Abstract: A method can include receiving a first image depicting a first dog and identifying, with a first model, a first breed for the first dog based on the first image. The method may further include determining, with a second model, a first body condition for the first dog based on the first image; generating, with a third model, a second image depicting the first dog with a second body condition different from the first body condition. The method may also include labeling the first image with indications of the breed and the first body condition, labeling the second image with indications of the breed and the second body condition, and training the second model using the first and second images.

Abstract: Systems and methods are disclosed herein for providing germplasm crop scenarios. The system may calculate a relative maturity (RM) for a germplasm for an area of a location. The system may use weather information associated with a selected area to calculate the relative maturity. The system may then calculate a predictive yield for the germplasm for the area based on the respective relative maturity for the germplasm. The system may then generate the germplasm information for the germplasm indicative of a respective performance for the area of the location based on the respective predictive yield. For example, a plurality of crop scenarios may be generated by date for acorn hybrid seed that provides a more accurate yield calculation based on what date the crop is planted.