## 5 Conclusions  
Overall, this study showed that the uncertainty in the relationship between satellite measurements and crop state variables caused by site and growth stage specific factors is significant and that this uncertainty leads to significant difficulties in using remotely sensed data to retrieve the genotype x environment x management (G x E x M) factors affecting crop growth. Specifically, we performed an extensive temporal analysis and retrieved the temporal change in the state variables to show the amount of uncertainty caused by this secondary factor variability. We also conducted a joint sensitivity analysis of the remote sensing regression parameters and crop model genotype x management (G x M) parameters to illustrate the ill-posedness of retrieving G x E x M factors from satellite measurements. This analysis demonstrated the criticalness of reducing the uncertainty in the relationship between satellite measurements and crop state variables to make the retrieval more feasible. The study shows the need for further data collection and model development that can ultimately lead to methods that will minimize the secondary uncertainty caused by site and growth stage specific factors. In addition, further work needs to be conducted to address the application of the methods to use training data in regions where biotic stresses are poorly controlled and where, unlike the case in highly developed commercial agriculture systems [7], crop growth models show significant uncertainties in predicting actual yields (as opposed to potential yields) due to suboptimal management [112]. This research is critical to achieving the goal of mapping G x E x M factors on a global scale, which can improve our ability to make predictions about the global agricultural system [113]. **Author Contributions:** Conceptualization, N.L., Y.K., P.C., F.M., and B.G. ; Methodology, N.L. and B.G. ; Software, N.L. ; Validation, N.L. ; Formal analysis, N.L. ; Investigation, N.L., Y.K., M.O., and V.M. ; Resources, Y.K., M.O., and V.M. ; Data curation, N.L., Y.K., M.O., and V.M. ; Writing--original draft preparation, N.L. ; Writing--review and editing, N.L., Y.K., M.O., V.M., P.C., F.M., and B.G. ; Visualization, N.L. ; Supervision, F.M. and B.G. ; Project administration, F.M. and B.G. **Funding:** This work was supported by NASA Headquarters under the NASA Earth and Space Science Fellowship Program--Grant 80 NSSC17K0339. We would also like to acknowledge partial support by NOAA under the grant CREST agreement #NA16 SEC4810008. In addition, data used in this study was funded by a variety of sources. Observations collected at the US Southern Great Plains site (US-ARM) were supported by the Office of Biological and Ecological Research of the US Department of Energy under contract no. DE-AC02-05 ch11231 as part of the Atmospheric Radiation Measurement (ARM) Program. Observations at DE-Kli were funded by EU project CARBOEUROPE-IP, by German BMBF project ICOS-D and by the state of Savony (TU Dresden, LFLUG). Data acquisition at FR-Lam are mainly funded by the Institutional National des Sciences de l'Univers (INSU) through the ICOS and OSR SW observatories. Facilities and staff at FR-Lam are funded and supported by the Observatory Midi-Pyrenex, the University Paul Sabatier of Toulouse, CNRS (Centre National de la Recherche Scientifique), CNES (Centre National d'Etude Spatial), and IRD (Institut de Recherche pour le Developpement). Facilities and staff at FR-Gri were funded and supported by INRA, AgroParisTech, European projects NitroEurope-IP (EU-), ECLAIRE-FP7 (EU-), INGOS-FP7, Accent, and ESF-NinE, French National Research Agency (ANR) projects Vulnoz, CNRS, Ile de France region R2 DS, CNRS-INSU, Fr-De Photona, Programme LabEx BASC, ANR-11-LABX-0034. **Acknowledgments:** We are grateful to all of the investigators and personnel who collected and provided the ground truth data used in this study.