Zargham Fazel Niari; Amir hossein Afkari-Sayyah; Yousef Abbaspour-Gilandeh
Abstract
The acquisition of basic knowledge in quality control of wheat seed using machine vision technology is important. The objective of this research was to develop hardware and appropriate software to determine seven-grain groups in wheat seed samples. Ninety-one features were extracted through 21000 single ...
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The acquisition of basic knowledge in quality control of wheat seed using machine vision technology is important. The objective of this research was to develop hardware and appropriate software to determine seven-grain groups in wheat seed samples. Ninety-one features were extracted through 21000 single seed images and the shape, texture and color features were ranked. Five classification models were investigated. The highest classification accuracy was obtained by artificial neural network with two hidden layers and the first 35 superior features. In the test run of this model with independent data, classifying accuracy for big white wheat, small white wheat, broken white wheat, wrinkled white wheat, red wheat, barley and rye were 100, 96.7, 99.3, 90.3, 99, 99.7, and 98 percent respectively with the average of 97.6 %. Shape features were more prominent and textural and color characteristics followed it respectively. Average classification accuracy in models of linear discriminant analysis, quadratic discriminant analysis, K- nearest neighbor and artificial neural network with a hidden layer were 95, 96.7, 91.6 and 97.3 % respectively. In the context of this study, the machine vision system comprising an industrial digital camera and artificial neural network with two hidden layers was identified as a valuable system in the investigation of the visual qualities of wheat seeds.
Sedaghat Fazeli; Yousef Abbaspour-Gilandeh; Gholamhosein Shahgoli; Zargham Fazel-Niari
Abstract
Traction efficiency and fuel consumption hgave close affinity and are considered to be important unit operations, especially during primary tillage operations. Therefore, analyzing factors that affect the amount of Traction efficiency and fuel consumption is considered important. Amongst these factors, ...
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Traction efficiency and fuel consumption hgave close affinity and are considered to be important unit operations, especially during primary tillage operations. Therefore, analyzing factors that affect the amount of Traction efficiency and fuel consumption is considered important. Amongst these factors, forward speed of tractor and tillage depth are of prime importance. Experiments were conducted for comparison of draft force and fuel consumption using, three types of cultivator blades (flat Duckfoot, Duckfoot with curve shank and Chisel plow), under sandy loam soil condition by using a factorial experiment based on randomized complete block design (RCBD). The effect of forward speed (3, 6.5 and 9 km/h) and tillage depth (10 and 20 cm) was the experimental conditions. Within each experimental plot, draft force of cultivators, fuel consumption, soil cone index, soil dispersion and percent of soil moisture content were measured.Analysis of variance showed that the effects of the blade type, forward speed and depth on the draft force and fuel consumption was significant at 1%. Comparing the draft force and fuel consumption of blades in different forward speeds and also considering the relatively light texture of the soil, it was found that duckfoot blade with curve shank with forward speed of 3 km/h was more appropriate.
