Flowering estimation in apple orchards by image analysis

Flowering estimation in apple orchards by image analysis Tree-specific management practice related to individual tree physiological condition is necessary for higher quality and quantity in apple fruit production. Detection of apple flowering abundance based on analysis of HSL (hue, saturation, luminance) images was used to estimate the number of flower clusters (FC) of individual trees in a high density apple orchard. The image acquisition was performed with a still camera and an industrial color camera during the day and night. The FC estimation algorithm included HSL thresholding with parameter optimization. Three hypothetical, tree-specific management practices (sprayings) were assumed, using >25, >50 and >100 FC thresholds to carry out the practice. When an industrial camera was used for image acquisition during the daytime and hypothetical spraying was done by on/off criterion >100 FC per tree, 10 % incorrect executions were identified. Comparable FC counting performance was achieved by using a still camera or an industrial camera. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Flowering estimation in apple orchards by image analysis

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Publisher
Springer US
Copyright
Copyright © 2013 by Springer Science+Business Media New York
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-013-9341-6
Publisher site
See Article on Publisher Site

Abstract

Tree-specific management practice related to individual tree physiological condition is necessary for higher quality and quantity in apple fruit production. Detection of apple flowering abundance based on analysis of HSL (hue, saturation, luminance) images was used to estimate the number of flower clusters (FC) of individual trees in a high density apple orchard. The image acquisition was performed with a still camera and an industrial color camera during the day and night. The FC estimation algorithm included HSL thresholding with parameter optimization. Three hypothetical, tree-specific management practices (sprayings) were assumed, using >25, >50 and >100 FC thresholds to carry out the practice. When an industrial camera was used for image acquisition during the daytime and hypothetical spraying was done by on/off criterion >100 FC per tree, 10 % incorrect executions were identified. Comparable FC counting performance was achieved by using a still camera or an industrial camera.

Journal

Precision AgricultureSpringer Journals

Published: Dec 20, 2013

References

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