دانلود مقاله ISI انگلیسی شماره 81133
ترجمه فارسی عنوان مقاله

محاسبه خودکار شاخص برگ از درختان میوه با استفاده از الگوریتم های بهبود پردازش تصویر اعمال شده به تاج پوشش عکس های دیجیتال

عنوان انگلیسی
Automated computation of leaf area index from fruit trees using improved image processing algorithms applied to canopy cover digital photograpies
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
81133 2016 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Computers and Electronics in Agriculture, Volume 123, April 2016, Pages 195–202

ترجمه کلمات کلیدی
منطقه برگ تجزیه و تحلیل تصویر، سنسور دست، پوشش سایبان
کلمات کلیدی انگلیسی
Leaf area; Image analysis; Hand-held sensor; Canopy cover

Leaf area index (LAI) is a critical parameter in plant physiology for models related to growth, photosynthetic activity and evapotranspiration. It is also important for farm management purposes, since it can be used to assess the vigor of trees within a season with implications in water and fertilizer management. Among the diverse methodologies to estimate LAI, those based on cover photography are of great interest, since they are non-destructive, easy to implement, cost effective and have been demonstrated to be accurate for a range of tree species. However, these methods could have an important source of error in the LAI estimation due to the inclusion within the analysis of non-leaf material, such as trunks, shoots and fruits depending on the complexity of canopy architectures. This paper proposes a modified cover photography method based on specific image segmentation algorithms to exclude contributions from non-leaf materials in the analysis. Results from the implementation of this new image analysis method for cherry tree canopies showed a significant improvement in the estimation of LAI compared to ground truth data using allometric methods and previously available cover photography methods. The proposed methodological improvement is very simple to implement, with numerical relevance in species with complex 3D canopies where the woody elements greatly influence the total leaf area.