## 5 Conclusions  
In terms of inputs required and computational efficiency, the application of intermediate complexity models of crop C and N dynamics under the constraints of observations is favorable when upscaling the models from local to regional extents. This study has demonstrated that an intermediate complexity model, DALEC-Crop, can produce reliable estimates of leaf N content and yields using growing season data on climate and LAI across a range of N application rates for multiple winter wheat seasons. Further validation of the DALEC-Crop modelling framework using experimental data from additional wheat sites and seasons is a critical next step for testing application.  
The CARDAMOM MDF system was able to extract valuable information from LAI data that improved estimates of crop N status and yield. Spatial and temporal variation in yield is driven by climate, soil and management variations, and our testing showed that combining a process model with time-series of weather and LAI data could diagnose their combined effects to explain yield variation robustly. The growing availability of high resolution (10 m) and frequent Earth observations of LAI (sub-weekly depending on cloud conditions) means that, when used in conjunction with our approach, there is a potential to map wheat N status and forecast yields during the growing season. We showed that CARDAMOM could generate reliable estimates of crop yield even during early growth stages when N fertilizer is typically applied, providing clear-sky observations are available during this period. Our analysis demonstrates a scalable proof-of-concept MDF approach for the timely prediction of yield responses to N management.  
**Supplementary Materials:** The following are available online at [[https://www.mdpi.com/2073-4](https://www.mdpi.com/2073-4)]([https://www.mdpi.com/2073-4](https://www.mdpi.com/2073-4)) 395/11/2/314/s1, Table S1: The DALEC-Crop and Aggregated Canopy Model (ACM) parameters, Figure S1: Probability density function of parameters for DALEC-Crop from calibrating on a treatment-by-treatment basis, Figure S2: Probability density function of the retrieved parameters for DALEC-Crop from an aggregated model calibration, Figure S3: Experiment 2: Yield estimated from experiments involving the multi-year DALEC-Crop calibration to determine the influence of model inputs between the two seasons.  
**Author Contributions:** Conceptualization, A.R. and M.W.; methodology, A.R., V.M., A.F. and M.W.; validation, A.R.; formal analysis, A.R.; investigation, A.R.; resources, A.R., M.W. and S.H.; data curation, A.R. and A.F.; writing--original draft preparation, A.R. and M.W.; writing--review and editing, A.R., V.M., S.H., R.R. and M.W.; project administration, A.M. and M.W.; funding acquisition, A.M. and M.W. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the joint Biotechnology and Biological Sciences Research Council (BBSRC) and National Environment Research Council (NERC) Sustainable Agricultural Research and Innovation Club (SARIC) initiative (grant numbers: BB/P004628/1 and BB/P004458/1), NERC grant NE/P018920/1, the Royal Society and NCEO.  
Data Availability Statement: Datasets supporting reported results can be found within the ATEC (Advanced Technologies for Efficient Crop management) collection on Edinburgh DataShare publicly available depository (datashare.is.ed.ac.uk/handle/10283/3697).  
We acknowledge the technical support from [PERSON] at Scotland's Rural College (SRUC).  
The authors declare no conflict of interest.