Post-harvest technologies
H. Masoudi
Abstract
In this study, an electronic system was built to determine the mass and volume of orange fruits from their dimensions using ultrasonic sensors. The system hardware parts include a metal box, three ultrasonic sensors, a load-cell sensor, an Arduino board, a memory card module, a voltage converter, a keypad, ...
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In this study, an electronic system was built to determine the mass and volume of orange fruits from their dimensions using ultrasonic sensors. The system hardware parts include a metal box, three ultrasonic sensors, a load-cell sensor, an Arduino board, a memory card module, a voltage converter, a keypad, a display and a power adapter. A computer program was written to obtain data from ultrasonic sensors and determine the mass and volume of fruits using regression relationships in Arduino software. 100 samples of orange fruits (Dezful local variety) were picked randomly from a garden and various measurements were done to determine the main physical properties of fruits including three dimensions, mass (M), and volume (V). The system output values for mass and volume of orange fruits with their actual values had no significant difference at 1% probability level. The root mean square error (RMSE) in determining the oranges mass and volume by the system were 9.02 g and 10.90 cm3, respectively. In general, the proposed system performance was acceptable and it can be used for determining the mass and volume of orange fruits.
Design and Construction
A. Rezaei; H. Masoudi; H. Zaki Dizaji; M. E. Khorasani
Abstract
Introduction The cereal combine harvester is one of the agricultural machines that works in difficult conditions and its parts are constantly under various static and dynamic loads. For the optimal design of vehicle parts, types and values of loads applied to them must be determined correctly. The purpose ...
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Introduction The cereal combine harvester is one of the agricultural machines that works in difficult conditions and its parts are constantly under various static and dynamic loads. For the optimal design of vehicle parts, types and values of loads applied to them must be determined correctly. The purpose of this study was to design and fabricate an electronic system that could instantly measure and store the amount of vertical load exerted on the rear axle of grain combine harvester in various conditions to be used in the design and optimization of the axle.Materials and Methods Main components of the designed system included a steel coupling, a disc loadcell (H2F-C2-10t ZEMIC model), an electronic board for amplifying loadcell output voltage, a data logger (AdvanTech DAQ Navi model), a 12-volt battery, and a laptop. A special steel coupling was designed in CATIA software for connecting the loadcell to the axle. The loadcell was placed between the coupling plates and then the coupling was installed on the center point of the rear axle of a JD 955 combine harvester. A standard tensile-compression testing machine (Cantam STM-150) was used to calibrate the loadcell. The relationship between the input load and the loadcell output voltage was linear and had a high coefficient of determination (R2 = 0.9991). In the static test, the vertical load exerted on the axle was recorded by the electronic system while the combine was stopped and the combine engine was in ON/OFF modes. In the dynamic test, the combine was driven in three positions including asphalt road, dirt road, and wheat field at three different forward speeds, and loads on the rear axle were recorded by the electronic system. Finally, the data obtained from the tests were analyzed as a factorial experiment in a completely randomized design with five replications in Excel and SPSS software.Results and Discussion The average static loads on the combine rear axle in ON and OFF modes were 14.908 and 14.905 kN, respectively. The results of the Student's t-test of paired samples to compare the values of axle vertical loads in two modes of static load measurement showed that there is no significant difference between the axle loads in ON and OFF mode of the engine at 1% probability level. The average vertical loads on the rear axle of the combine were equal to 15.20, 15.27, and 15.28 kN, while driving on asphalt roads at speeds of 10, 15, and 20 km h-1 respectively. These values were equal to 17.57, 17.99, and 18.15 kN, while driving on the dirt road at speeds of 2, 4, and 6 km h-1 respectively, and they were equal to 16.47, 18.01, and 17.78 kN when harvesting wheat in the field at speeds of 3, 4, and 5 km h-1 respectively. The average load applied on the axle in the turning path was more than the load applied in the straight path, which indicates load transfer to the rear axle during turning. The effect of forward speed and path type on the amount of axle load was significant at a 1% probability level, but their interaction was not significant. Therefore, the critical conditions for applying load on the rear axle of combine harvester are occurred while combine turns with high forward speed, and the design of the axle should be based on these conditions. The maximum load on the axle was obtained equal to 50 kN on the dirt road, which was due to the combine movement on a steep uphill at the end of the path.Conclusion Evaluation of the system in different conditions showed that the performance and accuracy of the system are acceptable and the data of this system can be trusted and used to measure the vertical load on the rear axle of the combine. The current rear axle of the JD955 combine harvester looks relatively safe, but at some very rugged elevations, especially steep uphills, it suffers from a lot of stress that may cause damage. So, optimizing the axle such as increasing the thickness of the triangular piece in the middle of axis and using a stronger alloy for the middle areas of the axle are recommended.
H. Maghsoudi; S. Minaei; B. Ghobadian; H. Masoudi
Abstract
Electronic canopy characterization to determine structural properties is an important issue in tree crop management. Ultrasonic and optical sensors are the most used sensors for this purpose. The objective of this work was to assess the performance of an ultrasonic sensor under laboratory and field conditions ...
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Electronic canopy characterization to determine structural properties is an important issue in tree crop management. Ultrasonic and optical sensors are the most used sensors for this purpose. The objective of this work was to assess the performance of an ultrasonic sensor under laboratory and field conditions in order to provide reliable estimations of distance measurements to apple tree canopies. To achieve this purpose, a methodology has been designed to analyze sensor performance in relation to foliage distance and to the effects of interference with adjacent sensors when working simultaneously. Results showed that the average error in distance measurement using the ultrasonic sensor in laboratory conditions was 0.64 cm. However, the increase of variability in field conditions reduced the accuracy of this kind of sensors when estimating distances to canopies. The average error in such situations was 3.19 cm. When analyzing interferences of adjacent sensors 30 cm apart, the average error was ±14.65 cm. When adjacent sensors were placed apart by 60 cm, the average error became 6.73 cm. The ultrasonic sensor tested has been proven to be suitable to estimate distances to the canopy in pistachio garden conditions when sensors are 60 cm apart or more and can, therefore, be used in a system to estimate structural canopy parameters in precision horticulture.
A. Rohani; H. Ghaffari; R. Felehgari; Kh. Mohammadi; H. Masoudi
Abstract
Farm machinery managers often need to make complex economic decisions on machinery replacement. Repair and maintenance costs can have significant impacts on this economic decision. The farm manager must be able to predict farm machinery repair and maintenance costs. This study aimed to identify a regression ...
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Farm machinery managers often need to make complex economic decisions on machinery replacement. Repair and maintenance costs can have significant impacts on this economic decision. The farm manager must be able to predict farm machinery repair and maintenance costs. This study aimed to identify a regression model that can adequately represent the repair and maintenance costs in terms of machine age in cumulative hours of use. The regression model has the ability to predict the repair and maintenance costs for longer time periods. Therefore, it can be used for the estimation of the economic life. The study was conducted using field data collected from 11 John-Deer 955 combine harvesters used in several western provinces of Iran. It was found that power model has a better performance for the prediction of combine repair and maintenance costs. The results showed that the optimum replacement age of John-Deer 955 combine was 54300 cumulative hours.
