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The results of probabilistic event attribution studies depend on the choice of the extreme value statistics used in the analysis, particularly with the arbitrariness in the selection of appropriate thresholds to define extremes. We bypass this issue by using the Extended Generalized Pareto Distribution (ExtGPD), which jointly models low precipitation with a generalized Pareto distribution and extremes with a different Pareto tail, to conduct daily precipitation attribution across the contiguous United States (CONUS). We apply the ExtGPD to 12 general circulation models from the Coupled Model Intercomparison Project Phase 6 and compare counterfactual scenarios with and without anthropogenic emissions. Observed precipitation by the Climate Prediction Center is used for evaluating the GCMs. We find that greenhouse gases rather than natural variability can explain the observed magnitude of extreme daily precipitation, especially in the temperate regions. Our results highlight an unambiguous linkage of anthropogenic emissions to daily precipitation extremes across CONUS. Plain Language Summary: We investigate how human‐induced emissions affect daily rainfall extremes across the United States. The attribution of an extreme event to human‐induced emissions depends on the selected extreme event statistics, with setting a threshold to define what counts as an extreme event remaining a major challenge. To overcome this, we used the Extended Generalized Pareto Distribution (ExtGPD) that jointly models both low and heavy rainfall events without defining a threshold, providing a more complete picture of the full distribution including extremes. We fitted the ExtGPD to 12 general circulation models and compared scenarios with and without human‐induced emissions. Our findings suggest that human emissions are responsible for the observed intensity of daily rainfall extremes across the United States, especially in regions with temperate climates, and that these extremes would have been smaller without greenhouse gases. Key Points: We apply the Extended Generalized Pareto Distribution for probabilistic event attribution to bypass issues with threshold specificationAnthropogenic emissions alone could exacerbate the observed magnitude of extreme daily precipitation across the United StatesThe study underscores the urgent need for mitigation, revealing a clear link between anthropogenic activities and extreme precipitation [ABSTRACT FROM AUTHOR]

In this study, future precipitation and drought in the Ca river basin, Vietnam, were projected based on an ensemble of 27 CMIP6 models for four climate change scenarios. The impact of climate change on precipitation and drought was investigated. Monthly precipitation observation data were adjusted using the bias correction method. To detect drought events, the Standard Precipitation Index (SPI) was employed. Changes in drought were assessed using SPI3, SPI6, and SPI12. Although the amount of annual total precipitation slightly increased, the drought events may become more severe. There is a high likelihood of increased drought intensity and severity in Vietnam due to climate change. The frequency of droughts is likely to change depending on the location and climate change scenario. We found that the frequency and severity of droughts may be altered depending on the window size of SPI. The short-term drought events will be more frequent and severe, and long-term drought events will become more severe in the Ca river basin. [ABSTRACT FROM AUTHOR]

Extreme flood events have regional differences in their generating mechanisms due to the complex interaction of different climate and catchment processes. This study aims to examine the capability of climate drivers to capture year‐to‐year variability in global flood extremes. Here, we use a statistical attribution approach to model seasonal and annual maximum daily discharge for 7,886 stations worldwide, using season‐ and basin‐averaged precipitation and temperature as predictors. The results show robust performance of our seasonal climate‐informed models in describing the inter‐annual variability in seasonal and annual maximum discharges regardless of the geographical region, climate type, basin size, degree of regulation, and impervious area. The developed models enable the assessment of the sensitivity of flood discharge to precipitation and temperature changes, indicating their potential to reliably project changes in the magnitude of flood extremes. Plain Language Summary: Successfully modeling the changes in magnitudes of flood events is challenging due to the complexity of flood‐driving processes, which vary depending on region and season. Here, we examine how seasonal precipitation and temperature can describe changes in the flood magnitudes. Although we only consider these basic climate factors as predictors, our climate‐informed models consistently show a good performance in capturing the year‐to‐year variability in the magnitude of seasonal and annual flooding events across 7,886 stations worldwide. These results show the suitability of seasonal precipitation and temperature as proxies for different climate and catchment processes leading to flooding. Key Points: For 7,886 stations across the globe, we develop statistical attribution models for seasonal and annual maximum daily discharge seriesUsing only climate predictors, our models perform well across climate type, basin size, degree of regulation, and impervious areaSeasonal climate predictors are suitable to capture complex interplays of different climate and catchment processes leading to peak flows [ABSTRACT FROM AUTHOR]

Simple Summary: This study investigated the effect of varying levels of dietary fat in concentrate mixes on growth performance, rumen characteristics, digestibility, blood metabolites, and methane emissions in growing Hanwoo steers. The experiment was conducted for 12 weeks by feeding three concentrate mixes with different levels of dietary fat (i.e., 48, 74, 99 g/kg dry matter [DM] of concentrate mix). Increasing fat levels in the concentrate mix significantly reduced the intake of concentrate mix (p < 0.01); however, there were no significant adverse effects on the growth rate, feed efficiency, and digestibility (p > 0.05). Increasing fat levels also affected the characteristics of rumen fluid, increasing the proportion of propionate (p < 0.01) and decreasing the proportion of butyrate and acetate to propionate in the total volatile fatty acids (p < 0.01). Cholesterol in blood serum increased significantly with increasing fat levels (p < 0.01). The highest fat level showed 18% lower methane concentration in exhaled gas from eructation than the lowest (basal) fat level (p < 0.05). In conclusion, increasing the fat level up to 100 g/kg DM in the concentrate mix reduced methane concentration in the exhaled gas from eructation without altering growth performance in growing Hanwoo steers. This study investigated the effect of different dietary fat levels in concentrate mixes on the growth performance, rumen characteristics, digestibility, blood metabolites, and methane emissions in growing Hanwoo steers. Thirty steers (386 ± 24.6 kg of body weight [BW]; 12 months old), blocked by BW, were randomly assigned to three dietary treatments with varying fat concentrations in concentrate mix (48, 74, and 99 g of ether extract per kg dry matte [DM]). The fat intake of the low-fat treatment represented 4.15% of the total dry matter intake (DMI), while the medium- and high-fat treatments accounted for 5.77% and 7.23% of total DMI, respectively. Concentrate mix DMI decreased with increasing fat level (p < 0.01). The growth rate and digestibility did not significantly differ based on the fat level (p > 0.05). As the fat level increased, propionate in the total ruminal volatile fatty acids increased, and butyrate and acetate-to-propionate decreased (p < 0.01). Cholesterol in blood serum increased significantly with increasing dietary fat levels (p < 0.01). Methane emissions exhibited a linear decrease with increasing fat level (p < 0.05). In conclusion, elevating fat content in the concentrates up to 100 g/kg DM reduced methane emissions without compromising the growth performance of growing Hanwoo steers. [ABSTRACT FROM AUTHOR]

Weather types or weather regimes represent the dominant modes of large‐scale atmospheric circulation patterns and have been used to understand and explain the physical mechanisms of different weather events. While there have been many studies that analyse the changes in extreme climate events through the lenses of weather typing, there is a lack of studies that attribute changes in flood extremes to changes in weather regimes. Here we examine the potential applicability of weather types as predictors of flood extremes. For 4535 streamgages across the conterminous United States, we employ a statistical attribution approach to model the seasonal and annual maximum discharge, utilizing five weather types with distinct synoptic features. Although there are regional patterns in the relationship between weather types and the major climate drivers of flooding, our results show that the frequency of weather types does not provide enough information to model the interannual variability in the magnitude of flood peaks across the conterminous United States. [ABSTRACT FROM AUTHOR]

Simple Summary: As the price of imported corn rises due to environmental issues and the growing demand for bio-ethanol production, animal nutritionists are actively seeking alternative energy sources to corn. While previous research has shown that rice grain provides a comparable nutritional value to corn, it is noted that most of the studies on rice grain as a starch source for ruminants have been conducted on dairy cattle. The objective of this study is to assess the effects of total mixed ration (TMR) containing rice grains on the growth performance, blood metabolites, rumen fermentation, and rumen microbial community in fattening Hanwoo steers. Our results demonstrated that rice grain had no adverse effects on the growth performance of Hanwoo steers, rumen fermentation characteristics, and blood metabolites. In conclusion, this study suggests that utilizing rice grains as the primary starch source in TMR may serve as an alternative option for fattening Hanwoo steers. This study aimed to assess the influence of rice grain in the total mixed ration (TMR) on the growth performance, blood metabolites, rumen fermentation, and rumen microbial community of fattening Hanwoo steers. Two experimental diets were prepared: (i) a TMR containing 33% dry matter (DM) corn grains (Corn TMR) and (ii) a TMR containing 33% DM rice grains (Rice TMR). Twenty-two Hanwoo steers (body weight [BW], 498 ± 32 kg; months, 17 ± 0.5) were distributed into two treatment groups in a completely randomized block design according to BW. The Rice TMR group had a higher final BW and DM intake (DMI) compared to those in the Corn TMR group (p < 0.01). However, no difference was observed in the average daily gain (ADG) and feed conversion ratio (FCR) between the two treatments. For the rumen fermentation parameters, the molar portion of butyrate in the Rice TMR was higher than in the Corn TMR (p < 0.01). Streptococcus bovis tended to be higher in the Rice TMR (p = 0.09). The results of this study suggest that using rice grain as the primary starch source in TMRs may be an alternative option for fattening Hanwoo steers. [ABSTRACT FROM AUTHOR]

Extreme rainfall and floods have increased in frequency and severity in recent years, due to climate change and urbanization. Consequently, interest in estimating the probable maximum precipitation (PMP) has been burgeoning. The World Meteorological Organization (WMO) recommends two types of methods for calculating the PMP: hydrometeorological and statistical methods. This study proposes a modified Hershfield's nomograph method and assesses the changes in PMP values based on the two representative concentration pathway (RCP4.5 and RCP8.5) scenarios in South Korea. To achieve the intended objective, five techniques were employed to compute statistical PMPs (SPMPs). Moreover, the most suitable statistical method was selected by comparing the calculated SPMP with the hydrometeorological PMP (HPMP), by applying statistical criteria. Accordingly, SPMPs from the five methods were compared with the HPMPs for the historical period of 2020 and the future period of 2100 for RCP 4.5 and 8.5 scenarios, respectively. The results confirmed that the SPMPs from the modified Hershfield's nomograph showed the smallest MAE (mean absolute error), MAPE (mean absolute percentage error), and RMSE (root mean square error), which are the best results compared with the HPMP with an average SPMP/HPMP ratio of 0.988 for the 2020 historical period. In addition, Hershfield's method with varying K M exhibits the worst results for both RCP scenarios, with SPMP/HPMP ratios of 0.377 for RCP4.5 and 0.304 for RCP8.5, respectively. On the contrary, the modified Hershfield's nomograph was the most appropriate method for estimating the future SPMPs: the average ratios were 0.878 and 0.726 for the 2100 future period under the RCP 4.5 and 8.5 scenarios, respectively, in South Korea. [ABSTRACT FROM AUTHOR]

The increasing prevalence of methicillin-resistant Staphylococcus aureus (MRSA) in the dairy industry has become a fundamental concern. Endolysins are bacteriophage-derived peptidoglycan hydrolases that induce the rapid lysis of host bacteria. Herein, we evaluated the lytic activity of endolysin candidates against S. aureus and MRSA. To identify endolysins, we used a bioinformatical strategy with the following steps: (1) retrieval of genetic information, (2) annotation, (3) selection of MRSA, (4) selection of endolysin candidates, and (5) evaluation of protein solubility. We then characterized the endolysin candidates under various conditions. Approximately 67% of S. aureus was detected as MRSA, and 114 putative endolysins were found. These 114 putative endolysins were divided into three groups based on their combinations of conserved domains. Considering protein solubility, we selected putative endolysins 117 and 177. Putative endolysin 117 was the only successfully overexpressed endolysin, and it was renamed LyJH1892. LyJH1892 showed potent lytic activity against both methicillin-susceptible S. aureus and MRSA and showed broad lytic activity against coagulase-negative staphylococci. In conclusion, this study demonstrates a rapid strategy for the development of endolysin against MRSA. This strategy could also be used to combat other antibiotic-resistant bacteria. [ABSTRACT FROM AUTHOR]

Coastal areas are subject to the joint risk associated with rainfall‐driven flooding and storm surge hazards. To capture this dependency and the compound nature of these hazards, bivariate modelling represents a straightforward and easy‐to‐implement approach that relies on observational records. Most existing applications focus on a single tide gauge–rain gauge/streamgauge combination, limiting the applicability of bivariate modelling to develop high‐resolution space–time design events that can be used to quantify the dynamic, that is, varying in space and time, compound flood hazard in coastal basins. Moreover, there is a need to recognize that not all extreme events always come from a single population, but can reflect a mixture of different generating mechanisms. Therefore, this paper describes an empirical approach to develop design storms with high‐resolution in space and time (i.e., ~5 km and hourly) for different joint annual exceedance probabilities. We also stratify extreme rainfall and storm surge events depending on whether they were caused by tropical cyclones (TCs) or not. We find that there are significant differences between the TC and non‐TC populations, with very different dependence structures that are missed if we treat all the events as coming from a single population. While we apply this methodology to one basin near Houston, Texas, our approach is general enough to make it applicable for any coastal basin exposed to compounding flood hazards from storm surge and rainfall‐induced flooding. [ABSTRACT FROM AUTHOR]

Baseflow is an important water resource because it supplies streamflow between precipitation events and during dry seasons. We report the first continental assessment of baseflow in Africa by analyzing the baseflow index, baseflow seasonality, and monthly baseflow trends for three periods (1950–2018, 1950–1980, and 1981–2018). To explain changes in baseflow, we analyze precipitation trends. Results highlight that the baseflow season in west-central Africa occurs during August–November. In southern and northern Africa, the baseflow season is similar (January–May and January–April, respectively). Trend analysis detected monthly baseflow decreases in west-central Africa over the entire record and from 1950 to 1980, with increases after 1980. A clear pattern was absent in southern Africa for the whole record, but increases were detected earlier and decreases from 1981 to 2018. In northern Africa, decreasing baseflow trends were pronounced over the whole record, with no clear shift present. Precipitation trends were only consistent with baseflow changes in west-central Africa. [ABSTRACT FROM AUTHOR]

The use of a long-term and high-quality precipitation dataset is crucial for hydrologic modeling and flood risk management. This study evaluates the Analysis of Period of Record for Calibration (AORC) dataset, a newly released product with high temporal and spatial resolutions. Our study region is centered on Louisiana because of the major flooding it has been experiencing. We compare the AORC hourly precipitation to other widely used gridded rainfall products and rain-gauge observations. To evaluate the performance of rainfall products according to different weather conditions causing severe flooding, we stratify the analyses depending on whether precipitation is associated with a tropical cyclone (TC) or not. Compared to observations, our results show that the AORC has the highest correlation coefficients (i.e., values above 0.75) with respect to observations among all rainfall products for both TC and non-TC periods. When the skill metric is decomposed into the potential skill and biases, the AORC clearly shows the highest potential skill with relatively small biases for the whole period. In addition, the AORC performs better for the TC period compared to the non-TC ones. Our results suggest that AORC precipitation shows good potential to be viable for hydrologic modeling and simulations of TC and non-TC events. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the effects of dietary supplementation with red ginseng byproduct (RGB) on rumen fermentation, growth performance, blood metabolites, and mRNA expression of heat shock proteins (HSP) in fattening Hanwoo steers under heat stress. Two experimental total mixed rations (TMR) were prepared: (1) a TMR meeting the requirement of fattening beef having an average daily gain (ADG) 0.8 kg/day (CON) and (2) a TMR that included 2% RGB on a dry matter (DM) basis (GINSENG). In vitro rumen fermentation and in vivo growth experiments were conducted using two experimental diets. A total of 22 Hanwoo steers were distributed to two treatments (CON vs. GINSENG) in a completely randomized block design according to body weight (BW). The experiment was conducted during the summer season for five weeks. The final BW, ADG, DM intake, and feed conversion ratio did not differ between treatments in the growth trial. In the mRNA expression results, only HSP 90 showed an increasing tendency in the GINSENG group. The use of 2%DM RGB did not improve the growth performance or alleviate heat stress in fattening Hanwoo steers during the summer season. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) have been extensively used to forecast monthly precipitation for water resources management over the past few decades. Efforts to produce more accurate and stable forecasts face ongoing challenges as the so‐called single‐ANN (S‐ANN) approach has several limitations, particularly regarding uncertainty. Many attempts have been made to deal with different types of uncertainties by applying ensemble approaches. Here, we propose a new ANN ensemble model (ANN‐ENS) dealing with uncertainty in model structure and input variable selection to provide a more accurate and stable forecasting performance. This model is structured by generating various input layers, considering all the candidate input variables (i.e.,large‐scale climate indices and lagged precipitation). We developed a modified backward elimination method to select the preliminary input variables from all the candidate input variables. Then, we tested and validated the proposed ANN‐ENS using observed monthly precipitation from 10 meteorological stations in the Han River basin, South Korea. Our results demonstrated that the ANN‐ENS enhanced the forecasting performance in terms of both accuracy and stability. Although a significant uncertainty was introduced by using all the candidate input variables, the forecasting result outperformed S‐ANNs for all employed stations. Additionally, the ANN‐ENS provided a more stable forecasting performance in comparison with S‐ANNs, which are highly sensitive. Moreover, the generated ensemble members were slightly biased at some stations but were generally reliable. Key Points: We develop a new artificial neural network (ANN) ensemble model (ANN‐ENS) to deal with uncertainty in model structure and input variable selectionThis is based on a modified backward elimination method that improves preliminary input variables for the ANN‐ENSThe resulting ANN‐ENS demonstrated remarkable performance in terms of forecasting accuracy, stability, and ensemble reliability [ABSTRACT FROM AUTHOR]

Extreme value modeling for extreme rainfall is one of the most important processes in the field of hydrology. For the improvement of extreme value modeling and its physical meaning, large-scale climate modes have been widely used as covariates of distribution parameters, as they can physically account for climate variability. This study proposes a novel procedure for extreme value modeling of rainfall based on the significant relationship between the long-term trend of the annual maximum (AM) daily rainfall and large-scale climate indices. This procedure is characterized by two main steps: (a) identifying significant seasonal climate indices (SCIs), which impact the long-term trend of AM daily rainfall using statistical approaches, such as ensemble empirical mode decomposition, and (b) selecting an appropriate generalized extreme value (GEV) distribution among the stationary GEV and nonstationary GEV (NS-GEV) using time and SCIs as covariates by comparing their model fit and uncertainty. Our findings showed significant relationships between the long-term trend of AM daily rainfall over South Korea and SCIs (i.e., the Atlantic Meridional Mode, Atlantic Multidecadal Oscillation in the fall season, and North Atlantic Oscillation in the summer season). In addition, we proposed a model selection procedure considering both the Akaike information criterion and residual bootstrap method to select an appropriate GEV distribution among a total of 59 GEV candidates. As a result, the NS-GEV with SCI covariates generally showed the best performance over South Korea. We expect that this study can contribute to estimating more reliable extreme rainfall quantiles using climate covariates. [ABSTRACT FROM AUTHOR]

Simple Summary: Development of endolysin is a promising strategy because of having the ability to control problematic bacteria specifically. In this study, we developed and characterized the endolysin having lytic activity against Streptococcus bovis (S. bovis), which is one of the initiators of ruminal acidosis. Based on our findings, endolysin LyJH307 showed potent lytic activity in ruminal pH range and ruminal temperature. In addition, LyJH307 was effective against not only S. bovis isolated from rumen, but also several S. bovis groups. We suggest that LyJH307 may have a lytic effect in the ruminal condition and prevent acute ruminal acidosis by controlling S. bovis specifically. Streptococcus bovis (S. bovis) is one of the critical initiators of acute acidosis in ruminants. Therefore, we aimed to develop and characterize the endolysin LyJH307, which can lyse ruminal S. bovis. We tested the bactericidal activity of recombinant LyJH307 against S. bovis JB1 under a range of pH, temperature, NaCl, and metal ion concentrations. In silico analyses showed that LyJH307 has a modular design with a distinct, enzymatically active domain of the NLPC/P60 superfamily at the N-terminal and a cell wall binding domain of the Zoocin A target recognition domain (Zoocin A_TRD) superfamily at the C-terminal. The lytic activity of LyJH307 against S. bovis JB1 was the highest at pH 5.5, and relatively higher under acidic, than under alkaline conditions. LyJH307 activity was also the highest at 39 °C, but was maintained between 25°C and 55°C. LyJH307 bactericidal action was retained under 0-500 mM NaCl. While the activity of LyJH307 significantly decreased on treatment with ethylenediaminetetraacetic acid (EDTA), it was only restored with supplementation of 10 mM Ca2+. Analyses of antimicrobial spectra showed that LyJH307 lysed Lancefield groups D (S. bovis group and Enterococcus faecalis) and H (S. sanguinis) bacteria. Thus, LyJH307 might help to prevent acute ruminal acidosis. [ABSTRACT FROM AUTHOR]

Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential information about climate variability, as they usually have a direct or indirect correlation with hydrologic variables. This study aims to use large-scale climate indices in monthly reservoir inflow forecasting for considering climate variability. For this purpose, time series and artificial intelligence models, such as Seasonal AutoRegressive Integrated Moving Average (SARIMA), SARIMA with eXogenous variables (SARIMAX), Artificial Neural Network (ANN), Adaptive Neural-based Fuzzy Inference System (ANFIS), and Random Forest (RF) models were employed with two types of input variables, autoregressive variables (AR-) and a combination of autoregressive and exogenous variables (ARX-). Several statistical methods, including ensemble empirical mode decomposition (EEMD), were used to select the lagged climate indices. Finally, monthly reservoir inflow was forecasted by SARIMA, SARIMAX, AR-ANN, ARX-ANN, AR-ANFIS, ARX-ANFIS, AR-RF, and ARX-RF models. As a result, the use of climate indices in artificial intelligence models showed a potential to improve the model performance, and the ARX-ANN and AR-RF models generally showed the best performance among the employed models. [ABSTRACT FROM AUTHOR]

Multivariate frequency analysis has been developed for analyzing hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula model has been used as a useful tool for multivariate frequency analysis because the copula model has no limitation on deciding marginal distributions. Generally, the inference function for margin (IFM) and the maximum pseudo-likelihood (MPL) are the most common methods to estimate the copula parameter. However, the MPL method includes the non-parametric procedure which cannot consider the skewness of the data and suppress characteristics of the variables. In this study, the modified MPL method is presented by substituting the non-parametric procedure and assessed their performances with the Monte-Carlo simulation. In simulation procedure, the GEV distribution is selected as a population of marginal distribution with positive-skewed parameter set. Then, the estimated parameters from the IFM, MPL and modified MPL methods are compared to true value. [ABSTRACT FROM AUTHOR]

This study investigated the effect of different dietary fat levels in concentrate mixes on the growth performance, rumen characteristics, digestibility, blood metabolites, and methane emissions in growing Hanwoo steers. Thirty steers (386 ± 24.6 kg of body weight [BW]; 12 months old), blocked by BW, were randomly assigned to three dietary treatments with varying fat concentrations in concentrate mix (48, 74, and 99 g of ether extract per kg dry matte [DM]). The fat intake of the low-fat treatment represented 4.15% of the total dry matter intake (DMI), while the medium- and high-fat treatments accounted for 5.77% and 7.23% of total DMI, respectively. Concentrate mix DMI decreased with increasing fat level ( p < 0.01). The growth rate and digestibility did not significantly differ based on the fat level ( p > 0.05). As the fat level increased, propionate in the total ruminal volatile fatty acids increased, and butyrate and acetate-to-propionate decreased ( p < 0.01). Cholesterol in blood serum increased significantly with increasing dietary fat levels ( p < 0.01). Methane emissions exhibited a linear decrease with increasing fat level ( p < 0.05). In conclusion, elevating fat content in the concentrates up to 100 g/kg DM reduced methane emissions without compromising the growth performance of growing Hanwoo steers.

This study aimed to assess the influence of rice grain in the total mixed ration (TMR) on the growth performance, blood metabolites, rumen fermentation, and rumen microbial community of fattening Hanwoo steers. Two experimental diets were prepared: (i) a TMR containing 33% dry matter (DM) corn grains (Corn TMR) and (ii) a TMR containing 33% DM rice grains (Rice TMR). Twenty-two Hanwoo steers (body weight [BW], 498 ± 32 kg; months, 17 ± 0.5) were distributed into two treatment groups in a completely randomized block design according to BW. The Rice TMR group had a higher final BW and DM intake (DMI) compared to those in the Corn TMR group ( p < 0.01). However, no difference was observed in the average daily gain (ADG) and feed conversion ratio (FCR) between the two treatments. For the rumen fermentation parameters, the molar portion of butyrate in the Rice TMR was higher than in the Corn TMR ( p < 0.01). Streptococcus bovis tended to be higher in the Rice TMR ( p = 0.09). The results of this study suggest that using rice grain as the primary starch source in TMRs may be an alternative option for fattening Hanwoo steers.

Objective: The objective of this study was to develop a novel endolysin (PanLys.1) for the specific killing of the ruminal hyper-ammonia-producing bacterium Peptostreptococcus anaerobius (P. anaerobius)., Methods: Whole genome sequences of P. anaerobius strains and related bacteriophages were collected from the National Center for Biotechnology Information database, and the candidate gene for PanLys.1 was isolated based on amino acid sequences and conserved domain database (CDD) analysis. The gene was overexpressed using a pET system in Escherichia coli BL21 (DE3). The lytic activity of PanLys.1 was evaluated under various conditions (dosage, pH, temperature, NaCl, and metal ions) to determine the optimal lytic activity conditions. Finally, the killing activity of PanLys.1 against P. anaerobius was confirmed using an in vitro rumen fermentation system., Results: CDD analysis showed that PanLys.1 has a modular design with a catalytic domain, amidase-2, at the N-terminal, and a cell wall binding domain, from the CW-7 superfamily, at the C-terminal. The lytic activity of PanLys.1 against P. anaerobius was the highest at pH 8.0 (p<0.05) and was maintained at 37°C to 45°C, and 0 to 250 mM NaCl. The activity of PanLys.1 significantly decreased (p<0.05) after Mn2+ or Zn2+ treatment. The relative abundance of P. anaerobius did not decrease after administration PanLys.1 under in vitro rumen conditions., Conclusion: The application of PanLys.1 to modulate P. anaerobius in the rumen might not be feasible because its lytic activity was not observed in in vitro rumen system.

The main objective of this in vitro study was to evaluate red ginseng byproduct (RGP) as a protein resource and its effects on rumen fermentation characteristics, microflora, CO 2 , and CH 4 production in ruminants. Four treatments for in vitro fermentation using buffered rumen fluid over a 48 h incubation period were used: 1, RGP; 2, corn gluten feed (CGF); 3, wheat gluten (WG); and 4, corn germ meal. In vitro dry matter digestibility (IVDMD), in vitro neutral detergent fiber digestibility (IVNDFD), in vitro crude protein digestibility (IVCPD), volatile fatty acids, pH, and ammonia nitrogen (NH 3 -N) were estimated after 48 h incubation. Gas production was investigated after 3, 6, 12, 24, 36 and 48 h. The CO 2 and CH 4 were evaluated after 12, 24, 36, and 48 h. A significant difference in total gas production and CO 2 emissions was observed ( p < 0.01) at all incubation times. CH 4 production in RGP were higher ( p < 0.05) than that in other treatments but a higher CH 4 portion in the total gas production was observed in WG ( p < 0.05) at 48 h incubation. The IVDMD, IVNDFD, and IVCPD of RGP was lower than those of other conventional ingredients ( p < 0.01). The RGP had the lowest NH 3 -N value among the treatments ( p < 0.01). The RGP also had the lowest total VFA concentration ( p < 0.01), but presented the highest acetate proportion and acetate to propionate ratio among the treatments (both, p < 0.01). The abundance of Prevotella ruminicola was higher in RGP than in WG ( p < 0.01), whereas RGP has lower methanogenic archaea ( p < 0.01). In conclusion, based on the nutritive value, IVDMD, low NH 3 -N, and decreased methanogenic archaea, RGP inclusion as a protein source in ruminant diets can be an option in replacing conventional feed sources., Competing Interests: No potential conflict of interest relevant to this article was reported., (© Copyright 2020 Korean Society of Animal Science and Technology.)

Objective: The objective of this study was to evaluate the effects of lysophospholipids (LPL) supplementation on rumen fermentation, degradability, and microbial diversity in forage with high oil diet in an in vitro system., Methods: Four experimental treatments were used: i) annual ryegrass (CON), ii) 93% annual ryegrass +7% corn oil on a dry matter (DM) basis (OiL), iii) OiL with a low level (0.08% of dietary DM) of LPL (LLPL), and iv) OiL with a high level (0.16% of dietary DM) of LPL (HLPL). An in vitro fermentation experiment was performed using strained rumen fluid for 48 h incubations. In vitro DM degradability (IVDMD), in vitro neutral detergent fiber degradability, pH, ammonia nitrogen (NH3-N), volatile fatty acid (VFA), and microbial diversity were estimated., Results: There was no significant change in IVDMD, pH, NH3-N, and total VFA production among treatments. The LPL supplementation significantly increased the proportion of butyrate and valerate (Linear effect [Lin], p = 0.004 and <0.001, respectively). The LPL supplementation tended to increase the total bacteria in a linear manner (p = 0.089). There were significant decreases in the relative proportions of cellulolytic (Fibrobacter succinogenes and Ruminococcus albus) and lipolytic (Anaerovibrio lipolytica and Butyrivibrio proteoclasticus) bacteria with increasing levels of LPL supplementation (Lin, p = 0.028, 0.006, 0.003, and 0.003, respectively)., Conclusion: The LPL supplementation had antimicrobial effects on several cellulolytic and lipolytic bacteria, with no significant difference in nutrient degradability (DM and neutral detergent fiber) and general bacterial counts, suggesting that LPL supplementation might increase the enzymatic activity of rumen bacteria. Therefore, LPL supplementation may be more effective as an antimicrobial agent rather than as an emulsifier in the rumen.

This study determined the substitution effects of rice for corn as the main grain source in a total mixed ration (TMR). In vitro rumen fermentation characteristics and microbes were assessed using two experimental diets. Diets included 33% dry matter (DM) of either corn (Corn TMR) or rice grains (Rice TMR). In a 48-h in vitro incubation, DM digestibility (IVDMD), neutral detergent fiber degradability (IVNDFD), crude protein digestibility (IVCPD), volatile fatty acids (VFAs), pH and ammonia nitrogen (NH 3 -N) were estimated. Gas production has been calculated at 3, 6, 12, 24 and 48 h. Our results indicate that the gas production, VFAs, IVDMD, and IVNDFD of Rice TMR were higher than those of Corn TMR ( p < 0.05). Ruminal pH and total fungi were significantly higher in Corn TMR ( p < 0.05) than in Rice TMR; however, NH 3 -N and IVCPD were not affected by treatment type. In conclusion, substituting rice for corn at 33% DM in TMR appears to have no negative effects on in vitro rumen fermentation characteristics. Therefore, rice grains are an appropriate alternative energy source in early fattening stage diets of beef cattle., Competing Interests: No potential conflict of interest relevant to this article was reported., (© Copyright 2020 Korean Society of Animal Science and Technology.)

Objective: This study was realized to evaluate the nutritional value of rice grains as a replacement for corn grains in the diet of growing Hanwoo steers., Methods: Two experimental diets were prepared: i) Corn total mixed ration (TMR) consisting of 20% corn grains and ii) Rice TMR consisting of 20% rice grains, in a dry matter (DM) basis. These treatments were used for in vitro rumen fermentation and in vivo growth trials. In the rumen fermentation experiment, the in vitro DM digestibility (IVDMD), in vitro crude protein digestibility (IVCPD), in vitro neutral detergent fiber digestibility, pH, ammonia nitrogen, and volatile fatty acids (VFA) were estimated at 48 h, and the gas production was measured at 3, 6, 12, 24, and 48 h. Twenty four growing Hanwoo steers (9 months old; body weight [BW]: 259±13 kg) were randomly divided into two treatment groups and the BW, dry matter intake (DMI), average daily gain (ADG), and feed conversion ratio (FCR) were measured., Results: The in vitro experiment showed that the IVDMD, IVCPD, and VFA production of the Rice TMR were higher than those of the Corn TMR (p<0.05). The growth trial showed no differences (p>0.05) in the final BW, ADG, DMI, and FCR between the two TMRs., Conclusion: The use of rice grains instead of corn grains did not exhibit any negative effects on the rumen fermentation or growth performance, thereby rice grains with a DM of less than 20% could be used as a starch source in the diet of growing steers.

The aim of this study was to investigate the effects of 3-nitrooxypropanol (NOP) on gas production, rumen fermentation, and animal performances depending on animal type using a meta-analysis approach. A database consisted of data from 14 studies, 18 experiments and 55 treatments. The supplementation of NOP linearly decreased methane (CH 4 ) emissions [g/kg dry matter intake (DMI)] regardless of animal type and length of experimental period (beef, p < 0.0001, R 2 = 0.797; dairy, p = 0.0003, R 2 = 0.916; and long term, p < 0.0001, R 2 = 0.910). The total volatile fatty acids (VFA) concentration and the proportion of acetate, based on beef cattle database, were significantly decreased with increasing NOP supplementation ( p = 0.0015, R 2 = 0.804 and p = 0.0003, R 2 = 0.918), whereas other individual VFAs was increased. Based on the dairy database, increasing levels of NOP supplementation linearly decreased proportion of acetate ( p = 0.0284, R 2 = 0.769) and increased that of valerate ( p = 0.0340, R 2 = 0.522), regardless of significant change on other individual VFAs. In animal performances, the DMI, from beef cattle database, tended to decrease when the levels of NOP supplementation increased ( p = 0.0574, R 2 = 0.170), whereas there was no significant change on DMI from dairy cattle database. The NOP supplementation tended to decrease milk yield ( p = 0.0606, R 2 = 0.381) and increase milk fat and milk protein ( p = 0.0861, R 2 = 0.321, p = 0.0838, R 2 = 0.322). NOP is a viable candidate as a feed additive because of its CH 4 mitigation effects, regardless of animal type and experiment period, without adverse effects on animal performances., Competing Interests: No potential conflict of interest relevant to this article was reported., (© Copyright 2020 Korean Society of Animal Science and Technology.)

Objective: The objective of this study was to investigate the effects of essential oil mixture (EOM) supplementation on rumen fermentation characteristics and microbial changes in an in vitro., Methods: Three experimental treatments were used: control (CON, no additive), EOM 0.1 (supplementation of 1 g EOM/kg of substrate), and EOM 0.2 (supplementation of 2 g EOM/kg of substrate). An in vitro fermentation experiment was carried out using strained rumen fluid for 12 and 24 h incubation periods. At each time point, in vitro dry matter digestibility (IVDMD), neutral detergent fiber digestibility (IVNDFD), pH, ammonia nitrogen (NH3-N), and volatile fatty acid (VFA) concentrations, and relative microbial diversity were estimated., Results: After 24 h incubation, treatments involving EOM supplementation led to significantly higher IVDMD (treatments and quadratic effect; p = 0.019 and 0.008) and IVNDFD (linear effect; p = 0.068) than did the CON treatment. The EOM 0.2 supplementation group had the highest NH3-N concentration (treatments; p = 0.032). Both EOM supplementations did not affect total VFA concentration and the proportion of individual VFAs; however, total VFA tended to increase in EOM supplementation groups, after 12 h incubation (linear; p = 0.071). Relative protozoa abundance significantly increased following EOM supplementation (treatments, p<0.001). Selenomonas ruminantium and Ruminococcus albus (treatments; p<0.001 and p = 0.005), abundance was higher in the EOM 0.1 treatment group than in CON. The abundance of Butyrivibrio fibrisolvens, fungi and Ruminococcus flavefaciens (treatments; p< 0.001, p<0.001, and p = 0.005) was higher following EOM 0.2 treatment., Conclusion: The addition of newly developed EOM increased IVDMD, IVNDFD, and tended to increase total VFA indicating that it may be used as a feed additive to improve rumen fermentation by modulating rumen microbial communities. Further studies would be required to investigate the detailed metabolic mechanism underlying the effects of EOM supplementation.