25 resultados para Statistical genomics


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Recreational fisheries in the waters off the northeast U.S. target a variety of pelagic and demersal fish species, and catch and effort data sampled from recreational fisheries are a critical component of the information used in resource evaluation and management. Standardized indices of stock abundance developed from recreational fishery catch rates are routinely used in stock assessments. The statistical properties of both simulated and empirical recreational fishery catch-rate data such as those collected by the National Marine Fisheries Service (NMFS) Marine Recreational Fishery Statistics Survey (MRFSS) are examined, and the potential effects of different assumptions about the error structure of the catch-rate frequency distributions in computing indices of stock abundance are evaluated. Recreational fishery catch distributions sampled by the MRFSS are highly contagious and overdispersed in relation to the normal distribution and are generally best characterized by the Poisson or negative binomial distributions. The modeling of both the simulated and empirical MRFSS catch rates indicates that one may draw erroneous conclusions about stock trends by assuming the wrong error distribution in procedures used to developed standardized indices of stock abundance. The results demonstrate the importance of considering not only the overall model fit and significance of classification effects, but also the possible effects of model misspecification, when determining the most appropriate model construction.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): We describe an empirical-statistical model of climates of the southwestern United States. Boundary conditions include sea surface temperatures, atmospheric transmissivity, and topography. Independent variables are derived from the boundary conditions along 1000-km paths of atmospheric circulation. ... Predictor equations are derived over a larger region than the application area to allow for the increased range of paleoclimate. This larger region is delimited by the autocorrelation properties of climatic data.

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A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance, 17 foraminiferal species, species were clustered into 5 groups with row normalisation and varimax rotation for Q-mode factor analysis. The 19 stations were also grouped into 5 groups with only 2 groups statistically significant using column normalisation and varimax rotation for R-mode analysis. This assemblage grouping method is suitable because groups of species/stations can explain the maximum amount of variation in them in relation to prevailing environmental conditions in the area of study.

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Apart from the use of statistical quality control chart for variables or attributes of food products in a food processing industry, the application of these charts for attributes of fishery products is explained. Statistical quality control chart for fraction defectives is explained by noting defective fish sausages per shift from a sausage industry while control chart for number of defectives is illustrated for number of defective fish cans in each hour of its production of a canning industry. C-chart is another type of control chart which is explained here for number of defects per single fish fillet sampled a1l random for every five minutes in a processing industry. These statistical quality control charts help in the more economic use of resource, time and labour than control charts for variables of products. Also control charts for attributes exhibit the quality history of finished products at different times of production thereby minimizing the risk of consumer rejection.

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The quality of raw and processed fishery products depend on several factors like physiological conditions at the time of capture, morphological differences, rigor mortis, species, rate of icing and subsequent storage conditions. Sensory evaluation is still the most reliable method for evaluation of the freshness of raw processed fishery products. Sophisticated methods like Intelectron fish tester, cell fragility technique and chemical and bacteriological methods like estimation of trimethylamine, hypoxanthine, carbonyl compounds, volatile acid and total bacterial count have no doubt been developed for accessing the spoilage in fish products.

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This paper deals with an extensive study conducted to estimate the extent of weight loss in frozen prawns. The weight Joss varied from 7 to 12% in peeled and deveined (PD), 5 to 7% in headless (HL) and about 7% in cooked and peeled (CP) prawns from the date of processing to the date of inspection, normally within two weeks. To compensate the weight loss nearly 11% of excess material is being added with every frozen block resulting in an average annual loss of Rs. 2.68 crores in foreign exchange. The relevant data pertain to the period 1971 to 1973 and the annual average loss was estimated for the ten years ending 1973.

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The number of fishing trials required for comparing the efficiency of fishing gears was investigated. A unique solution to this problem did not appear to exist because of the heterogeneity of the experimental material. Sequential experimentation and analysis have been found to be a practical approach to this problem. By this, the experiment can be terminated almost after 35 days fishing for catches with standard error per unit as per cent of the mean about 30% or less (after logarithmic transformation). For data with mean catches less than 1.5 kg analysis of variance approach does not appear to be meaningful.

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The distribution of fish caught by experimental gill nets has been found to be in the Poisson or Negative binomial form. Using this information, application of Chi-square test as suggested by Mood et al. (1974) has been illustrated, for comparing the efficiencies of gill nets. This test provides an alternative to Anova F-test especially in the context of significance of non-additivity for the two-way model. Based on the present work and the findings by Nair (1982) and Nair & Alagaraja (1982, 1984) an outline approach for statistical comparison of the efficiencies of fishing gear is presented.

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A simple statistical index, for evaluating the condition of growth in an aquaculture experiment and indicating the extent of effect of any plausible rival hypothesis, is presented.