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Proceedings Paper

Application of image analysis techniques to evaluate the effect of urban residuals fertilization on corn (Zea mays) production
Author(s): P. Menesatti; S. D'Andrea; S. Socciarelli
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Paper Abstract

The work focused the application of an image analysis technique to determine corn leaves morphology as objective indicator of the growth performance of corn (Zea mays) resulting from the urban residual fertilization. The analyses were related to six fertilization plots: original soil; chemical fertilizer (160 and 200 kg ha-1 of nitrogen); organic fertilizer (32 t ha-1) and two different doses of urban residues (sewage sludges) (7.5 and 22.5 t ha-1, this last amount corresponds to is the maximum level permitted from the Italian law in three year of fertilization). Those tests were realized by full randomized plots, with two three repetitions for each treatment. Measurements were performed for the first year of the trials in the period proximate to harvest (Rome, Italy - July 2000). Four plants for each plot were harvested and stripped of all leaves, whose RGB images were acquired by a digital photo camera (Kodak Ltd). Image analysis was performed first through the separation of RGB channels into single monochromatic 8-bit distribution, than the blue channel images, the most informative, were then submitted to enhancement, low pass filtering to reduce noise, threshold of binarization (based on statistical parameter affected on Gaussian grey levels distribution), binary morphology and object measurement. For ach single leaf the length, the width, the area were measured. The test results indicated positive and significant responses in relation between the crop growth (leaves area, length and width greater) and the different doses of urban residues (sewage sludges).

Paper Details

Date Published: 22 October 2007
PDF: 6 pages
Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 67611B (22 October 2007); doi: 10.1117/12.735558
Show Author Affiliations
P. Menesatti, Agricultural Research Council, Agricultural Mechanization Research Institute (Italy)
S. D'Andrea, Agricultural Research Council, Agricultural Mechanization Research Institute (Italy)
S. Socciarelli, Agricultural Research Council, Plant Nutrition Research Institute (Italy)

Published in SPIE Proceedings Vol. 6761:
Optics for Natural Resources, Agriculture, and Foods II
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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