No abstract

Wheat is one of the most important strategic crops in Iran and in the world. The major component that distinguishes wheat from other grains is the gluten section. In Iran, sunn pest is one of the most important factors influencing the characteristics of wheat gluten and in removing it from a balanced state. The existence of bug-damaged grains in wheat will reduce the quality and price of the product. In addition, damaged grains reduce the enrichment of wheat and the quality of bread products. In this study, after preprocessing and segmentation of images, 25 features including 9 colour features, 10 morphological features, and 6 textual statistical features were extracted so as to classify healthy and bug-damaged wheat grains of Azar cultivar of four levels of moisture content (9, 11.5, 14 and 16.5% w.b.) and two lighting colours (yellow light, the composition of yellow and white lights). Using feature selection methods in the WEKA software and the CfsSubsetEval evaluator, 11 features were chosen as inputs of artificial neural network, decision tree and discriment analysis classifiers. The results showed that the decision tree with the J.48 algorithm had the highest classification accuracy of 90.20%. This was followed by artificial neural network classifier with the topology of 11-19-2 and discrimient analysis classifier at 87.46 and 81.81%, respectively

One of the aerodynamic characteristics of lentil is its terminal velocity. In order to determinate the terminal velocity, was designed a vertical wind tunnel. It was fabricated based on existing methods and standards. For decreasing the non-uniformity of airflow in the vertical wind column, was used a honey comb test area with 5 mesh screens. So, a wind tunnel nozzle was designed and fabricated using Morel method with the aim of increasing airflow rate and decreasing losses due to mesh screens. The height and section area of tunnel were 1.425 m and 0.1 × 0.1 m2, respectively. The pressure loss values were calculated at different parts of tunnel and then, the required power of tunnel was determined. In this study, lentil grains of Kimia and Gachsaran varieties were separated at three groups based on their size (small, medium and large). Then, the terminal velocity was measured at 5 levels of moisture content (8, 12, 16, 20 and 24% (w.b.)) for each group. The results showed that Kimia and Gachsaran variety had the highest (7.204 m·s–1) and the lowest (6.987 m·s–1) terminal velocity, respectively. The mean value of terminal velocity increased linearly from 6.751 to 7.396 m·s–1 by increasing the moisture content from 8 to 24% (w.b.). Also, by increasing the grains dimension from small to large, the terminal velocity increased from 6.345 to 7.792 m·s–1.

Considering the fact that the presence of bug-damaged wheat in the bulk results in a decrease of the flour quality and its final product, which is bread, it is necessary to differentiate the bug-damaged wheat grains from the healthy ones. Therefore, the present study investigated the mechanical properties of bug-damaged and healthy wheat grains of the Azar cultivar. By making use of these mechanical properties, it would be possible to provide a more precise texture identification of the bug-damaged wheat grains compared to the healthy ones. In this study, the mechanical properties (rupture energy, toughness and apparent elastic coefficient) were determined under compressive loading, with four levels of loading velocity (5, 15, 25 and 35 mm.min^–1) and four levels of moisture content (9, 11.5, 14 and 16.5% wet basis) in both bug-damaged and healthy wheat grains. Due to the significant difference in the mean value of apparent elastic coefficient between the bug-damaged grains (74.779 MPa) and the healthy ones (289.071 MPa), this parameter can be employed as the most appropriate factor to distinguish the bug-damaged wheat grains from the healthy ones.