Systems and methods for predicting regional turfgrass performance

• US 10,332,220 B2
• Filed: 06/16/2015
• Issued: 06/25/2019
• Est. Priority Date: 10/05/2012
• Status: Active Grant

• Current Assignee: Heritage Landscape Supply Group, Inc. (SRS Group Holdings, Inc.)
• Original Assignee: Land O'Lakes Incorporated
• Inventors: Jump, Bruce A.
• Primary Examiner(s): Le, Toan M
• Assistant Examiner(s): Sun, Xiuquin
• Application Number:
  US14/740,846
• Publication Number:
  US 20150278967A1
• Time in Patent Office: 1,470 Days
• Field of Search: 702180
• CPC Class Codes: A01G 20/00 Cultivation of turf, lawn or the like; Apparatus or methods therefor hand-held edge trimmers or shears for lawn A01G3/06; edging for lawn A01G9/28; lawn-mowers A01D34/00
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06Q 50/02 Agriculture; Fishing; Forestry; Mining

Abstract

Grass seed performance may be predicted by receiving grass seed selections for individual grass seed varieties and target geographic regions for growing the grass seed selection. A common set of grass attributes is identified from historical grass attribute values associated with the selected target regions. The historical grass attribute values in the first common set of grass attributes are retrieved and are displayed in a graphical format for the at least two individual grass seed varieties in the at least two selected target regions. A weighted average may be calculated for the historical grass attribute values in the common set and may provide a prediction of performance of the individual grass seed varieties across the selected geographic regions or in regions proximate the selected geographic regions.

Claims

1. A computer-implemented method for predicting performance of grass seed varieties, the method comprising:

using a computer database to store a set of historical grass performance data for each of a plurality of individual grass seed varieties, the sets of historical grass performance data each comprising at least an identity of the individual grass seed variety, a geographic region in which the grass seed variety was grown, a historical growing year, grass attributes and grass attribute rankings, wherein a number of grass attributes or the grass attribute rankings differ among the sets; and

using a computer processor to;

receive a selection of a plurality of individual grass seed varieties;

display a visual interface that includes graphical representation of a common set of grass attributes and corresponding grass attribute rankings in a plurality of geographic regions in which the grass seeds were grown as identified from the stored data for the selection of the plurality of individual grass seed varieties as a prediction of performance of the individual grass seed varieties, wherein the graphical representation includes arranging the common set of historical grass attributes for the selected individual grass seed varieties by the geographical regions in which the seeds were grown;

calculate a weighted average and a statistical benchmark for each historical grass attribute rankings for the selected individual grass seed varieties in each of the geographic regions, wherein the statistical benchmark includes a least significant differences value;

overlay, on the graphical representation included on the visual interface, a first visual indicator of the weighted average of each of the common set of historical grass attributes for the selected individual grass seed varieties;

overlay, on the graphical representation included on the visual interface, a second visual indicator associated with each calculated statistical benchmark in combination with the display of the common set of historical grass attribute rankings for the selected individual grass seed varieties; and

overlay, on the graphical representation included on the visual interface, a third visual indication provided by each graphical representation of the calculated statistical benchmark as to whether or not differences between the corresponding historical grass attribute rankings are statistically significant to supplement the prediction of performance of the individual grass seed varieties.

2. The method of claim 1, wherein the plurality of selections comprise selections of a plurality of individual grass seed varieties by historical growing year, and wherein the processor is used to identify the common set of historical grass attributes for the historical growing year.

3. The method of claim 1, wherein the grass attributes stored using the computer database comprise National Turfgrass Evaluation Program (NTEP) grass attributes.

4. The method of claim 1, further comprising using the computer processor to:

receive a themed selection, the themed selection representing a group of grass attributes having commonalities; and

identify the common set of grass attributes from the themed selection.

5. A computer-implemented method for predicting performance of grass seed varieties, the method comprising:

using a computer database to store a set of historical grass performance data for each of a plurality of individual grass seed varieties, the sets of historical grass performance data each comprising at least an identity of the individual grass seed variety, a geographic region in which the grass seed variety was grown, a historical growing year, grass attributes and grass attribute rankings, wherein a number of grass attributes or the grass attribute rankings differ among the sets; and

using a computer processor to;

receive a plurality of selections from the group consisting of;

individual grass seed variety, geographic region, historical growing year, or grass attribute;

display a visual interface that includes graphical representation of a common set of grass attributes and corresponding grass attribute rankings for a plurality of individual grass seed varieties identified using the received plurality of selections as a prediction of performance of the individual grass seed varieties within at least two geographic regions of interest, wherein the graphical representation includes arranging the common set of historical grass attributes and corresponding grass attribute rankings for the plurality of individual grass seed varieties by the at least two geographical regions of interest;

overlay, on the graphical representation included on the visual interface, a weighted average of grass attribute rankings for each historical grass attribute, calculated across the at least two geographic regions of interest;

receive a subsequent selection of a different at least two geographic regions of interest; and

update the overlay of weighted averages on the graphical representation included on the visual interface such that the weighted averages of grass attribute rankings for each historical grass attribute are calculated across the different at least two geographic regions of interest.

6. The method of claim 5, wherein the identified common set of grass attributes and corresponding grass attribute rankings are for at least two individual grass seed varieties grown in at least two geographic regions.

7. The method of claim 6, wherein the at least two geographic regions are proximate one of the at least one geographic region of interest.

8. The method of claim 5, wherein the plurality of selections comprise selections of a plurality of grass seed varieties by historical growing year, and wherein the processor is used to identify the common set of historical grass attributes for the historical growing year.

9. The method of claim 5, wherein the grass attributes stored using the computer database comprise National Turfgrass Evaluation Program (NTEP) grass attributes.

10. The method of claim 5, further comprising using the computer processor to:

receive a themed selection, the themed selection representing a group of grass attributes having commonalities; and

identify the common set of grass attributes from the themed selection.

11. A computer-implemented method for predicting performance of individual seed varieties across geographic regions, the method comprising:

using a computer database to store a set of historical grass performance data for each of a plurality of individual grass seed varieties, the sets of historical grass performance data each comprising at least an identity of the individual grass seed variety, a geographic region in which the grass seed variety was grown, a historical growing year, grass attributes and grass attribute values, wherein a number of grass attributes or the grass attribute values differ among the sets; and

using a computer processor to;

receive a selection of at least two individual grass seed varieties and a geographic region of interest;

display a visual interface that includes graphical representation of a common grass attribute and corresponding historical grass attribute values identified for the at least two individual grass seed varieties in the selected geographic region of interest as a prediction of performance of the individual grass seed varieties within the geographic region of interest, wherein the grass attribute values comprise one or more of numerical values, grades or rankings, wherein the graphical representation includes arranging the common set of historical grass attributes and corresponding grass attribute values for the individual grass seed varieties by each individual attribute of the common set of historical grass attributes;

overlay, on the graphical representation included on the visual interface, a first visual indicator a weighted average for each historical grass attribute rankings for the selected individual grass seed varieties in the geographic region of interest;

overlay, on the graphical representation included on the visual interface and in combination with the display of the common set of historical grass attribute values for the selected individual grass seed varieties, a second visual indicator associated with a statistical benchmark for each historical grass attribute based on the corresponding grass attribute values for the individual grass seed varieties for the selected individual grass seed varieties in the geographic region of interest, wherein the statistical benchmark includes a least significant differences value; and

overlay a third visual indicator on the graphical representation included on the visual interface that indicates whether or not differences between the corresponding historical grass attribute values are statistically significant to supplement the prediction of performance of the individual grass seed varieties.

12. The method of claim 11, wherein the selections further comprise selections by historical growing year, and wherein the processor is used to identify the common set of historical grass attributes for the historical growing year.

13. The method of claim 11, wherein the grass attributes stored using the computer database comprise National Turfgrass Evaluation Program (NTEP) grass attributes.

14. The method of claim 11, further comprising using the computer processor to:

receive a themed selection, the themed selection representing a group of grass attributes having commonalities; and

identify the common set of grass attributes from the themed selection.