Bayer grant share with artificial intelligence as a theme is 11% in Q3 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Methods for identifying crosses for use in plant breeding (Patent ID: US20230255155A1)
The patent filed by Bayer AG discloses methods for identifying crosses for use in plant breeding. One method involves generating population prediction scores for potential crosses and selecting a subgroup of potential crosses based on thresholds associated with the population prediction scores. From this subgroup, multiple target crosses are selected based on the genetic relatedness of the parents and the associated risk. The selected target crosses are then directed into a breeding pipeline based on the commercial success of the parents.
The method includes accessing a data structure representing multiple parents and identifying a set of potential crosses that include at least two of the parents. Population prediction scores are generated for each potential cross, which predict the commercial success of the cross. A subgroup of potential crosses is selected based on thresholds associated with the population prediction scores. Multiple target crosses are then selected from the subgroup based on the genetic relatedness of the parents and the risk associated with the crosses. The selected target crosses are directed into a breeding pipeline, taking into account the commercial success of the parents.
The patent also describes an algorithm for generating the population prediction scores, which involves calculating the probability of success for each potential cross based on certain variables. The method further includes clustering the parents of the potential crosses based on their relatedness and selecting the target crosses based on a relatedness threshold. Additionally, the selection of target crosses can be based on certain rules related to characteristics such as stalk lodging, root lodging, Goss Wilt, parental similarity, and the difference in expected relative maturity between the parents. The method also considers the risk associated with the crosses, which is determined using a quadratic algorithm dependent on risk, diversity, and performance variables.
The patent also describes a system for implementing the method, which includes a data structure representing the parents and potential crosses, a computing device for generating the population prediction scores and selecting the target crosses, and a breeding pipeline for planting the selected crosses. The computing device can be configured to cluster the parents and select the target crosses based on relatedness thresholds. The system can also incorporate user input to identify the set of potential crosses and apply additional rules for selecting the target crosses.
In summary, the patent filed by Bayer AG discloses methods and systems for identifying crosses for plant breeding based on population prediction scores, genetic relatedness, and risk assessment. The method involves selecting a subgroup of potential crosses, selecting multiple target crosses from the subgroup, and directing them into a breeding pipeline based on the commercial success of the parents. The system includes a data structure, a computing device, and a breeding pipeline to implement the method.
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