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Refinado por: Nome da Publicação: Crop Science remover
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1
Classification of plant growth‐promoting bacteria inoculation status and prediction of growth‐related traits in tropical maize using hyperspectral image and genomic data
Classification of plant growth‐promoting bacteria inoculation status and prediction of growth‐related traits in tropical maize using hyperspectral image and genomic data
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Classification of plant growth‐promoting bacteria inoculation status and prediction of growth‐related traits in tropical maize using hyperspectral image and genomic data

Rafael Massahiro Yassue Giovanni Galli; Roberto Fritsche‐Neto; Gota Morota

Crop Science Oxford p. 1-13, August 2022

Oxford 2022

Item não circula. Consulte sua biblioteca.(Acessar)

2
Genomic Prediction of Autogamous and Allogamous Plants by SNPs and Haplotypes
Genomic Prediction of Autogamous and Allogamous Plants by SNPs and Haplotypes
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Genomic Prediction of Autogamous and Allogamous Plants by SNPs and Haplotypes

Filipe Inacio Matias Giovanni Galli; Italo Stefanine Correia Granato; Roberto Fritsche-Neto

Crop Science Madison v .57, n. 6, p. 2951-2958, 2017

Madison 2017

Item não circula. Consulte sua biblioteca.(Acessar)

3
Genomic prediction enables early but low-intensity selection in soybean segregating progenies
Genomic prediction enables early but low-intensity selection in soybean segregating progenies
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Genomic prediction enables early but low-intensity selection in soybean segregating progenies

Leandro de Freitas Mendonça Giovanni Galli; G Malone; Roberto Fritsche-Neto

Crop Science Oxford online, p. 1-16, 2020

Oxford 2020

Item não circula. Consulte sua biblioteca.(Acessar)

4
Improving the identification of haploid maize seeds using convolutional neural networks
Improving the identification of haploid maize seeds using convolutional neural networks
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Improving the identification of haploid maize seeds using convolutional neural networks

Felipe Sabadin Giovanni Galli; Ronaldo Borsato; Raysa Gevartosky; Gabriela Romêro Campos; Roberto Fritsche-Neto

Crop Science Oxford p. 1-11, 2021

Oxford 2021

Item não circula. Consulte sua biblioteca.(Acessar)

5
Impact of phenotypic correction method and missing phenotypic data on genomic prediction of maize hybrids
Impact of phenotypic correction method and missing phenotypic data on genomic prediction of maize hybrids
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Impact of phenotypic correction method and missing phenotypic data on genomic prediction of maize hybrids

Giovanni Galli Danilo Hottis Lyra; Filipe Couto Alves; Ítalo Stefanine Correia Granato; Massaine Bandeira e Sousa; Roberto Fritsche-Neto

Crop Science Madison v. 58, n. 4, p. 1481-1491, 2018

Madison 2018

Item não circula. Consulte sua biblioteca.(Acessar)

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Deste Autor:

  1. Galli, G
  2. Fritsche-Neto, R
  3. Yassue, R
  4. Matias, F
  5. Granato, Í

Neste Assunto:

  1. Genômica
  2. Milho
  3. Melhoramento Genético Vegetal
  4. Hibridação Vegetal
  5. Plantas Cultivadas

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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