Search results for: vascular tree
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1278

Search results for: vascular tree

978 Research and Application of Multi-Scale Three Dimensional Plant Modeling

Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

Abstract:

Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

Procedia PDF Downloads 278
977 Antifeedant Activity of Plant Extracts on the Spongy Moth (Lymantria dispar) Larvae

Authors: Jovana M. Ćirković, Aleksandar M. Radojković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

Abstract:

The protection of forests is a national interest and of strategic importance in every country. The spongy moth (Lymantria dispar) is a damaging invasive pest that can weaken and destroy trees by defoliating them. Chemical pesticides commonly used to protect forests against spongy moths not only have a negative impact on terrestrial and aquatic organisms/ecosystems but also often fail to provide significant protection. Therefore, many eco-friendly alternatives have been considered. Within this research, a new biopesticide was developed based on the method of nanoencapsulation of plant extracts in a biopolymer matrix, which provides a slow release of the active components during a substantial time period. The antifeedant activity of plant extracts of common (Fraxinus excelsior L.), manna (F. ornus L.) ash tree, and the tree of heaven Ailanthus altissima (Mill.) was tested on the spongy moth (Lymantria dispar L, 1758) larvae. To test the antifeedant activity of these compounds, the choice and non-choice tests in laboratory conditions for different plant extract concentrations (0.01, 0.1, 0.5, and 1 % v/v) were carried out. In both cases, the best results showed formulations based on the tree of heaven and common ash for the concentration of 1%, with deterioration indices of 163 and 132, respectively. The main benefit of these formulations is their versatility, effectiveness, prolonged effect, and because they are completely environmentally acceptable. Therefore, they can be considered for suppression of the spongy moth in forest ecosystems.

Keywords: Ailanthus altissima (Mill.), Fraxinus excelsior L., encapsulation, Lymantria dispar

Procedia PDF Downloads 78
976 Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering

Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

Procedia PDF Downloads 413
975 Determination of Water Pollution and Water Quality with Decision Trees

Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

Procedia PDF Downloads 83
974 A Reliable Multi-Type Vehicle Classification System

Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

Procedia PDF Downloads 359
973 Bayesian System and Copula for Event Detection and Summarization of Soccer Videos

Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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972 Fungi Associated with Decline of Kikar (Acacia nilotica) and Red River Gum (Eucalyptus camaldulensis) in Faisalabad

Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

Abstract:

During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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971 Chemical Composition and Nutritional Value of Leaves and Pods of Leucaena Leucocephala, Prosopis Laevigata and Acacia Farnesiana in a Xerophyllous Shrubland

Authors: Miguel Mellado, Cecilia Zapata

Abstract:

Goats can be exploited in harsh environments due to their capacity to adjust to limited quantity and quality forage sources. In these environments, leguminous trees can be used as supplementary feeds as foliage and fruits of these trees can contribute to maintain or improve production efficiency in ruminants. The objective of this study was to determine the nutritional value of three leguminous trees heavily selected by goats in a xerophyllous shrubland. Chemical composition and in vitro dry matter disappearance (IVDMD) of leaves and pods from leucaena (Leucaena leucocephala), mesquite (Prosopis laevigata) and huisache (Acacia farnesiana) is presented. Crude protein (CP) ranged from 17.3% for leaves of huisache to 21.9% for leucaena. The neutral detergent fiber (NDF) content ranged from 39.0 to 40.3 with no difference among fodder threes. Across tree species, mean IVDMD was 61.6% for pods and 52.2% for leaves. IVDMD for leaves was highest (P < 0.01) for leucaena (54.9%) and lowest for huisache (47.3%). Condensed tannins in an acetonic extract were highest for leaves of huisache (45.3 mg CE/g DM) and lowest for mesquite (25.9 mg CE/g DM). Pods and leaves of huisache presented the highest number of secondary metabolites, mainly related to hydrobenzoic acid and flavonols; leucaena and mesquite presented mainly flavonols and anthocyanins. It was concluded that leaves and pods of leucaena, mesquite and huisache constitute valuable forages for ruminant livestock due to its low fiber, high CP levels, moderate in vitro fermentation characteristics and high mineral content. Keywords: Fodder tree; ruminants; secondary metabolites; minerals; tannins

Keywords: fodder tree, ruminants, secondary metabolites, minerals, tannins

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970 Assessing the Effectiveness of Machine Learning Algorithms for Cyber Threat Intelligence Discovery from the Darknet

Authors: Azene Zenebe

Abstract:

Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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969 The Femoral Eversion Endarterectomy Technique with Transection: Safety and Efficacy

Authors: Hansraj Riteesh Bookun, Emily Maree Stevens, Jarryd Leigh Solomon, Anthony Chan

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Objective: This was a retrospective cross-sectional study evaluating the safety and efficacy of femoral endarterectomy using the eversion technique with transection as opposed to the conventional endarterectomy technique with either vein or synthetic patch arterioplasty. Methods: Between 2010 to mid 2017, 19 patients with mean age of 75.4 years, underwent eversion femoral endarterectomy with transection by a single surgeon. There were 13 males (68.4%), and the comorbid burden was as follows: ischaemic heart disease (53.3%), diabetes (43.8%), stage 4 kidney impairment (13.3%) and current or ex-smoking (73.3%). The indications were claudication (45.5%), rest pain (18.2%) and tissue loss (36.3%). Results: The technical success rate was 100%. One patient required a blood transfusion following bleeding from intraoperative losses. Two patients required blood transfusions from low post operative haemogloblin concentrations – one of them in the context of myelodysplastic syndrome. There were no unexpected returns to theatre. The mean length of stay was 11.5 days with two patients having inpatient stays of 36 and 50 days respectively due to the need for rehabilitation. There was one death unrelated to the operation. Conclusion: The eversion technique with transection is safe and effective with low complication rates and a normally expected length of stay. It poses the advantage of not requiring a synthetic patch. This technique features minimal extraneous dissection as there is no need to harvest vein for a patch. Additionally, future endovascular interventions can be performed by puncturing the native vessel. There is no change to the femoral bifurcation anatomy after this technique. We posit that this is a useful adjunct to the surgeon’s panoply of vascular surgical techniques.

Keywords: endarterectomy, eversion, femoral, vascular

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968 Decision-Tree-Based Foot Disorders Classification Using Demographic Variable

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

Abstract:

Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

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967 Structured Access Control Mechanism for Mesh-based P2P Live Streaming Systems

Authors: Chuan-Ching Sue, Kai-Chun Chuang

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Peer-to-Peer (P2P) live streaming systems still suffer a challenge when thousands of new peers want to join into the system in a short time, called flash crowd, and most of new peers suffer long start-up delay. Recent studies have proposed a slot-based user access control mechanism, which periodically determines a certain number of new peers to enter the system, and a user batch join mechanism, which divides new peers into several tree structures with fixed tree size. However, the slot-based user access control mechanism is difficult for accurately determining the optimal time slot length, and the user batch join mechanism is hard for determining the optimal tree size. In this paper, we propose a structured access control (SAC) mechanism, which constructs new peers to a multi-layer mesh structure. The SAC mechanism constructs new peer connections layer by layer to replace periodical access control, and determines the number of peers in each layer according to the system’s remaining upload bandwidth and average video rate. Furthermore, we propose an analytical model to represent the behavior of the system growth if the system can utilize the upload bandwidth efficiently. The analytical result has shown the similar trend in system growth as the SAC mechanism. Additionally, the extensive simulation is conducted to show the SAC mechanism outperforms two previously proposed methods in terms of system growth and start-up delay.

Keywords: peer-to-peer, live video streaming system, flash crowd, start-up delay, access control

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966 Immature Palm Tree Detection Using Morphological Filter for Palm Counting with High Resolution Satellite Image

Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

Abstract:

Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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965 Addressing Ophthalmic and Vascular Diabetic Complications in South Asians

Authors: Haaris Khan, Farhad Udwadia

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South Asians are the fastest-growing immigrant population in Canada and are 3-4 times more likely to develop diabetes. In a primary care setting, language barriers continue to persist as a prominent obstacle when delivering crucial health information. Given the abundance of languages in the South Asian community and the varying levels of English fluency, there is compelling evidence that these language barriers can adversely impact health outcomes. The microvascular and macrovascular complications of poor diabetic management are well established and universally recognized. However, these are often difficult concepts to grasp for even individuals fluent in English. In order to lessen the burden of language barriers, we developed a comprehensive guide in various languages that discuss the complications and screening guidelines for diabetic and prediabetic patients. The guide is presented in the form of a pamphlet, with an electronic version being constructed as well, that provides basic information on diabetic retinopathy, neuropathy and nephropathy as well as the screening recommendations. We also conducted a review of the literature around the topic and incorporated our findings into our project. Our goal is for primary care physicians to have this resource and to be able to provide the link or pamphlet to patients in need. Our presentation also provides a comprehensive overview of some of the other barriers that individuals in the South Asian community face when seeking care. Given the staggering number of individuals in the South Asian community with diabetes and the morbidity and mortality associated with diabetes and its complications, effective community-specific strategies are needed to mitigate the potential consequences of poor diabetes management.

Keywords: diabetes, patient education, ophthalmology, vascular surgery

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964 Development of Electrospun Membranes with Defined Polyethylene Collagen and Oxide Architectures Reinforced with Medium and High Intensity Statins

Authors: S. Jaramillo, Y. Montoya, W. Agudelo, J. Bustamante

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Cardiovascular diseases (CVD) are related to affectations of the heart and blood vessels, within these are pathologies such as coronary or peripheral heart disease, caused by the narrowing of the vessel wall (atherosclerosis), which is related to the accumulation of Low-Density Lipoproteins (LDL) in the arterial walls that leads to a progressive reduction of the lumen of the vessel and alterations in blood perfusion. Currently, the main therapeutic strategy for this type of alteration is drug treatment with statins, which inhibit the enzyme 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMG-CoA reductase), responsible for modulating the rate of cholesterol production and other isoprenoids in the mevalonate pathway. This enzyme induces the expression of LDL receptors in the liver, increasing their number on the surface of liver cells, reducing the plasma concentration of cholesterol. On the other hand, when the blood vessel presents stenosis, a surgical procedure with vascular implants is indicated, which are used to restore circulation in the arterial or venous bed. Among the materials used for the development of vascular implants are Dacron® and Teflon®, which perform the function of re-waterproofing the circulatory circuit, but due to their low biocompatibility, they do not have the ability to promote remodeling and tissue regeneration processes. Based on this, the present research proposes the development of a hydrolyzed collagen and polyethylene oxide electrospun membrane reinforced with medium and high-intensity statins, so that in future research it can favor tissue remodeling processes from its microarchitecture.

Keywords: atherosclerosis, medium and high-intensity statins, microarchitecture, electrospun membrane

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963 Anatomical Adaptations of Three Astragalus Species under Salt Stress

Authors: Faycal Boughalleb, Raoudha Abdellaoui

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The effect of NaCl stress on root and leaf anatomy was investigated in three Astragalus species grown in 0-300 mM NaCl for 30 days under greenhouse conditions. Root cross section and cortex thickness was reduced under salt stress in both species while A. tenuifolius showed thinner cortex and the root cross section was unchanged. The epidermis stele thickness was unaffected by salinity in A. armatus and A. tenuifolius and was reduced in A. mareoticus with smaller xylem vessel size. In addition, vessel density and wall thickness of xylem was increased under salt conditions in the studies species. The entire lamina and mesophyll of the three species were thinner in salt-stressed plants. A. armatus and A. tenuifolius showed the higher thickness with increased size of the lower epidermis. NaCl (300 mM) reduced leaf water content by 41.5 % in A. mareoticus while it was unchanged in the other species. The size of the vascular bundle increased under salinity in A. tenuifolius leaves and it was unchanged in the other ones. A longer distance between leaf vascular bundle was occurred in A. mareoticus. The effects of NaCl on root and leaf ultrastructure are discussed in relation to the degree of salt resistance of these species. The unchanged biomass production under salt stress confirmed the higher tolerance oft A. tenuifolius to salinity. A. armatus was moderately salt tolerant with decrease of biomass production by 14.2 % while A. mareoticus was considered as salt sensitive plant when the decrease in biomass production reached 56.8%.

Keywords: Astragalus species, leaf ultrastructure, root anatomy, salt stress

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962 The Assessment Groundwater Geochemistry of Some Wells in Rafsanjan Plain, Southeast of Iran

Authors: Milad Mirzaei Aminiyan, Abdolreza Akhgar, Farzad Mirzaei Aminiyan

Abstract:

Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Pistachio is a main crop that accounts for a considerable portion of Iranian agricultural exports. Give that pistachio tree is a tolerant type of tree to saline and alkaline soil and water conditions, but groundwater and irrigation water quality play important roles in main production this crop. For this purpose, 94 well water samples were taken from 25 wells and samples were analyzed. The results showed give that region’s geological, climatic characteristics, statistical analysis, and based on dominant cations and anions in well water samples (piper diagram); four main types of water were found: Na-Cl, K-Cl, Na-SO4, and K-SO4. It seems that most wells in terms of water quality (salinity and alkalinity) and based on Wilcox diagram have critical status. The analysis suggested that more than eighty-seven percentage of the well water samples have high values of EC that these values are higher than into critical limit EC value for irrigation water, which may be due to the sandy soils in this area. Most groundwater were relatively unsuitable for irrigation but it could be used by application of correct management such as removing and reducing the ion concentrations of Cl‾, SO42‾, Na+ and total hardness in groundwater and also the concentrated deep groundwater was required treatment to reduce the salinity and sodium hazard. Given that irrigation water quality in this area was relatively unsuitable for most agriculture production but pistachio tree was adapted to this area conditions. The integrated management of groundwater for irrigation is the way to solve water quality issues not only in Rafsanjan area, but also in other arid and semi-arid areas.

Keywords: groundwater quality, irrigation water quality, salinity, alkalinity, Rafsanjan plain, pistachio

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961 Comparison of Support Vector Machines and Artificial Neural Network Classifiers in Characterizing Threatened Tree Species Using Eight Bands of WorldView-2 Imagery in Dukuduku Landscape, South Africa

Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

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Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

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960 Study of Irritant and Anti-inflammatory Activity of Snuhi/Zaqqum (Euphorbia nerifolia) with Special Reference to Holy Quran and Ayurveda

Authors: Mohammed Khalil Ur Rahman, Pradnya Chigle, Bushra Farhen

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Indian mythology believes that Vedas are eternal treatises. Vedas are categorized into four divisions viz., Rigveda, Yajurveda, Samveda, Atharveda. All these spiritual classics not only deal with rituals and customs but also consist of inclusion of many references related to health. Out of these four, Atharveda deals with maximum principles pertaining to health sciences. Therefore, it is said that the science and the art of Ayurveda has developed from Atharveda. Ayurveda deals with many medicinal plants either as a single therapeutic use or in combination. One such medicinal plant is Snuhi (Euphorbia neriifolia Linn.) which finds its extensive importance along with Haridra and Apamargakshar, in the preparation of Ksharsutra which in turn is used for the treatment of Fistula in Ano. It is interesting to note that this plant Snuhi is also referred in Holy Quran as the Tree of Zaqqum advocated as the food for the sinners as a part of torment. The reference in Surat Ad-Dukhan is as follows: - 44:43-46. “Verily, the tree of Zaqqum will be the food of the sinners, Like boiling oil, it will boil in the bellies, like the boiling of scalding water.” The above verse implies that plant Snuhi/Zaqqum due to irritant property acts as a drastic purgative but at the same time it also possesses anti inflammatory properties in order to relieve the irritation. These properties of Zaqqum has been unfolded in the modern research which states that, Diterpene polycyclic esters are responsible for its toxic and irritant nature whereas; triterpenes are responsible for its anti inflammatory property. Present work will be an effort to review the concept of Quran about latex of the Tree of Zaqqum in terms of its phytochemistry and its therapeutic use in Ksharsutra pertaining to irritant and anti inflammatory property.

Keywords: ayurveda, Quran, zaqqum, ksharsutra, latex piles, inflammation

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959 Influence of Species and Harvesting Height on Chemical Composition, Buffer Nitrogen Solubility and in vitro Ruminal Fermentation of Browse Tree Leaves

Authors: Thabiso M. Sebolai, Victor Mlambo, Solomon Tefera, Othusitse R. Madibela

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In some tree species, sustained herbivory can induce changes in biosynthetic pathways resulting in overproduction of anti-nutritional secondary plant compounds. This inductive mechanism, which has not been demonstrated in semi-arid rangelands of South Africa, may result in browse leaves of lower nutritive value. In this study we investigate the interactive effect of browsing pressure and tree species on chemical composition, buffer nitrogen solubility index (NSI), in vitro ruminal dry matter degradability (IVDMD) and in vitro ruminal N degradability (IVND) of leaves. Leaves from Maytenus capitata, Olea africana, Coddia rudis, Carissa macrocarpa, Rhus refracta, Ziziphus mucronata, Boscia oliedes, Grewia robusta, Phyllanthus vessucosus and Ehretia rigida trees growing in a communal grazing area were harvested at two heights: browsable ( < 1.5 m) and non-browsable ( > 1.5 m), representing high and low browsing pressure, respectively. The type of animals utilizing the communal rangeland includes cattle at 1 livestock unit (450kg)/12 to 15 hectors and goats at 1 livestock unit/4 ha. Harvested leaves were dried, milled and analysed for proximate components, soluble phenolics, condensed tannins, minerals and in vitro ruminal fermentation. A significant plant species and harvesting height interaction effect (P < 0.05) was observed for total nitrogen (N) and soluble phenolics concentration. Tree species and harvesting height affected (P < 0.05) condensed tannin (CTs) content where samples harvested from the non-browsable height had higher (0.61 AU550 nm/200 mg) levels than those harvested at browsable height (0.55 AU550 nm/200 mg) while their interaction had no effects. Macro and micro-minerals were only influenced (P < 0.05) by browse species but not harvesting height. Species and harvesting height interacted (P < 0.05) to influence IVDMD and IVND of leaves at 12, 24 and 36 hours of incubation. The different browse leaves contained moderate to high protein, moderate level of phenolics and minerals, suggesting that they have the potential to provide supplementary nutrients for ruminants during the dry seasons.

Keywords: browse plants, chemical composition, harvesting heights, phenolics

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958 Comparative Isotherms Studies on Adsorptive Removal of Methyl Orange from Wastewater by Watermelon Rinds and Neem-Tree Leaves

Authors: Sadiq Sani, Muhammad B. Ibrahim

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Watermelon rinds powder (WRP) and neem-tree leaves powder (NLP) were used as adsorbents for equilibrium adsorption isotherms studies for detoxification of methyl orange dye (MO) from simulated wastewater. The applicability of the process to various isotherm models was tested. All isotherms from the experimental data showed excellent linear reliability (R2: 0.9487-0.9992) but adsorptions onto WRP were more reliable (R2: 0.9724-0.9992) than onto NLP (R2: 0.9487-0.9989) except for Temkin’s Isotherm where reliability was better onto NLP (R2: 0.9937) than onto WRP (R2: 0.9935). Dubinin-Radushkevich’s monolayer adsorption capacities for both WRP and NLP (qD: 20.72 mg/g, 23.09 mg/g) were better than Langmuir’s (qm: 18.62 mg/g, 21.23 mg/g) with both capacities higher for adsorption onto NLP (qD: 23.09 mg/g; qm: 21.23 mg/g) than onto WRP (qD: 20.72 mg/g; qm: 18.62 mg/g). While values for Langmuir’s separation factor (RL) for both adsorbents suggested unfavourable adsorption processes (RL: -0.0461, -0.0250), Freundlich constant (nF) indicated favourable process onto both WRP (nF: 3.78) and NLP (nF: 5.47). Adsorption onto NLP had higher Dubinin-Radushkevich’s mean free energy of adsorption (E: 0.13 kJ/mol) than WRP (E: 0.08 kJ/mol) and Temkin’s heat of adsorption (bT) was better onto NLP (bT: -0.54 kJ/mol) than onto WRP (bT: -0.95 kJ/mol) all of which suggested physical adsorption.

Keywords: adsorption isotherms, methyl orange, neem leaves, watermelon rinds

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957 Unraveling the Threads of Madness: Henry Russell’s 'The Maniac' as an Advocate for Deinstitutionalization in the Nineteenth Century

Authors: T. J. Laws-Nicola

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Henry Russell was best known as a composer of more than 300 songs. Many of his compositions were popular for both their sentimental texts, as in ‘The Old Armchair,’ and those of a more political nature, such as ‘Woodsman, Spare That Tree!’ Indeed, Russell had written such songs of advocacy as those associated with abolitionism (‘The Slave Ship’) and environmentalism (‘Woodsman, Spare that Tree!’). ‘The Maniac’ is his only composition addressing the issue of institutionalization. The text is borrowed and adapted from the monodrama The Captive by M.G. ‘Monk’ Lewis. Through an analysis of form, harmony, melody, text, and thematic development and interactions between text and music we can approach a clearer understanding of ‘The Maniac’ and how the text and music interact. Select periodicals, such as The London Times, provide contemporary critical review for ‘The Maniac.’ Additional nineteenth century songs whose texts focus on madness and/or institutionalization will assist in building a stylistic and cultural context for ‘The Maniac.’ Through comparative analyses of ‘The Maniac’ with a body of songs that focus on similar topics, we can approach a clear understanding of the song as a vehicle for deinstitutionalization.

Keywords: 19th century song, institutionalization, M. G. Lewis, Henry Russell

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956 The Lopsided Burden of Non-Communicable Diseases in India: Evidences from the Decade 2004-2014

Authors: Kajori Banerjee, Laxmi Kant Dwivedi

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India is a part of the ongoing globalization, contemporary convergence, industrialization and technical advancement that is taking place world-wide. Some of the manifestations of this evolution is rapid demographic, socio-economic, epidemiological and health transition. There has been a considerable increase in non-communicable diseases due to change in lifestyle. This study aims to assess the direction of burden of disease and compare the pressure of infectious diseases against cardio-vascular, endocrine, metabolic and nutritional diseases. The change in prevalence in a ten-year period (2004-2014) is further decomposed to determine the net contribution of various socio-economic and demographic covariates. The present study uses the recent 71st (2014) and 60th (2004) rounds of National Sample Survey. The pressure of infectious diseases against cardio-vascular (CVD), endocrine, metabolic and nutritional (EMN) diseases during 2004-2014 is calculated by Prevalence Rates (PR), Hospitalization Rates (HR) and Case Fatality Rates (CFR). The prevalence of non-communicable diseases are further used as a dependent variable in a logit regression to find the effect of various social, economic and demographic factors on the chances of suffering from the particular disease. Multivariate decomposition technique further assists in determining the net contribution of socio-economic and demographic covariates. This paper upholds evidences of stagnation of the burden of communicable diseases (CD) and rapid increase in the burden of non-communicable diseases (NCD) uniformly for all population sub-groups in India. CFR for CVD has increased drastically in 2004-2014. Logit regression indicates the chances of suffering from CVD and EMN is significantly higher among the urban residents, older ages, females, widowed/ divorced and separated individuals. Decomposition displays ample proof that improvement in quality of life markers like education, urbanization, longevity of life has positively contributed in increasing the NCD prevalence rate. In India’s current epidemiological phase, compression theory of morbidity is in action as a significant rise in the probability of contracting the NCDs over the time period among older ages is observed. Age is found to play a vital contributor in increasing the probability of having CVD and EMN over the study decade 2004-2014 in the nationally representative sample of National Sample Survey.

Keywords: cardio-vascular disease, case-fatality rate, communicable diseases, hospitalization rate, multivariate decomposition, non-communicable diseases, prevalence rate

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955 Feature Weighting Comparison Based on Clustering Centers in the Detection of Diabetic Retinopathy

Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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954 Potential of Water Purification of Turbid Surface Water Sources in Remote Arid and Semi-Arid Rural Areas of Rajasthan by Moringa Oleifera (Drumstick) Tree Seeds

Authors: Pomila Sharma

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Rajasthan is among regions with greatest climate sensitivity and lowest adaptive capabilities. In many parts of the Rajasthan surface water which can be highly turbid and contaminated with fecal coliform bacteria is used for drinking purposes. The majority rely almost exclusively upon traditional sources of highly turbid and untreated pathogenic surface water for their domestic water needs. In many parts of rural areas of Rajasthan, it is still difficult to obtain clean water, especially remote habitations with no groundwater due to quality issues or depletion and limited feasibility to connect with surface water schemes due to low density of population in these areas to justify large infrastructure investment. The most viable sources are rain water harvesting, community managed open wells, private wells, ponds and small-scale irrigation reservoirs have often been the main traditional sources of rural drinking water. Turbidity is conventionally removed by treating the water with expensive chemicals. This study has to investigate the use of crushed seeds from the tree Moringa oleifera (drumstick) as a natural alternative to conventional coagulant chemicals. The use of Moringa oleifera seed powder can produce potable water of higher quality than the original source. Moringa oleifera a native species of northern India, the tree is now grown extensively throughout the tropics and found in many countries of Africa, Asia & South America. The seeds of tree contains significant quantities of low molecular weight, water soluble proteins which carries the positive charge when the crushed seeds are added to water. This protein binds in raw water with negatively charged turbid water with bacteria, clay, algae, etc. Under proper mixing, these particles make flocks, which may be left to settle by gravity or be removed by filtration. Using Moringa oleifera as a replacement coagulation in such surface sources of arid and semi-arid areas can meet the need for water purification in remote places of Rajasthan state of India. The present study accesses to find out laboratory based investigation of the effect of seeds of Moringa tree on its coagulation effectiveness (purification) using turbid water samples of surface source of the Rajasthan state. In this study, moringa seed powder showed that filtering with seed powder may diminish water pollution and bacterial counts. Results showed Moringa oleifera seeds coagulate 90-95% of turbidity and color efficiently leading to an aesthetically clear supernatant & reduced about 85-90% of bacterial load reduction in samples.

Keywords: bacterial load, coagulant, turbidity, water purification

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953 Reduction of Plants Biodiversity in Hyrcanian Forest by Coal Mining Activities

Authors: Mahsa Tavakoli, Seyed Mohammad Hojjati, Yahya Kooch

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Considering that coal mining is one of the important industrial activities, it may cause damages to environment. According to the author’s best knowledge, the effect of traditional coal mining activities on plant biodiversity has not been investigated in the Hyrcanian forests. Therefore, in this study, the effect of coal mining activities on vegetation and tree diversity was investigated in Hyrcanian forest, North Iran. After filed visiting and determining the mine, 16 plots (20×20 m2) were established by systematic-randomly (60×60 m2) in an area of 4 ha (200×200 m2-mine entrance placed at center). An area adjacent to the mine was not affected by the mining activity, and it is considered as the control area. In each plot, the data about trees such as number and type of species were recorded. The biodiversity of vegetation cover was considered 5 square sub-plots (1 m2) in each plot. PAST software and Ecological Methodology were used to calculate Biodiversity indices. The value of Shannon Wiener and Simpson diversity indices for tree cover in control area (1.04±0.34 and 0.62±0.20) was significantly higher than mining area (0.78±0.27 and 0.45±0.14). The value of evenness indices for tree cover in the mining area was significantly lower than that of the control area. The value of Shannon Wiener and Simpson diversity indices for vegetation cover in the control area (1.37±0.06 and 0.69±0.02) was significantly higher than the mining area (1.02±0.13 and 0.50±0.07). The value of evenness index in the control area was significantly higher than the mining area. Plant communities are a good indicator of the changes in the site. Study about changes in vegetation biodiversity and plant dynamics in the degraded land can provide necessary information for forest management and reforestation of these areas.

Keywords: vegetation biodiversity, species composition, traditional coal mining, Caspian forest

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952 Reusing Assessments Tests by Generating Arborescent Test Groups Using a Genetic Algorithm

Authors: Ovidiu Domşa, Nicolae Bold

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Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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951 Machine Learning-Driven Prediction of Cardiovascular Diseases: A Supervised Approach

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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950 Embolism: How Changes in Xylem Sap Surface Tension Affect the Resistance against Hydraulic Failure

Authors: Adriano Losso, Birgit Dämon, Stefan Mayr

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In vascular plants, water flows from roots to leaves in a metastable state, and even a small perturbation of the system can lead a sudden transition from the liquid to the vapor phase, resulting in xylem embolism (cavitation). Xylem embolism, induced by drought stress and/or freezing stress is caused by the aspiration of gaseous bubbles into xylem conduits from adjacent gas-filled compartments through pit membrane pores (‘air seeding’). At water potentials less negative than the threshold for air seeding, the surface tension (γ) stabilizes the air-water interface and thus prevents air from passing the pit pores. This hold is probably also true for conifers, where this effect occurs at the edge of the sealed torus. Accordingly, it was experimentally demonstrated that γ influences air seeding, but information on the relevance of this effect under field conditions is missing. In this study, we analyzed seasonal changes in γ of the xylem sap in two conifers growing at the alpine timberline (Picea abies and Pinus mugo). In addition, cut branches were perfused (40 min perfusion at 0.004 MPa) with different γ solutions (i.e. distilled and degassed water, 2, 5 and 15% (v/v) ethanol-water solution corresponding to a γ of 74, 65, 55 and 45 mN m-1, respectively) and their vulnerability to drought-induced embolism analyzed via the centrifuge technique (Cavitron). In both species, xylem sap γ changed considerably (ca. 53-67 and ca. 50-68 mN m-1 in P. abies and P. cembra, respectively) over the season. Branches perfused with low γ solutions showed reduced resistance against drought-induced embolism in both species. A significant linear relationship (P < 0.001) between P12, P50 and P88 (i.e. water potential at 12, 50 and 88% of the loss of conductivity) and xylem sap γ was found. Based on this correlation, a variation in P50 between -3.10 and -3.83 MPa (P. abies) and between -3.21 and -4.11 MPa (P. mugo) over the season could be estimated. Results demonstrate that changes in γ of the xylem sap can considerably influence a tree´s resistance to drought-induced embolism. They indicate that vulnerability analyses, normally conducted at a γ near that of pure water, might often underestimate vulnerabilities under field conditions. For studied timberline conifers, seasonal changes in γ might be especially relevant in winter, when frost drought and freezing stress can lead to an excessive embolism.

Keywords: conifers, Picea abies, Pinus mugo, timberline

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949 Prioritizing Forest Conservation Strategies Using a Multi-Attribute Decision Model to Address Concerns with the Survival of the Endangered Dragon Tree (Dracaena ombet Kotschy and Peyr.)

Authors: Tesfay Gidey, Emiru Birhane, Ashenafi Manaye, Hailemariam Kassa, Tesfay Atsbha, Negasi Solomon, Hadgu Hishe, Aklilu Negussie, Petr Madera, Jose G. Borges

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The globally endangered Dracaena ombet is one of the ten dragon multipurpose tree species in arid ecosystems. Anthropogenic and natural factors are now impacting the sustainability of the species. This study was conducted to prioritize criteria and alternative strategies for the conservation of the species using the analytical hierarchy process (AHP) model by involving all relevant stakeholders in the Desa'a dry Afromontane forest in northern Ethiopia. Information about the potential alternative strategies and the criteria for their evaluation was first collected from experts, personal experiences, and literature reviews. Afterward, they were validated using stakeholders' focus group discussions. Five candidate strategies with three evaluation criteria were considered for prioritization using the AHP techniques. The overall priority ranking value of the stakeholders showed that the ecological criterion was deemed as the most essential factor for the choice of alternative strategies, followed by the economic and social criteria. The minimum cut-off strategy, combining exclosures with the collection of only 5% of plant parts from the species, soil and water conservation, and silviculture interventions, was selected as the best alternative strategy for sustainable D. ombet conservation. The livelihood losses due to the selected strategy should be compensated by the collection of non-timber forest products, poultry farming, home gardens, rearing small ruminants, beekeeping, and agroforestry. This approach may be extended to study other dragon tree species and explore strategies for the conservation of other arid ecosystems.

Keywords: conservation strategies, analytical hierarchy process model, Desa'a forest, endangered species, Ethiopia, overexploitation

Procedia PDF Downloads 93