Evaluation and Modeling of Residual Chlorine in Dangila Town Water Supply System

Application of chlorine for protection of drinking water in distribution system is not well established for the Dangila town. The study was conducted to assess chlorine dosing and model for residual chlorine using Water CAD software. The necessary dates were collected using primary and secondary sources. The existing maximum residual chlorine concentration at sample point 6 through the samples by 1.5 kg/m3 chlorine dose with 3 ml/s flow rates was found to be 0.17 mg/l. Even, it was less than the minimum recommended WHO and ESA standard (0.2mg/l). The amount of total Coliform was found 5 colonies per 100ml and pH (8.68-9.1) and the remaining main chemical water quality parameters that analyses were found within WHO & ESA limits. In order to model the residual chlorine content 3 scenarios were developed. Scenario I and II were developed with 0.6 mg/l chlorine dose with 26 ml/s flow rate and 0.5 mg/l chlorine dose with 22 ml/s flow rate, respectively. In both scenarios residual chlorine concentration was recorded above the maximum limits (0.5mg/l) around the injection point which is a bit higher than the maximum limit, while 4 sample points got less than 0.2mg/l. Scenario II, all residual chlorine results were below 0.5 mg/l, but still the farthest 4 sample points got lower than 0.2mg/l.  To solve the above problem Scenario III was developed with three injection points at reservoir, Junction 4 & 55`` within 0.45, 0.15 and 0.2 mg/l chlorine dose to keep the residual chlorine concentration acceptable. Therefore, installing two additional chlorine injection points were the best solution that identified from the analysis. Keywords: Residual chlorine, Water quality and Water CAD DOI: 10.7176/CER/12-1-01 Publication date: January 31st 202

Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F(2)-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F(2)-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set

Principles, requirements and prospects of genetic mapping in plants

Genetic mapping (also known as linkage mapping or meiotic mapping) refers to the determination of the relative position and distances between markers along chromosomes. Genetic map distancesbetween two markers are defined as the mean number of recombination events, involving a given chromatid, in that region per meiosis. Genetic map construction requires that the researcher developappropriate mapping population, decide the sample size and type of molecular marker(s) for genotyping, genotype the mapping population with sufficient number of markers, and perform linkageanalyses using statistical programs. The construction of detailed genetic maps with high levels of genome coverage is a first step for localizing genes or quantitative trait loci (QTL) that are associatedwith economically important traits, marker assisted selection, comparative mapping between different species, a framework for anchoring physical maps, and the basis for map-based cloning of genes.Highly reproducible, high throughput, codominant, and transferable molecular markers, especially developed from expressed regions, are sought to increase the utility of genetic maps. This articlereviews the principles, requirements, and future prospects of genetic mapping in plants

Patterns of phenotypic variation in endod (Phytolacca dodecandra) from Ethiopia

The extent of morphological variability of endod (Phytolacca dodecandra) sampled from 17 localities in Ethiopia that varied from 1600 to 3000 meters above sea level (m.a.s.l) was investigated using 16 characters. Statistical analyses were performed using leaf hairiness and altitude as categorical variables. Cluster analysis performed using average taxonomic distance matrix revealed the separation of most plants into their respective leaf hairiness and altitude groups. When leaf hairiness was used as categorical variable, canonical discriminant analysis performed using characters selected by the stepwise procedure revealed the distinct separation of all glabrous plants from the pubescent ones with the slightly pubescent plants being intermediate. Classificatory discriminant analysis was used to assign 95.8% of the plants into their respective hairiness groups. Our data therefore support the hypothesis that pubescent forms are highly likely to be a different taxon. For altitude groups, canonical discriminant analysis performed using characters selected by the stepwise procedure resulted to the separation of most plants into lowland (1600-2100 m.a.s.l.), central highlands (2101-2500 m.a.s.l.), and highland (2501-3000 m.a.s.l) groups. Classificatory discriminant analysis was able to assign 70.8% of the plants into their respective altitude groups. However, all results from discriminant analyses of the morphological data were not strong enough to support the presence of morphological ecotypes in endod along altitudinal gradients. Key Words: Altitude, endod, morphological variation, Phytolacca dodecandra, pubescence. African Journal of Biotechnology Vol.3(1) 2004: 32-3

Associations among Yield and Yield-related Characters in Potato (Solanum tuberosum L.)

Twenty potato (Solanum tuberosum L.) genotypes were tested at Ankober (3100 masl), Ethiopia, during the 2002 main rainy season to estimate the nature  and magnitude of correlations and path coefficient analysis among eleven characters. The experiment was laid out in RCB design with three replications  on a plot size of 6.75 m2. Highly significant differences (P < 0.01) were observed among the genotypes for all the characters studied. The result of the  experiment indicated that though genotypic correlations were higher in magnitude than that of phenotypic correlations, the direction of phenotypic  correlation coefficients were the same as that of corresponding genotypic ones for majority of the characters. At genotypic level, tuber yield per plant  was positively and significantly (P < 0.01) correlated with stem number per hill (rg = 0.588) and leaf area per plant (rg = 0.759). Path coefficient analysis at  genotypic level also indicated that these characters had positive indirect effects on tuber yield via tuber number per plant. This result suggested the  possibility of simultaneous selection of stem number per hill and leaf area per plant with tuber number per plant to maximize tuber yield. Path coefficient  analysis at genotypic level further indicated that average tuber weight, tuber number per plant, above ground biomass and internode  number are important components of tuber yield per plant. Positive and high magnitude direct effect of average tuber weight and tuber number per  plant, and their relatively high negative indirect effects on tuber yield per plant via each other indicated the need to be cautious during simultaneous  selection for improving tuber yield per plant.&nbsp

An overview of molecular marker methods for plants

The development and use of molecular markers for the detection and exploitation of DNA polymorphism is one of the most significant developments in the field of molecular genetics. The presence of various types of molecular markers, and differences in their principles, methodologies, and applications require careful consideration in choosing one or more of such methods. No molecular markers are available yet that fulfill all requirements needed by researchers. According to the kind of study to be undertaken, one can choose among the variety of molecular techniques, each of which combines at least some desirable properties. This article provides detail review for 11 different molecular marker methods: restriction fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), inter-simple sequencerepeats (ISSRs), sequence characterized regions (SCARs), sequence tag sites (STSs), cleaved amplified polymorphic sequences (CAPS), microsatellites or simple sequence repeats (SSRs), expressedsequence tags (ESTs), single nucleotide polymorphisms (SNPs), and diversity arrays technology (DArT)

Progress and prospects of marker assisted backcrossing as a tool in crop breeding programs

Marker assisted backcrossing (MAB) is one of the most anticipated and frequently cited benefits of molecular markers as indirect selection tools in breeding programs. However, routine implementationsof MAB in ongoing plant breeding programs are still scarce. Currently MAB of single gene is perhaps the most powerful approach that uses DNA markers effectively. Improvement of quantitative traits loci(QTLs) through MAB resulted to variable results ranging from limited success and/or even a failure to a few highly successful stories. A major constraint to the implementation of MAB in pragmatic breedingprograms has been the high relative cost compared to conventional phenotypic selection. It is a popular misconception that a ‘DNA fingerprint’ is always to be preferred. To be useful to plant breeders,gains made from MAB must be more cost-effective than gains through traditional breeding or MAB must generate significant time savings, which justifies the additional cost involved. Currently, mostnational agricultural research systems (NARS) in Africa have either no or very limited facilities, skilled manpower, and financing for integrating molecular markers as part of their breeding programs. Therefore, conventional breeding methods remain the main option for NARS for many years to come, but targeted use of MAB may become a supplement if well-validated markers are developed or availablethrough collaboration with the international agricultural research centers. This paper provides detail review of the current literature on MAB, including requirements and selected experimental results

Microsatellites and agronomic traits for assessing genetic relationships among 18 New Rice for Africa (NERICA) varieties

The Africa Rice Center (WARDA) has developed several interspecific rice varieties by crossing the high yielding Asian rice (Oryza sativa subsp. japonica) with the locally adapted African rice (Oryza glaberrima). Eighteen varieties were named with the prefix NERICA (New Rice for Africa) but theirgenetic difference and patterns of relationship is largely unknown. A total of 102 polymorphic microsatellite markers were used to genotype 18 NERICAs. A subset of seven NERICAs (NERICA 1 to 7) was further characterized for 10 agronomic traits. The microsatellites data revealed no genetic difference between NERICA 8 and 9. The absence of genetic distance and identical SSR haplotype distribution (banding pattern) observed between NERICAs 8 and 9 is highly likely to be due to lack molecular difference at the DNA level but the possibility for seed admixture remains to be explored. This study, however, revealed the presence of a wide range of genetic differences among all other NERICAs, with the highest being between NERICA 6 and 17. Cluster and principal component analyses of the SSR data revealed distinct separation of NERICA 1 to 7 from NERICA 8 to 18. The possible reasons for such separation and the implications for breeding programs are discusse