SYSTEMS AND METHODS FOR PREDICTING REGIONAL TURFGRASS PERFORMANCE
First Claim
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;
identify, from the stored data, a common set of grass attributes and corresponding grass attribute rankings in a plurality of geographic regions for the plurality of individual grass seed varieties selected; and
display the common set of historical grass attribute rankings for the selected individual grass seed varieties in the plurality of geographic regions in which the grass seeds were grown as a prediction of performance of the individual grass seed varieties.
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Accused Products
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.
6 Citations
14 Claims
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1. A computer-implemented method for predicting performance of grass seed varieties, the method comprising:
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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; identify, from the stored data, a common set of grass attributes and corresponding grass attribute rankings in a plurality of geographic regions for the plurality of individual grass seed varieties selected; and display the common set of historical grass attribute rankings for the selected individual grass seed varieties in the plurality of geographic regions in which the grass seeds were grown as a prediction of performance of the individual grass seed varieties. - View Dependent Claims (2, 3, 4)
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5. A computer-implemented method for predicting performance of grass seed varieties, the method comprising:
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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; identify a common set of grass attributes and corresponding grass attribute rankings for a plurality of individual grass seed varieties using the received selections; and display the identified common set of historical grass attributes and corresponding grass attribute rankings for the plurality of individual grass seed varieties as a prediction of performance of the individual grass seed varieties within at least one geographic region of interest. - View Dependent Claims (6, 7, 8, 9, 10)
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11. A computer-implemented method for predicting performance of individual seed varieties across geographic regions, the method comprising:
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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; identify a common grass attribute and corresponding historical grass attribute values for the at least two individual grass seed varieties in the selected geographic region of interest; and display the identified common set of historical grass attributes and corresponding grass attribute values for the individual grass seed varieties 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. - View Dependent Claims (12, 13, 14)
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Specification