• Title/Summary/Keyword: ANIMAL MODEL

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Antimicrobial Activity of Propolis Extract and Their Application as a Natural Preservative in Livestock Products: A Meta-Analysis

  • Andre, Andre;Arief, Irma Isnafia;Apriantini, Astari;Jayanegara, Anuraga;Budiman, Cahyo
    • Food Science of Animal Resources
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    • v.42 no.2
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    • pp.280-294
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    • 2022
  • This study aimed to evaluate the effectiveness of propolis extract as a natural preservative for livestock products in term of chemical and microbiological characteristics by meta-analysis. The stages carried out in this study were identification, selection, checking suitability, and the resulting selected articles were used in the meta-analysis. The selection results obtained a total of 22 selected journal articles consisting of 9 articles for analysis of the antimicrobial activity of propolis extract and 13 articles for analysis of the chemical and mirobiological characteristics of livestock products. The articles were obtained from electronic databases, namely Science Direct and Google Scholar. The model used in this study is the random-effect model involving two groups, control and experimental. Heterogeneity and effect size values were carried out in this study using Hedge's obtained through openMEE software. Forest plot tests and data validation on publication bias was obtained using Kendall's test throught JASP 0.14.1 software. The results showed that there is a significant relationship between propolis extract with the results of the antimicrobial activity (p<0.05). In addition, the results of the application of propolis extract on the livestock products for the test microbes and the value of thiobarbituric acid reactive substances (TBARs) showed significant results (p<0.05). Conclusion based on the random-effect model on the effectiveness of antimicrobial activity of propolis extract and their apllication as a natural preservative of the chemical and microbiological characteristics of livestock products is valid by Kendall's test (p>0.05). Propolis in this case effectively used as natural preservatives in livestock products.

A Research on Yield Prediction of Mixed Pastures in Korea via Model Construction in Stages (혼파초지에서 모형의 단계적 적용을 통한 수량예측 연구)

  • Oh, Seung Min;Kim, Moon Ju;Peng, Jinglun;Lee, Bae Hun;Kim, Ji Yung;Kim, Byong Wan;Jo, Mu Hwan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.37 no.1
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    • pp.80-91
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    • 2017
  • The objective of this study was to select a model showing high-levels of interpretability which is high in R-squared value in terms of predicting the yield in the mixed pasture using the factors of fertilization, seeding rate and years after pasture establishment in steps, as well as the climate as a basic factor. The processes of constructing the yield prediction model for the mixed pasture were performed in the sequence of data collection (forage and climatic data), preparation, analysis, and model construction. Through this process, six models were constructed after considering climatic variables, fertilization management, seeding rates, and periods after pasture establishment years in steps, thereafter the optimum model was selected through considering the coincidence of the models to the forage production theories. As a result, Model VI (R squared = 53.8%) including climatic variables, fertilization amount, seeding rates, and periods after pasture establishment was considered as the optimum yield prediction model for mixed pastures in South Korea. The interpretability of independent variables in the model were decreased in the sequence of climatic variables(24.5%), fertilization amount(17.8%), seeding rates(10.7%), and periods after pasture establishment(0.8%). However, it is necessary to investigate the reasons of positive correlation between dry matter yield and days of summer depression (DSD) by considering cultivated locations and using other cumulative temperature related variables instead of DSD. Meanwhile the another research about the optimum levels of fertilization amounts and seeding rates is required using the quadratic term due to the certain value-centered distribution of these two variables.

Low Protein Digestibility of Beef Puree in Infant In Vitro Digestion Model

  • Lee, Seonmin;Jo, Kyung;Hur, Sun Jin;Choi, Yun-Sang;Kim, Hyun-Joo;Jung, Samooel
    • Food Science of Animal Resources
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    • v.39 no.6
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    • pp.1000-1007
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    • 2019
  • This study investigated protein digestibility of beef puree in infant and adult in vitro digestion models. The simulated digestive juices for infant and adult were prepared. Protein digestibility of beef puree was calculated in the gastric and gastrointestinal compartments. The 10% trichloroacetic acid soluble nitrogen and α-amino group contents of gastric digesta were lower in the infant in vitro digestion model than those in the adult in vitro digestion model (p<0.05). In addition, the gastrointestinal digesta from the infant in vitro digestion model had lower value of the 10% trichloroacetic acid soluble nitrogen and α-amino group contents than those of the adult in vitro digestion model (p<0.05). The results of sodium dodecyl sulfate-polyacrylamide gel electrophoresis showed that the remarkable bands of actin and myosin light chain B were found in the digesta of beef puree from the infant in vitro digestion model. The results of this study revealed the lower protein digestibility of beef puree in infants compared to that in adults. Therefore, the development of ways to increase digestibility of meat protein can improve the nutritional quality of meat products for infants.

Genetic parameters for worm resistance in Santa Inês sheep using the Bayesian animal model

  • Rodrigues, Francelino Neiva;Sarmento, Jose Lindenberg Rocha;Leal, Tania Maria;de Araujo, Adriana Mello;Filho, Luiz Antonio Silva Figueiredo
    • Animal Bioscience
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    • v.34 no.2
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    • pp.185-191
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    • 2021
  • Objective: The objective of this study was to estimate the genetic parameters for worm resistance (WR) and associated characteristics, using the linear-threshold animal model via Bayesian inference in single- and multiple-trait analyses. Methods: Data were collected from a herd of Santa Inês breed sheep. All information was collected with animals submitted to natural contamination conditions. All data (number of eggs per gram of feces [FEC], Famacha score [FS], body condition score [BCS], and hematocrit [HCT]) were collected on the same day. The animals were weighed individually on the day after collection (after 12-h fasting). The WR trait was defined by the multivariate cluster analysis, using the FEC, HCT, BCS, and FS of material collected from naturally infected sheep of the Santa Inês breed. The variance components and genetic parameters for the WR, FEC, HCT, BCS, and FS traits were estimated using the Bayesian inference under the linear and threshold animal model. Results: A low magnitude was obtained for repeatability of worm-related traits. The mean values estimated for heritability were of low-to-high (0.05 to 0.88) magnitude. The FEC, HCT, BCS, FS, and body weight traits showed higher heritability (although low magnitude) in the multiple-trait model due to increased information about traits. All WR characters showed a significant genetic correlation, and heritability estimates ranged from low (0.44; single-trait model) to high (0.88; multiple-trait model). Conclusion: Therefore, we suggest that FS be included as a criterion of ovine genetic selection for endoparasite resistance using the trait defined by multivariate cluster analysis, as it will provide greater genetic gains when compared to any single trait. In addition, its measurement is easy and inexpensive, exhibiting greater heritability and repeatability and a high genetic correlation with the trait of resistance to worms.

Variance component analysis of growth and production traits in Vanaraja male line chickens using animal model

  • Ullengala, Rajkumar;Prince, L. Leslie Leo;Paswan, Chandan;Haunshi, Santosh;Chatterjee, Rudranath
    • Animal Bioscience
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    • v.34 no.4
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    • pp.471-481
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    • 2021
  • Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

Inclusion of bioclimatic variables in genetic evaluations of dairy cattle

  • Negri, Renata;Aguilar, Ignacio;Feltes, Giovani Luis;Machado, Juliana Dementshuk;Neto, Jose Braccini;Costa-Maia, Fabiana Martins;Cobuci, Jaime Araujo
    • Animal Bioscience
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    • v.34 no.2
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    • pp.163-171
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    • 2021
  • Objective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models. Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models. Results: The THI and DTV thresholds for milk yield losses was THI = 74 (-0.106 kg/d/THI) and DTV = 13 (-0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (-2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model. Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability.

Evaluation of porcine intestinal organoids as an in vitro model for mammalian orthoreovirus 3 infection

  • Se-A Lee;Hye Jeong Lee;Na-Yeon Gu;Yu-Ri Park;Eun-Ju Kim;Seok-Jin Kang;Bang-Hun Hyun;Dong-Kun Yang
    • Journal of Veterinary Science
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    • v.24 no.4
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    • pp.53.1-53.12
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    • 2023
  • Background: Mammalian orthoreovirus type 3 (MRV3), which is responsible for gastroenteritis in many mammalian species including pigs, has been isolated from piglets with severe diarrhea. However, the use of pig-derived cells as an infection model for swine-MRV3 has rarely been studied. Objectives: This study aims to establish porcine intestinal organoids (PIOs) and examine their susceptibility as an in vitro model for intestinal MRV3 infection. Methods: PIOs were isolated and established from the jejunum of a miniature pig. Established PIOs were characterized using polymerase chain reaction (PCR) and immunofluorescence assays (IFAs) to confirm the expression of small intestine-specific genes and proteins, such as Lgr5, LYZI, Mucin-2, ChgA, and Villin. The monolayered PIOs and three-dimensional (3D) PIOs, obtained through their distribution to expose the apical surface, were infected with MRV3 for 2 h, washed with Dulbecco's phosphate-buffered saline, and observed. Viral infection was confirmed using PCR and IFA. We performed quantitative real-time reverse transcription-PCR to assess changes in viral copy numbers and gene expressions linked to intestinal epithelial genes and antiviral activity. Results: The established PIOs have molecular characteristics of intestinal organoids. Infected PIOs showed delayed proliferation with disruption of structures. In addition, infection with MRV3 altered the gene expression linked to intestinal epithelial cells and antiviral activity, and these effects were observed in both 2D and 3D models. Furthermore, viral copy numbers in the supernatant of both models increased in a time-dependent manner. Conclusions: We suggest that PIOs can be an in vitro model to study the infection mechanism of MRV3 in detail, facilitating pharmaceutical development.

A GENERAL SIMULATION MODEL FOR CATTLE GROWTH AND BEEF PRODUCTION

  • Hirooka, H.;Yamada, Y.
    • Asian-Australasian Journal of Animal Sciences
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    • v.3 no.3
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    • pp.205-218
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    • 1990
  • A general model was developed to simulate cattle growth and beef production. The present model was constructed, based on ARC metabolizable energy system in principle, and incorporated up-to-date knowledge and information into previous models, which were reported by Sanders and Cartwright (1979a,b) and Kahn (1982). The model may apply to cover a wide range of genetic and environmental conditions, because many factors relating to cattle growth and beef production are taken into consideration. The model may provide better understanding of various components and processes of beef cattle production systems.

Model Prediction of Nutrient Supply to Ruminants from Processed Field Tick Beans

  • Yu, P.;Christensen, D.A.
    • Asian-Australasian Journal of Animal Sciences
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    • v.17 no.12
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    • pp.1674-1680
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    • 2004
  • The objective of this study was to compare the Dutch DVE/OEB system and the NRC-2001 model in the prediction of supply of protein to dairy cows from processed field tick beans. Comparisons were made in terms of 1) ruminally synthesized microbial CP, 2) truly absorbed protein in the small intestine, and 3) degraded protein balance. The results showed that the predicted values from the DVE/OEB system and the NRC-2001 model had significant correlations with high R (>0.90) values. However, using the DVE/OEB system, the overall average microbial protein supply based on available energy was 16% higher and the truly absorbed protein in the small intestine was 9% higher than that predicted by the NRC-2001 model. The difference was also found in the prediction of the degraded protein balances (DPB), which was 5% lower than that predicted based on data from the NRC-2001 model. These differences are due to considerably different factors used in calculations in the two models, although both are based on similar principles. It need to mention that this comparison was based on the limited data, the full comparison involving various types of concentrate feeds will be investigated in the future.