Evaluation and selection of thin-layer models for drying kinetics of apricot (cv. NASIRY)

E. Mirzaee, S. Rafiee, A. Keyhani(Agricultural Machinery Engineering Department, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran) Abstract: This paper presents the thin layer drying behavior of apricot (cv. NASIRY) at the air temperatures of 40ºC, 50ºC, 60ºC, 70ºC and air velocity of 1m/s and 2 m/s.  In order to select a suitable form of the drying curve, 12 different thin layer drying models were fitted to experimental data.  Fick’s second law was used as a major equation to calculate the moisture diffusivity with some simplification.  The high values of coefficient of determination and the low values of reduced chi-square and root mean square error indicated that the Logarithmic model and the Midilli et al. model could satisfactorily describe the drying curve of apricot for drying air velocity of 1m/s and 2 m/s, respectively.  According to the research results the calculated value of effective moisture diffusivity varied from 1.78×10-10–5.11×10-10 m2/s and the value of activation energy varied from a minimum of 24.01 kJ/mol to a maximum of 25.00 kJ/mol.Keywords: apricot, thin layer drying, effective moisture diffusivity, activation energy Citation: E. Mirzaee, S. Rafiee, A. Keyhani.  Evaluation and selection of thin-layer models for drying kinetics of apricot (cv. NASIRY).  Agric Eng Int: CIGR Journal, 2010, 12(2): 111-116.  &nbsp

Investigating the cost of wheat production in Iran and the effect of combine availability on harvesting cost

The aim of this study was investigated the cost of wheat production in Iran and the effect of combine availability on harvesting cost. Information of combine number and cost of wheat production in each province, for this period (2000 – 2006), attained from Ministry of Jihad-e-Agriculture of Iran statistics.  Data from variable costs such as land preparing, planting, cultivating, harvesting and land price in each province in each year was entered into computer. Comparisons between means of producing cost, specially harvesting cost, were carried out with use of SPSS15. To compare the mean of costs in each province Duncan test was used. The result showed that the cost of wheat harvesting in provinces has decreased with increasing the number of combine harvester in provinces. Therefore for decreasing the harvesting cost in Iran provinces it is necessary to distribute more combine harvester in provinces

A pattern for power distribution based on tractor demand in Iran

This study was aimed to propose a pattern to distribute tractors in the country, Iran. A pattern was suggested based on previous tractor demands in all provinces. Results showed that Iran agriculture needs minimal 33460 tractors with nominal power average of 53 kw. These tractors cost approximately 334.6 million dollars to the country. Tractors’ allowance should be continued with the previous rate till farmers have no longer problem with power supplies are needed to fulfill their demands and to replace the depreciated machines

Mathematical Modeling of Kinetics of Thin-layer Drying of Apple (var. Golab)

Mathematical models of thin-layer drying of apple were studied and verified with experimental data. Fourteen different mathematical drying models were compared according to three statistical parameters, i.e. root mean square error (RMSE), chi-square (X2) and modeling efficiency (EF). The thin-layer drying kinetics of apple slices was experimentally investigated in a laboratory convective dryer and the mathematical modeling, using thin-layer drying models present in the literature, was performed. The main objective of the study was the verification of models already developed. Experiments were performed at air temperature between 40 and 80 °C, velocity of 0.5, 1 and 2 m/s, and thickness of thin layer of 2, 4, 6 mm. Besides the effects of drying air temperature and velocity, effects of slice thickness on the drying characteristics and drying time were also determined. Drying curves obtained from the experimental data were fitted to the-thin layer drying models. The results have shown that, model introduced by Midilli et al. (2002) obtained the highest value of EF = 0.99972, the lowest value of RMSE = 0.00292 and X2 = 10-5. Therefore this model was the best for describing the drying curves of apples. The effects of drying air temperature, velocity and thickness on the drying constant and coefficient were shown to compare the circumstances of drying

Some Physical Properties of Apple cv. ‘Golab’

Apple is among the popular fruits and of a high economic value. Sorting and grading of apple is needed for the fruit to be presented to local and foreign markets. A study of apple physical properties therefore is imperative. Some physical properties of apples were determined. These properties include: dimensions, mass, volume, surface area, porosity, packaging coefficient and coefficient of static friction. The maximum, average and minimum diameters of apple were 65.04, 53.50 and 35.14 mm respectively. Average volume and mass were 104.5 cm3 and 74.87 g respectively. As for an apple pile, the density and apparent density were respectively calculated as 0.7427 and 0.2401 g/cm3. Maximum, average and minimum porosity of apples were 57.24, 54.13 and 50.17 percent with their sphericity being 1.0028, 0.93 and 0.84 respectively. Average static friction angle of apple on galvanized, glass and plywood surfaces were 20, 26.3 and 26.8 degrees respectively. Average packaging coefficient for the apples studied was 0.45

Classification of Pomegranate Fruit using Texture Analysis of MR Images

Images obtained by Magnetic Resonance Imaging (MRI) of Iranian important export cultivar of pomegranate Malase-e-Torsh were analyzed by texture analysis to determine Gray Level Co-occurrence Matrix (GLCM) and Pixel Run-Length Matrix (PRLM) parameters. The T2 slices measured at 1.5 T for 4 quality classes of pomegranate semi-ripe, ripe, over-ripe and internal defects classes were analyzed numerically using the software MaZda. To classify pomegranate into different classes, discriminant analysis was conducted using cross-validation method and texture features. Ten GLCM and 5 PRLM features were used in 2 different classifiers. Mean classification accuracy was 95.75 % and 91.28 % for GLCM and PRLM features respectively. By using GLCM and RPLM features, classification accuracy for semi-ripe, over-ripe and internal defects classes was higher when GLCM features were used. Ripe class had higher classification accuracy while PRLM features were used. To improve classification accuracy, combination of GLCM and PRLM features were used. For achieving best classification accuracy, optimum numbers of features were selected based on their contribution to the model. Combination of 7 GLCM and 4 PRLM features resulted in mean accuracy of 98.33 % and the lowest type I and II errors. Especially, type I error in ripe and over-ripe classes were significantly decreased. The classification accuracies were 100, 98.47, 100 and 95 % for semi-ripe, ripe, over-ripe and internal defects classes

Instrumented undriven steering wheel to illustrate dynamic behavior of vehicles

In this paper, a low-cost dynamometer for undriven, steered wheels is described.  The dynamometer was produced to determine whether such an instrumented mechanism is practical.  Four S-beam load cells and two opto-counters were used to obtain all moments, forces, and points of their application.  Overturning, aligning, and rolling resistance moments besides vertical force are directly measured by the load cells.  The opto-counters detect wheel angular velocity and steering angle.  The dynamometer evaluation results showed significant correlation between expected values and measured data with high accuracy.  Wheel dynamic behavior can be defined according to dynamic and kinematic analysis in which relative calculations have minimum simplifying assumptions.   Keywords: dynamometer, wheel forces and moments, point of force application, load cell, opto-counte

Simulation and control of fan speed in a solar dryer for optimization of energy efficiency

In a forced convection solar dryer, the dryer efficiency is continuously changing during the drying process due to changes of solar radiation and temperature. So, it is important to use a control system to optimize energy efficiency based on changing drying factors. For this reason, a controller was designed, simulated and evaluated. In this research fan speed was simulated and controlled based on changing system variables accordingly to maintain the optimized efficiency. Fan speed was simulated by SIMULINK toolbar of MATLAB software. The dryer efficiency was determined by considering the mathematical relations and monitoring the air temperature in 3 positions: inlet and outlet of collector and outlet of drying chamber. All experiments were carried out in three replications. The current and optimized dryer efficiencies were calculated by using the control program. Results showed that the simulated model was capable of modeling fan speed. So, statistical analysis showed that the control system highly improved the dryer efficiency throughout its operation at probability level of 1%

An Analysis of Improving Energy use with Data Envelopment Analysis in Apple Orchard

Abstract In this paper, Data Envelopment Analysis (DEA) technique was applied for apple (Red and Golden delicious varieties) producers in West Azarbaijan province, Iran (2008Iran ( -2009. Results showed that the highest share of energy consumption belongs to packaging (57%) and irrigation (16%). Highest share of expenses were found to be 34% and 30% for labor and packaging, respectively. The total energy input for apple production, energy productivity, net energy and output-input energy value were estimated as 101,505 MJ.ha-1, 0.23 kg.MJ-1, -56.320 MJ.ha-1 and 0.44, respectively. Also, The study has helped to segregate efficient farmers from inefficient ones, identify wasteful uses of energy by inefficient producers and suggest reasonable savings in energy uses from effective sources while it describes the process of benchmarking energy inputs and apple yield. Technical, pure technical and scale efficiencies were calculated (by using CCR and BCC models) for all orchards. Inquiries on 80 orchards were conducted in a face-to-face interviewing. The VRS analysis showed that only 41 out of 80 DMUs were efficient. The TE of the inefficient DMUs was calculated as 87.8%. This implies that 12.2% of overall resources could be saved by raising the performance of these DMUs to the highest level. Results showed that the maximum share to the total energy saving is from diesel (39.7%) followed by packaging and about (28.1%). The results of analysis showed that DEA is an effective tool to analyze and benchmark productive efficiency of farms