Abstract: Improved molecular breeding methods include a method in which an association data set is developed by associating the phenotypes of a broad population of individuals with the individual genotypes. The association data set is used in conjunction with a growth model in order to select breeding pairs likely to generate offspring with one or more desirable traits.

Abstract: A method of evaluating one or more kernels of an ear of maize using digital imagery that includes acquiring a digital image of the one or more kernels of the ear of maize without the use of spatial reference points, processing the digital image to estimate at least one physical property of the one or more kernels of the ear of maize from the digital image, and evaluating the at least one kernel of maize using the estimate of the at least one physical property of the at least one kernel of maize. The method includes using one or more such digital images to estimate yield on a plant, management zone, field, county and country level.

Abstract: Systems and methods that integrate breeding and agronomy by employing genotype (G) by environment (E) by management (M) practice to improve synchronized breeding for crop yield gain are provided. Methods to perform G×E×M through machine learning, simulation, crop models, quantitative models and other prediction techniques are provided.

Abstract: A method of evaluating one or more kernels of an ear of maize using digital imagery that includes acquiring a digital image of the one or more kernels of the ear of maize without the use of spatial reference points, processing the digital image to estimate at least one physical property of the one or more kernels of the ear of maize from the digital image, and evaluating the at least one kernel of maize using the estimate of the at least one physical property of the at least one kernel of maize. The method includes using one or more such digital images to estimate yield on a plant, management zone, field, county and country level.

Abstract: Methods to improve drought tolerance and increasing yield by the application limited transpiration trait in maize plants are provided. Expression of the limited transpiration trait in maize under increasing vapor pressure deficit conditions provide positive impact on overall crop yield, depending on environmental conditions.

Abstract: A method of evaluating one or more kernels of an ear of maize using digital imagery that includes acquiring a digital image of the one or more kernels of the ear of maize without the use of spatial reference points, processing the digital image to estimate at least one physical property of the one or more kernels of the ear of maize from the digital image, and evaluating the at least one kernel of maize using the estimate of the at least one physical property of the at least one kernel of maize. The method includes using one or more such digital images to estimate yield on a plant, management zone, field, county and country level.

Abstract: A method for targeting trait phenotyping of a plant breeding experiment includes collecting soil data for at least one location, applying the soil data to a crop model, performing environmental monitoring at the at least one location to generate environmental data, updating the crop model with the environmental data, and using the crop model to provide predicted crop conditions. The method further includes determining environmental conditions for each of the plant breeding experiments, determining a likelihood of trait phenotype variations for each experiment using the environmental conditions and the predicted crop conditions, selecting a subset of the plant breeding experiments for collecting trait phenotype measurements based on the likelihood of trait phenotypic variation, and collecting trait phenotype measurements from the subset of the plant breeding experiments.

Abstract: A method for targeting trait phenotyping of a plant breeding experiment includes collecting soil data for at least one location, applying the soil data to a crop model, performing environmental monitoring at the at least one location to generate environmental data, updating the crop model with the environmental data, and using the crop model to provide predicted crop conditions. The method further includes determining environmental conditions for each of the plant breeding experiments, determining a likelihood of trait phenotype variations for each experiment using the environmental conditions and the predicted crop conditions, selecting a subset of the plant breeding experiments for collecting trait phenotype measurements based on the likelihood of trait phenotypic variation, and collecting trait phenotype measurements from the subset of the plant breeding experiments.