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

Q3 Agricultural and Biological Sciences Journal of Horticultural Research Pub Date : 2021-12-01 DOI:10.2478/johr-2021-0017
W. Treder, K. Klamkowski, A. Tryngiel-Gać, K. Wójcik
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Abstract

Abstract The 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%.
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ImageJ软件在梨树开花强度和生长活力评价中的应用
摘要本研究利用ImageJ软件进行图像采集和处理,评价了“会议”梨树生长活力和开花强度的可能性。为了评估开花强度,我们在树木盛开时进行了人工花簇计数和拍摄照片。树木活力是通过人工测量单株树中央主枝和枝条的总长度来估算的。这些树是用手持相机从相同的距离拍摄的。通过图像分析来评估树木活力或开花的校准模型是基于对9棵枝条总长度或花簇数量不同的树木的测量和拍摄的照片。然后,在26棵非选择的树木上对模型进行质量评估。图像处理采用ImageJ软件。照片上测得的花瓣表面积与计算到的花序数之间有较高的回归系数(r2 = 0.98);然而,第二年进行的观测表明,需要在每个评价季节单独校准估算模型。随后,利用先前确定的校准模型对梨树开花强度的估计质量进行了评估。根据测量时间的不同,平均绝对百分比误差(MAPE)值从14.0%到21.8%不等。在评估树木生长活力时,每棵树的实际枝长与通过摄影图像分析得到的值也有很高的相关性(r2 = 0.98),其中MAPE误差为12.9%。
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来源期刊
Journal of Horticultural Research
Journal of Horticultural Research Agricultural and Biological Sciences-Horticulture
CiteScore
1.90
自引率
0.00%
发文量
14
审稿时长
20 weeks
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