In this study, we carried out an experiment for estimation the larval digestibility in aspects which digestive enzymatic activities and nutrition of the rotifers, Brachionus rotundiformis. Thus we enhanced the digestive enzymatic activity through the addition of starch for the increase of digestibility of rotifer (starch-rotifer), and compared with the feed efficiency through rearing of the olive flounder, Paralichthys olivaceus used rotifer lipid-enriched with Algamac $2000^{(R)}$ (CE-rotifer). The digestive enzyme activities (except for TG-lipase), total protein contents, total essential amino acid, essential amino acids (methionin and phenylalanine) of starch-rotifer (the rotifer used a starch as additive, and enriched not) was assayed significantly higher than CE-rotifer (P<0.05). And total lipid, lipid classes (except for sterol) and fatty acids as DHA and EPA showed higher in CE-rotifer than starch-rotifer (P<0.05). But, sterol contents and ST/TG ratio were shown significantly higher in starch-rotifer (P<0.05). The flounder larvae supplied the two rotifers showed standard length and body weight that not significantly differed with ranges $3.72{\sim}3.79\;mm$ and $32.9{\sim}37.8\;mg$/larva on 6 days after hatching (DAH), respectively (P>0.05). However, these of 12 DAH showed the values of significantly higher to $5.94{\pm}0.249\;mm$, $144.0{\pm}23.86\;mg$/larva and $26.2{\pm}12.13%$ in standard length, body weight and survival in CE-flounder than that of starch-flounder (P<0.05). The hydrolytic enzymatic activities of flounder larvae severally supplied the two rotifers showed the significantly higher activities in acidic -amylase, neutral -amylase, TG-lipase, lysozyme and acidic phosphatase in starch-flounder on 5 DAH (P<0.05). But neutral $\alpha$-amylase, three proteases and two phosphatases of CE-flounder on 11 DAH showed the significantly higher activities than that of starch-flounder (P<0.05). Therefore, for the flounder, Paralichthys olivaceus larvae just depleted yolk was more beneficial to supply the feed, rotifer, enhanced the digestibility than to supply the feed lipid-enriched for aspect of larval digestibility up to 6 DAH, thereafter nutrition of absorption due to the development of digestive organs suggested that enrichment effect appeared with larval somatic growth. Consequently, investigation more detailed about the larval digestive physiological and nutritional requirement variations after 6 DAH will be necessary, thereafter.
The objective of this study was to investigate the effect of the environmental and genetic factors on the carcass traits of Korean cattle. We have used the data of 22,954 Korean cattle slaughtered from 2005 to 2009 in Gyeongnam region and estimated the genetic parameters of 36,868 cattle including the pedigree individuals by means of EM-REML analytical method. In summary, the heritability of the carcass weight, eye muscle area, backfat thickness and marbling score was 0.39, 0.30, 0.33 and 0.62, respectively. The carcass weight and the eye muscle area showed high correlation between them with the genetic correlation of 0.86 and the phenotypic correlation of 0.72. The high heritability of marbling score is assumed to be the result of focusing the breed improvement on the quality of the meat. Through this study, it is considered that the Korean cattle in Gyeongnam region are improving, which will thus contribute to the increase of the farmer's income. Additional study on the economic trait must be carried out to obtain clearer results that will lead to further improvement of Korean cattle.
The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.
This study was conducted to estimate genetic parameters for growth and egg production traits in Black Korean native chicken (L strain) and Korean White Leghorn (F, K strains) using a multi-traits animal model BLUP. Traits used for this study were body weight at 150 days (BW150) and 270 days (BW270), age at first egg (DAY1st), egg weight at first egg (EW1st) and 270 days (EW270), and number of eggs laid by 270 days (EP270), and included 68,688 pedigree and 123,905 performance records collected from 2001 to 2013. In L, F, K strains, heritability estimates of BW150 were high (0.48, 0.52 and 0.50, respectively); of BW270 were high (0.56, 0.57 and 0.56); of DAY1st were medium to high (0.45, 0.39 and 0.31); of EW1st were low (0.15, 0.16 and 0.15); of EW270 were high (0.58, 0.55 and 0.59) and of EP270 were moderate (0.22, 0.21 and 0.20). The genetic and phenotypic correlation of DAY1st with EP270 were highly negative (-0.73 to -0.63 and -0.48 to -0.42). The genetic and phenotypic correlation of EP270 with BW150 and BW270, respectively were low negative (-0.16 to 0.01 and -0.14 to -0.03) and low to moderate positive (-0.08 to 0.07 and -0.13 to 0.04). The genetic and phenotypic correlation of EW270 with BW150 and BW270, respectively were moderate to high positive (0.39 to 0.49 and 0.36 to 0.46) and (0.29 to 0.33 and 0.34 to 0.37). The study showed that there is a potential for genetic improvement of Korean Indigenous chicken through selection program.
For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.
The purpose of this study was to estimate genetic parameters for productive traits in swine. Productive traits were considered on average daily gain (ADG), body height (BH) and body length (BL). Genetic analysis was consisted of 18,668 heads for productive traits which were based on on-farm performance tested from May, 2007 to Apr, 2011. For estimating genetic parameters on productive traits, single best model was fitted after finding source of variance on fixed and random effects and estimated with a multiple trait animal model by using DF-REML (Derivative-Free Restricted Maximum Likelihood). The estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire 0.22-0.58 for the average daily gain, 0.34-0.41 for the body height and 0.4-0.52 for the body length, respectively. Phenotypic correlations of average daily gain with body height and body length for the four breeds were 0.42-0.48, 0.53-0.58, 0.34-0.46 and 0.47-0.56, respectively. Phenotypic correlations of body height with body length were 0.41, 0.57, 0.52, 0.59, respectively. The estimated genetic correlation coefficients of average daily gain with body height and body length estimated for the four breeds were 0.34-0.47, 0.70-0.75, 0.17-0.38 and 0.50-0.53, respectively. The estimated genetic correlation coefficients of body height with body length were 0.57, 0.69, 0.61 and 0.71, respectively.
This study was conducted to develope allometric equations and to estimate biomass, stem density, and biomass expansion factor for the three stand age classes (I-II, III-IV, and V-VI) of Japanese larch (Larix leptolepis) in Gapyeong area. Total dry weight (kg/tree) and aboveground biomass (ton/ha) were 57.8 and 71.1 for I-II class, 185.4 and 195.6 for III-IV class, and 1047.9 and 180.6 for V-VI class, respectively. Total above and belowground biomass (ton/ha) was 96.3 for I-II class, 265.7 for III-IV class, and 244.5 for V-VI class. The proportion (%) of stem to total biomass increased with stand age class and was 53.9 for I-II class, 55.7 for III-IV class, and 57.7 for V-VI class, respectively, while that of foliage decreased and was 7.1 for I-II class, 4.5 for III-IV class, 2.3 for V-VI class. Ratios of root to aboveground biomass were 0.35 for all age classes. Stem density ($g/cm^3$) differed between I-II class and III-VI class. Aboveground and total biomass expansion factors were 1.31-1.44 and 1.26-1.94. Our results showed that differences in stand density with stand age classes might influence allometric equation, stem density and ratios of aboveground biomass to stem biomass and total biomass to stem biomass (biomass expansion factors).
Currently, many studies are being conducted to cope with climate changes due to global warming and abnormal weather. The objective of this study was to investigate the effects of weather on the growth, yield components, and quality of soybeans using weather data from 2017 and 2018. The average temperature in 2018 was higher than that in 2017 from R1 to R5 of the growth stage for all cultivars. On the other hand, precipitation in 2018 was reduced compared to that in 2017 for Daewon and Daepung-2ho. It was observed that the flowering date in 2018 was earlier than that in 2017 for Daewon and Daepung-2ho, but the flowering date for Pungsannamul in 2018 was similar to that in 2017. Simulating soil water content with the estimation model (AFKAE0.5) determined that there were fewer drought dates in 2017 than those in 2018, and drought lasted from R1 to early R5 of the growth stage in 2018. Soybean growth in 2017 was better than that in 2018, and seed yield and 100-seed weight of soybean were higher in 2017 than those in 2018 for all cultivars. The seed size in 2017 was larger than that in 2018 for all cultivars. Oil content in 2017 was higher than that in 2018; in particular, the difference between both years was observed for Daewon and Daepung-2ho. Protein content was higher in 2018 than that in 2017; however, there were different levels for each cultivar. Thus, these results indicate that the yield component and quality of soybeans are affected by high temperature and drought.
Data on egg number from time of first lay to 71 week of age were obtained from samples of single comb white leghorn breeder and brown layer breeder populations which were raised at manny breeding Co. These data were used to estimate the heritabilities of age at sexual maturity, early egg number, residual egg number and annual egg number. Also, the genetic correlation coefficients between these traits were estimated and selection efficiencies of each segment in early part record were estimated by use of the heritabilities and generic correlations. The estimated heritabilities and standard errors in two lines(W and B) were $0.30\pm0.07$ and $0.33\pm0.08$ at early records, $0.19\pm0.06$ and $0.18\pm$0.05 at residual records and $0.37\pm0.09$ and $0.49\pm0.10$ at time of first lay. Those at annual records were $0.24\pm0.06$ equally. The estimated correlation coefficients and standard errors between early record and annual record were $0.76\pm0.08$ and $0.77\pm0.07$. Those between early record and residual record were $0.46\pm0.15$ and $0.39\pm0.16$ respectively. At improving annual egg production per year, selection based on early part record(SM to 40 week of age) would be 69% more efficient than on annual record in line W and 80% more efficient than on annual record in line B. But, if it were considered that egg weight decreased due to sexual maturity and cost for data collection, use of selected segment from 35~40week of age in line W and from 31~40 week of age in line B would be desired in spite of a. small loss in relative selection efficiency. The generation interval would not be shortened.
The genetic parameters used in National Hanwoo Genetic Evaluation(NHGE) were needed to be monitored and updated periodically for accounting any possible changes in population parameters due to selection and environmental changes. Genetic parameters were estimated with single and two-trait models with MTDFREML package using 2,791 carcass records of steers collected from Hanwoo Progeny Test Program(HPTP). Single and two-trait models gave similar parameter estimates for all traits. The heritability estimates from single and two-trait models for carcass weight(CW), dressing percentage(DP), eye muscle area(EMA), back fat thickness(BFT) and marbling score(MS) were 0.30, 0.30, 0.37, 0.44 and 0.44, respectively. The heritability estimates for all the traits except BFT were slightly lower than those used in NHGE but seemed to be within the acceptable ranges. However, further monitoring is needed because the data might not have fully reflected the changes such as carcass grading standards in performance testing program. In order to shift statistical model of NHGE from single trait model to multiple-trait model, the genetic correlations between carcass traits were estimated with pairwise two-trait models. The genetic correlation coefficients between CW and DP, between CW and EMA, between CW and BFT and between CW and MS were 0.44, 0.63, 0.17 and 0.06, respectively. Those between DP and EMA, between DP and BFT and between DP and MS were 0.29, 0.40 and 0.20. Those between EMA and BFT and between EMA and MS were -0.24 and 0.15, respectively. The genetic correlation coefficient between BFT and MS was 0.03.
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