Modeling of physical properties of apple slices (Golab variety) using artificial neural networks

 Apple is one of the most popular fruits and of 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.  In this work, some physical properties of apples (Golab variety) such as main diameter, mass, volume and fruit density were determined and relation between mass and other parameters were modeled by using artificial neural networks.  In this study, we used Feed-Forward Back Propagation (FFBP) network with training algorithms, Levenberg-Marquard and Momentum.  The results show that Levenberg-Marquard algorithm give better result than Momentum algorithm do, and Feed-Forward Back Propagation (FFBP) network with topology 3-6-4-1, 3-6-1, 3-4-2-2-1 and 3-6-6-1; and Levenberg-Marquard algorithm could predict relation between mass and other parameters with error percentages 0.999999, 0.999999, 0.999999 and 0.999999; and mean square error 0.000078, 0.000118, 0.000158 and 0.000194. Keywords: apple (Golab variety), artificial neural network, Feed-Forward Back Propagation, Levenberg-Marquard algorithm, Momentum algorithm, physical propertie

Regression modeling of field emissions in wheat production using a life cycle assessment (LCA) approach

Field emissions of Irianian wheat production were investigated. Data were collected from 260 farms from the city of Fereydonshahr in the Esfahan province. Life cycle assessment (LCA) methodology was developed to assess environmental impacts associated with the production of wheat in the studied region. Global warming potential (GWP), eutrophication potential (EP), human toxicity potential (HTP), terrestrial eco-toxicity potential (TEP), oxidant formation potential (OFP) and acidification potential (AP) were calculated as 2620.86 kg CO2 eq.t-1 (tonne of grain), 14.25 kg PO4 -2 eq.t-1, 1111.7 kg 1,4-DCB eq.t-1, 10.59 kg 1,4-DCB eq.t-1, 0.0073 kg ethylene eq.t-1 and 19.07 kg SO2 eq.t-1, respectively. In order to specify a relationship between input materials and field emissions (direct and indirect emission), the Cobb-Douglass production function was applied. The impacts of farm area, N, P2O5, K2O, diesel fuel and biocides were entered as independent variables and different impact categories as dependent variables. RMSE of models for GWP, EP, HTP, TEP, OFP and AP was 0.07, 0.19, 0.17, 0.34, 0.49 and 0.26, respectively. Accordingly with a rise in farm size level, the emissions per tonne of grain produced decreased

Appropriate building repair and maintenance strategies using multicriteria decision-making analysis – a Delphi study

As an influential and significant factor in improving the service of building components and elements, maintenance plays an essential role in maintaining reliability, availability, and quality, as well as increasing efficiency and security. Therefore, how to define this maintenance system and determine the appropriate criteria and strategies for that play an important role in the cost and longevity of the buildings after construction and during their operation. The purpose of the article is to determine the effective criteria for evaluating buildings based on maintenance and repair (R&M) and finally determining the appropriate strategy for the maintenance of residential buildings, using multicriteria decision-making methods. These criteria were first identified by reviewing the literature and using the Delphi method to obtain the opinions of maintenance experts. The criteria were then prioritized, based on the SWARA method, and the results were compared and evaluated. Based on comparison, safety, health, environment, and proper utilisation were rated the top four criteria to consider for building R&M. Finally, using the VIKOR2 method, it was found that the breakdown maintenance (BM) and corrective maintenance (CM) strategies are the best strategies to use for the R&M of residential buildings

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

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

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

Using online image processing technique for measurement the browning in banana during drying (a new and automatic method)

Determination and controlling of quality parameters can be useful for ordering and marketing of fruits.  Color is the first and the most important parameter in the visual appearance of fruits, specifically in banana.  The aim of this study is to use image-processing technique (online operation) to measure and analyze the color change of banana slices during thin layer drying.  Using online-image-processing technique resulted in designing a machine vision system to control the color change of products automatically.  The results show a linear relation with high correlation coefficient for L*, a* and b* (0.967, 0.962 and 0.991 respectively) between the data of the image-processing technique and the hold-hand colorimeter.  In this study, parameters of chroma, hue and browning index were determined to describe the kinetics of color change in banana slices.  The change of chroma was not significant, but hue was decreased and browning index was increased during drying time.  In addition, the experimental data of the L* and ∆E was fitted using zero and first order models with high correlation coefficient (0.80-0.97).   Keywords: image processing, machine vision, online, banan

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