Search results for: agriculture yield prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5746

Search results for: agriculture yield prediction

5296 A New Prediction Model for Soil Compression Index

Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

Procedia PDF Downloads 347
5295 Growth and Yield Response of Solanum retroflexum to Different Level of Salinity

Authors: Fhatuwani Herman Nndwambi, P. W. Mashela

Abstract:

Salinity is a major constraint limiting crop productivity. It has been predicted that by the year 2050, more than 50% of the arable land will be affected by salinity. Two similar salinity experiments were conducted in two seasons under greenhouse condition. Six levels of salinity plus control (viz; control, 2, 4, 8, 16, 32 and 64 % NaCl and CaCl2 at 3:1 ratio) were applied in a form of irrigation water in a single factor experiment arranged in a complete block design with 20 replications. Plant growth and yield were negatively affected by salinity treatments especially at the high levels of salinity. For example, our results suggest that the 32 and 64% of NaCl and CaCl2 treatment were too much for the plant to withstand as determined by reduced dry shoot mass, stem diameter and plant height in both seasons. On the other hand, stomatal conductance and chlorophyll content increased with an increased level of salinity.

Keywords: growth, salinity, season, yield

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5294 OBD-Biofertilizer Impact on Crop Yield and Soil Quality in Lowland Rice Production, Badeggi, Niger State, Nigeria

Authors: Ayodele A. Otaiku

Abstract:

Purpose: Nigeria has become the largest importer of rice in Africa and second in the world, 2015. Investigate interactions of organic rice farming on soil quality and health from bio-waste converted to biofertilizer and its environmental impact on rice crop. Methodology: Bio-wastes, poultry waste, organic agriculture wastes, wood ash mixed with microbial inoculant organisms called OBD-Plus microbes (broad spectrum) composted in anaerobic digester to OBD-biofertilizer (2010 - 2012) uses microbes to build humus and other stable carbons. Two field experiments were carried out at Badeggi, Niger state in 2011 and 2012 to evaluate the response of lowland rice production using biofertilizer. The experimental field was laid out in a strip-plot design with five treatments and three replications and at twenty-one day old seedlings of FARO 44 and FARO 52 rice varieties were transplanted. Plots without fertiliser application served as control. Findings: The highest rice grain yield increase of 4.4 t/ha over the control in 2012 against the Nigeria average of lowland rice grain yields of 1.5 t/ha. The utilization of OBD-Biofertilizer can decrease the use of chemical nitrogen fertilizer, prevent the depletion of soil organic matter and reduce environmental pollution. Increasing the floodwater productivity and optimizing the recycling of nutrients cum grazer populations and disease by biocontrols microbes present in the OBD-Biofertilizer. Organic matter in the soil improves by 58% and C/N 15 (2011) and 13.35 (2012). Implications: OBD- Biofertilizer produce plant growth hormones such as indole acetic acid (IAA), glomalin related soil protein and extracellular enzymes as phosphatases that promote soil health and quality. Conclusion: Microorganisms can enhance nutrients use efficiency by increasing root surface area e.g., mycorrhizal, fungi, promoting other beneficial symbioses of the host plant and microbial interactions resulting to increase in soil organic matter. By 2030, climate change is projected to depress cereal production in Africa by 2 to 3 percent. Improved seeds and increased fertilizer use should more than compensate, but this factor will still weigh heavily on efforts to make progress.

Keywords: OBD-plus microbial consortia, OBD-biofertilizer, rice production, soil quality, sustainable agriculture

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5293 Predicting Photovoltaic Energy Profile of Birzeit University Campus Based on Weather Forecast

Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

Abstract:

This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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5292 Prediction of MicroRNA-Target Gene by Machine Learning Algorithms in Lung Cancer Study

Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

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5291 Effect of Integrated Nutrient Management Practice on Cultivation Scented Rice Varieties- a Better Approach for Resource Conservation

Authors: Amit Kumar Patel, M. C. Bhambri, Damini Thawait, Srishti Pandey

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The experiment was carried out at Raipur during rainy season of 2012. The experiment revealed that the performance of Dubraj was comparatively better than that of badshah bhog, Vishnu bhog and bisni. The number of grains panicle-1, number of filled grains panicle-1 were comparable in Dubraj and badshah bhog. Among the different nutrient, application of 80:50:40 kg N:P2O5:K2O ha-1(50% Inorganic+50% Organic) gave better performance in all the above characters. It is revealed that the variety Dubraj fertilized with 80:50:40 kg N:P2O5:K2O ha-1(50% Inorganic+50% Organic) gave the good yield attributing characters along with highest yield.

Keywords: scented rice, organic manures, chemical fertilizers, yield, varieties

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5290 Project Progress Prediction in Software Devlopment Integrating Time Prediction Algorithms and Large Language Modeling

Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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5289 Predicting Recessions with Bivariate Dynamic Probit Model: The Czech and German Case

Authors: Lukas Reznak, Maria Reznakova

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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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5288 Evaluation of the Effect of Milk Recording Intervals on the Accuracy of an Empirical Model Fitted to Dairy Sheep Lactations

Authors: L. Guevara, Glória L. S., Corea E. E, A. Ramírez-Zamora M., Salinas-Martinez J. A., Angeles-Hernandez J. C.

Abstract:

Mathematical models are useful for identifying the characteristics of sheep lactation curves to develop and implement improved strategies. However, the accuracy of these models is influenced by factors such as the recording regime, mainly the intervals between test day records (TDR). The current study aimed to evaluate the effect of different TDR intervals on the goodness of fit of the Wood model (WM) applied to dairy sheep lactations. A total of 4,494 weekly TDRs from 156 lactations of dairy crossbred sheep were analyzed. Three new databases were generated from the original weekly TDR data (7D), comprising intervals of 14(14D), 21(21D), and 28(28D) days. The parameters of WM were estimated using the “minpack.lm” package in the R software. The shape of the lactation curve (typical and atypical) was defined based on the WM parameters. The goodness of fit was evaluated using the mean square of prediction error (MSPE), Root of MSPE (RMSPE), Akaike´s Information Criterion (AIC), Bayesian´s Information Criterion (BIC), and the coefficient of correlation (r) between the actual and estimated total milk yield (TMY). WM showed an adequate estimate of TMY regardless of the TDR interval (P=0.21) and shape of the lactation curve (P=0.42). However, we found higher values of r for typical curves compared to atypical curves (0.9vs.0.74), with the highest values for the 28D interval (r=0.95). In the same way, we observed an overestimated peak yield (0.92vs.6.6 l) and underestimated time of peak yield (21.5vs.1.46) in atypical curves. The best values of RMSPE were observed for the 28D interval in both lactation curve shapes. The significant lowest values of AIC (P=0.001) and BIC (P=0.001) were shown by the 7D interval for typical and atypical curves. These results represent the first approach to define the adequate interval to record the regime of dairy sheep in Latin America and showed a better fitting for the Wood model using a 7D interval. However, it is possible to obtain good estimates of TMY using a 28D interval, which reduces the sampling frequency and would save additional costs to dairy sheep producers.

Keywords: gamma incomplete, ewes, shape curves, modeling

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5287 Effects of Irrigation Scheduling and Soil Management on Maize (Zea mays L.) Yield in Guinea Savannah Zone of Nigeria

Authors: I. Alhassan, A. M. Saddiq, A. G. Gashua, K. K. Gwio-Kura

Abstract:

The main objective of any irrigation program is the development of an efficient water management system to sustain crop growth and development and avoid physiological water stress in the growing plants. Field experiment to evaluate the effects of some soil moisture conservation practices on yield and water use efficiency (WUE) of maize was carried out in three locations (i.e. Mubi and Yola in the northern Guinea Savannah and Ganye in the southern Guinea Savannah of Adamawa State, Nigeria) during the dry seasons of 2013 and 2014. The experiment consisted of three different irrigation levels (7, 10 and 12 day irrigation intervals), two levels of mulch (mulch and un-mulched) and two tillage practices (no tillage and minimum tillage) arranged in a randomized complete block design with split-split plot arrangement and replicated three times. The Blaney-Criddle method was used for measuring crop evapotranspiration. The results indicated that seven-day irrigation intervals and mulched treatment were found to have significant effect (P>0.05) on grain yield and water use efficiency in all the locations. The main effect of tillage was non-significant (P<0.05) on grain yield and WUE. The interaction effects of irrigation and mulch were significant (P>0.05) on grain yield and WUE at Mubi and Yola. Generally, higher grain yield and WUE were recorded on mulched and seven-day irrigation intervals, whereas lower values were recorded on un-mulched with 12-day irrigation intervals. Tillage exerts little influence on the yield and WUE. Results from Ganye were found to be generally higher than those recorded in Mubi and Yola; it also showed that an irrigation interval of 10 days with mulching could be adopted for the Ganye area, while seven days interval is more appropriate for Mubi and Yola.

Keywords: irrigation, maize, mulching, tillage, savanna

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5286 Prediction of Oil Recovery Factor Using Artificial Neural Network

Authors: O. P. Oladipo, O. A. Falode

Abstract:

The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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5285 Data-Driven Strategies for Enhancing Food Security in Vulnerable Regions: A Multi-Dimensional Analysis of Crop Yield Predictions, Supply Chain Optimization, and Food Distribution Networks

Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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5284 Agriculture, Food Security and Poverty Reduction in Nigeria: Cointegration and Granger Causality Approach

Authors: Ogunwole Cecilia Oluwakemi, Timothy Ayomitunde Aderemi

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Provision of sufficient food and elimination of abject poverty have usually been the conventional benefits of agriculture in any society. Meanwhile, despite the fact that Nigeria is an agrarian society, food insecurity and poverty have become the issues of concern among both scholars and policymakers in the recent times. Against this backdrop, this study examined the nexus among agriculture, food security, and poverty reduction in Nigeria from 1990 to 2019 within the framework of the Cointegration and Granger Causality approach. Data was collected from the Central Bank of Nigeria Statistical Bulletin and the World Development Indicators, respectively. The following are the major results that emanated from the study. A long run equilibrium relationship exists among agricultural value added, food production index, and GDP per capita in Nigeria. Similarly, there is a unidirectional causality which flows from food production index to poverty reduction in Nigeria. In the same vein, one way causality flows from poverty reduction to agricultural value added in Nigeria. Consequently, this study makes the following recommendation for the policymakers in Nigeria, and other African countries by extension, that agricultural value added and food production are the important variables that cannot be undermined when poverty reduction occupies the central focus of the policymakers. Therefore, any time these policymakers want to reduce poverty, policies that drive agricultural value added and food production should be embarked upon. Therefore, this study will contribute to the literature by establishing the type of linkage that exists between agriculture, food security, and poverty reduction in Nigeria.

Keywords: agriculture, value added, food production, GDP per capita, Nigeria

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5283 Simulation of Corn Yield in Carmen, North Cotabato, Philippines Using Aquacrop Model

Authors: Marilyn S. Painagan

Abstract:

This general objective of the study was to apply the AquaCrop model to the conditions in the municipality of Carmen, North Cotabato in terms of predicting corn yields in this area and determine the influence of rainfall and soil depth on simulated yield. The study revealed wide disparity in monthly yields as a consequence of similarly varying monthly rainfall magnitudes. It also found out that simulated yield varies with the depth of soil, which in this case was clay loam, the predominant soil in the study area. The model was found to be easy to use even with limited data and shows a vast potential for various farming and policy applications, such as formulation of a cropping calendar.

Keywords: aquacrop, evapotranspiration, crop modelling, crop simulation

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5282 Life Prediction Method of Lithium-Ion Battery Based on Grey Support Vector Machines

Authors: Xiaogang Li, Jieqiong Miao

Abstract:

As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines.For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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5281 Sustainable Water Resource Management and Challenges in Indian Agriculture

Authors: Rajendra Kumar Isaac, Monisha Isaac

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India, having a vast cultivable area and regional climatic variability, encounters water Resource Management Problems at various levels. The agricultural production of India needs to be increased to meet out projected population growth. Sustainable water resource is the only option to ensure food security, especially in northern Indian states, where the ground and surface water resources are fast depleting. Various tools and technologies available for management of scarce water resources have been discussed. It was concluded that multiple use of water, adopting latest water management options, identification of climate adoptable cropping and farming systems, can enhance water productivity and would encounter the fast growing water management and water shortage problems in Indian agriculture.

Keywords: water resource management, sustainable, water management technologies, water productivity, agriculture

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5280 Assessing the Effects of Community Informatics on Livelihoods Sustainability in Nigeria: a Model for Rural Communities

Authors: Adebayo J. Julius, Oluremi N. Iluyomade

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Livelihood in Nigeria is a paradox of poverty amidst plenty. The Country is endowed with a good climate for agriculture, naturally growing fruit trees and vegetables, and undomesticated water resources. In spite of all its endowment, Nigeria continues to live in poverty year in year out. This thus raises a very important question as to how can there be so much poverty in Nigeria with all its natural endowments. This study focused comparative analysis of the utilization of community informatics for sustainable livelihoods through agriculture. The idea projected in this study is that small strategic changes in the modus operandi of social informatics can have a significant impact on sustainability of livelihoods. This paper carefully explored the theories of community informatics and its efficacies in dealing with sustainability issues. This study identified, described and evaluates the roles of community informatics in some sectors of the economy, different analytical tools to benchmark the influence of social informatics in agriculture against what is obtainable in agricultural sectors of the economy were used. It further employed comparative analysis to build a case model for sustainable livelihood in agriculture through community informatics.

Keywords: informatics , model, rural community, livelihoods sustainability, Nigeria

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5279 Assessment on the Level of Development of Macedonia and Iran Organic Agriculture as Compared to Nigeria: A Review

Authors: Y. A. Sani., A. A. Yakubu., A. A. Jamilu., J. Omeke, I. J. Sambo

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With the rising global threat of food security, cancer, and related diseases (carcinogenic) because of increased usage of inorganic substances in agricultural food production, the Ministry of Food Agriculture and Livestock of the Republic of Turkey organized an International Workshop on Organic Agriculture between 8–12th December 2014 at the International Agricultural Research and Training Center, Izmir. About 21 countries, including Nigeria, were invited to attend the training workshop. Several topics on organic agriculture were presented by renowned scholars, ranging from regulation, certification, crop, animal, seed production, pest and disease management, soil composting, and marketing of organic agricultural products, among others. This paper purposely selected two countries (Macedonia and Iran) out of the 21 countries to assess their level of development in terms of organic agriculture as compared to Nigeria. Macedonia, with a population of only 2.1 million people as of 2014, started organic agriculture in 2005 with only 266ha of land and has grown significantly to over 5,000ha in 2010, covering such crops as cereals (62%), forage (20%) fruit orchard (7%), vineyards (5%), vegetables (4%), oil seed and industrial crops (1%) each. Others are organic beekeeping from 110 hives to over 15,000 certified colonies. As part of government commitment, the level of government subsidy for organic products was 30% compared to the direct support for conventional agricultural products. About 19 by-laws were introduced on organic agricultural production that was fully consistent with European Union regulations. The republic of Iran, on the other hand, embarked on organic agriculture for the fact, that the country recorded the highest rate of cancer disease in the world, with over 30,000 people dying every year and 297 people diagnosed every day. However, the host country, Turkey, is well advanced in organic agricultural production and now being the largest exporter of organic products to Europe and other parts of the globe. A technical trip to one of the villages that are under the government scheme on organic agriculture reveals that organic agriculture was based on market-demand-driven and the support of the government was very visible, linking the farmers with private companies that provide inputs to them while the companies purchase the products at harvest with a high premium price. However, in Nigeria, research on organic agriculture was very recent, and there was very scanty information on organic agriculture due to poor documentation and very low awareness, even among the elites. The paper, therefore, recommends that the government should provide funds to NARIs to conduct research on organic agriculture and to establish clear government policy and good pre-conditions for sustainable organic agricultural production in the country.

Keywords: organic agriculture, food security, food safety, food nutrition

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5278 Virtual Chemistry Laboratory as Pre-Lab Experiences: Stimulating Student's Prediction Skill

Authors: Yenni Kurniawati

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Students Prediction Skill in chemistry experiments is an important skill for pre-service chemistry students to stimulate students reflective thinking at each stage of many chemistry experiments, qualitatively and quantitatively. A Virtual Chemistry Laboratory was designed to give students opportunities and times to practicing many kinds of chemistry experiments repeatedly, everywhere and anytime, before they do a real experiment. The Virtual Chemistry Laboratory content was constructed using the Model of Educational Reconstruction and developed to enhance students ability to predicted the experiment results and analyzed the cause of error, calculating the accuracy and precision with carefully in using chemicals. This research showed students changing in making a decision and extremely beware with accuracy, but still had a low concern in precision. It enhancing students level of reflective thinking skill related to their prediction skill 1 until 2 stage in average. Most of them could predict the characteristics of the product in experiment, and even the result will going to be an error. In addition, they take experiments more seriously and curiously about the experiment results. This study recommends for a different subject matter to provide more opportunities for students to learn about other kinds of chemistry experiments design.

Keywords: virtual chemistry laboratory, chemistry experiments, prediction skill, pre-lab experiences

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5277 Growth and Yield Response of an Indian Wheat Cultivar (HD 2967) to Ozone and Water Stress in Open-Top Chambers with Emphasis on Its Antioxidant Status, Photosynthesis and Nutrient Allocation

Authors: Annesha Ghosh, S. B. Agrawal

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Agricultural sector is facing a serious threat due to climate change and exacerbation of different atmospheric pollutants. Tropospheric ozone (O₃) is considered as a dynamic air pollutant imposing substantial phytotoxicity to natural vegetations and agriculture worldwide. Naturally, plants are exposed to different environmental factors and their interactions. Amongst such interactions, studies related to O₃ and water stress are still rare. In the present experiment, wheat cultivar HD2967 were grown in open top chambers (OTC) under two O₃ concentration; ambient O₃ level (A) and elevated O₃ (E) (ambient + 20 ppb O₃) along with two different water supply; well-watered (W) and 50% water stress conditions (WS), with an aim to assess the individual and interactive effect of two most prevailing stress factors in Indo-Gangetic Plains of India. Exposure to elevated O₃ dose caused early senescence symptoms and reduction in growth and biomass of the test cultivar. The adversity was more pronounced under the combined effect of EWS. Significant reduction of stomatal conductance (gs) and assimilation rate were observed under combined stress condition compared to the control (AW). However, plants grown under individual stress conditions displayed higher gs, biomass, and antioxidant defense mechanism compared to the plants grown under the presence of combined stresses. Higher induction in most of the enzyme activities of catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR), peroxidase (POD) and superoxide dismutase (SOD) was displayed by HD 2967 under EW while, under the presence of combined stresses (EWS), a moderate increment of APX and CAT activity was observed only at its vegetative phase. Furthermore, variations in nutrient uptake and redistribution to different plants parts were also observed in the present study. Reduction in water availability has checked nutrient uptake (N, K, P, Ca, Cu, Mg, Zn) in above-ground parts (leaf) and below-ground parts (root). On the other hand, carbon (C) accumulation with subsequent C-N ratio was observed to be higher in the leaves under EWS. Such major nutrient check and limitation in carbon fixation due to lower gs under combined stress conditions might have weakened the defense mechanisms of the test cultivar. Grain yield was significantly reduced under EWS followed by AWS and EW as compared to their control, exhibiting an additive effect on the grain yield.

Keywords: antioxidants, open-top chambers, ozone, water stress, wheat, yield

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5276 Responses of Grain Yield, Anthocyanin and Antioxidant Capacity to Water Condition in Wetland and Upland Purple Rice Genotypes

Authors: Supaporn Yamuangmorn, Chanakan Prom-U-Thai

Abstract:

Wetland and upland purple rice are the two major types classified by its original ecotypes in Northern Thailand. Wetland rice is grown under flooded condition from transplanting until the mutuality, while upland rice is naturally grown under well-drained soil known as aerobic cultivations. Both ecotypes can be grown and adapted to the reverse systems but little is known on its responses of grain yield and qualities between the 2 ecotypes. This study evaluated responses of grain yield as well as anthocyanin and antioxidant capacity between the wetland and upland purple rice genotypes grown in the submerged and aerobic conditions. A factorial arrangement in a randomized complete block design (RCBD) with two factors of rice genotype and water condition were carried out in three replications. The two wetland genotypes (Kum Doi Saket: KDK and Kum Phayao: KPY) and two upland genotypes (Kum Hom CMU: KHCMU and Pieisu1: PES1) were used in this study by growing under submerged and aerobic conditions. Grain yield was affected by the interaction between water condition and rice genotype. The wetland genotypes, KDK and KPY grown in the submerged condition produced about 2.7 and 0.8 times higher yield than in the aerobic condition, respectively. The 0.4 times higher grain yield of upland genotype (PES1) was found in the submerged condition than in the aerobic condition, but no significant differences in KHCMU. In the submerged condition, all genotypes produced higher yield components of tiller number, panicle number and percent filled grain than in the aerobic condition by 24% and 32% and 11%, respectively. The thousand grain weight and spikelet number were affected by water condition differently among genotypes. The wetland genotypes, KDK and KPY, and upland genotype, PES1, grown in the submerged condition produced about 19-22% higher grain weight than in the aerobic condition. The similar effect was found in spikelet number which the submerged condition of wetland genotypes, KDK and KPY, and the upland genotype, KHCMU, had about 28-30% higher than the aerobic condition. In contrast, the anthocyanin concentration and antioxidant capacity were affected by both the water condition and genotype. Rice grain grown in the aerobic condition had about 0.9 and 2.6 times higher anthocyanin concentration than in the submerged condition was found in the wetland rice, KDK and upland rice, KHCMU, respectively. Similarly, the antioxidant capacity of wetland rice, KDK and upland rice, KHCMU were 0.5 and 0.6 times higher in aerobic condition than in the submerged condition. There was a negative correlation between grain yield and anthocyanin concentration in wetland genotype KDK and upland genotype KHCMU, but it was not found in the other genotypes. This study indicating that some rice genotype can be adapted in the reverse ecosystem in both grain yield and quality, especially in the wetland genotype KPY and upland genotype PES1. To maximize grain yield and quality of purple rice, proper water management condition is require with a key consideration on difference responses among genotypes. Increasing number of rice genotypes in both ecotypes is needed to confirm their responses on water management.

Keywords: purple rice, water condition, anthocyanin, grain yield

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5275 The Best Prediction Data Mining Model for Breast Cancer Probability in Women Residents in Kabul

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

Abstract:

The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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5274 Yield Performance of Two Locally Adapted and Two Introductions of Common Cowpea in Response to Amended In-Row-Spaces and Planting Dates

Authors: Ayman M. A. Rashwan, Mohamed F. Mohamed, Mohamed M. A. Abdalla

Abstract:

A field experiment was conducted in the Agricultural Research Station, at El-Ghoraieb, Assiut to study dry seed yield performance of two locally adapted cultivars (‘Azmerly’ and ‘Cream 7’) and two line introductions (IT81D-1032 and IT82D-812) of common cowpea (Vigna unguiculata (L.) Walp) grown at three different within-row spaces (20, 30 and 40 cm) and two planting dates in the summer (April 15th and 30th) and in the fall season (Aug. 12th and 27th) of two successive seasons. The data showed that total dry-seed yield produced by plants grown at 20 cm was greater than at 30 cm in all cvs/lines in both years. Increases in 1000-seed weight were detected in cv ‘Azmerly’ and line IT82D-812 when they were grown at 30 cm as compared with 20 cm in the summer season. However, in the fall season such increases were found in all cvs/lines. Planting at 40 cm produced seeds of greater weight than planting at 30 cm for all cvs/lines in the fall season and also in cv. Cream 7 and line IT82D-812 in the summer season. Planting on April 15th in the summer and also planting on Aug. 12th in the fall had plants which showed increases in 1000-seed weight and total dry-seed yield. The greatest 1000-seed weight was found in the line IT81D-1032 in the summer season and in the line IT82D-812 in the fall season. The sum up results revealed that ‘Azmerly’ produced greater dry-seed yield than ‘Cream 7’ and both of them were superior to the line IT82D-812 and IT81D-1032 in the summer season. In the fall, however, the line IT82D-812 produced greater dry-seed yield than the other cultivars/lines.

Keywords: Cowpea, Assiut, fall, planting dates, El-Ghoraieb, dry-seed yield

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5273 Challenges of Peri-Urban Agriculture in Cities of Developing Countries: A Case Study of Nairobi City Peri-Urban Area

Authors: Aggrey Daniel Maina Thuo

Abstract:

Rapid urban population growth means an increasing demand for urban land, particularly for housing, and also for various other urban uses. This land is not available within cities but in peri-urban areas. The expansion of the cities into the peri-urban areas is creating direct and indirect impacts with those living there facing new challenges and opportunities in meeting their life needs and accommodating the by-products of urbanization. Although urbanization of these areas provides opportunities for employment, better housing, education, knowledge and technology transfer, and ready markets for the agricultural products, increase in population places enormous stress on natural resources and existing social services and infrastructure, therefore causing environmental degradation. This environmental degradation is affecting agriculture for those still holding onto their farms for agricultural purposes. This paper, using a multiple theoretical framework and qualitative research approach, attempts to describe the positive and adverse effects of urbanization on peri-urban agriculture, using the Town Council of Karuri within Nairobi peri-urban areas as a case study.

Keywords: peri-urban agriculture, urbanization, land use, environmental degradation, planning

Procedia PDF Downloads 332
5272 Protected Cultivation of Horticultural Crops: Increases Productivity per Unit of Area and Time

Authors: Deepak Loura

Abstract:

The most contemporary method of producing horticulture crops both qualitatively and quantitatively is protected cultivation, or greenhouse cultivation, which has gained widespread acceptance in recent decades. Protected farming, commonly referred to as controlled environment agriculture (CEA), is extremely productive, land- and water-wise, as well as environmentally friendly. The technology entails growing horticulture crops in a controlled environment where variables such as temperature, humidity, light, soil, water, fertilizer, etc. are adjusted to achieve optimal output and enable a consistent supply of them even during the off-season. Over the past ten years, protected cultivation of high-value crops and cut flowers has demonstrated remarkable potential. More and more agricultural and horticultural crop production systems are moving to protected environments as a result of the growing demand for high-quality products by global markets. By covering the crop, it is possible to control the macro- and microenvironments, enhancing plant performance and allowing for longer production times, earlier harvests, and higher yields of higher quality. These shielding features alter the environment of the plant while also offering protection from wind, rain, and insects. Protected farming opens up hitherto unexplored opportunities in agriculture as the liberalised economy and improved agricultural technologies advance. Typically, the revenues from fruit, vegetable, and flower crops are 4 to 8 times higher than those from other crops. If any of these high-value crops are cultivated in protected environments like greenhouses, net houses, tunnels, etc., this profit can be multiplied. Vegetable and cut flower post-harvest losses are extremely high (20–0%), however sheltered growing techniques and year-round cropping can greatly minimize post-harvest losses and enhance yield by 5–10 times. Seasonality and weather have a big impact on the production of vegetables and flowers. The variety of their products results in significant price and quality changes for vegetables. For the application of current technology in crop production, achieving a balance between year-round availability of vegetables and flowers with minimal environmental impact and remaining competitive is a significant problem. The future of agriculture will be protected since population growth is reducing the amount of land that may be held. Protected agriculture is a particularly profitable endeavor for tiny landholdings. Small greenhouses, net houses, nurseries, and low tunnel greenhouses can all be built by farmers to increase their income. Protected agriculture is also aided by the rise in biotic and abiotic stress factors. As a result of the greater productivity levels, these technologies are not only opening up opportunities for producers with larger landholdings, but also for those with smaller holdings. Protected cultivation can be thought of as a kind of precise, forward-thinking, parallel agriculture that covers almost all aspects of farming and is rather subject to additional inspection for technical applicability to circumstances, farmer economics, and market economics.

Keywords: protected cultivation, horticulture, greenhouse, vegetable, controlled environment agriculture

Procedia PDF Downloads 59
5271 Volarization of Sugarcane Bagasse: The Effect of Alkali Concentration, Soaking Time and Temperature on Fibre Yield

Authors: Tamrat Tesfaye, Tilahun Seyoum, K. Shabaridharan

Abstract:

The objective of this paper was to determine the effect of NaOH concentration, soaking time, soaking temperature and their interaction on percentage yield of fibre extract using Response Surface Methodology (RSM). A Box-Behnken design was employed to optimize the extraction process of cellulosic fibre from sugar cane by-product bagasse using low alkaline extraction technique. The quadratic model with the optimal technological conditions resulted in a maximum fibre yield of 56.80% at 0.55N NaOH concentration, 4 h steeping time and 60ᵒC soaking temperature. Among the independent variables concentration was found to be the most significant (P < 0.005) variable and the interaction effect of concentration and soaking time leads to securing the optimized processes.

Keywords: sugarcane bagasse, low alkaline, Box-Behnken, fibre

Procedia PDF Downloads 226
5270 Enhanced Methane Production from Waste Paper through Anaerobic Co-Digestion with Macroalgae

Authors: Cristina Rodriguez, Abed Alaswad, Zaki El-Hassan, Abdul G. Olabi

Abstract:

This study investigates the effect on methane production from the waste paper when co-digested with macroalgal biomass as a source of nitrogen. Both feedstocks were previously mechanically pretreated in order to reduce their particle size. Methane potential assays were carried out at laboratory scale in batch mode for 28 days. The study was planned according to two factors: the feedstock to inoculum (F/I) ratio and the waste paper to macroalgae (WP/MA) ratio. The F/I ratios checked were 0.2, 0.3 and 0.4 and the WP/MA ratios were 0:100, 25:75, 50:50, 75:25 and 100:0. The highest methane yield (608 ml/g of volatile solids (VS)) was achieved at an F/I ratio of 0.2 and a WP/MA ratio of 50:50. The methane yield at a ratio WP/MA of 50:50 is higher than for single compound, while for ratios WP/MA of 25:75 and 75:25 the methane yield decreases compared to biomass mono-digestion. This behavior is observed for the three levels of F/I ratio being more noticeable at F/I ratio of 0.3. A synergistic effect was found for the WP/MA ratio of 50:50 and all F/I ratios and for WP/MA=50:50 and F/I=0.2. A maximum increase of methane yield of 49.58% was found for a co-digestion ratio of 50:50 and an F/I ratio of 0.4. It was concluded that methane production from waste paper improves significantly when co-digested with macroalgae biomass. The methane yields from co-digestion were also found higher that from macroalgae mono-digestion.

Keywords: anaerobic co-digestion, biogas, macroalgae, waste paper

Procedia PDF Downloads 347
5269 Stress Recovery and Durability Prediction of a Vehicular Structure with Random Road Dynamic Simulation

Authors: Jia-Shiun Chen, Quoc-Viet Huynh

Abstract:

This work develops a flexible-body dynamic model of an all-terrain vehicle (ATV), capable of recovering dynamic stresses while the ATV travels on random bumpy roads. The fatigue life of components is forecasted as well. While considering the interaction between dynamic forces and structure deformation, the proposed model achieves a highly accurate structure stress prediction and fatigue life prediction. During the simulation, stress time history of the ATV structure is retrieved for life prediction. Finally, the hot sports of the ATV frame are located, and the frame life for combined road conditions is forecasted, i.e. 25833.6 hr. If the usage of vehicle is eight hours daily, the total vehicle frame life is 8.847 years. Moreover, the reaction force and deformation due to the dynamic motion can be described more accurately by using flexible body dynamics than by using rigid-body dynamics. Based on recommendations made in the product design stage before mass production, the proposed model can significantly lower development and testing costs.

Keywords: flexible-body dynamics, veicle, dynamics, fatigue, durability

Procedia PDF Downloads 369
5268 Extraction of M. paradisiaca L. Inflorescences Using Compressed Propane

Authors: Michele C. Mesomo, Madeline de Souza Correa, Roberta L. Kruger, Luis R. S. Kanda, Marcos L. Corazza

Abstract:

Natural extracts of plants have been used for many years for different purposes and recently they have been screened for their potential use as alternative remedies and food preservatives. Inflorescences of M. paradisiaca L., also known as the heart of the banana, have great economic interest due to its fruit. All parts of the banana are used for many different purposes, including use in folk medicine. The use of extraction via supercritical technology has grown in recent years, though it is still necessary to obtain experimental information for the construction of industrial plants. This work reports the extraction of Musa paradisiaca L. using compressed propane as solvent. The effects of the supercritical extraction conditions, pressure and temperature on the yield were evaluated. The raw material, inflorescences banana, was dried at 313.15 K and milled. The particle size used for the packaging of the extraction cell was 12 mesh (23.5%), 16 mesh (23.5%), 32 mesh (34.5%), 48 mesh (18.5%). The extractions were performed in a laboratory scale unit at pressures of 3.0 MPa, 6.5 MPa and 10.0 MPa and at 308.15 K, 323.15 K and 338.15 K. The operating conditions tested achieved a maximum yield of 2.94 wt% for the CO2 extraction at 10.0 MPa and 338.15 K, higher pressure and temperature. The lower yield, 2.29 wt%, was obtained in the condition of lower pressure and higher temperature. Temperature presented significant and positive effect on the extraction yield with supercritical CO2, while pressure had no effect on the yield. The overall extraction curves showed typical behavior obtained for the supercritical extraction procedure and and reached a constant extraction rate of about 80 to 100 min. The largest amount of extract was obtained at the beginning of the process, within 10 to 60 min.

Keywords: banana, natural products, supercritical extraction, temperature

Procedia PDF Downloads 589
5267 Grain Yield, Morpho-Physiological Parameters and Growth Indices of Wheat (Triticum Aestivum L.) Varieties Exposed to High Temperature under Late Sown Condition

Authors: Shital Bangar, Chetana Mandavia

Abstract:

A field experiment was carried out in Factorial Randomized Block Design (FRBD) with three replications at Instructional Farm Krushigadh, Junagadh Agricultural University, Junagadh, India to assess the biochemical parameters of wheat in order to assess the thermotolerance. Nine different wheat varieties GW 433, GW 431, HI 1571, GW 432, RAJ 3765, HD 2864, HI 1563, HD 3091 and PBW 670 sown in timely and late sown conditions (i.e., 22 Nov and 6 Dec 2012) were analysed. All the varieties differed significantly with respect to grain yield morpho-physiological parameters and growth indices for time of sowing, varieties and varieties x time of sowing interactions. The observations on morpho-physiological parameters viz., germination percentage, canopy temperature depression and growth indices viz., leaf area index (LAI), leaf area ratio (LAR) were recorded. Almost all the morpho-physiological parameters, growth indices and grain yield studied were affected adversely by late sowing, registering reduction in their magnitude. Germination percentage was reduced under late sown condition but variety PBW 670 was the best. Varieties GW 432 performed better with respect to canopy temperature depression while sown late. Under late sown condition, variety GW 431 recorded higher LAI while HI 1563 had maximum LAR. Considering yield performance, HD 2864 was best under timely sown condition, while GW 433 was best under late sown condition. Varieties HI 1571, GW 433 and GW 431 could be labelled as thermo-tolerant because there was least reduction in grain yield under late sown condition (1.75 %, 7.90 % and13.8 % respectively). Considering correlation coefficient, grain yield showed very strong significant positive association with germination percentage. Leaf area ratio was strongly and significantly correlated with grain yield but in negative direction. Canopy temperature depression and leaf area index also had positive correlation with grain yield but were non-significant.

Keywords: growth indices, morpho-physiological parametrs, thermo-tolerance, wheat

Procedia PDF Downloads 423