Machine learning in agricultural planting, growing, and harvesting contexts

A system comprising:

• a processor;
• and
• a non-transitory computer-readable storage medium storing executable instructions that, when executed by the processor, cause the processor to perform steps comprising:
• identifying a cluster of portions of land associated with a threshold similarity;
• selecting a portion of land from the cluster of portions of land, the selected portion of land associated with crop growth information describing 1) characteristics of the selected portion of land, 2) a first set of farming operations to be performed, and 3) a first expected carbon sequestration corresponding to the first set of farming operations;
• applying a prediction model trained on historical crop growth information from a plurality of geographically diverse locations to inputs comprising the characteristics of the selected portion of land, the first set of farming operations to be performed, and the first expected carbon sequestration corresponding to the first set of farming operations, wherein the prediction model optimizes a second expected carbon sequestration by producing an output comprising a second set of farming operations that can produce the optimized second expected carbon sequestration;
• and
• for the selected portion of land, 1) modifying the first set of farming operations to be performed based on the identified second set of farming operations, and 2) modifying a user interface displayed by a client device of the user to display a crop growth program based on the modified first set of farming operations.

A non-transitory computer-readable storage medium storing executable instructions that, when executed by a processor, cause the processor to perform steps comprising:

• identifying a cluster of portions of land associated with a threshold similarity;
• selecting a portion of land from the cluster of portions of land, the selected portion of land associated with crop growth information describing 1) characteristics of the selected portion of land, 2) a first set of farming operations to be performed, and 3) a first expected carbon sequestration corresponding to the first set of farming operations;
• applying a prediction model trained on historical crop growth information from a plurality of geographically diverse locations to inputs comprising the characteristics of the selected portion of land, the first set of farming operations to be performed, and the first expected carbon sequestration corresponding to the first set of farming operations, wherein the prediction model optimizes a second expected carbon sequestration by producing an output comprising a second set of farming operations that can produce the optimized second expected carbon sequestration;
• and
• for the selected portion of land, 1) modifying the first set of farming operations to be performed based on the identified second set of farming operations, and 2) modifying a user interface displayed by a client device of the user to display a crop growth program based on the modified first set of farming operations.