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).
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Patent number: 12243112Abstract: 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: GrantFiled: August 25, 2023Date of Patent: March 4, 2025Assignee: 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
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Publication number: 20250064009Abstract: 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: ApplicationFiled: December 29, 2022Publication date: February 27, 2025Inventors: Ponsi Trivisvavet, Claudia M. Nari, Ronald E. Wulfkuhle
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Publication number: 20250057096Abstract: 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: ApplicationFiled: December 29, 2022Publication date: February 20, 2025Inventors: Ponsi Trivisvavet, Claudia M. Nari, Ronald E. Wulfkuhle
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Publication number: 20250048987Abstract: 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: ApplicationFiled: December 29, 2022Publication date: February 13, 2025Inventors: Michael Andreas Kock, Joshua L. Price, Michael Lee Nuccio, Ponsi Trivisvavet, Claudia M. Nari, Ronald E. Wulfkuhle
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Publication number: 20240127367Abstract: 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: ApplicationFiled: August 25, 2023Publication date: April 18, 2024Inventors: 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
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Patent number: 11776071Abstract: 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: GrantFiled: March 11, 2021Date of Patent: October 3, 2023Assignee: 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
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Patent number: 11263707Abstract: 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: GrantFiled: August 7, 2018Date of Patent: March 1, 2022Assignee: 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
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Publication number: 20210224927Abstract: 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: ApplicationFiled: March 11, 2021Publication date: July 22, 2021Inventors: 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
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Publication number: 20190050948Abstract: 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: ApplicationFiled: August 7, 2018Publication date: February 14, 2019Inventors: 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