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OPTIMIZING CROP PROFIT ACROSS MULTIPLE GRAIN ATTRIBUTES AND STOVER

IP.com Disclosure Number: IPCOM000183536D
Publication Date: 2009-May-26
Document File: 16 page(s) / 75K

Publishing Venue

The IP.com Prior Art Database

Abstract

A Decision Support System which is more advanced than in the prior art. These advancements are broadly described as (1) prescribing fertilizer and other chemical rates based on more than a grain/forage/fiber response yield curve and optionally a single attribute response curve; (2) considering site-specific environmental conditions for a site-specific application rate; (3) considering crop genetics and past performance in various field and weather conditions; (4) considering transport logistics; and (5) determining the best use of the primary grain/forage/fiber as well as the rest of the plant.

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OPTIMIZING CROP PROFIT ACROSS MULTIPLE GRAIN ATTRIBUTES AND

STOVER

BACKGROUND OF THE INVENTION
1. Field of the Invention
[0001]
The present invention relates to agricultural processes, and, more particularly, to a method of field management.
2. Description of the Related Art
[0002]
References cited herein include the following:
(1) Freeman, Kyle et al. "By-plant Prediction of Corn Forage Biomass and Nitrogen Uptake at Various Growth Stages by Remote Sensing and Plant Height Measures".

(2) Miao, Yuxin; Mulla, David; Robert, Pierre; and Hernandez, Jose. "Within-Field Variation in Corn Yield and Grain Quality Response to Nitrogen Fertilization and Hybrid Selection". Agron J. 98:129-140 (2006).

[0003] Farmers wish to maximize the economic return from their investments for raising a crop. For grain, forage, and fiber crop producers, this has historically meant maximizing yield until the incremental cost of adding more fertilizer is greater than the incremental yield value increase (i.e., http://landresources.montana.edu/FertilizerFacts/25_Nitrogen_Requirement_and_Yield_Potentia l_of_Spring_Wheat_as_Affected_by_Water.htm ).
[0004] In the late 20th century, a number of situations were realized in which the attributes of the crop were of more importance than the gross yield as a function of inputs. These were related to the value of the attribute to the processor who paid not just on gross material, but quality. Three examples are cited below:

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Ɣ The quality of some foods is highly dependent on the protein content of wheat used in them. A key management decision is to get the right amount of nitrogen fertilizer for the available moisture to produce a quality wheat. This is nicely documented by Alberta Agriculture, Food, and Rural Development at http://www1.agric.gov.ab.ca/$department/deptdocs.nsf/all/agdex95 .

Ɣ As sugar beets increase in size, the amount of extractable sugar can decrease. For over 10 years, American Crystal Sugar of Moorhead, Mn has been instructing its growers in nitrogen management practices to maximize extractable sugar rather than maximum beet tonnage. For example, http://www.ag.ndsu.edu/pubs/plantsci/soilfert/sf714w.htm .

Ɣ Plant growth regulators such as "PIX" are used to reduce cotton plant vegetation while increasing yield and lint quality. For example, http://extension.missouri.edu/explore/agguides/crops/g04258.htm .

[0005] The general method used for the crop management described above is depicted immediately below in Fig. 1. The Decision Support System (DSS) (1) is used to generate a Chemical Rate Recommendation (2). To do this, a Yield Response Curve (3) and an Attribute Response Curve (4) are available to the DSS. These curves are similar to those in Figure 2 of the above-cited reference Miao et al., 2006. If chemical Input Costs (5) and/or Crop Prices (6) vary significantly from year to year, current or projected values may be used by the DSS. Other...