## 4 Conclusions  
NIRS represents a rapid and cost-effective analytical tool when the predictive models are accurate enough. The models for nitrogen, protein, starch, fiber, and total minerals quality constituents of taro and sweet potato showed good prediction accuracy. The TC-tuber in sweet potato and CaOx-shoot in taro, the \(\delta^{15}\)N in the underground organs and the \(\delta^{13}\)C in the vegetative parts of both crops showed the poorest prediction performances. However, these last constituent predictions could be used as an informative tool in germplasm screening. The present models could be applied in further research on crop quality subjected to water scarcity conditions. Additional work is needed to improve the existing models with new data from new drought trials. The development of more robust NIRS models for all constituents will improve their efficiency and reliability for assessing crop quality and phenotyping plants subjected to water scarcity.  
**Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2076-3417/10/23/8724/s1](http://www.mdpi.com/2076-3417/10/23/8724/s1)]([http://www.mdpi.com/2076-3417/10/23/8724/s1](http://www.mdpi.com/2076-3417/10/23/8724/s1)), Table S1: Taro quality constituents of the flour obtained by laboratory reference analysis (1 st trial) and NIRS prediction (2 nd trial) for both corms and shoots submitted to control and drought conditions, Table S2: Pearson correlations of taro corms and shoots, from the 1 st agronomic trial, Table S3: Sweet potato quality constituents of the flour obtained by laboratory reference analysis (1 st trial) and NIRS prediction (2 nd trial) for both tuber and shoot organs, under control and drought conditions, Table S4: Pearson correlations of sweet potato tubers and shoots, from the 1 st agronomic trial, Table S5: Pearson correlations of taro corms and shoots, from the 2 nd agronomic trial, Table S6: Pearson correlations of sweet potato tubers and shoots, from the 2 nd agronomic trial.  
**Author Contributions:** Conceptualization, V.L. and M.P.d.C.; methodology, C.S.S.G.; investigation, C.S.S.G.; data curation, C.S.S.G.; writing--original draft preparation, C.S.S.G.; writing--review and editing, V.L., M.P.d.C. and C.S.S.G.; software, C.S.S.G.; supervision, V.L. and M.P.d.C.; funding acquisition, C.S.S.G. and M.P.d.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Programa Operacional Madeira 14-20, Portugal 2020 and the European Union through the European Regional Development Fund, grant number M1420-01-0145-FEDER-000011, [CASBio] and [PERSON] was funded by ARDITI--Agencia Regional para o Desenvolvimento da Investigacao Tecnologia e Inovacao, Portugal 2020 and the European Union through the European Social Fund, grant number M1420-09-5369-FSE-00001.  
**Acknowledgments:** The authors would like to thank [PERSON], [PERSON], and [PERSON] (ISOPlexis Genebank, Madeira University, Portugal), for providing valuable assistance with the drought assay design, the management of the field trials and meaningfully contributed to the harvest and samples preparation. The authors are grateful to [PERSON] (InnoTech Alberta, Canada) for coordinating the isotopic compositions. The authors also acknowledge the support by National Funds FCT--Portuguese Foundation for Science and Technology, under the projects UIDB/04033/2020 and UIDP/04033/2020.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.