Comparing digital image analysis and visual rating of gamma ray induced Bent grass (Agrostis stolonifera) mutants
238 / 50
Keywords:
Agrostis stolonifera, Digital image analysis, Dark green color index, Turf qualityAbstract
The effectiveness of digital image analysis (DIA) for determining turf quality over visual rating was judged. It provides an alternative method to measure the reflectance from vegetative surfaces and showed strong agreement with visual ratings in evaluating turf color. It is clear from the data that the correlations of hue and dark green colour index (DGCI) were significantly positive with the parameters of visual rating. There were non-significant correlation of brightness with quality and texture, and saturation and texture. The DGCI values were in line with each of these parameters when the slope of regression line was significantly different from zero (P<0.05). These relationships were better in DGCI and quality; DGCI and colour and DGCI and texture. Non-linear relationship was noticed between DGCI and saturation and DGCI and brightness. Therefore, digital photography and subsequent image analysis was capable of quantifying turf grass color in field experiments.Downloads
References
Baghzouz, M, Devitt D A and Morris R L. 2007. Assessing canopy spectral reflectance of hybrid Bermuda grass under various combinations of nitrogen and water treatments. Applied Engineering in Agriculture 23: 763–74. DOI: https://doi.org/10.13031/2013.24055
DaCosta, M, Wang Z and Huang B. 2004. Physiological adaptation of Kentucky bluegrass to localized soil drying. Crop Science 44: 1 307–14. DOI: https://doi.org/10.2135/cropsci2004.1307
Díaz Lago J E, Stuthman D D and Leonard, K J. 2003. Evaluation of components of partial resistance too at crown rust using digital image analysis. Plant Disgest 87: 667–74. DOI: https://doi.org/10.1094/PDIS.2003.87.6.667
Freund, RJ and Wilson WJ. 1993. Statistical Methods. Academic Press, San Diego, CA.
Goodenough A E and Goodenough A S. 2012. Development of a rapid and precise method of digital image analysis to quantify canopy density and structural complexity. ISRN Ecology Article ID 619842:11 http://dx.doi.org/10.5402/2012/619842. DOI: https://doi.org/10.5402/2012/619842
Horst, G L, Engelke M C, and Meyers W. 1984. Assessment of visual evaluation techniques. Agronomy Journal 76:619–21. DOI: https://doi.org/10.2134/agronj1984.00021962007600040027x
Karcher D E and Richardson M D. 2003. Quantifying turf grass color using digital image analysis. Crop Science 43: 943–51. DOI: https://doi.org/10.2135/cropsci2003.9430
Mirik M, Michels G J, Kassymzhanova M S E, Catana N C, Jones D B V and Bowling R. 2006. Using digital image analysis and spectral reflectance data to quantify damage by greenbug (Aphididae) in winter wheat. Computers and Electronics in Agriculture 51: 86–98. Tiwari A K and Kumar V .2011. Gamma-rays induced morphological changes in pot marigold (Calendulla officinalis). Progressive Agriculture-An international Journal 11(1): 99– 102. DOI: https://doi.org/10.1016/j.compag.2005.11.004
Tiwari A K, Srivastva R M, Kumar V, Yadava L B, and Mishra S K. 2010. Gamma-rays induced morphological changes in gladiolus. Progressive Agriculture-An international Journal 10: 75–82.
Tiwari A K, Kumar R, Kumar G, Ganesh B K, Saha T N, Girish K S and Tiwari B. 2014. Mutagenesis and digital image analysis of mutants for quality attributes of native Cynodon dactylon. Indian Journal of Agricultural Sciences 84 (6): 70–3.
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2015 The Indian Journal of Agricultural Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright of the articles published in The Indian Journal of Agricultural Sciences is vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR.