• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.5 no.3
• /
• pp.195-207
• /
• 2000

Organic and inorganic characteristics including bacterial cell number, enzyme activity, nutrients, and heavy metals have been monitored in twelve acrylic experimental tanks for two weeks to estimate and compare self-purification capacities in two Korean wet-land environments, tidal flat and rice field, which are possibly different with the environments in other countries because of their own climatic conditions. FW tanks, filled with rice field soils and fresh water, consist of FW1&2 (with paddy), FW3&4 (without paddy), and FW5&6 (newly reclaimed, without paddy). SW tanks, filled with tidal flat sediments and salt water, are SW1&2 (with anoxic silty mud), SW3&4 (anoxic mud), and SW5&6 (suboxic mud). Contaminated solution, which is formulated with the salts of Cu, Cd, As, Cr, Pb, Hg, and glucose+glutamic acid, was spiked into the supernatent waters in the tanks. Nitrate concentrations in supernatent waters as well as bacterial cell numbers and enzyme activities of soils in the FW tanks (except FW5&6) are clearly higher than those in the SW tanks. Phosphate concentrations in the SW1 tank increase highly with time compared to those in the other SW tanks. Removal rates of Cu, Cd, and As in supematent waters of the FW5&6 tanks are most slow in the FW tanks, while the rates in SW1&2 are most fast in the SW tanks. The rate for Pb in the SW1&2 tanks is most fast in the SW tanks, and the rate for Hg in the FW5&6 tanks is most slow in the FW tanks. Cr concentrations decrease generally with time in the FW tanks. In the SW tanks, however, the Cr concentrations decrease rapidly at first, then increase, and then remain nearly constant. These results imply that labile organic materials are depleted in the FW5&6 tanks compared to the FW1&2 and FW3&4 tanks. Removal of Cu, Cd, As from the supernatent waters as well as slow removal rates of the elements (including Hg) are likely due to the combining of the elements with organic ligands on the suspended particles and subsequent removal to the bottom sediments. Fast removal rates of the metal ions (Cu, Cd, As) and rapid increase of phosphate concentrations in the SW1&2 tanks are possibly due to the relatively porous anoxic sediments in the SW1&2 tanks compared to those in the SW3&4 tanks, efficient supply of phosphate and hydrogen sulfide ions in pore wates to the upper water body, complexing of the metal ions with the sulfide ions, and subsequent removal to the bottom sediments. Organic materials on the particles and sulfide ions from the pore waters are the major factors constraining the behaviors of organic/inorganic elements in the supernatent waters of the experimental tanks. This study needs more consideration on more diverse organic and inorganic elements and experimental conditions such as tidal action, temperature variation, activities of benthic animals, etc.

• Journal of Animal Science and Technology
• /
• v.48 no.1
• /
• pp.29-38
• /
• 2006

The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were －0.47 and －0.67 using modelⅠand －0.56 and －0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were －0.26 and 0.01 using modelⅠand －0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were －0.49 and －0.67 suing model Ⅰ and －0.57 and －0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were －0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were －0.43 and －0.67 using model Ⅰ and －0.50 and －0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were －0.09 and 0.02 using model Ⅰ and －0.02 and 0.13 using model Ⅱ.