Search results for: precision agriculture

Authors: Oliver Echezona Ngwu

Abstract:

The research was conducted in 2011 cropping season at the Teaching and Research farm of the Faculty of Agriculture and Natural Resources Management, Enugu State University of Science and Technology, Enugu, Nigeria to study the effect of organic and inorganic fertilizers on the growth and yield of physic Nut (Jatropha curcas). There were five treatments namely, control, (no application of treatment), NPK 20:10:10, NPK 15:15;15, poultry droppings and goat dung. The treatments were laid out in a Randomized complete Block Design (RCBD) with five replications. The total land area used was 228m2 (19x12m) while the plot size was 3mx2 (6m2). The growth parameters measured were plant height, number of leaves, and leaf area, index (LAI). The results obtained showed that there were significant differences at P=0.05 among the different treatments in 30, to and 90 DAP. Based on the results T4 (poultry droppings) had higher effect at P=0.05 at 30, 60, 90 DAP than the other treatments when compared and is hereby recommended as the best type of fertilizer for the optimum growth and production of physic Nut (Jatropha Curcas) in South Eastern Nigeria.

Keywords: organic, inorganic fertilizers, growth, yield, Jatropha curcas

Procedia PDF Downloads 288

Authors: Akhilesh Mishra, Geeta Rai, Arvind Srivastava, Nalini Tiwari

Abstract:

A field experiment was conducted during two consecutive Rabi seasons of 2007 and 2008 to study the economics of different bio-fertilizer’s inoculations in fieldpea (cv. Jai) at Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (India). Results indicated that the seed inoculation with Rhizobium + PSB + PGPR improved all the growth; yield attributes and yields of field pea. Fresh and dry weight plant-1, nodules number and dry weight plant-1 were found significantly maximum. Number of grains pod-1, number and weight of pods plant-1 at maturity attributed significantly in increasing the grain yield as well as net return. On pooled basis, maximum net income (Rs.22169 ha-1) was obtained with the use of Rhizobium + PSB + PGPR which was improved by a margin of Rs.1502 (6.77%), 2972 (13.40%), 2672 (12.05%), 5212 (23.51%), 6176 (27.85%), 4666 (21.04%) and 8842/ha (39.88%) over the inoculation of PSB + PGPR, Rhizobium + PGPR, Rhizobium + PSB, PGPR, PSB, Rhizobium and control, respectively. Thus, it can be recommended that to earn the maximum net profit from dwarf field pea, seed should be inoculated with Rhizobium + PSB + PGPR.

Keywords: rhizobium, phosphorus solubilizing bacteria, plant growth promoting rhizobacteria, field pea

Procedia PDF Downloads 414

Authors: Olusegun Raphael Adeyemi, Samuel Oluwaseun Osunleti, Abiddin Adekunle Bashiruddin

Abstract:

Field trials were conducted in 2020 and 2021 at the Teaching and Research Farm of the Federal University of Agriculture Abeokuta, Ogun State, Nigeria to evaluate the effect of biochar application under different weeding regimes on growth and yield of okra. Treatments were laid out in split- plot in a randomized complete block design with three replications. Main plot treatments were three levels of biochar namely 0t/ha, 10t/ha and 20t/ha while sub-plots treatments consisted of four weeding regimes (weeding at 3, 6 and 9 WAS, weeding at 3 and 6 WAS, weeding at 3 WAS and weedy check as control). Data collected on growth and yield of okra, and weed parameters were subjected to analysis of variance and treatment means were separated using least significant difference at p < 0.05. Results showed that biochar applied at 20 t/ha increased okra yield by 47.5% compared to the control. Weeding at 3, 6 and 9 WAS gave the highest okra yield. Uncontrolled weed infestation throughout crop growth resulted in 87.3% yield reduction in okra. It is concluded that weed suppression , growth and yield of okra can be enhanced by the application of biochar at 20t/ha and weeding at 3, 6 and 9 WAS hence recommended.

Keywords: biochar, okra, weeding, weed competition

Procedia PDF Downloads 68

Authors: Hoda Mahgoub, Abeer Hanafy

Abstract:

Linagliptin (LNG) belongs to dipeptidyl-peptidase-4 (DPP-4) inhibitor class. DPP-4 inhibitors represent a new therapeutic approach for the treatment of type 2 diabetes in adults. The aim of this work was to develop and validate an accurate and reproducible HPLC method for the determination of LNG with high sensitivity in rat plasma. The method involved separation of both LNG and pindolol (internal standard) at ambient temperature on a Zorbax Eclipse XDB C18 column and a mobile phase composed of 75% methanol: 25% formic acid 0.1% pH 4.1 at a flow rate of 1.0 mL.min-1. UV detection was performed at 254nm. The method was validated in compliance with ICH guidelines and found to be linear in the range of 5–1000ng.mL-1. The limit of quantification (LOQ) was found to be 5ng.mL-1 based on 100µL of plasma. The variations for intra- and inter-assay precision were less than 10%, and the accuracy values were ranged between 93.3% and 102.5%. The extraction recovery (R%) was more than 83%. The method involved a single extraction step of a very small plasma volume (100µL). The assay was successfully applied to an in-vivo pharmacokinetic study of LNG in rats that were administered a single oral dose of 10mg.kg-1 LNG. The maximum concentration (Cmax) was found to be 927.5 ± 23.9ng.mL-1. The area under the plasma concentration-time curve (AUC0-72) was 18285.02 ± 605.76h.ng.mL-1. In conclusion, the good accuracy and low LOQ of the bioanalytical HPLC method were suitable for monitoring the full pharmacokinetic profile of LNG in rats. The main advantages of the method were the sensitivity, small sample volume, single-step extraction procedure and the short time of analysis.

Keywords: HPLC, linagliptin, pharmacokinetic study, rat plasma

Procedia PDF Downloads 242

Authors: Jocelyn Solomons, Kraak

Abstract:

Rhythmic movement, also referred to as “dance”, involves the execution of different motor skills as well as the integration and sequencing of actions between limbs, timing and spatial precision. The aim of this study was therefore to investigate and compare the effect of a 16-week rhythmic movement intervention on flexibility, dynamic balance, agility, power and local muscular endurance of academy rugby players in the Western Cape, according to positional groups. Players (N ¼ 54) (age 18.66 0.81 years; height 1.76 0.69 cm; weight 76.77 10.69 kg), were randomly divided into a treatment-control [TCA] (n ¼ 28) and a control-treatment [CTB] (n ¼ 26) group. In this crossover experimental design, the interaction effect of the treatment order and the treatment time between the TCA and CTB group, was determined. Results indicated a statistically significant improvement (p < 0.05) in agility2 (p ¼ 0.06), power2 (p ¼ 0.05), local muscular endurance1 (p ¼ 0.01) & 3 (p ¼ 0.01) and dynamic balance (p < 0.01). Likewise, forwards and backs also showed statistically significant improvements (p < 0.05) per positional groups. Therefore, a rhythmic movement intervention has the potential to improve rugby-specific bio-motor skills and furthermore, improve positional specific skills should it be designed with positional groups in mind. Future studies should investigate, not only the effect of rhythmic movement on improving specific rugby bio-motor skills, but the potential of its application as an alternative training method during off- season (or detraining phases) or as a recovery method.

Keywords: agility, dance, dynamic balance, flexibility, local muscular endurance, power, training

Procedia PDF Downloads 65

Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

Abstract:

This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

Procedia PDF Downloads 29

Authors: Olusegun Raphael Adeyemi, Samuel Oluwaseun Osunleti, Abiddin Adekunle Bashiruddin

Abstract:

Field trials were conducted in 2020 and 2021 at the Teaching and Research Farm of the Federal University of Agriculture Abeokuta, Ogun State, Nigeria, to evaluate the effect of biochar application under different weeding regimes on the growth and yield of okra. Treatments were laid out in a split- plot in a randomized complete block design with three replications. Main plot treatments were three levels of biochar, namely 0t/ha, 10t/ha and 20t/ha while sub-plot treatments consisted of four weeding regimes (weeding at 3, 6 and 9 WAS, weeding at 3 and 6 WAS, weeding at 3 WAS and weedy check as control). Data collected on growth and yield of okra and weed parameters were subjected to analysis of variance, and treatment means were separated using the least significant difference at p < 0.05. Results showed that biochar applied at 20 t/ha increased okra yield by 47.5% compared to the control. Weeding at 3, 6 and 9 WAS gave the highest okra yield. Uncontrolled weed infestation throughout crop growth resulted in an 87.3% yield reduction in okra. It is concluded that weed suppression, growth and yield of okra can be enhanced by the application of biochar at 20t/ha and weeding at 3, 6 and 9 WAS hence recommended.

Keywords: biochar, okra, weeding, weed competition, yield

Procedia PDF Downloads 68

Authors: Yendo Hu, Xu-Yu Wu, Dylan Oh

Abstract:

GPS-Denied drones open the possibility of indoor applications, including dynamic arial surveillance, inspection, safety enforcement, and discovery. Indoor swarming further enhances these applications in accuracy, robustness, operational time, and coverage. For micro-drones, power management becomes a critical issue, given the battery payload restriction. This paper proposes an application enabling battery replacement solution that extends the micro-drone active phase without human intervention. First, a framework to quantify the effectiveness of a power management solution for a drone fleet is proposed. The operation-to-non-operation ratio, ONR, gives one a quantitative benchmark to measure the effectiveness of a power management solution. Second, a survey was carried out to evaluate the ONR performance for the various solutions. Third, through analysis, this paper proposes a solution tailored to the indoor micro-drone, suitable for swarming applications. The proposed automated battery replacement solution, along with a modified micro-drone architecture, was implemented along with the associated micro-drone. Fourth, the system was tested and compared with the various solutions within the industry. Results show that the proposed solution achieves an ONR value of 31, which is a 1-fold improvement of the best alternative option. The cost analysis shows a manufacturing cost of $25, which makes this approach viable for cost-sensitive markets (e.g., consumer). Further challenges remain in the area of drone design for automated battery replacement, landing pad/drone production, high-precision landing control, and ONR improvements.

Keywords: micro-drone, battery swap, battery replacement, battery recharge, landing pad, power management

Procedia PDF Downloads 128

Authors: Nalika S. Rajapaksha, James Airton, Amina Aboobakar, Nick Chappell, Andy Dyer

Abstract:

Nutrient pollution and their impact on water quality is a key concern in England. Many water quality issues originate from multiple sources of pollution spread across the catchment. The river water quality in England has improved since 1990s and wastewater effluent discharges into rivers now contain less phosphorus than in the past. However, excess phosphorus is still recognised as the prevailing issue for rivers failing Water Framework Directive (WFD) good ecological status. To achieve WFD Phosphorus objectives, Wastewater Treatment Works (WwTW) permit limits are becoming increasingly stringent. Nevertheless, in some rural catchments, the apportionment of Phosphorus pollution can be greater from agricultural runoff and other sources such as septic tanks. Therefore, the challenge of meeting the requirements of watercourses to deliver WFD objectives often goes beyond water company activities, providing significant opportunities to co-deliver activities in wider catchments to reduce nutrient load at source. The aim of this study was to apply the United Utilities' Catchment Systems Thinking (CaST) strategy and pilot an innovative permitting approach - Catchment Nutrient Balancing (CNB) in a rural catchment in Cumbria (the River Petteril) in collaboration with the regulator and others to achieve WFD objectives and multiple benefits. The study area is mainly agricultural land, predominantly livestock farms. The local ecology is impacted by significant nutrient inputs which require intervention to meet WFD obligations. There are a range of Phosphorus inputs into the river, including discharges from wastewater assets but also significantly from agricultural contributions. Solely focusing on the WwTW discharges would not have resolved the problem hence in order to address this issue effectively, a CNB trial was initiated at a small WwTW, targeting the removal of a total of 150kg of Phosphorus load, of which 13kg were to be reduced through the use of catchment interventions. Various catchment interventions were implemented across selected farms in the upstream of the catchment and also an innovative polonite reactive filter media was implemented at the WwTW as an alternative to traditional Phosphorus treatment methods. During the 3 years of this trial, the impact of the interventions in the catchment and the treatment works were monitored. In 2020 and 2022, it respectively achieved a 69% and 63% reduction in the phosphorus level in the catchment against the initial reduction target of 9%. Phosphorus treatment at the WwTW had a significant impact on overall load reduction. The wider catchment impact, however, was seven times greater than the initial target when wider catchment interventions were also established. While it is unlikely that all the Phosphorus load reduction was delivered exclusively from the interventions implemented though this project, this trial evidenced the enhanced benefits that can be achieved with an integrated approach, that engages all sources of pollution within the catchment - rather than focusing on a one-size-fits-all solution. Primarily, the CNB approach and the act of collaboratively engaging others, particularly the agriculture sector is likely to yield improved farm and land management performance and better compliance, which can lead to improved river quality as well as wider benefits.

Keywords: agriculture, catchment nutrient balancing, phosphorus pollution, water quality, wastewater

Procedia PDF Downloads 72

Authors: Adinda Syifa Azhari, Eleonora Agustine, Dini Fitriani

Abstract:

This measurement has been done to analyze the impact of industrial pollution on the environment. Our research is to indicate the soil which has contained some pollution by industrial activity around the area, especially in Sumedang, West Java. The parameter phsyics such as total dissolved solid, volumetric water content, electrical conductivity bulk and FD have shown that the soil has polluted and measured by Decagon EM 50. Decagon EM 50 is one of the geophysical environment instrumentation that is used to interpret the soil condition. This experiment has given a result of these parameter physics, these are: Volumetric water content (m³/m³) = 0,154 – 0,384; Electrical Conductivity Bulk (dS/m) = 0,29 – 1,11 ; Dielectric Permittivity (DP) = 77,636 – 78, 339.Based on these data, we have got the conclusion that the area has, in fact, been contaminated by dangerous materials. VWC is parameter physics that has shown water in soil. The data show the pollution of the soil at the place, of which the specifications are PH, Total Dissolved Solid (TDS), Electrical Conductivity (EC) bigger (>>) and Frequency Dependent (FD) smaller (<<); that means the soil is alkali with big grain and has high salt concentration.

Keywords: Decagon EM 50, electrical conductivity, industrial textiles, land, pollution

Procedia PDF Downloads 384

Authors: Anil P. Dewani, Ravindra L. Bakal, Anil V. Chandewar

Abstract:

Present work demonstrates the applicability of high-performance liquid chromatography (HPLC) with UV detection for the determination of malondialdehyde as malondialdehyde-thiobarbituric acid complex (MDA-TBA) in-vivo in rats. The HPLC-UV method for MDA-TBA was achieved by isocratic mode on a reverse-phase C18 column (250mm×4.6mm) at a flow rate of 1.0mLmin−1 followed by UV detection at 278 nm. The chromatographic conditions were optimized by varying the concentration and pH followed by changes in percentage of organic phase optimal mobile phase consisted of mixture of water (0.2% Triethylamine pH adjusted to 2.3 by ortho-phosphoric acid) and acetonitrile in ratio (80:20 % v/v). The retention time of MDA-TBA complex was 3.7 min. The developed method was sensitive as limit of detection and quantification (LOD and LOQ) for MDA-TBA complex were (standard deviation and slope of calibration curve) 110 ng/ml and 363 ng/ml respectively. The method was linear for MDA spiked in plasma and subjected to derivatization at concentrations ranging from 100 to 1000 ng/ml. The precision of developed method measured in terms of relative standard deviations for intra-day and inter-day studies was 1.6–5.0% and 1.9–3.6% respectively. The HPLC method was applied for monitoring MDA levels in rats subjected to chronic treatment of ciprofloxacin (CFL) (5mg/kg/day) for 21 days. Results were compared by findings in control group rats. Mean peak areas of both study groups was subjected for statistical treatment to unpaired student t-test to find p-values. The p value was < 0.001 indicating significant results and suggesting increased MDA levels in rats subjected to chronic treatment of CFL of 21 days.

Keywords: MDA, TBA, ciprofloxacin, HPLC-UV

Procedia PDF Downloads 329

Authors: Kimberly Samaha

Abstract:

In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

Procedia PDF Downloads 162

Authors: Evangelos Koumparoudis

Abstract:

The definition of death is a deep philosophical question, and no single meaning can be ascribed to it. This essay focuses on the ontological, epistemological, and ethical aspects of death and dying in view of technological progress in information technology and biomedicine. It starts with the ad hoc 1968 Harvard committee that proposed that the criterion for the definition of death be irreversible coma and then refers to the debate over the whole brain death formula, emphasizing the integrated function of the organism and higher brain formula, taking consciousness and personality as essential human characteristics. It follows with the contribution of information technology in personalized and precision medicine and anti-aging measures aimed at life prolongation. It also touches on the possibility of the creation of human-machine hybrids and how this raises ontological and ethical issues that concern the “cyborgization” of human beings and the conception of the organism and personhood based on a post/transhumanist essence, and, furthermore, if sentient AI capable of autonomous decision-making that might even surpass human intelligence (singularity, superintelligence) deserves moral or legal personhood. Finally, there is the question as to whether death and dying should be redefined at a transcendent level, which is reinforced by already-existing technologies of “virtual after-” life and the possibility of uploading human minds. In the last section, I refer to the current (and future) applications of nanomedicine in diagnostics, therapeutics, implants, and tissue engineering as well as the aspiration to “immortality” by cryonics. The definition of death is reformulated since age and disease elimination may be realized, and the criterion of irreversibility may be challenged.

Keywords: death, posthumanism, infomedicine, nanomedicine, cryonics

Procedia PDF Downloads 76

Authors: Sandesh Achar

Abstract:

Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

Procedia PDF Downloads 112

Authors: Ali Ashraf Hamedi Oghul Beyk

Abstract:

The main objective of the study is to determine the factors which influence the acceptance or rejection of rural livestock insurance in Garmsar. The research method is descriptive one. There are two groups of research populations: 1467 cases in acceptance group and 7000 cases in rejection group. The sample population is 320 cases among 8467 ones. Data collection instrument is questionnaire. The validity of the questionnaire was measured by faculty members and other agriculture experts and also reliability of it determined through Cronbach alpha which was %83. Correlation between acceptance and rejection of investigated population. According to the findings of the research, between educational level, basic income from farm-related communication channels, contacts of experts and acceptance and rejection of livestock insurance at %5 & the mortality rate, loan awareness of the objectives of the livestock insurance benefits %1 there is a meaningful relationship. Mann-Whitney test shows the different educational levels, different awareness and interest to livestock insurance between the two groups. Besides, the T-test shows the livestock losses rate in two groups.

Keywords: insurance, livestock, Garmsar, Semnan

Procedia PDF Downloads 356

Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

Abstract:

The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

Procedia PDF Downloads 52

Authors: Saeed Yazdani, Shahrbanoo Bagheri, Sepideh Nikravesh

Abstract:

Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting on farmer’s decision on the application of water saving technologies with emphasize on crop price variation and water sources. A Logit model was employed to examine the impact of different variables on use of water saving technology. The required data gathered from a sample of 204 farmers in the year 2012. The results indicate that different variables such as crop price variability, water supply source, high-value crops, farm size, income, education, membership in cooperatives have a positive effect and variables such as age and number of plots have a negative impact on the probability of adopting modern water saving technologies.

Keywords: irrigation, water, water saving technology, scarcity

Procedia PDF Downloads 228

Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

Abstract:

Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

Procedia PDF Downloads 171

Authors: Farzaneh Sarbandi Farahani

Abstract:

Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes are of great importance, and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation, which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from groundwater and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of a scenario-based design and optimal strategy selection. For optimal strategy selection, a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.

Keywords: drought simulation, Mead lake, entity component system programming, deep reinforcement learning

Procedia PDF Downloads 95

Authors: Gule Teri

Abstract:

The effective validation of analytical methods forms a crucial component of pharmaceutical manufacturing. However, traditional validation techniques can occasionally fail to fully account for inherent variations within datasets, which may result in inconsistent outcomes. This deficiency in validation accuracy is particularly noticeable when quantifying low concentrations of active pharmaceutical ingredients (APIs), excipients, or impurities, introducing a risk to the reliability of the results and, subsequently, the safety and effectiveness of the pharmaceutical products. In response to this challenge, we introduce an enhanced, tolerance-based Design of Experiments (DoE) approach for the validation of analytical methods. This approach distinctly measures variability with reference to tolerance or design margins, enhancing the precision and trustworthiness of the results. This method provides a systematic, statistically grounded validation technique that improves the truthfulness of results. It offers an essential tool for industry professionals aiming to guarantee the accuracy of their measurements, particularly for low-concentration components. By incorporating this innovative method, pharmaceutical manufacturers can substantially advance their validation processes, subsequently improving the overall quality and safety of their products. This paper delves deeper into the development, application, and advantages of this tolerance-based DoE approach and demonstrates its effectiveness using High-Performance Liquid Chromatography (HPLC) data for verification. This paper also discusses the potential implications and future applications of this method in enhancing pharmaceutical manufacturing practices and outcomes.

Keywords: tolerance-based design, design of experiments, analytical method validation, quality control, biopharmaceutical manufacturing

Procedia PDF Downloads 85

Authors: Vasanth C. Shunmugasamy, Bilal Mansoor

Abstract:

Magnesium alloys are increasingly being considered for structural systems across different industrial sectors, including precision components of biomedical devices, owing to their high specific strength, stiffness and biodegradability. However, Mg alloys exhibit a high corrosion rate that restricts their application as a biomaterial. For safe use as biomaterial, it is essential to control their corrosion rates. Mg alloy corrosion is influenced by several factors, such as grain size, precipitates and texture. In Mg alloys, microgalvanic coupling between the α-Mg matrix and secondary precipitates can exist, which results in an increased corrosion rate. The present research addresses this challenge by engineering the microstructure of a biodegradable Mg–Zn–RE–Zr alloy by friction stir processing (FSP), a severe plastic deformation process. The FSP-processed Mg alloys showed improved corrosion resistance and mechanical properties. FSPed Mg alloy showed refined grains, a strong basal texture and broken and uniformly distributed secondary precipitates in the stir zone. Mg, alloy base material, exposed to In vitro corrosion medium showed micro galvanic coupling between precipitate and matrix, resulting in the unstable passive layer. However, FS processed alloy showed uniform corrosion owing to stable surface film formation. The stable surface film is attributed to refined grains, preferred texture and distribution of precipitates. The research results show promising potential for Mg alloy to be developed as a biomaterial.

Keywords: biomaterials, severe plastic deformation, magnesium alloys, corrosion

Procedia PDF Downloads 47

Authors: Margarida Soares, Zlatina Genisheva, Lucas Nascimento, André Ribeiro, Tiago Miranda, Eduardo Pereira, Joana Carvalho

Abstract:

In the current global context, we face a significant challenge: the rapid population increase combined with the pressing need for sustainable management of agro-industrial waste. Beyond understanding how population growth impacts waste generation, it is essential to first identify the primary types of waste produced and the countries responsible to guide targeted actions. This study presents key statistical data on waste production from the agriculture, forestry, and fishing sectors across the European Union, alongside information on the agricultural areas dedicated to crop production in each European Union country. These insights will form the basis for future research into waste production by crop type and country to improve waste management practices and promote recovery methods that are vital for environmental sustainability. The agricultural sector must stay at the forefront of scientific and technological advancements to meet climate change challenges, protect the environment, and ensure food and health security. The study's findings indicate that population growth significantly increases pressure on natural resources, leading to a rise in agro-industrial waste production. EUROSTAT data shows that, in 2020, the agriculture, forestry, and fishing sectors produced over 21 million tons of waste. Spain emerged as the largest producer, contributing nearly 30% of the EU's total waste in these sectors. Furthermore, five countries—Spain, the Netherlands, France, Sweden, and Germany—were responsible for producing more than two-thirds of the waste from these sectors. Regarding agricultural land use, the data for 2020 revealed that around two-thirds of the total agricultural area was concentrated in six countries: France, Spain, Germany, Poland, Romania, and Italy. Regarding waste production per capita, the Netherlands had the highest figures in the EU for 2020. The data presented in this study highlights the urgent need for action in managing agricultural waste in the EU. As population growth continues to drive up demand for agricultural products, waste generation will inevitably rise unless significant changes are made in managing of agro-industrial waste. The countries must lead the way in adopting technological waste management strategies that focus on reducing, reusing, and recycling waste to benefit both the environment and society. Equally important is the need to promote collaborative efforts between governments, industries, and research institutions to develop and implement technologies that transform waste into valuable resources. The insights from this study are critical for informing future strategies to improve the management and valorization of waste from the agro-industrial sector. One of the most promising approaches is adopting circular economy principles to create closed-loop systems that minimize environmental impacts. By rethinking waste as a valuable resource rather than a by-product, agricultural industries can contribute to more sustainable practices that support both environmental health and economic growth.

Keywords: agricultural area, agricultural waste, circular economy, environmental challenges, population growth

Procedia PDF Downloads 21

Authors: Nubwimana Rachel, Mugabowindekwe Maurice

Abstract:

Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

Procedia PDF Downloads 82

Authors: Aminu Mansur

Abstract:

A comparison of soil temperature at (5 and 30 cm) depths at a research site over the period (1976-2008) was analyzed. Based on the statistical analysis of the database of (12,045) days of individual soil temperature measurements in sandy-loam of the (salwick series) soils, the mean soil temperature revealed a statistically significant increase of about -1.1 to 10.9°C at 5 cm depth in 1976 compared to 2008. Similarly, soil temperature at 30 cm depth increased by -0.1 to 2.1°C in 2008 compared to 1976. Although, rapid increase in soil temperature at all depths was observed during that period, but a thorough assessment of these conditions suggested that the soil temperature at 5 cm depth are progressively increasing over time. A typical example of those increases in soil temperature was provided for agriculture where Miscanthus (elephant) plant that grows within the study area is adversely affected by the mean soil temperature increase. The study concluded that these observations contribute to the growing mass of evidence of global warming and knowledge on secular trends. Therefore, there was statistically significant increase in soil temperature at Compton Experimental Site between 1976-2008.

Keywords: soil temperature, warming trend, environment science, climate and atmospheric sciences

Procedia PDF Downloads 303

Authors: Ishita Singh

Abstract:

Social-dimension of Climate Change is no longer peripheral to Science, Technology and Innovation (STI). Indeed, STI is being mobilized to address small farmers’ vulnerability and adaptation to Climate Change. The experiences from the cold desert of Leh (Ladakh) in North-West Himalaya illustrate the potential of STI to address the challenges of Climate Change and the needs of small farmers through the use of Artificial Glacier Techniques. Small farmers have a unique technique of water harvesting to augment irrigation, called “Artificial Glaciers” - an intricate network of water channels and dams along the upper slope of a valley that are located closer to villages and at lower altitudes than natural glaciers. It starts to melt much earlier and supplements additional irrigation to small farmers’ improving their livelihoods. Therefore, the issue of vulnerability, adaptive capacity and adaptation strategy needs to be analyzed in a local context and the communities as well as regions where people live. Leh (Ladakh) in North-West Himalaya provides a Case Study for exploring the ways in which adaptation to Climate Change is taking place at a community scale using Artificial Glacier Technology. With the above backdrop, an attempt has been made to analyze the rural poor households' vulnerability and adaptation practices to Climate Change using this technology, thereby drawing lessons on vulnerability-livelihood interactions in the cold desert of Leh (Ladakh) in North-West Himalaya, India. The study is based on primary data and information collected from 675 households confined to 27 villages of Leh (Ladakh) in North-West Himalaya, India. It reveals that 61.18% of the population is driving livelihoods from agriculture and allied activities. With increased irrigation potential due to the use of Artificial Glaciers, food security has been assured to 77.56% of households and health vulnerability has been reduced in 31% of households. Seasonal migration as a livelihood diversification mechanism has declined in nearly two-thirds of households, thereby improving livelihood strategies. Use of tactical adaptations by small farmers in response to persistent droughts, such as selling livestock, expanding agriculture lands, and use of relief cash and foods, have declined to 20.44%, 24.74% and 63% of households. However, these measures are unsustainable on a long-term basis. The role of policymakers and societal stakeholders becomes important in this context. To address livelihood challenges, the role of technology is critical in a multidisciplinary approach involving multilateral collaboration among different stakeholders. The presence of social entrepreneurs and new actors on the adaptation scene is necessary to bring forth adaptation measures. Better linkage between Science and Technology policies, together with other policies, should be encouraged. Better health care, access to safe drinking water, better sanitary conditions, and improved standards of education and infrastructure are effective measures to enhance a community’s adaptive capacity. However, social transfers for supporting climate adaptive capacity require significant amounts of additional investment. Developing institutional mechanisms for specific adaptation interventions can be one of the most effective ways of implementing a plan to enhance adaptation and build resilience.

Keywords: climate change, adaptation, livelihood, stakeholders

Procedia PDF Downloads 72

Authors: Seyedeh Fatemeh Nabavi, Hamid Dalir, Anooshiravan Farshidianfar

Abstract:

Laser welding is pivotal in modern manufacturing, offering unmatched precision, speed, and efficiency. Its versatility in minimizing heat-affected zones, seamlessly joining dissimilar materials, and working with various metals makes it indispensable for crafting intricate automotive components. Integration into automated systems ensures consistent delivery of high-quality welds, thereby enhancing overall production efficiency. Noteworthy are the safety benefits of laser welding, including reduced fumes and consumable materials, which align with industry standards and environmental sustainability goals. As the automotive sector increasingly demands advanced materials and stringent safety and quality standards, laser welding emerges as a cornerstone technology. A comprehensive model encompassing thermal dynamic and characteristics models accurately predicts geometrical, metallurgical, and mechanical aspects of the laser beam welding process. Notably, Model 2 showcases exceptional accuracy, achieving remarkably low error rates in predicting primary and secondary dendrite arm spacing (PDAS and SDAS). These findings underscore the model's reliability and effectiveness, providing invaluable insights and predictive capabilities crucial for optimizing welding processes and ensuring superior productivity, efficiency, and quality in the automotive industry.

Keywords: laser welding process, geometrical characteristics, mechanical characteristics, metallurgical characteristics, comprehensive model, thermal dynamic

Procedia PDF Downloads 53

Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

Abstract:

The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

Procedia PDF Downloads 336

Authors: Jihène Khalifa

Abstract:

This study analyzed the relationships between Tunisia’s economic growth, food security, agricultural productivity, and climate change using the ARDL model for the period from 1990 to 2022. The ARDL model reveals a positive correlation between economic growth and lagged agricultural productivity. Additionally, the vector autoregressive (VAR) model highlights the beneficial impact of lagged agricultural productivity on economic growth and the negative effect of rainfall on economic growth. Granger causality analysis identifies unidirectional relationships from economic growth to agricultural productivity, crop production, food security, and temperature variations, as well as from temperature variations to crop production. Furthermore, a bidirectional causality is established between crop production and food security. The study underscores the impact of climate change on crop production and suggests the need for adaptive strategies to mitigate these climate effects.

Keywords: economic growth, climate change, agriculture, ARDL, Granger causality, VAR

Procedia PDF Downloads 38

Authors: Sven Ratković

Abstract:

The survey of public attitudes and knowledge was conducted as part of the Dinara back to LIFE project during June and July 2020. The aim of the research was to collect public opinions and knowledge on the topics of the biodiversity of Dinara, perception of tourist potential, sustainable development, and acceptance of the project. The research was conducted using the survey method in the cities of Sinj, Knin, Vrlika, and Trilj, and the municipalities of Hrvace, Otok, Kijevo, and Civljane, where a total of 404 people were surveyed. The respondents perceive the cultural and recreational potential of Dinara and recognize it as a potential for agriculture and tourism. According to respondents, the biological diversity of Dinara is most affected by fires and human activity. When it comes to nature protection, the majority of respondents don’t trust local self-government units and relevant ministries. The obtained results indicate the need for informing and educating the community, and they serve to adjust the project activities and better guide the touristic development of the project area. The examination will be repeated in the last project year (2023).

Keywords: protected area tourism, Dinara Nature Park, dry grasslands, touristic infrastructure

Procedia PDF Downloads 104

Authors: Tovondahiniriko Fanjirindratovo, Olga Ramiarinjanahary, Paulisimone Rasoavonjy

Abstract:

The sunshine duration, which is the sum of all the moments when the solar beam radiation is up to a minimal value, is an important parameter for climatology, tourism, agriculture and solar energy. Its measure is usually given by a pyrheliometer installed on a two-axis solar tracker. Due to the high cost of this device and the availability of global radiation on a horizontal surface, on the other hand, several studies have been done to make a correlation between global radiation and sunshine duration. Most of these studies are fitted for the northern hemisphere using a pyrheliometric database. The aim of the present work is to list and assess all the existing methods and apply them to Reunion Island, a tropical region in the southern hemisphere. Using a database of ten years, global, diffuse and beam radiation for a horizontal surface are employed in order to evaluate the uncertainty of existing algorithms for a tropical region. The methodology is based on indirect comparison because the solar beam radiation is not measured but calculated by the beam radiation on a horizontal surface and the sun elevation angle.

Keywords: Carpentras method, data fitting, global radiation, sunshine duration, Slob and Monna algorithm, step algorithm

Procedia PDF Downloads 130