• Title/Summary/Keyword: Random yield

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Association of Leptin Polymorphism with Production, Reproduction and Plasma Glucose Level in Iranian Holstein Cows

  • Moussavi, A. Heravi;Ahouei, M.;Nassiry, M.R.;Javadmanesh, A.
    • Asian-Australasian Journal of Animal Sciences
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    • v.19 no.5
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    • pp.627-631
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    • 2006
  • The objective of this study was to evaluate the association of genetic differences in the bovine leptin gene and milk yield, reproduction, body condition score (BCS), and plasma glucose level in Iranian Holstein cows. In total, two hundred and thirty eight cows were used and genotyped for a restricted fragment length polymorphism at the leptin gene locus. Two genotypes, AA and AB, have been distinguished which have the frequencies of 0.89 and 0.11, respectively. The genotypes were distributed according to the Hardy - Weinberg equilibrium ($x^2$ = 0.733). During the first 12 wk of lactation, milk yield and composition, live weight, BCS and plasma glucose were measured in 50 cows. Data were analyzed based on a repeated measures ANOVA. During this period, milk yield and composition, live weight, BCS and plasma glucose level were similar among the genotypes. The first cumulative 60-d milk yield, 305-d milk yield, days to first breeding, days open and days from first breeding to conception using previous lactation records were also analyzed using Standard Least Square within mixed models. Fixed effects were year, season, parity and age at calving, and sire. For the reproductive traits the cumulative first 60-d milk yield was also added to the model. Animal was fitted as a random effect. A significant association was detected between the RFLP-AB genotype and 305-d milk yield (p<0.05). The first 60-d cumulative milk yield was similar for the two genotypes (p = 0.21) and tended to be higher in the heterozygous cows. The heterozygous genotypes at the above mentioned locus had a trend to better reproductive performance than the homozygous. The results demonstrate that the RFLP B-allele can yield a higher 305-d milk production with a trend to better reproductive performance.

A Model for Determining Optimal Input Quantity in a Semiconductor Production Line Considering Yield Randomness and Demand Uncertainty (불확실한 수율과 수요를 고려한 반도체 생산라인에서의 최적 투입량 결정모형)

  • 박광태;안봉근
    • Journal of the Korean Operations Research and Management Science Society
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    • v.20 no.1
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    • pp.27-34
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    • 1995
  • In this paper, we have developed a model to determine the input quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need reworking at this stage. Yield randomness. especially in a semiconductor industry, is a most challenging problem for production control. The demand for flnal product is uncertain. We have extended the model proposed in Park and Kim[9] to consider a multiple number of reworkings which can be done at any stage prior to or tat the stage whose output in bad, depending on the level of the defect.

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Application of data mining and statistical measurement of agricultural high-quality development

  • Yan Zhou
    • Advances in nano research
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    • v.14 no.3
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    • pp.225-234
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    • 2023
  • In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

An accurate substructural synthesis approach to random responses

  • Ying, Z.G.;Zhu, W.Q.;Ye, S.Q.;Ni, Y.Q.
    • Structural Engineering and Mechanics
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    • v.39 no.1
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    • pp.47-75
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    • 2011
  • An accurate substructural synthesis method including random responses synthesis, frequency-response functions synthesis and mid-order modes synthesis is developed based on rigorous substructure description, dynamic condensation and coupling. An entire structure can firstly be divided into several substructures according to different functions, geometric and dynamic characteristics. Substructural displacements are expressed exactly by retained mid-order fixed-interfacial normal modes and residual constraint modes. Substructural interfacial degree-of-freedoms are eliminated by interfacial displacements compatibility and forces equilibrium between adjacent substructures. Then substructural mode vibration equations are coupled to form an exact-condensed synthesized structure equation, from which structural mid-order modes are calculated accurately. Furthermore, substructural frequency-response function equations are coupled to yield an exact-condensed synthesized structure vibration equation in frequency domain, from which the generalized structural frequency-response functions are obtained. Substructural frequency-response functions are calculated separately by using the generalized frequency-response functions, which can be assembled into an entire-structural frequency-response function matrix. Substructural power spectral density functions are expressed by the exact-synthesized substructural frequency-response functions, and substructural random responses such as correlation functions and mean-square responses can be calculated separately. The accuracy and capacity of the proposed substructure synthesis method is verified by numerical examples.

Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

  • Meseret, S.;Tamir, B.;Gebreyohannes, G.;Lidauer, M.;Negussie, E.
    • Asian-Australasian Journal of Animal Sciences
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    • v.28 no.9
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    • pp.1226-1234
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    • 2015
  • The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days

  • Yamazaki, Takeshi;Takeda, Hisato;Hagiya, Koichi;Yamaguchi, Satoshi;Sasaki, Osamu
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.10
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    • pp.1542-1549
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    • 2018
  • Objective: Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a RR model. Methods: We analyzed test-day milk records from 85,690 Holstein cows in their first lactations and 131,727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. Results: The first-order Legendre polynomials were practical covariates of RR for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Conclusion: Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

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.

Variance Components and Genetic Parameters for Milk Production and Lactation Pattern in an Ethiopian Multibreed Dairy Cattle Population

  • Gebreyohannes, Gebregziabher;Koonawootrittriron, Skorn;Elzo, Mauricio A.;Suwanasopee, Thanathip
    • Asian-Australasian Journal of Animal Sciences
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    • v.26 no.9
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    • pp.1237-1246
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    • 2013
  • The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

Yield and Fracture of Paper

  • Park, Jong-moon;James L. Thorpe
    • Journal of Korea Technical Association of The Pulp and Paper Industry
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    • v.31 no.5
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    • pp.57-72
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    • 1999
  • Traditional theories of the tensile failure of paper have assumed that uniform strain progresses throughout the sheet until an imperfection within the structure causes a catastrophic break. The resistance to tensile elongation is assumed to be elastic , at first, throughout the structure, followed by an overall plastic yield. However, linear image strain analysis (LISA) has demonstrated that the yield in tensile loading of paper is quite non-uniform throughout the structure, Traditional theories have failed to define the flaws that trigger catastrophic failure. It was assumed that a shive or perhaps a low basis weight area filled that role. Studies of the fracture mechanics of paper have typically utilized a well-defined flaw around which yield and failure could be examined . The flaw was a simple razor cut normal to the direction of tensile loading. Such testing is labeled mode I analysis. The included fla in the paper was always normal to the tensile loading direction, never at another orientation . However, shives or low basis weight zones are likely to be at random angular orientations in the sheet. The effects of angular flaws within the tensile test were examined. The strain energy density theory and experimental work demonstrate the change in crack propagation from mode I to mode IIas the initial flaw angle of crack propagation as a function of the initial flaw angle is predicted and experimentally demonstrated.

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Estimation of Genetic, Phenotypic and Environmental Trends in Hariana Cattle

  • Singh, K.;Sangwan, M.L.;Dalal, D.S.
    • Asian-Australasian Journal of Animal Sciences
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    • v.15 no.1
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    • pp.7-10
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    • 2002
  • The breeding data relating to Hariana herd spread over 18 years (1979-96) were analysed to estimate genetic, phenotypic and environmental changes in characters of economic importance which might have taken place during the several years of selective breeding practiced in the herd. The average genetic changes in a given character were estimated by four methods. The phenotypic trends observed for different economic traits were not significant. On changing the method of estimation, magnitude and direction of genetic trends changed. Comparison of estimates of genetic trends by different methods showed that adjustments for biases due to non-random allotment of dams with respect to their age and merit suggested by Powell and Freeman (1974) were useful for increasing the precision of the estimates. Hence, this method was found to be the best method for estimation of genetic trends. The estimate of genetic trends by this method were 4.03${\pm}$6.21 days, 3.24${\pm}$5.33 kg, 0.15${\pm}$0.43 days, 0.09${\pm}$0.59 days, 0.01${\pm}$0.02 kg and 0.01${\pm}$0.01 kg for age at first calving, first lactation milk yield, first lactation length, first calving interval, first lactation milk yield per day lactation length and first lactation milk yield per day of calving interval, respectively.