Search results for: forest soil

Authors: S. A. Naeini, Z. Eftekhari

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Liquefaction phenomenon in sand is nowadays a classical soil mechanics subject. Using a cyclic triaxial test apparatus, we use non-woven geotextile reinforcement to improve the liquefaction resistance of sand. The layer configurations used are zero, one, two and three horizontal reinforcing layers in a triaxial test sample. The influences of the number of geotextile layers, and cyclic stress ratio (CSR) were studied and described. The results illustrated that the geotextile inclusion increases liquefaction resistance.

Keywords: liquefaction resistance, geotextile, sand, cyclic triaxial test, cyclic stress ratio

Procedia PDF Downloads 579

Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

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Authors: Maria Trimintziou, Michael Sakellariou, Prodromos Psarropoulos

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Nowadays, the exploitation of hydrocarbons reserves in deep seas and oceans, in combination with the need to transport hydrocarbons among countries, has made the design, construction and operation of offshore pipelines very significant. Under this perspective, it is evident that many more offshore pipelines are expected to be constructed in the near future. Since offshore pipelines are usually crossing extended areas, they may face a variety of geohazards that impose substantial permanent ground deformations (PGDs) to the pipeline and potentially threaten its integrity. In case of a geohazard area, there exist three options to proceed. The first option is to avoid the problematic area through rerouting, which is usually regarded as an unfavorable solution due to its high cost. The second is to apply (if possible) mitigation/protection measures in order to eliminate the geohazard itself. Finally, the last appealing option is to allow the pipeline crossing through the geohazard area, provided that the pipeline will have been verified against the expected PGDs. In areas with moderate or high seismicity the design of an offshore pipeline is more demanding due to the earthquake-related geohazards, such as landslides, soil liquefaction phenomena, and active faults. It is worthy to mention that although worldwide there is a great experience in offshore geotechnics and pipeline design, the experience in seismic design of offshore pipelines is rather limited due to the fact that most of the pipelines have been constructed in non-seismic regions (e.g. North Sea, West Australia, Gulf of Mexico, etc.). The current study focuses on the seismic design of offshore pipelines against active faults. After an extensive literature review of the provisions of the seismic norms worldwide and of the available analytical methods, the study simulates numerically (through finite-element modeling and strain-based criteria) the distress of offshore pipelines subjected to PGDs induced by active seismic faults at the seabed. Factors, such as the geometrical properties of the fault, the mechanical properties of the ruptured soil formations, and the pipeline characteristics, are examined. After some interesting conclusions regarding the seismic vulnerability of offshore pipelines, potential cost-effective mitigation measures are proposed taking into account constructability issues.

Keywords: offhore pipelines, seismic design, active faults, permanent ground deformations (PGDs)

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Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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Watercourses in Brazilian urban areas are constantly being degraded due to the unplanned use of the urban space; however, due to the different contexts of land use and occupation in the river watersheds, different intervention strategies are required to requalify them. When it comes to requalifying watercourses, we can list three main techniques to fulfill this purpose: restoration, revitalization and recovery; each one being indicated for specific contexts of land use and occupation in the basin. In this study, it was demonstrated that the application of these three techniques to three small basins in São Paulo city, listing the aspects involved in each of the contexts and techniques of requalification. For a protected watercourse within a forest park, renaturalization was proposed, where the watercourse is preserved in a state closer to the natural one. For a watercourse in an urban context that still preserves open spaces for its maintenance as a landscape element, an intervention was proposed following the principles of revitalization, integrating the watercourse with the landscape and the population. In the case of a watercourse in a harder context, only recovery was proposed, since the watercourse is found under the road system, which makes it difficult to integrate it into the landscape.

Keywords: sustainable drainage, river restoration, river revitalization, river recovery

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Authors: Siraj Beyan Mohamed, Woldia University

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The study is accompanied in northern Ethiopian basement rocks, Finarwa area, and its surrounding areas, south eastern Tigray. From the field observations, the geology of the area haven been described and mapped based on mineral composition, texture, structure, and colour of both fresh and weather rocks. Inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectrometry (AAS) have conducted to analysis gold and base metal mineralization. The ore mineral under microscope are commonly base metal sulphides pyrrhotite, Chalcopyrite, pentilanditeoccurring in variable proportions. Galena, chalcopyrite, pyrite, and gold mineral are hosted in quartz vein. Pyrite occurs both in quartz vein and enclosing rocks as a primary mineral. The base metal sulfides occur as disseminated, vein filling, and replacement. Geochemical analyses result determination of the threshold of geochemical anomalies is directly related to the identification of mineralization information. From samples, stream sediment samples and the soil samples indicated that the most promising mineralization occur in the prospect area are gold(Au), copper (Cu), and zinc (Zn). This is also supported by the abundance of chalcopyrite and sphalerite in some highly altered samples. The stream sediment geochemical survey data shows relatively higher values for zinc compared to Pb and Cu. The moderate concentration of the base metals in some of the samples indicates availability base metal mineralization in the study area requiring further investigation. The rock and soil geochemistry shows the significant concentration of gold with maximum value of 0.33ppm and 0.97 ppm in the south western part of the study area. In Finarwa, artisanal gold mining has become an increasingly widespread economic activity of the local people undertaken by socially differentiated groups with a wide range of education levels and economic backgrounds incorporating a wide variety of ‘labour intensive activities without mechanisation.

Keywords: gold, base metal, anomaly, threshold

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Authors: Felix Lankester, Alicia Davis, Safari Kinung'hi, Catherine Bunga, Shayo Alkara, Imam Mzimbiri, Jonathan Yoder, Sarah Cleaveland, Guy H. Palmer

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Achieving the London Declaration goal of a 90% reduction in neglected tropical diseases (NTDs) by 2030 requires cost-effective strategies that attain high and comprehensive coverage. The first objective of this trial was to assess the impact on cost and coverage of employing a novel integrative One Health approach linking two NTD control programs: mass drug administration (MDA) for soil-transmitted helminths in humans (STH) and mass dog rabies vaccination (MDRV). The second objective was to compare the coverage achieved by the MDA, a community-wide deworming intervention, with that of the existing national primary school-based deworming program (NSDP), with particular focus on the proportion of primary school-age children reached and their school enrolment status. Our approach was unconventional because, in line with the One Health approach to disease control, it coupled the responsibilities and resources of the Ministries responsible for human and animal health into one program with the shared aim of preventing multiple NTDs. The trial was carried out in hard-to-reach pastoral communities comprising 24 villages of the Ngorongoro District, Tanzania, randomly allocated to either Arm A (MDA and MDRV), Arm B (MDA only) or Arm C (MDRV only). Objective one: The percentage of people in each target village that received treatment through MDA in Arms A and B was 63% and 65%, respectively (χ2 = 1, p = 0.32). The percentage of dogs vaccinated in Arm A and C was 70% and 81%, respectively (χ2 =9, p = 0.003). It took 33% less time for a single person and a dog to attend the integrated delivery than two separate events. Cost per dose (including delivery) was lower under the integrated strategy, with delivery of deworming and rabies vaccination reduced by $0.13 (54%) and $0.85 (19%) per dose, respectively. Despite a slight reduction in the proportion of village dogs vaccinated in the integrated event, both the integrated and non-integrated strategies achieved the target threshold of 70% required to eliminate rabies. Objective two: The percentages of primary school age children enrolled in school that was reached by this trial (73%) and the existing NSDP (80%) were not significantly different (F = 0.9, p = 0.36). However, of the primary school age children treated in this trial, 46% were not enrolled in school. Furthermore, 86% of the people treated would have been outside the reach of the NSDP because they were not primary school age or were primary school age children not enrolled in school. The comparable reach, the substantial reductions in cost per dose delivered and the decrease in participants’ time support this integrated One Health approach to control multiple NTDs. Further, the recorded level of non-enrolment at primary school suggests that, in remote areas, school-based delivery strategies could miss a large fraction of school-age children and that programs that focus delivery solely at the level of the primary school will miss a substantial proportion of both primary school age children as well as other individuals from the community. We have shown that these populations can be effectively reached through extramural programs.

Keywords: canine mediated human rabies, integrated health interventions, mass drug administration, neglected tropical disease, One Health, soil-transmitted helminths

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Authors: Mateus L. O. Freitas, Flávia H. de M. Libório, Letycia L. Ricardo, Patrícia da C. Zonetti, Graciene de S. Bido

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Weeds compete with agricultural crops for resources such as light, water, and nutrients. This competition can cause significant damage to agricultural producers, and, currently, the use of agrochemicals is the most effective method for controlling these undesirable plants. Morning glory (Ipomoea grandifolia [Dammer] O'Donell) is an aggressive weed and significantly reduces agricultural productivity making harvesting difficult, especially mechanical harvesting. The biggest challenge in modern agriculture is to preserve high productivity reducing environmental damage and maintaining soil characteristics. No-till is a sustainable practice that can reduce the use of agrochemicals and environmental impacts due to the presence of plant residues in the soil, which release allelopathic compounds and reduce the incidence or alter the growth and development of crops and weeds. Sorghum (Sorghum bicolor [L.] Moench) is a forage with proven allelopathic activity, mainly for producing sorgholeone. In this context, this research aimed to evaluate the allelopathic action of sorghum fractions using hexane, dichloromethane, butanol, and ethyl acetate on the germination and initial growth of morning glory. The parameters analyzed were the percentage of germination, speed of germination, seedling length, and biomass weight (fresh and dry). The bioassays were performed in Petri dishes, kept in an incubation chamber for 7 days, at 25 °C, with a 12h photoperiod. The experimental design was completely randomized, with five replicates of each treatment. The data were evaluated by analysis of variance, and the averages between each treatment were compared using the Scott Knott test at a 5% significance level. The results indicated that the dichloromethane and ethyl acetate fractions showed bioherbicidal effects, promoting effective reductions on germination and initial growth of the morning glory. It was concluded that allelochemicals were probably extracted in these fractions. These secondary metabolites can reduce the use of agrochemicals and environmental impact, making agricultural production systems more sustainable.

Keywords: allelochemicals, secondary metabolism, sorgoleone, weeds

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Authors: Vhuhwavho Gadisi, Rebecca Alowo, German Nkhonjera

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This article sets out to detail an investigation of groundwater management in the Juksei Catchment of South Africa through spatial mapping of key hydrological relationships, interactions, and parameters in catchments. The Department of Water Affairs (DWA) noted gaps in the implementation of the South African National Water Act 1998: article 16, including the lack of appropriate models for dealing with water quantity parameters. For this reason, this research conducted a drastic GIS-based groundwater assessment to improve groundwater monitoring system in the Juksei River basin catchment of South Africa. The methodology employed was a mixed-methods approach/design that involved the use of DRASTIC analysis, questionnaire, literature review and observations to gather information on how to help people who use the Juskei River. GIS (geographical information system) mapping was carried out using a three-parameter DRASTIC (Depth to water, Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, Hydraulic conductivity) vulnerability methodology. In addition, the developed vulnerability map was subjected to sensitivity analysis as a validation method. This approach included single-parameter sensitivity, sensitivity to map deletion, and correlation analysis of DRASTIC parameters. The findings were that approximately 5.7% (45km2) of the area in the northern part of the Juksei watershed is highly vulnerable. Approximately 53.6% (428.8 km^2) of the basin is also at high risk of groundwater contamination. This area is mainly located in the central, north-eastern, and western areas of the sub-basin. The medium and low vulnerability classes cover approximately 18.1% (144.8 km2) and 21.7% (168 km2) of the Jukskei River, respectively. The shallow groundwater of the Jukskei River belongs to a very vulnerable area. Sensitivity analysis indicated that water depth, water recharge, aquifer environment, soil, and topography were the main factors contributing to the vulnerability assessment. The conclusion is that the final vulnerability map indicates that the Juksei catchment is highly susceptible to pollution, and therefore, protective measures are needed for sustainable management of groundwater resources in the study area.

Keywords: contamination, DRASTIC, groundwater, vulnerability, model

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Authors: Subir Kundu, Sukhendra Singh, Sumedha Ojha, Kanika Kundu

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The continuous decline of petroleum and natural gas reserves and non linear rise of oil price has brought about a realisation of the need for a change in our perpetual dependence on the fossil fuel. A day to day increased consumption of crude and petroleum products has made a considerable impact on our foreign exchange reserves. Hence, an alternate resource for the conversion of energy (both liquid and gas) is essential for the substitution of conventional fuels. Biomass is the alternate solution for the present scenario. Biomass can be converted into both liquid as well as gaseous fuels and other feedstocks for the industries.

Keywords: bioenergy, biomass conversion, biorefining, efficient utilisation of night soil

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Yosiya Chanta, Jantrararuk Tovaranont

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Species distribution model (SDMs) is one of the powerful tools used to create a suitability map used to predict and address ecology and conservation approaches. MaxEnt is a tool used among SDMs that is highly popular because it only uses presence data. Zanthoxylum rhetsa has more than 200 species distributed in the tropics. Most commonly found in cooler forest environments, there are 8-9 species found in Thailand. In northern Thailand, 3 varieties are commonly grown: Zanthoxylum myriacanthum, Zanthoxylum rhetsa and Zanthoxylum armatum. In the northern regions, these varieties are mainly used as a spice and as a cooking ingredient. MaxEnt has been used in this study to predict potential habitats for these Zanthoxylums in current and future times (2041and 2060). Suitable habitats are predicted using data from the EC-Earth3-Veg general circulation model with 19 climatic variables. The results indicate that the suitability of future habitats of Zanthoxylum rhetsa may expand into the lower northern part of Thailand. The habitat suitability map obtained from the MaxEnt tool shows that the Precipitation of Wettest Quarter (Bio16) is the most important climatic variable influencing the current and future spread of Zanthoxylum rhetsa.

Keywords: MaxEnt, Zanthoxylum rhets, species distribution modelling, climate change

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Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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Authors: Alvarado M. Lady G., Ortiz V. Yaylenne, Quintero B. Quelbis R.

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The oil palm sector has seen significant growth in Colombia after the insertion of policies to stimulate the use of biofuels, which eventually contributes to the reduction of greenhouse gases (GHG) that deteriorate not only the environment but the health of people. However, the policy of using biofuels has been strongly questioned by the impacts that can generate; an example is the increase of other more harmful GHGs like the CH₄ that underlies the amount of solid waste generated. Casanare's department is estimated be one of the major producers of palm oil of the country given that has recently expanded its sowed area, which implies an increase in waste generated primarily in the industrial stage. For this reason, the following study evaluated the agronomic potential of the biochar obtained from empty fruit bunches and its nutritional contribution in cultivated soils with Elaeis guineensis in Casanare, Colombia. The biochar was obtained by slow pyrolysis of the clusters in a retort oven at an average temperature of 190 °C and a residence time of 8 hours. The final product was taken to the laboratory for its physical and chemical analysis as well as a soil sample from a cultivation of Elaeis guineensis located in Tauramena-Casanare. With the results obtained plus the bibliographical reports of the nutrient demand in this cultivation, the possible nutritional contribution of the biochar was determined. It is estimated that the cultivation requirements of nitrogen is 12.1 kg.ha⁻¹, potassium is 59.3 kg.ha⁻¹, magnesium is -31.5 kg.ha⁻¹ and phosphorus is 5.6 kg.ha⁻¹ obtaining a biochar contribution of 143.1 kg.ha⁻¹, 1204.5 kg.ha⁻¹, 39.2 kg.ha⁻¹ and 71.6 kg.ha⁻¹ respectively. The incorporation of biochar into the soil would significantly improve the concentrations of N, P, K and Mg, nutrients considered important in the yield of palm oil, coupled with the importance of nutrient recycling in agricultural production systems sustainable. The biochar application improves the physical properties of soils, mainly in the humidity retention. On the other hand, it regulates the availability of nutrients for plants absorption, with economic savings in the application of synthetic fertilizers and water by irrigation. It also becomes an alternative to manage agricultural waste, reducing the involuntary emissions of greenhouse gases to the environment by decomposition in the field, reducing the CO₂ content in the atmosphere.

Keywords: biochar, nutrient recycling, oil palm, pyrolysis

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Dilnee D. Suraweera, Tim Groom, Brian Chung, Brendan Bond, Andrew Schipp, Marc E. Nicolas

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Pyrethrum (Tanacetum cinerariifolium) is a perennial plant belongs to family Asteraceae. This is cultivated commercially for extraction of natural insecticide pyrethrins, which accumulates in their flower head achenes. Approximately 94% of the pyrethrins are produced within secretory ducts and trichomes of achenes of the mature pyrethrum flower. This is the most widely used botanical insecticide in the world and Australia is the current largest pyrethrum producer in the world. Rainfall in pyrethrum growing regions in Australia during pyrethrum flowering period, in late spring and early summer is significantly less. Due to lack of adequate soil moisture and under elevated temperature conditions during post-anthesis period, resulting in yield reductions. Therefore, understanding of yield responses of pyrethrum to irrigation is important for Pyrethrum as a commercial crop. Irrigation management has been identified as a key area of pyrethrum crop management strategies that could be manipulated to increase yield. Pyrethrum is a comparatively drought tolerant plant and it has some ability to survive in dry conditions due to deep rooting. But in dry areas and in dry seasons, the crop cannot reach to its full yield potential without adequate soil moisture. Therefore, irrigation is essential during the flowering period prevent crop water stress and maximise yield. Irrigation during the water deficit period results in an overall increased rate of water uptake and growth by the plant which is essential to achieve the maximum yield benefits from commercial crops. The effects of irrigation treatments applied at post-anthesis period on pyrethrum yield responses were studied in two irrigation methods. This was conducted in a first harvest commercial pyrethrum field in Waubra, Victoria, during 2012/2013 season. Drip irrigation and overhead sprinkler irrigation treatments applied during whole flowering period were compared with ‘rainfed’ treatment in relation to flower yield and pyrethrin yield responses. The results of this experiment showed that the application of 180mm of irrigation throughout the post-anthesis period, from early flowering stages to physiological maturity under drip irrigation treatment increased pyrethrin concentration by 32%, which combined with the 95 % increase in the flower yield to give a total pyrethrin yield increase of 157%, compared to the ‘rainfed’ treatment. In contrast to that overhead sprinkler irrigation treatment increased pyrethrin concentration by 19%, which combined with the 60 % increase in the flower yield to give a total pyrethrin yield increase of 91%, compared to the ‘rainfed’ treatment. Irrigation treatments applied throughout the post-anthesis period significantly increased flower yield as a result of enhancement of number of flowers and flower size. Irrigation provides adequate soil moisture for flower development in pyrethrum which slows the rate of flower development and increases the length of the flowering period, resulting in a delayed crop harvest (11 days) compared to the ‘rainfed’ treatment. Overall, irrigation has a major impact on pyrethrin accumulation which increases the rate and duration of pyrethrin accumulation resulting in higher pyrethrin yield per flower at physiological maturity. The findings of this study will be important for future yield predictions and to develop advanced agronomic strategies to maximise pyrethrin yield in pyrethrum.

Keywords: achene, drip irrigation, overhead irrigation, pyrethrin

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Authors: Bo Wang

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As the first high-resolution civil optical satellite, ZY-3 satellite is able to obtain high-resolution multi-view images with three linear array sensors. The images can be used to generate Digital Elevation Models (DEM) through dense matching of stereo images. However, due to the clouds, forest, water and buildings covered on the images, there are some problems in the dense matching results such as outliers and areas failed to be matched (matching holes). This paper introduced an algorithm to verify the accuracy of DEM that generated by ZY-3 satellite with Shuttle Radar Topography Mission (SRTM). Since the accuracy of SRTM (Internal accuracy: 5 m; External accuracy: 15 m) is relatively uniform in the worldwide, it may be used to improve the accuracy of ZY-3 DEM. Based on the analysis of mass DEM and SRTM data, the processing can be divided into two aspects. The registration of ZY-3 DEM and SRTM can be firstly performed using the conjugate line features and area features matched between these two datasets. Then the ZY-3 DEM can be refined by eliminating the matching outliers and filling the matching holes. The matching outliers can be eliminated based on the statistics on Local Vector Binning (LVB). The matching holes can be filled by the elevation interpolated from SRTM. Some works are also conducted for the accuracy statistics of the ZY-3 DEM.

Keywords: ZY-3 satellite imagery, DEM, SRTM, refinement

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Authors: Nuraeni, Suryanti, Saida, Annas Boceng

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Farm forestry is a forest where farmers or landowners do cultivation and farming activities on their land. This study aims to determine the dimensions of sustainable development of farm forestry and to analyze the leverage factors to improve the sustainability status of farm forestry management in Bulukumba Regency. This research was conducted in Kajang District, Bulukumba Regency. The analysis of the sustainability of farm forestry management applied Multi-Dimensional Scaling (MDS), a modification of the Rapid Appraisal of The Status of Farming (RAPFARM). The index value of farm forestry sustainability was by 62.01% for ecological dimension, 51.54% for economic dimension, 61.00% for the social and cultural dimension, and 63.24% for legal and institutional dimension with sustainable enough category status. Meanwhile, the index value for the technology and infrastructure was by 47.16% of less sustainable category status. The result of leverage analysis of attributes for the dimensions of ecological, economic, social and cultural, legal and institutional as well as infrastructure and technology afforded twenty-two (22) leverage sensitive factors that influence the sustainability of farm forestry.

Keywords: farm forestry, South Sulawesi, management, sustainability

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Gabriel Vusanimuzi Nkomo

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The majority of soils in communal areas of Zimbabwe are sandy and inherently infertile and sustainable cultivation is not feasible without addition of plant nutrients. Most farmers find it difficult to raise the capital required for investments in mineral fertilizer and find it cheaper to use low nutrition animal manure. An experiment was conducted to determine the effects of nitrokara biofertiliser on early growth, development and maize yield while also comparing nitrokara biofertiliser on availability of nitrogen and phosphorous in soil. The experiment was conducted at Africa University Farm. The experiment had six treatments (nitrokara +300kg/ha Compound D, nitrokara+ 300kg/ha Compound D(7N;14P;7K) + 75kg/ha Ammonium Nitrate(AN), nitrokara +300kg/ha Compound D +150kg AN, nitrokara +300kg/ha Compound D +225kg/ha AN, nitrokara +300kg/ha Compound D + 300 kg/ha AN and 0 nitrokara+300kg/ha Compound D +0 AN). Early maturing SC 403 maize (Zea mays) was inoculated with nitrokara and a compound mineral fertilizer at 300 kg/ha at planting while ammonium nitrate was applied at 45 days after planting. There were no significant differences (P > 0.05) on emergence % from 5days up to 10 days after planting using maize seed inoculated with nitrokara. Emergence percentage varied with the number of days. At 5 days the emergence % was 62% to a high of 97 % at 10 days after emergence among treatments. There were no significant differences (P > 0.05) on plant biomass on treatments 1 to 6 at 4 weeks after planting as well as at 8 weeks after planting. There were no significant differences among the treatments on the availability of nitrogen after 6 weeks (P > 0.05). However at 8 and 10 weeks after planting there were significant differences among treatments on nitrogen availability (P < 0.05). There were no significant differences among the treatments at week 6 after planting on soil pH (p > 0.05). However there were significant differences among treatments pH at weeks 9 and 12 (p < 0.05). There were significant differences among treatments on phosphorous availability at 6, 8 and 10 weeks after planting (p < 0.05). There were no significant differences among treatments on stem diameter at 3 and 6 weeks after planting (p > 0.05).However at 9 and 12 weeks after planting there were significant differences among treatments on stem diameter (p < 0.05).There were no significant differences among treatments on plant height from week 3 up to week 6 on plant height (P > 0.05).However there were significant differences among treatments at week 9 and 12 (p < 0.05). There were significant differences among treatments on days to early, 50% and 100% anthesis (P < 0.05). There were significant differences during early, 50% and 100% days to silking among the treatments (P < 0.05).Also there were significant differences during early, 50% and 100% days to silking among the treatments (P < 0.05).The study revealed that inoculation of nitrokara biofertiliser at planting with subsequent addition of ammonium nitrate has a positive effect on maize crop development and yield.

Keywords: nitrokara, biofertiliser, symbiotic, plant biomass, inoculated

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

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Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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Authors: Ayşen Melda Çolak, Volkan Okatan, Ercan Yıldız

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In our country, fruit production was determined as 17.2 million tons in 2011 according to official data. Turkey fig, apricot, cherry and quince production ranks first in the world. Almost all the regions of our country, despite the growing of fruit 54% of the total fruit production occur in the Mediterranean and the Aegean Region. However, fruit production in the country is consumed in the domestic market and export rates are often very low. In this study, a questionnaire to 100 farmers face-to-face interview. According to the survey, 40% of those in fruit and 7 da of 7 hectares land are small. 30% of soil testing for manufacturers, testing for 20% of the water. Manufacturers who deliberately fertilization rate of only 10%.

Keywords: fruit, generation, potential, Sivasli survey

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Authors: Indu Bala Sethi, Meena Sewhag, Rakesh Kumar, Parveen Kumar

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Field experiment was conducted at Pulse Research Area of CCS Haryana Agricultural University, Hisar during rabi 2012-13 to study the economics of chickpea cultivars as influenced by sowing time and seed rate on sandy loam soils under irrigated conditions. The factorial experiment consisting of 24 treatment combinations with two sowing time (1st fortnight of November and 1st fortnight of December.) and four cultivars (H09-23, H08-18, C-235 and HC-1) kept in main plots while three seed rates viz. 40 kg ha-1, 50 kg ha-1 and 60 kg ha-1 was laid out in split plot design with three replications. The crop was sown with common row spacing of 30 cm as per the dates of sowing. The fertilizer was applied in the form of di- ammonium phosphate. The soil of the experimental site was deep sandy loam having pH of 7.9, EC of 0.13 dS/m and low in organic carbon (0.34%), low in available N status (193.36 kg ha-1), medium in available P2O5 (32.18 kg ha-1) and high in available K2O (249.67 kg ha-1). The crop was irrigated as and when required so as to maintain adequate soil moisture in the root zone The crop was sprayed with monocrotophos (1.25 l/ha) at initiation of flowering and at pod filling stage to protect the crop from pod borer attack. The yield was measured at the time of harvest. The cost of field preparation, sowing of seeds, thinning, weeding, plant protection, harvesting and cleaning contributed to fixed cost. The experiment was laid out in a split plot design with two sowing time (1st fortnight of November and 1st fortnight of December.) and four cultivars (H09-23, H08-18, C-235 and HC-1) kept in main plots while three seed rates viz. 40 kg ha-1, 50 kg ha-1 and 60 kg ha-1 were kept in subplots and replicated thrice. Results revealed that 1st fortnight of November sowing recorded significantly higher gross (Rs.1, 01,254 ha-1), net returns (Rs. 68,504 ha-1) and BC (3.09) ratio as compared to delayed crop of chickpea. Highest gross (Rs.91826 ha-1), net returns (Rs. 59076ha-1) and BC ratio (2.81) was recorded with H08-18. Higher value of cost of cultivation of chickpea was observed in higher seed rate than the lower ones. However no significant variation in net and gross returns was observed due to seed rates. Highest BC (2.72) ratio was recorded with 50 kg ha-1 which differs significantly from 60 kg ha-1 but was at par with 40 kg ha-1. This is because of higher grain yield obtained with 50 kg ha-1 seed rate. Net profit for farmers growing chickpea with seed rate of 50 kg ha-1 was higher than the farmers growing chickpea with seed rate of 40 and 60 kg ha.

Keywords: chickpea, cultivars, seed rate, sowing time

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Authors: Olgha Giorgishvili

Abstract:

The work is mainly concerned with the determination of modulus of deformation by laboratory method. It is known that a modulus of deformation is defining by laboratory and field methods. By laboratory method the modulus of deformation is defined in the compressive devices. Our goal is to conduct experiments by both methods and finally make to interpret the obtained results. In this article is considered the definition by new offered laboratory method of deformation modulus that is closer to the real deformation modulus. Finally, the obtained results gives the possibility to us to raise the issue of change the state norms for determining ground by laboratory method.

Keywords: building, soil mechanic, deformation moulus, compression methods

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Authors: Isa Muhammad Zumo

Abstract:

The African Great Green Wall (GGW) is a significant initiative in northern Nigeria because it promotes land restoration and conservation utilizing both commercial and species of forest trees while also helping to mitigate desertification and hazards from the sand dunes and shifting Sahara deserts. Conflicts and weather, however, pose a significant danger to the achievement of these goals. The scientific method for monitoring the vegetation dynamics since inception has not received the required attention, despite the African Development Bank (ADB)'s help in funding the project and its integration into the state's development plans for GGW initiatives. This study will monitor the changes in the vegetation cover of the great green wall within Yobe State Nigeria from 2014 to 2023. The vegetation dynamics will be monitored using Landsat 8 Operational Land Imager (OLI) for 6 years at 2 years intervals. The result will show the fluctuations in the vegetation cover density within the period of study. This will guide the design and implementation of policies of the GGW in achieving its objectives. The result can also contribute to the realization of Sustainable Development Goal (SDG) Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

Keywords: monitoring, green wall, Landsat 8, Nigeria

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Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Kiran Nawaz, Ahmad Ali Shahid, Sehrish Iftikhar, Waheed Anwar, Muhammad Nasir Subhani

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Chili (Solanum annum L.) attacks by many fungal pathogens, including members of Oomycetes which are responsible for root rot in different chili growing areas of the world. Oomycetes pathogens cause economic losses in different regions of the Pakistan. Most of the plant tissues, including roots, crowns, fruit, and leaves, are vulnerable to Phytophthora capsici. It is very difficult to manage the Phytophthora root rot of chili as many commercial varieties are tremendously vulnerable to P. capsici. The causal agent of the disease was isolated on corn meal agar (CMA) and identified on a morphological basis by using available taxonomic keys. The pathogen was also confirmed on the molecular basis through internal transcribed spacer region and with other molecular markers.The Blastn results showed 100% homology with already reported sequences of P. capsici in NCBI database. Most of the farmers have conventionally relied on foliar fungicide applications to control Phytophthora root rot in spite of their incomplete effectiveness. In this study, in vitro plate assay, seed soaking and foliar applications of 6 fungicides were evaluated against root rot of chili. In vitro assay revealed that significant inhibition of linear growth was obtained with Triflumizole at 7.0%, followed by Thiophanate methyl (8.9%), Etridiazole (6.0%), Propamocarb (5.9%) and 7.5% with Mefenoxam and Iprodione for P. capsici. The promising treatments of in vitro plate bioassay were evaluated in pot experiments under controlled conditions in the greenhouse. All fungicides were applied after at 6-day intervals. Results of pot experiment showed that all treatments considerably inhibited the percentage of P. capsici root rot incidence. In addition, application of seed soaking with all six fungicides combined with the foliar spray of the same components showed the significant reduction in root rot incidence. The combine treatments of all fungicides as in vitro bioassay, seed soaking followed by foliar spray is considered non-harmful control methods which have advantages and limitation. Hence, these applications proved effective and harmless for the management of soil-borne plant pathogens.

Keywords: blastn, bioassay, corn meal agar(CMA), oomycetes

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Authors: Garima Sharma, R. N. Sharma

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Integrated watershed management programme based on 'Four Water Concept' was implemented in Sali village, in Jaipur District, Rajasthan State of India . The latitude 26.7234486 North and longitude 75.023876 East are the geocoordinate of the Sali. 'Four Waters Concept' is evolved by integrating the 'Four Waters', viz. rain water, soil moisture, ground water and surface water This methodology involves various water harvesting techniques to prevent the runoff of water by treatment of catchment, proper utilization of available water harvesting structures, renovation of the non-functional water harvesting structures and creation of new water harvesting structures. The case study included questionnaire survey from farmers and continuous study of village for two years. The total project area is 6153 Hac, and the project cost is Rs. 92.25 million. The sanctioned area of Sali Micro watershed is 2228 Hac with an outlay of Rs. 10.52 million. Watershed treatment activities such as water absorption trench, continuous contour trench, field bunding, check dams, were undertaken on agricultural lands for soil and water conservation. These measures have contributed in preventing runoff and increased the perennial availability of water in wells. According to the survey, water level in open wells in the area has risen by approximately 5 metres after the introduction of water harvesting structures. The continuous availability of water in wells has increased the area under irrigation and helped in crop diversification. Watershed management activities have brought the changes in cropping patterns and crop productivity. It helped in transforming 567 Hac culturable waste land into culturable arable land in the village. The farmers of village have created an additional income from the increased crop production. The programme also assured the availability of water during peak summers for the day to day activities of villagers. The outcomes indicate that there is positive impact of watershed management practices on the water resource potential as well the crop production of the area. This suggests that persistent efforts in this direction may lead to sustainability of the watershed.

Keywords: four water concept, groundwater potential, irrigation potential, watershed management

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

Procedia PDF Downloads 315