X-RAY BASED GERMINATION TEST OF COTTON SEED

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Published: Jun 20, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i5.3429
Keywords:
Germination Test, X-ray radiography, Digital image processing, MATLAB.

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Mrinal Ruprao Sawarkar
Sipna College of Engineering, Amravati, Maharashtra, India.

Abstract

In this paper we used digital image processing for germination from X-ray images of cotton seeds. Germination is the process by which a plant grows from a seed. The methods discussed in this paper are internal damages, embryo, and percentage of germination of cotton seeds. The recent development of digital image processing techniques for monitoring cotton seed germination has been done. X-ray analysis can be used to determine the quality of cotton seeds, showing the cause of bad germination. X-ray images provide information on the internal structure and morphology of seeds, mechanical damage, and percentage of empty and filled seeds, micro fractures, possible embryo deformations and insect infestation. This paper various digital image processing techniques which reduces the labour input required to evaluate seedling growth rate and increases the accuracy of these measurements. X-ray photographs were prepared with Faxitron 43805N X-ray Film exposed at 10kev, 2mA(soft X-ray) at a distance of 35cm from the X-ray source for 2min. X-ray photographs were evaluated based on embryo morphology and the presence of endosperm. Embryo morphology was scored as either normal or abnormal.

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Vol. 8 No. 5 (2017): May-June 2017
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References

Seed Vigor Testing Handbook, AOSA. Contribution No. 35, 1992, pp. 101.

Guide to Handling of Tropical and Subtropical Forest Seed’ Chapter 11, Seed Testing, by Lars Schmidt, Danida Forest Seed Centre, 2000.

‘Seed Technology’, 2nd Edition, by Rattan Lal Agrawal, Oxford & IBH Publishing Co. Pvt. Ltd. New Delhi. 2004

Y. Sako, M. B. McDonald, K. Fujimura, A. F. Evans, and M. A. Bennett, ‘A System for Automated Seed Vigor Assessment’, 2001.

A.L. Hoffmaster, K. Fujimura, M.B. McDonald, M.A. Bennett, ‘An Automated System for Vigor Testing Three-Day-Old Soybean Seedlings’, 2003.

Robert L. Geneve, Sharon T. Kester, ‘Evaluation of Seedling Size Following Germination Using Computer-aided Analysis of Digital Images from a Flat-bed Scanner’, HortScience 36(6): 1117-1120, 2001.

K. Oakley, S. T. Kester, R.L. Geneve, ‘Computeraided Digital Image Analysis of Seedling Size and Growth Rate for Assessing Seed Vigor in Impatiens’, Seed Sci. & Technology, 32, 907-915, 2004.

M. S. Howarth, P.C. Stanwood, ‘Measurement of Seedling Growth Rate By Machine Vision’,

Emerging Technologies Div. of ASAE, Vol. 36(3): 959-963, May-June 1993.

A. Dell’Aquilla, ‘Application of a Computer– Aided Image Analysis System to Evaluate Seed

Germination under Different Environmental Conditions’, Ital. J. Agron., 8, 1, 51-62, 2004.

Chao Li, Amar Raheja, and David W. Still, ‘Application of Computer Vision for Lettuce Seeds Germination Detection’.

Antonio Dell’Aquilla,‘New Perspectives for Seed Germination Testing Through Digital Imaging Technology’, The Open Agriculture Journal, 2009.