Replication Data for: Effective Use of Water and Increased Dry Matter Partitioned to Grain Contribute to Yield of Common Bean Improved for Drought Resistancehttps://doi.org/10.7910/DVN/1XOLXYPolanía, JoséPoschenrieder, CharlotteRao, Idupulapati MBeebe, StephenHarvard Dataverse2016-12-202019-07-08T16:46:33ZTraits related with drought resistance in common beans. A set of 36 bean genotypes belonging to the Middle American gene pool were evaluated under field conditions with two levels of water supply (irrigated and drought) over two seasons. Eight bean lines (NCB 280, NCB 226, SEN 56, SCR 2, SCR 16, SMC 141, RCB 593 and BFS 67) were identified as resistant to drought stress. Resistance to terminal drought stress was positively associated with EUW combined with increased dry matter partitioned to pod and seed production and negatively associated with days to flowering and days to physiological maturity. Based on phenotypic differences in CID, leaf stomatal conductance, canopy biomass and grain yield under drought stress, the lines tested were classified into two groups, water savers and water spenders.Earth and Environmental SciencesCanopy biomassGrain carbon isotope discriminationLeaf carbon isotope discriminationPod harvest indexDrought stressWater use efficiencyLatin America and the CaribbeanAgrobiodiversity - AGBIOCommon Bean OntologyEffective Use of Water and Increased Dry Matter Partitioned to Grain Contribute to Yield of Common Bean Improved for Drought Resistance, doi, 10.3389/fpls.2016.00660, http://dx.doi.org/10.3389/fpls.2016.006602016-12-20Garcia, Carolina2016-12-092012-06-012014-05-30Experimental DataPhenomic DataCIAT-HQValle del CaucaColombiaPalmira<P><a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.</P> <Strong>Disclaimer</Strong> <P> Whilst utmost care has been taken by CIAT and data authors while collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, CIAT, or relevant funding agencies be liable for any actual, incidental or consequential damages arising from use of the data. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study. </P>