Measuring Leaf Area using Otsu Segmentation Method (LAMOS)

Radzali, Muhammad Haqqiman; Kamal, Nor Ashikin Mohamad; Diah, Norizan Mat

doi:10.17485/ijst/2016/v9i48/109307

Cited by 8 publications

(5 citation statements)

References 6 publications

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“…(2012) or Visual C++ in Haqqiman Radzali et al. (2016)) or user adjustments (e.g. Schrader et al., 2017), the full automation of FAMeLeS enabled high‐precision measurements on thousands of leaves, including isolated leaves or multiple leaves scanned at once, regardless of the number of leaves in the image.…”

Section: Discussionmentioning

confidence: 99%

“…Comparisons of leaf area measurements errors between methods on a set of 145 leaves belonging to 69 species.The accuracy of FAMeLeS on images from field sampling mixed with web images attests to the efficiency of the method even with images from multiple devices (scanner or photographs). While some authors warned about the limitation of their method depending on image quality(Meira et al, 2020) or brightness(Haqqiman Radzali et al, 2016), FAMeLeS has proven to be very tolerant of the di-versity of image sizes (compressed or not), resolutions and lighting conditions which makes it possible to work on existing leaf image databases or to aggregate data sets from different sources. The combination of such a high tolerance to image type and leaf characteristics offers the opportunity to build standardized database of leaf binary images from any biome, and to produce high amounts of data to address functional ecology questions, to study biogeographical patterns and drivers of morphological leaf traits and to feed allometric models and algorithms of plant leaf classification.…”

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confidence: 99%

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FAMeLeS: A multispecies and fully automated method to measure morphological leaf traits

Montès,

Tosini,

Laffont‐Schwob

et al. 2024

Methods Ecol Evol

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Leaf shape parameters are of key importance to explain the role of energy balance and water economy in plant species distribution, plant productivity and, more generally, in plant–environment interactions. Yet, leaf shape measurements based on image processing are still challenging due to the high diversity of leaf shapes, colours and sizes leading to the development of time‐consuming methods with a narrow field of applicability, sometimes species‐specific or often limited to a few species. We developed a fully automated method for measuring multiple leaf shape parameters (area, perimeter, length, width, circularity and solidity) based on a large image sampling of leaf diversity (including litter) belonging to 587 species and spread over 232 countries worldwide. To evaluate the accuracy of the method to detect small objects, the sampling particularly targeted Mediterranean ecosystems (32 species and 25,205 leaves), in which small leaves often represent methodological challenges. We compared our approach and found that its mean error in leaf area measurement (+0.46%) was 1.7–148 times lower than four existing methods. It was also the only one capable of detecting and measuring all leaves in the test data set, even variegated and small leaves (less than 1 mm2). Its reliability was extensively checked on the largest and most diversified data set ever used. Our method, accessible to the broader scientific community, was simple, rapid and effective on multiple image file types and on a high diversity of leaf size, shape and colour. As such, our approach allows measurement not only on fresh leaves but also on dry leaves, such as leaf litter or leaves from herbaria. This tolerance to leaf characteristics is crucial to increase large‐scale sampling efforts and paves the way for a standardized multispecies approach to measuring leaf morphological traits for ecological and agricultural studies.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

FAMeLeS: A multispecies and fully automated method to measure morphological leaf traits

Montès,

Tosini,

Laffont‐Schwob

et al. 2024

Methods Ecol Evol

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“…In the case of such methods, a number of climatic, atmospheric parameters, or other external factors, can influence the accuracy according to which the leaf area is determined [92][93][94]. At the same time, these methods are very expensive because they require specialized equipment and certain calibration works, but they offer the possibility determining the leaf area and derived indices (leaf area index-LAI, leaf area duration-LAD, net assimilation rate-NAR, specific leaf area-SLA, specific leaf weight-SLW) over relatively large areas [84,[95][96][97].…”

Section: Discussionmentioning

confidence: 99%

Leaf Area Calculation Models for Vines Based on Foliar Descriptors

Sala

Dobrei

Herbei

2021

Plants

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In the case of foliar area studies on vines, with a large number of determinations, a simple, fast, sufficiently accurate and low-cost method is very useful. The typology of leaves on the vine is complex, characterized by several descriptive parameters: median rib; secondary venations of the first and second order; angles between the median rib and the secondary venations; sinuses; length and width of the leaf. The present study aimed to evaluate models for calculating the leaf area based on descriptive parameters and KA (KA as the surface constant used to calculate the leaf area) for six vine cultivars, ‘Cabernet Sauvignon’ (CS), ‘Muscat Iantarnîi’ (MI), ‘Muscat Ottonel’ (MO), ‘Chasselas’ (Ch), ‘Victoria’ (Vi) and ‘Muscat Hamburg’ (MH). The determined KA surface constants had subunit values (0.91 to 0.97), except for the cultivars ‘Muscat Iantarnîi’ and ‘Muscat Ottonel’ where the surface constant KA2 (in relation to the second-order secondary venations) had supraunitary values (1.07 and 1.08, respectively). The determination of the leaf area was possible under different conditions of statistical accuracy (R2 = 0.477, p = 0.0119, up to R2 = 0.988, p < 0.001) in relation to the variety and parametric descriptors considered. The models obtained from the regression analysis facilitated a more reliable prediction of the leaf area based on the elements on the left side of the leaf, in relation to the median rib, compared to those on the right. The accuracy of the results was checked on the basis of minimum error (ME) and confirmed by parameters R2, p and RMSE.

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“…Leaf thickness was measured using a digital vernier caliper, making sure to avoid the leaf midribs. Leaf area was measured by drawing a leaf outline on A4-sized paper and measuring the area of leaves by the grid method (Radzali et al 2016). The sampled leaves were kept in between newspapers using the herbarium press and brought to the laboratory.…”

Section: Leaf Morphological Traitsmentioning

confidence: 99%

Regeneration and leaf traits variation of Rhododendron campanulatum along elevation gradient in western Nepal Himalaya

Karki,

Pandeya,

Bhandari

et al. 2024

J Ecol Environ

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Plant species of the alpine treeline ecotone are highly sensitive to climate change and may adjust their population dynamics, and functional traits in response to changing climate. This study examined regeneration patterns and leaf traits variations in an important treeline ecotone element Rhododendron campanulatum along the elevation gradient in western Nepal to assess its potential adaptive responses to climate change. The distribution range of R. campanulatum (3,400-3,800 m above sea level [a.s.l.]) was divided into five horizontal bands, each with a 100 m elevational range. Eight plots (10 m × 10 m) were sampled in each band, resulting into a total of 40 plots. In each plot, all R. campanulatum individuals and co-occurring tree species were counted. From each elevation, R. campanulatum leaf samples were collected to determine leaf dimensions, leaf density, specific leaf area (SLA), and stomatal density (SD). Results: The density-diameter curve indicated that R. campanulatum was regenerating well, with enhanced regeneration at higher elevation (3,800 m a.s.l.) than at lower. Tree canopy cover appeared to be the major determinant of R. campanulatum regeneration, as indicated by a higher number of seedlings in treeless stands. With increasing elevation, the leaf length, width, SLA, and stomata length decreased but leaf thickness and SD increased. Conclusions: Overall, a higher regeneration and lower SLA with the high SD in the leaves at the upper limit of the species distribution suggested that R. campanulatum is well adapted at its upper distribution range with the possibility of upslope range shift as temperature increases.

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Measuring Leaf Area using Otsu Segmentation Method (LAMOS)

Cited by 8 publications

References 6 publications

FAMeLeS: A multispecies and fully automated method to measure morphological leaf traits

FAMeLeS: A multispecies and fully automated method to measure morphological leaf traits

Leaf Area Calculation Models for Vines Based on Foliar Descriptors

Regeneration and leaf traits variation of Rhododendron campanulatum along elevation gradient in western Nepal Himalaya

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