Patent Description:
In recent years, the availability of advanced location-specific agricultural soil measurement systems (used in so-called "precision farming" practices) has increased grower interest in determining spatial variations in soil properties. However, soil sensors in soil and remote satellite soil sensing can both suffer from measurement accuracy issues. <CIT> discloses soil sensing systems and implements for sensing different soil parameters, in which a soil sensing system includes a mechanical component of an agricultural implement and at least one sensor disposed on the mechanical component. The sensor generates an electromagnetic field through a region of soil as the agricultural implement traverses a field. The sensor comprises at least one radar transmitter and at least one radar receiver and the sensor measures different soil parameters including a soil dielectric constant. <CIT> discloses remote wireless moisture sensors for irrigation, in which a remote wireless moisture sensing unit is insertable into soil. The sensing unit includes at least three capacitive sensors positioned at three spaced apart levels with respect to the surface of the soil. The capacitance of each sensor increases in the presence of increased moisture content of the soil proximate to the sensor. An analog multiplexer selectively routes each sensor to an input to a capacitively-controlled oscillator to cause the oscillator to generate a clock signal having a frequency responsive to the capacitance of the currently connected sensor and thus responsive to the moisture content proximate to the currently selected sensor. A processor generates a respective data value for the frequency corresponding to each sensor and transmits the data values for the sensors via a radio frequency transceiver. The data values are processed to determine the moisture content of the soil at the three sensor levels.

The present disclosure is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which:.

<FIG> shows an example of a soil and plant analysis system <NUM> (apparatus <NUM>) that includes an implement <NUM> (e.g., Planter, Seeder, Drill, Fertilizer Spreader, Sprayer, Plow, Harrow, Disk, Ripper, Center pivot irrigator, Tillage equipment) and a machine <NUM> (e.g., translatable self-propelled or pulled machine, vehicle, All-terrain vehicle, Utility Terrain Vehicle, Pick-up truck, Combine Harvester, Tractor), in accordance with one embodiment.

According to the invention there is provided a soil or plant analysis apparatus as defined by the appended claims.

Described herein are systems, machines, and implements having high and low frequency soil and plant analysis sensors for soil and plant analysis. The high and low frequency measurements allow a potentially quicker, higher resolution, and lower accuracy measurement to be corrected by a less frequent, higher accuracy measurement. The terms high frequency and low frequency are relative to each other, and they are defined by a ratio described below. High frequency is any frequency that is higher than low frequency, and low frequency is any frequency that is lower than high frequency.

In the following description, numerous details are set forth. It will be apparent, however, to one skilled in the art, that embodiments of the present disclosure may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present disclosure.

<FIG> shows an example of a system <NUM> for performing agricultural operations (e.g., high and low frequency soil and plant analysis, sensing soil and agricultural plant characteristics, applying fluid applications to plants) of agricultural fields in accordance with one embodiment. For example and in one embodiment, the system <NUM> may be implemented as a cloud based system with servers, data processing devices, computers, etc. Aspects, features, and functionality of the system <NUM> can be implemented in a laboratory testing device, planters, planter monitors, All-terrain vehicle, Utility Terrain Vehicle, Pick-up truck, Combine Harvester, Tractor, Planter, Seeder, Drill, Fertilizer Spreader, Sprayer, Plow, Harrow, Disk, Ripper, irrigation implement (e.g., Center pivot irrigator), Tillage equipment, sidedress bars, servers, laptops, tablets, computer terminals, client devices, aviation device <NUM> (e.g., airplane <NUM>, aerial drone device), handheld computers, personal digital assistants, cellular telephones, cameras, smart phones, mobile phones, computing devices, or a combination of any of these or other data processing devices. A laboratory device is a device is a stand alone device for analyzing samples. It can be stationed in a laboratory, or it can be used elsewhere not on a vehicle.

In other embodiments, the system <NUM> includes a network computer or an embedded processing device within another device (e.g., display device) or within a machine (e.g., planter, combine), or other types of data processing systems having fewer components or perhaps more components than that shown in <FIG>. The system <NUM> (e.g., cloud based system) can sense soil and plants for soil and plant analysis using one or more of an implement (e.g., Planter, Seeder, Drill, Fertilizer Spreader, Sprayer, Plow, Harrow, Disk, Ripper, Center pivot irrigator, Tillage equipment), a machine (e.g., translatable self-propelled or pulled machine, vehicle, All-terrain vehicle, Utility Terrain Vehicle, Pick-up truck, Combine Harvester, Tractor), and an aviation device, or in a laboratory device. The system <NUM> includes machines <NUM>, <NUM>, <NUM>, <NUM> and implements <NUM>, <NUM>, <NUM> coupled to a respective machine <NUM>, <NUM>, <NUM>, <NUM>. The implements can include sub-systems <NUM>, <NUM> and the machines and aviation devices can include sub-systems <NUM>, <NUM> with sensors for sensing soil and plants within associated fields (e.g., fields <NUM>, <NUM>, <NUM>, <NUM>).

The system <NUM> includes an agricultural analysis system <NUM> that includes a weather store <NUM> with current and historical weather data, weather predictions module <NUM> with weather predictions for different regions, and at least one processing system <NUM> for executing instructions for controlling and monitoring different operations (e.g., soil and plant measurements). The storage medium <NUM> may store instructions, software, software programs, etc. for execution by the processing system and for performing operations of the agricultural analysis system <NUM>. In one example, storage medium <NUM> may contain a plant sensing prescription (e.g., plant sensing prescription that relates georeferenced positions in the field to locations of plants, plant data for each plant). The implement <NUM> (or any of the implements) may include sensors, a pump, flow sensors and/or flow controllers that may be specifically the elements that are in communication with the network <NUM> for sending control signals or receiving as-applied data.

An image database <NUM> stores captured images of crops at different growth stages. A data analytics module <NUM> may perform analytics on agricultural data (e.g., images, weather, field, yield, etc.) to generate crop predictions <NUM> relating to agricultural operations.

A field information database <NUM> stores agricultural data (e.g., sensed data for determining plant characteristics (e.g., stalk diameter, plant dimensions), crop growth stage, soil types, sensed data for determining soil characteristics, moisture holding capacity, etc.) for the fields that are being monitored by the system <NUM>. An agricultural practices information database <NUM> stores farm practices information (e.g., as-applied planting information, as-applied spraying information, as-applied fertilization information, planting population, applied nutrients (e.g., nitrogen), yield levels, proprietary indices (e.g., ratio of seed population to a soil parameter), etc.) for the fields that are being monitored by the system <NUM>. An implement can obtain fluid application data from the application units and provide this data to the system <NUM>. A cost/price database <NUM> stores input cost information (e.g., cost of seed, cost of nutrients (e.g., nitrogen)) and commodity price information (e.g., revenue from crop).

The system <NUM> shown in <FIG> may include a network interface <NUM> for communicating with other systems or devices such as drone devices, user devices, and machines (e.g., planters, combines) via a network <NUM> (e.g., Internet, wide area network, WiMax, satellite, cellular, IP network, etc.). The network interface includes one or more types of transceivers for communicating via the network <NUM>.

The processing system <NUM> may include one or more microprocessors, processors, a system on a chip (integrated circuit), or one or more microcontrollers. The processing system includes processing logic for executing software instructions of one or more programs. The system <NUM> includes the storage medium <NUM> for storing data and programs for execution by the processing system. The storage medium <NUM> can store, for example, software components such as a software application for sensing plant data or any other software application. The storage medium <NUM> can be any known form of a machine readable non-transitory storage medium, such as semiconductor memory (e.g., flash; SRAM; DRAM; etc.) or non-volatile memory, such as hard disks or solid-state drive.

While the storage medium (e.g., machine-accessible non-transitory medium) is shown in an exemplary embodiment to be a single medium, the term "machine-accessible non-transitory medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term "machine-accessible non-transitory medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present disclosure. The term "machine-accessible non-transitory medium" shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media, and carrier wave signals.

Turning to <FIG>, an embodiment is illustrated in which the row unit <NUM> is a planter row unit. <FIG> illustrates one example of a particular application of the soil and plant analysis sensors <NUM> as described herein that are disposed on a row unit <NUM> of an agricultural planter. The row unit <NUM> includes a soil and plant analysis sensor 100A disposed on a forward end of the row unit <NUM> and a soil and plant analysis sensor 100B disposed rearward end of the row unit <NUM>. The soil and plant analysis sensors 100A, 100B may be above ground <NUM> for certain applications (e.g., plant contact sensing, remote soil or plant sensing) or below ground <NUM> for other applications (e.g., soil contact sensing).

With respect to <FIG>, the row unit <NUM> is comprised of a frame <NUM> pivotally connected to the toolbar <NUM> by a parallel linkage <NUM> enabling each row unit <NUM> to move vertically independently of the toolbar <NUM>. The frame <NUM> operably supports one or more hoppers <NUM>, a seed meter <NUM>, a seed delivery mechanism <NUM>, a downforce control system <NUM>, a seed trench opening assembly <NUM>, a trench closing assembly <NUM>, a packer wheel assembly <NUM>, and a row cleaner assembly <NUM>. It should be understood that the row unit <NUM> shown in <FIG> may be for a conventional planter or the row unit <NUM> may be a central fill planter, in which case the hoppers <NUM> may be replaced with one or more mini-hoppers and the frame <NUM> modified accordingly as would be recognized by those of skill in the art.

The downforce control system <NUM> is disposed to apply lift and/or downforce on the row unit <NUM> such as disclosed in U. Publication No. <CIT>.

The seed trench opening assembly <NUM> includes a pair of opening discs <NUM> rotatably supported by a downwardly extending shank member <NUM> of the frame <NUM>. The opening discs <NUM> are arranged to diverge outwardly and rearwardly so as to open a v-shaped trench <NUM> in the soil <NUM> as the planter traverses the field. The seed delivery mechanism <NUM>, such as a seed tube or seed conveyor, is positioned between the opening discs <NUM> to deliver seed from the seed meter <NUM> and deposit it into the opened seed trench <NUM>. The depth of the seed trench <NUM> is controlled by a pair of gauge wheels <NUM> positioned adjacent to the opening discs <NUM>. The gauge wheels <NUM> are rotatably supported by gauge wheel arms <NUM> which are pivotally secured at one end to the frame <NUM> about pivot pin <NUM>. A rocker arm <NUM> is pivotally supported on the frame <NUM> by a pivot pin <NUM>. It should be appreciated that rotation of the rocker arm <NUM> about the pivot pin <NUM> sets the depth of the trench <NUM> by limiting the upward travel of the gauge wheel arms <NUM> (and thus the gauge wheels) relative to the opening discs <NUM>. The rocker arm <NUM> may be adjustably positioned via a linear actuator <NUM> mounted to the row unit frame <NUM> and pivotally coupled to an upper end of the rocker arm <NUM>. The linear actuator <NUM> may be controlled remotely or automatically actuated as disclosed, for example, in International Publication No. <CIT>.

A downforce sensor <NUM> is configured to generate a signal related to the amount of force imposed by the gauge wheels <NUM> on the soil. In some embodiments the pivot pin <NUM> for the rocker arm <NUM> may comprise the downforce sensor <NUM>, such as the instrumented pins disclosed in <CIT>. The seed meter <NUM> may be any commercially available seed meter, such as the fingertype meter or vacuum seed meter, such as the vSet® meter, available from Precision Planting LLC, <NUM> Townline Rd, Tremont, IL <NUM>.

The trench closing assembly <NUM> includes a closing wheel arm <NUM> which pivotally attaches to the row unit frame <NUM>. A pair of offset closing wheels <NUM> are rotatably attached to the closing wheel arm <NUM> and angularly disposed to direct soil back into the open seed trench so as to "close" the soil trench. An actuator <NUM> may be pivotally attached at one end to the closing wheel arm <NUM> and at its other end to the row unit frame <NUM> to vary the down pressure exerted by the closing wheels <NUM> depending on soil conditions. The closing wheel assembly <NUM> may be of the type disclosed in International Publication No. <CIT>.

The packer wheel assembly <NUM> comprises an arm <NUM> pivotally attached to the row unit fame <NUM> and extends rearward of the closing wheel assembly <NUM> and in alignment therewith.

The arm <NUM> rotatably supports a packer wheel <NUM>. An actuator <NUM> is pivotally attached at one end to the arm and at its other end to the row unit frame <NUM> to vary the amount of downforce exerted by the packer wheel <NUM> to pack the soil over the seed trench <NUM>.

The row cleaner assembly <NUM> may be the CleanSweep® system available from Precision Planting LLC, <NUM> Townline Rd, Tremont, IL <NUM>. The row cleaner assembly <NUM> includes an arm <NUM> pivotally attached to the forward end of the row unit frame <NUM> and aligned with the trench opening assembly <NUM>. A pair of row cleaner wheels <NUM> are rotatably attached to the forward end of the arm <NUM>. An actuator <NUM> is pivotally attached at one end to the arm <NUM> and at its other end to the row unit frame <NUM> to adjust the downforce on the arm to vary the aggressiveness of the action of the row cleaning wheels <NUM> depending on the amount of crop residue and soil conditions.

It should be appreciated that rather than positioning the soil and plant analysis sensors <NUM> as shown in <FIG>, the sensors may be positioned after the row cleaner assembly <NUM> and before the trench opening assembly <NUM> or in one or more other locations between the trench opening discs <NUM> and the closing wheels <NUM> or the packing wheel <NUM> depending on the soil region or characteristics of interest.

Turning to <FIG>, a soil and plant monitoring system <NUM> is schematically illustrated. The monitor <NUM> is preferably in data communication with components associated with each row unit <NUM> including the drives <NUM>, the seed sensors <NUM>, the GPS receiver <NUM>, the downforce sensors <NUM>, the valves <NUM>, the depth adjustment actuator <NUM>, and the depth actuator encoders <NUM>. In some embodiments, particularly those in which each seed meter <NUM> is not driven by an individual drive <NUM>, the monitor <NUM> is also preferably in data communication with clutches <NUM> configured to selectively operably couple the seed meter <NUM> to the drive <NUM>.

Continuing to refer to <FIG>, the monitor <NUM> is preferably in data communication with a cellular modem <NUM> or other component configured to place the monitor <NUM> in data communication with the Internet, indicated by reference numeral <NUM>. The internet connection may comprise a wireless connection or a cellular connection. Via the Internet connection, the monitor <NUM> preferably receives data from a weather data server <NUM> and a soil/plant data server <NUM>. Via the Internet connection, the monitor <NUM> preferably transmits measurement data (e.g., soil and plant measurements described herein) to a recommendation server (which may be the same server as the weather data server <NUM> and/or the soil/plant data server <NUM>) for storage and receives agronomic recommendations (e.g., planting recommendations such as planting depth, whether to plant, which fields to plant, which seed to plant, or which crop to plant) from a recommendation system stored on the server; in some embodiments, the recommendation system updates the planting recommendations based on the measurement data provided by the monitor <NUM>.

Continuing to refer to <FIG>, the monitor <NUM> is also preferably in data communication with one or more temperature sensors <NUM> mounted to the planter <NUM> and configured to generate a signal related to the temperature of soil being worked by the planter row units <NUM>. The monitor <NUM> is preferably in data communication with one or more sensors <NUM> (e.g., reflectivity, optical wavelength reflectance/absorption, electromagnetic wavelength reflectance/absorption, electrical current flow, Xray flourescence, Laser-Induced Breakdown Spectroscopy, Near Infrared Spectroscopy, Mid Infrared Spectroscopy, Far Infrared Spectroscopy, Xray Diffraction, Gamma Ray emission, Multi-Spectral Sensing, Short wave infrared, Ion-Selective Electrode, Chemical Field Effect Transistor, Microfluidics, Flow Injection Analysis, Inductively Coupled Plasma, UV Visible or Near Infrared Flourescence, Photoacoustic Spectroscopy) mounted to the planter <NUM> and configured to generate a signal related to the soil or plant being worked by the planter row units <NUM>.

Referring to <FIG>, the monitor <NUM> is preferably in data communication with one or more electrical conductivity sensors <NUM> mounted to the planter <NUM> and configured to generate a signal related to the temperature of soil being worked by the planter row units <NUM>.

In some embodiments, a first set of sensors <NUM>, temperature sensors <NUM>, and electrical conductivity sensors are mounted to a seed firmer <NUM> and disposed to measure soil characteristics, temperature and electrical conductivity, respectively, of soil in the trench <NUM>. In some embodiments, a second set of sensors <NUM>, temperature sensors <NUM>, and electrical conductivity sensors <NUM> are mounted to a reference sensor assembly <NUM> and disposed to measure soil characteristics, temperature and electrical conductivity, respectively, of the soil, preferably at a depth different than the sensors on the seed firmer <NUM>.

In some embodiments, a subset of the sensors are in data communication with the monitor <NUM> via a bus <NUM> (e.g., a CAN bus). In some embodiments, the sensors mounted to the seed firmer <NUM> and the reference sensor assembly <NUM> are likewise in data communication with the monitor <NUM> via the bus <NUM>. However, in the embodiment illustrated in <FIG>, the sensors mounted to the seed firmer the sensors mounted to the seed firmer <NUM> and the reference sensor assembly <NUM> are in data communication with the monitor <NUM> via a first wireless transmitter <NUM>-<NUM> and a second wireless transmitter <NUM>-<NUM>, respectively. The wireless transmitters <NUM> at each row unit are preferably in data communication with a single wireless receiver <NUM> which is in turn in data communication with the monitor <NUM>. The wireless receiver may be mounted to the toolbar <NUM> or in the cab of the tractor <NUM>.

Each sub-system of a soil and plant analysis system can use sensing technology including but not limited to: optical wavelength reflectance/absorption values, electromagnetic wavelength reflectance/absorption values, temperature, electrical current flow, electrical conductivity, Xray flourescence, Laser-Induced Breakdown Spectroscopy, Near Infrared Spectroscopy, Mid Infrared Spectroscopy, Far Infrared Spectroscopy, Xray Diffraction, Gamma Ray emission, Multi-Spectral Sensing, Short wave infrared, Ion-Selective Electrode, Chemical Field Effect Transistor, Microfluidics, Flow Injection Analysis, Inductively Coupled Plasma, UV Visible or Near Infrared Flourescence, Photoacoustic Spectroscopy.

Each sub-system could have various potential embodiments in regards to proximity to the soil including but not limited to direct physical contact with the soil (or plant) and remote measurements of soil or plants with no direct physical contact to soil or plants.

The direct measurement apparatuses can be mounted on the one of the following vehicles or equipment including but not limited to: Planter, Seeder, Drill, Fertilizer Spreader, Sprayer, Plow, Harrow, Disk, Ripper, Center pivot irrigator, Tillage equipment, translatable self-propelled or pulled machine, vehicle, All-terrain vehicle, Utility Terrain Vehicle, Pick-up truck, Combine Harvester, Tractor.

For no direct physical contact applications, the remote measurement apparatuses could be mounted on any of the previously mentioned vehicles or equipment, but also on aerial devices such as airplane, drone, satellite (e.g., satellite imagery), etc. Also, samples can be collected and tested in a laboratory testing device.

Each sub-system could have various potential embodiments in regards to soil preparation including but not limited to the following embodiments. In a first example, the soil could receive no preparation, but simply be in native field conditions, and the measurement apparatus could directly measure the soil properties.

In a second example, a soil solution could be created by adding a diluent or extractant, followed by using the measurement apparatus to measure the properties in the soil solution. The extractant is specifically chosen for extracting a chemical to be tested. In some embodiments, the diluent or extractant is water. In other embodiments, the extractant is any chemical extractant used to test for nutrients in soil and/or vegetation. Examples of extractants include, but are not limited to water, Mehlich <NUM> extractant, NaCl, DTPA (diethylenetriaminepentaacetic acid), AB-DTPA (ammonium bicarbonate-diethylenetriaminepentaacetic acid), Mehlich <NUM>, Mehlich <NUM>, Mehlich <NUM>, NH<NUM>OAc, Olsen P test extractant, Morgan extractant, Modified Morgan extractant, Bray-Kurtz extractant, CaCl<NUM>, BaCl<NUM>, SrCl<NUM>, Hot Water, Truog extractant, Ambic extractant, HNO<NUM>, LiCl, calcium-acetate-lactate, oxalate, citrate-bicarbonate-dithionite, HCl, acid ammonium oxalate.

In a third example, a soil "pellet" could be created by mechanically compressing the soil followed by using the measurement apparatus to measure the properties in the soil "pellet".

In a fourth example, a soil sample could be prepared by removing the water from the soil by a drying process followed by using the measurement apparatus to measure the properties in the soil.

In a fifth example, a soil sample could be prepared by mechanically smoothing or roughening the surface properties of the soil to assist in follow-up measurement method.

The soil and plant analysis system can measure different parameters including soil and plant measurements such as soil physical properties, soil chemical properties, soil mechanical properties, soil biological properties, and plant properties.

The soil physical properties include density, strength, texture, structure, moisture content, consistence, permeability, pore space, and mineralogy.

Soil chemical properties (extractable and non-extractable forms) include pH, buffer pH, Phosphorus, Potassium, Calcium, Magnesium, Cation Exchange Capacity, Organic Matter, Sulfur, Nitrate, Zinc, Sodium, Iron, Manganese, Molybdenum, Boron, Copper, Chlorine, Chloride, Iron, base saturation, Nitrate, Nitrite, Total Nitrogen, Ammonium, Phosphate, Orthophosphate, Polyphosphate, Total Phosphate, Cation Exchange Capacity, Percent Base Saturation of Cations, Soluble Salts, Organic Matter, Excess Lime, Active Carbon, Aluminum, Amino Sugar Nitrate, Ammoniacal Nitrogen, Carbon:Nitrogen Ratio, Electrical Conductivity, Texture (Sand, Silt, Clay), Cyst nematode egg counts, and Mineralizable Nitrogen.

Soil mechanical properties includes shear strength, compressibility, erodability, elasticity, plasticity, available water capacity, plastic limit, liquid limit, specific gravity, etc..

Soil biological properties include mineralization potential, CO2 burst, Nematode analysis, and Cyst nematode.

Plants/vegetation measured properties include Nitrogen, Nitrate, Phosphorus, Potassium, Magnesium, Calcium, Sodium, Percent Base Saturation of Cations, Sulfur, Zinc, Manganese, Iron, Copper, Boron, Ammoniacal Nitrogen, Carbon, Chloride, Cobalt, Molybdenum, Selenium, Total Nitrogen, and live plant parasitic nematode.

In one example, a measurement frequency can be represented by the following units but is not limited to Measurements/area (e.g., acre, hectare, m^<NUM>, ft^<NUM>), Measurements/time, Measurements/distance (e.g., foot, meter, kilometer, etc), Measurements/grid with a grid being a pattern of polygonal shapes superimposed on a field, measurements/zone with a zone being an irregular shape superimposed onto a field.

<FIG> illustrates a soil and plant analysis apparatus in accordance with one embodiment. The soil analysis apparatus <NUM> can be self-propelled or pulled by a tractor <NUM> or machine. The soil and plant analysis apparatus <NUM> includes a sub-system <NUM> and a sub-system <NUM>. In one example, a diluent can be added to sub-system <NUM> and soil and plant properties are measured with a flow injection analysis system. The sub-system <NUM> (e.g., soil collection knife, plant collection knife) may include soil/plant collection probe <NUM> and a sensor <NUM> (e.g., NIR sensor) in direct contact with soil or plant tissue. The sensor <NUM> can be mounted to the sub-system <NUM>. The sensor <NUM> can be above, near, or below a soil surface level <NUM> depending a soil or plant analysis application. Alternatively, soil or plant samples can be collected and then tested on a laboratory device separate from the vehicle.

<FIG> illustrate a soil and plant analysis apparatus in accordance with another embodiment. The soil and plant analysis apparatus <NUM> can be self-propelled or pulled by a tractor <NUM>, <NUM>, or machine. The soil and plant analysis apparatus <NUM> includes a sub-system <NUM> in <FIG> and a sub-system <NUM> in <FIG>. The sub-system <NUM> may include a sensor <NUM> (e.g., laser-induced breakdown spectroscopy (LIBS) probe sensor) in direct contact with soil or plants to measure soil or plant properties with laser-induced breakdown spectroscopy. The sensor <NUM> can be mounted to the sub-system <NUM>.

In one example, the sub-system <NUM> may include a sensor <NUM> (e.g., VIS-NIR sensor) in direct contact with soil to sense soil properties. The sensor <NUM> can be mounted to the sub-system <NUM>, which can be connected or mounted to an implement <NUM> (e.g., planter <NUM>). The sensors <NUM> and <NUM> can be above, near, or below a soil surface level <NUM>.

<FIG> illustrates a soil and plant analysis apparatus in accordance with another embodiment. The soil and plant analysis apparatus <NUM> can be self-propelled or pulled by a tractor <NUM> or machine. The soil and plant analysis apparatus <NUM> includes a sub-system <NUM> having a knife <NUM> with a sensor <NUM> and soil/plant collection probe <NUM>. A sub-system <NUM> can be mounted to an irrigation system <NUM> (e.g., center pivot irrigator) or a different type of implement. In one example, the sub-system <NUM> can compress soil/plant tissue into a small sample (e.g., pellet), which is then analyzed by xray diffraction. The knife <NUM> includes the soil/plant probe <NUM> to obtain soil or plant tissue from a field and provide this soil or plant tissue as an input to the sub-system <NUM>. The knife <NUM> includes an xray diffraction sensor <NUM> to sense soil or plant properties. The sub-system <NUM> performs non-contact soil/plant sensing using a Gamma ray emission technique. The sensor <NUM> can be positioned above, near, or below a soil surface level <NUM> while the sub-system <NUM> is positioned above the soil surface level for the Gamma ray emission technique.

<FIG> illustrates a soil and plant analysis apparatus in accordance with another embodiment. The soil and plant analysis apparatus <NUM> includes a sub-system <NUM> and a sub-system <NUM>. The sub-system <NUM> can be self-propelled or pulled by a tractor <NUM> or machine. In one example, a diluent can be added to analysis unit <NUM> of sub-system <NUM> and soil/plant properties are measured with an ion selective electrode. The soil collection knife <NUM> of the sub-system <NUM> may include soil/plant tissue collection probe <NUM>. The knife <NUM> can be positioned below the soil surface level <NUM>.

The sub-system <NUM> includes a multi-spectral sensor with the sub-system <NUM> being mounted or integrated with an aviation device <NUM>. The multi-spectral sensor measures soil or plant characteristics without contacting the soil or plant tissue.

In one example of a first embodiment, a soil analysis apparatus includes a first sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs low frequency soil measurements and a second sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs high frequency soil measurements. A first frequency of the high frequency measurement of the second sub-system and a second frequency of the low frequency measurement of the first sub-system have a frequency ratio of at least <NUM>. In one example, the frequency ratio (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, etc.) is at least <NUM> and the low frequency measurements with higher accuracy can be used to improve accuracy for high frequency measurements with lower accuracy.

A third sub-system (e.g., processing system <NUM>, processing system <NUM>, processing system <NUM>, processing system <NUM>) is configured to combine measurements from the first sub-system with measurements from the second sub-system into a spatial map of soil properties that can be displayed on a display device (e.g., display device <NUM>, <NUM>, monitor <NUM>).

In one example, the first and second sub-systems are one or more of the following: mechanically coupled, in fluid communication, or in electrical communication with each other.

The first sub-system and second sub-system are both attached to a single vehicle or attached pieces of equipment in a field. The measurement accuracy of the first sub-system can be at least <NUM>% better than the measurement accuracy of the second sub-system.

In one example of a second embodiment, a soil analysis apparatus includes a first sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs high accuracy soil measurements and a second sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs low accuracy soil measurements. The high measurement accuracy of the first sub-system is at least <NUM> times (e.g., <NUM> times, <NUM> times, <NUM> times, <NUM> times, etc.) the low measurement accuracy of the second sub-system.

The first sub-system and second sub-system are both attached to a single vehicle or attached pieces of equipment in a field. The high and low accuracy measurements allow a potentially quicker, higher resolution, and lower accuracy measurement to be corrected by a less frequent, higher accuracy measurement.

In one example of a third embodiment, a plant analysis apparatus includes a first sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs low frequency plant measurements and a second sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs high frequency plant measurements. The high frequency measurements of the second sub-system can be greater than <NUM> times the low frequency measurements of the first sub-system. In one example, the frequency ratio (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, etc.) between high and low frequency measurements is at least <NUM>.

A third sub-system (e.g., processing system <NUM>, processing system <NUM>, processing system <NUM>, processing system <NUM>) is configured to combine measurements from the first sub-system with measurements from the second sub-system into a spatial map of plant properties that can be displayed on a display device (e.g., display device <NUM>, <NUM>, monitor <NUM>).

In one example of a fourth embodiment, a plant analysis apparatus includes a first sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs high accuracy soil measurements and a second sub-system (e.g., <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, sensors <NUM>, probe <NUM>, sensors <NUM>) that performs low accuracy soil measurements. The high measurement accuracy of the first sub-system is at least <NUM> times (e.g., <NUM> times, <NUM> times, <NUM> times, <NUM> times, etc.) the low measurement accuracy of the second sub-system.

A third sub-system (e.g., processing system <NUM>, processing system <NUM>, processing system <NUM>, monitor <NUM>) is configured to combine measurements from the first sub-system with measurements from the second sub-system into a spatial map of plant properties that can be displayed on a display device (e.g., display device <NUM>, <NUM>, monitor <NUM>). The measurements may include any measurements for analysis of plant tissue including nitrate temporal measurements.

In an example, the high frequency measurement occurs at <NUM> measurements per hectare i.e. <NUM> measurements per acre, and the low frequency measurement occurs at <NUM> measurements per hectare i.e. <NUM> measurements per acre, resulting in a ratio of <NUM>:<NUM>, thus meeting the criteria (e.g., high frequency measurement of the second sub-system can be greater than <NUM> times the low frequency measurement of the first sub-system).

In another example, the high frequency measurement occurs at <NUM> measurements per second, and the low frequency measurement occurs at <NUM> measurements per second, resulting in a ratio of <NUM>:<NUM>.

Soil analysis measurement accuracy is calculated by comparing measured values with comparable soil lab values. For example, in the case of a soil phosphate measurement, the measurement accuracy is calculated by the following equation:.

|Lab Phosphate - Soil analysis measured phosphate|/lab Phosphate.

In one example, (|<NUM> ppm - <NUM> ppm|/<NUM> ppm) * <NUM>% = <NUM>%, given <NUM> ppm for Lab Phosphate, <NUM> ppm for soil analysis measured phosphate, and <NUM> ppm for Lab Phosphate.

A third sub-system is capable of combining measurements that are received from other sub-systems. There are many ways for the third sub-system <NUM> to combine the measurements from the first and second sub-system.

In one example, it is assumed that the high frequency data from the second sub-system is the "primary" data that will be operated on, since it has the benefit of a greater resolution than the data from the first system.

<FIG> illustrates a flow diagram of one embodiment for a method <NUM> of combining soil or plant measurements that are received from first and second sub-systems of a soil and plant analysis apparatus. The method <NUM> is performed by hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine or a device), or a combination of both. In one embodiment, the method <NUM> is performed by a third sub-system (e.g., processing system <NUM> of cloud based processing entity, processing system <NUM>, processing system <NUM>, monitor <NUM>) of a soil and plant analysis apparatus (e.g., apparatus <NUM>, <NUM>, <NUM>, <NUM>). The third sub-system can execute instructions of a software application or program with processing logic.

In any embodiment herein, at operation <NUM>, a third sub-system of the soil and plant analysis system receives data (e.g., soil and plant measurements, soil and plant dataset) from the first and second sub-systems. At operation <NUM>, the third sub-system to cause a dataset from the second sub-system to be plotted on a spatial grid (e.g., grid <NUM>) composed of n cells. At operation <NUM>, the third sub-system to cause a dataset from the first sub-system to be plotted on the same spatial grid composed of n cells.

At operation <NUM>, the third sub-system to select around each data point from the dataset of the second sub-subsystem the m closest cells (e.g., m = <NUM>, m equals any integer value). At operation <NUM>, the third sub-system determines a median measurement of the m cells for the dataset of the second sub-system.

At operation <NUM>, the third sub-system performs a first linear regression of these median measurements from the dataset of the second sub-system versus the data points for the first sub-system. This first linear regression generates new data points for the dataset of the second sub-system.

At operation <NUM>, the third sub-system performs a second linear regression from the original second sub-system dataset to the regression line of the first linear regression that is associated with new/modified data points (e.g., soil or plant measurement data) for the second sub-system.

At operation <NUM>, the third sub-system applies a slope/offset from the second linear regression to all cells in the second sub-system dataset for a final corrected value or values.

<FIG> illustrates plots of the datasets from the first and second sub-systems in accordance with one embodiment. The high frequency dataset <NUM> from the second sub-system is plotted on a grid <NUM>. A low frequency dataset <NUM> from the second sub-system is plotted on the same grid <NUM>.

<FIG> illustrates an overlay of the datasets from the first and second sub-systems on the same grid <NUM>. The third sub-system to select around each data point from the dataset of the second sub-subsystem the m closest cells (e.g., m = <NUM>, m equals any integer value). The third sub-system determines a median measurement (e.g., <NUM>,<NUM>,<NUM>) of the m cells for the dataset of the second sub-system. The third sub-system performs a first linear regression (e.g., y = <NUM>. 4286x +<NUM>, y = <NUM>nd sub-system, x = <NUM>st sub-system) of these median measurements from the dataset of the second sub-system versus the data points (e.g., <NUM>, <NUM>, <NUM>) for the first sub-system.

The third sub-system perform a second linear regression (e.g., y = <NUM>. 9644x +<NUM>, y = <NUM>nd sub-system new values (<NUM>, <NUM>, <NUM>), x = 2nd sub-system original values (<NUM>,<NUM>,<NUM>)) from the original second sub-system dataset to the regression line from the first linear regression. The third sub-system applies this slope/offset from the second linear regression to all cells in the second sub-system dataset for a final corrected value (new values).

<FIG> shows an example of a soil and plant analysis system <NUM> (apparatus <NUM>) that includes an implement <NUM> (e.g., Planter, Seeder, Drill, Fertilizer Spreader, Sprayer, Plow, Harrow, Disk, Ripper, Center pivot irrigator, Tillage equipment) and a machine <NUM> (e.g., translatable self-propelled or pulled machine, vehicle, All-terrain vehicle, Utility Terrain Vehicle, Pick-up truck, Combine Harvester, Tractor), in accordance with one embodiment. The machine <NUM> includes a processing system <NUM>, memory <NUM>, machine network <NUM> (e.g., a controller area network (CAN) serial bus protocol network, an ISOBUS network, etc.), and a network interface <NUM> for communicating with other systems or devices including the implement <NUM>. The machine network <NUM> includes sensors <NUM> (e.g., speed sensors, optical wavelength reflectance/absorption, electromagnetic wavelength reflectance/absorption, temperature, electrical current flow, electrical conductivity, Xray flourescence, Laser-Induced Breakdown Spectroscopy, Near Infrared Spectroscopy, Mid Infrared Spectroscopy, Far Infrared Spectroscopy, Xray Diffraction, Gamma Ray emission, Multi-Spectral Sensing, Short wave infrared, Ion-Selective Electrode, Chemical Field Effect Transistor, Microfluidics, Flow Injection Analysis, Inductively Coupled Plasma, UV Visible or Near Infrared Flourescence, Photoacoustic Spectroscopy), controllers <NUM> (e.g., GPS receiver, radar unit) for controlling and monitoring operations of the machine or implement. The network interface <NUM> can include at least one of a GPS transceiver, a WLAN transceiver (e.g., WiFi), an infrared transceiver, a Bluetooth transceiver, Ethernet, or other interfaces from communications with other devices and systems including the implement <NUM>. The network interface <NUM> may be integrated with the machine network <NUM> or separate from the machine network <NUM> as illustrated in Figure <NUM>. The I/O ports <NUM> (e.g., diagnostic/on board diagnostic (OBD) port) enable communication with another data processing system or device (e.g., display devices, sensors, etc.).

In one example, the machine performs operations of a tractor that is coupled to an implement for soil and plant analysis of a field. The soil and plant analysis data for each row unit of the implement can be associated with locational data at time of application to have a better understanding of the soil and plant analysis for each row and region of a field. Data associated with the soil and plant analysis can be displayed on at least one of the display devices <NUM> and <NUM>. The display devices can be integrated with other components (e.g., processing system <NUM>, memory <NUM>, etc.) to form the monitor <NUM>.

The processing system <NUM> may include one or more microprocessors, processors, a system on a chip (integrated circuit), or one or more microcontrollers. The processing system includes processing logic <NUM> for executing software instructions of one or more programs and a communication unit <NUM> (e.g., transmitter, transceiver) for transmitting and receiving communications from the machine via machine network <NUM> or network interface <NUM> or implement via implement network <NUM> or network interface <NUM>. The communication unit <NUM> may be integrated with the processing system or separate from the processing system. In one embodiment, the communication unit <NUM> is in data communication with the machine network <NUM> and implement network <NUM> via a diagnostic/OBD port of the I/O ports <NUM>.

Processing logic <NUM> including one or more processors or processing units may process the communications received from the communication unit <NUM> including agricultural data (e.g., GPS data, planting application data, soil characteristics, plant characteristics, any data sensed from sensors of the implement <NUM> and machine <NUM>, etc.). The processing logic <NUM> can process high and low frequency soil/plant measurements as described herein to determine soil and plant properties and characteristics. The system <NUM> includes memory <NUM> for storing data and programs for execution (software <NUM>) by the processing system. The memory <NUM> can store, for example, software components such as soil and plant analysis software for analysis of soil and planting applications for performing operations of the present disclosure, or any other software application or module, images (e.g., captured images of crops, soil, furrow, soil clods, row units, etc.), alerts, maps, etc. The memory <NUM> can be any known form of a machine readable non-transitory storage medium, such as semiconductor memory (e.g., flash; SRAM; DRAM; etc.) or non-volatile memory, such as hard disks or solid-state drive. The system can also include an audio input/output subsystem (not shown) which may include a microphone and a speaker for, for example, receiving and sending voice commands or for user authentication or authorization (e.g., biometrics).

The processing system <NUM> communicates bi-directionally with memory <NUM>, machine network <NUM>, network interface <NUM>, header <NUM>, display device <NUM>, display device <NUM>, and I/O ports <NUM> via communication links <NUM>-<NUM>, respectively. The processing system <NUM> can be integrated with the memory <NUM> or separate from the memory <NUM>.

Display devices <NUM> and <NUM> can provide visual user interfaces for a user or operator. The display devices may include display controllers. In one embodiment, the display device <NUM> is a portable tablet device or computing device with a touchscreen that displays data (e.g., soil and plant analysis data, planting application data, captured images, localized view map layer, soil color data and images, high definition field maps of seed germination data, seed environment data, as-planted or as-harvested data or other agricultural variables or parameters, yield maps, alerts, etc.) and data generated by an agricultural data analysis software application and receives input from the user or operator for an exploded view of a region of a field, monitoring and controlling field operations. The operations may include configuration of the machine or implement, reporting of data, control of the machine or implement including sensors and controllers, and storage of the data generated. The display device <NUM> may be a display (e.g., display provided by an original equipment manufacturer (OEM)) that displays images and data for a localized view map layer, as-applied fluid application data, as-planted or as-harvested data, yield data, seed germination data, seed environment data, controlling a machine (e.g., planter, tractor, combine, sprayer, etc.), steering the machine, and monitoring the machine or an implement (e.g., planter, combine, sprayer, etc.) that is connected to the machine with sensors and controllers located on the machine or implement.

A cab control module <NUM> may include an additional control module for enabling or disabling certain components or devices of the machine or implement. For example, if the user or operator is not able to control the machine or implement using one or more of the display devices, then the cab control module may include switches to shut down or turn off components or devices of the machine or implement.

The implement <NUM> includes an implement network <NUM>, a processing system <NUM>, a network interface <NUM>, and optional input/output ports <NUM> for communicating with other systems or devices including the machine <NUM>. The implement network <NUM> (e. g, a controller area network (CAN) serial bus protocol network, an ISOBUS network, etc.) includes a pump <NUM> for pumping fluid from a storage tank(s) <NUM> to application units <NUM>, <NUM>,. N of the implement, sensors <NUM> (e.g., speed sensors, optical wavelength reflectance/absorption, electromagnetic wavelength reflectance/absorption, temperature, electrical current flow, electrical conductivity, Xray flourescence, Laser-Induced Breakdown Spectroscopy, Near Infrared Spectroscopy, Mid Infrared Spectroscopy, Far Infrared Spectroscopy, Xray Diffraction, Gamma Ray emission, Multi-Spectral Sensing, Short wave infrared, Ion-Selective Electrode, Chemical Field Effect Transistor, Microfluidics, Flow Injection Analysis, Inductively Coupled Plasma, UV Visible or Near Infrared Flourescence, Photoacoustic Spectroscopy seed sensors for detecting passage of seed, sensors for detecting characteristics of soil or a trench including soil moisture, soil organic matter, soil temperature, soil color, seed presence, seed spacing, percentage of seeds firmed, and soil residue presence, downforce sensors, actuator valves, moisture sensors or flow sensors for a combine, speed sensors for the machine, seed force sensors for a planter, fluid application sensors for a sprayer, or vacuum, lift, lower sensors for an implement, flow sensors, etc.) for sensing soil and plant properties and characteristics, probes <NUM> for collecting soil and plant samples for the soil and plant analysis, controllers <NUM> (e.g., GPS receiver), and the processing system <NUM> for controlling and monitoring operations of the implement. The pump controls and monitors the application of the fluid to crops or soil as applied by the implement. The fluid application can be applied at any stage of crop development including within a planting trench upon planting of seeds, adjacent to a planting trench in a separate trench, or in a region that is nearby to the planting region (e.g., between rows of corn or soybeans) having seeds or crop growth. In other embodiments, the applicator can be granular material applicator or a combination of fluid applicator and granular material applicator.

For example, the controllers may include processors in communication with a plurality of seed sensors. The processors are configured to process data (e.g., fluid application data, seed sensor data, soil data, plant data, furrow or trench data) and transmit processed data to the processing system <NUM> or <NUM>. The controllers and sensors may be used for monitoring motors and drives on a planter including a variable rate drive system for changing plant populations. The controllers and sensors may also provide swath control to shut off individual rows or sections of the planter. The sensors and controllers may sense changes in an electric motor that controls each row of a planter individually. These sensors and controllers may sense seed delivery speeds in a seed tube for each row of a planter.

The network interface <NUM> can be a GPS transceiver, a WLAN transceiver (e.g., WiFi), an infrared transceiver, a Bluetooth transceiver, Ethernet, or other interfaces from communications with other devices and systems including the machine <NUM>. The network interface <NUM> may be integrated with the implement network <NUM> or separate from the implement network <NUM> as illustrated in Figure <NUM>.

The processing system <NUM> communicates bi-directionally with the implement network <NUM>, network interface <NUM>, and I/O ports <NUM> via communication links <NUM>-<NUM>, respectively.

Claim 1:
A soil or plant analysis apparatus (<NUM>, <NUM>, <NUM>, <NUM>) comprising:
a first sub-system (<NUM>. <NUM>, <NUM>, <NUM>) configured to perform soil or plant measurements at a first measurement frequency represented by a first number of measurements per unit area; and
a second sub-system (<NUM>, <NUM>, <NUM>, <NUM>) configured to perform soil or plant measurements at a second measurement frequency represented by a second number of measurements per unit area, characterized in that the second measurement frequency of the second sub-system (<NUM>, <NUM>, <NUM>, <NUM>) is at least <NUM> times the first measurement frequency of the first sub-system (<NUM>, <NUM>, <NUM>, <NUM>).