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WisDM Green: Harnessing Artificial Intelligence to Design and Prioritize Compound Combinations in Peat Moss for Sustainable Farming Applications
  • +6
  • Peter Wang,
  • Kui You,
  • Yoon Hun Ong,
  • Joe Ning Yeoh,
  • Jerica Ong,
  • Anh Thanh Lan Truong,
  • Agata Blasiak,
  • Edward Kai-Hua Chow,
  • Dean Ho
Peter Wang
National University of Singapore

Corresponding Author:[email protected]

Author Profile
Kui You
National University of Singapore
Yoon Hun Ong
National University of Singapore
Joe Ning Yeoh
National University of Singapore
Jerica Ong
National University of Singapore
Anh Thanh Lan Truong
National University of Singapore
Agata Blasiak
National University of Singapore
Edward Kai-Hua Chow
National University of Singapore
Dean Ho
National University of Singapore


The substantial increase in global population and climate change, among other factors have led to global food security and supply chain challenges. The United Nations has laid out an agenda to sustainably achieve zero hunger by 2030 as one of its sustainable development goals. However, sustainably achieving improved food yield has become a challenge as excessive use of fertilizers has also led to adverse environmental impact. To address the aforementioned challenges, WisDM Green, an artificial intelligence (AI)-based platform that aims to pinpoint and prioritize compound (e.g. biostimulants) combinations in peat moss, is harnessed to sustainably improve the yield of Amaranthus cruentus (red spinach). In this proof-of-concept study, from a pool of 8 compounds, WisDM Green-pinpointed combinations (6-Benzylaminopurine/Ethylenediaminetetraacetic Acid Iron (III) and Humic Acid/Seaweed Extract) achieve 26.34±15.80 and 33.59±14.60 increase in %Yield, respectively. The study also indicates that compound combinations may exhibit concentration-dependent synergies and thus, properly adjusting the concentration ratios of combinations may further improve plant yield in the context of sustainable farming.
P. Wang and K. You contributed to this work equally.
Corresponding author(s) Email:   [email protected], [email protected], [email protected] 
13 May 2022Submitted to AISY Interactive Papers
13 May 2022Published in AISY Interactive Papers
27 May 2022Published in Advanced Intelligent Systems on pages 2200095. 10.1002/aisy.202200095