Welcome To Website IAS

Hot news
Achievement

Independence Award

- First Rank - Second Rank - Third Rank

Labour Award

- First Rank - Second Rank -Third Rank

National Award

 - Study on food stuff for animal(2005)

 - Study on rice breeding for export and domestic consumption(2005)

VIFOTEC Award

- Hybrid Maize by Single Cross V2002 (2003)

- Tomato Grafting to Manage Ralstonia Disease(2005)

- Cassava variety KM140(2010)

Centres
Website links
Vietnamese calendar
Library
Visitors summary
 Curently online :  52
 Total visitors :  7667208

Machine Learning Reveals Important Genes to Help Corn Grow with Less Fertilizer
Wednesday, 2021/10/06 | 07:10:01

A study conducted by researchers at New York University (NYU) together with their colleagues from National Taiwan University, Purdue University, and the University of Illinois has found genes, through machine learning, that help crops grow with less fertilizer and predict additional traits in plants and disease outcomes in animals.

 

In the Nature Communications paper, it was indicated that the research team used machine learning, a type of artificial intelligence used to detect patterns in data. As a proof-of-concept, the researchers showed that genes whose responsiveness to nitrogen is evolutionarily conserved between two diverse plant species—Arabidopsis, and varieties of corn—significantly improved the ability of machine learning models to predict genes of importance for how efficiently plants use nitrogen, a crucial nutrient for plants and the main component of fertilizer. Crops that use nitrogen more efficiently grow better and require less fertilizer, which has economic and environmental benefits.

 

Experiments validated eight master transcription factors as genes of importance to nitrogen use efficiency. They showed that altered gene expression in Arabidopsis or corn could increase plant growth in low nitrogen soils, which they tested both in the lab at NYU and in cornfields at the University of Illinois. The researchers showed that machine learning can be applied to other traits and species by predicting additional traits in plants, including biomass and yield in both Arabidopsis and corn. They also showed that this approach can predict genes of importance to drought resistance in rice, as well as disease outcomes in animals.

 

For more details, read the news releases from New York University and the University of Illinois.

Back      Print      View: 151

[ Other News ]___________________________________________________
  • Egypt Holds Workshop on New Biotech Applications
  • UN Agencies Urge Transformation of Food Systems
  • Taiwan strongly supports management of brown planthopper—a major threat to rice production
  • IRRI Director General enjoins ASEAN states to invest in science for global food security
  • Rabies: Educate, vaccinate and eliminate
  • “As a wife I will help, manage, and love”: The value of qualitative research in understanding land tenure and gender in Ghana
  • CIP Director General Wells Reflects on CIP’s 45th Anniversary
  • Setting the record straight on oil palm and peat in SE Asia
  • Why insect pests love monocultures, and how plant diversity could change that
  • Researchers Modify Yeast to Show How Plants Respond to Auxin
  • GM Maize MIR162 Harvested in Large Scale Field Trial in Vinh Phuc, Vietnam
  • Conference Tackles Legal Obligations and Compensation on Biosafety Regulations in Vietnam
  • Iloilo Stakeholders Informed about New Biosafety Regulations in PH
  • Global wheat and rice harvests poised to set new record
  • GM Maize Harvested in Vietnam Field Trial Sites
  • New label for mountain products puts premium on biological and cultural diversity
  • The Nobel Prize in Physiology or Medicine 2016
  • Shalabh Dixit: The link between rice genes and rice farmers
  • People need affordable food, but prices must provide decent livelihoods for small-scale family farmers
  • GM Seeds Market Growth to Increase through 2020 Due to Rise in Biofuels Use

 

Designed & Powered by WEBSO CO.,LTD