Search results for: phytoremediation with trees

Authors: Rita Rani, Ramesh Kumar

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The intend of the current study is to date an old grand Peepal tree that is still alive. The tree is situated in Kalibard village, Sector 9, Chandigarh (India). Due to its huge structure, it has got the status of ‘Heritage tree.’ Optically Stimulated Luminescence of sediments beneath the roots is used to determine the age of the tree. Optical dating is preferred over conventional dating methods due to more precession. The methodology includes OSL of quartz grain using SAR protocol for accumulated dose measurement. The age determination of an alive tree using sedimentary quartz is in close agreement with the approximated age provided by the related agency. This is the first attempt at using optically stimulated luminescence in the age determination of alive trees in this region. The study concludes that the Luminescence dating of alive trees is the nondestructive and more precise method.

Keywords: luminescence, dose rate, optical dating, sediments

Procedia PDF Downloads 149

Authors: Yunfeng Shan, Xiaoliang Wang, Youjun Zhou

Abstract:

Whole-genome data from two lungfish species, along with other species, present a valuable opportunity to re-investigate the longstanding debate regarding the evolutionary relationships among tetrapods, lungfishes, and coelacanths. However, the use of bootstrap support has become outdated for large-scale phylogenomic data. Without robust phylogenetic support, the phylogenetic trees become meaningless. Therefore, it is necessary to re-evaluate the phylogenies of tetrapods, lungfishes, and coelacanths using novel measures of phylogenetic support specifically designed for phylogenomic data, as the previous phylogenies were based on 100% bootstrap support. Our findings consistently provide strong evidence favoring lungfish as the closest living relative of tetrapods. This conclusion is based on high internode certainty, relative gene support, and high gene concordance factor. The evidence stems from five previous datasets derived from lungfish transcriptomes. These results yield fresh insights into the three hypotheses regarding the phylogenies of tetrapods, lungfishes, and coelacanths. Importantly, these hypotheses are not mere conjectures but are substantiated by a significant number of genes. Analyzing real biological data further demonstrates that the inclusion of additional taxa leads to more diverse tree topologies. Consequently, gene trees and species trees may not be identical even when whole-genome sequencing data is utilized. However, it is worth noting that many gene trees can accurately reflect the species tree if an appropriate number of taxa, typically ranging from six to ten, are sampled. Therefore, it is crucial to carefully select the number of taxa and an appropriate outgroup, such as slow-evolving species, while excluding fast-evolving taxa as outgroups to mitigate the adverse effects of long-branch attraction and achieve an accurate reconstruction of the species tree. This is particularly important as more whole-genome sequencing data becomes available.

Keywords: novel measures of phylogenetic support for phylogenomic data, gene concordance factor confidence, relative gene support, internode certainty, origin of tetrapods

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Authors: Irfan Ahmad, Raza Ghafoor, Hammad Raza Ahmad, Muhammad Asif, Farrakh Nawaz, M. Tahir Siddiqui

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Due to the exploding population of Pakistan the pressure on natural forests is increasing to meet the demands of wood and wood based products. Agroforestry is being practiced throughout the world on scientific basis but unfortunately the farmers of Pakistan are reluctant in its adoption. The presents study was designed to assess the adoption of agroforestry practices in Faisalabad with respect to land holdings of farmers and future suitability by using Geographic information system (GIS). Faisalabad is the third largest city of the country and is famous due to the textile industry. A comprehensive survey from target villages of the Lyallpur town of Faisalabad district was carried out. Out of total 65 villages, 40 were selected for study. From each selected village, one farmer who was actively engaged in farming activities was selected. It was observed that medium sized farmers having 10-20 acre were more in number as compared to small and large farmers. Number of trees was found maximum in large farm lands, ratio of diseased trees was almost similar in all categories with maximum in small farmlands (24.1%). Regarding the future prospects 35% farmer were interested in agroforestry practices 65% were not interested in the promotion of trees due to the non-availability of technical guidance and proper markets. Geographic images of the study site can further help the researchers and policy makers in the promotion of agroforestry.

Keywords: agroforestry trends, adoption, Faisalabad, geographic information system (GIS)

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Authors: K. M. K. D Weerasekara, R. M. K. M Rathnayake, R. U. Halwatura, G. Y. Jayasinghe

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Wood apple (Limonia acidissima L.) trees are native to Sri Lanka and India. Wood apple gum is widely used in the food, coating, and pharmaceutical industries. Wood apple gum was a major component in ancient Sri Lankan coating technology as well. It is also used as a suspending agent in liquid syrups and food ingredients such as sauces, emulsifiers, and stabilizers. Industrial applications include adhesives for labeling and packaging, as well as paint binder. It is also used in the production of paper and cosmetics. Extraction of wood apple gum is an important step in ensuring maximum benefits for various uses. It is apparent that an abundance of untapped potential lies in wood apple gum if people are able to mass produce them. Hence, the current study uses a two-factor factorial design with two major variables and four replications to investigate the best gum-extracting tapping system for Wood apple gum. This study's findings will be useful to Wood apple cultivators, researchers, and gum-based industries alike.

Keywords: wood apple gum, limonia acidissima l., tapping, tapping cuts

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

Procedia PDF Downloads 116

Authors: Muhammad Iqbal, Hafiz Muhammad Tauqeer, Hamza Rafaqat, Muhammad Naveed, Muhammad Awais Irshad

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Soil pollution with chromium (Cr) has become one of the most important concerns due to its toxicity for humans. To date, various remediation approaches have been employed for the remediation and management of Cr contaminated soils. Phytoextraction is an eco-friendly and emerging remediation approach which has gained attention due to several advantages over conventional remediation approach. The use of energy crops for phytoremediation is an emerging trend worldwide. These energy crops have high tolerance against various environmental stresses, the potential to grow in diverse ecosystems and high biomass production make them a suitable candidate for phytoremediation of contaminated soils. The removal efficiency of plants in phytoextraction depends upon several soil and plant factors including solubility, bioavailability and metal speciation in soils. A pot scale experiment was conducted to evaluate the phytoextraction potential of Arundo donax L. with the application of acetic acid (A.A) in Cr contaminated soils. Plants were grown in pots filled with 5 kg soils for 90 days. After 30 days plants acclimatization in pot conditions, plants were treated with various levels of Cr (2.5 mM, 5 mM, 7.5 mM, 10 mM) and A.A (Cr 2.5 mM + A.A 2.5 mM, Cr 5 mM + A.A 2.5 mM, Cr 7.5 mM + A.A 2.5 mM, Cr 10 mM + A.A 2.5 mM). The application of A.A significantly increased metal uptake and in roots and shoots of A. donax. This increase was observed at Cr 7.5 mM + A.A 2.5 mM but at high concentrations, visual symptoms of Cr toxicity were observed on leaves. Similarly, A.A applications also affect the activities of key enzymes including catalase (CAT), superoxidase dismutase (SOD), and ascorbate peroxidase (APX) in leaves of A. donax. Based on results it is concluded that the applications of A.A acid for phytoextraction is an alternative approach for the management of Cr affected soils and synthetic chelators should be replaced with organic acids.

Keywords: acetic acid, A. donax, chromium, energy crop, phytoextraction

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Authors: Sahar Elkaee Behjati

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Air pollution, particularly with dust, is one of the biggest issues Tehran is dealing with, and the city's green space which consists of trees has a critical role in absorption of it. The question this study aimed to investigate was which tree species the highest uptake capacity of the dust and carbon have suspended in the air. On this basis, 30 samples of trees from two different districts in Tehran were collected, and after washing and centrifuging, the samples were oven dried. The results of the study revealed that Ulmus minor had the highest amount of deposited dust in both districts. In addition, it was found that in Chamran district Ailanthus altissima and in Gandi district Ulmus minor has had the highest absorption of deposited carbon. Therefore, it could be argued that decision making on the selection of species for urban green spaces should take the above-mentioned parameters into account.

Keywords: dust, leaves, uptake total carbon, Tehran, tree species

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Tanjil Sowgat, Shamim Kobir

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World is now experiencing the consequences of climate change such as increased heat stress due to high temperature rise. In the context of changing climate, this study intends to find out the planning interventions necessary to adapt to the current heat stress in the planned residential areas of Khulna city. To carry out the study Sonadanga residential area (phase I) of Khulna city has been taken as the study site. This residential neighbourhood covering an area of 30 acres has 206 residential plots. The study area comprises twelve access roads, one park, one playfield, one water body and two street furniture’s. This study conducts visual analysis covering green, open space, water body, footpath, drainage and street trees and furniture and questionnaire survey deals with socio-economic, housing tenancy, experience of heat stress and urban design interventions. It finds that the current state that accelerates the heat stress condition such as lack of street trees and inadequate shading, maximum uses are not within ten minutes walking distance, no footpath for the pedestrians and lack of well-maintained street furniture. It proposes that to adapt to the heat stress pedestrian facilities, buffer sidewalk with landscaping, street trees and open spaces, soft scape, natural and man-made water bodies, green roofing could be effective urban design interventions. There are evidences of limited number of heat stress adaptive planned residential area. Since current sub-division planning practice focuses on rigid land use allocation, it partly addresses the climatic concerns through creating open space and street trees. To better respond to adapt to the heat stress, urban design considerations in the context of sub-division practice would bring more benefits.

Keywords: climate change, urban design, adaptation, heat stress, water-logging

Procedia PDF Downloads 267

Authors: Yunfeng Shan, Xiaoliang Wang, Youjun Zhou

Abstract:

Whole-genome data from two lungfish species, along with other species, present a valuable opportunity to reassess the longstanding debate regarding the evolutionary relationships among tetrapods, lungfishes, and coelacanths. However, the use of bootstrap support has become outdated for large-scale phylogenomic data. Without robust phylogenetic support, the phylogenetic trees become meaningless. Therefore, it is necessary to re-evaluate the phylogenies of tetrapods, lungfishes, and coelacanths using novel measures of phylogenetic support specifically designed for phylogenomic data, as the previous phylogenies were based on 100% bootstrap support. Our findings consistently provide strong evidence favoring lungfish as the closest living relative of tetrapods. This conclusion is based on high gene support confidence with confidence intervals exceeding 95%, high internode certainty, and high gene concordance factor. The evidence stems from two datasets containing recently deciphered whole genomes of two lungfish species, as well as five previous datasets derived from lungfish transcriptomes. These results yield fresh insights into the three hypotheses regarding the phylogenies of tetrapods, lungfishes, and coelacanths. Importantly, these hypotheses are not mere conjectures but are substantiated by a significant number of genes. Analyzing real biological data further demonstrates that the inclusion of additional taxa diminishes the number of orthologues and leads to more diverse tree topologies. Consequently, gene trees and species trees may not be identical even when whole-genome sequencing data is utilized. However, it is worth noting that many gene trees can accurately reflect the species tree if an appropriate number of taxa, typically ranging from six to ten, are sampled. Therefore, it is crucial to carefully select the number of taxa and an appropriate outgroup while excluding fast-evolving taxa as outgroups to mitigate the adverse effects of long-branch attraction (LBA) and achieve an accurate reconstruction of the species tree. This is particularly important as more whole-genome sequencing data becomes available.

Keywords: gene support confidence (GSC), origin of land vertebrates, coelacanth, two whole genomes of lungfishes, confidence intervals

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Authors: Maria Francesca Scannone, Martina Bochicchio

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One of the major environmental problems today is hydrocarbon contamination. The promising sustainable technologies for the treatment of these contaminated sites involves the use of biological organisms. In Agri Valley (Basilicata Region) there is a living laboratory (natural oil seeps) where the selective pressure has enriched the environmental matrices with microorganisms, fungi and plant species able to use the hydrocarbons as a source of metabolic energy, to degrade or tolerate hydrocarbons. Observers visiting this area are fascinated by its unspoiled nature, and the condition of the ecosystem does not appear to has been damaged. The amazing resiliency observed in Tramutola site is of key importance to try to bring green remediation technologies, but no research has been done to identify high-performing native species. The aim of this research was to study how natural processes affect the fate of released oil or how individual species or communities of plants and animals are capable of dealing with the burden of otherwise toxic chemicals. The survey of vegetation was carried out, more than 60 species have been identified and divided into tree, shrub and herb layer. Plant data sheets have been completed only for the species that showed the most appropriate properties for phytoremediation. In general, members of the Salicales, Cyperales, Poales, Fagales, Cornales, Equisetales orders were the most commonly identified orders. They are pioneer plants with high adaptive capacity and vegetative propagation. The literature review has highlighted the existence of rhizosphere effect and a green liver model on selected plants. The study provides significant information on the environmental stress adaptation processes of many indigenous plants that are living and growing on a natural leak of crude oil and gas that migrates up through subsurface.

Keywords: green liver, hydrocarbon degradation, oil seeps, phytoremediation

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Authors: Sony Baral, Harald Vacik

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This study analyzes the sustainability of community forest management in two community forests in Terai and Hills of Nepal, representing four forest types: 1) Shorearobusta, 2) Terai hardwood, 3) Schima-Castanopsis, and 4) other Hills. The sustainability goals for this region include maintaining and enhancing the forest stocks. Considering this, we analysed changes in species composition, stand density, growing stock volume, and growth-to-removal ratio at 3-5 year intervals from 2005-2016 within 109 permanent forest plots (57 in the Terai and 52 in the Hills). To complement inventory data, forest users, forest committee members, and forest officials were consulted. The results indicate that the relative representation of economically valuable tree species has increased. Based on trends in stand density, both forests are being sustainably managed. Pole-sized trees dominated the diameter distribution, however, with a limited number of mature trees and declined regeneration. The forests were over-harvested until 2013 but under-harvested in the recent period in the Hills. In contrast, both forest types were under-harvested throughout the inventory period in the Terai. We found that the ecological dimension of sustainable forest management is strongly achieved while the economic dimension is lacking behind the current potential. Thus, we conclude that maintaining a large number of trees in the forest does not necessarily ensure both ecological and economical sustainability. Instead, priority should be given on a rational estimation of the annual harvest rates to enhance forest resource conditions together with regular benefits to the local communities.

Keywords: community forests, diversity, growing stock, forest management, sustainability, nepal

Procedia PDF Downloads 67

Authors: Fabio R. Pires, Paulo R. C. C. Ribeiro, Douglas G. Viana, Robson Bonomo, Fernando B. Egreja Filho, Alberto Cargnelutti Filho, Luiz F. Martins, Leila B. S. Cruz, Mauro C. P. Nascimento

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The use of barite (BaSO₄) as a weighting agent in drilling fluids for oil and gas activities makes barium a potential contaminant in the case of spills onto flooded soils, where barium sulfate solubility is increased due to low redox conditions. In order to select plants able to remove barium in such scenarios, seven plant species were evaluated on barium phytoextraction capacity: Brachiaria arrecta; Cyperus cf. papyrus; Eleocharis acutangula; Eleocharis interstincta; Nephrolepsis cf. rivularis; Paspalum conspersum and Typha domingensis. Plants were grown in pots with 13 kg of soil each, and exposed to six barium concentrations (established with BaCl₂): 0; 2.5; 5.0; 10.0; 30.0; 65.0 mg kg-1. To simulate flooding conditions, every pot was manteined with a thin irrigation water depth over soil surface (~1.0 cm). Treatments were carried out in triplicate, and pots were distributed randomly inside the greenhouse. Biometric and chemical analyses were performed throughout the experiment, including Ba²⁺ accumulation in shoots and roots. The highest amount of barium was observed in T. domingensis biomass, followed by C. cf. papyrus. However, the latter exported most of the barium to shoot, especially in higher BaCl₂ doses, while the former accumulated barium preferentially in roots. Thus, barium removal with C. cf. papyrus could be achieved by simply harvesting aerial biomass. The amount of barium in C. cf. papyrus was a consequence of high biomass production rather than barium concentration in plant tissues, whereas T. domingensis showed high barium concentration in plant tissues and high biomass production as well. These results make T. domingensis and C. cf. papyrus potential candidates to be applied in phytoremediation schemes to remove barium from flooded soils.

Keywords: barium sulfate, cyperus, drilling fluids, phytoextraction, Typha

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Authors: Siti Khairunniza-Bejo, Yusnida Yusoff, Nik Salwani Nik Yusoff, Idris Abu Seman, Mohamad Izzuddin Anuar

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Most of the oil palm plantations have been threatened by Basal Stem Rot (BSR) disease which causes serious economic impact. This study was conducted to identify the healthy and BSR-infected oil palm tree using thirteen color indices. Multispectral and thermal camera was used to capture 216 images of the leaves taken from frond number 1, 9 and 17. Indices of normalized difference vegetation index (NDVI), red (R), green (G), blue (B), near infrared (NIR), green – blue (GB), green/blue (G/B), green – red (GR), green/red (G/R), hue (H), saturation (S), intensity (I) and thermal index (T) were used. From this study, it can be concluded that G index taken from frond number 9 is the best index to differentiate between the healthy and BSR-infected oil palm trees. It not only gave high value of correlation coefficient (R=-0.962), but also high value of separation between healthy and BSR-infected oil palm tree. Furthermore, power and S model developed using G index gave the highest R2 value which is 0.985.

Keywords: oil palm, image processing, disease, leaves

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Authors: Fahed Alrshoudi

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Saudi Arabia is ranked the third of the largest suppliers of Dates worldwide (about 28.5 million palm trees), producing more than 2 million tons of dates yearly. These trees produce large quantity of dates palm seeds (DPS) which can be considered literally as a waste. The date seeds are stiff, therefore, it is possible to utilize DPS as coarse aggregates in lightweight concrete for certain structural applications and to participate at reusing the waste. The use of DPS as coarse aggregate in concrete can be an alternative choice as a partial replacement of the stone aggregates (SA). This paper reports the influence of partially replaced stone aggregates with DPS on the hardened properties of concrete performance. Based on the experimental results, the DPS has the potential use as an acceptable alternative aggregates in producing structural lightweight concrete members, instead of stone aggregates.

Keywords: compressive strength, tensile Strength, date palm seeds, aggregate

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Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

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Authors: Allaw Kamel, Al-Chami Leila

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It is important to reduce the human influence on natural resources by identifying an appropriate land use. Moreover, it is essential to carry out the scientific land evaluation. Such kind of analysis allows identifying the main factors of agricultural production and enables decision makers to develop crop management in order to increase the land capability. The key is to match the type and intensity of land use with its natural capability. Therefore; in order to benefit from these areas and invest them to obtain good agricultural production, they must be organized and managed in full. Lebanon suffers from the unorganized agricultural use. We take south Lebanon as a study area, it is the most fertile ground and has a variety of crops. The study aims to identify and locate the most suitable area to cultivate thirteen type of permanent trees which are: apples, avocados, stone fruits in coastal regions and stone fruits in mountain regions, bananas, citrus, loquats, figs, pistachios, mangoes, olives, pomegranates, and grapes. Several geographical factors are taken as criterion for selection of the best location to cultivate. Soil, rainfall, PH, temperature, and elevation are main inputs to create the final map. Input data of each factor is managed, visualized and analyzed using Geographic Information System (GIS). Management GIS tools are implemented to produce input maps capable of identifying suitable areas related to each index. The combination of the different indices map generates the final output map of the suitable place to get the best permanent tree productivity. The output map is reclassified into three suitability classes: low, moderate, and high suitability. Results show different locations suitable for different kinds of trees. Results also reflect the importance of GIS in helping decision makers finding a most suitable location for every tree to get more productivity and a variety in crops.

Keywords: agricultural production, crop management, geographical factors, Geographic Information System, GIS, land capability, permanent trees, suitable location

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Authors: M. F. El-Barghathi, R. El-Tajouri

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The effect of different concentrations of cadmium sulfate "CdSO4" (0.0, 10, 50, 100, 500 ppm) was tested on seed germination, seedling elongation and growth of Lepidium sativum (garden cress) plants. Results indicated that seed germination and seedling elongation were not inhibited by different concentrations of CdSO4. This could suggest that, Lepidium sativum may be used as a phyto remediation tool of soils contaminated with cadmium.

Keywords: Lepidium sativum, heavy metals, ionic toxicity, phytoremediation

Procedia PDF Downloads 530

Authors: Emiru Birhane, Tesfay Gidey, Haftu Abrha, Abrha Brhan, Amanuel Zenebe, Girmay Gebresamuel, Florent Noulèkoun

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Dracaena ombet and Dobera glabra are two of the most rare and endangered tree species in dryland areas. Unfortunately, their sustainability is being compromised by different anthropogenic and natural factors. However, the impacts of ongoing land use and climate change on the population structure and distribution of the species are less explored. This study was carried out in the grazing lands and hillside areas of the Desa'a dry Afromontane forest, northern Ethiopia, to characterize the population structure of the species and predict the impact of climate change on their potential distributions. In each land-use type, abundance, diameter at breast height, and height of the trees were collected using 70 sampling plots distributed over seven transects spaced one km apart. The geographic coordinates of each individual tree were also recorded. The results showed that the species populations were characterized by low abundance and unstable population structure. The latter was evinced by a lack of seedlings and mature trees. The study also revealed that the total abundance and dendrometric traits of the trees were significantly different between the two land uses. The hillside areas had a denser abundance of bigger and taller trees than the grazing lands. Climate change predictions using the MaxEnt model highlighted that future temperature increases coupled with reduced precipitation would lead to significant reductions in the suitable habitats of the species in northern Ethiopia. The species' suitable habitats were predicted to decline by 48–83% for D. ombet and 35–87% for D. glabra. Hence, to sustain the species populations, different strategies should be adopted, namely the introduction of alternative livelihoods (e.g., gathering NTFP) to reduce the overexploitation of the species for subsistence income and the protection of the current habitats that will remain suitable in the future using community-based exclosures. Additionally, the preservation of the species' seeds in gene banks is crucial to ensure their long-term conservation.

Keywords: grazing lands, hillside areas, land-use change, MaxEnt, range limitation, rare and endangered tree species

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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 59

Authors: Titinan Pothong, Prasit Wangpakapattanawong, Stephen Elliott

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Shifting cultivation is an indigenous agricultural practice among upland people and has long been one of the major land-use systems in Southeast Asia. As a result, fallows and secondary forests have come to cover a large part of the region. However, they are increasingly being replaced by monocultures, such as corn cultivation. This is believed to be a main driver of deforestation and forest degradation, and one of the reasons behind the recurring winter smog crisis in Thailand and around Southeast Asia. Accurate biomass estimation of trees is important to quantify valuable carbon stocks and changes to these stocks in case of land use change. However, presently, Thailand lacks proper tools and optimal equations to quantify its carbon stocks, especially for secondary evergreen forests, including fallow areas after shifting cultivation and smaller trees with a diameter at breast height (DBH) of less than 5 cm. Developing new allometric equations to estimate biomass is urgently needed to accurately estimate and manage carbon storage in tropical secondary forests. This study established new equations using a destructive method at three study sites: approximately 50-year-old secondary forest, 4-year-old fallow, and 7-year-old fallow. Tree biomass was collected by harvesting 136 individual trees (including coppiced trees) from 23 species, with a DBH ranging from 1 to 31 cm. Oven-dried samples were sent for carbon analysis. Wood density was calculated from disk samples and samples collected with an increment borer from 79 species, including 35 species currently missing from the Global Wood Densities database. Several models were developed, showing that aboveground biomass (AGB) was strongly related to DBH, height (H), and wood density (WD). Including WD in the model was found to improve the accuracy of the AGB estimation. This study provides insights for reforestation management, and can be used to prepare baseline data for Thailand’s carbon stocks for the REDD+ and other carbon trading schemes. These may provide monetary incentives to stop illegal logging and deforestation for monoculture.

Keywords: aboveground biomass, allometric equation, carbon stock, secondary forest

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Authors: Ashwinder K. Dhaliwal, G. P. S. Dhillon

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Eucalyptus is one of the most important forest tree species that can tolerate and grow well on degraded and unfertile soils which are not suitable for other tree species. Besides this, these trees have a short rotation and good economic value. However, the gall inducing wasp Leptocybe invasa Fisher and La Salle has been reported from many countries throughout the world. The spread of L. invasa is of huge economic concern as more than 20,000 ha of young Eucalyptus trees have already been affected in southern states of India. The host plant resistance being the first line of defense against insect pests demands the screening of different germplasm source against L. invasa. Keeping this in view, fourteen different clones of Eucalyptus spp. were evaluated for their susceptibility to L. invasa from a replicated clonal trial planted at Punjab Agricultural University, Ludhiana. The degree of gall infestation was recorded from three plants of each clone in each replication. Three branches selected from the lower, middle and upper canopy of the trees were selected for recording the total number of galls induced by L. invasa. The statistical analysis was done as per the procedure laid down for completely randomised block design (CRBD), analysis of variance (ANOVA), critical difference (CD) and variance components using Proc GLM (SAS software 9.3, SAS Institute Ltd. U.S.A). All possible treatment means were compared with Duncan’s multiple range test (DMRT) at 1 % probability level. The results showed that the clones C-9, C-45 and C-42 were completely free from the infestation of L. invasa. However, there was minor infestation of L. invasa on C-2135, C-413, C-407, C-35, C-72 and C-37 clones. The clone C-6 was severely infested by L. invasa followed by C-11, C-12, F-316 and C-25 clones. The information generated by this study will be helpful for future breeding and use in afforestation programmes.

Keywords: eucalyptus clones, gall wasp, Leptocybe invasa, screening, susceptibility

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Authors: Miguel Mellado, Cecilia Zapata

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

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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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Authors: Omar Alelweet

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Carbon emissions are quantified in terms of carbon dioxide equivalents, generated through a specific activity or accumulated throughout the life stages of a product or service. Given the growing concern about climate change and the role of carbon dioxide emissions in global warming, this initiative aims to create awareness and understanding of the impact of human activities and identify potential areas for improvement regarding the management of the carbon footprint on campus. Given that trees play a vital role in reducing carbon emissions by absorbing CO₂ during the photosynthesis process, this paper evaluated the contribution of each tree to reducing those emissions. Collecting data over an extended period of time is essential to monitoring carbon dioxide levels. This will help capture changes at different times and identify any patterns or trends in the data. By linking the data to specific activities, events, or environmental factors, it is possible to identify sources of emissions and areas where carbon dioxide levels are rising. Analyzing the collected data can provide valuable insights into ways to reduce emissions and mitigate the impact of climate change.

Keywords: sustainability, green building, environmental impact, CO₂

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Authors: Kareem Kalo Qassim, Hassan A. M. Mezori

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The bioaccumulation of heavy metals in the environment has become a matter of public interest because it persists in the soil longer than other components of the biosphere. Bioremediation has emerged as the ideal alternative environmentally friendly and ecological sound technology for removing pollutants from polluted sites. Phytoremediation is an attractive remediation technology that makes use of plants to remove contaminants from the environment. A pot experiment was conducted under lath house conditions to evaluate the ability of plants (H. Annuus, S. Bicolor, and Z. Mays) to phytoextract heavy metals from artificially polluted soils by different concentrations of Cadmium, Lead, and Copper (0, 100, 200, 200 + EDTA). The Seed germination was influenced by the presence of heavy metals and inhibition increased by increasing the heavy metals concentration. A significant difference was observed in the effect of lead and copper. Generally, the length of root, shoot, and intact plant was reduced by all the concentrations used in the experiments. The root system was affected more than the shoot system of the same plants. All heavy metals concentrations caused a reduction in the dry weight and chlorophyll content of all tested plant species; the reduction was increased by increasing the concentration of all heavy metals, especially when EDTA was added. The Bioaccumulation of heavy metals concentration of all the tested plants increased by increasing the concentration. The highest accumulation of cadmium was (81.77mg kg⁻¹), and copper was ( 65.07 mg kg⁻¹) in S. bicolor, while lead-in H. annuus was (60.74 mg kg⁻¹). The order of accumulation of heavy metals in all the tested plant species in the root system and the intact plant was as follows: H. annuus ˃ S. bicolor ˃ Z. mays and shoot system was: H. annuus ˃ Z. mays ˃ S. bicolor. The highest TF of cadmium was (0.41) in H. annuus; lead was (0.72) in Z. mays and S. bicolor, and copper was (0.44) in Z. mays. The tested plant species varied in their response to the heavy metals and the inhibition was concentration depended. In general, the roots system was more affected by heavy metals toxicity than the shoots system; the roots system accumulated more heavy metals in the roots than the shoots system. The addition of EDTA to the last concentration of heavy metals facilitated the availably and absorption of heavy metals from the polluted soil by all tested plant species.

Keywords: phytoextyraction, phytoremediation, translocation, heavy metals, soil pollution

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Authors: Seyed Armin Hashemi, Somayeh Rahimzadeh

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One-year seedlings of Acer velutinum were provided from plantations and the solution of Mercuric chloride was developed in 20,40 and 60 mg/l concentrations, then this solution was added to the soil and the Acer velutinum were placed in a vase. Six months after seedlings’ growth, the leaf, stem and roots were separated. The results were investigated by variance analysis and Duncan test. The highest level of mercury accumulation in the organs of leaf, stem and root was 45.67, 40 and 55 mg/kg, respectively. According to the obtained results from this research, the velutinum species was appropriate for refining the soils contaminated by mercury.

Keywords: heavy metals, acer velutinum, mercury, phytoremediation

Procedia PDF Downloads 371

Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

Procedia PDF Downloads 115

Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Misheck Musokwa, Paramu Mafongoya, Simon Lorentz

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Seasonal shortages of fodder during the dry season is a major constraint to smallholder livestock farmers in South Africa. To mitigate the shortage of fodder, legume trees can be intercropped with pastures which can diversify the sources of feed and increase the amount of protein for grazing animals. The objective was to evaluate dry matter yield of Panicum maximum and land productivity under different fodder production systems during 2016/17-2017/18 seasons at Empangeni (28.6391° S and 31.9400° E). A randomized complete block design, replicated three times was used, the treatments were sole Panicum maximum, Panicum maximum + Sesbania sesban, Panicum maximum + pigeonpea, sole Sesbania sesban, Sole pigeonpea. Three months S.sesbania seedlings were transplanted whilst pigeonpea was direct seeded at spacing of 1m x 1m. P. maximum seeds were drilled at a respective rate of 7.5 kg/ha having an inter-row spacing of 0.25 m apart. In between rows of trees P. maximum seeds were drilled. The dry matter yield harvesting times were separated by six months’ timeframe. A 0.25 m² quadrant randomly placed on 3 points on the plot was used as sampling area during harvesting P. maximum. There was significant difference P < 0.05 across 3 harvests and total dry matter. P. maximum had higher dry matter yield as compared to both intercrops at first harvest and total. The second and third harvest had no significant difference with pigeonpea intercrop. The results was in this order for all 3 harvest: P. maximum (541.2c, 1209.3b and 1557b) kg ha¹ ≥ P. maximum + pigeonpea (157.2b, 926.7b and 1129b) kg ha¹ > P. maximum + S. sesban (36.3a, 282a and 555a) kg ha¹. Total accumulation of dry matter yield of P. maximum (3307c kg ha¹) > P. maximum + pigeonpea (2212 kg ha¹) ≥ P. maximum + S. sesban (874 kg ha¹). There was a significant difference (P< 0.05) on seed yield for trees. Pigeonpea (1240.3 kg ha¹) ≥ Pigeonpea + P. maximum (862.7 kg ha¹) > S.sesbania (391.9 kg ha¹) ≥ S.sesbania + P. maximum. The Land Equivalent Ratio (LER) was in the following order P. maximum + pigeonpea (1.37) > P. maximum + S. sesban (0.84) > Pigeonpea (0.59) ≥ S. Sesbania (0.57) > P. maximum (0.26). Results indicates that it is beneficial to have P. maximum intercropped with pigeonpea because of higher land productivity. Planting grass with pigeonpea was more beneficial than S. sesban with grass or sole cropping in terms of saving the shortage of arable land. P. maximum + pigeonpea saves a substantial (37%) land which can be subsequently be used for other crop production. Pigeonpea is recommended as an intercrop with P. maximum due to its higher LER and combined production of livestock feed, human food, and firewood. Panicum grass is low in crude protein though high in carbohydrates, there is a need for intercropping it with legume trees. A farmer who buys concentrates can reduce costs by combining P. maximum with pigeonpea this will provide a balanced diet at low cost.

Keywords: fodder, livestock, productivity, smallholder farmers

Procedia PDF Downloads 123