A computer-based instrumentation system for measuring tractor field performance

A computer based tractor instrumentation system was developed to measure field performance parameters. The system development was divided into three parts: tractor instrumentation, data acquisition, and data analysis systems. Tractor instrumentation was developed by completing the transducer installations on a John Deere farm tractor model 4430H. The data acquisition system was developed by installing a 21XL micrologger, a thermal printer, and a digital tape recorder on the tractor inside the cab. A data analysis system was also developed to retrieve the data from the cassette tape through a C20 interface system and transfer the data to the microcomputer diskette and further to a main frame computer for analysis. The instrumented tractor was tested in the field by conducting a series of experiments under different terrain and operating conditions. Data from these experiments were selected for specific conditions to assist in verification of a previously developed computer model TERMS . The instrumentation system tested in the field was convenient, simple, and reliable in operation. The instrumented tractor was tested in the field four times without malfunctioning in either data collecting or recording. The data analysis system could dump the data successfully to the main frame computer for analysis

Optimization cane traction output from hopper in full-automatic sugarcane planters by using response surface modeling and analytical hierarchy process

Agriculture mechanization plays a significant economic role by increasing agriculture production and reducing cost of cultivation.  There is a dire need to develop more processing machinery for value addition of agricultural produce with a reduction in time and labour.  The planting operation is one of the most important tasks that sugarcane growers undertake.  It should result in a plant stand at the desired density that emerges quickly and uniformly.  Austoft sugarcane planter was studied and the CAD model for metering device was simulated with Catia software.  Main components of this machine are hopper, metering device, and basis.  Multiple regression and Response Surface Methodology (RSM) were applied to data for investigating the effect of angle and speed of sugarcane billet metering device on discharging and precision indices.  The speed of metering device had more effect than angle on both performance indices.  Analytical hierarchy process (AHP) used to match the best operation condition for discharging billets from hopper.  The angle of 80° and speed of 1 m s-1 was the best suited condition for sugarcane billet metering device with 98.64% for precision index and 4.2 billets in per second for discharging index. A consistency ratio evaluation value of 0.1 confirmed the results.   Keywords: sugarcane, planters, AHP, mechanization agriculture, RSM, computer aided design (CAD)

Pattern Analysis of a 'vertical Spinning Disk Nozzle

Agricultural Engineerin

Moisture content determination of oilseeds based on dielectric measurement

Oilseeds have an important role in edible oil production.  Moisture content measurement of oilseed is an inevitable operation in harvesting and almost all postharvest processing such as handling, storage, milling and oil extraction.  In this paper, a cylindrical capacitive sensor was used to predict the moisture content of sesame, soybean and canola seed as a simple, low cost, rapid and reliable method.  Two varieties of each oilseed were selected and extracted equation from a variety was evaluated for another variety.  The hyperbolic regression and paired t-test were utilized to extract the calibration equations and perform a comparison between predicted moisture with actual values.  The R2 of calibration for Dashtestan and Ultan sesame were 0.998 and 0.999, respectively, for L17 and Sahar soybean were 0.972 and 0.965, respectively and for Okapi and Talaiyeh canola were 0.993 and 0.994, respectively.  The R2 of prediction for Dashtestan and Ultan sesame were 0.966 and 0.932, respectively, for L17 and Sahar soybean were 0.963 and 0.952, respectively and for Okapi and Talaiyeh canola were 0.993 and 0.994, respectively.  Results of paired t-test confirmed that the measured and predicted moisture content of all oilseeds were not statistically different at the 5% level (p > 0.05).  Based on obtained results the designed system using capacitive sensor is valid and reliable for moisture measurement of the studied oilseeds.   Keywords: oilseed, sesame, soybean, canola, moisture content, capacitive senso

Fuel consumption models of MF285 tractor under various field conditions

Due to the ascending importance of energy in the world, prediction and optimization of Fuel Consumption (FC) in agricultural tasks is merit to consideration. In this study a Massey Ferguson (MF285) tractor was implemented with a low cost and precise data acquisition system as a means to record and monitor the affectual parameters on FC such as forward speed and instant fuel flow rate during field operation. Field experiments were carried out in the experimental farm of Agricultural Engineering Department of Tehran University, Karaj province, Iran, which had loamy soil texture. A mouldboard plow was used as tillage toll during the experiments at various tillage depths, engine speeds, forward speeds, tire inflation pressures, moisture contents and cone indexes. Acquired data were used to elicit an accurate model for Temporal, Area-specific and Specific Fuel Consumption (TFC, AFC and SFC). Results showed considerable effect of all measured parameters on TFC, AFC and SFC. For instance the TFC, AFC and SFC decreased by 11%, 13% and 56% respectively when the cone index increased from 105 to 1161 kPa. And also augmenting tillage depth from 10 to 20 cm led to 44% increase of TFC while SFC decreased by 164% oppositely. AFC rate was 1.1 liter per cm of tillage depth. Increasing the engine speed from 1200 to 2000 r/min led to increase of TFC, AFC and SFC by 56%, 71% and 46%, respectively. The forward speed was the most influential parameter on TFC, AFC and SFC while the moisture content and tire inflation pressure effects were minor. Models validation was acceptable and the fuel consumption rate could be predicted with accuracy of about 95%

Artificial Neural Network Based Modeling of Tractor Performance at Different Field Conditions

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 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 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

Design a capacitive sensor for rapid monitoring of seed rate of sugarcane planter

A capacitive sensor method for measuring billet spacing uniformity with sugarcane (Saccharum officinarm L.) billet planter is investigated in this paper.  Therefore, an electronic device based on capacitive sensor was designed and developed to predict the planting spacing of sugarcane billets.  It consisted of four components: a rectangular parallel plate capacitor, electronic circuitry, microcontroller, and display unit.  Accordingly, a prototype of the precision metering device for sugarcane billets was developed.  After calibrating the monitoring system, the results were verified with calibrated curve by means of linear regression and paired T-test.  The performance of the device, including quality of feed index (QFI), multiple index and miss index was investigated under laboratory conditions using a capacitive sensor and a test stand with camera system.  The results revealed that the forward speed had a significant effect on these variables.  The coefficient of variation was less than 3%, which indicated that billet spacing calculated via capacitive sensing method has no significant difference with the computed billet spacing via image processing method.   Keywords: capacitive system, sugarcane, compare monitoring, performance indices, precision plantin

Models of mechanical cutting parameters in terms of moisture content and cross section area of sugarcane stalks

The objective of this study was to find optimizing moisture content and cutting area of sugarcane stalk cutting parameters using multiple regressions and to verify the optimum levels of the variables.  The effect of moisture content and cutting section area on mechanical cutting properties of sugarcane stalks was studied using a linear blade cutting and UTM (Universal Testing Machine) size reduction device.  Data obtained in the laboratory were divided into four different groups in order to determine the peak force, cutting energy, ultimate stress and specific energy.  Additional criterions were also proposed and used as an indicator of the cutting performance.  These were the marginal cutting parameter (MCP) and return to scale (RTS).  The data obtained in the laboratory were then used to develop functions in polynomial form that allowed the calculation of the optimum level of each independent variable considered in the study.  Moisture content had the highest effect on peak force, ultimate stress and specific energy with an impact of -15.936, -0.147 and -0.179, respectively.  Also cutting energy affected with cutting section area with a 36.06 coefficient.  The high moisture content level compared to low moisture content level produced a significant reduction in the peak force, ultimate stress and specific energy.  Cutting parameters were relatively insensitive to moisture content of sugarcane stalk more than cutting section area of that.   Keywords: mechanical cutting, moisture content, sugarcane stalk, cutting energy&nbsp

Estimation and assessment of cost and revenue for solid waste management subsystems in Tehran city using mathematical functions

Background and Aims: The municipality of Tehran has recently attempted to implement the integrated waste management system (IWMS) with the approach of minimizing environmental emissions, the lowest cost and the maximum utilization of existing potential. The present study set out with the aim of assessingthe fixed and variable investment costs along with estimating the cost functions of its subsystems.Materials and Methods: Recorded data from September to October in 2014- 2015 were used, making arrangements well in advance. The annual waste input to each subsystems of IWMS was firstly divided into 0 to twice of input ratio. The amount of fixed and variable investment costs along with future costs were then determined considering experts’ opinions. Finally, MATLAB software version 7.1 was used in order to coding, estimating cost functions, and determining the correlation coefficient (R2) between the input and cost values.Results: The results showed that transportation subsystem allocated the maximum amount of costs (43%). Processing (23%), anaerobic digestion (12%), aerobic digestion (9%), landfilling (7%), and incineration (6%) were ranked in the next positions, respectively. Furthermore, using actual cost data based on existing capacity as well as peer reviewed experts’ data with theoretical capacity indicated that all subsystems had economic scale with high correlation coefficients.Conclusion: It is concluded that directing the waste flow from burial site to other waste processing technologies such as separation of recyclable materials, aerobic digestion, anaerobic digestion, and incineration would result in a significant reduction in the total amount of costs.Keywords: Municipal solid waste, Waste management, Mathematical Functions, Operating cost, Unit costFor downloading the full text please click here

A Review of Non-Destructive Methods for Detection of Insect Infestation in Fruits and Vegetables

Insect damage in fruits and vegetables cause major production and economic losses in the agriculture and food industry worldwide. Monitoring of internal quality and detection of insect infestation in fruits and vegetables is critical for sustainable agriculture. Early detection of an infestation in fruits can facilitate the control of insects and the quarantine operations through proper post-harvest management strategies and can improve productivity. The present review recognizes the need for developing a rapid, cost-effective, and reliable insect infestation monitoring system that would lead to advancements in agriculture and food industry. In this paper, an overview of non-destructive detection insect damages in fruits and vegetables was presented, and the research and applications were discussed. This paper elaborated all of the post-harvest fruit infestation detection methods which are based on the following technologies: optical properties, machine vision technique, sonic properties, magnetic resonance imaging (MRI), thermal imaging, x-ray computed tomography and chemical chromatography. Also, the main challenges and limitations of non-destructive detection methods in the agricultural products quality assessment were also elucidated