IP Library Granted Patent US 11,592,431
Granted Patent B2
US 11,592,431 · App. 17/724,912 · Granted Feb 28, 2023

Addressing incomplete soil sample data in soil enrichment protocol projects

Inventors: Brian Segal (Boston, MA); Charles David Brummitt (Boston, MA)
Assignee: Indigo Ag, Inc.
G01N33/24
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,592,431
App. No.
17/724,912
Granted
Feb 28, 2023
Kind
B2
Abstract

In various embodiments, methods, systems, and computer program products are provided for estimating greenhouse gas emissions. In particular, methods, systems, and computer program products are presented for the task of quantifying emissions reduction from changes in stocks of soil organic carbon (SOC). The methods apply more generally to tasks that involve quantification of a total or average across a population of land (and/or possibly any space and any time) using measurements at a sample from that population. The sample may not be representative or unbiased. In some examples, estimating greenhouse gas emissions may apply to quantifying the total stock of SOC in land, the total nitrous oxide emissions in land and a time interval.

Claims (63)

1. A method for estimating greenhouse gas emissions, the method comprising:

receiving a plurality of soil sample locations within a land area, soil attributes for at least some of the plurality of soil sample locations, and regional soil data of the land area;

estimating soil organic carbon (SOC) emissions reduction of the land area;

determining a plurality of pre-strata based on the plurality of soil sample locations and the regional soil data, wherein each pre-stratum of the plurality of pre-strata comprises a plurality of soil sample points across the land area;

for each pre-stratum of the plurality of pre-strata:

determining a potential for bias in an estimate of emissions reduction for the pre-stratum;

comparing the potential for bias with a predetermined threshold; and

when the potential for bias is above the predetermined threshold, determining a plurality of post-strata based on the pre-stratum, wherein the plurality of post-strata are disjoint subsets of the pre-stratum; and

determining a total estimated emissions reduction of the land area based on the plurality of post-strata and the estimated SOC emissions reduction of the land area.

2. The method of claim 1 , wherein determining the potential for bias comprises:

determining a first average value of an attribute among observed sample locations;

determining a second average value of the attribute among all locations where samples were planned to be taken;

determining a pooled standard deviation based on variation associated with the attribute; and

labelling the pre-strata as likely including bias when the difference between the first and second average values, divided by the pooled standard deviation, is above a predetermined threshold.

3. The method of claim 1 , wherein estimating SOC emissions reduction comprises generating a plurality of simulations of SOC emissions reduction based on soil attributes of the land area.

4. The method of claim 3 , wherein the plurality of simulations comprises Monte Carlo simulations.

5. The method of claim 1 , wherein the soil attributes include % SOC, soil texture, pH, and bulk density.

6. The method of claim 1 , wherein the regional soil data comprises land management practices.

7. The method of claim 1 , wherein the regional soil data comprises soil characteristics.

8. The method of claim 1 , further comprising combining at least two of the plurality of pre-strata.

9. The method of claim 1 , wherein determining the plurality of pre-strata comprises applying a zone attribute table and a point attribute table.

10. The method of claim 1 , wherein determining the post-stratum further comprises:

partitioning the land area into a plurality of fields, each field comprising one or more soil sample locations of the plurality of soil sample locations; and

binning the plurality of fields into a plurality of bins based on at least one variable.

11. The method of claim 10 , wherein determining the post-stratum further comprises applying one or more rules to the binned plurality of fields.

12. The method of claim 10 , wherein the at least one variable comprises land management practices.

13. The method of claim 10 , wherein the at least one variable comprises soil texture.

14. The method of claim 10 , wherein the at least one variable comprises crop type.

15. The method of claim 10 , wherein binning comprises applying clustering to the plurality of fields.

16. The method of claim 15 , wherein clustering comprises k-means clustering.

17. The method of claim 10 , wherein at least one of the plurality of fields includes at least one observed soil measurement at the one or more soil sample locations.

18. The method of claim 17 , wherein at least one of the plurality of fields includes at least one missing soil measurements at the one or more soil sample locations.

19. The method of claim 18 , wherein determining the total estimated emissions reduction comprises:

for each post-stratum:

determining a mean emissions reduction based on the at least one observed soil measurement in the plurality of fields within the post-stratum;

determining a total emissions reduction based on the mean emission reduction and a total area of the post-stratum; and

determining a variance of the total emissions reduction.

20. The method of claim 19 , wherein determining the total estimated emissions reduction further comprises:

summing each total emissions reduction; and

summing each variance.

21. The method of claim 1 , further comprising determining a potential for bias for each post-stratum in the plurality of post-strata.

22. A system comprising:

a soil attribute database;

a soil sample location database;

a regional soil data database;

a computing node comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor of the computing node to cause the processor to perform a method comprising:

receiving a plurality of soil sample locations within a land area from the soil sample location database, soil attributes for at least some of the plurality of soil sample locations from the soil attribute database, and regional soil data of the land area from the regional soil data database;

estimating soil organic carbon (SOC) emissions reduction of the land area;

determining a plurality of pre-strata based on the plurality of soil sample locations and the regional soil data, wherein each pre-stratum of the plurality of pre-strata comprises a plurality of soil sample points across the land area;

for each pre-stratum of the plurality of pre-strata:

determining a potential for bias in an estimate of emissions reduction for the pre-stratum;

comparing the potential for bias with a predetermined threshold; and

when the potential for bias is above the predetermined threshold, determining a plurality of post-strata based on the pre-stratum, wherein the plurality of post-strata are disjoint subsets of the pre-stratum; and

determining a total estimated emissions reduction of the land area based on the plurality of post-strata and the estimated SOC emissions reduction of the land area.

23. A computer program product for estimating greenhouse gas emissions comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:

receiving a plurality of soil sample locations within a land area, soil attributes for at least some of the plurality of soil sample locations, and regional soil data of the land area;

estimating soil organic carbon (SOC) emissions reduction of the land area;

determining a plurality of pre-strata based on the plurality of soil sample locations and the regional soil data, wherein each pre-stratum of the plurality of pre-strata comprises a plurality of soil sample points across the land area;

for each pre-stratum of the plurality of pre-strata:

determining a potential for bias in an estimate of emissions reduction for the pre-stratum;

comparing the potential for bias with a predetermined threshold; and

when the potential for bias is above the predetermined threshold, determining a plurality of post-strata based on the pre-stratum, wherein the plurality of post-strata are disjoint subsets of the pre-stratum; and

determining a total estimated emissions reduction of the land area based on the plurality of post-strata and the estimated SOC emissions reduction of the land area.

Assignments (6)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 15, 2026
From: INDIGO AG, LLC
To: INDIGO AGRICULTURE, INC.
Reel/Frame 075279/0881 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 15, 2026
From: INDIGO AGRICULTURE, INC.
To: TERION AI, INC.
Reel/Frame 075280/0039 →
RELEASE OF SECURITY INTEREST Recorded Oct 25, 2023
From: CORTLAND CAPITAL MARKET SERVICES LLC
To: INDIGO AG, INC.; INDIGO AGRICULTURE, INC.
Reel/Frame 065344/0780 →
SECURITY INTEREST Recorded Aug 10, 2023
From: INDIGO AGRICULTURE, INC.; INDIGO AG, INC.
To: CORTLAND CAPITAL MARKET SERVICES LLC, AS AGENT
Reel/Frame 064559/0438 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE NAME INVENTOR TO INDIGO AG, INC. PREVIOUSLY RECORDED AT REEL: 060131 FRAME: 0665. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Oct 11, 2022
From: SEGAL, BRIAN; BRUMMITT, CHARLES DAVID
To: INDIGO AG, INC.
Reel/Frame 061641/0245 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 8, 2022
From: SEGAL, BRIAN; BRUMMITT, CHARLES DAVID
To: INDIGO AG, INC. (TRUDI BAKER)
Reel/Frame 060131/0665 →
Continuity (5)
Provisional Application 63319629 · Mar 14, 2022
Provisional Application 63306284 · Feb 3, 2022
Provisional Application 63238541 · Aug 30, 2021
Provisional Application 63177376 · Apr 20, 2021
Related Publication 20220365061A1 · Nov 17, 2022