Mahmoud Omid | University of Tehran (original) (raw)

Papers by Mahmoud Omid

New spectral absorption photometry methods are introduced to estimate chlorophyll (Chl) content o... more New spectral absorption photometry methods are introduced to estimate chlorophyll (Chl) content of corn leaves by smart phones. The first method acquires light passing through a leaf by smartphone camera, compensating for differences in illumination conditions. In order to improve performance of the method, spectral absorption photometry (SAP) with background illumination has been considered as well. Data were acquired by smartphone camera in Iowa State University maize fields. Various indices were extracted and their correlation with Chl content were examined by Minolta SPAD-502. Hue index in SAP reached R 2 value of 0.59. However, with light-aided SAP (LASAP), R 2 of 0.97 was obtained. Among traits, the vegetation index gave the most accurate indication. We can conclude that the high performance of LASAP method for estimating Chl content, leads to new opportunities offered by smart phones at much lower cost. This is a highly accurate alternative to SPAD meters for estimating Chl content nondestructively.

Computers and Electronics in Agriculture

A new android app for smartphones to estimate chlorophyll content of a corn leaf is presented. Co... more A new android app for smartphones to estimate chlorophyll content of a corn leaf is presented. Contact imaging was used image acquisition from the corn leaves. In this method, the light passing through the leaf is captured directly by a smartphone camera. This approach would eliminate the needs for background segmentation and other pre-processing tasks. To estimate SPAD (Soil Plant Analysis Development) values, various features were extracted from each image. Then, superior features were extracted by stepwise regression and sensitivity analysis. The selected features were finally used use as inputs to the linear (regression) and neural network models. Performance of the models was evaluated using the images taken from a corn field located in West of Ames, IA, USA, with Minolta SPAD 502 Chlorophyll Meter. The R2 and RMSE values for the linear model were 0.74 and 6.2. The corresponding values for the neural network model were 0.82 and 5.10, respectively. Finally, these models were suc...

Journal of Cleaner Production, 2013

Application of tractors in farming is undeniable as a power supply. Therefore, performance model ... more Application of tractors in farming is undeniable as a power supply. Therefore, performance model for evolving parameters of tractors and implements are essential for farm machinery, operators and manufacturers alike. The objective of this study was to assess the predictive capability of several configurations of ANNs for performance evaluating of tractor in parameters of drawbar power, fuel consumption, rolling resistance and tractive efficiency. A conventional tillage system which included a moldboard plow with three furrows was used for collecting data from MF285 Massey Ferguson tractor. To predict performance parameters, ANN models with back-propagation algorithm were developed using the MATLAB software with different topologies and training algorithms. For drawbar power, the best result was obtained by the ANN with 6-7-1 topology and Bayesian regulation training algorithm with R2 of 0.995 and MSE of 0.00024. The ANN model with 6-7-1 structure and Levenberg-Marquardt training algorithm had the best performance with R2 of 0.969 and MSE of 0.13427 for TFC prediction. The 6-8-1 topology shows the best power for prediction of AFC with R2 and MSE of 0.885 and 0.01348, respectively. Also, the 6-10-1 structure yielded the best performance for prediction of SFC with R2 of 0.935 and MSE of 0.012756. The obtained result showed that the 6-7-1 structured ANN with Levenberg-Marquardt training algorithm represents a good prediction of TE with R2 equal to 0.989 and MSE of 0.001327. The obtained results confirmed that the neural network can be able to learn the relationships between the input variables and performance parameters of tractor, very well.

The objective of this study is to use a Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and geograph... more The objective of this study is to use a Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and geographical mapping models using Geographical Information System (GIS) to locate the most appropriate sites for solar energy farms in Shodirwan region in Iran. GIS interpolation showed that annual solar insolation in Shodirwan is very good and can be used for potential solar farm locations. The average of solar insolation in the region is 5.12 kWh/m2/day annually. Results showed that 18.25% of the Shodirwan area is exploitable as solar farms. With a conversion efficiency of 10% and area factor of 70%, annual electricity production for the exploitable area is roughly 16100 GWh. Land suitability analysis for solar farms implementation was carried out and overlay results obtained from the analysis of the resultant maps showed that 13.98% and 3.79% of the total land area demonstrate high and good suitability levels, respectively. The total electricity generation potential from both highly and good suitability levels in Shodirwan region was about 15,690 GWh annually.

The incorporation of environmental criteria into the conventional supplier selection practices is... more The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of three popular multi-criteria supplier selection methods in a fuzzy environment. The incorporation of fuzzy set theory into TOPSIS, VIKOR and GRA methods is thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the agri-food industry. Our comparative analysis for this case study indicates that the three fuzzy methods arrive at identical supplier rankings, yet fuzzy GRA requires less computational complexity to generate the same results. Additional analyses of the numerical results are completed on the normalization functions, distance metrics, and aggregation functions that can be used for each method.

Journal of American …, 2011

Olive oil is one of the most important agricultural crops due to its digestive properties and eco... more Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However , olive oil production is a costly process which causes an expensive price of the final product. The most job-bery ways during olive oil production consist of mixing other oils such as maize, sunflower and soya oil into the olive oil. So, the aim of this study was to develop a dielectric-based system to detect adulteration in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Linear Discrimi-nant Analysis (LDA) was developed. A set of 15 samples of olive oil, sunflower oil and canola oil which mixed with different ratio of adulteration, were used for calibration and evaluation of developed system. For each sample , 25 iterations were performed. Regarding results, the highest error rate was for a sample containing 60% olive oil-40% canola oil. In general, 7 iterations failed to be properly recognized. Regarding to accuracy indexes, spec-ificity and sensitivity, the system had the minimum error for a mixed sample (60% olive oil-40% canola oil), spec-ificity and sensitivity were obtained as 98% and 100%, respectively and accuracy was obtained as 72%, which was the weakest value. Finally, regarding mean value table for all sample, accuracy reached to 97%. Results showed the developed technique has a good capability of detecting impurities in olive oil. It is concluded from obtained results that the developed system revealed an acceptable adulterated detection in oil production.

The purpose of this study was to quantify the spatial and technological variability in life cycle... more The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran. Methods The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N2O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat. Results and discussionThe average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO2-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO2-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of −2/3. This indicates that the carbon footprint of durum wheat production (in kg CO2-eq kg−1) typically decreases by 67% with a 100% increase in yield (in kg ha−1 year−1). Conclusions Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.

Better growing conditions are achieved in greenhouses by maintaining a higher internal ambient a... more Better growing conditions are achieved in greenhouses by maintaining a higher internal ambient as compared with external ambient temperature. A computer-based control and monitoring system which provides visualization, control and coordination of temperature and humidity in a greenhouse was recently developed. To validate the system performance, a number of experiments were carried out during the autumn of 2003. In this paper, one of the experimental results conducted from 10 to 12 a.m. on December 7, 2003, in the city of Karaj, is presented and discussed. The system was tested for two modes of operation: the uncontrolled mode of operation and the controlled mode. Four sensors, three for temperature measurements and one for relative humidity measurements, were installed inside and outside. During the first hour and a half the system was tested as a data-acquisition system, ie, only data from the sensors were recorded and monitored on the screen with no operation of fans, sprayer and other installed environmental systems in the greenhouse. For the last 20 min of the experiment, inside air temperature was controlled by the system. The result on temperature measurements shows that external ambient temperature, Tout, is always less than the inside temperature. This is attributed to the solar radiation entering the greenhouse through transparent plastic and being trapped there. We also observed fluctuations on temperature profile inside the greenhouse. This is caused by natural conditions such as surface evaporation within the greenhouse, solar radiation, external ambient temperature and rapid weather changes during the time of the experiment. It was also found that the rate of change of temperature increase in the upper part, Tup, ie near plastic cover, is higher than that of the plants height, Tmid. This rise in vertical temperature gradient is partly due to the different amount of solar incident radiation being received at the locations of sensors. This trend proves the effectiveness of our polytube system, a re- circulating fan with an attached perforated polyethylene tube, in guiding the air toward the plant root zone. For the last 20 min of the experiment, the controller was put into action. The overall per- formance of the system in maintaining the temperature within a given range, around the set point, is found to be satisfactory. The time constant of the fan and heater combination was short, about 10 min, in reaching the desired set point temperature.

This review discusses biofuel and bioenergy production from seaweed, and ranges from cultivation ... more This review discusses biofuel and bioenergy production from seaweed, and ranges from cultivation to final product, and investigates opportunities, problems, advantages, disadvantages and other issues of this emerging industry. High levels of structural polysaccharides and low lignin contents make seaweed attractive feedstocks for production of liquid biofuels via fermentation and biogas production via anaerobic digestion. Since macroalgae can be grown in water (oceans and lakes), they will not compete with land-based crops, and thus will not be in competition with human foods. And biofuel and bioenergy production from macroalgae has some environmental benefits. Electricity produced from biogas derived from macroalgae can be cost-competitive to solar thermal, solar photovoltaic and biomass generated electricity. Biofuel and bioenergy production from macroalgae, however, will entail higher costs than terrestrial biomass feedstocks due to higher costs of cultivation and higher costs to remove harmful content such as sulfur and nitrogen from the resulting fuel or heavy metals from the residues. Economic production of biofuels and bioenergy will be available by increasing the scale and efficiency of production of this emerging resource.

Computers and Electronics in Agriculture, 2012

Food and Bioprocess Technology, 2012

Abstract In recent years, due to the increasing consciousness of quality in the food and health s... more Abstract In recent years, due to the increasing consciousness of quality in the food and health sector, much progress has been made in developing non-invasive techniques for the evaluation or inspection of internal qualitative parameters of fruits, vegetables, and processed foodstuffs considering, eg, moisture content, soluble solid content, acidity, and mechanical properties. This paper reviews the theoretical and technical principles as well as the recent achievements and applications of light backscattering imaging for ...

International Journal of Food Properties, 2014

ABSTRACT The aim of this research was to predict quality factors of tomato fruit during storage u... more ABSTRACT The aim of this research was to predict quality factors of tomato fruit during storage using backscattering and multispectral imaging techniques. To gather the required information for developing prediction models, batches of 200 tomatoes (cv. Pannovy) harvested at two maturity stages, were stored at standard condition up to four weeks. During storage, the modulus of elasticity, moisture content (MC), soluble solid content (SSC), titratable acidity (TA), hyperspectral data, and backscattering images were acquired on forty tomatoes at regular intervals of one week. After extracting the spectral data from forty points on each sample, they were subjected to preprocessing operations. Several feature selection techniques, including filter (ReliefF, Fisher-Score, and t-Score) and wrapper (genetic algorithm) methods were used to find the sensitive wavelengths for each fruit quality parameter. With the novel strategy used, the wavelengths found by the fusion of genetic algorithm and t-Score techniques showed good prediction performance for all considered qualitative parameters. In order to verify the usefulness of selected wavelengths, backscattering and multispectral imaging techniques were applied. The ANN produced the calibration models which gave a reasonably good correlation for estimating the modulus of elasticity, SSC and TA at 660 nm and MC at 830 nm of tomato from backscattering images. The correlation coefficient between the multispectral and backscattering imaging prediction results and reference measurement results were 0.952 and 0.891 for modulus of elasticity, 0.727 and 0.539 for MC, 0.736 and 0.561 for SSC, and 0.811 and 0.706 for TA, respectively. It can thus be concluded that proposed wavelength selection strategy is potentially useful for assessing quality of horticultural products by multispectral and backscattering imaging techniques.

Computers and Electronics in Agriculture, 2013

ABSTRACT Light backscattering imaging is an advanced technology applicable as a non-destructive t... more ABSTRACT Light backscattering imaging is an advanced technology applicable as a non-destructive technique for monitoring quality of horticultural products. Because of novelty of this technique, developed algorithms for processing this type of images are in preliminary stage. The present study investigates the feasibility of texture-based analysis and coefficients from space-domain analysis to develop better models for predicting mechanical properties (fruit flesh firmness or elastic modulus) of horticultural products. Images of apple, plum, tomato, and mushroom were acquired using a backscattering imaging setup capturing 660 nm. After segmenting the backscattering regions of images by variable thresholding technique, they were subjected to texture analyses and space domain techniques in order to extract a number of features. Adaptive neuro-fuzzy inference system models were developed for firmness or elasticity prediction using individual types of feature sets and their combinations as input for prediction model applicable in real-time applications. Results showed that fusion of the selected feature sets of image texture analysis and space domain techniques provide an effective means for improving the performance of backscattering imaging systems in predicting mechanical properties of horticultural products. The maximum value of correlation coefficient in the prediction stage was achieved as 0.887, 0.790, 0.919, and 0.896 for apple, plum, tomato, and mushroom products, respectively.

Computers and Electronics in Agriculture

Journal of Cleaner Production, 2013

Journal of American …, 2011

Computers and Electronics in Agriculture, 2012

Food and Bioprocess Technology, 2012

International Journal of Food Properties, 2014

Computers and Electronics in Agriculture, 2013

Implementation of tractors in agriculture is Substantial as a power supply. Therefore, performanc... more Implementation of tractors in agriculture is Substantial as a power supply. Therefore, performance model for developing parameters of tractors and implements are major for farm machinery, operators and manufacturers alike. The objective of this study was to assess the predictive capability of several configurations of ANNs for performance evaluating of tractor in parameters of drawbar power, rolling resistance and tractive efficiency. A conventional tillage system which included a moldboard plow with three furrows was used for collecting data from MF285 Massey Ferguson tractor. To predict performance parameters, ANN models with back-propagation algorithm were developed using a MATLAB software with different topologies and training algorithms. For drawbar power. The best result was obtained by the ANN with 6-7-1 topology and Bayesian regulation training algorithm with R 2 of 0.995 and MSE of 0.00024. The obtained result showed that the 6-7-1structred ANN with Levenberg-Marquardt training algorithm represents a good prediction of TE with R 2 equal to 0.989 and MSE of 0.001327. The obtained results confirmed that the neural network can be able to learn the relationships between the input variables and performance parameters of tractor, very well.

Due to the ascending significance of energy in the world, prognostication and optimization of Fue... more Due to the ascending significance of energy in the world, prognostication and optimization of Fuel Consumption (FC) in agricultural works is merit to consideration. Therefore, performance model for evolving parameters of tractors and implements are essential for farm machinery, operators and manufacturers alike. A conventional tillage system which included a moldboard plow with three furrows was used for collecting data from MF285 Massey Ferguson tractor. Field experiments were carried out in the experimental farm of Agricultural Engineering Department of Tehran University, Karaj province, Iran, which had loamy soil texture. The objective of this study was to assess the predictive capability of several configurations of ANNs for performance evaluating of tractor in parameter of fuel consumption. To predict performance parameters, ANN models with back-propagation algorithm were developed using a MATLAB software with different topologies and training algorithms. The ANN model with 6-7-1 structure and Levenberg-Marquardt training algorithm had the best performance with R 2 of 0.969 and MSE of 0.13427 for TFC prediction. The 6-8-1 topology shows the best power for prediction of AFC with R 2 and MSE of 0.885 and 0.01348, respectively. Also, the 6-10-1 structure yielded the best performance for prediction of SFC with R 2 of 0.935 and MSE of 0.012756. The obtained results promoted that the neural network can be able to learn the relationships between the input variables and fuel consumption of tractor, reliable.

The paper “Implementation of On/Off Controller for Automation of Greenhouse Using LabVIEW’’ in th... more The paper “Implementation of On/Off Controller for Automation of Greenhouse Using LabVIEW’’ in this volume has been withdrawn, because it was submitted by the corresponding author, Payam Javadikia, without the knowledge of the other authors.

In this paper, an artificial neural network based system, is presented to separate closed pistach... more In this paper, an artificial neural network based system, is presented to separate closed pistachio nuts from the open ones in the real-time. This intelligent system includes a feeding
part, an acoustical recognition part, and a pneumatic air rejection mechanism. Features of
pistachio nut types are extracted by analysis of sound signal in both time and frequency domains through fast Fourier transform, power spectral density, and principal component
analysis methods. These features are used as input vector to LVQ models, and various LVQ
learning algorithms, including LVQ1, OLVQ, LVQ4.a are evaluated. Further, the performance of the LVQ-based system is compared with those systems using MLP. The best performance is obtained through LVQ4.a algorithm; that is the correct separation
rates for closed shell and open shell ones are 96.5% and 96.83%, respectively and overall 96.67%. The designed system due to its non-destructively, does not cause any damage to the
kernels of open shell pistachios.

The current study evaluates the potential of hyperspectral imaging combined with artificial neura... more The current study evaluates the potential of hyperspectral imaging combined with artificial
neural networks to predict the moisture content in tomato fruit and to obtain spatial
distribution maps. A total of 192 tomato samples, Solanum lycopersicum 'Pannovy', were
harvested in the third and fourths stage of ripening according to the OECD color chart.
Samples were immediately transmitted to the laboratory and stored at 15°C and 92% rH.
Measurements were carried out after 1, 8, 15, 22, and 30 days of storage. After acquisition of
hyperspectral images of 40 tomatoes on each date, moisture content of samples was
calculated after oven drying (105°C). The electromagnetic spectrum between 400 to 1000
nm was recorded at 495 passbands by a hyperspectral imaging system. After applying
preprocessing operations and removal of data in saturation, valid data sets were collected
manually from the region of interest. Spectral dimensionality was reduced by selecting the
wavelengths in which high correlation exists between the spectral data and fruit moisture
content. A multilayer percepteron neural network has been trained with training dataset to
predict the moisture content of samples. To prepare the spatial prediction maps, tomato
samples were separated from the background. After that, 2D images were unfolded to
vectors and the intensity values of each pixel in the selected wavelengths were fed into the
fully trained neural network. The output matrix, containing the predicted values of moisture
content in every pixel, was folded back to form a 2D matrix with the same spatial dimension
of the hyperspectral images. Finally, the spatial distribution of moisture content was
displayed as a color map, where colors represent different values of predicted attribute. Results proof the feasibility of the method for characterizing the spatial distribution of an attribute in horticultural produce.

Forecasting meteorological behaviors are often needed for solar energy applications, particularly... more Forecasting meteorological behaviors are often needed for solar energy applications, particularly in design methods, in system characterization and in decision making for renewable energy management. In this study, a neuro-fuzzy system called ANFIS is used to forecast mean daily solar radiation ( D R ) in Alborz province of Iran. To design ANFIS models, meteorological data for the year 2008 were collected from the IRIMO data center. Input variables were maximum temperature, relative sunshine duration and extraterrestrial solar radiation. The best result was obtained with triangular membership functions (MF) for the input variables and linear type as output MF. For this model R, RMSE, MAE and MAPE were 0.98, 0.84, 0.69 and 5.3%, respectively. The forecast accuracy which is the measure of how close the actual is to the forecasted D R was 94.7%. Results showed that ANFIS can be successfully used for forecasting D R in the region and may be adopted with minor modification for any other location.

According to the growing population and shortage of fossil energy and the need for utilization of... more According to the growing population and shortage of fossil energy and the need for utilization of alternative energy sources is felt. One of the most accessible and renewable energy is solar energy which can be used as an alternative to fossil fuels to eliminate concerns about the environmental pollution caused by such fuels. Flat plate solar collectors are the major component in a water heating system and thermally optimized operation of the whole system has a considerable impact. One of the important factors determining the performance of a solar collector is the fluid flow rate. Therefore, in this study the performance of flat plate solar collector at three different flow rates of 3, 4 and 5 liters per minute was experimentally evaluated. The most efficient rate at four liters per minute flow rate was equal to 53.5% and at three and five liters per minute were, respectively, 50.46% and 46.35%. The highest received power from by the collectors at the four liters per minute was equ...

Renewable energy has important advantages compared to fossil energy. It produces minor or no poll... more Renewable energy has important advantages compared to fossil energy. It produces minor or no pollutant gases emission. Unlike fossil fuels, renewable energy sources are not limited and are available in all countries in various forms. The availability of renewable energy and solar power is that it can be used in a different form. In this study, received the power and efficiency of flat plate solar collector on the weather sunny, cloudy and overcast rainy examined. Based on the results, the flat plate collector was most efficient on a cloudy rainy day (with an efficiency 61.61%) and had the lowest yield on a sunny day (with an efficiency of %51.66), While the maximum amount of power from the system for a sunny day was 1046.5 W and the lowest power out from the system for a rainy cloudy day was 326.5 W.

Classification is vital for the evaluation of agricultural produce. However, the high costs, subj... more Classification is vital for the evaluation of agricultural produce. However, the high costs, subjectivity,
tediousness, and inconsistency associated with manual sorting have been forcing the post harvest industry
to apply automation in sorting operations. In this study, Fuzzy Logic (FL) was applied as a decision making
support to grade apples. Features such as color and size were measured through webcam. The same set of
apples was graded by both human expert and a fuzzy logic system designed for this purpose. For input and
output variables of the fuzzy logic system, triangular and trapezoidal membership functions were applied.
Totally, 125 rules with logical operator of “AND” and mamdani inference system for decision making and
the centroid (Center of Gravity (COG)) method for defuzzification was applied. For determination the
degree of membership of apples, the trial and error method was done. The algorithm was designed, can
capture an image from apples under the black box, and extract some features and then compare these
features with reference input, and determine the grade of apples. Grading results obtained from fuzzy logic
showed 90.8 % general agreement with the results from the human expert.

The purpose of this study was to evaluate feasibility of near infrared (NIR) spectroscopy with fi... more The purpose of this study was to evaluate feasibility
of near infrared (NIR) spectroscopy with fibre optic probe for
predicting fatty acids profile of Beluga caviar. Measurement was performed on 100 samples of Beluga. The wild caviar samples caught sturgeon comprised Huso huso. NIR calibrations were developed using partial least square regression (PLSR). Selected models for the estimation of fatty acids in this specie of caviar exhibited coefficients of determination for cross validation which ranged 0.81-0.91 % with root mean square errors of (RMSE) between 2.1 and 3.0. This information suggested that in general, NIR interactance spectroscopy could provide an opportunity to measure fatty acids contents of caviars.

2004, Ottawa, Canada August 1 - 4, 2004, 2004

Computer Applications in Engineering Education, 2011

In new agriculture, with agricultural mechanization development and available softwares, decision... more In new agriculture, with agricultural mechanization development and available softwares,
decision making systems, intelegent decision making is an easy process for advanced farmer.
Objective of this study is to use analytical hierarchy process, AHP, technique in selecting
appropriate combine type from four common combine type Class, John deere 955, Sahand and
Kordestan Reaper in the harvesting operation in the Yazd province. The AHP supports the group
decision-making process and the use of ergonomic criteria with different and incommensurable
metrics. Criterions of this study included: machine losses, safety and driver’s welfare, the costs of
repairment and maintenance and road traffic. Data analyzed with Expert Choice software version 11. Results indicated from the parameters that Class combine is the most approperiate harvesting machine.

The objective of this paper is to calculate of economic indices of broiler farms and analysis of ... more The objective of this paper is to calculate of economic indices of broiler farms and analysis
of the effects of grower’s literacy and experience on Benefit to Cost Ratio (BCR). Data was obtained
from 44 growers using a face-to-face questionnaire method. Questionnaire was included the effects
of literacy in three levels and experience in four levels, and also the calculation of BCR. The results
indicated that a mean BCR, variable costs and total income were calculated as: 1.38, 3506.29 /1000birdsand4995.49/1000birds and 4995.49 /1000birdsand4995.49/1000birds, respectively. The ANOVA results indicated that the grower
literacy had significant effect on BCR (P<0.01) and level 2 (diploma degree) had the highest BCR.
The Growers’ experience had significant effect at 5% level and level 4 (more than 20 years experience) on the highest BCR, respectively. Growers with more experiences had an effective management with the costs involve and inputs were applied more properly.

In order to improve the efficiency of production units we must measure the efficiency and factors... more In order to improve the efficiency of production units we must measure the efficiency and factors affecting it. This study aims to achieve this goal by evaluating the efficiency of broiler and laying production in Alborz Province. Used energy inputs include fuel, electricity, feed, labor, equipment, chicken and pullet. According to the results, the average energy consumption of broiler and laying units were computed as 189805.48 and 137656.34 MJ per 1000 bird, respectively. Fuel in broiler and feed in laying units had the largest share of the input energy. We used data envelopment analysis (DEA) to evaluate the energy efficiency in the studied farms. The average values of technical efficiency and pure technical efficiency were 0.90 and 0.93 in broiler farms, and 0.91 and 0.97 in laying farms, respectively. DEA also showed that broiler and laying farms can save up to 21.09% and 21.34% of their current input energies, respectively, without any reduction in their outputs. Fuel consumpt...

Supplier selection process is a key operational function to develop sustainable partnerships and ... more Supplier selection process is a key operational function to develop sustainable partnerships and enhance the supply chain performance. This chapter aims to develop an applicable methodology for green supplier selection in food industry. The methodology consists of two phases of classification and ranking of criteria, and the supplier selection phase. In first phase 10 criteria of supplier selection with two dimensions (conventional and green) are identified. Then the criteria are examined and ranked by evaluation factors (frequency in references, adaptation with kind of product, easily understand and easily measurement). The financial, qualitative, service and environmental management system criteria are selected as high ranked criteria. In second phase, potential suppliers are evaluated by high ranked criteria. Group decision making using fuzzy and grey set theories helped to give better results in green supplier selection. At the end of this study in order to demonstrate effective...

DESCRIPTION اين مقاله به معرفي ابزار هايي مي پردازد كه مي توانند شما را در يافتن منابع اطلاعاتي ج... more DESCRIPTION اين مقاله به معرفي ابزار هايي مي پردازد كه مي توانند شما را در يافتن منابع اطلاعاتي جهت انجام تحقيقات پيرامون موضوعات تخصصي ياري رسانند. تمركز ما روي ابزارهايي است كه قادرند در منابع وب (www) به جستجو بپردازند. امروزه وب بعنوان يك روش با ارزش و قانوني براي انتشار اطلاعات در آمده است. اساتيد و دانشجويان بيش از پيش از كتابداران براي دريافت اينگونه اطلاعات تقاضاي كمك مي كنند. تجربه نشان داده است كه بعضي اطلاعات خاص را ميتوان از طريق وب آسانتر و سريعتر بدست آورد تا از منابع چاپي. آدرس تعدادي از سايتهاي وب كه ميتوانند نقاط شروع مناسبي براي انجام كارهاي تحقيقاتي شما از طريق رسانه اينترنت بحساب آيند نيز گردآوري شده اند. اميد است مقاله حاضر شما را در جمع آوري سريع و آسان منابع تحقيقاتي مورد احتياجتان، بدون اينكه نيازي به كنكاش درون ميليونها سايت وب داشته باشيد، ياري رساند.

DESCRIPTION اين روزها بحث و گفتگوهاي فراواني پيرامون اينترنت در سطح ملي و بين المللي است. اما اين... more DESCRIPTION اين روزها بحث و گفتگوهاي فراواني پيرامون اينترنت در سطح ملي و بين المللي است. اما اينكه اينترنت واقعأ چيست و ما بعنوان متوليان و طراحان آموزش عالي چگونه مي توانيم از آن به بهترين نحو در مراكز دانشكاهي استفاده كنيم؟ كمتر صحبت مي شود. درحال حاضر اينترنت يك نام عمومي براي شبكه ها و برنامه هاي بهم متصل متنوعي كه مي توانند اطلاعات را به (يا از) كامپيوتر هاي سراسر دنيا تحويل داده (يا از آنها بازيابي كنند)، اطلاق مي شود. اخيرأ محبوبيت اينترنت بعنوان يك محيط و رسانه با ارزش براي ارائه آموزش و كسب تحصيل از راه دور نيز رو به رشد است. اما منظور از طراحي و ارائه آموزش از طريق شبكه چه معنايي دارد؟ و آن چه تفاوتي با آموزش سنتي – حضور در سر كلاس درس- و ساير روشهاي آموزش از راه دور-تطبيقي-مكاتبه اي، ويدئويي و …- دارد؟ اين مقاله قصد دارد تا پاسخ به سؤالاتي نظير چه زماني مي توان اينترنت را بعنوان يك فناوري مناسب براي ارائه آموزش در نطر گرفت؟ و افرادي كه قصد ارائه آموزش دوره هايي از طريق آن را دارند نياز به چه چيزهايي دارند؟ را برايتان تهيه ببيند.

DESCRIPTION در اين مقاله ما شما را با نحوه تحقيق و پيدا كردن منابع اطلاعاتي مرتبط با رشته تخصصي ا... more DESCRIPTION در اين مقاله ما شما را با نحوه تحقيق و پيدا كردن منابع اطلاعاتي مرتبط با رشته تخصصي از طريق اينترنت آشنا مي كنيم. استفاده از ابزارهاي جستجو، روبوت ها و پست الكترونيكي براي يافتن اطلاعات موجود در فيلد تخصصي و همگامي با تازه هاي موضوع تخصصي شما، توصيه مي گردد. اميد است اين راهنمائيها شما را در جمع آوري اطلاعات مفيد و مورد نيازتان، بدون نياز به كنكاش درون ميليونها سايت وب، بسرعت و سهولت ياري نمايد.