کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8875367 1623648 2017 44 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evaluation of some engineering properties of cucumber (Cucumis sativus L.) seeds and kernels based on image processing
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
پیش نمایش صفحه اول مقاله
Evaluation of some engineering properties of cucumber (Cucumis sativus L.) seeds and kernels based on image processing
چکیده انگلیسی
In this study, a method based on digital image processing was employed to investigate effect of the moisture content on gravimetrical and frictional properties of the cucumber seeds and kernels. This research indicated that the application of visual machines and the image processing could be a rapid method that enables accurate measurement of the dimensional parameters of two varieties of this product meticulously. The length, width, and thickness of the seeds of Rashid variety ranged from 6.40 to 9.07, 2.91 to 4.21 and 0.65 to1.50 mm, respectively; the corresponding value of Negin variety ranged from 6.89 to 9.07, 2.49 to 4.21, and 0.69 to 1.68 mm, respectively. Kernel and shell ratios of the Rashid variety were found to be 69.811 and 30.189%, respectively; the corresponding values of the Negin variety were found to be 72.727 and 27.273%, respectively. Despite the bulk densities of the two varieties of cucumber seeds and kernels that decreased with the moisture content, true density and porosity of the two varieties of cucumber seeds and kernels increased. As the moisture content increased from 5.04 to 21.12% (d.b), the angle of the static friction of the seeds of Negin variety increased from 30.39° to 37.18°, 28.83° to 34.99°, 24.37° to 30.04°, and 15.77° to 19.57° for wood, rubber, iron, and galvanized, respectively,; the corresponding value of the Negin variety increased from 21.12° to 27.16°, 24.43° to 31.41°, 19.90° to 25.59° and 14.09° to 18.12° as the moisture content increased from 5.02 to 21.02% (d.b).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Processing in Agriculture - Volume 4, Issue 4, December 2017, Pages 300-315
نویسندگان
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