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| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.15081713 |
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Table of Contents:
- <p>This dataset regards the project KIWIQUALI (Grant Agreement 101066378) which was funded by Marie Slodovska Curie (Horizon Europe). The data was collected in 2023 in a commercial orchard of <em>Actinidia chinensis </em>var <em>chinensis.</em></p> <p>The kiwifruit vines were subjected to four irrigation treatments as percentages of crop evapotranspiration (ETc).</p> <ul> <li>100% ETc (T100);</li> <li>68% ETc (T68);</li> <li>57% ETc (T57);</li> <li>40% ETc (T40).</li> </ul> <p>Four kiwifruit vines per treatment were monitored through the Tmax method regarding sap flux density (from June to October), and in nine days from July to September leaf gas exchange measurements were performed throughout the day, with at least one measurement every hour per kiwifruit vine.</p> <p>Besides the analysis of the stomatal conductance (gs) daily curves, this data was also used to obtain artificial neural network models with different input variables, from environmental data (atmospheric vapor pressure, photosynthetic photon flux and soil water content) to physiological measurements (sap flux density and leaf temperature).</p> <p>The dataset contains five folders to help organize the files regarding their subjects. The description of each folder is detailed in the following table.</p> <table> <tbody> <tr> <td>Folder name</td> <td>Description</td> </tr> <tr> <td>EnvironmentalConditions</td> <td>Files with data regarding the irrigation volumes from June to October 2023; the meteorological conditions from July to October 2023; and the soil water content from July to October 2023. </td> </tr> <tr> <td>FruitGrowthQuality</td> <td>Files with fruit dry matter content measured from August to October 2023; fruit growth monitored through fruit gauges from August to October 2023; the fruit growth measured with an automatic caliper from June to October 2023; and the fruit quality at harvest (fruit size, fruit weight, solid soluble content, firmness and acidity).</td> </tr> <tr> <td>ModelStomatalConductance</td> <td>Files in the format .h5 containing artificial neural network models obtained with different input variables.</td> </tr> <tr> <td>Physiology</td> <td>Files containing leaf gas exchange measurements performed in 9 days (from July to September 2023), throughout the day, with at least one measurement every hour; sap flux density measured with the Tmax method from June to October 2023.</td> </tr> <tr> <td>Scripts_DataAnalysis</td> <td>Files in the .R and .ipynb formats containing the scripts in R and Python languages (respectively). The R file regards the analysis of the data and the optimization of the mechanistic model of stomatal conductance (Buckley 2012). The Python file regards the training and testing the artificial neural network models regarding stomatal conductance from different input variables.</td> </tr> </tbody> </table> <p>Each folder contains its own README file (either in .txt or .ods formats) with the explanation of the data.</p> <p> </p>