Genetic Analysis of Tolerance to Rice Tungro Bacilliform Virus in Rice (Oryza sativa L.) Through Agroinoculation

Balimau Putih [an Indonesian cultivar tolerant to rice tungro bacilliform virus (RTBV)] was crossed with IR64 (RTBV, susceptible variety) to produce the three filial generations F1, F2 and F3. Agroinoculation was used to introduce RTBV into the test plants. RTBV tolerance was based on the RTBV level in plants by analysis of coat protein using enzyme-linked immunosorbent assay. The level of RTBV in cv. Balimau Putih was significantly lower than that of IR64 and the susceptible control, Taichung Native 1. Mean RTBV levels of the F1, F2 and F3 populations were comparable with one another and with the average of the parents. Results indicate that there was no dominance and an additive gene action may control the expression of tolerance to RTBV. Tolerance based on the level of RTBV coat protein was highly heritable (0.67) as estimated using the mean values of F3 lines, suggesting that selection for tolerance to RTBV can be performed in the early selfing generations using the technique employed in this study. The RTBV level had a negative correlation with plant height, but positive relationship with disease index value

Optimization of long rural feeders using a genetic algorithm

This paper describes the optimization of conductor size and the voltage regulator location & magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.

Dynamic coast control of train movement with genetic algorithm

The railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. Train service usually varies with the population activities throughout a day and train coordination and service regulation are then expected to meet the daily passengers' demand. Dwell time control at stations and fixed coasting point in an inter-station run are the current practices to regulate train service in most metro railway systems. However, a flexible and efficient train control and operation is not always possible. To minimize energy consumption of train operation and make certain compromises on the train schedule, coast control is an economical approach to balance run-time and energy consumption in railway operation if time is not an important issue, particularly at off-peak hours. The capability to identify the starting point for coasting according to the current traffic conditions provides the necessary flexibility for train operation. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigates the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. Further, a hierarchical genetic algorithm (HGA) is introduced here to identify the number of coasting points required according to the traffic conditions, and Minimum-Allele-Reserve-Keeper (MARK) is adopted as a genetic operator to achieve fitter solutions.

Railway junction conflict resolution by genetic algorithm

In general, simple and traditional methods are applied to resolve traffic conflicts at railway junctions. They are, however, either inefficient or computationally demanding. A simple genetic algorithm is presented to enable a search for a near optimal resolution to be carried out while meeting the constraints on generation evolution and minimising the search time.

Signalling layout for fixed-block railway lines with real-coded genetic algorithms.

Signalling layout design is one of the keys to railway operations with fixed-block signalling system and it also carries direct effect on overall train efficiency and safety. Based on an analysis to system objectives, this paper presents an optimization model with two objectives in order to devise an efficient signalling layout scheme. Taking into account the present railway line design practices in China, the paper describes steps of the computer-based signalling layout optimisation with real-coded genetic algorithms. A computer-aided system, based on train movement simulator, has also been employed to assist the optimisation process. A case study on a practical railway line has been conducted to make comparisons between the proposed GA-based approach and the current practices. The results illustrate the improved performance of the proposed approach in reducing signal block joints and shortening minimum train service headway.

Coast control of train movement with genetic algorithms

Railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. We present an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigate the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. The multiple coasting point control with hierarchical genetic algorithm (HGA) is then proposed to integrate the determination of the number of coasting points.

Coasting control of train operation by genetic algorithm

Balancing between the provision of high quality of service and running within a tight budget is one of the biggest challenges for most metro railway operators around the world. Conventionally, one possible approach for the operator to adjust the time schedule is to alter the stop time at stations, if other system constraints, such as traction equipment characteristic, are not taken into account. Yet it is not an effective, flexible and economical method because the run-time of a train simply cannot be extended without limitation, and a balance between run-time and energy consumption has to be maintained. Modification or installation of a new signalling system not only increases the capital cost, but also affects the normal train service. Therefore, in order to procure a more effective, flexible and economical means to improve the quality of service, optimisation of train performance by coasting point identification has become more attractive and popular. However, identifying the necessary starting points for coasting under the constraints of current service conditions is no simple task because train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting points and investigates the possible improvement on computation time and fitness of genes.

Hierarchical fuzzy logic traffic control at a road junction using genetic algorithms

Traffic control at a road junction by a complex fuzzy logic controller is investigated. The increase in the complexity of junction means more number of input variables must be taken into account, which will increase the number of fuzzy rules in the system. A hierarchical fuzzy logic controller is introduced to reduce the number of rules. Besides, the increase in the complexity of the controller makes formulation of the fuzzy rules difficult. A genetic algorithm based off-line leaning algorithm is employed to generate the fuzzy rules. The learning algorithm uses constant flow-rates as training sets. The system is tested by both constant and time-varying flow-rates. Simulation results show that the proposed controller produces lower average delay than a fixed-time controller does under various traffic conditions.

Optimisation of a class of transportation problems using genetic algorithms

This paper presents a Genetic Algorithms (GA) approach to search the optimized path for a class of transportation problems. The formulation of the problems for suitable application of GA will be discussed. Exchanging genetic information in the sense of neighborhoods will be introduced for generation reproduction. The performance of the GA will be evaluated by computer simulation. The proposed algorithm use simple coding with population size 1 converged in reasonable optimality within several minutes.

12 fingers or one, it’s how you play? Genetic discrimination in the Australian workforce

For quite some time, debate has raged about what the human race can and should do with its knowledge of genetics. We are now nearly 60 years removed from the work of Watson and Crick who determined the structure of deoxyribonucleic acid (DNA), yet our opinions as how best to employ scientific knowledge of the human genome, remain as diverse and polarised as ever. Human judgment is often shaped and coloured by popular media and culture, so it should come as no surprise that box office movies such as Gattaca (1997) continue to play a role in informing public opinion on genetics. In order to perform well at the box office, movies such as Gattaca take great liberty in sensationalising (and even distorting) the implications that may result from genetic screening and testing. If the public’s opinion on human genetics is strongly derived from the box office and popular media, then it is no wonder that the discourse on human genetics is couched in the polar parlances of future utopias or future dystopias. When legislating in an area like genetic discrimination in the workforce, we must be mindful of not overplaying the causal link between genetic predisposition towards a disability and an employee’s ability to perform the inherent requirements of their job. Genetic information is ultimately about people, it is not about genes. Genetic discrimination is ultimately about actions, it is not about the intrinsic value of genetic information.

Genetic resources in wild and cultured stocks of the Asian mud crab, Scylla paramamosain

The mud crab (Scylla spp.) aquaculture industry has expanded rapidly in recent years in many countries in the Indo - West Pacific (IWP) region as an alternative to marine shrimp culture because of significant disease outbreaks and associated failures of many shrimp culture industries in the region. Currently, practices used to produce and manage breeding crabs in hatcheries may compromise levels of genetic diversity, ultimately compromising growth rates, disease resistance and stock productivity. Therefore, to avoid “genetic pollution” and its harmful effects and to promote further development of mud crab aquaculture and fisheries in a sustainable way, a greater understanding of the genetic attributes of wild and cultured mud crab stocks is required. Application of these results can provide benefits for managing wild and cultured Asian mud crab populations for multiple purposes including for commercial production, recreation and conservation and to increase profitability and sustainability of newly emerging crab culture industries. Phylogeographic patterns and the genetic structure of Asian mud crab populations across the IWP were assessed to determine if they were concordant with those of other widespread taxa possessing pelagic larvae of relatively long duration. A 597 bp fragment of the mitochondrial DNA COI gene was amplified and screened for variation in a total of 297 individuals of S. paramamosain from six sampling sites across the species’ natural geographical distribution in the IWP and 36 unique haplotypes were identified. Haplotype diversities per site ranged from 0.516 to 0.879. Nucleotide diversity estimates among haplotypes were 0.11% – 0.48%. Maximum divergence observed among S. paramamosain samples was 1.533% and samples formed essentially a single monophyletic group as no obvious clades were related to geographical location of sites. A weak positive relationship was observed however, between genetic distance and geographical distance among sites. Microsatellite markers were then used to assess contemporary gene flow and population structure in Asian mud crab populations sampled across their natural distribution in the IWP. Eight microsatellite loci were screened in sampled S. paramamosain populations and all showed high allelic diversity at all loci in sampled populations. In total, 344 individuals were analysed, and 304 microsatellite alleles were found across the 8 loci. The mean number of alleles per locus at each site ranged from 20.75 to 28.25. Mean allelic richness per site varied from 17.2 to 18.9. All sites showed high levels of heterozygosity as average expected heterozygosities for all loci ranged from 0.917 – 0.953 while mean observed heterozygosity ranged from 0.916 – 0.959. Allele diversities were similar at all sites and across all loci. The results did not show any evidence for major differences in allele frequencies among sites and patterns of allele frequencies were very similar in all populations across all loci. Estimates of population differentiation (FST) were relatively low and most probably largely reflect intra – individual variation for very highly variable loci. Results from nDNA analysis showed evidence for only very limited population genetic structure among sampled S. paramamosain, and a positive and significant association for genetic and geographical distance among sample sites. Microsatellite markers were then employed to determine if adequate levels of genetic diversity has been captured in crab hatcheries for the breeding cycle. The results showed that all microsatellite loci were polymorphic in hatchery samples. Culture populations were in general, highly genetically depauperate, compared with comparable wild populations, with only 3 to 8 alleles recorded for the same loci set per population. In contrast, very high numbers of alleles per locus were found in reference wild S. paramamosain populations, which ranged from 18 to 46 alleles per locus per population. In general, this translates into a 3 to 10 fold decline in mean allelic richness per locus in all culture stocks compared with wild reference counterparts. Furthermore, most loci in all cultured S. paramamosain samples showed departures from HWE equilibrium. Allele frequencies were very different in culture samples from that present in comparable wild reference samples and this in particular, was reflected in a large decline in allele diversity per locus. The pattern observed was best explained by significant impacts of breeding practices employed in hatcheries rather than natural differentiation among wild populations used as the source of brood stock. Recognition of current problems and management strategies for the species both for the medium and long-term development of the new culture industry are discussed. The priority research to be undertaken over the medium term for S. paramamosain should be to close the life cycle fully to allow individuals to be bred on demand and their offspring equalised to control broodstock reproductive contributions. Establishing a broodstock register and pedigree mating system will be required before any selection program is implemented. This will ensure that sufficient genetic variation will be available to allow genetic gains to be sustainably achieved in a future stock improvement program. A fundamental starting point to improve hatchery practices will be to encourage farmers and hatchery managers to spawn more females in their hatcheries as it will increase background genetic diversity in culture stocks. Combining crablet cohorts from multiple hatcheries into a single cohort for supply to farmers or rotation of breeding females regularly in hatcheries will help to address immediate genetic diversity problems in culture stocks. Application of these results can provide benefits for managing wild and cultured Asian mud crab populations more efficiently. Over the long-term, application of data on genetic diversity in wild and cultured stocks of Asian mud crab will contribute to development of sustainable and productive culture industries in Vietnam and other countries in the IWP and can contribute towards conservation of wild genetic resources.