Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP)
Reciprocal recurrent selection (RRS) has been adopted for oil palm breeding in Indonesia. Due to a long selection cycle and the large area required, a satisfactory oil palm progeny trial is difficult to conduct. Knowledge of the parental genetic parameters is very important in achieving the expected genetic progress, but the evaluation of these parameters is constrained by highly unbalanced data sets. In this study, the unbalanced agronomic data sets and the pedigree information of an oil palm breeding programme in Indonesia were analysed by using the restricted maximum likelihood (REML) and the best linear unbiased predictor (BLUP) methods. The characters analysed were bunch and oil yields of the adult period (from 7 to 9 years after planting). The coefficients of parentage varied from 0.125 to 0.891 and from zero to 0.750 between parents in the Deli and African groups, respectively. The average coefficients of inbreeding were 0.269 and 0.166 for the parents within the Deli and African groups, respectively. The additive variances of the bunch number, industrial oil-extraction rate and oil yield characters were higher in the parents of the Deli group than those in the African ones. The coefficients of correlation between the predicted and observed hybrids performances varied from 0.55 to 0.64 for oil yield, 0.49 to 0.71 for bunch number, 0.47 to 0.58 for bunch production, 0.48 to 0.64 for industrial oil-extraction rate and 0.42 to 0.56 for plant-height increment. For selection on the basis of oil yield character, BLUPs ability to predict single-cross performance should be sufficient, and will result in a significant contribution to the oil palm seed and clone productions.
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Subjects: | F30 - Génétique et amélioration des plantes, U10 - Informatique, mathématiques et statistiques, F01 - Culture des plantes, Elaeis guineensis, sélection récurrente, amélioration des plantes, technique de prévision, critère de sélection, facteur de rendement, paramètre génétique, http://aims.fao.org/aos/agrovoc/c_2509, http://aims.fao.org/aos/agrovoc/c_27595, http://aims.fao.org/aos/agrovoc/c_5956, http://aims.fao.org/aos/agrovoc/c_3041, http://aims.fao.org/aos/agrovoc/c_1078, http://aims.fao.org/aos/agrovoc/c_16091, http://aims.fao.org/aos/agrovoc/c_24847, http://aims.fao.org/aos/agrovoc/c_3840, |
Online Access: | http://agritrop.cirad.fr/481719/ http://agritrop.cirad.fr/481719/1/481719.pdf |
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dig-cirad-fr-4817192024-01-28T09:22:20Z http://agritrop.cirad.fr/481719/ http://agritrop.cirad.fr/481719/ Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP). Purba Abdul Razak, Flori Albert, Baudouin Luc, Hamon Serge. 2001. Theoretical and Applied Genetics, 102 (5) : 787-792.https://doi.org/10.1007/s001220051711 <https://doi.org/10.1007/s001220051711> Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) Purba, Abdul Razak Flori, Albert Baudouin, Luc Hamon, Serge eng 2001 Theoretical and Applied Genetics F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques F01 - Culture des plantes Elaeis guineensis sélection récurrente amélioration des plantes technique de prévision critère de sélection facteur de rendement paramètre génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_27595 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_1078 http://aims.fao.org/aos/agrovoc/c_16091 http://aims.fao.org/aos/agrovoc/c_24847 Indonésie http://aims.fao.org/aos/agrovoc/c_3840 Reciprocal recurrent selection (RRS) has been adopted for oil palm breeding in Indonesia. Due to a long selection cycle and the large area required, a satisfactory oil palm progeny trial is difficult to conduct. Knowledge of the parental genetic parameters is very important in achieving the expected genetic progress, but the evaluation of these parameters is constrained by highly unbalanced data sets. In this study, the unbalanced agronomic data sets and the pedigree information of an oil palm breeding programme in Indonesia were analysed by using the restricted maximum likelihood (REML) and the best linear unbiased predictor (BLUP) methods. The characters analysed were bunch and oil yields of the adult period (from 7 to 9 years after planting). The coefficients of parentage varied from 0.125 to 0.891 and from zero to 0.750 between parents in the Deli and African groups, respectively. The average coefficients of inbreeding were 0.269 and 0.166 for the parents within the Deli and African groups, respectively. The additive variances of the bunch number, industrial oil-extraction rate and oil yield characters were higher in the parents of the Deli group than those in the African ones. The coefficients of correlation between the predicted and observed hybrids performances varied from 0.55 to 0.64 for oil yield, 0.49 to 0.71 for bunch number, 0.47 to 0.58 for bunch production, 0.48 to 0.64 for industrial oil-extraction rate and 0.42 to 0.56 for plant-height increment. For selection on the basis of oil yield character, BLUPs ability to predict single-cross performance should be sufficient, and will result in a significant contribution to the oil palm seed and clone productions. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/481719/1/481719.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1007/s001220051711 10.1007/s001220051711 http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=166332 info:eu-repo/semantics/altIdentifier/doi/10.1007/s001220051711 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/s001220051711 |
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F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques F01 - Culture des plantes Elaeis guineensis sélection récurrente amélioration des plantes technique de prévision critère de sélection facteur de rendement paramètre génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_27595 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_1078 http://aims.fao.org/aos/agrovoc/c_16091 http://aims.fao.org/aos/agrovoc/c_24847 http://aims.fao.org/aos/agrovoc/c_3840 F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques F01 - Culture des plantes Elaeis guineensis sélection récurrente amélioration des plantes technique de prévision critère de sélection facteur de rendement paramètre génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_27595 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_1078 http://aims.fao.org/aos/agrovoc/c_16091 http://aims.fao.org/aos/agrovoc/c_24847 http://aims.fao.org/aos/agrovoc/c_3840 |
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F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques F01 - Culture des plantes Elaeis guineensis sélection récurrente amélioration des plantes technique de prévision critère de sélection facteur de rendement paramètre génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_27595 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_1078 http://aims.fao.org/aos/agrovoc/c_16091 http://aims.fao.org/aos/agrovoc/c_24847 http://aims.fao.org/aos/agrovoc/c_3840 F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques F01 - Culture des plantes Elaeis guineensis sélection récurrente amélioration des plantes technique de prévision critère de sélection facteur de rendement paramètre génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_27595 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_1078 http://aims.fao.org/aos/agrovoc/c_16091 http://aims.fao.org/aos/agrovoc/c_24847 http://aims.fao.org/aos/agrovoc/c_3840 Purba, Abdul Razak Flori, Albert Baudouin, Luc Hamon, Serge Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) |
description |
Reciprocal recurrent selection (RRS) has been adopted for oil palm breeding in Indonesia. Due to a long selection cycle and the large area required, a satisfactory oil palm progeny trial is difficult to conduct. Knowledge of the parental genetic parameters is very important in achieving the expected genetic progress, but the evaluation of these parameters is constrained by highly unbalanced data sets. In this study, the unbalanced agronomic data sets and the pedigree information of an oil palm breeding programme in Indonesia were analysed by using the restricted maximum likelihood (REML) and the best linear unbiased predictor (BLUP) methods. The characters analysed were bunch and oil yields of the adult period (from 7 to 9 years after planting). The coefficients of parentage varied from 0.125 to 0.891 and from zero to 0.750 between parents in the Deli and African groups, respectively. The average coefficients of inbreeding were 0.269 and 0.166 for the parents within the Deli and African groups, respectively. The additive variances of the bunch number, industrial oil-extraction rate and oil yield characters were higher in the parents of the Deli group than those in the African ones. The coefficients of correlation between the predicted and observed hybrids performances varied from 0.55 to 0.64 for oil yield, 0.49 to 0.71 for bunch number, 0.47 to 0.58 for bunch production, 0.48 to 0.64 for industrial oil-extraction rate and 0.42 to 0.56 for plant-height increment. For selection on the basis of oil yield character, BLUPs ability to predict single-cross performance should be sufficient, and will result in a significant contribution to the oil palm seed and clone productions. |
format |
article |
topic_facet |
F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques F01 - Culture des plantes Elaeis guineensis sélection récurrente amélioration des plantes technique de prévision critère de sélection facteur de rendement paramètre génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_27595 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_3041 http://aims.fao.org/aos/agrovoc/c_1078 http://aims.fao.org/aos/agrovoc/c_16091 http://aims.fao.org/aos/agrovoc/c_24847 http://aims.fao.org/aos/agrovoc/c_3840 |
author |
Purba, Abdul Razak Flori, Albert Baudouin, Luc Hamon, Serge |
author_facet |
Purba, Abdul Razak Flori, Albert Baudouin, Luc Hamon, Serge |
author_sort |
Purba, Abdul Razak |
title |
Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) |
title_short |
Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) |
title_full |
Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) |
title_fullStr |
Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) |
title_full_unstemmed |
Prediction of oil palm (Elaeis guineensis, Jacq.) agronomic performances using the best linear unbiased predictor (BLUP) |
title_sort |
prediction of oil palm (elaeis guineensis, jacq.) agronomic performances using the best linear unbiased predictor (blup) |
url |
http://agritrop.cirad.fr/481719/ http://agritrop.cirad.fr/481719/1/481719.pdf |
work_keys_str_mv |
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_version_ |
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