Patents by Inventor Ponsi Trivisvavet

Ponsi Trivisvavet has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12243112
    Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
    Type: Grant
    Filed: August 25, 2023
    Date of Patent: March 4, 2025
    Assignee: Indigo Ag, Inc.
    Inventors: David Patrick Perry, Geoffrey Albert von Maltzahn, Robert Berendes, Eric Michael Jeck, Barry Loyd Knight, Rachel Ariel Raymond, Ponsi Trivisvavet, Justin Y H Wong, Neal Hitesh Rajdev, Marc-Cedric Joseph Meunier, Casey James Leist, Pranav Ram Tadi, Andrea Lee Flaherty, Charles David Brummitt, Naveen Neil Sinha, Jordan Lambert, Jonathan Hennek, Carlos Becco, Mark Allen, Daniel Bachner, Fernando Derossi, Ewan Lamont, Rob Lowenthal, Dan Creagh, Steve Abramson, Ben Allen, Jyoti Shankar, Chris Moscardini, Jeremy Crane, David Weisman, Gerard Keating, Lauren Moores, William Pate
  • Publication number: 20250064009
    Abstract: A method for producing grain with improved feed traits is presented, whereby the feed trait is introduced directly into the grain through pollen applied from a donor source produced separate from the farmer's field, applied to the farmers field at the proper time, thereby eliminating multiple steps of trait introgression currently in practice for such grain production.
    Type: Application
    Filed: December 29, 2022
    Publication date: February 27, 2025
    Inventors: Ponsi Trivisvavet, Claudia M. Nari, Ronald E. Wulfkuhle
  • Publication number: 20250057096
    Abstract: A method for producing grain with improved fuel traits is presented, whereby the fuel trait is introduced directly into the grain through pollen applied from a donor source produced separate from the farmer's field, applied to the farmers field at the proper time, thereby eliminating multiple steps of trait introgression currently in practice for such grain production.
    Type: Application
    Filed: December 29, 2022
    Publication date: February 20, 2025
    Inventors: Ponsi Trivisvavet, Claudia M. Nari, Ronald E. Wulfkuhle
  • Publication number: 20250048987
    Abstract: Transgenic INOT1824 maize plants comprising an amy797E expression cassette linked to a secondary nopaline synthase terminator element which lack a promoter and a coding region but retain the terminator of a selectable marker gene and/or which comprise modifications such as cognate guide RNA recognition sites that provide for facile excision of the INOT1824 transgenic locus from the maize plant genome are provided. Genomic DNA of INOT1824 transgenic plants, detection of INOT1824 plants and products thereof, methods of making INOT1824 plants, and use of INOT1824 plants to facilitate breeding are disclosed.
    Type: Application
    Filed: December 29, 2022
    Publication date: February 13, 2025
    Inventors: Michael Andreas Kock, Joshua L. Price, Michael Lee Nuccio, Ponsi Trivisvavet, Claudia M. Nari, Ronald E. Wulfkuhle
  • Publication number: 20240127367
    Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
    Type: Application
    Filed: August 25, 2023
    Publication date: April 18, 2024
    Inventors: David Patrick Perry, Geoffrey Albert von Maltzahn, Robert Berendes, Eric Michael Jeck, Barry Loyd Knight, Rachel Ariel Raymond, Ponsi Trivisvavet, Justin Y H Wong, Neal Hitesh Rajdev, Marc-Cedric Joseph Meunier, Casey James Leist, Pranav Ram Tadi, Andrea Lee Flaherty, Charles David Brummitt, Naveen Neil Sinha, Jordan Lambert, Jonathan Hennek, Carlos Becco, Mark Allen, Daniel Bachner, Fernando Derossi, Ewan Lamont, Rob Lowenthal, Dan Creagh, Steve Abramson, Ben Allen, Jyoti Shankar, Chris Moscardini, Jeremy Crane, David Weisman, Gerard Keating, Lauren Moores, William Pate
  • Patent number: 11776071
    Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
    Type: Grant
    Filed: March 11, 2021
    Date of Patent: October 3, 2023
    Assignee: INDIGO AG, INC.
    Inventors: David Patrick Perry, Geoffrey Albert von Maltzahn, Robert Berendes, Eric Michael Jeck, Barry Loyd Knight, Rachel Ariel Raymond, Ponsi Trivisvavet, Justin Y H Wong, Neal Hitesh Rajdev, Marc-Cedric Joseph Meunier, Casey James Leist, Pranav Ram Tadi, Andrea Lee Flaherty, Charles David Brummitt, Naveen Neil Sinha, Jordan Lambert, Jonathan Hennek, Carlos Becco, Mark Allen, Daniel Bachner, Fernando Derossi, Ewan Lamont, Rob Lowenthal, Dan Creagh, Steve Abramson, Ben Allen, Jyoti Shankar, Chris Moscardini, Jeremy Crane, David Weisman, Gerard Keating, Lauren Moores, William Pate
  • Patent number: 11263707
    Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
    Type: Grant
    Filed: August 7, 2018
    Date of Patent: March 1, 2022
    Assignee: INDIGO AG, INC.
    Inventors: David Patrick Perry, Geoffrey Albert von Maltzahn, Robert Berendes, Eric Michael Jeck, Barry Loyd Knight, Rachel Ariel Raymond, Ponsi Trivisvavet, Justin Y H Wong, Neal Hitesh Rajdev, Marc-Cedric Joseph Meunier, Casey James Leist, Pranav Ram Tadi, Andrea Lee Flaherty, Charles David Brummitt, Naveen Neil Sinha, Jordan Lambert, Jonathan Hennek, Carlos Becco, Mark Allen, Daniel Bachner, Fernando Derossi, Ewan Lamont, Rob Lowenthal, Dan Creagh, Steve Abramson, Ben Allen, Jyoti Shankar, Chris Moscardini, Jeremy Crane, David Weisman, Gerard Keating, Lauren Moores, William Pate
  • Publication number: 20210224927
    Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
    Type: Application
    Filed: March 11, 2021
    Publication date: July 22, 2021
    Inventors: David Patrick Perry, Geoffrey Albert von Maltzahn, Robert Berendes, Eric Michael Jeck, Barry Loyd Knight, Rachel Ariel Raymond, Ponsi Trivisvavet, Justin Y. H. Wong, Neal Hitesh Rajdev, Marc-Cedric Joseph Meunier, Casey James Leist, Pranav Ram Tadi, Andrea Lee Flaherty, Charles David Brummitt, Naveen Neil Sinha, Jordan Lambert, Jonathan Hennek, Carlos Becco, Mark Allen, Daniel Bachner, Fernando Derossi, Ewan Lamont, Rob Lowenthal, Dan Creagh, Steve Abramson, Ben Allen, Jyoti Shankar, Chris Moscardini, Jeremy Crane, David Weisman, Gerard Keating, Lauren Moores, William Pate
  • Publication number: 20190050948
    Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
    Type: Application
    Filed: August 7, 2018
    Publication date: February 14, 2019
    Inventors: David Patrick Perry, Geoffrey Albert von Maltzahn, Robert Berendes, Eric Michael Jeck, Barry Loyd Knight, Rachel Ariel Raymond, Ponsi Trivisvavet, Justin Y H Wong, Neal Hitesh Rajdev, Marc-Cedric Joseph Meunier, Charles Vincent Michell, JR., Casey James Leist, Pranav Ram Tadi, Andrea Lee Flaherty, Charles David Brummitt, Naveen Neil Sinha, Jordan Lambert, Jonathan Hennek, Carlos Becco, Mark Allen, Daniel Bachner, Fernando Derossi, Ewan Lamont, Rob Lowenthal, Dan Creagh, Steve Abramson, Ben Allen, Jyoti Shankar, Chris Moscardini, Jeremy Crane, David Weisman, Gerard Keating, Lauren Moores, William Pate