WisDM Green: Harnessing Artificial Intelligence to Design and Prioritize Compound Combinations in Peat Moss for Sustainable Farming Applications. (27th May 2022)
- Record Type:
- Journal Article
- Title:
- WisDM Green: Harnessing Artificial Intelligence to Design and Prioritize Compound Combinations in Peat Moss for Sustainable Farming Applications. (27th May 2022)
- Main Title:
- WisDM Green: Harnessing Artificial Intelligence to Design and Prioritize Compound Combinations in Peat Moss for Sustainable Farming Applications
- Authors:
- Wang, Peter
You, Kui
Ong, Yoong Hun
Yeoh, Joe Ning
Ong, Jerica Pang Qi
Truong, Anh Thanh Lan
Blasiak, Agata
Chow, Edward Kai-Hua
Ho, Dean - Abstract:
- Abstract : 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 eight compounds, WisDM Green‐pinpointed combinations (6‐benzylaminopurine/ethylenediaminetetraacetic acid iron (III) (6‐BAP/EDTA‐Fe) and humic acid/seaweed extract (HA/SWE)) achieved 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. An interactive preprint version of the article can be found at: https://www.authorea.com/doi/full/10.22541/au.165244695.56681780 . Abstract : WisDM Green, an artificial intelligence‐based platform, is harnessed to design and prioritizeAbstract : 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 eight compounds, WisDM Green‐pinpointed combinations (6‐benzylaminopurine/ethylenediaminetetraacetic acid iron (III) (6‐BAP/EDTA‐Fe) and humic acid/seaweed extract (HA/SWE)) achieved 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. An interactive preprint version of the article can be found at: https://www.authorea.com/doi/full/10.22541/au.165244695.56681780 . Abstract : WisDM Green, an artificial intelligence‐based platform, is harnessed to design and prioritize compound combinations to sustainably increase the yield of Amaranthus cruentus (red spinach). This workflow enables the prioritization of WisDM Green‐pinpointed combinations, such as humic acid (HA) in combination with seaweed extract (SWE), and these combinations were able to achieve a 15% – 35% increase in the biological yield of red spinach. … (more)
- Is Part Of:
- Advanced intelligent systems. Volume 4:Number 10(2022)
- Journal:
- Advanced intelligent systems
- Issue:
- Volume 4:Number 10(2022)
- Issue Display:
- Volume 4, Issue 10 (2022)
- Year:
- 2022
- Volume:
- 4
- Issue:
- 10
- Issue Sort Value:
- 2022-0004-0010-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-05-27
- Subjects:
- agritech -- artificial intelligence -- food security -- optimization -- sustainability
Artificial intelligence -- Periodicals
Robotics -- Periodicals
Control theory -- Periodicals
006.3 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
https://onlinelibrary.wiley.com/journal/26404567 ↗ - DOI:
- 10.1002/aisy.202200095 ↗
- Languages:
- English
- ISSNs:
- 2640-4567
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24148.xml