Monsanto Technology LLC

The Climate Corporation

Bruce J Schnicker

Kevin Lee Deppermann

Sam R Eathington

Heather M Forbes

Jason Kendrick Bull

Michael W Petersen

David V Butruille

John Tamulonis

Stanton B Dotson

Allen N Ondes

David W Finley

Brian J Forinash

Andrew M Singleton

Lee Yannakakis

Angela Ranae Koestel

Xiao Yang

Tonya S Ehlmann

Timothy Reich

Yao Xie

Angela R Cargill

Matthew Sorge

Morrison Jacobs

Allan Trapp

William M Fischer

John M Jensen

Herbert Ssegane

Shilpa Sood

Nikisha Shah

Susan Andrea Macisaac

Kevin Cook

Travis J Frey

Terri B Hinchey

Robert G Getschman

Jeremy Nefzger

Mike Bohnert

Jeremy Conry

Jeff Hartsook

Qiang Zhang

Heather Forbes

Jeremy Neizger

Brian J Forninash

A method is provided for use in analyzing seeds, in a population of seeds, for one or more desired characteristic. The method includes removing tissue from individual seeds in a population of seeds using an automated seed sampler, while preserving germination viability of the seeds, and analyzing the tissue for the presence or absence of one or more desired characteristic. The method then includes, based on the analysis of the tissue, quantifying the one or more desired characteristic for each of the individual seeds that possess the one or more desired characteristic.

Methods of seed breeding using high throughput nondestructive seed sampling

Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.

Using machine learning-based seed harvest moisture predictions to improve a computer-assisted agricultural farm operation

Techniques are provided for generating a set of target hybrid seeds with optimal yield and risk performance, including a server receiving a candidate set of hybrid seeds along with probability of successful yield values, associated historical agricultural data and property information, and selecting a subset of the hybrid seeds that have probability of success values greater than a filtering threshold. The server generates representative yield values for hybrid seeds based on the historical agricultural data and risk values for each hybrid seed. The server generates a dataset of target hybrid seeds for planting based on the risk values, the yield values, and the properties for the target fields. The dataset of target hybrid seeds includes target hybrid seeds that meet a specific threshold for a range of risk values. The server causes display of the dataset of target hybrid seeds including yield values and risk values for the target fields.

Hybrid seed selection and seed portfolio optimization by field

An automated method for operating an automated seed sampling system having a seed loading station, a seed transport subsystem, and a seed sampling station generally includes sensing whether individual seeds are successfully isolated from a bulk of seeds at the seed loading station, and sensing whether the isolated seeds are properly positioned by the seed transport subsystem adjacent the seed sampling station in preparation for removing tissue from the isolated seeds. In some aspects, the method further includes analyzing the tissue removed from the seeds for presence or absence of at least one characteristic, and selecting seeds based on presence or absence of the at least one characteristic.

Automated high-throughput seed sampler and methods of sampling, testing and bulking seeds

A method is provided for use in a plant breeding program to generate a population having one or more desired traits. The method includes removing a tissue sample from each of one or more seeds using an automated seed sampler while preserving germination viability of the sampled seeds; analyzing the tissue samples for the presence or absence of a genetic sequence associated with at least one desired trait; based on the analysis of the tissue samples, cultivating plants from the sampled seeds that either possess or lack the genetic sequence associated with the at least one desired trait; creating a parental cross using at least one of the cultivated plants; and selecting seeds from the parental cross and cultivating offspring of the parental cross using the selected seeds.

A seed sampling system is provided having an automated seed loading assembly including a seed bin and being operable to singulate seeds from a plurality of seeds within the seed bin. The system also includes an automated seed sampling assembly operable to remove tissue samples from the singulated seeds, and an automated seed transport assembly operable to transfer the singulated seeds from the seed loading assembly to the seed sampling assembly. The seed transport assembly includes multiple retention members. Each of the retention members is movable relative to the seed loading assembly and to the seed sampling assembly. The seed transport assembly is operable to position one of the multiple retention members adjacent to the seed loading assembly for engaging one of the singulated seeds, while positioning another of the retention members adjacent to the seed sampling assembly for presenting another of the singulated seeds to the seed sampling assembly.

Automated systems for removing tissue samples from seeds, and related methods

An automated method for analyzing seeds generally includes collecting image data from individual seeds using a seed sampling system, determining at least one characteristic of each of the individual seeds based on the collected image data, and removing tissue from each of the individual seeds using the seed sampling system. The method also includes, prior to removing the tissue sample from each of the individual seeds, adjusting at least one operational parameter of the seed sampling system based on the at least one characteristic of the seed from which the tissue is to be removed to thereby allow for generally consistent removal of tissue from each of the individual seeds. In some aspects, the method further includes analyzing the tissue removed from the seeds for presence or absence of at least one characteristic, and selecting seeds based on presence or absence of the at least one characteristic.

Novel methods are provided to facilitate germplasm improvement activities through the use of high throughput, nondestructive sampling of seeds. A method for introgressive hybridization, for example, generally includes removing tissue samples from individual seeds using an automated seed sampler without affecting germination viability of the seeds, and analyzing nucleic acids extracted from the tissue samples for at least one genetic marker. The method then further includes selecting the sampled seeds that possess the at least one genetic marker, cultivating fertile plants from the selected seeds, and crossing the fertile plants with other plants.

The present invention provides for novel methods to facilitate germplasm improvement activities through the use of high throughput, nondestructive sampling of seeds. A method of evaluating seeds for a desired trait, for example, for facilitating germplasm improvement activities, etc., generally includes removing tissue samples from individual seeds using an automated seed sampler without affecting germination viability of the seeds, analyzing the tissue samples for one or more characteristics indicative of a desired trait, and selecting the sampled seeds that include the desired trait.

An automated system for sampling seeds includes a seed loading station for separating individual seeds from a plurality of seeds held in a seed hopper, an imaging station configured to receive the separated seeds from the seed loading station and collect image data of the received seeds, and a seed sampling subsystem configured to remove tissue samples from the seeds after the image data of the seeds is collected. And, an automated method for sampling seeds includes separating individual seeds from a plurality of seeds, imaging the separated seeds, and removing tissue samples from the imaged seeds.

The present invention provides for novel methods to facilitate germplasm improvement activities through the use of high throughput, nondestructive sampling of seeds. A method for analyzing a population of haploid seeds generally includes providing a population of seeds comprising haploid seeds, removing tissue samples from a plurality of the seeds in the population using an automated seed sampler system while preserving the germination viability of the sampled seeds, and analyzing the tissue samples for the presence or absence of one or more characteristics indicative of at least one genetic or chemical trait.

Growing community of inventors

Wildwood, MO, United States of America

Bruce J Schnicker