11 research outputs found

    Multivariate analysis of tilapia growth experiments in ponds : case studies from the Philippines, Israel, Zambia and Peru

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    Three multivariate statistical methods for the analysis of aquaculture experiment data are introduced and their application is demonstrated on different datasets. The methods are based on multiple regression and path analysis (causal analysis). The two multiple regression methods are termed the 'extended Gulland-and-Holt method' and the 'extended Bayley method', where the latter is derived and presented here for the first time. With these methods, the variables controlling fish growth rate in aquaculture experiments can be identified and their effects quantified in form of empirical, multiple regression models. Both methods permit the derivation of parameters of the von Bertalanffy growth function. These can be used for growth prediction and decision making in fish farm management and production under a wide range of environmental and treatment conditions. By computing the index of growth performance,ϕ' (phi-prime), the obtained growth parameters can be compared. The application of the presented methods is demonstrated on different types of datasets: 1) integrated livestock-fish farming experiments with mixed-sex populations of Nile tilapia (Oreochromis niloticus) conducted in the Philippines, 2) chicken manure-fed Nile tilapia culture experiments at Dor Station in Israel, 3) all-male hybrid tilapia, grown in polyculture at commercial farms in Israel, 4) pig and duck manure-fed Nile tilapia culture trials in Lima, Peru, and 5) experiments with mixed-sex populations of Oreochromis andersonii in Zambia, Africa. Depending on the amount of variables available in the datasets, and the precision of their measurement, models of different accuracy could be derived. The effect of the different variables was investigated with sensitivity analysis. Differences between the methods were studied. From the understanding gained by analyzing different types of datasets, recommendations are given for future applications of the methods, and for the design of new experiments that are to be analyzed with these methods

    The influence of environmental factors on fish production in tropical ponds investigated with multiple regression and path analyses

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    1. A data set from integrated animal-fish farming experiments comprising 63 variables with nearly 45000 data points was analysed for interrelationships in the system and for causal effects on fish growth. 2. A new multivariate method for the analysis of multifactor data on the basis of multiple regression resulted in the identification of five major environmental variables governing fish growth in the present system: water temperature, wind, BOD of the added manure, pond size, and early morning oxygen content of the pond water. 3. It was found that the early morning oxygen content is mainly a measure of plankton standing crop and therefore represents the nutritional status of the pond for the cultured fish. This explains the negative sign of the regression coefficient for oxygen content. All other environmental variables showed positive effects on fish growth. 4. The new method permitted to derive parameters of the von Bertalanffy growth function for Nile tilapias. The obtained value for K is 5.409, indicating rapid growth of the fish. The values for Loo range from 15.8 to 23.9 cm depending on environmental conditions. 5. One of the advantages of the new method is the possibility to predict fish growth with good accuracy over the whole experimental period, simultaneously taking into account the environmental changes affecting fish growth. The level of precision in growth prediction is mainly affected by the quality of the fish-size data used in deriving the model. 6. The method of path analysis was successfully introduced to aquaculture for the interpretation of experiments and proved valuable to unravel interrelationships in the system

    Increased Income from Seasonally Flooded Rice Fields through Community Based Fish Culture in Bangladesh and Vietnam

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    In extensive river floodplains and deltaic lowlands, floods lasting several months render the land unavailable for crop (often rice) production during the rainy season. Aside from crop production during the flood-free dry season, the land area can be utilized for fish production during the flood season. This can be done by enclosing parts of these floodwater areas to produce a crop of stocked fish aside from the naturally occurring ‘wild’ species. The WorldFish Center and its national partners recently tested (1) concurrent rice-fish culture in the shallower flooded areas and (2) alternating rice and fish culture in the deep-flooded areas of Bangladesh and Vietnam through a community-based management system. This paper presents the key results of this work, focusing on the economics of existing land use patters and the impact of community based fish culture on rice yields and income. Rice production was maintained, or even enhanced. Fish production was increased beyond the wild catch by about 600 kg/ha/year in shallow-flooded areas and up to 1.5 t/ha/year in deep-flooded areas, without reduction in wild fish catch. For the overall system on an annual basis, an additional income ranging from US135perhectareinsouthernVietnamtoUS 135 per hectare in southern Vietnam to US 437 per hectare in Bangladesh was achieved, which is an increase of 20 to 85 percent over the profitability of the previous systems involving cropping and fish capture. The results indicate that community-based fish culture in rice fields is technically feasible, economically profitable, environmentally non-destructive, and socially acceptable

    Effective screening and cleaning of secondary fibers

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