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Johan Engblom - One of the best experts on this subject based on the ideXlab platform.
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surfactant softening of Plant Leaf cuticle model wax a differential scanning calorimetry dsc and quartz crystal microbalance with dissipation qcm d study
Journal of Colloid and Interface Science, 2014Co-Authors: Anton Fagerstrom, Vitaly Kocherbitov, Peter Westbye, Karin Bergstrom, Thomas Arnebrant, Johan EngblomAbstract:Abstract The aim was to quantify the softening effect that two surfactants (C 10 EO 7 and C 8 G 1.6 ) have on a Plant Leaf cuticle model wax. Effects on the thermotropic phase behavior and fluidity of the wax (C 22 H 45 OH/C 32 H 66 /H 2 O) were determined. The model wax is crystalline at ambient conditions, yet it is clearly softened by the surfactants. Both surfactants decreased the transition temperatures in the wax and the G ″/ G ′ ratio of the wax film increased in irreversible steps following surfactant exposure. C 10 EO 7 has a stronger fluidizing effect than C 8 G 1.6 due to stronger interaction with the hydrophobic waxes. Intracuticular waxes (IW) comprise both crystalline and amorphous domains and it has previously been proposed that the fluidizing effects of surfactants are due to interactions with the amorphous parts. New data suggests that this may be a simplification. Surfactants may also absorb in crevices between crystalline domains. This causes an irreversible effect and a softer cuticle wax.
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characterization of a Plant Leaf cuticle model wax phase behaviour ofmodel wax water systems
Thermochimica Acta, 2013Co-Authors: Anton Fagerstrom, Vitaly Kocherbitov, Peter Westbye, Karin Bergstrom, Varvara Mamontova, Johan EngblomAbstract:Abstract We investigated the thermotropic phase behaviour of Plant Leaf intracuticular wax and two representatives of its main components, 1-docosanol (C22H45OH) and dotriacontane (C32H66), in dry and hydrated state. One objective was to obtain a model wax, which can be used to estimate formulations effects on cuticle diffusivity in vitro. The two wax components were chosen based on results from Gas Chromatography coupled to Mass Spectrometry analysis of cuticular wax. The wax was extracted from Clivia Miniata Regel leaves and contained 68% primary alcohols (C16–C32) and 16% n-alkanes (C21–C33). Differential Scanning Calorimetry, Polarized Light Microscopy and Small- and Wide Angle X-ray Diffraction were used to characterize the cuticular extract and the phase behaviour of the C22H45OH/C32H66/H2O model system. Four individual crystalline phases were discovered in the model wax–water system and eutectic melting occurred in both dry and hydrated state. The thermotropic transitions of the model wax occur within the broader transition region of the extracted Leaf wax.
Sylvie Cloutier - One of the best experts on this subject based on the ideXlab platform.
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molecular and phenotypic characterization of seedling and adult Plant Leaf rust resistance in a world wheat collection
Molecular Breeding, 2013Co-Authors: Brent Mccallum, Abdulsalam Dakouri, Natasa Radovanovic, Sylvie CloutierAbstract:Genetic resistance is the most effective approach to managing wheat Leaf rust. The aim of this study was to characterize seedling and adult Plant Leaf rust resistance of a world wheat collection. Using controlled inoculation with ten races of Puccinia triticina, 14 seedling resistance genes were determined or postulated to be present in the collection. Lr1, Lr3, Lr10 and Lr20 were the most prevalent genes around the world while Lr9, Lr14b, Lr3ka and/or Lr30 and Lr26 were rare. To confirm some gene postulations, the collection was screened with gene-specific molecular markers for Lr1, Lr10, Lr21 and Lr34. Although possessing the Lr1 and/or Lr10 gene-specific marker, 51 accessions showed unexpected high infection types to P. triticina race BBBD. The collection was tested in the field, where rust resistance ranged from nearly immune or highly resistant with severity of 1 % and resistant host response to highly susceptible with severity of 84 % and susceptible host response. The majority of the accessions possessing the adult Plant resistance (APR) gene Lr34 had a maximum rust severity of 0–35 %, similar to or better than accession RL6058, a Thatcher-Lr34 near-isogenic line. Many accessions displayed an immune response or a high level of resistance under field conditions, likely as a result of synergy between APR genes or between APR and seedling resistance genes. However, accessions with three or more seedling resistance genes had an overall lower field severity than those with two or fewer. Immune or highly resistant accessions are potential sources for improvement of Leaf rust resistance. In addition, some lines were postulated to have known but unidentified genes/alleles or novel genes, also constituting potentially important sources of novel resistance. Electronic supplementary material The online version of this article (doi:10.1007/s11032-013-9899-8) contains supplementary material, which is available to authorized users.
Zhongqiu Zhao - One of the best experts on this subject based on the ideXlab platform.
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apLeaf an efficient android based Plant Leaf identification system
Neurocomputing, 2015Co-Authors: Zhongqiu Zhao, Yiuming Cheung, Yuan Yan Tang, Chun Lung Philip ChenAbstract:Abstract To automatically identify Plant species is very useful for ecologists, amateur botanists, educators, and so on. The Leafsnap is the first successful mobile application system which tackles this problem. However, the Leafsnap is based on the IOS platform. And to the best of our knowledge, as the mobile operation system, the Android is more popular than the IOS. In this paper, an Android-based mobile application designed to automatically identify Plant species according to the photographs of tree leaves is described. In this application, one Leaf image can be either a digital image from one existing Leaf image database or a picture collected by a camera. The picture should be a single Leaf placed on a light and untextured background without other clutter. The identification process consists of three steps: Leaf image segmentation, feature extraction, and species identification. The demo system is evaluated on the ImageCLEF2012 Plant Identification database which contains 126 tree species from the French Mediterranean area. The outputs of the system to users are the top several species which match the query Leaf image the best, as well as the textual descriptions and additional images about Plant leaves, flowers, etc. Our system works well with state-of-the-art identification performance.
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Plant Leaf identification via a growing convolution neural network with progressive sample learning
Asian Conference on Computer Vision, 2014Co-Authors: Zhongqiu Zhao, Baojian Xie, Yiuming CheungAbstract:Plant identification is an important problem for ecologists, amateur botanists, educators, and so on. Leaf, which can be easily obtained, is usually one of the important factors of Plants. In this paper, we propose a growing convolution neural network (GCNN) for Plant Leaf identification and report the promising results on the ImageCLEF2012 Plant Identification database. The GCNN owns a growing structure which starts training from a simple structure of a single convolution kernel and is gradually added new convolution neurons to. Simultaneously, the growing connection weights are modified until the squared-error achieves the desired result. Moreover, we propose a progressive learning method to determine the number of learning samples, which can further improve the recognition rate. Experiments and analyses show that our proposed GCNN outperforms other state-of-the-art algorithms such as the traditional CNN and the hand-crafted features with SVM classifiers.
Deshuang Huang - One of the best experts on this subject based on the ideXlab platform.
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multiscale distance matrix for fast Plant Leaf recognition
IEEE Transactions on Image Processing, 2012Co-Authors: Rongxiang Hu, Haibin Ling, Deshuang HuangAbstract:In this brief, we propose a novel contour-based shape descriptor, called the multiscale distance matrix, to capture the shape geometry while being invariant to translation, rotation, scaling, and bilateral symmetry. The descriptor is further combined with a dimensionality reduction to improve its discriminative power. The proposed method avoids the time-consuming pointwise matching encountered in most of the previously used shape recognition algorithms. It is therefore fast and suitable for real-time applications. We applied the proposed method to the task of plan Leaf recognition with experiments on two data sets, the Swedish Leaf data set and the ICL Leaf data set. The experimental results clearly demonstrate the effectiveness and efficiency of the proposed descriptor.
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classification of Plant Leaf images with complicated background
International Conference on Intelligent Computing, 2008Co-Authors: Xiaofeng Wang, Deshuang Huang, Laurent HeutteAbstract:Classifying Plant leaves has so far been an important and difficult task, especially for leaves with complicated background where some interferents and overlapping phenomena may exist. In this paper, an efficient classification framework for Leaf images with complicated background is proposed. First, a so-called automatic marker-controlled watershed segmentation method combined with pre-segmentation and morphological operation is introduced to segment Leaf images with complicated background based on the prior shape information. Then, seven Hu geometric moments and sixteen Zernike moments are extracted as shape features from segmented binary images after Leafstalk removal. In addition, a moving center hypersphere (MCH) classifier which can efficiently compress feature data is designed to address obtained mass high-dimensional shape features. Finally, experimental results on some practical Plant leaves show that proposed classification framework works well while classifying Leaf images with complicated background. There are twenty classes of practical Plant leaves successfully classified and the average correct classification rate is up to 92.6%.
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computer aided Plant species identification capsi based on Leaf shape matching technique
Transactions of the Institute of Measurement and Control, 2006Co-Authors: Jixiang Du, Deshuang Huang, Xiaofeng Wang, Xiao GuAbstract:In this paper, an efficient computer-aided Plant species identification (CAPSI) approach is proposed, which is based on Plant Leaf images using a shape matching technique. Firstly, a Douglas - Peucker approximation algorithm is adopted to the original Leaf shapes and a new shape representation is used to form the sequence of invariant attributes. Then a modified dynamic programming (MDP) algorithm for shape matching is proposed for the Plant Leaf recognition. Finally, the superiority of our proposed method over traditional approaches to Plant species identification is demonstrated by experiment. The experimental result showed that our proposed algorithm for Leaf shape matching is very suitable for the recognition of not only intact but also partial, distorted and overlapped Plant leaves due to its robustness.
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computer aided Plant species identification capsi based on Leaf shape matching technique
Transactions of the Institute of Measurement and Control, 2006Co-Authors: Deshuang Huang, Xiaofeng WangAbstract:In this paper, an efficient computer-aided Plant species identification (CAPSI) approach is proposed, which is based on Plant Leaf images using a shape matching technique. Firstly, a Douglas - Peuc...
Anton Fagerstrom - One of the best experts on this subject based on the ideXlab platform.
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surfactant softening of Plant Leaf cuticle model wax a differential scanning calorimetry dsc and quartz crystal microbalance with dissipation qcm d study
Journal of Colloid and Interface Science, 2014Co-Authors: Anton Fagerstrom, Vitaly Kocherbitov, Peter Westbye, Karin Bergstrom, Thomas Arnebrant, Johan EngblomAbstract:Abstract The aim was to quantify the softening effect that two surfactants (C 10 EO 7 and C 8 G 1.6 ) have on a Plant Leaf cuticle model wax. Effects on the thermotropic phase behavior and fluidity of the wax (C 22 H 45 OH/C 32 H 66 /H 2 O) were determined. The model wax is crystalline at ambient conditions, yet it is clearly softened by the surfactants. Both surfactants decreased the transition temperatures in the wax and the G ″/ G ′ ratio of the wax film increased in irreversible steps following surfactant exposure. C 10 EO 7 has a stronger fluidizing effect than C 8 G 1.6 due to stronger interaction with the hydrophobic waxes. Intracuticular waxes (IW) comprise both crystalline and amorphous domains and it has previously been proposed that the fluidizing effects of surfactants are due to interactions with the amorphous parts. New data suggests that this may be a simplification. Surfactants may also absorb in crevices between crystalline domains. This causes an irreversible effect and a softer cuticle wax.
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characterization of a Plant Leaf cuticle model wax phase behaviour ofmodel wax water systems
Thermochimica Acta, 2013Co-Authors: Anton Fagerstrom, Vitaly Kocherbitov, Peter Westbye, Karin Bergstrom, Varvara Mamontova, Johan EngblomAbstract:Abstract We investigated the thermotropic phase behaviour of Plant Leaf intracuticular wax and two representatives of its main components, 1-docosanol (C22H45OH) and dotriacontane (C32H66), in dry and hydrated state. One objective was to obtain a model wax, which can be used to estimate formulations effects on cuticle diffusivity in vitro. The two wax components were chosen based on results from Gas Chromatography coupled to Mass Spectrometry analysis of cuticular wax. The wax was extracted from Clivia Miniata Regel leaves and contained 68% primary alcohols (C16–C32) and 16% n-alkanes (C21–C33). Differential Scanning Calorimetry, Polarized Light Microscopy and Small- and Wide Angle X-ray Diffraction were used to characterize the cuticular extract and the phase behaviour of the C22H45OH/C32H66/H2O model system. Four individual crystalline phases were discovered in the model wax–water system and eutectic melting occurred in both dry and hydrated state. The thermotropic transitions of the model wax occur within the broader transition region of the extracted Leaf wax.