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Buğday Tanelerinin Bazı Fiziksel Özelliklerinin Görüntü İşleme Tekniğiyle Belirlenmesi

Year 2007, Volume: 13 Issue: 03, 176 - 185, 01.08.2007
https://doi.org/10.1501/Tarimbil_0000000544

Abstract

Bu araştırmada; ülkemizde yaygın olarak yetiştirilen bazı buğday çeşitleri tanelerinin uzunluk, genişlik, kalınlık, izdüşüm alanı, çevre, küresellik derecesi ve farklı şekil katsayıları gibi bazı fiziksel özelliklerinin görüntü işleme tekniğinden yararlanılarak belirlenmesi amaçlanmıştır. Ekmeklik ve makarnalık tipte 13 farklı buğday çeşidi seçilmiştir. % 10, % 12, % 14 tohum nem içeriklerindeki buğday taneleri; hilum ekseni yanda, hilum ekseni altta ve dik olmak üzere 3 farklı konumda kağıtlar üzerine yerleştirilerek örnekler hazırlanmıştır. Bunlar bir tarayıcıdan geçirilerek TIFF uzantılı dosyalar halinde bilgisayar ortamına aktarılmış ve “UTHSCSA Image Tool Version 3.0” görüntü işleme programıyla değerlendirilmiştir. Çalışma sonucunda; elle ve görüntü işlemeyle yapılan ölçüm sonuçları arasındaki korelasyon katsayısının yüksek olması nedeniyle buğday tanelerinin bazı fiziksel özelliklerinin belirlenmesinde görüntü işleme tekniğinden başarıyla yararlanılacağı belirlenmiştir

References

  • Anonim 2006. Buğday. (http://www.hatap.com/Bugday.htm).
  • Anonymous 2002. UTHSCSA Image Tool Version 3.0. Guide of Use. (http://ddsdx.uthscsa.edu)
  • Anonymous 2005. Wheat Production. (http://www.fao.org.)
  • Anonymous 2006. Cereals and Cereal Products. Determination of Moisture Content. (http://www.fao.org)
  • Bacci, L., B. R. Colucci and P. Novaro. 2002. Durum wheat quality evaluation software. Proceedings of the World Congress of Computers in Agriculture and Natural Resources, 49-55, Brazil.
  • Dalen, G. V. 2004. Determination of the size distribution and percentage of broken kernels of rice using flatbed scanning and image analysis. Food Research International 37: 51-58.
  • Deshpande S. D., S. Bal, T. P. Ojha. 1993. Physical properties of soybean. Journal of Agricultural Engineering Research 56(2): 89-98.
  • Dursun, G. I., 2001. Bazı taneli ürünlerin izdüşüm alanlarının görüntü işlemeyle belirlenmesi. Tarım Bilimleri Dergisi 7(3): 102-107.
  • Jayas, D. S. and C. Karunakaran. 2005. Machine vision system in postharvest tecnology. Stewart Postharvest Rewiev, 22.
  • Kashaninejad, M., A. Mortazavi, A. Safekordi and L. G. Tabil. 2006. Some physical propertiese of pistachio (Pistacia vera L.) nut and its kernel. Journal of Food Engineering 72(1): 30-38.
  • Keefe, P. D. 1992. A Dedicated wheat grain image analyzer. Plant Varieties and Seeds 5: 27-33.
  • Kün, E. 1983. Serin İklim Tahılları. Ankara Üniv. Ziraat Fak., Yayın No: 875, Ders Kitabı: 240, 307 s, Ankara.
  • Mohsenin, N. N. 1970. Physical Properties of Plant and Animal Materials. New York: Gordon and Breach Science Publishers.
  • Neuman, M. R., H. D. Sapirstein, E. Shwedyk and W. Bushuk. 1989. Wheat grain colour analysis by digital image processing. II. Wheat class discrimination. Journal of Cereal Science 10: 183-188.
  • Nimkar, P. M., D. S. Mandwe and R. M. Dudhe. 2005. Physical properties of moth gram. Biosystems Engineering 91(2): 183-189.
  • Pérez, A. J., F. Lopez, J. V. Benlloch and S. Christensen. 2000. Colour and shape analysis techniques for weed detection in cereal fields. Computers and Electronics in Agriculture 25: 197-212.
  • Shouche, S. P., R. Rastogi, S. G. Bhagwat and J. K. Sainis. 2001. Shape analysis of grains of Indian wheat varieties. Computers and Electronics in Agriculture 33: 55-76.
  • Symons, S. J., L. V. Schepdael and J. E. Dexter. 2003. Measurement of hard vitreous kernels in Durum wheat by machine vision. Cereal Chemistry 80(5): 511-517.
  • Tang J. and S. Sokhansanj. 1993. Geometric changes in lentil seeds caused by drying. Journal of Agricultural İletişim adresi: Engineering Research 56(4): 313-326. İlknur DURSUN
  • Trooien, T. P. and D. F. Heermann, 1992. Measurement and simulation of potato leaf area using image processing. Model development. Transactions of the ASAE 35(5): 1709-1712.
  • Zayas, I., Y. Pomeranz and F. S. Lai, 1989. Discrimination of wheat and nonwheat componentsin grain samples by image analysis. Cereal Chemistry 66 (3): 233-237.
  • Zayas, I. Y., C. R. Martin, J. L. Steele and A. Katsevich, 1996. Wheat classification using image analysis and crush force parameters. Transaction of the ASAE 39(6): 2199- 2204.

Determination of Some Physical Properties of Wheat Grains by Using Image Analysis

Year 2007, Volume: 13 Issue: 03, 176 - 185, 01.08.2007
https://doi.org/10.1501/Tarimbil_0000000544

Abstract

The objective of this study was to determine some physical properties such as length, width, thickness, projected area, sphericity, periphery and different shape coefficients relating to some variety of wheat grains which are widely grown in our country by using image analysis technique. Thirteen different wheat varieties which are suitable for bread and macaroni were selected. The tests were carried out at three moisture contents of 10, 12 and 14%. Wheat grains were placed on the papers at three different positions such as hilum axis at the lateral side, hilum axis at the under side and vertical. The samples were scanned and the images of samples were loaded to the computer as a TIFF file. Then the images of samples were evaluated using UTHSCSA Image Tool Version 3.0. At the end of this study, it was found high correlation between results obtained manually and image analysis. As a result, it was determined that image analysis technique could be used for the determination of some physical properties of wheat grains

References

  • Anonim 2006. Buğday. (http://www.hatap.com/Bugday.htm).
  • Anonymous 2002. UTHSCSA Image Tool Version 3.0. Guide of Use. (http://ddsdx.uthscsa.edu)
  • Anonymous 2005. Wheat Production. (http://www.fao.org.)
  • Anonymous 2006. Cereals and Cereal Products. Determination of Moisture Content. (http://www.fao.org)
  • Bacci, L., B. R. Colucci and P. Novaro. 2002. Durum wheat quality evaluation software. Proceedings of the World Congress of Computers in Agriculture and Natural Resources, 49-55, Brazil.
  • Dalen, G. V. 2004. Determination of the size distribution and percentage of broken kernels of rice using flatbed scanning and image analysis. Food Research International 37: 51-58.
  • Deshpande S. D., S. Bal, T. P. Ojha. 1993. Physical properties of soybean. Journal of Agricultural Engineering Research 56(2): 89-98.
  • Dursun, G. I., 2001. Bazı taneli ürünlerin izdüşüm alanlarının görüntü işlemeyle belirlenmesi. Tarım Bilimleri Dergisi 7(3): 102-107.
  • Jayas, D. S. and C. Karunakaran. 2005. Machine vision system in postharvest tecnology. Stewart Postharvest Rewiev, 22.
  • Kashaninejad, M., A. Mortazavi, A. Safekordi and L. G. Tabil. 2006. Some physical propertiese of pistachio (Pistacia vera L.) nut and its kernel. Journal of Food Engineering 72(1): 30-38.
  • Keefe, P. D. 1992. A Dedicated wheat grain image analyzer. Plant Varieties and Seeds 5: 27-33.
  • Kün, E. 1983. Serin İklim Tahılları. Ankara Üniv. Ziraat Fak., Yayın No: 875, Ders Kitabı: 240, 307 s, Ankara.
  • Mohsenin, N. N. 1970. Physical Properties of Plant and Animal Materials. New York: Gordon and Breach Science Publishers.
  • Neuman, M. R., H. D. Sapirstein, E. Shwedyk and W. Bushuk. 1989. Wheat grain colour analysis by digital image processing. II. Wheat class discrimination. Journal of Cereal Science 10: 183-188.
  • Nimkar, P. M., D. S. Mandwe and R. M. Dudhe. 2005. Physical properties of moth gram. Biosystems Engineering 91(2): 183-189.
  • Pérez, A. J., F. Lopez, J. V. Benlloch and S. Christensen. 2000. Colour and shape analysis techniques for weed detection in cereal fields. Computers and Electronics in Agriculture 25: 197-212.
  • Shouche, S. P., R. Rastogi, S. G. Bhagwat and J. K. Sainis. 2001. Shape analysis of grains of Indian wheat varieties. Computers and Electronics in Agriculture 33: 55-76.
  • Symons, S. J., L. V. Schepdael and J. E. Dexter. 2003. Measurement of hard vitreous kernels in Durum wheat by machine vision. Cereal Chemistry 80(5): 511-517.
  • Tang J. and S. Sokhansanj. 1993. Geometric changes in lentil seeds caused by drying. Journal of Agricultural İletişim adresi: Engineering Research 56(4): 313-326. İlknur DURSUN
  • Trooien, T. P. and D. F. Heermann, 1992. Measurement and simulation of potato leaf area using image processing. Model development. Transactions of the ASAE 35(5): 1709-1712.
  • Zayas, I., Y. Pomeranz and F. S. Lai, 1989. Discrimination of wheat and nonwheat componentsin grain samples by image analysis. Cereal Chemistry 66 (3): 233-237.
  • Zayas, I. Y., C. R. Martin, J. L. Steele and A. Katsevich, 1996. Wheat classification using image analysis and crush force parameters. Transaction of the ASAE 39(6): 2199- 2204.
There are 22 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Hande Yıldız Demirbaş This is me

İlknur Dursun This is me

Publication Date August 1, 2007
Submission Date January 1, 2007
Published in Issue Year 2007 Volume: 13 Issue: 03

Cite

APA Demirbaş, H. Y., & Dursun, İ. (2007). Buğday Tanelerinin Bazı Fiziksel Özelliklerinin Görüntü İşleme Tekniğiyle Belirlenmesi. Journal of Agricultural Sciences, 13(03), 176-185. https://doi.org/10.1501/Tarimbil_0000000544

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