Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in<i> Brassica</i> Species

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      </button><div class="floats-full-page-caption"><div>Heatmaps of genotypic correlations for various phenomic and agronomic traits at various days after treatment (DAT) measured in control (a), drought (b), heat (c), and combined heat and drought (d) stress treatments. For trait abbreviations see Table <a href="../tab2/">2</a>.</div></div><div class="floats-full-page-content"><table class="figure-group"><tr class="fig-image"><td><object data="https://s3-eu-west-1.amazonaws.com/spj-html-parsed-preprod/articles/plantphenomics/volume-2019/3264872/figures/3264872.fig.006.svgz" name="3264872.fig.006" type="image/svg+xml"></object></td></tr></table></div></div>

Figure 6 | Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in<i> Brassica</i> Species

title

Figure 6: Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in<i> Brassica</i> Species

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Figure 6 | Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in Brassica Species

Figure 6

About this journal

<p>The open access journal <em>Plant Phenomics</em>, published in association with NAU, publishes novel research that advances plant phenotyping and connects phenomics with other research domains.</p>


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<p><em>Plant Phenomics'</em> editorial board is led by Seishi Ninomiya (University of Tokyo),&nbsp;Frédéric Baret (French National Institute of Agricultural Research), and&nbsp;Zong-Ming Cheng (Nanjing Agricultural University/University of Tennessee) and is comprised of leading experts in the field.</p>


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<p>Published Special Issues:</p>

<p><br />
<strong><a href="https://spj.sciencemag.org/plant-phenomics-special-issues/image-analysis">Image Analysis and Machine Learning for Cyber-Agricultural Systems</a></strong><br />
&nbsp;</p>

<p><strong><a href="https://spj.sciencemag.org/plant-phenomics-special-issues/statistics-bioinformatics/">Statistics, Bioinformatics, and Machine Learning Methods in Phenomics</a></strong></p>
