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| 141. |  | MONTEIRO, R. A. C.; BEHLING, M.; TONINI, H.; LULU, J.; COLETTI, A. J.; SHIRATSUCHI, L. S. Integração entre a Lavoura, a Pecuária e a Floresta: ciência e arte. In: SIMPÓSIO BRASILEIRODE AGROPECUÁRIA SUSTENTÁVEL., 8.; INTERNATIONAL CONFERENCE ON SUSTAINABLE AGRICULTURE, 5., 2016. Sinop. Ciência, tecnologia e inovação para o desenvolvimento sustentável das novas fronteiras agrícolas: anais. Sinop: [SIMBRAS], 2016. 123-140. SIMBRAS. 18 p.| Biblioteca(s): Embrapa Agrossilvipastoril. |
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| 156. | | DIAS, T. C.; TONINI, H.; DEMICHELI, M.; VOLPATO, M.; PILOCELLI, A. Fatores que influenciam na sobrevivência de mudas de eucalipto em sistemas agroflorestais In: JORNADA CIENTÍFICA DA EMBRAPA AGROSSILVIPASTORIL, 2.,2013, Sinop. Anais... Sinop, MT: Embrapa Agrossilvipastoril, 2013. 1 CD.| Biblioteca(s): Embrapa Agrossilvipastoril. |
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Registro Completo
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Biblioteca(s): |
Embrapa Agrossilvipastoril; Embrapa Milho e Sorgo. |
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Data corrente: |
28/11/2017 |
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Data da última atualização: |
09/03/2018 |
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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: |
BALDONI, A. B.; TONINI, H.; TARDIN, F. D.; BOTELHO, S. C. C.; TEODORO, P. E. |
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Afiliação: |
AISY BOTEGA BALDONI TARDIN, CPAMT; HELIO TONINI, CPPSUL; FLAVIO DESSAUNE TARDIN, CNPMS; SILVIA DE CARVALHO CAMPOS BOTELHO, CPAMT; Universidade Federal de Viçosa. |
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Título: |
Minimum number of measurements for evaluating Bertholletia excelsa. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Genetics and Molecular Research, Ribeirão Preto, v. 16, n. 3, p. 1-10, 2017. |
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DOI: |
10.4238/gmr16039783 |
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Idioma: |
Inglês |
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Notas: |
Artigo - gmr16039783. |
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Conteúdo: |
Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r,which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%. MenosRepeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r,which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the... Mostrar Tudo |
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Palavras-Chave: |
Dry mass of seeds; Massa seca de semente; Number of fruits; Repetibilidade. |
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Thesagro: |
Bertholletia Excelsa; Castanha do Pará. |
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Thesaurus NAL: |
Brazil nuts; Repeatability. |
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Categoria do assunto: |
--
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/167647/1/Minimum-number.pdf
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Marc: |
LEADER 02429naa a2200289 a 4500
001 2080879
005 2018-03-09
008 2017 bl uuuu u00u1 u #d
024 7 $a10.4238/gmr16039783$2DOI
100 1 $aBALDONI, A. B.
245 $aMinimum number of measurements for evaluating Bertholletia excelsa.$h[electronic resource]
260 $c2017
500 $aArtigo - gmr16039783.
520 $aRepeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r,which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%.
650 $aBrazil nuts
650 $aRepeatability
650 $aBertholletia Excelsa
650 $aCastanha do Pará
653 $aDry mass of seeds
653 $aMassa seca de semente
653 $aNumber of fruits
653 $aRepetibilidade
700 1 $aTONINI, H.
700 1 $aTARDIN, F. D.
700 1 $aBOTELHO, S. C. C.
700 1 $aTEODORO, P. E.
773 $tGenetics and Molecular Research, Ribeirão Preto$gv. 16, n. 3, p. 1-10, 2017.
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Embrapa Milho e Sorgo (CNPMS) |
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