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Application of ImageJ Software in the assessment of flowering Intensity and growth Vigor of Pear Trees

Application of ImageJ Software in the assessment of flowering Intensity and growth Vigor of Pear... AbstractThe study evaluated the possibility of using the image acquisition and processing method with ImageJ software for estimating growth vigor and flowering intensity of ‘Conference’ pear trees. For assessing flowering intensity, manual counting of flower clusters and taking of photographs of the trees were conducted at full bloom. Tree vigor was estimated by manually measuring the total length of the central leader and shoots of individual trees. The trees were photographed from the same distance using a hand-held camera. The calibration model for assessing the vigor or flowering of trees by image analysis was based on measurements and photographs taken for nine selected trees differing in the total length of shoots or in the number of flower clusters. Then, a quality assessment of the model was carried out on 26 nonselected trees. Image processing was performed using ImageJ software. High regression coefficients were obtained between the surface area of petals measured on the photographs and the number of inflorescences counted (r2 = 0.98); however, observations carried out in the following year indicate the need for individual calibration of estimation models in each evaluation season. Subsequently, the quality of estimating the flowering intensity of pear trees was assessed using a previously determined calibration model. Mean absolute percentage error (MAPE) values ranged from 14.0% to 21.8%, depending on the measurement time. In the assessment of tree growth vigor, a high correlation (r2 = 0.98) was also obtained between the actual length of shoots measured individually for each tree and the values obtained by analyzing the photographic image, where the MAPE error was 12.9%. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Horticultural Research de Gruyter

Application of ImageJ Software in the assessment of flowering Intensity and growth Vigor of Pear Trees

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Publisher
de Gruyter
Copyright
© 2021 Waldemar Treder et al., published by Sciendo
eISSN
2300-5009
DOI
10.2478/johr-2021-0017
Publisher site
See Article on Publisher Site

Abstract

AbstractThe study evaluated the possibility of using the image acquisition and processing method with ImageJ software for estimating growth vigor and flowering intensity of ‘Conference’ pear trees. For assessing flowering intensity, manual counting of flower clusters and taking of photographs of the trees were conducted at full bloom. Tree vigor was estimated by manually measuring the total length of the central leader and shoots of individual trees. The trees were photographed from the same distance using a hand-held camera. The calibration model for assessing the vigor or flowering of trees by image analysis was based on measurements and photographs taken for nine selected trees differing in the total length of shoots or in the number of flower clusters. Then, a quality assessment of the model was carried out on 26 nonselected trees. Image processing was performed using ImageJ software. High regression coefficients were obtained between the surface area of petals measured on the photographs and the number of inflorescences counted (r2 = 0.98); however, observations carried out in the following year indicate the need for individual calibration of estimation models in each evaluation season. Subsequently, the quality of estimating the flowering intensity of pear trees was assessed using a previously determined calibration model. Mean absolute percentage error (MAPE) values ranged from 14.0% to 21.8%, depending on the measurement time. In the assessment of tree growth vigor, a high correlation (r2 = 0.98) was also obtained between the actual length of shoots measured individually for each tree and the values obtained by analyzing the photographic image, where the MAPE error was 12.9%.

Journal

Journal of Horticultural Researchde Gruyter

Published: Dec 1, 2021

Keywords: Pyrus communis; image analysis; plant morphology

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