost 1/4 of Perkins consumption report and 1/3 of Mostaan for three replications. Fruits weights of two pollen-flour treatments were significantly lower than others. As there is not any report available on the effect of the presence of flour or concentration of pollen on date fruits weights, so with the available data no definite reasoning can be made. Conclusion The developed pollen-duster could be used instead of the traditional date palm pollination method with the same fruit set and lower pollen consumption. The weight of the fruits in pollen-flour treatments `was lower than pure pollen and traditional treatments.
Research Article
A. Ziaaddini; H. Mortezapour; M. Shamsi; A. Sarafi
Abstract
Introduction Greenhouse cultivation has been increased in response to population growth, reduction in available supplies and arable lands and raising the standards of living. The quality and quantity of the products are profoundly affected by the greenhouse temperature. Therefore, providing an appropriate ...
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Introduction Greenhouse cultivation has been increased in response to population growth, reduction in available supplies and arable lands and raising the standards of living. The quality and quantity of the products are profoundly affected by the greenhouse temperature. Therefore, providing an appropriate heating system is an elementary requirement for greenhouse cultivation. A number of factors such as glazing material, greenhouse configuration, product type, and climate conditions should be considered to design a greenhouse heating system. Due to the environmental concerns associated with the fossil fuels, renewable energy-powered heating systems such as geothermal, solar and biomass- are increasingly considered as the alternative or supplementary to the traditional fossil fuel heating equipment in greenhouses. In this way, a number of researchers have developed different greenhouse heating systems to reduce fossil fuel consumption. In Iran, because of appropriate available solar irradiance, the solar heating systems can be efficiently employed for greenhouse cultivation. A compound solar greenhouse heating system was experimentally and analytically investigated in the present study. To verify the obtained heat transfer equations, a set of experiments were carried out at Biosystems Engineering Campus of the Shahid Bahonar University of Kerman. Materials and Methods The designed system was comprised of a Parabolic Trough solar Collector (PTC), a dual-purpose modified Flat Plate solar Collector (FPC) and a heat storage tank. The modified FPC was located inside the greenhouse to act as a heat exchanger to transfer the stored heat to the greenhouse atmosphere during the night. The FPC also collects the solar radiations during the sunshine hours to enhance the thermal energy generation. Heat transfer equations of the PTC and the FPC were written and the useful energy gain of the heating system was determined at the quasi-static condition during the day. Experimental verification of the analytical models was conducted using regression coefficient (r) and root mean square percent deviation (e) criteria as follows: where Xi and Yi are respectively the ith analytical and experimental data and n shows the number of observations. Exergy analysis of the PTC and the FPC were carried out and the effect of the different fluid flow rates through the PTC on the exergy efficiency of the different components was investigated using the experimental data. Results and Discussion Increasing the fluid flow rate increased outlet temperature of the PTC due to the increase in heat removal factor and inlet temperature; whereas, caused a reduction in outlet temperature of the FPC. Since the thermal efficiency of the PTC improved with the fluid flow rate, the PTC fraction enhanced when the flow rate increased from 0.5 to 1.5 kg min-1. However, the PTC fraction values were less than 50% and sometimes have dropped below zero. The exergy efficiency of the PTC improved with increasing the flow rate. The reason was that the difference between the inlet and outlet temperatures of the PTC increased with the flow rate at the similar conditions of solar irradiance and ambient temperature. The highest exergy efficiency of the FPC was observed at the flow rate of 0.5 kg min-1. Conclusion The results of the study revealed that: There was a suitable agreement between the obtained analytical expressions and the experimental data based on root mean square percent deviation and regression coefficient criteria. The highest stored energy in the tank was around 40.02 MJ at the flow rate of 0.5 kg min-1. Increasing the flow rate improved the PTC exergy efficiency.
Research Article
F. Afsharnia; A. Marzban
Abstract
Introduction Given the risk management and improving the process, reliability is important in operations and production management, especially agricultural process. Failure modes and effects analysis (FMEA) is regarded as one of the most powerful methods in this area. High applicability and proper analyzability ...
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Introduction Given the risk management and improving the process, reliability is important in operations and production management, especially agricultural process. Failure modes and effects analysis (FMEA) is regarded as one of the most powerful methods in this area. High applicability and proper analyzability of FMEA have caused to be among the most important techniques of systems for risk analysis and safety improvement. Risk management in all sectors is important, especially in agricultural sector. Sugarcane is one of the industrial crops used as raw material for several major and minor industries. In Iran, this crop is cultivated by sugarcane agro-industry companies. The sugarcane trailers were used to transport harvested sugarcane from farm to mill in these companies. There are many problems to milling it on time. One of the most important risks involved in sugarcane transportation is the delays encountered in this process which can affect the quality and quantity of the product. Delay in milling of the harvested sugarcane is caused by various reasons in agro-industry units including factory downtime, breakdowns of tractors at factory gate, tractor accident in factory yard and staff shift changes creating long queues. So, considering and using risk management techniques and eliminating risk factors can be an effective step to increase the efficiency of this process. Materials and Methods This research was carried out on Sugarcane and By-Products Development Company of Khuzestan. At first, the sugarcane transport operations and used equipment were investigated through an interview with experts in the safety and technical sectors and engineers of the Sugarcane and By-Products Development Company of Khuzestan and the study of related books in 2017. After that, the defects and errors of each equipment that caused technical problems and problems in other equipment, as well as the occurrence of injuries and human casualties were identified. Finally, the risks were written for valuation in the FMEA method paper. In this research, risk pricing was based on the Brainstorming method. Risk evaluation is based on the ranking of the effect severity, the risk occurrence probability and the degree of risk detection available in the FMEA method. In this research, analytical network process (ANP), a modern and powerful method in the decision-making field, has been used in combination with FMEA (FMEA-ANP) for defeating the shortcomings. FMEA-ANP considers mutual relationships of hazardous factors, and by offering a certain structure, develops a systematic and flexible view in risk management scope. The suggested method deploys a simple concept of risk priority number and assigns different importance in the form of power for each factor. The resulted RPN will cope better with the system, in which it is applied. This method provides a more accurate analysis of risk and, consequently, more efficient and effective actions, causing attainment and maintenance of more desirable reliability. Results and Discussion The results of FMEA-ANP model indicated that the mill equipment in the sugar factory is the most important delayed factor (failure) in the sugarcane transformation. For this reason, the basis failure causes in the sugar factory has been carefully investigated and it has been concluded by experts' opinions that factory mill and the conveyers failures are important causes of the delay in this process, respectively. Based on statistical analysis, 73.15% of the factory downtimes were related to mill and ranked as first compared with the other risk factors. Among the conveyors, the most damage was related to the inlet conveyor to the first mill and 49% of conveyors failures occurred in this conveyor. Conclusion This research validated the application of FMEA-ANP for the rational organization of the harvest-transport complex. According to this investigation, the probable downtimes and delays can be prevented by implementing the optimal preventive repair and maintenance planning in the sugar factory, and in particular on the factory mill equipment. In addition, efforts to adapt the speed of harvesting and the speed of delivery by the factory can be effective in reducing the delivery delay time by the factory.
Research Article
Modeling
H. Zaki Dizaji; H. Bahrami; N. Monjezi; M. J. Sheikhdavoodi
Abstract
Introduction The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. ...
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Introduction The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. Each agronomist wants to know how much yield to expect as soon as possible. The aim of this study was to determine the performance of C5.0 and QUEST algorithms to predict the yield of sugarcane production in Amir-Kabir agro-industry Company of Khuzestan province, Iran. However, the working method described in this paper is applicable to other geographical areas and other kinds of crops. Materials and Methods The data for the study were collected from Amir-Kabir agro-industry Company. The data is obtained from 2012 to 2016 years. The study area is located in Khuzestan Province which is a major agricultural region in Iran. The geographical location of the study area is between latitudes 31° 15′ to 31° 40′ north and longitudes 48° 12′ to 48° 30′ east. It covers an area of about 12000 ha. The average elevation of the study area is 8m above sea level. Mean annual rainfall within the study area is 147.1mm, the mean annual temperature is approximately 25°C and the mean soil temperature at 50cm depth is 21.2°C. The used data were obtained from a survey with 15 variables carried out on 1201 sugarcane farms. Variables used in the study of data mining can be divided into two categories: target variable and predictor variables. The variable of yield was used as the target variable (dependent) and other variables as predictor variables (independent). In two models, the input data included crop cultivar, month of harvest, chemical fertilizer (Nitrogen), chemical fertilizer (Phosphate), age (plant or ratoon), times irrigation, ratio of surface spraying, soil texture, soil electrical conductivity (EC), water consumption per hectare, drain, farm management, crop duration, area, and yield-category. The study was included in 1201 farms. The necessary data were collected and pre-processing was performed. We propose to analyze different decision tree methods (C5.0 and QUEST). Results and Discussion First, decision tree methods were analyzed for variables. Then, according to C5.0 method (error rate 0.2319 for the training set and 0.3306 for test set) performed slightly better than another method in predicting yield. Crop cultivar is found that an important variable for the yield prediction. 24 rules were found in this study, C4.5 showed a better degree of separation. The measured prediction rate of C5.0 was correct: 76.81% and wrong: 23.19% in the training data, and correct: 66.94% and wrong: 33.06% in the test data. The prediction rate of QUEST was correct: 68.25% and wrong: 31.75% in the training data, and correct: 70.83% and wrong: 29.17% in the test data. Using the training data comparison between the model types showed that the C5.0 model produces a more accurate prediction model and was, therefore, the model to use. Using the testing data in comparison with the model types showed that the QUEST model produced a more accurate prediction model. The results of our assessment showed that C5.0 and QUEST algorithms were capable to produce rules for sugarcane yield. Therefore, our proposed methods as an expert and intelligent system had an impressive impact on sugarcane yield prediction. Conclusion In today's conditions, agricultural enterprises are capable of generating and collect large amounts of data. Growth of data size requires an automated method to extract necessary data. By applying data mining technique it is possible to extract useful knowledge and trends. Knowledge gained in this manner may be applied to increase work efficiency and improve decision making quality. Data mining techniques are directed towards finding those schemes of work in data which are valuable and interesting for crop management. In this research, decision tree algorithms (C5.0 and QUEST) were used. This classification algorithm was selected because it has the potential to yield good results in prediction and classification applications. This study was performed to present a model-based data mining to predict sugarcane yield in 2012-2016. The 24 classification rules generated from the C5.0 decision tree algorithm have great practical value in agricultural applications. The results showed the QUEST and C5.0 decision tree algorithms produced the best prediction accuracy. Sensitivity analysis results indicated that crop cultivar was the most important variables. It was observed that efficient technique can be developed and analyzed using the appropriate data, which was collected from Khuzestan province to solve complex agricultural problems using data mining techniques (decision tree). The decision tree has been found useful in classification and prediction modeling due to the fact that it can capability to accurately discover hidden relationships between variables, it is capable of removing insignificant attributes within a dataset.
