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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
05/07/2019 |
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Data da última atualização: |
30/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VOLPATO, L.; ALVES, R. S.; TEODORO, P. E.; RESENDE, M. D. V. de; NASCIMENTO, M.; NASCIMENTO, A. C. C.; LUDKE, W. H.; SILVA, F. L. da; BORÉM, A. |
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Afiliação: |
Leonardo Volpato, Universidade Federal de Viçosa; Rodrigo Silva Alves, Universidade Federal de Viçosa; Paulo Eduardo Teodoro, Universidade Federal de Mato Grosso do Sul; MARCOS DEON VILELA DE RESENDE, CNPF; Moysés Nascimento, Universidade Federal de Viçosa; Ana Carolina Campana Nascimento, Universidade Federal de Viçosa; Willian Hytalo Ludke, Universidade Federal de Viçosa; Felipe Lopes da Silva, Universidade Federal de Viçosa; Aluízio Borém, Universidade Federal de Viçosa. |
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Título: |
Multi-trait multi-environment models in the genetic selection of segregating soybean progeny. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
PLoS ONE, v. 14, n. 4, e0215315, Apr. 2019. 22 p. |
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DOI: |
10.1371/journal.pone.0215315 |
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Idioma: |
Inglês |
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Conteúdo: |
At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; h2 prog) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of h2 prog. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny. MenosAt present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; h2 prog) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided... Mostrar Tudo |
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Palavras-Chave: |
Bayesian-inference; Breeding values; Genomic selection; Inferência Bayesian; Mixed models; Modelo misto; Seed protein; Seleção genômica. |
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Thesagro: |
Soja. |
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Thesaurus Nal: |
Agronomic traits; Prediction; Soybeans. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/199239/1/2019-M.Deon-PO-Multi-trait.pdf
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Marc: |
LEADER 02789naa a2200373 a 4500
001 2110400
005 2019-10-30
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1371/journal.pone.0215315$2DOI
100 1 $aVOLPATO, L.
245 $aMulti-trait multi-environment models in the genetic selection of segregating soybean progeny.$h[electronic resource]
260 $c2019
520 $aAt present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; h2 prog) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of h2 prog. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny.
650 $aAgronomic traits
650 $aPrediction
650 $aSoybeans
650 $aSoja
653 $aBayesian-inference
653 $aBreeding values
653 $aGenomic selection
653 $aInferência Bayesian
653 $aMixed models
653 $aModelo misto
653 $aSeed protein
653 $aSeleção genômica
700 1 $aALVES, R. S.
700 1 $aTEODORO, P. E.
700 1 $aRESENDE, M. D. V. de
700 1 $aNASCIMENTO, M.
700 1 $aNASCIMENTO, A. C. C.
700 1 $aLUDKE, W. H.
700 1 $aSILVA, F. L. da
700 1 $aBORÉM, A.
773 $tPLoS ONE$gv. 14, n. 4, e0215315, Apr. 2019. 22 p.
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Registro original: |
Embrapa Florestas (CNPF) |
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Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
14/07/2023 |
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Data da última atualização: |
14/07/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
SILVA, A. M. M.; JONES, D. L.; CHADWICK, D. R.; QI, X.; COTTA, S. R.; ARAÚJO, V. L. V. P.; MATTEOLI, F. P.; LACERDA-JÚNIOR, G. V.; PEREIRA, A. P. A.; FERNANDES JUNIOR, P. I.; CARDOSO, E. J. B. N. |
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Afiliação: |
ANTONIO M. M. SILVA, ESALQ; DAVEY L. JONES, School of Natural Sciences, Bangor University, United Kingdom; DAVE R. CHADWICK, School of Natural Sciences, Bangor University, Bangor, United Kingdom; XUE QI, School of Natural Sciences, Bangor University, United Kingdom; SIMONE R. COTTA, USP/CENA; VICTOR L. V. P. ARAÚJO, ESALQ; FILIPE P. MATTEOLI, Laboratory of Microbial Bioinformatics, Department of Biological Sciences, Faculty of Sciences, São Paulo State University, Bauru; GILENO V. LACERDA JÚNIOR; ARTHUR P. A. PEREIRA, Federal University of Ceará, Fortaleza, CE; PAULO IVAN FERNANDES JUNIOR, CPATSA; ELKE J. B. N. CARDOSO, ESALQ. |
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Título: |
Can arbuscular mycorrhizal fungi and rhizobacteria facilitate P33 uptake in maize plants under water stress? |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Microbiological Research, v. 271, 127350, 2023. |
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DOI: |
https://doi.org/10.1016/j.micres.2023.127350 |
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Idioma: |
Inglês |
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Conteúdo: |
Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are able to provide key ecosystem services, protecting plants against biotic and abiotic stresses. Here, we hypothesized that a combination of AMF (Rhizophagus clarus) and PGPR (Bacillus sp.) could enhance 33P uptake in maize plants under soil water stress. A microcosm experiment using mesh exclusion and a radiolabeled phosphorus tracer (33P) was installed using three types of inoculation: i) only AMF, ii) only PGPR, and iii) a consortium of AMF and PGPR, alongside a control treatment without inoculation. For all treatments, a gradient of three water-holding capacities (WHC) was considered i) 30% (severe drought), ii) 50% (moderate drought), and iii) 80% (optimal condition, no water stress). In severe drought conditions, AMF root colonization of dual-inoculated plants was significantly lower compared to individual inoculation of the AMF, whilst 33P uptake by dual-inoculated plants or plants inoculated with bacteria was 2.4-fold greater than the uninoculated treatment. Under moderate drought conditions the use of AMF promoted the highest 33P uptake by plants, increasing it by 2.1-fold, when compared to the uninoculated treatment. Without drought stress, AMF showed the lowest 33P uptake and, overall, plant P acquisition was lower for all inoculation types when compared to the severe and moderate drought treatments. The total shoot P content was modulated by the water-holding capacity and inoculation type, with the lowest values observed under severe drought and the highest values under moderate drought. The highest soil electrical conductivity (EC) values were found under severe drought in AMF-inoculated plants and the lowest EC for no drought in single or dual-inoculated plants. Furthermore, water-holding capacity influenced the total soil bacterial and mycorrhizal abundance over time, with the highest abundances being found under severe and moderate drought. This study demonstrates that the positive influence of microbial inoculation on 33P uptake by plants varied with soil water gradient. Furthermore, under severe stress conditions, AMF invested more in the production of hyphae, vesicles and spore production, indicating a significant carbon drain from the host plant as evidenced by the lack of translation of increased 33P uptake into biomass. Therefore, under severe drought the use of bacteria or dual-inoculation seems to be more effective than individual AMF inoculation in terms of 33P uptake by plants, while under moderate drought, the use of AMF stood out. MenosArbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are able to provide key ecosystem services, protecting plants against biotic and abiotic stresses. Here, we hypothesized that a combination of AMF (Rhizophagus clarus) and PGPR (Bacillus sp.) could enhance 33P uptake in maize plants under soil water stress. A microcosm experiment using mesh exclusion and a radiolabeled phosphorus tracer (33P) was installed using three types of inoculation: i) only AMF, ii) only PGPR, and iii) a consortium of AMF and PGPR, alongside a control treatment without inoculation. For all treatments, a gradient of three water-holding capacities (WHC) was considered i) 30% (severe drought), ii) 50% (moderate drought), and iii) 80% (optimal condition, no water stress). In severe drought conditions, AMF root colonization of dual-inoculated plants was significantly lower compared to individual inoculation of the AMF, whilst 33P uptake by dual-inoculated plants or plants inoculated with bacteria was 2.4-fold greater than the uninoculated treatment. Under moderate drought conditions the use of AMF promoted the highest 33P uptake by plants, increasing it by 2.1-fold, when compared to the uninoculated treatment. Without drought stress, AMF showed the lowest 33P uptake and, overall, plant P acquisition was lower for all inoculation types when compared to the severe and moderate drought treatments. The total shoot P content was modulated by the water-holding capacity and inocula... Mostrar Tudo |
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Palavras-Chave: |
Arbuscular mycorrhizal fungi; Crescimento vegetal; Estresse hídrico; Falta de água; Fungos micorrízicos arbusculares; Micróbios que vivem no solo; Nutrição de fosfato; Rastreador de isótopos; Simbiose vegetal. |
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Thesagro: |
Microbiologia; Microbiologia do Solo; Milho. |
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Thesaurus NAL: |
Microbiology; Water shortages. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1154944/1/Can-arbuscular-mycorrhizal-fungi-and-rhizobacteria-facilitate-2023.pdf
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Marc: |
LEADER 03892naa a2200421 a 4500
001 2154944
005 2023-07-14
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.micres.2023.127350$2DOI
100 1 $aSILVA, A. M. M.
245 $aCan arbuscular mycorrhizal fungi and rhizobacteria facilitate P33 uptake in maize plants under water stress?$h[electronic resource]
260 $c2023
520 $aArbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are able to provide key ecosystem services, protecting plants against biotic and abiotic stresses. Here, we hypothesized that a combination of AMF (Rhizophagus clarus) and PGPR (Bacillus sp.) could enhance 33P uptake in maize plants under soil water stress. A microcosm experiment using mesh exclusion and a radiolabeled phosphorus tracer (33P) was installed using three types of inoculation: i) only AMF, ii) only PGPR, and iii) a consortium of AMF and PGPR, alongside a control treatment without inoculation. For all treatments, a gradient of three water-holding capacities (WHC) was considered i) 30% (severe drought), ii) 50% (moderate drought), and iii) 80% (optimal condition, no water stress). In severe drought conditions, AMF root colonization of dual-inoculated plants was significantly lower compared to individual inoculation of the AMF, whilst 33P uptake by dual-inoculated plants or plants inoculated with bacteria was 2.4-fold greater than the uninoculated treatment. Under moderate drought conditions the use of AMF promoted the highest 33P uptake by plants, increasing it by 2.1-fold, when compared to the uninoculated treatment. Without drought stress, AMF showed the lowest 33P uptake and, overall, plant P acquisition was lower for all inoculation types when compared to the severe and moderate drought treatments. The total shoot P content was modulated by the water-holding capacity and inoculation type, with the lowest values observed under severe drought and the highest values under moderate drought. The highest soil electrical conductivity (EC) values were found under severe drought in AMF-inoculated plants and the lowest EC for no drought in single or dual-inoculated plants. Furthermore, water-holding capacity influenced the total soil bacterial and mycorrhizal abundance over time, with the highest abundances being found under severe and moderate drought. This study demonstrates that the positive influence of microbial inoculation on 33P uptake by plants varied with soil water gradient. Furthermore, under severe stress conditions, AMF invested more in the production of hyphae, vesicles and spore production, indicating a significant carbon drain from the host plant as evidenced by the lack of translation of increased 33P uptake into biomass. Therefore, under severe drought the use of bacteria or dual-inoculation seems to be more effective than individual AMF inoculation in terms of 33P uptake by plants, while under moderate drought, the use of AMF stood out.
650 $aMicrobiology
650 $aWater shortages
650 $aMicrobiologia
650 $aMicrobiologia do Solo
650 $aMilho
653 $aArbuscular mycorrhizal fungi
653 $aCrescimento vegetal
653 $aEstresse hídrico
653 $aFalta de água
653 $aFungos micorrízicos arbusculares
653 $aMicróbios que vivem no solo
653 $aNutrição de fosfato
653 $aRastreador de isótopos
653 $aSimbiose vegetal
700 1 $aJONES, D. L.
700 1 $aCHADWICK, D. R.
700 1 $aQI, X.
700 1 $aCOTTA, S. R.
700 1 $aARAÚJO, V. L. V. P.
700 1 $aMATTEOLI, F. P.
700 1 $aLACERDA-JÚNIOR, G. V.
700 1 $aPEREIRA, A. P. A.
700 1 $aFERNANDES JUNIOR, P. I.
700 1 $aCARDOSO, E. J. B. N.
773 $tMicrobiological Research$gv. 271, 127350, 2023.
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Embrapa Semiárido (CPATSA) |
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