Conclusion
In this proof-of-concept study, WisDM Green was experimentally validated towards the prioritization of compound combinations for sustainable farming. Compound combinations pinpointed by WisDM Green demonstrated substantial increase in %Yield, without fertilizer-driven enhancement. Further analysis on compound combinations revealed concentration-dependent interactions, which suggest that properly pairing and designing compound combinations and their respective concentration ratios are critical to achieving improved plant yield. Furthermore, continuous effort to refine and improve WisDM Green is essential before the scale-up and potential integration of the platform for farming applications.
Acknowledgements
The authors gratefully thank the Everything Green Pte Ltd and STATS Asia Pacific for helpful discussions. D. Ho gratefully acknowledges funding from the Institute for Digital Medicine (WisDM) Translational Research Programme (R-719-000-037-733) at the Yong Loo Lin School of Medicine, National University of Singapore. P. Wang and K. You contributed equally to this work.
Conflict of interest
All authors are co-inventors on a provisional patent pertaining to artificial intelligence-enabled platform that optimizes agriculture and food production yield. E.K.-H. Chow and D. Ho are co-founders and shareholders of KYAN Therapeutics, which is commercializing intellectual property pertaining to AI-based personalized medicine.
Supporting Information
[
Please don't insert supporting information here! We encourage you to include all your results and data in the main article. However, if you need to submit a
supporting information document, you can upload it to AISY's Supporting Information
collection on Authorea via
https://authorea.com/inst/21456 and insert the DOI here
.]