964 resultados para Fertility of Kuttanad waters


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Issued, 1917- as Bulletin no. 15 of the Division of the State Water Surveys, Dept. of Registration and Education.

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Title within ornamental border.

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This study determined the relationship between two measures of field fertility of I I high-use Australian artificial insemination (AI) dairy bulls and thirty standard laboratory assessments of spermatozoal post-thaw viability. The two measures of field fertility used, conception rates (cCR) and non-return rates (cNRR), were both corrected for all major non-bull variables. Sperm viability assessments were conducted on semen collected within the same season as that used to derive the field fertility estimates. These assessments measured sperm concentration, motility, morphology and membrane integrity at thawing, after 2 h incubation and after the swim-up sperm selection procedure. Derivations of these measures and in vitro embryo fertilizing and developmental capacity were also determined. The Genstat Statistical Package [Genstat 5 Release 4.2 Reference Manual, VSN International, Oxford, 20001 was used to conduct an analysis of variance on the viability parameters across semen straws and bulls, and to calculate the strength of correlation between each semen parameter, cNRR and cCR in a correlation matrix. Step forward multiple regression identified the combination of semen parameters that were most highly correlated with cCR and with cNRR. The sperm parameters identified as being most predictive of cCR were the percentage of morphologically normal sperm immediately post-thaw (zeroNorm), the number of morphologically normal sperm after the swim-up procedure (nSuNorm), and the rate of zygote cleavage in vitro (Clv); the predictive equation formed by these parameters accounted for 70% of variance. The predictive equation produced for cNRR contained the variables zeroNorm, the proportion of membrane intact sperm after 2 h incubation at 37 degreesC (twoMem) and Clv and accounted for 76.5% of the variation. ZeroNorm was found to be consistent across straws and semen batches within-bull and the sperm parameter with the strongest individual predictive capacity for both cCR (P = 0.1) and cNRR (P = 0.001). Post-thaw sperm parameters can be used to predict field fertility of Australian dairy sires; the calculated predictive equations are particularly useful for identifying and monitoring bulls of very high and very low potential fertility within a group. (C) 2003 Elsevier B.V. All rights reserved.

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The Thames Estuary, UK, and the Brisbane River, Australia, are comparable in size and catchment area. Both are representative of the large and growing number of the world's estuaries associated with major cities. Principle differences between the two systems relate to climate and human population pressures. In order to assess the potential phytotoxic impact of herbicide residues in the estuaries, surface waters were analysed with a PAM fluorometry-based bioassay that employs the photosynthetic efficiency (photosystem II quantum yield) of laboratory cultured microalgae, as an endpoint measure of phytotoxicity. In addition, surface waters were chemically analysed for a limited number of herbicides. Diuron atrazine and simazine were detected in both systems at comparable concentrations. In contrast, bioassay results revealed that whilst detected herbicides accounted for the observed phytotoxicity of Brisbane River extracts with great accuracy, they consistently explained only around 50% of the phytotoxicity induced by Thames Estuary extracts. Unaccounted for phytotoxicity in Thames surface waters is indicative of unidentified phytotoxins. The greatest phytotoxic response was measured at Charing Cross, Thames Estuary, and corresponded to a diuron equivalent concentration of 180 ng L-1. The study employs relative potencies (REP) of PSII impacting herbicides and demonstrates that chemical analysis alone is prone to omission of valuable information. Results of the study provide support for the incorporation of bioassays into routine monitoring programs where bioassay data may be used to predict and verify chemical contamination data, alert to unidentified compounds and provide the user with information regarding cumulative toxicity of complex mixtures. (c) 2005 Elsevier B.V. All rights reserved.