SYSTEMS AND METHODS FOR USE IN PLANTING SEEDS IN GROWING SPACES

1 . A computer-implemented method for use in identifying a set of candidate seeds for a target field based on a prediction model, the method comprising:

accessing, by a computing device, data from a data server, the data including data representative of seeds harvested from at least one of a research growing space, a development growing space, and a field growing space;

generating a yield delta prediction model, based on at least a portion of the accessed data;

for each of a plurality of candidate seeds, automatically generating a probability of a yield delta for the candidate seed, relative to a target seed, exceeding a performance threshold, based on the generated model;

identifying, by the computing device, a set of the candidate seeds, based on the probability of the respective candidate seed satisfying a defined threshold;

outputting, by the computing device, the identified set of candidate seeds to a user; and

including at least one seed from the identified set of candidate seeds in a target field.

2 . The computer-implemented method of claim 1 , further comprising:

receiving a request including the target seed and a target field from the user; and

filtering, by the computing device, the accessed data based on a region including the target field, wherein the region includes one of: a relative maturity band and a region of interest.

3 . The computer-implemented method of claim 1 , wherein the data includes data representative of seeds harvested from the research growing space, the development growing space, and the field growing space; and

wherein the data representative of seeds harvested from the field growing space includes split planting data indicative of: at least two candidate seeds or one candidate seed and the target seed.

4 . The computer-implemented method of claim 1 , wherein generating the yield delta prediction model includes generating the model based on a Bayesian framework; and/or

wherein generating the model includes generating a plurality of samples for a training data set and a model expression.

5 . The computer-implemented method of claim 1 , wherein the plurality of candidate seeds includes a first candidate seed and a second candidate seed;

wherein generating the yield delta prediction model is based, at least in part, on:

d ij 1 j 2 =z j 1 −z j 2 +σ i ε ij 1 j 2 ; and

wherein d i is the yield delta, z j 1 is the first candidate seed, z j 2 is the second candidate seed, and σ i ε i is a noise expression.

6 . The computer-implemented method of claim 1 , wherein generating the model includes generating a plurality of samples for a training data set and a model expression; and

wherein the probability of a yield delta for the candidate seed relative to a target seed exceeding a performance threshold is based on a distribution of the predicted yield deltas for the candidate seed and the target seed included in the samples.

7 . The computer-implemented method of claim 6 , wherein the performance threshold is between about 1.0 bushels/acre and about 10.0 bushels/acre; and/or

wherein the defined threshold is between about 50% and about 100%; and/or

wherein the samples of the training data set include more than one thousand samples.

8 . The computer-implemented method of claim 1 , further comprising selecting one or more seed from the identified set of candidate seeds; and

wherein including at least one seed from the identified set of candidate seeds in the target field includes planting the target seed and the selected one or more seed in a field, in a split planting configuration.

9 . A non-transitory computer-readable storage medium including executable instructions, which, when executed by at least one processor in connection with identifying a set of candidate seeds for a target field based on a prediction model, cause the at least one processor to perform the following steps:

accessing data from a data server, the data including data representative of seeds harvested from at least one of a research growing space, a development growing space, and a field growing space;

generating a yield delta prediction model, based on at least a portion of the accessed data;

for each of a plurality of candidate seeds, generating a probability of a yield delta for the candidate seed, relative to a target seed, exceeding a performance threshold, based on the generated model;

identifying a set of the candidate seeds, based on the probability of the respective candidate seed satisfying a defined threshold;

outputting the identified set of seeds to a user;

generating planting instructions for an agricultural planting apparatus, based on the identified set of candidate seeds, to plant at least one seed from the identified set of candidate seeds in a target field; and

transmitting the planting instructions to the agricultural planting apparatus, whereby the agricultural planting apparatus operates, in response to the planting instructions, to plant the at least one seed in the target field.

10 . A system for use in identifying a set of candidate seeds for a target field based on a prediction model, the system comprising:

at least one data server including data representative of seeds harvested from at least one of a research growing space, a development growing space, and a field growing space; and

at least one computing device in communication with the at least one data server, the at least one computing device configured to:

generate a yield delta prediction model based on at least a portion of the data in the at least one data server;

for each of a plurality of candidate seeds, automatically generate a probability of a yield delta for the candidate seed, relative to a target seed, exceeding a performance threshold, based on the generated model;

identify a set of the candidate seeds based on the probability of the respective candidate seed satisfying a defined threshold;

output the identified set of seeds to a user; and

generate planting instructions for an agricultural planting apparatus, based on the identified set of candidate seeds, to plant at least one seed from the identified set of candidate seeds in a target field, whereby the agricultural planting apparatus operates to plant the at least one seed in the target field in response to the planting instructions.

11 . The system of claim 10 , wherein the at least one computing device is further configured to:

receive a request including the target seed and a target field from the user; and

filter the accessed data based on a region including the target field, wherein the region includes one of: a relative maturity band and a region of interest.

12 . The system of claim 11 , wherein the at least one computing device is configured, in order to generate the yield delta prediction model, to generate the yield delta prediction model based on a Bayesian framework.

13 . The system of claim 12 , wherein the at least one computing device is configured, in order to generate the yield delta prediction model, to generate a plurality of samples for a training data set and a model expression.

14 . The system of claim 13 , wherein the probability of the yield delta for the candidate seed, relative to the target seed, for each of the plurality of candidate seeds, exceeding the performance threshold is further based on a distribution of the predicted yield deltas for the candidate seed and the target seed included in the samples.

15 . The system of claim 14 , wherein the performance threshold is between about 1.0 bushels/acre and about 10.0 bushels/acre;

wherein the defined threshold is between about 50% and about 100%; and

wherein the samples of the training data set include more than one thousand samples.

16 . The system of claim 10 , wherein the plurality of candidate seeds includes a first candidate seed and a second candidate seed;

wherein the at least one computing device is configured, in order to generate the yield delta prediction model, to generate the yield delta prediction model based, at least in part, on:

d ij 1 j 2 =z j 1 −z j 2 +σ i ε ij 1 j 2 and

wherein d i is the yield delta, z j 1 is the first candidate seed, z j 2 is the second candidate seed, and σ i ε i is a noise expression.

17 . The system of claim 10 , wherein the data includes data representative of seeds harvested from the research growing space, the development growing space, and the field growing space; and

wherein the data representative of seeds harvested from the field growing space includes split planting data indicative of: at least two candidate seeds or one candidate seed and the target seed.

18 . The system of claim 10 , further comprising the target field in which the at least one seed from the identified set of candidate seeds output to the user is planted, in a split planting configuration.