Search results for: yield curve
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3344

Search results for: yield curve

3194 Comparative Study of the Effect of Three Fungicides: Tilt and Artea Amistarxtra about Growing Wheat, Hard, and Soft and Their Impact on Grain Yield and Its Components in the Semi-Arid Zone of Setif

Authors: Cheniti Khalissa, Dekhili Mohamed

Abstract:

Several fungal diseases may infect hard and soft wheat, which directly affect the yield and thus the economy of the homeland. So, a treatment fungicide is one of means of diseases control. In this context, we studied two varieties of wheat; Waha for soft wheat and Hidhab for hard wheat, at the level of the Technical Institute of crops (ITGC) in the wilaya of Setif under semi-arid conditions. This study consists of a successive application of three fungicides (Tilt, Artea, and Armistarxtra) according to three treatments (T1, T2, and T3) in addition to the witness (T0) at different stages of plant development (respectively, Montaison, earing and after flowering) whose purpose is to test and determine the effectiveness of these products used sequentially. The study showed good efficacy when we use the sum of these pesticides The comparison between these different treatments indicates that the T3 treatment reduced yield losses significantly; which is evident in the main yield components such as fertility, grain yield and weight of 1000 grains. The various components of yield and final yield are all parameters to be taken into account in such a study. In general, the fungal treatment is an effective way of improving profitability. In general, the fungal treatment is an effective way of improving profitability and positioning interventions in time is one of the requirements for an appreciable efficiency.

Keywords: hard wheat, soft wheat, diseases, fungicide treatment, fertility, 1000-grain weight, semi-arid zone

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3193 Numerical Analysis Of Stainless Steel Beam To Column Joints With Bolted Flush End Plates

Authors: Takwiir Tahriim Khan, Tausif Khalid, Mohammad Redwan Ahamed, Md Soebur Rahman

Abstract:

The mutual connection in joints has a significant impact on the safe and cost-effective design of steel structures. Generally, the end plates are welded at the end of the beam and columns are bolted with the end plates. Thus, the moment will be transferred at the interface, which is a critical segment at the connection. 3-D Finite Element Models (FEM) has been developed using ABAQUS 2017 software to predict the yield capacity of the end plate connections. The parameters used in this study are the depth, width, and thickness of the end plate, dimensions of the bolt, sectional and material properties of beams and columns. The influence width, depth, and thicknesses of the end plate connection on yield capacity were investigated through parametric studies. The results showed that, for increasing plate thickness from 0.3 inch to 0.8 inch by an increment of 0.1 inch the yield capacity increased by 2.85% on average, for decreasing the end plate depth from 13 inch to 11 inch the yield capacity increased by 25.4 %, and for decreasing the end plate width from 6.5 inch to 5.75 inch the yield capacity increased by 35.4%. Variation in yield capacity was also found by changing the beam and column section. Besides, the numerical results showed a good agreement with published experimental literature with an average variation of less than 8.3 % in yield capacity. So the study allows for a more effective combination of beam, column, and end plate dimensions.

Keywords: steel beam-column joints, finite element analysis, yield moment capacity, parametric study, ABAQUS, bolted joints, flush end plates, moment vs rotation curves

Procedia PDF Downloads 83
3192 Fingerprint Image Encryption Using a 2D Chaotic Map and Elliptic Curve Cryptography

Authors: D. M. S. Bandara, Yunqi Lei, Ye Luo

Abstract:

Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances.

Keywords: arnold cat map, biometric encryption, block cipher, elliptic curve cryptography, fingerprint encryption, Koblitz’s encoding

Procedia PDF Downloads 178
3191 Comparison of Sediment Rating Curve and Artificial Neural Network in Simulation of Suspended Sediment Load

Authors: Ahmad Saadiq, Neeraj Sahu

Abstract:

Sediment, which comprises of solid particles of mineral and organic material are transported by water. In river systems, the amount of sediment transported is controlled by both the transport capacity of the flow and the supply of sediment. The transport of sediment in rivers is important with respect to pollution, channel navigability, reservoir ageing, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. The sediment load transported in a river is a very complex hydrological phenomenon. Hence, sediment transport has attracted the attention of engineers from various aspects, and different methods have been used for its estimation. So, several experimental equations have been submitted by experts. Though the results of these methods have considerable differences with each other and with experimental observations, because the sediment measures have some limits, these equations can be used in estimating sediment load. In this present study, two black box models namely, an SRC (Sediment Rating Curve) and ANN (Artificial Neural Network) are used in the simulation of the suspended sediment load. The study is carried out for Seonath subbasin. Seonath is the biggest tributary of Mahanadi river, and it carries a vast amount of sediment. The data is collected for Jondhra hydrological observation station from India-WRIS (Water Resources Information System) and IMD (Indian Meteorological Department). These data include the discharge, sediment concentration and rainfall for 10 years. In this study, sediment load is estimated from the input parameters (discharge, rainfall, and past sediment) in various combination of simulations. A sediment rating curve used the water discharge to estimate the sediment concentration. This estimated sediment concentration is converted to sediment load. Likewise, for the application of these data in ANN, they are normalised first and then fed in various combinations to yield the sediment load. RMSE (root mean square error) and R² (coefficient of determination) between the observed load and the estimated load are used as evaluating criteria. For an ideal model, RMSE is zero and R² is 1. However, as the models used in this study are black box models, they don’t carry the exact representation of the factors which causes sedimentation. Hence, a model which gives the lowest RMSE and highest R² is the best model in this study. The lowest values of RMSE (based on normalised data) for sediment rating curve, feed forward back propagation, cascade forward back propagation and neural network fitting are 0.043425, 0.00679781, 0.0050089 and 0.0043727 respectively. The corresponding values of R² are 0.8258, 0.9941, 0.9968 and 0.9976. This implies that a neural network fitting model is superior to the other models used in this study. However, a drawback of neural network fitting is that it produces few negative estimates, which is not at all tolerable in the field of estimation of sediment load, and hence this model can’t be crowned as the best model among others, based on this study. A cascade forward back propagation produces results much closer to a neural network model and hence this model is the best model based on the present study.

Keywords: artificial neural network, Root mean squared error, sediment, sediment rating curve

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3190 Modeling and Optimization of Algae Oil Extraction Using Response Surface Methodology

Authors: I. F. Ejim, F. L. Kamen

Abstract:

Aims: In this experiment, algae oil extraction with a combination of n-hexane and ethanol was investigated. The effects of extraction solvent concentration, extraction time and temperature on the yield and quality of oil were studied using Response Surface Methodology (RSM). Experimental Design: Optimization of algae oil extraction using Box-Behnken design was used to generate 17 experimental runs in a three-factor-three-level design where oil yield, specific gravity, acid value and saponification value were evaluated as the response. Result: In this result, a minimum oil yield of 17% and maximum of 44% was realized. The optimum values for yield, specific gravity, acid value and saponification value from the overlay plot were 40.79%, 0.8788, 0.5056 mg KOH/g and 180.78 mg KOH/g respectively with desirability of 0.801. The maximum point prediction was yield 40.79% at solvent concentration 66.68 n-hexane, temperature of 40.0°C and extraction time of 4 hrs. Analysis of Variance (ANOVA) results showed that the linear and quadratic coefficient were all significant at p<0.05. The experiment was validated and results obtained were with the predicted values. Conclusion: Algae oil extraction was successfully optimized using RSM and its quality indicated it is suitable for many industrial uses.

Keywords: algae oil, response surface methodology, optimization, Box-Bohnken, extraction

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3189 Effect of Marginal Quality Groundwater on Yield of Cotton Crop and Soil Salinity Status

Authors: A. L. Qureshi, A. A. Mahessar, R. K. Dashti, S. M. Yasin

Abstract:

In this paper, effect of marginal quality groundwater on yield of cotton crop and soil salinity was studied. In this connection, three irrigation treatments each with four replications were applied. These treatments were use of canal water, use of marginal quality groundwater from tube well, and conjunctive use by mixing with the ratio of 1:1 of canal water and marginal quality tubewell water. Water was applied to the crop cultivated in Kharif season 2011; its quantity has been measured using cut-throat flume. Total 11 watering each of 50 mm depth have been applied from 20th April to 20th July, 2011. Further, irrigations were stopped from last week of July, 2011 due to monsoon rainfall. Maximum crop yield (seed cotton) was observed under T1 which was 1,516.8 kg/ha followed by T3 (mixed canal and tube well water) having 1009 kg/ha and 709 kg/ha for T2 i.e. marginal quality groundwater. This concludes that crop yield in T2 and T3 with in comparison to T1was reduced by about 53 and 30% respectively. It has been observed that yield of cotton crop is below potential limit for three treatments due to unexpected rainfall at the time of full flowering season; thus the yield was adversely affected. However, salt deposition in soil profiles was not observed that is due to leaching effect of heavy rainfall occurred during monsoon season.

Keywords: conjunctive use, cotton crop, groundwater, soil salinity status, water use efficiency

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3188 Predicting Recessions with Bivariate Dynamic Probit Model: The Czech and German Case

Authors: Lukas Reznak, Maria Reznakova

Abstract:

Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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3187 Bulking Rate of Cassava Genotypes and Their Root Yield Relationship at Guinea Savannah and Forest Transition Agroecological Zone of Nigeria

Authors: Olusegun D. Badewa, E. K. Tsado, A. S. Gana, K. D. Tolorunse, R. U. Okechukwu, P. Iluebbey, S. Ibrahim

Abstract:

Farmers are faced with varying production challenges ranging from unstable weather due to climate change, low yield, malnutrition, cattle invasion, and bush fires that have always affected their livelihood. Research effort must therefore be centered on improving farmers’ livelihood, nutrition, and health by providing early bulking biofortified cassava varieties that could be harvested earlier with reasonable root yield and thereby preventing long stay of the crop on their farmland. This study evaluated cassava genotypes at different harvesting months of 3, 6, 9, and 12 months after planting in order to evaluate their bulking rate at different agroecology of Mokwa and Ubiaja. Data were collected on fresh storage root yield, Harvest index, and Dry matter content. It was shown from the study that traits FSRY, HI, and DM were significant for genotype and months after planting and variable among the genotype while location had no effect on the yield traits. Early bulking genotypes were not high yielding and showed discontinuity at some point across the months. The retrogression in yield performance across months had no effect on the highest yielding. Also, for all the genotypes and across evaluated months, FSRY reduces at 9 MAP due to a reduction in dry matter content during the same month, and the best performing genotype was the genotype IBA90581, followed by IBA120036, IBA130896, and IBA980581 while the least performing was genotype IBA130818.

Keywords: early bulking, dry mater, harvest index, high yielding, root yield

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3186 Winter Wheat Yield Forecasting Using Sentinel-2 Imagery at the Early Stages

Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

Abstract:

Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

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3185 Estimation of Soil Erosion and Sediment Yield for ONG River Using GIS

Authors: Sanjay Kumar Behera, Kanhu Charan Patra

Abstract:

A GIS-based method has been applied for the determination of soil erosion and sediment yield in a small watershed in Ong River basin, Odisha, India. The method involves spatial disintegration of the catchment into homogenous grid cells to capture the catchment heterogeneity. The gross soil erosion in each cell was calculated using Universal Soil Loss Equation (USLE) by carefully determining its various parameters. The concept of sediment delivery ratio is used to route surface erosion from each of the discretized cells to the catchment outlet. The process of sediment delivery from grid cells to the catchment outlet is represented by the topographical characteristics of the cells. The effect of DEM resolution on sediment yield is analyzed using two different resolutions of DEM. The spatial discretization of the catchment and derivation of the physical parameters related to erosion in the cell are performed through GIS techniques.

Keywords: DEM, GIS, sediment delivery ratio, sediment yield, soil erosion

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3184 The Stage and Cause of Regional Industrial Specialization Evolution in China

Authors: Cheng Wen, Zhang Jianhua

Abstract:

This paper aims to probe into the general rules of industry specialization or diversification in a region during its process of economic growth and the specific reasons for the difference of industry specialization development in the eastern, central and western regions of China. It is found in this paper that the changes of regional industry specialization in China, like most of countries in the world, also present the U-shaped curve. Regional industrial structure is diversified in the first place. And when the per capita income exceeds a certain level, distribution of economic resources in this region will be concentrated again. From the perspective of rising total factor productivity and falling of transaction cost in the process of economic development, this paper comes up with a theoretical model to explain the U-shaped curve. Through the empirical test of China's provincial panel data, this paper explains the factors that cause the inequality of the industry specialization development in the eastern, central and western regions of China.

Keywords: u-shaped curve, regional industrial specialization, technological progress, transaction costs

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3183 Investigation of Biochar from Banana Peel

Authors: Anurita Selvarajoo, Svenja Hanson

Abstract:

Growing energy needs and increasing environmental issues are creating awareness for alternative energy which substitutes the non-renewable and polluting fossil fuels. Agricultural wastes are a good feedstock for biochar production through the pyrolysis process. There is potential to generate solid fuel from agricultural wastes, as there are large quantities of agricultural wastes available in Malaysia. This paper outlines the experimental study on the pyrolysis of banana peel. The effects of pyrolysis temperatures on the yield of biochar from the banana peel were investigated. Banana peel was pyrolysed in a horizontal tubular reactor under inert atmosphere by varying the temperatures between 300 and 700 0C. With increasing temperature, the total biochar yield decreased with increased heating value. It was found that the pyrolysis temperature had major effect on the yield of biochar product. It also exerted major influence on the heating value and C,H and O composition. The obtained biochar ranged between 31.9 to 56.7 %wt, at different pyrolysis temperatures. The optimum biochar yield was obtained at 325 0C. Biochar yield obtained at optimum temperature was 47 % wt with a heating value of 25.9 MJ kg-1. The study has been performed in order to demonstrate that agricultural wastes like banana peel are also important source of solid fuel.

Keywords: agricultural Wastes, banana peel, biochar, pyrolysis

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3182 Impact of Brassinosteroid with GA3, CPPU on Yield and Quality of Newly Introduced Grape cv. Italia

Authors: Senthilkumar S, Vijayakumar R M , Soorianathasundaram K, Durga Devi D

Abstract:

A study was conducted to assess the influence of brassinosteroid and other bioregulators as pre-harvest sprays on yield and quality of newly introduced Californian grape cv. Italia. The vines were exposed to standardized pruning level of pruning 50% of the canes to 5-6 bud level for fruiting and 50% of the canes to two bud level for vegetative growth. The influence of brassinosteroid was assessed using BR (1 ppm) alone and in combination with GA3 and CPPU, sprayed at three different stages over the control (water spray) were given as treatments. The results revealed that the bunches treated with Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage i.e., 7-8 mm berry size, recorded the maximum values on yield characters like bunch weight (719.94 g), yield per vine (12.70 kg/vine) and yield per hectare (15.88 t). The berry characters and quality traits were also significantly influenced by the application of bioregulators. The maximum value for all those characters was registered under bunch sprays of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage. The economic feasibility indicated that the treatment combination Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) had registered the maximum benefit cost ratio of 3.13, as compared to 1.89 in control (water spray). Overall, it was observed that a combined bunch spray of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) was adjudged as the best treatment for promoting the crop for better the bunch quality and yield.

Keywords: bioregulators, brassinosteroid, CPPU, GA3, Italia grape cultivar

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3181 Effect of Irrigation Regime and Plant Density on Chickpea (Cicer arietinum L.) Yield in a Semi-Arid Environment

Authors: Atif Naim, Faisal E. Ahmed, Sershen

Abstract:

A field experiment was conducted for two consecutive winter seasons at the Demonstration Farm of the Faculty of Agriculture, University of Khartoum, Sudan, to study effects of different levels of irrigation regime and plant density on yield of introduced small seeded (desi type) chickpea cultivar (ILC 482). The experiment was laid out in a 3X3 factorial split-plot design with 4 replications. The treatments consisted of three irrigation regimes (designated as follows: I1 = optimum irrigation, I2 = moderate stress and I3 = severe stress; this corresponded with irrigation after drainage of 50%, 75% and 100% of available water based on 70%, 60% and 50% of field capacity, respectively) assigned as main plots and three plant densities (D₁=20, D₂= 40 and D₃= 60 plants/m²) assigned as subplots. The results indicated that the yield components (number of pods per plant, number of seeds per pod, 100 seed weight), seed yield per plant, harvest index and yield per unit area of chickpea were significantly (p < 0.05) affected by irrigation regime. Decreasing irrigation regime significantly (p < 0.05) decreased all measured parameters. Alternatively, increasing plant density significantly (p < 0.05) decreased the number of pods and seed yield per plant and increased seed yield per unit area. While number of seeds per pod and harvest index were not significantly (p > 0.05) affected by plant density. Interaction between irrigation regime and plant density was also significantly (p < 0.05) affected all measured parameters of yield, except for harvest index. It could be concluded that the best irrigation regime was full irrigation (after drainage of 50% available water at 70% field capacity) and the optimal plant density was 20 plants/m² under conditions of semi-arid regions.

Keywords: irrigation regime, Cicer arietinum, chickpea, plant density

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3180 Optimized and Secured Digital Watermarking Using Fuzzy Entropy, Bezier Curve and Visual Cryptography

Authors: R. Rama Kishore, Sunesh

Abstract:

Recent development in the usage of internet for different purposes creates a great threat for the copyright protection of the digital images. Digital watermarking can be used to address the problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field of secured, robust and imperceptible watermarking. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (2, 2) share visual cryptography and Bezier curve based algorithm to improve the security of the watermark. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method. The algorithm is optimized using fuzzy entropy for better results.

Keywords: digital watermarking, fractional transform, visual cryptography, Bezier curve, fuzzy entropy

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3179 Phillips Curve Estimation in an Emerging Economy: Evidence from Sub-National Data of Indonesia

Authors: Harry Aginta

Abstract:

Using Phillips curve framework, this paper seeks for new empirical evidence on the relationship between inflation and output in a major emerging economy. By exploiting sub-national data, the contribution of this paper is threefold. First, it resolves the issue of using on-target national inflation rates that potentially causes weakening inflation-output nexus. This is very relevant for Indonesia as its central bank has been adopting inflation targeting framework based on national consumer price index (CPI) inflation. Second, the study tests the relevance of mining sector in output gap estimation. The test for mining sector is important to control for the effects of mining regulation and nominal effects of coal prices on real economic activities. Third, the paper applies panel econometric method by incorporating regional variation that help to improve model estimation. The results from this paper confirm the strong presence of Phillips curve in Indonesia. Positive output gap that reflects excess demand condition gives rise to the inflation rates. In addition, the elasticity of output gap is higher if the mining sector is excluded from output gap estimation. In addition to inflation adaptation, the dynamics of exchange rate and international commodity price are also found to affect inflation significantly. The results are robust to the alternative measurement of output gap

Keywords: Phillips curve, inflation, Indonesia, panel data

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3178 Genetic Trait Analysis of RIL Barley Genotypes to Sort-out the Top Ranked Elites for Advanced Yield Breeding Across Multi Environments of Tigray, Ethiopia

Authors: Hailekiros Tadesse Tekle, Yemane Tsehaye, Fetien Abay

Abstract:

Barley (Hordeum vulgare L.) is one of the most important cereal crops in the world, grown for the poor farmers in Tigray with low yield production. The purpose of this research was to estimate the performance of 166 barley genotypes against the quantitative traits with detailed analysis of the variance component, heritability, genetic advance, and genetic usefulness parameters. The finding of ANOVA was highly significant variation (p ≤ 0:01) for all the genotypes. We found significant differences in coefficient of variance (CV of 15%) for 5 traits out of the 12 quantitative traits. The topmost broad sense heritability (H2) was recorded for seeds per spike (98.8%), followed by thousand seed weight (96.5%) with 79.16% and 56.25%, respectively, of GAM. The traits with H2 ≥ 60% and GA/GAM ≥ 20% suggested the least influenced by the environment, governed by the additive genes and direct selection for improvement of such beneficial traits for the studied genotypes. Hence, the 20 outstanding recombinant inbred lines (RIL) barley genotypes performing early maturity, high yield, and 1000 seed weight traits simultaneously were the top ranked group barley genotypes out of the 166 genotypes. These are; G5, G25, G33, G118, G36, G123, G28, G34, G14, G10, G3, G13, G11, G32, G8, G39, G23, G30, G37, and G26. They were early in maturity, high TSW and GYP (TSW ≥ 55 g, GYP ≥ 15.22 g/plant, and DTM below 106 days). In general, the 166 genotypes were classified as high (group 1), medium (group 2), and low yield production (group 3) genotypes in terms of yield and yield component trait analysis by clustering; and genotype parameter analysis such as the heritability, genetic advance, and genetic usefulness traits in this investigation.

Keywords: barley, clustering, genetic advance, heritability, usefulness, variability, yield

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3177 The Effects of Inoculation and N Fertilization on Soybean (Glycine max (L.) Merr.) Seed Yield and Protein Concentration under Drought Stress

Authors: Oqba Basal, Andras Szabo

Abstract:

Using mineral fertilization is increasing worldwide, as it is claimed to be majorly responsible for achieving high yields; however, the negative impacts of mineral fertilization on soil and environment are becoming more obvious, with alternative methods being more necessary and applicable, especially with the current climatic changes which have imposed serious abiotic stresses, such as drought. An experiment was made during 2017 growing season in Debrecen, Hungary to investigate the effects of inoculation and N fertilization on the seed yield and protein concentration of the soybean (Glycine max (L.) Merr.) cultivar (Panonia Kincse) under three different irrigation regimes: severe drought stress (SD), moderate drought stress (MD) and control with no drought stress (ND). Three N fertilizer rates were applied: no N fertilizer (0 N), 35 kg ha⁻¹ of N fertilizer (35 N) and 105 kg ha⁻¹ of N fertilizer (105 N). Half of the seeds in each treatment was inoculated with Bradyrhizobium japonicum inoculant, and the other half was not inoculated. The results showed significant differences in the seed yield associated with inoculation, irrigation and the interaction between them, whereas there were no significant differences in the seed yield associated with fertilization alone or in interaction with inoculation or irrigation or both. When seeds were inoculated, yield was increased when (35 N) was applied compared to (0 N) but not significantly; however, the high rate of N fertilizer (105 N) reduced the yield to a level even less than (0 N). When seeds were not inoculated, the highest rate of N increased the yield the most compared to the other two N fertilizer rates whenever the drought was present (moderate or severe). Under severe drought stress, inoculation was positively and significantly correlated with yield; however, adding N fertilizer increased the yield of uninoculated plants compared to the inoculated ones, regardless of the rate of N fertilizer. Protein concentration in the seeds was significantly affected by irrigation and by fertilization, but not by inoculation. Protein concentration increased as the N fertilization rate increased, regardless of the inoculation or irrigation treatments; moreover, increasing the N rate reduced the correlation coefficient of protein concentration with the irrigation. It was concluded that adding N fertilizer is not always recommended, especially when seeds are inoculated before being sown; however, it is very important under severe drought stress to sustain yield. Enhanced protein concentrations could be achieved by applying N fertilization, whether the seeds were pre-inoculated or not.

Keywords: drought stress, N fertilization, protein concentration, soybean

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3176 A Method to Estimate Wheat Yield Using Landsat Data

Authors: Zama Mahmood

Abstract:

The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

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3175 Comparative Study of the Effects of Process Parameters on the Yield of Oil from Melon Seed (Cococynthis citrullus) and Coconut Fruit (Cocos nucifera)

Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

Abstract:

Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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3174 Synthesis and Photophysical Studies of BOPIDY Dyes Conjugated with 4-Benzyloxystyryl Substituents

Authors: Bokolombe Pitchou Ngoy, John Mack, Tebello Nyokong

Abstract:

Synthesis and photochemical studies of BODIPY dyes have been investigated in this work in order to have a broad benchmark of this functionalized photosensitizer for biological applications such as photodynamic therapy or antimicrobial activity. The common acid catalyzed synthetic method was used, and BODIPY dyes were obtained in quite a good yield (25 %) followed by bromination and Knoevenagel condensation to afford the BODIPY dyes conjugated with maximum absorbance in the near-infrared region of the electromagnetic spectrum. The fluorescence lifetimes, fluorescence quantum yield, and Singlet oxygen quantum yield of the conjugated BODIPY dyes were determined in different solvents by using Time Correlation Single Photon Counting (TCSPC), fluorimeter, and Laser Flash Photolysis respectively. It was clearly shown that the singlet oxygen quantum yield was higher in THF followed by DMSO compared to another solvent. The same trend was observed for the fluorescence lifetimes.

Keywords: BODIPY, photodynamic therapy, photosensitizer, singlet oxygen

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3173 A Deletion-Cost Based Fast Compression Algorithm for Linear Vector Data

Authors: Qiuxiao Chen, Yan Hou, Ning Wu

Abstract:

As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

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3172 System Productivity Enhancement by Inclusion of Mungbean in Potato-Jute -T. Aman Rice Cropping Pattern

Authors: Apurba Kanti Chowdhury, Taslima Zahan

Abstract:

The inclusion of mungbean in a cropping pattern not only increases the cropping intensity but also enriches soil health as well as ensures nutrition for the fast-growing population of Bangladesh. A study was conducted in the farmers’ field during 2013-14 and 2014-15 to observe the performance of four-crop based improve cropping pattern Potato-Mungbean-Jute -t.aman rice against the existing cropping pattern Potato-Jute -t.aman rice at Domar, Nilphamari followed by randomized complete block design with three replications. Two years study revealed that inclusion of mungbean and better management practices in improved cropping pattern provided higher economic benefit over the existing pattern by 73.1%. Moreover, the average yield of potato increased in the improved pattern by 64.3% compared to the existing pattern; however yield of jute and t.aman rice in improved pattern declined by 5.6% and 10.7% than the existing pattern, respectively. Nevertheless, the additional yield of mungbean in the improved pattern helped to increase rice equivalent yield of the whole pattern by 38.7% over the existing pattern. Thus, the addition of mungbean in the existing pattern Potato-Jute -t.aman rice seems to be profitable for the farmers and also might be sustainable if the market channel of mungbean developed.

Keywords: crop diversity, food nutrition, production efficiency, yield improvement

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3171 Selection of Intensity Measure in Probabilistic Seismic Risk Assessment of a Turkish Railway Bridge

Authors: M. F. Yilmaz, B. Ö. Çağlayan

Abstract:

Fragility curve is an effective common used tool to determine the earthquake performance of structural and nonstructural components. Also, it is used to determine the nonlinear behavior of bridges. There are many historical bridges in the Turkish railway network; the earthquake performances of these bridges are needed to be investigated. To derive fragility curve Intensity measures (IMs) and Engineering demand parameters (EDP) are needed to be determined. And the relation between IMs and EDP are needed to be derived. In this study, a typical simply supported steel girder riveted railway bridge is studied. Fragility curves of this bridge are derived by two parameters lognormal distribution. Time history analyses are done for selected 60 real earthquake data to determine the relation between IMs and EDP. Moreover, efficiency, practicality, and sufficiency of three different IMs are discussed. PGA, Sa(0.2s) and Sa(1s), the most common used IMs parameters for fragility curve in the literature, are taken into consideration in terms of efficiency, practicality and sufficiency.

Keywords: railway bridges, earthquake performance, fragility analyses, selection of intensity measures

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3170 How Much the Role of Fertilizers Management and Wheat Planting Methods on Its Yield Improvement?

Authors: Ebrahim Izadi-Darbandi, Masoud Azad, Masumeh Dehghan

Abstract:

In order to study the effects of nitrogen and phosphoruse management and wheat sowing method on wheat yield, two experiments was performed as factorial, based on completely randomized design with three replications at Research Farm, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran in 2009. In the first experiment nitrogen application rates (100kg ha-1, 200 kg ha-1, 300 kg ha-1), phosphorus application rates (100 kg ha-1, 200 kg ha-1) and two levels of their application methods (Broadcast and Band) were studied. The second experiment treatments included of wheat sowing methods (single-row with 30 cm distance and twine row on 60 cm width ridges), as main plots and nitrogen and phosphorus application methods (Broadcast and Band) as sub plots (150 kg ha-1). Phosphorus and nitrogen sources for fertilization at both experiment were respectively super phosphate, applied before wheat sowing and incorporated with soil and urea, applied in two phases (50% pre plant) and (50%) near wheat shooting. Results from first experiment showed that the effect of fertilizers application methods were significant (p≤0.01) on wheat yield increasing. Band application of phosphorus and nitrogen were increased biomass and seed yield of wheat with nine and 15% respectively compared to their broadcast application. The interaction between the effects of nitrogen and phosphorus application rate with phosphorus and nitrogen application methods, showed that band application of fertilizers and the rate of application of 200kg/ha phosphorus and 300kg/ha nitrogen were the best methods in wheat yield improvement. The second experiment also showed that the effect of wheat sowing method and fertilizers application methods were significant (p≤0.01) on wheat seed and biomass yield improvement. Wheat twine row on 60 cm width ridges sowing method, increased its biomass and seed yield for 22% and 30% respectively compared to single-row with 30 cm. Wheat sowing method and fertilizers application methods interaction indicated that band application of fertilizers and wheat twine row on 60 cm width ridges sowing method was the best treatment on winter wheat yield improvement. In conclusion these results indicated that nitrogen and phosphorus management in wheat and modifying wheat sowing method have important role in increasing fertilizers use efficiency.

Keywords: band application, broadcast application, rate of fertilizer application, wheat seed yield, wheat biomass yield

Procedia PDF Downloads 439
3169 Combining an Optimized Closed Principal Curve-Based Method and Evolutionary Neural Network for Ultrasound Prostate Segmentation

Authors: Tao Peng, Jing Zhao, Yanqing Xu, Jing Cai

Abstract:

Due to missing/ambiguous boundaries between the prostate and neighboring structures, the presence of shadow artifacts, as well as the large variability in prostate shapes, ultrasound prostate segmentation is challenging. To handle these issues, this paper develops a hybrid method for ultrasound prostate segmentation by combining an optimized closed principal curve-based method and the evolutionary neural network; the former can fit curves with great curvature and generate a contour composed of line segments connected by sorted vertices, and the latter is used to express an appropriate map function (represented by parameters of evolutionary neural network) for generating the smooth prostate contour to match the ground truth contour. Both qualitative and quantitative experimental results showed that our proposed method obtains accurate and robust performances.

Keywords: ultrasound prostate segmentation, optimized closed polygonal segment method, evolutionary neural network, smooth mathematical model, principal curve

Procedia PDF Downloads 174
3168 Effect of Tillage Practices and Planting Patterns on Growth and Yield of Maize (Zee Maize)

Authors: O. R. Obalowu, F. B. Akande, T. P Abegunrin

Abstract:

Maize (Zea may) is mostly grown and consumed by Nigeria farmers using different tillage practices which have a great effect on its growth and yield. In order to maximize output, there is need to recommend a suitable tillage practice for crop production which will increase the growth and yield of maize. This study investigated the effect of tillage practices and planting pattern on the growth and yield of maize. The experiment was arranged in a 4x3x3 Randomized Complete Block Design (RCBD) layout, with four tillage practices consisting of no-tillage (NT), disc ploughing only (Ponly), disc ploughing followed by harrowing (PH), and disc ploughing, harrowing then ridging (PHR). Three planting patterns which include; 65 x 75, 75 x 75 and 85 x 75 cm spacing within and between the rows respectively, were randomly applied on the plots. All treatments were replicated three times. Data which consist of plant height, stem girth, leaf area and weight of maize per plots were taken and recorded. Data gathered were analyzed using Analysis of Variance (ANOVA) in the Minitab Software Package. The result shows that PHR under the third planting pattern has the highest growth rate (216.50 cm) while NT under the first planting pattern has the lowest mean value of growth rate (115.60 cm). Also, Ponly under the first planting pattern gives a better maize yield (19.45 kg) when compared with other tillage practices while NT under first planting pattern recorded the least yield of maize (9.40 kg). In conclusion, considering soil and weather conditions of the research area, plough only under the first planting pattern (65 x 75 cm) is the best alternative for the production of the Swan maize variety.

Keywords: tillage practice, planting pattern, disc ploughing, harrowing, ridging

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3167 Simulation of Growth and Yield of Rice Under Irrigation and Nitrogen Management Using ORYZA2000

Authors: Mojtaba Esmaeilzad Limoudehi

Abstract:

To evaluate the model ORYZA2000, under the management of irrigation and nitrogen fertilization experiment, a split plot with a randomized complete block design with three replications on hybrid cultivars (spring) in the 1388-1387 crop year was conducted at the Rice Research Institute. Permanent flood irrigation as the main plot in the fourth level, around 5 days, from 11 days to 8 days away, and the four levels of nitrogen fertilizer as the subplots 0, 90, 120, and 150 kg N Ha were considered. Simulated and measured values of leaf area index, grain yield, and biological parameters using the regression coefficient, t-test, the root mean square error (RMSE), and normalized root mean square error (RMSEn) were performed. Results, the normalized root mean square error of 10% in grain yield, the biological yield of 9%, and 23% of maximum LAI was determined. The simulation results show that grain yield and biological ORYZA2000 model accuracy are good but do not simulate maximum LAI well. The results show that the model can support ORYZA2000 test results and can be used under conditions of nitrogen fertilizer and irrigation management.

Keywords: evaluation, rice, nitrogen fertilizer, model ORYZA2000

Procedia PDF Downloads 48
3166 Impact of Climate on Sugarcane Yield Over Belagavi District, Karnataka Using Statistical Mode

Authors: Girish Chavadappanavar

Abstract:

The impact of climate on agriculture could result in problems with food security and may threaten the livelihood activities upon which much of the population depends. In the present study, the development of a statistical yield forecast model has been carried out for sugarcane production over Belagavi district, Karnataka using weather variables of crop growing season and past observed yield data for the period of 1971 to 2010. The study shows that this type of statistical yield forecast model could efficiently forecast yield 5 weeks and even 10 weeks in advance of the harvest for sugarcane within an acceptable limit of error. The performance of the model in predicting yields at the district level for sugarcane crops is found quite satisfactory for both validation (2007 and 2008) as well as forecasting (2009 and 2010).In addition to the above study, the climate variability of the area has also been studied, and hence, the data series was tested for Mann Kendall Rank Statistical Test. The maximum and minimum temperatures were found to be significant with opposite trends (decreasing trend in maximum and increasing in minimum temperature), while the other three are found in significant with different trends (rainfall and evening time relative humidity with increasing trend and morning time relative humidity with decreasing trend).

Keywords: climate impact, regression analysis, yield and forecast model, sugar models

Procedia PDF Downloads 48
3165 Effect of Vermicompost and Vermitea on the Growth and Yield of Selected Vegetable Crops

Authors: Josephine R. Migalbin, Jurhamid C. Imlan, Evelyn P. Esteban

Abstract:

A study was conducted to determine the effect of vermicompost and vermitea as organic fertilizers on the growth and yield of selected vegetable crops specifically eggplant, tomatoes and sweet pepper. The study was laid-out in Randomized Complete Block Design with 4 treatments replicated 4 times. The treatments were as follows: Treatment I (control), Treatment II (vermitea), Treatment III (vermicompost with buffalo manure), and Treatment IV (vermicompost with goat and sheep manure). In all the vegetable crops, almost all parameters significantly increased compared with the control except for number of fruits in eggplant and plant height in tomatoes where no significant difference was observed among treatments. The highest marketable fruit yield (tons/ha) was obtained from plants applied with vermicompost with goat and sheep manure but comparable with plants applied with vermicompost with buffalo manure and vermitea while the control plots received the lowest yield. The 28 spotted beetle (Epilachna philippinensis), and shoot and fruit borer (Leucinodes orbonalis) were the serious pests observed in the study on eggplant.

Keywords: marketable fruit yield, vermicompost, vermitea, vegetable crops

Procedia PDF Downloads 549