Image analysis and statistical modelling for measurement and quality assessment of ornamental horticulture crops in glasshouses
Parsons, Nicholas R., Edmondson, R. N. and Song, Yu. (2009) Image analysis and statistical modelling for measurement and quality assessment of ornamental horticulture crops in glasshouses. Biosystems Engineering, Vol.10 (No.2). pp. 161-168. ISSN 1537-5110
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Official URL: http://dx.doi.org/10.1016/j.biosystemseng.2009.06....
Image analysis for ornamental crops is discussed with examples from the bedding plant industry. Feed-forward artificial neural networks are used to segment top and side view images of three contrasting species of bedding plants. The segmented images provide objective measurements of leaf and flower cover, colour, uniformity and leaf canopy height. On each imaging occasion, each pack was scored for quality by an assessor panel and it is shown that image analysis can explain 88.5%, 81.7% and 70.4% of the panel quality scores for the three species, respectively. Stereoscopy for crop height and uniformity is outlined briefly. The methods discussed here could be used for crop grading at marketing or for monitoring and assessment of growing crops within a glasshouse during all stages of production.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HA Statistics
S Agriculture > SB Plant culture
|Divisions:||Faculty of Medicine > Warwick Medical School > Health Sciences
Faculty of Science > Life Sciences (2010- ) > Warwick HRI (2004-2010)
Faculty of Medicine > Warwick Medical School
|Library of Congress Subject Headings (LCSH):||Greenhouse plants -- Mathematical models, Plants, Ornamental, Image analysis -- Mathematical models, Horticulture -- Mathematical models, Photography, Stereoscopic|
|Journal or Publication Title:||Biosystems Engineering|
|Official Date:||October 2009|
|Page Range:||pp. 161-168|
|Access rights to Published version:||Open Access|
|Funder:||Horticultural Development Council (Great Britain) (HDC)|
|Grant number:||PC200 (HDC), CP37 (HDC)|
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