Real-time projections and estimated distributions of agricultural pests, diseases, and biocontrol agents
Abstract
An apparatus includes at least one processor configured to obtain multiple spatiotemporal population projection models. Different spatiotemporal population projection models are associated with different pests, diseases, or biocontrol agents. Each spatiotemporal population projection model defines how the associated pest, disease, or biocontrol agent spreads and contracts in a growing area over time. The at least one processor is also configured to receive information associated with an actual presence of a specific pest, disease, or biocontrol agent at one or more monitored spatial locations in the growing area. Different monitored spatial locations in the growing area are associated with different plants. The at least one processor is further configured to project a future presence of the specific pest, disease, or biocontrol agent in the growing area using the spatiotemporal population projection model associated with the specific pest, disease, or biocontrol agent.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . An apparatus comprising:
at least one processor configured to:
obtain multiple spatiotemporal population projection models, different spatiotemporal population projection models associated with different pests, diseases, or biocontrol agents, each spatiotemporal population projection model defining how the associated pest, disease, or biocontrol agent spreads and contracts in a growing area over time;
receive information associated with an actual presence of a specific pest, disease, or biocontrol agent at one or more monitored spatial locations in the growing area, different monitored spatial locations in the growing area associated with different plants; and
project a future presence of the specific pest, disease, or biocontrol agent in the growing area using the spatiotemporal population projection model associated with the specific pest, disease, or biocontrol agent;
wherein each spatiotemporal population projection model defines, for each monitored spatial location in the growing area, an estimated pressure of the associated pest, disease, or biocontrol agent at that spatial location based on:
a prior pressure of the associated pest, disease, or biocontrol agent at the spatial location;
a maximum limit of the associated pest, disease, or biocontrol agent at the spatial location;
a growth parameter defining how quickly the associated pest, disease, or biocontrol agent is able to grow and spread in the growing area;
a rate of overall change of all pressures of the associated pest, disease, or biocontrol agent at multiple monitored spatial locations in the growing area; and
one or more pressures of the associated pest, disease, or biocontrol agent in one or more neighboring spatial locations.
2 . The apparatus of claim 1 , wherein each spatiotemporal population projection model further defines the estimated pressure of the associated pest, disease, or biocontrol agent at each monitored spatial location in the growing area based on:
a climate in the growing area; and a treatment applied to the spatial location.
3 . The apparatus of claim 2 , wherein each spatiotemporal population projection model is commissioned by selecting one or more parameters of the spatiotemporal population projection model to minimize errors between actual measurements of the associated pest, disease, or biocontrol agent and projected measurements of the associated pest, disease, or biocontrol agent.
4 . The apparatus of claim 1 , wherein, to project the future presence of the specific pest, disease, or biocontrol agent in the growing area, the at least one processor is configured to generate an estimated distribution of the specific pest, disease, or biocontrol agent across some or all monitored spatial locations in the growing area.
5 . The apparatus of claim 4 , wherein the at least one processor is further configured to at least one of:
output the estimated distribution of the specific pest, disease, or biocontrol agent to at least one electronic device of at least one human scout; and generate at least one notification or alert based on the estimated distribution of the specific pest, disease, or biocontrol agent and at least one location of the at least one human scout.
6 . The apparatus of claim 4 , wherein the at least one processor is further configured to output the estimated distribution of the specific pest, disease, or biocontrol agent to at least one electronic device of at least one user to provide insight into whether the specific pest, disease, or biocontrol agent is increasing or decreasing in the growing area and whether to apply at least one treatment to one or more of the monitored spatial locations in the growing area.
7 . The apparatus of claim 1 , wherein the at least one processor is further configured to:
identify at least one treatment to be applied to one or more of the monitored spatial locations in the growing area; and control at least one actuator in order to initiate the at least one identified treatment.
8 . The apparatus of claim 7 , wherein the at least one processor is further configured to:
identify an effectiveness of at least one prior treatment previously applied to one or more of the monitored spatial locations in the growing area; and identify at least one additional treatment to be applied to at least one of the monitored spatial locations in the growing area based on the effectiveness of the at least one prior treatment.
9 . A non-transitory computer readable medium containing instructions that when executed cause at least one processor to:
obtain multiple spatiotemporal population projection models, different spatiotemporal population projection models associated with different pests, diseases, or biocontrol agents, each spatiotemporal population projection model defining how the associated pest, disease, or biocontrol agent spreads and contracts in a growing area over time; receive information associated with an actual presence of a specific pest, disease, or biocontrol agent at one or more monitored spatial locations in the growing area, different monitored spatial locations in the growing area associated with different plants; and project a future presence of the specific pest, disease, or biocontrol agent in the growing area using the spatiotemporal population projection model associated with the specific pest, disease, or biocontrol agent; wherein each spatiotemporal population projection model defines, for each monitored spatial location in the growing area, an estimated pressure of the associated pest, disease, or biocontrol agent at that spatial location based on:
a prior pressure of the associated pest, disease, or biocontrol agent at the spatial location;
a maximum limit of the associated pest, disease, or biocontrol agent at the spatial location;
a growth parameter defining how quickly the associated pest, disease, or biocontrol agent is able to grow and spread in the growing area;
a rate of overall change of all pressures of the associated pest, disease, or biocontrol agent at multiple monitored spatial locations in the growing area; and
one or more pressures of the associated pest, disease, or biocontrol agent in one or more neighboring spatial locations.
10 . The non-transitory computer readable medium of claim 9 , wherein each spatiotemporal population projection model further defines the estimated pressure of the associated pest, disease, or biocontrol agent at each monitored spatial location in the growing area based on:
a climate in the growing area; and a treatment applied to the spatial location.
11 . The non-transitory computer readable medium of claim 10 , wherein each spatiotemporal population projection model is commissioned by selecting one or more parameters of the spatiotemporal population projection model to minimize errors between actual measurements of the associated pest, disease, or biocontrol agent and projected measurements of the associated pest, disease, or biocontrol agent.
12 . The non-transitory computer readable medium of claim 9 , wherein the instructions that when executed cause the at least one processor to project the future presence of the specific pest, disease, or biocontrol agent in the growing area comprise:
instructions that when executed cause the at least one processor to generate an estimated distribution of the specific pest, disease, or biocontrol agent across some or all monitored spatial locations in the growing area.
13 . The non-transitory computer readable medium of claim 12 , further containing instructions that when executed cause the at least one processor to at least one of:
output the estimated distribution of the specific pest, disease, or biocontrol agent to at least one electronic device of at least one human scout; and generate at least one notification or alert based on the estimated distribution of the specific pest, disease, or biocontrol agent and at least one location of the at least one human scout.
14 . The non-transitory computer readable medium of claim 12 , further containing instructions that when executed cause the at least one processor to:
output the estimated distribution of the specific pest, disease, or biocontrol agent to at least one electronic device of at least one user to provide insight into whether the specific pest, disease, or biocontrol agent is increasing or decreasing in the growing area and whether to apply at least one treatment to one or more of the monitored spatial locations in the growing area.
15 . The non-transitory computer readable medium of claim 9 , further containing instructions that when executed cause the at least one processor to:
identify at least one treatment to be applied to one or more of the monitored spatial locations in the growing area; and control at least one actuator in order to initiate the at least one identified treatment.
16 . The non-transitory computer readable medium of claim 15 , further containing instructions that when executed cause the at least one processor to:
identify an effectiveness of at least one prior treatment previously applied to one or more of the monitored spatial locations in the growing area; and identify at least one additional treatment to be applied to at least one of the monitored spatial locations in the growing area based on the effectiveness of the at least one prior treatment.
17 . A method comprising:
obtaining multiple spatiotemporal population projection models, different spatiotemporal population projection models associated with different pests, diseases, or biocontrol agents, each spatiotemporal population projection model defining how the associated pest, disease, or biocontrol agent spreads and contracts in a growing area over time; receiving information associated with an actual presence of a specific pest, disease, or biocontrol agent at one or more monitored spatial locations in the growing area, different monitored spatial locations in the growing area associated with different plants; and projecting a future presence of the specific pest, disease, or biocontrol agent in the growing area using the spatiotemporal population projection model associated with the specific pest, disease, or biocontrol agent; wherein each spatiotemporal population projection model defines, for each monitored spatial location in the growing area, an estimated pressure of the associated pest, disease, or biocontrol agent at that spatial location based on:
a prior pressure of the associated pest, disease, or biocontrol agent at the spatial location;
a maximum limit of the associated pest, disease, or biocontrol agent at the spatial location;
a growth parameter defining how quickly the associated pest, disease, or biocontrol agent is able to grow and spread in the growing area;
a rate of overall change of all pressures of the associated pest, disease, or biocontrol agent at multiple monitored spatial locations in the growing area; and
one or more pressures of the associated pest, disease, or biocontrol agent in one or more neighboring spatial locations.
18 . The method of claim 17 , wherein each spatiotemporal population projection model further defines the estimated pressure of the associated pest, disease, or biocontrol agent at each monitored spatial location in the growing area based on:
a climate in the growing area; and a treatment applied to the spatial location.
19 . The method of claim 18 , wherein each spatiotemporal population projection model is commissioned by selecting one or more parameters of the spatiotemporal population projection model to minimize errors between actual measurements of the associated pest, disease, or biocontrol agent and projected measurements of the associated pest, disease, or biocontrol agent.
20 . The method of claim 17 , wherein projecting the future presence of the specific pest, disease, or biocontrol agent in the growing area comprises:
generating an estimated distribution of the specific pest, disease, or biocontrol agent across some or all monitored spatial locations in the growing area.
21 . The method of claim 20 , further comprising at least one of:
outputting the estimated distribution of the specific pest, disease, or biocontrol agent to at least one electronic device of at least one human scout; and generating at least one notification or alert based on the estimated distribution of the specific pest, disease, or biocontrol agent and at least one location of the at least one human scout.
22 . The method of claim 20 , further comprising:
outputting the estimated distribution of the specific pest, disease, or biocontrol agent to at least one electronic device of at least one user to provide insight into whether the specific pest, disease, or biocontrol agent is increasing or decreasing in the growing area and whether to apply at least one treatment to one or more of the monitored spatial locations in the growing area.
23 . The method of claim 17 , further comprising:
identifying at least one treatment to be applied to one or more of the monitored spatial locations in the growing area; and controlling at least one actuator in order to initiate the at least one identified treatment.
24 . The method of claim 23 , further comprising:
identifying an effectiveness of at least one prior treatment previously applied to one or more of the monitored spatial locations in the growing area; and identifying at least one additional treatment to be applied to at least one of the monitored spatial locations in the growing area based on the effectiveness of the at least one prior treatment.Join the waitlist — get patent alerts
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