Systems And Methods For Use In Planting Seeds In Growing Spaces
Systems and methods are provided for use in identifying candidate seeds. An example computer-implemented method includes receiving, from a user, at a computer system, a request for a seed recommendation for a plurality of fields; identifying, by the computer system, multiple seeds and volumes for the multiple seeds to be planted in the plurality of fields, the multiple seeds included in a rank-ordered listing of ones of the multiple seeds for each of the plurality of fields; generating, by the computer system, a planting recommendation to plant the multiple seeds from the listing in the plurality of fields as a planting recommendation, based on an objective function, the objective function indicative of yield, multiple relative maturity thresholds, and one or more operational rules; and outputting, by the computer system, the planting recommendation of the seeds to the user associated with the fields, in response to the request.
1 . A computer-implemented method for use in identifying candidate seeds, the computer-implemented method comprising:
receiving, from a user, at a computer system, a request for a seed recommendation for a plurality of fields;
identifying, by the computer system, multiple seeds and volumes for the multiple seeds to be planted in the plurality of fields, the multiple seeds included in a rank-ordered listing of ones of the multiple seeds for each of the plurality of fields;
generating, by the computer system, a planting recommendation to plant the multiple seeds from the listing in the plurality of fields as a planting recommendation, based on an objective function, the objective function indicative of yield, multiple relative maturity thresholds, and one or more operational rules;
outputting, by the computer system, the planting recommendation of the seeds to the user associated with the fields, in response to the request; and
including at least one seed from the planting recommendation in one of the plurality of fields.
2 . The computer-implemented method of claim 1 , wherein the plurality of fields includes hundreds of acres.
3 . The computer-implemented method of claim 1 , further comprising clustering the plurality of fields based on distances between ones of the plurality of fields.
4 . The computer-implemented method of claim 3 , wherein the clustering is further based on size of the ones of the plurality of fields.
5 . The computer-implemented method of claim 1 , wherein the objective function includes:
max
{
-
ObjSlcPFrc
+
(
ObjYld
+
ObjGdPrdFld
-
ObjMtrRsk
1
-
ObjMtrRsk
2
-
ObjMtrRsk
3
-
Obj
Late
RmExt
-
ObjErlRmExt
-
ObjPrdCapSlc
)
-
ObjPltySlc
-
ObjPltyOprulSlc
}
.
6 . The computer-implemented method of claim 1 , wherein generating the planting recommendation is based on:
clustered groups of the plurality of fields, AERM risk median, and CRW risk at a key level of the multiple levels; and
clustered groups of the plurality of fields, the AERM risk median, the CRW risk, and the key feature at a group key level of the multiple levels; and
clustered groups of the plurality of fields, the AERM risk median, the CRW risk, the key feature, and the field identifier for the multiple fields at a field level.
7 . The computer-implemented method of claim 1 , wherein the planting recommendation includes multiple of the seeds in the one of the plurality of fields.
8 . The computer-implemented method of claim 1 , wherein including the at least one seed in the one of the plurality of fields incudes planting, by a planting device executing the planting recommendation, the at least one seed in the one of the plurality of fields.
9 . The computer-implemented method of claim 1 , further comprising comparing the planting recommendation to historical practices of the user in the plurality of fields; and
wherein outputting the planting recommendation includes outputting the planting recommendation in response to the planting recommendation being within one or more threshold(s) of the historical practices of the user.
10 . A non-transitory computer readable storage medium including executable instructions, which when executed by at least one processor, cause the at least one processor to:
receive from a user, via a field manager computing device associated with the user, a request for a seed recommendation for planting in a plurality of fields;
identify multiple seeds and volumes for the multiple seeds to be planted in the plurality of fields, the multiple seeds included in a rank-ordered listing of ones of the multiple seeds for each of the plurality of fields;
generate a planting recommendation to plant the multiple seeds from the listing in the plurality of fields as a planting recommendation, based on an objective function, the objective function indicative of yield, multiple relative maturity thresholds, and one or more operational rules;
output the planting recommendation of the seeds to the user, at the field manager computing device, in response to the request;
receive a selection of the planting recommendation from the user, via the field manager computing device; and
in response to the selection, cause at least one seed from the planting recommendation to be planted in one of the plurality of fields.
11 . The non-transitory computer readable storage medium of claim 10 , wherein the objective function includes:
max
{
-
ObjSlcPFrc
+
(
ObjYld
+
ObjGdPrdFld
-
ObjMtrRsk
1
-
ObjMtrRsk
2
-
ObjMtrRsk
3
-
Obj
Late
RmExt
-
ObjErlRmExt
-
ObjPrdCapSlc
)
-
ObjPltySlc
-
ObjPltyOprulSlc
}
.
12 . A system for use in identifying candidate seeds, the system comprising:
at least one processor; and
a memory in communication with the at least one processor, the memory storing executable instructions, which when executed by the at least one processor, cause the at least one processor to:
receive from a user, via a field manager computing device associated with the user, a request for a seed recommendation for planting in a plurality of fields;
identify multiple seeds and volumes for the multiple seeds to be planted in the plurality of fields, the multiple seeds included in a rank-ordered listing of ones of the multiple seeds for each of the plurality of fields;
generate a planting recommendation to plant the multiple seeds from the listing in the plurality of fields as a planting recommendation, based on an objective function, the objective function indicative of yield, multiple relative maturity thresholds, and one or more operational rules;
output the planting recommendation of the seeds to the user, at the field manager computing device, in response to the request;
receive a selection of the planting recommendation from the user, via the field manager computing device; and
in response to the selection, cause at least one seed from the planting recommendation to be planted in one of the plurality of fields.
13 . The system of claim 12 , wherein the plurality of fields includes hundreds of acres.
14 . The system of claim 12 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to cluster the plurality of fields based on distances between ones of the plurality of fields.
15 . The system of claim 14 , wherein the executable instructions, when executed by the at least one processor, cause the at least one processor to cluster the plurality of fields further based on a size of the ones of the plurality of fields.
16 . The system of claim 12 , wherein the objective function includes:
max
{
-
ObjSlcPFrc
+
(
ObjYld
+
ObjGdPrdFld
-
ObjMtrRsk
1
-
ObjMtrRsk
2
-
ObjMtrRsk
3
-
Obj
Late
RmExt
-
ObjErlRmExt
-
ObjPrdCapSlc
)
-
ObjPltySlc
-
ObjPltyOprulSlc
}
.
17 . The system of claim 12 , wherein the executable instructions, when executed by the at least one processor, cause the at least one processor to generate the planting recommendation further based on:
clustered groups of the plurality of fields, AERM risk median, and CRW risk at a key level of the multiple levels;
clustered groups of the plurality of fields, the AERM risk median, the CRW risk, and the key feature at a group key level of the multiple levels; and/or
clustered groups of the plurality of fields, the AERM risk median, the CRW risk, the key feature, and the field identifier for the multiple fields at a field level.
18 . The system of claim 12 , wherein the planting recommendation includes multiple of the seeds in the one of the plurality of fields.
19 . The system of claim 12 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to compare the planting recommendation to historical practices of the user in the plurality of fields; and
wherein the executable instructions, when executed by the at least one processor, cause the at least one processor to output the planting recommendation in response to the planting recommendation being within one or more threshold(s) of the historical practices of the user.
20 . The system of claim 12 , wherein the executable instructions, when executed by the at least one processor, cause the at least one processor to transmit the planting recommendation to a cab computer of a planting device in response to the selection of the planting recommendation from the user; and
wherein the system further comprises executable planting device instructions, which when executed by the cab computer of the planting device in response to the planting recommendation, cause the planting device to plant the at least one seed in the one of the plurality of fields.