• Title/Summary/Keyword: selection index

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Effects of selection index coefficients that ignore reliability on economic weights and selection responses during practical selection

  • Togashi, Kenji;Adachi, Kazunori;Yasumori, Takanori;Kurogi, Kazuhito;Nozaki, Takayoshi;Onogi, Akio;Atagi, Yamato;Takahashi, Tsutomu
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.1
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    • pp.19-25
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    • 2018
  • Objective: In practical breeding, selection is often performed by ignoring the accuracy of evaluations and applying economic weights directly to the selection index coefficients of genetically standardized traits. The denominator of the standardized component trait of estimated genetic evaluations in practical selection varies with its reliability. Whereas theoretical methods for calculating the selection index coefficients of genetically standardized traits account for this variation, practical selection ignores reliability and assumes that it is equal to unity for each trait. The purpose of this study was to clarify the effects of ignoring the accuracy of the standardized component trait in selection criteria on selection responses and economic weights in retrospect. Methods: Theoretical methods were presented accounting for reliability of estimated genetic evaluations for the selection index composed of genetically standardized traits. Results: Selection responses and economic weights in retrospect resulting from practical selection were greater than those resulting from theoretical selection accounting for reliability when the accuracy of the estimated breeding value (EBV) or genomically enhanced breeding value (GEBV) was lower than those of the other traits in the index, but the opposite occurred when the accuracy of the EBV or GEBV was greater than those of the other traits. This trend was more conspicuous for traits with low economic weights than for those with high weights. Conclusion: Failure of the practical index to account for reliability yielded economic weights in retrospect that differed from those obtained with the theoretical index. Our results indicated that practical indices that ignore reliability delay genetic improvement. Therefore, selection practices need to account for reliability, especially when the reliabilities of the traits included in the index vary widely.

Efficiency of Marker Assisted Selection(MAS) over The Phenotypic Selection for Economic Traits in Economic Animals (경제동물의 주요 경제형질에 대한 표지인자를 이용한 선발(MAS)의 효율성)

  • Jeon, Gwang-Joo
    • Journal of Animal Science and Technology
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    • v.44 no.6
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    • pp.669-676
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    • 2002
  • The efficiency of marker assisted selection(MAS) over conventional selection index based sorely on phenotypic records was studied by deterministic simulation model. Parameter combination of heritability and amount of genetic variation due to the markers included in the index was employed. For the index with own phenotypic information vs. the index with own phenotypic plus marker information, the relative efficiency of MAS over the selection with phenotypic records was about 38% high when heritability was low(0.05). However, when heritability was high(50%), the relative efficiency of MAS was vary low and almost negligible. For more practical situation of selection index which included information on own, sire and dam, MAS was less effective than when selection criteria was only on own performance.

Research on the Reformation of the Selection Index for Hanwoo Proven Bull (한우보증씨수소 선발지수 개선에 관한 연구)

  • Kim, Hyo-Sun;Hwang, Jeong-Mi;Choi, Tae-Jeong;Park, Byong-Ho;Cho, Kwang-Hyun;Park, Cheol-Jin;Kim, Si-Dong
    • Journal of Animal Science and Technology
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    • v.52 no.2
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    • pp.83-90
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    • 2010
  • Hanwoo proven bulls have been selected since 1987 and consequently contributed to farmers for the improvement of beef cattle in Korea. The demand for the quality beef production as well as higher production efficiency was erupted after early 2000 as relatively cheap imported beef released. Therefore the pressure on the reformation of selection index for Hanwoo proven bulls have been piled up to furnish with Hanwoo's competitive. A total of 734 progeny test data were analyzed to select traits and their weights in the selection index to meet the beef market requirement. Regression analysis with stepwise selection method was used to select proper trait and its weight for selection index. A series of computer simulation was carried out to compare the currently using selection index with the alternate two selection indices proposed in this study. New selection index using standardized breeding values of Loin eye Muscle Area (LMA), Backfat Thickness (BFT) and Marbling Score (MS) with weight ratio 1:-1:6 was proposed. Results showed higher performance in improving MS and BFT gain by 22% and 31% still holding 86%~89% of genetic gain achieved by current index in Carcass Weight (CW) and LMA when new selection index was fitted. Because, new index has little consideration for production cost, further research should be performed to build selection index including cost and income simultaneously.

Efficient estimation and variable selection for partially linear single-index-coefficient regression models

  • Kim, Young-Ju
    • Communications for Statistical Applications and Methods
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    • v.26 no.1
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    • pp.69-78
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    • 2019
  • A structured model with both single-index and varying coefficients is a powerful tool in modeling high dimensional data. It has been widely used because the single-index can overcome the curse of dimensionality and varying coefficients can allow nonlinear interaction effects in the model. For high dimensional index vectors, variable selection becomes an important question in the model building process. In this paper, we propose an efficient estimation and a variable selection method based on a smoothing spline approach in a partially linear single-index-coefficient regression model. We also propose an efficient algorithm for simultaneously estimating the coefficient functions in a data-adaptive lower-dimensional approximation space and selecting significant variables in the index with the adaptive LASSO penalty. The empirical performance of the proposed method is illustrated with simulated and real data examples.

Studies on the selection in soybean breeding. -II. Additional data on heritability, genotypic correlation and selection index- (대두육종에 있어서의 선발에 관한 실험적연구 -속보 : 유전력ㆍ유전상관, 그리고 선발지수의 재검토-)

  • Kwon-Yawl Chang
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.3
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    • pp.89-98
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    • 1965
  • The experimental studies were intended to clarify the effects of selection, and also aimed at estimating the heritabilities, the genotypic correlations among some agronomic characters, and at calculating the selection index on some selective characters for the selection of desirable lines, under different climatic conditions. Finally practical implications of these studies, especially on the selection index, were discussed. Twenty-two varieties, determinate growing habit type, were selected at random from the 138 soybean varieties cultivated the year before, were grown in a randomized block design with three replicates at Chinju, Korea, under May and June sowing conditions. The method of estimating heritabilities for the eleven agronomic characters-flowering date, maturity date, stem length, branch numbers per plant, stem diameter, plant weight, pod numbers per plant, grain numbers per plant and 100 grain weight, shown in Table 3, was the variance components procedures in a replicated trial for the varieties. The analysis of covariance was used to obtain the genotypic correlations and phenotypic correlations among the eight characters, and the selection indexes for some agronomic characters were calculated by Robinson's method. The results are summarized as follows: Heritabilities : The experiment on the genotype-environment interaction revealed that in almost all of the characters investigated the interaction was too large to be neglected and materially affected the estimates of various genotypic parameters. The variation in heritability due to the change of environments was larger in the characters of low heritability than in those of high heritability. Heritability values of flowering date, fruiting period (days from flowering to maturity), stem length and 100 grain weight were the highest in both environments, those of yield(grain weight) and other characters were showed the lower values(Table 3). These heritability values showed a decreasing trend with the delayed sowing in the experiments. Further, all calculated heritability values were higher than anticipated. This was expected since these values, which were the broad sense heritability, contain the variance due to dominance and epistasisf in addition to the additive genetic variance. Genotypic correlations : Genotypic correlations were slightly higher than the corresponding phenotypic correlations in both environments, but the variation in values due to the change of environment appeared between grain weight and some other characters, especially an increase between grain weight and flowering date, and the total growing period(Table 6). Genotypic correlations between grain weight and other characters indicated that high seed yield was genetically correlated with late flowering, late maturity, and the other five characters namely branch numbers per plant, stem diameter, plant weight, pod numbers per plant and grain numbers per plant, but not with 100 grain weight of soybeans. Pod numbers and grain numbers per plant were more closely correlated with seed yields than with other characters. Selection index : For the comparison and the use of selection indexes in the selection, two kinds of selection indexes were calculated, the former was called selection index A and the later selection index B as shown in Table 7. Selection index A was calculated by the values of grain weight per plant as the character of yield(character Y), but the other, selection index B, was calculated by the values of pod numbers per plant, instead of grain weight per plant, as the character of yield'(character Y'). These results suggest that selection index technique is useful in soybean breeding. In reality, however, as the selection index varies with population and environment, it must be calculated in each population to which selection is applied and in each environment in which the population is located. In spite of the expected usefulness of selection index technique in soybean breeding, unsolved problems such as the expense, time and labor involved in calculating the selection index remain. For these reasons and from these experimental studies, it was recognized that in the breeding of self-fertilized soybean plants the selection for yield should be based on a more simple selection index such as selection index B of these experiments rather than on the complex selection index such as selection index A. Furthermore, it was realized that the selection index for the selection should be calculated on the basis of the data of some 3-4 agronomic characters-maturity date(X$_1$), branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant etc. It must be noted that it should be successful in selection to select for maturity date(X$_1$) which has high heritability, and the selection index should be calculated easily on the basis of the data of branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant, directly after the harvest before drying and threshing. These characters should be very useful agronomic characters in the selection of Korean soybeans, determinate growing habit type, as they could be measured or counted easily thus saving time and expense in the duration from harvest to drying and threshing, and are affected more in soybean yields than the other agronomic characters.

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A Variable Selection Procedure for K-Means Clustering

  • Kim, Sung-Soo
    • The Korean Journal of Applied Statistics
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    • v.25 no.3
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    • pp.471-483
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    • 2012
  • One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

Forecasting the Baltic Dry Index Using Bayesian Variable Selection (베이지안 변수선택 기법을 이용한 발틱건화물운임지수(BDI) 예측)

  • Xiang-Yu Han;Young Min Kim
    • Korea Trade Review
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    • v.47 no.5
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    • pp.21-37
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    • 2022
  • Baltic Dry Index (BDI) is difficult to forecast because of the high volatility and complexity. To improve the BDI forecasting ability, this study apply Bayesian variable selection method with a large number of predictors. Our estimation results based on the BDI and all predictors from January 2000 to September 2021 indicate that the out-of-sample prediction ability of the ADL model with the variable selection is superior to that of the AR model in terms of point and density forecasting. We also find that critical predictors for the BDI change over forecasts horizon. The lagged BDI are being selected as an key predictor at all forecasts horizon, but commodity price, the clarksea index, and interest rates have additional information to predict BDI at mid-term horizon. This implies that time variations of predictors should be considered to predict the BDI.

Lactation Persistency as a Component Trait of the Selection Index and Increase in Reliability by Using Single Nucleotide Polymorphism in Net Merit Defined as the First Five Lactation Milk Yields and Herd Life

  • Togashi, K.;Hagiya, K.;Osawa, T.;Nakanishi, T.;Yamazaki, T.;Nagamine, Y.;Lin, C.Y.;Matsumoto, S.;Aihara, M.;Hayasaka, K.
    • Asian-Australasian Journal of Animal Sciences
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    • v.25 no.8
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    • pp.1073-1082
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    • 2012
  • We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation ($r_G$) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL ($r_G$ = 0.118 and 0.257, respectively).

Comparisons of Index Numbers: An Application to Sawmills and Planing Mills Industry of U.S.

  • Ahn, SoEun
    • Journal of Korean Society of Forest Science
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    • v.94 no.2 s.159
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    • pp.82-89
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    • 2005
  • The purpose of this paper is to investigate index numbers by conducting various comparisons among the widely used index formulas. The comparison is considered in three ways; 1) divergences in the magnitudes of index numbers due to the use of different formulas (Laspeyres, Paasche, Fisher, and Tornqvist); 2) the effect of selection of base year (fixed-year base vs. chain-type); 3) the degree of approximation of indirect to direct quantity index. The empirical application is to sawmills and planing mills industry of U.S. using a national time series data covering years of 1948-2000. The results show that the differences between Laspeyres and Paasche index can be substantial in some cases while the difference between Fisher and Tornqvist index is minimal. We also confirm that the selection of base year can cause significant divergences, especially when the variables undergo rapid price or quantity changes over time. We find that indirect quantity index approximates direct quantity index reasonably well in U.S. sawmill industry.

A study on the selection of technology development supporting business by AHP method in a BSC viewpoint : Focused on Daejeon TP (BSC관점에서 AHP기법을 이용한 기술개발지원사업 선정에 관한 연구 : 대전테크노파크를 중심으로)

  • Gu, Jeong-Hee;Choi, Jong-In
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.8
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    • pp.3371-3380
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    • 2012
  • This paper finds the selecting evaluation index of technical development supporting business, applied to determine its validity. Measuring the new evaluation index for selection against the existing select evaluation index, it shows which index has accurately estimated the ranking of the companies with good performance. Using the BSC and AHP method, this study developed the select evaluation index of technology development supporting business.