Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or...
Reexamination Certificate
1998-10-15
2001-12-04
Hafiz, Tariq R. (Department: 2163)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
C702S002000, C705S037000
Reexamination Certificate
active
06327569
ABSTRACT:
BACKGROUND OF THE INVENTION
1. The Field of the Invention
The present invention relates generally to precision agricultural systems and methods. More specifically the present invention relates to directly linking a harvest environment employing precision agricultural systems and methods to the marketplace. Even more specifically, the present invention relates to linking the harvest environment to the marketplace for conducting real time transactions of crops harvested from the harvest environment.
2. The Relevant Technology
The sequence of events that brings crops to the marketplace conventionally includes four phases. In the first phase, a farmer prepares an agricultural field, plants and harvests crops from the field and transports them to an elevator for storage. The second phase includes the warehousing of the crops while a brokerage house transacts for the stored crops. In the third phase, the crops are transported to a manufacturer such as a mill where they are transformed into various consumer goods such as foodstuffs and food-based products. The fourth phase includes the selling of the consumer goods to an end user for consumption or use.
In preparing an agricultural field a farmer typically samples the soil before, and frequently during, the growing season at predetermined locations (e.g. grids) throughout the field to determine its soil type and percentage of nutrient content. Once determined, a fertilizer prescription indicating relative amounts of nutrient requirements is devised for the agricultural field as a function of the crop to be planted therein. At some appropriate time in relation to the growing season of the crop the fertilizer prescription is applied to the field achieve greater harvests.
Although developing a fertilizer prescription in this manner has been used extensively by farming operations for decades, the taking and analysis of soil samples is time consuming and labor intensive. This is especially true with farming operations having numerous agricultural fields requiring soil sampling.
Regardless of where in a field soil samples are taken from, and no matter how accurate the analysis, soil samples taken in the foregoing manner are, at best, incomplete representations of the nutrients in an agricultural field. This is because the samples are only taken at a few select locations. Thus, to achieve a nutrient map indicating relative amounts of nutrient content in an agricultural field, and ultimately a fertilizer prescription, the analyzed soil samples must be interpolated for regions in the field where no samples were taken. Although still heavily relied upon by many farming operations, the soil samples only provide an informed guess as to the actual amount and composition of the nutrients.
In an effort to minimize some of the time required to obtain an understanding of the nutrient content in a field, and ultimately the time required to understand appropriate fertilizer requirements, farming operations often consult tabular data compiled by agronomists. Since this data is compiled according to “general” field characteristics, it is often strongly criticized as being too generic and not capable of providing meaningful impact upon any specific farming operation. This data has also been criticized as being less-than indicative of “real-world” growing environments because the data is frequently generated from “closed” environments, such as greenhouses and terrariums.
In contrast, if the farming operation is “precision” based, it is not uncommon to have soil samples taken and analyzed for every few feet of a multiple-acre agricultural field. Although this requires little or no interpolation to obtain an understanding of the nutrient content for a field, this method trades poor accuracy obtained from random or sparse soil sampling for increases in time and labor expense. As a result, this can be overly expensive for farming operations having numerous agricultural fields requiring precise soil sampling.
Consequently, mere use of soil sampling and tabular data to obtain a detailed understanding of the nutrient content in a particular agricultural field either lacks in details and precision or is obtained as a result of tremendous capital expenditure in time and labor.
Moreover, since it is known that fertilizer production is a colossal consumer of invaluable energy resources, farming operations that apply fertilizer to a particular location in an agricultural field without an accurate understanding of the nutrient requirements of that location not only waste fertilizer and capital resources for the fertilizer, but also cause society to suffer because of the unnecessary expenditure of energy resources in the production thereof. Poorly applied fertilizer also potentially creates environmental problems because of excessive run off, for example. With such a fragile ecosystem, these practices are unacceptable.
An industry-wide awareness of this and other problems has spawned intensive data collections for individual fields according to numerous and wide-ranging field characteristics. It is believed that with more data and information, more understanding of fertilizer or watering requirements is achieved and waste is prevented. As an example, it is now not uncommon for a farming operation using precision agricultural methods to generate extensive data on field characteristics such as micronutrients like boron and manganese, wind and water erosion, drainage, field histories, pH, lime, irrigation, predicted rainfall and topographical characteristics of the field, to name but a few.
Disadvantageously, however, these collections of data require even more time and money. One reason is because more soil sampling and analysis is required. Another reason is because various charts, such as topographical relief and rainfall charts, must be obtained and analyzed in combination and separately. Still another reason is because sophisticated computer software is required to interpret the vast amounts of data collected from a singular field.
Within the prior art still other techniques are used to determine field nutrient contents to assist in the development of a fertilizer prescription. These techniques, known commonly as variable rate technology (VRT), are primarily used to dispense substantially precise amounts of blended fertilizer compositions onto geographically small regions of an agricultural field.
In U.S. Pat. Nos. 4,700,895, 5,220,876, 5,355,815 and 5,689,418, all having common assignee Ag-Chem Equipment Co., Inc., of Minnesota, for example, exemplary VRT methods and apparatus are described that determine field nutrient contents and apply a unique fertilizer prescription to an agricultural field. In general, these patents combine to teach fertilization for a particular field by: (i) utilizing a soil map, particularized to the field, stored on-board a dispensing truck that is used to distribute the fertilizer; (ii) obtaining “real-time” soil samples from a soil sampler attached to the truck for supplementing and updating the soil map; and (iii) real-time variably adjusting the fertilizer blend from various nutrient bins stored upon the truck before distribution onto the field in order to “optimize” the fertilizer prescription.
While perhaps effective for dispensing substantially accurate fertilizer prescriptions, this VRT technology is extremely expensive for determining nutrient requirements of a field. The salient reason for the expense is because the dispensing trucks are extremely complex in function. Thus only wealthy farming operations are even able to afford such a means for determining nutrient contents.
Determining nutrient contents in this manner is also problematic because soil samples must still be taken and analyzed. Although sampling and analysis is performed “on-the-go” as the dispensing truck moves through the field, it would be an advance to eliminate reliance upon soil sampling because customized moving samplers, hence expensive samplers, must be employed on these trucks.
Regardless of whether the soil sampling of the field is precision based, VRT o
Hafiz Tariq R.
Kirton & McConkie
Krieger Michael F.
Meinecke-Diaz Susanna
Milestone Technology, Inc.
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