Search results for: genetic resources and new crop varieties

Authors: Koteswara Rao Pagolu, Raghava Rao Tamanam

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In India, genetic disease is a disregarded service element in the community health- protection system. This study aims to gauge the accessibility of services for treating genetic disorders and also to evaluate the practices on deterrence and management services in the district health system. A cross-sectional survey of selected health amenities in the government health sector was conducted from 15 primary health centers (PHC’s), 4 community health centers (CHC’s), 1 district government hospital (DGH) and 3 referral hospitals (RH’s). From these, the existing manpower like 130 medical officers (MO’s), 254 supporting staff, 409 nursing staff (NS) and 45 lab technicians (LT’s) was examined. From the side of private health institutions, 25 corporate hospitals (CH’s), 3 medical colleges (MC’s) and 25 diagnostic laboratories (DL’s) were selected for the survey and from these, 316 MO’s, 995 NS and 254 LT’s were also reviewed. The findings show that adequate staff was in place at more than 70% of health centers, but none of the staff have obtained any operative training on genetic disease management. The largest part of the DH’s had rudimentary infrastructural and diagnostic facilities. However, the greater part of the CHC’s and PHC’s had inadequate diagnostic facilities related to genetic disease management. Biochemical, molecular, and cytogenetic services were not available at PHC’s and CHC’s. DH’s, RH’s, and all selected medical colleges were found to have offered the basic Biochemical genetics units during the survey. The district health care infrastructure in India has a shortage of basic services to be provided for the genetic disorder. With some policy resolutions and facility strengthening, it is possible to provide advanced services for a genetic disorder in the district health system.

Keywords: district health system, genetic disorder, infrastructural amenities, management practices

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Authors: Sonia Bedhiaf-Romdhani

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The sheep (Ovis aries) was domesticated, approximately 11,000 years ago (YBP), in the Fertile Crescent from Asian Mouflon (Ovis Orientalis). The Northern African (NA) sheep is 7,000 years old, represents a remarkable diversity of sheep populations reared under traditional and low input farming systems (LIFS) over millennia. The majority of small ruminants in developing countries are encountered in low input production systems and the resilience of local communities in rural areas is often linked to the wellbeing of small ruminants. Regardless of the rich biodiversity encountered in sheep ecotypes there are four main sheep breeds in the country with 61,6 and 35.4 percents of Barbarine (fat tail breed) and Queue Fine de l’Ouest (thin tail breed), respectively. Phoenicians introduced the Barbarine sheep from the steppes of Central Asia in the Carthaginian period, 3000 years ago. The Queue Fine de l’Ouest is a thin-tailed meat breed heavily concentrated in the Western and the central semi-arid regions. The Noire de Thibar breed, involving mutton-fine wool producing animals, has been on the verge of extinction, it’s a composite black coated sheep breed found in the northern sub-humid region because of its higher nutritional requirements and non-tolerance of the prevailing harsher condition. The D'Man breed, originated from Morocco, is mainly located in the southern oases of the extreme arid ecosystem. A genetic investigation of Tunisian sheep breeds using a genome-wide scan of approximately 50,000 SNPs was performed. Genetic analysis of relationship between breeds highlighted the genetic differentiation of Noire de Thibar breed from the other local breeds, reflecting the effect of past events of introgression of European gene pool. The Queue Fine de l’Ouest breed showed a genetic heterogeneity and was close to Barbarine. The D'Man breed shared a considerable gene flow with the thin-tailed Queue Fine de l'Ouest breed. Native small ruminants breeds, are capable to be efficiently productive if essential ingredients and coherent breeding schemes are implemented and followed. Assessing the status of genetic variability of native sheep breeds could provide important clues for research and policy makers to devise better strategies for the conservation and management of genetic resources.

Keywords: sheep, farming systems, diversity, SNPs.

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Authors: H. Anzai, H. Nakayama, H. Kaminaga, Y. Morimoto, Y. Miyadera, S. Nakamura

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Various research resources such as papers and presentation slides are handled in the process of research activities. It is extremely important for smooth progress of the research to skillfully manage those research resources and utilize them for further investigations. However, number of the research resources increases more and more. Moreover, there are the differences in usage of each kind of research resource and their accumulation styles. So, it is actually difficult to satisfactorily manage and use the accumulated research resources. Therefore, a lack of tidiness of the resources causes the problems such as an oversight of the problem to be polish. Although there have existed research projects on support for management of research resources and for sharing of know-how, almost existing systems have not been effective enough since these systems have not sufficiently considered the polish process. This paper mainly describes a system that enables the strategic management of research resources together with polish process and their practical use.

Keywords: research resource, polish process, information sharing, knowledge management, information visualization

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Authors: Semiarto Aji Purwanto, Sutji Shinto

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Over a quarter century, the idea of sustainable development has become a global discussion. In Indonesia, more than five decades since the development of the country took priority over any other matter, a discussion on the need of development is still an intriguing. Far from the enthusiasm of development programs run by the Indonesian government since 1967, the Dayak community in the interior of Kalimantan tropical forest was significantly abandoned from the changes. There were not many programs for the interior because the focus of development mostly was in Java island. Consequently, the Dayak live their life as shifting cultivator that has been practiced for centuries. Our ethnographic observation conducted in April-July 2016, found that today, they still maintain the knowledge and keeping the existence of local variety of rice. While in Java, these varieties have been replaced by more-productive-and-resistant-to-pest varieties, the Dayak still maintain more than 60s varieties. From the biodiversity’s perspective, it is a delightful news; while from the cultural perspective, the persistence of their custom regarding to the practice of traditional cultivation is fascinating as well. The local knowledge of agriculture is well conserved and practice daily. It is revealed that the resilience of those rice varieties is related to the local social structure since the distribution of each variety usually limited to the particular clans in the community. While experiencing the lack of programs for village development, the community has maintained the local leadership and its government structure at the village level. The paper will explore the effect of how a neglected area, which was disregarded by development program, sustains their culture and biodiversity. We would like to discuss the concept of sustainability whether it needed for the development programs, for the changes into a modern civilisation, or for the sake of the local to survive.

Keywords: sustainable development, local knowledge, rice, resilience, Kalimantan, Indonesia

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Authors: Pramod Kumar Sharma, Pratibha Kumari, Udai Pratap Singh, Sustainability

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In the Indo-Gangetic Plains of South-East Asia, the rice-wheat cropping system (RWCS) is dominant with conventional tillage (CT) without residue management, which shows depletion of soil fertility and non-sustainable crop productivity. Hence, this investigation was planned to identify suitable natural resource management practices involving different tillage and crop establishment (TCE) methods along with crop residue and their effects, on the sustainability of dominant cropping systems through enhancing soil fertility and productivity. This study was conducted for two consecutive years 2018-19 and 2019-20 on a long-term field experiment that was started in the year 2015-16 taking six different combinations of TCE methods viz. CT, partial conservation agriculture (PCA) i.e. anchored residue of rice and full conservation agriculture (FCA)] i.e. anchored residue of rice and wheat under RWCS in terms of crop productivity, sustainability of soil health, and crop nutrition by the crops. Results showed that zero tillage direct-seeded rice (ZTDSR) - zero tillage wheat (ZTW) [FCA + green gram residue retention (RR)] recorded the highest yield attributes and yield during both the crops. Compared to conventional tillage rice (CTR)-conventional tillage wheat (CTW) [residue removal (R 0 )], the soil quality parameters were improved significantly with ZTDSR-ZTW (FCA+RR). Overall, ZTDSR-ZTW (FCA+RR) had higher nutrient uptake by the crops than CT-based treatment CTR-CTW (R 0 ) and CTR-CTW (RI).These results showed that there is significant profitability of yield and resource utilization by the adoption of FCA it may be a better alternative to the dominant tillage system i.e. CT in RWSC.

Keywords: tillage and crop establishment, soil fertility, rice-wheat cropping system, sustainability

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Authors: Ojiegbe Ikenna Nathan

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Obesity is a medical condition in which excess body fat has accumulated to the extent that it leads to reduced life expectancy and or increased health problems. Obesity as a worldwide problem is seen clustered in the families and it moves from generation to generation. It causes some disabilities, mortality and morbidity if left unattended to. The predisposing factors to obesity are either genetic or environment in origin. Nevertheless, the main predisposing factor to obesity is the excessive consumption of food rich in low-density lipoprotein (LDL) such as organ meats, saturated fats etc. This low-density lipoprotein causes an increase in adipose tissue and complicates to obesity. There are varieties of obesity which one needs to take appropriate measures to avoid; such as android, gynoid and morbid obesity. Nonetheless, studies have shown that there is hope for the obese individuals, despite the cause, type and degree of their obesity. This is through the use of the different available treatment measures which increase in physical activities, caloric restrictions, drug therapy and surgical intervention.

Keywords: low-density, lipoprotein, culprit, obesity

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Authors: Nafiseh Noormohammadi, Ahmad Sobhani Najafabadi

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Hypericins (hypericin and pseudohypericin) are natural napthodianthrone derivatives produced by Hypericum perforatum (St. John’s Wort), which have many medicinal properties such as antitumor, antineoplastic, antiviral, and antidepressant activities. Production and accumulation of hypericin in the plant are influenced by both genetic and environmental conditions. Despite the existence of different high-throughput data on the plant, genetic dimensions of hypericin biosynthesis have not yet been completely understood. In this research, 21 high-quality RNA-seq data on different parts of the plant were integrated into metabolic data to reconstruct a coexpression network. Results showed that a cluster of 30 transcripts was correlated with total hypericin. The identified transcripts were divided into three main groups based on their functions, including hypericin biosynthesis genes, transporters, detoxification genes, and transcription factors (TFs). In the biosynthetic group, different isoforms of polyketide synthase (PKSs) and phenolic oxidative coupling proteins (POCPs) were identified. Phylogenetic analysis of protein sequences integrated into gene expression analysis showed that some of the POCPs seem to be very important in the biosynthetic pathway of hypericin. In the TFs group, six TFs were correlated with total hypericin. qPCR analysis of these six TFs confirmed that three of them were highly correlated. The identified genes in this research are a rich resource for further studies on the molecular breeding of H. perforatum in order to obtain varieties with high hypericin production.

Keywords: hypericin, St. John’s Wort, data mining, transcription factors, secondary metabolites

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Authors: Soungwan Kim

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This paper discusses an analysis of how the characteristics of resources at vocational rehabilitation facilities for the disabled affect the improvement of independency skills among people with severe disabilities. The analysis results indicate that more internal financial resources and more connections to local communities among network resources had greater effects on improving the independency of people with severe disabilities. Based on this result, this paper presents strategies for mobilizing resources to improve the independency of people with severe disabilities at vocational rehabilitation facilities.

Keywords: vocational rehabilitation facility for people with disabilities, types of resources, independency, network resources

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Authors: Giacomo Barbieri

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In soilless culture, the management of the nutrient solution is the most important aspect for crop growing. Fertigation dose, frequency and nutrient concentration must be planned with the objective of reaching an optimal crop growth by limiting the utilized resources and the associated costs. The definition of efficient fertigation strategies is a complex problem since fertigation requirements vary on the basis of different factors, and crops are sensitive to small variations on fertigation parameters. To the best of author knowledge, a small-scale test bench that is flexible for both nutrient solution preparation and precise irrigation is currently missing, limiting the investigations in standard practices for soilless culture. Starting from the analysis of the state of the art, this paper proposes a small-scale system that is potentially able to concurrently test different fertigation strategies. The system will be designed and implemented throughout a three year project started on August 2018. However, due to the importance of the topic within current challenges as food security and climate change, this work is spread considering that may inspire other universities and organizations.

Keywords: soilless culture, fertigation, test bench, small-scale, automation

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Authors: Arega Shumetie Ademe, Belay Kassa, Degye Goshu, Majaliwa Mwanjalolo

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Currently the world economy is suffering from one critical problem, climate change. Some studies done before identified that impact of the problem is region specific means in some part of the world (temperate zone) there is improvement in agricultural performance but in some others like in the tropics there is drastic reduction in crop production and crop income. Climate variability is becoming dominant cause of short-term fluctuation in rain-fed agricultural production and income of developing countries. The purely rain-fed Ethiopian agriculture is the most vulnerable sector to the risks and impacts of climate variability. Thus, this study tried to identify impact of climate variability on crop income of smallholders in Ethiopia. The research used eight rounded unbalanced panel data from 1994- 2014 collected from six villages in the study area. After having all diagnostic tests the research used fixed effect method of regression. Based on the regression result rainfall and temperature deviation from their respective long term averages have negative and significant effect on crop income. Other extreme devastating shocks like flood, storm and frost, which are sourced from climate variability, have significant and negative effect on crop income of households’. Parameters that notify rainfall inconsistency like late start, variation in availability at growing season, and early cessation are critical problems for crop income of smallholder households as to the model result. Given this, impact of climate variability is not consistent in different agro-ecologies of the country. Rainfall variability has similar impact on crop income in different agro-ecology, but variation in temperature affects cold agro-ecology villages negatively and significantly, while it has positive effect in warm villages. Parameters that represent rainfall inconsistency have similar impact in both agro-ecologies and the aggregate model regression. This implies climate variability sourced from rainfall inconsistency is the main problem of Ethiopian agriculture especially the crop production sub-sector of smallholder households.

Keywords: climate variability, crop income, household, rainfall, temperature

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Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

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Authors: Ferinar Moaidi, Mahdi Moaidi

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Environmental issues and the ever-increasing in demand of electrical energy make it necessary to have distributed generation (DG) resources in the power system. In this research, in order to realize the goals of reducing losses and improving the voltage profile in a microgrid, the allocation and sizing of DGs have been used. The proposed Genetic Algorithm (GA) is described from the array of artificial intelligence methods for solving the problem. The algorithm is implemented on the IEEE 33 buses network. This study is presented in two scenarios, primarily to illustrate the effect of location and determination of DGs has been done to reduce losses and improve the voltage profile. On the other hand, decisions made with the one-level assumptions of load are not universally accepted for all levels of load. Therefore, in this study, load modelling is performed and the results are presented for multi-levels load state.

Keywords: distributed generation, genetic algorithm, microgrid, load modelling, loss reduction, voltage improvement

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Moheb R. Girgis, Tarek M. Mahmoud, Bahgat A. Abdullatif, Ahmed M. Rabie

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Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions.

Keywords: wireless mesh networks, genetic algorithms, simulated annealing, topology design

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Mehdi Rostamzadeh

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Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

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Authors: M. A. Rubio, A. Urquia

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Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.

Keywords: optimization, sensitivity, genetic algorithms, model calibration

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Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

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Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

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Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno

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The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective and management

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Authors: Zia Amjad, Salem S. Alghamdi

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This experiment was carried out at student educational farm College of Food and Agriculture, KSU, kingdom of Saudi Arabia; in order to characterize 154 V. faba accessions based on UPOV and IBPGR descriptors. 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e. principle component analysis (PCA). First six principle components (PC) had Eigen-value greater than one; accounted for 72% of available V. faba genetic diversity. However first three components revealed more than 10% of genetic diversity each i.e. 22.36%, 15.86% and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1 which represented 22.36% of the genetic diversity was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1) and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant.

Keywords: agro morphological characterization, diversity, vicia faba, PCA

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Authors: Mthiyane Pretty, Mitsui Toshiake, Aycan Murat, Nagano Hirohiko

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Methane (CH₄) is one of the most dangerous greenhouse gases (GHG) emitted into the atmosphere by terrestrial ecosystems, with a global warming potential (GWP) 25-34 times that of CO2 on a centennial scale. Paddy rice cultivations are a major source of methane emission and is the major driving force for climate change. Thus, it is necessary to find out GHG emissions mitigation strategies from rice cultivation. A study was conducted at Niigata University. And the prime objective of this research was to determine the effects of rice varieties CH4 lowland (NU1, YNU, Nipponbare, Koshihikari) and upland (Norin 1, Norin 24, Hitachihatamochi) japonica rice varieties using different growth media which was paddy field soil and artificial soil. The treatments were laid out in a split plot design. The soil moisture was kept at 40-50% and 70%, respectively. The CH₄ emission rates were determined by collecting air samples using the closed chamber technique and measuring CH₄ concentrations using a gas chromatograph. CH₄ emission rates varied with the growth, growth media type and development of the rice varieties. The soil moisture was monitored at a soil depth of 5–10 cm with an HydraGO portable soil sensor system every three days for each pot, and temperatures were be recorded by a sensitive thermometer. The lowest cumulative CH4 emission rate was observed in Norin 24, particularly under 40 to 50% soil moisture. Across the rice genotypes, 40-50% significantly reduced the cumulative CH4 , followed by irrigation of 70% soil moisture. During the tillering stage, no significant variation in tillering and plant height was observed between and 70% soil moisture. This study suggests that the cultivation of Norin 24 and Norin 1 under 70% soil irrigation could be effective at reducing the CH4 in rice fields.

Keywords: methane, paddy fields, rice varieties, soil moisture

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Larry V. Aceres, Jesryl B. Paulite, Emelie M. Pelicano, J. B. Anciano, J. A. Esteban

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Enhancing the population of beneficial arthropods under less diverse agroecosystem is the most sought by many researchers and plant growers. This strategy was done through the establishment of pintoi peanut, Arachis pintoi as live mulch or cover crop in pummelo orchard of the University of Southeastern Philippines (USeP), Mabini, Compostela Valley Province, Philippines. This study was conducted to compare and compute population dynamics and diversity of beneficial arthropods in pummelo in with and without Arachis pintoi cover crop. Data collections were done for the 12-month period (from June 2013 to May 2014) at the pummelo orchard of USeP Mabini Campus, COMVAL Province, Philippines and data were analyzed using the Independent Samples T-Test to compare the effect of the presence and absence of Arachis pintoi on beneficial arthropods incidence in pummelo orchard. Moreover, diversity and family richness analyses were computed using the Margalef’s diversity index for family richness; the Shannon index of general diversity and the evenness index; and the Simpson index of dominance. Results revealed numerically and statistically higher density of important beneficial arthropods such as microhymenopterans, macrohymenopterans, spiders, tachinid flies and ground beetles were recorded in pummelo orchard with Arachis pintoi than from without Arachis pintoi cover crop for the 12-month observation period. Further, the result of the study revealed the high family richness and diversity index with more or less even distribution of individuals within the family and low dominance index were documented in pummelo with Arachis pintoi cover crop than from pummelo without Arachis pintoi cover crop. The study revealed that planting A. pintoi in pummelo orchard could enhance natural enemy populations.

Keywords: Arachis pintoi, cover crop, beneficial arthropods, pummelo

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Authors: Mkhize Xolile, Davies Theopheluis

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The purpose of the study was to develop a variety of fruit, vegetable and indigenous wild herb (amaranth) based juices, which can increase mineral consumption (of Ca, Fe, K, Mg, Zn). Ten samples of juice varieties were developed. The concentration range for the standards was between 10 and 150 ppm. Standards and samples were analysed using Perkin Elmer Atomic Absorption Spectrophotometer and the AAnalyst 400 model was used. The indigenous herb based juice was the most nutritious than all the other varieties developed. Mg and Fe could contribute significantly in improving cardio vascular health, bone functionality and immunity of elderly.

Keywords: minerals, elderly, juice, hypertension, intervention

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Authors: Nadeem Munawar, Tariq Mahmood

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Habitat manipulation is an important technique that can be used for controlling rodent damage in agricultural ecosystems. It involves intentionally manipulation of vegetation cover in adjacent habitats around the active burrows of rodents to reduce shelter, food availability and to increase predation pressure. The current study was conducted in the Pothwar Plateau during the respective non-crop period of wheat-groundnut (post-harvested and un-ploughed/non-crop fallow lands) with the aim to assess the impact of the reduction in vegetation height of adjacent habitats (field borders) on rodent’s richness and abundance. The study area was divided into two sites viz. treated and non-treated. At the treated sites, habitat manipulation was carried out by removing crop cache, and non-crop vegetation’s over 10 cm in height to a distance of approximately 20 m from the fields. The trapping sessions carried out at both treated and non-treated sites adjacent to wheat-groundnut fields were significantly different (F 2, 6 = 13.2, P = 0.001) from each other, which revealed that a maximum number of rodents were captured from non-treated sites. There was a significant difference in the overall abundance of rodents (P < 0.05) between crop stages and between treatments in both crops. The manipulation effect was significantly observed on damage to crops, and yield production resulted in the reduction of damage within the associated croplands (P < 0.05). The outcomes of this study indicated a significant reduction of rodent population at treated sites due to changes in vegetation height and cover which affect important components, i.e., food, shelter, movements and increased risk sensitivity in their feeding behavior; therefore, they were unable to reach levels where they cause significant crop damage. This method is recommended for being a cost-effective and easy application.

Keywords: agricultural ecosystems, crop damage, habitat manipulation, rodents, trapping

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

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This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

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Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

Abstract:

Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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Authors: Chandanee Wasana Kalansooriya

Abstract:

Dietary behaviour is a crucial factor affecting diabetes control. With increasing rates of diabetes prevalence in Asian countries, examining their dietary patterns, which are largely based on rice, is timely required. It has been identified that higher consumption of some rice varieties is associated with increased risk of type 2 diabetes. Although diabetes patients are advised to consume healthier rice varieties, which contains low glycemic, several conditions, one of which food insecurity, make them difficult to preserve those healthy dietary guidelines. Hence this study tries to investigate how food security affects on making right decisions of rice consumption within diabetes affected households using a sample from Sri Lanka, a country which rice considered as the staple food and records the highest diabetes prevalence rate in South Asia. The study uses data from the Household Income and Expenditure Survey 2016, a nationally representative sample conducted by the Department of Census and Statistics, Sri Lanka. The survey used a two-stage stratified sampling method to cover different sectors and districts of the country and collected micro-data on demographics, health, income and expenditures of different categories. The study uses data from 2547 households which consist of one or more diabetes patients, based on the self-recorded health status. The Household Dietary Diversity Score (HDDS), which constructed based on twelve food groups, is used to measure the level of food security. Rice is categorized into three groups according to their Glycemic Index (GI), high GI, medium GI and low GI, and the likelihood and impact made by food security on each rice consumption categories are estimated using a Two-part Model. The shares of each rice categories out of total rice consumption is considered as the dependent variable to exclude the endogeneity issue between rice consumption and the HDDS. The results indicate that the consumption of medium GI rice is likely to increase with the increasing household food security, but low GI varieties are not. Households in rural and estate sectors are less likely and Tamil ethnic group is more likely to consume low GI rice varieties. Further, an increase in food security significantly decreases the consumption share of low GI rice, while it increases the share of medium GI varieties. The consumption share of low GI rice is largely affected by the ethnic variability. The effects of food security on the likelihood of consuming high GI rice varieties and changing its shares are statistically insignificant. Accordingly, the study concludes that a higher level of food security does not ensure diabetes patients are consuming healthy rice varieties or reducing consumption of unhealthy varieties. Hence policy attention must be directed towards educating people for making healthy dietary choices. Further, the study provides a room for further studies as it reveals considerable ethnic and sectorial differences in making healthy dietary decisions.

Keywords: diabetes, food security, glycemic index, rice consumption

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Authors: A. H. Nanher, N. P. Singh

Abstract:

In India, Agriculture is largely in rice- based cropping system. It has indicated decline in factor productivity along with emergence of multi - nutrient deficiency, buildup of soil pathogen and weed flora because it operates and removes nutrients from the same rooting depth. In designing alternative cropping systems, the common approaches are crop intensification, crop diversification and cultivar options. The intensification leads to the diversification of the cropping system. Intensification is achieved by introducing an additional component crop in a pre-dominant sequential system by desirable adjustments in cultivars of one or all the component crops. Invariably, this results in higher land use efficiency and productivity per unit time Crop Diversification through such crop and inclusion of fodder crops help to improve the economic situation of small and marginal farmers because of higher income. Inclusion of crops in sequential and intercropping systems reduces some obnoxious weeds through formation of canopies due to competitive planting pattern and thus provides an opportunity to utilize cropping systems as a tool of weed management with non-chemical means. Use of organic source not only acts as supplement for fertilizer (nitrogen) but also improve the physico-chemical properties of soils. Production and use of nitrogen rich biomass offer better prospect for supplementing chemical fertilizers on regular basis. Such biological diversity brings yield and economic stability because of its potential for compensation among components of the system. In a particular agro-climatic and resource condition, the identification of most suitable crop sequence is based on its productivity, stability, land use efficiency as well as production efficiency and its performance is chiefly judged in terms of productivity and net return.

Keywords: integrated farming systems, sustainable intensification, system of crop intensification, wheat

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Authors: Farahnaz Amini, Woo Yun Kin, Lazwani Kolandaiveloo

Abstract:

Availability of different genetic tests after completion of Human Genome Project increases the physicians’ responsibility to keep themselves update on the potential implementation of these genetic tests in their daily practice. However, due to numbers of barriers, still many of physicians are not either aware of these tests or are not willing to offer or refer their patients for genetic tests. This study was conducted an anonymous, cross-sectional, mailed-based survey to develop a primary data of Malaysian physicians’ level of knowledge and perception of gene profiling. Questionnaire had 29 questions. Total scores on selected questions were used to assess the level of knowledge. The highest possible score was 11. Descriptive statistics, one way ANOVA and chi-squared test was used for statistical analysis. Sixty three completed questionnaires was returned by 27 general practitioners (GPs) and 36 medical specialists. Responders’ age range from 24 to 55 years old (mean 30.2 ± 6.4). About 40% of the participants rated themselves as having poor level of knowledge in genetics in general whilst 60% believed that they have fair level of knowledge. However, almost half (46%) of the respondents felt that they were not knowledgeable about available genetic tests. A majority (94%) of the responders were not aware of any lab or company which is offering gene profiling services in Malaysia. Only 4% of participants were aware of using gene profiling for detection of dosage of some drugs. Respondents perceived greater utility of gene profiling for breast cancer (38%) compared to the colorectal familial cancer (3%). The score of knowledge ranged from 2 to 8 (mean 4.38 ± 1.67). Non-significant differences between score of knowledge of GPs and specialists were observed, with score of 4.19 and 4.58 respectively. There was no significant association between any demographic factors and level of knowledge. However, those who graduated between years 2001 to 2005 had higher level of knowledge. Overall, 83% of participants showed relatively high level of perception on value of gene profiling to detect patient’s risk of disease. However, low perception was observed for both statements of using gene profiling for general population in order to alter their lifestyle (25%) as well as having the full sequence of a patient genome for the purpose of determining a patient’s best match for treatment (18%). The lack of clinical guidelines, limited provider knowledge and awareness, lack of time and resources to educate patients, lack of evidence-based clinical information and cost of tests were the most barriers of ordering gene profiling mentioned by physicians. In conclusion Malaysian physicians who participate in this study had mediocre level of knowledge and awareness in gene profiling. The low exposure to the genetic questions and problems might be a key predictor of lack of awareness and knowledge on available genetic tests. Educational and training workshop might be useful in helping Malaysian physicians incorporate genetic profiling into practice for eligible patients.

Keywords: gene profiling, knowledge, Malaysia, physician

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