CA2567587C - Crop moisture data conversion tool - Google Patents
Crop moisture data conversion tool Download PDFInfo
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- CA2567587C CA2567587C CA2567587A CA2567587A CA2567587C CA 2567587 C CA2567587 C CA 2567587C CA 2567587 A CA2567587 A CA 2567587A CA 2567587 A CA2567587 A CA 2567587A CA 2567587 C CA2567587 C CA 2567587C
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
- G01N27/22—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance
- G01N27/223—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance for determining moisture content, e.g. humidity
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Abstract
A moisture data conversion tool is used with a moisture meter that determines an electrical capacitance representation and temperature of a sample of a selected type of product or commodity. The conversion tool comprises a portable housing storing correlation data therein for determining moisture content expressed as a percentage of mass of the product responsive to electrical capacitance representation data and temperature data measured by the moisture meter and input into the conversion tool. The conversion tool includes a mode of operation for indicating to the user a desired mass of the sample to be placed into the moisture meter responsive to the user selecting the particular type of product or commodity to be measured.
Description
CROP MOISTURE DATA CONVERSION TOOL
FIELD OF THE INVENTION
The present invention relates to a tool for use with a meter of the type used to measure an electrical capacitance representation as an indication of moisture content of a sample of a given commodity, in which the tool is arranged to correlate the electrical capacitance representation measured by the meter, in the form of a dial drum reading, and a temperature of the commodity to a percentage of moisture of the sample using correlation data associated with the given commodity.
BACKGROUND
For more than 55 years, the Model 919 grain moisture tester has been the industry standard throughout the Canadian grain handling system for the determination of moisture in more than 100 different agricultural commodities.
This scientific piece of equipment has formed the cornerstone of grain moisture testing in Canada and is used by government agencies, grain elevators and farmers across Canada and the United States. There are approximately 25,000 units presently in use by Canadian farms and the importance of this piece of moisture testing equipment is unquestionable to everyone in the grain handling system.
The Canadian Grain Commission generates moisture charts that are used in conjunction with Dimo's Tool and Die Ltd.'s Model 919 moisture tester.
Generally a 250 gram sample of the commodity is weighed and placed into the dump tube of the moisture meter. At this time, the temperature of the grain sample is recorded. The sample is then dumped into the measuring cell and a dial drum reading or number value is obtained when the needle of the analogue meter movement reaches the lowest point. The dial drum value corresponds indirectly to a measured capacitance of the sample. The temperature and dial drum value are then searched
FIELD OF THE INVENTION
The present invention relates to a tool for use with a meter of the type used to measure an electrical capacitance representation as an indication of moisture content of a sample of a given commodity, in which the tool is arranged to correlate the electrical capacitance representation measured by the meter, in the form of a dial drum reading, and a temperature of the commodity to a percentage of moisture of the sample using correlation data associated with the given commodity.
BACKGROUND
For more than 55 years, the Model 919 grain moisture tester has been the industry standard throughout the Canadian grain handling system for the determination of moisture in more than 100 different agricultural commodities.
This scientific piece of equipment has formed the cornerstone of grain moisture testing in Canada and is used by government agencies, grain elevators and farmers across Canada and the United States. There are approximately 25,000 units presently in use by Canadian farms and the importance of this piece of moisture testing equipment is unquestionable to everyone in the grain handling system.
The Canadian Grain Commission generates moisture charts that are used in conjunction with Dimo's Tool and Die Ltd.'s Model 919 moisture tester.
Generally a 250 gram sample of the commodity is weighed and placed into the dump tube of the moisture meter. At this time, the temperature of the grain sample is recorded. The sample is then dumped into the measuring cell and a dial drum reading or number value is obtained when the needle of the analogue meter movement reaches the lowest point. The dial drum value corresponds indirectly to a measured capacitance of the sample. The temperature and dial drum value are then searched
2 for on the corresponding paper chart for the particular commodity. This process of manually determining the final moisture content of the grain by looking up the temperature and dial drum value can be tedious and difficult as the paper charts are in a table format and contain a vast amount of data. The presentation of the information contained in the charts is completed as well as can be, considering the huge amount of data they contain.
SUMMARY OF THE INVENTION
According to one aspect of the invention there is provided a moisture data conversion tool for use with a meter for determining an electrical capacitance representation of a sample of a given product, the tool comprising:
a portable housing;
a data input supported on the housing for receiving electrical capacitance representation data and temperature data of the sample;
a memory supported on the housing for storing correlation data therein which correlates electrical capacitance representation data to moisture content of the given product;
a processor supported on the housing for determining moisture content of the sample using the electrical capacitance representation data, the temperature data, and the correlation data;
a display supported on the housing for displaying the moisture content of the sample as determined by the processor; and a power source for supplying electrical power to the processor and the display.
The display on the housing also displays the commodity selection, stored results, and temperature data.
SUMMARY OF THE INVENTION
According to one aspect of the invention there is provided a moisture data conversion tool for use with a meter for determining an electrical capacitance representation of a sample of a given product, the tool comprising:
a portable housing;
a data input supported on the housing for receiving electrical capacitance representation data and temperature data of the sample;
a memory supported on the housing for storing correlation data therein which correlates electrical capacitance representation data to moisture content of the given product;
a processor supported on the housing for determining moisture content of the sample using the electrical capacitance representation data, the temperature data, and the correlation data;
a display supported on the housing for displaying the moisture content of the sample as determined by the processor; and a power source for supplying electrical power to the processor and the display.
The display on the housing also displays the commodity selection, stored results, and temperature data.
3 This electronic hand held tool will contain the chart data for every commodity that their Model 919 can be used to determine moisture content. The measured electrical capacitance representation corresponds to a dial drum value read from the Model 919 moisture meter available by Dimo's Tool and Die Ltd.
Stored in the device will be commodity information and related temperature, dial drum and moisture content values. Farmers will simply select the commodity that they would like to test, use our moisture tester and input the temperature of the sample along with the dial drum value given by the Model 919.
The LCD display of the device will show the producer the percent moisture.
This will dramatically cut down on the time it takes to test individual samples and make the Model 919 an even more user friendly moisture testing device. Instead of producers having to look values up in a paper chart they can simple input the values into the storage device and have the moisture content displayed for them. They will also be able to store previous test values to be recalled later in the season if necessary.
Preferably the memory stores correlation data therein associated with a plurality of different given products, and the data input is arranged for receiving product selection data. The processor is thus arranged to determine moisture content of the sample using the electrical capacitance representation data, the temperature data, the product selection data and the correlation data associated with a selected one of the given products as determined by the product selection data.
The memory may include test weight data indicating test weight of the sample for use with the meter for each of the given products, the display being arranged for displaying the test weight data responsive to determination of the selected one of the products.
At least some of the correlation data preferably comprises one or more
Stored in the device will be commodity information and related temperature, dial drum and moisture content values. Farmers will simply select the commodity that they would like to test, use our moisture tester and input the temperature of the sample along with the dial drum value given by the Model 919.
The LCD display of the device will show the producer the percent moisture.
This will dramatically cut down on the time it takes to test individual samples and make the Model 919 an even more user friendly moisture testing device. Instead of producers having to look values up in a paper chart they can simple input the values into the storage device and have the moisture content displayed for them. They will also be able to store previous test values to be recalled later in the season if necessary.
Preferably the memory stores correlation data therein associated with a plurality of different given products, and the data input is arranged for receiving product selection data. The processor is thus arranged to determine moisture content of the sample using the electrical capacitance representation data, the temperature data, the product selection data and the correlation data associated with a selected one of the given products as determined by the product selection data.
The memory may include test weight data indicating test weight of the sample for use with the meter for each of the given products, the display being arranged for displaying the test weight data responsive to determination of the selected one of the products.
At least some of the correlation data preferably comprises one or more
4 regression formulas, each representing moisture content as a function of electrical capacitance and temperature of a sample of the given product. When the memory stores correlation data associated with a plurality of different given products, the correlation data preferably comprises different formulas associated with the different given products respectively.
Some of the correlation data may comprise a plurality of different moisture content values, each with a respective electrical capacitance representation and temperature associated therewith. In this instance the processor is arranged to determine moisture content by determining which moisture content value is associated with the input electrical capacitance representation data and temperature data of the sample. Some of the correlation data in this instance may also comprise a formula representing moisture content as a function of moisture content values associated with a different one of a plurality of given products.
The processor may also be arranged to extrapolate moisture content from moisture content values stored in the memory when the electrical capacitance representation data and the temperature data fall outside of a range of electrical capacitance representation and temperature values associated with the respective moisture content values stored in the memory. This extends or increases the measuring range of the moisture meter.
The processor may be operable in two modes: a moisture content determination mode and a test weight determination mode. In the moisture content determination mode, the processor determines moisture content of the sample using the electrical capacitance representation data, the temperature data and the correlation data. In the test weight determination mode, the processor is arranged to display one of a test weight or a conversion of density units responsive to a measured density (in units of grams per half litre) input into the data input.
When the memory includes test weight data for a sample of the given product associated with a plurality of different given products, the processor is preferably arranged to determine the test weight data responsive to a selection of one
Some of the correlation data may comprise a plurality of different moisture content values, each with a respective electrical capacitance representation and temperature associated therewith. In this instance the processor is arranged to determine moisture content by determining which moisture content value is associated with the input electrical capacitance representation data and temperature data of the sample. Some of the correlation data in this instance may also comprise a formula representing moisture content as a function of moisture content values associated with a different one of a plurality of given products.
The processor may also be arranged to extrapolate moisture content from moisture content values stored in the memory when the electrical capacitance representation data and the temperature data fall outside of a range of electrical capacitance representation and temperature values associated with the respective moisture content values stored in the memory. This extends or increases the measuring range of the moisture meter.
The processor may be operable in two modes: a moisture content determination mode and a test weight determination mode. In the moisture content determination mode, the processor determines moisture content of the sample using the electrical capacitance representation data, the temperature data and the correlation data. In the test weight determination mode, the processor is arranged to display one of a test weight or a conversion of density units responsive to a measured density (in units of grams per half litre) input into the data input.
When the memory includes test weight data for a sample of the given product associated with a plurality of different given products, the processor is preferably arranged to determine the test weight data responsive to a selection of one
5 the given products and a measured density (in grams per half litre) of the sample being received by the data input.
The processor may be arranged to convert density data which is input into the data input into a plurality of density values each having different units of measurement, the density values being displayed on the display. The density values preferably include kilograms per hectalitre and pounds per bushel.
The memory preferably comprises a rewritable memory arranged to store determined moisture content for a plurality of different samples and subsequently recall the moisture content of the plurality of different samples.
The memory is also preferably arranged to store appended data with each moisture content. The appended data may include for example: data relating to field conditions or location with which the sample is associated, an identification of the given product, or a date of moisture content determination by the processor.
When the memory stores correlation data therein associated with a plurality of different given products, the memory preferably includes a first (or favourites) location storing correlation data of a first portion of the given products and a second location storing correlation data associated with a second portion of the given products, the first location of the memory being more readily accessible by a user using the data input than the second location.
One embodiment of the invention will now be described in conjunction with the accompanying drawings in which:
The processor may be arranged to convert density data which is input into the data input into a plurality of density values each having different units of measurement, the density values being displayed on the display. The density values preferably include kilograms per hectalitre and pounds per bushel.
The memory preferably comprises a rewritable memory arranged to store determined moisture content for a plurality of different samples and subsequently recall the moisture content of the plurality of different samples.
The memory is also preferably arranged to store appended data with each moisture content. The appended data may include for example: data relating to field conditions or location with which the sample is associated, an identification of the given product, or a date of moisture content determination by the processor.
When the memory stores correlation data therein associated with a plurality of different given products, the memory preferably includes a first (or favourites) location storing correlation data of a first portion of the given products and a second location storing correlation data associated with a second portion of the given products, the first location of the memory being more readily accessible by a user using the data input than the second location.
One embodiment of the invention will now be described in conjunction with the accompanying drawings in which:
6 BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 is a perspective view of the housing of the tool.
Figure 2 is a schematic illustration of the electrical components of the tool.
Figure 3 is a flow chart illustrating the order of operation of the processor of the tool.
In the drawings like characters of reference indicate corresponding parts in the different figures.
DETAILED DESCRIPTION
Referring to the accompanying figures there is illustrated a tool generally indicated by reference numeral 10. The tool 10 is an apparatus which is particularly suited for use with a moisture meter, for example a Model 919TM moisture tester made available by Dimo's Tool & Die Limited, Winnipeg, Canada. The tool 10 makes use of the electrical capacitance of a product as determined by the moisture tester to correlate this data to a moisture content expressed as a percentage of mass which is useful for grading various commodities including various types of grain or other similar crops.
The moisture meter generally involves applying an electrical current to a sample of the given product having a known mass. Electrical capacitance (in units of picofarads or microfarads) is measured and a representation thereof is displayed as an indirectly corresponding dial drum value. Temperature of the sample at the time of capacitance measurement is also measured by a separate thermometer. Various testing is performed by more complex means other than the tool 10 of the present invention to associate a moisture content value with various different values of electrical capacitance representation and temperature and selection of the type of
Figure 1 is a perspective view of the housing of the tool.
Figure 2 is a schematic illustration of the electrical components of the tool.
Figure 3 is a flow chart illustrating the order of operation of the processor of the tool.
In the drawings like characters of reference indicate corresponding parts in the different figures.
DETAILED DESCRIPTION
Referring to the accompanying figures there is illustrated a tool generally indicated by reference numeral 10. The tool 10 is an apparatus which is particularly suited for use with a moisture meter, for example a Model 919TM moisture tester made available by Dimo's Tool & Die Limited, Winnipeg, Canada. The tool 10 makes use of the electrical capacitance of a product as determined by the moisture tester to correlate this data to a moisture content expressed as a percentage of mass which is useful for grading various commodities including various types of grain or other similar crops.
The moisture meter generally involves applying an electrical current to a sample of the given product having a known mass. Electrical capacitance (in units of picofarads or microfarads) is measured and a representation thereof is displayed as an indirectly corresponding dial drum value. Temperature of the sample at the time of capacitance measurement is also measured by a separate thermometer. Various testing is performed by more complex means other than the tool 10 of the present invention to associate a moisture content value with various different values of electrical capacitance representation and temperature and selection of the type of
7 given product.
The tool 10 generally comprises a portable housing 12 which is suitable sized to be handheld by an operator for being portable to various different working environments. Within the housing there is provided a central processing unit 14 for controlling various operations of the tool.
Input keys 16 are provided for inputting data into the processor by an operator manually contacting the various keys. The input keys 16 preferable comprise a numbered keypad including characters 1 through 9 and 0 along with additional functions of up and down scrolling buttons, enter and delete keys, and alternate function keys.
A display 18 is supported on the housing on a front surface of the housing along with the input keys 16. The display comprises a graphical liquid crystal display (LCD) or other suitable electronic display for displaying characters to an operator of the tool.
Within the interior of the housing there is provided a read only memory for long term storage of the correlation data relating to various types of given product. This correlation data remains stored in the read only memory 20 throughout the various functions of the tool.
A rewritable memory 22 is also coupled to the processor 14 for 20 temporary storage of determined values of moisture content as well as any associated data to be stored therewith. Moisture content values associated with a plurality of different samples of one or more given products can be stored within the rewritable memory for subsequent recall of any one of the moisture content values.
Alternatively the values may be deleted and overwritten with new data values in the rewritable memory 22.
The tool 10 generally comprises a portable housing 12 which is suitable sized to be handheld by an operator for being portable to various different working environments. Within the housing there is provided a central processing unit 14 for controlling various operations of the tool.
Input keys 16 are provided for inputting data into the processor by an operator manually contacting the various keys. The input keys 16 preferable comprise a numbered keypad including characters 1 through 9 and 0 along with additional functions of up and down scrolling buttons, enter and delete keys, and alternate function keys.
A display 18 is supported on the housing on a front surface of the housing along with the input keys 16. The display comprises a graphical liquid crystal display (LCD) or other suitable electronic display for displaying characters to an operator of the tool.
Within the interior of the housing there is provided a read only memory for long term storage of the correlation data relating to various types of given product. This correlation data remains stored in the read only memory 20 throughout the various functions of the tool.
A rewritable memory 22 is also coupled to the processor 14 for 20 temporary storage of determined values of moisture content as well as any associated data to be stored therewith. Moisture content values associated with a plurality of different samples of one or more given products can be stored within the rewritable memory for subsequent recall of any one of the moisture content values.
Alternatively the values may be deleted and overwritten with new data values in the rewritable memory 22.
8 A battery 24 is provided within the housing to provide a portable power supply for operating the processor and the display, and all other associated electrical components of the tool.
The central processor is arranged to control various functions and modes of the tool 10 for determining moisture content values as well as other useful information for use with the moisture meter of the prior art. As shown in figure 3, upon initially operating the tool a user first selects a mode of operation between a moisture content determination mode 26 or a test weight determination mode 28.
In the moisture content determination mode 26, the processor queries the operator with the relevant type of commodity or product with which moisture content is to be determined. This is accomplished by providing a list of all of the different given product stored in the memory having correlation data associated therewith on the display 18 of the tool. The selection may first require selection between different classes of commodities displayed as a first list including for example cereals, oilseeds, etc., before a second list of commodities is then presented representing a subgrouping of commodities within the selected class. The memory also includes weight data associated with each of the different commodity or product types which represents the desired mass of the sample to be placed into the moisture meter with which the tool is to be used to obtain a proper electrical capacitance representation from the moisture meter which can be used by the processor with the correlation data.
Once the sample weight for testing has been identified to the user on the display 18, the user measures an appropriate sized sample to be placed into the moisture tester and measures the temperature of the sample. The moisture tester measures an electrical capacitance through the sample, resulting in a representation
The central processor is arranged to control various functions and modes of the tool 10 for determining moisture content values as well as other useful information for use with the moisture meter of the prior art. As shown in figure 3, upon initially operating the tool a user first selects a mode of operation between a moisture content determination mode 26 or a test weight determination mode 28.
In the moisture content determination mode 26, the processor queries the operator with the relevant type of commodity or product with which moisture content is to be determined. This is accomplished by providing a list of all of the different given product stored in the memory having correlation data associated therewith on the display 18 of the tool. The selection may first require selection between different classes of commodities displayed as a first list including for example cereals, oilseeds, etc., before a second list of commodities is then presented representing a subgrouping of commodities within the selected class. The memory also includes weight data associated with each of the different commodity or product types which represents the desired mass of the sample to be placed into the moisture meter with which the tool is to be used to obtain a proper electrical capacitance representation from the moisture meter which can be used by the processor with the correlation data.
Once the sample weight for testing has been identified to the user on the display 18, the user measures an appropriate sized sample to be placed into the moisture tester and measures the temperature of the sample. The moisture tester measures an electrical capacitance through the sample, resulting in a representation
9 of the electrical capacitance which is displayed as a dial drum value on the tester. The processor then uses the inputted temperature data, electrical capacitance representation data (or dial drum data) and selection of the given product to determine which correlation data to use and subsequently determine the moisture content using the correlation data.
The determined moisture content is then displayed as a numerical value on the display 18 and the option is given to the operator to store this determined moisture content value in the rewriteable memory 22. When storing in the memory 22, the option is also given for the operator to append additional data with the moisture content value being stored. This additional appended data may comprise a description of the field, its location or a storage location associated with the particular sample of which the moisture content is being determined. Other appended data may include a date of the moisture content determination and the type of product, however some of this additional appended data can be appended automatically rather than requiring additional input by the user.
In the alternative mode of test weight determination 28, the processor again queries the operator for the particular type of product concerned. The processor then queries the operator through the display 18 for a density (in grams per half litre) to be input. The density of the desired sample to be measured of a given product is measured in units of grams per half litre and inputted under these units of measure into the processor using the input keys. The processor then converts this density data, which has been measured, into a plurality of different density values each having different units of measure but expressing an identical density. These various conversions are displayed on the display 18 for the operator to see.
Also displayed is the desired test weight (for some commodities) for a sample to be used in the moisture meter as the read only memory 20 includes multiple different test weights associated with at least some of the plurality of different types of product which are categorized according to different densities of the sample.
Thus the tool will display to the operator the correct test weight to be used which 5 corresponds with the correlation data associated with that particular selected product depending also upon the varying density of the product.
Once the test weight has been displayed following the weight determination mode 28, the operator is given the option of immediately inputting a measured temperature and electrical capacitance representation (represented by a
The determined moisture content is then displayed as a numerical value on the display 18 and the option is given to the operator to store this determined moisture content value in the rewriteable memory 22. When storing in the memory 22, the option is also given for the operator to append additional data with the moisture content value being stored. This additional appended data may comprise a description of the field, its location or a storage location associated with the particular sample of which the moisture content is being determined. Other appended data may include a date of the moisture content determination and the type of product, however some of this additional appended data can be appended automatically rather than requiring additional input by the user.
In the alternative mode of test weight determination 28, the processor again queries the operator for the particular type of product concerned. The processor then queries the operator through the display 18 for a density (in grams per half litre) to be input. The density of the desired sample to be measured of a given product is measured in units of grams per half litre and inputted under these units of measure into the processor using the input keys. The processor then converts this density data, which has been measured, into a plurality of different density values each having different units of measure but expressing an identical density. These various conversions are displayed on the display 18 for the operator to see.
Also displayed is the desired test weight (for some commodities) for a sample to be used in the moisture meter as the read only memory 20 includes multiple different test weights associated with at least some of the plurality of different types of product which are categorized according to different densities of the sample.
Thus the tool will display to the operator the correct test weight to be used which 5 corresponds with the correlation data associated with that particular selected product depending also upon the varying density of the product.
Once the test weight has been displayed following the weight determination mode 28, the operator is given the option of immediately inputting a measured temperature and electrical capacitance representation (represented by a
10 dial drum value) of the sample of proper test weight which has been then placed within the moisture meter associated with the tool 10 of the present invention. The processor is then arranged to follow the remaining steps of the moisture content determination mode 26 to automatically determine the moisture content using the correlation data associated with the already selected one of the plurality of different product types.
The correlation data may comprise a chart of values in which a plurality of different moisture content values each have a respective electrical capacitance representation and temperature associated therewith for a given commodity type. The processor thus determines moisture content by locating on the chart of information the temperature and electrical capacitance representation which most closely match the temperature and electrical capacitance representation inputted into the processor and then the associated moisture content value is determined to be the moisture content of the sample.
Due to the desire to minimize the amount of data stored on the read only memory, only a limited number of temperature and electrical capacitance
The correlation data may comprise a chart of values in which a plurality of different moisture content values each have a respective electrical capacitance representation and temperature associated therewith for a given commodity type. The processor thus determines moisture content by locating on the chart of information the temperature and electrical capacitance representation which most closely match the temperature and electrical capacitance representation inputted into the processor and then the associated moisture content value is determined to be the moisture content of the sample.
Due to the desire to minimize the amount of data stored on the read only memory, only a limited number of temperature and electrical capacitance
11 representation values are stored along with their respective moisture content values so that in most instances when the processor searches for similar temperature or electrical capacitance representation data for a particular selected type of product, the processor will either average the moisture content values of the two closest sets of data of related temperature and electrical capacitance values or if outside of the range of the charted information the processor will automatically extrapolate a moisture content value using averaging and extrapolating algorithms beyond the range of temperature and electrical capacitance representations (dial drum values) stored in the memory, thus extending the measuring range of the moisture tester.
Some or all of the correlation data can instead be in the form of an arithmetic formula which has been determined by experimentation to represent moisture content as a function of temperature of the sample, the measured electrical capacitance representation (or dial drum value) of the sample using the moisture tester and the selection as to the type of product being measured. Use of a formulaic representation of the correlation data greatly saves space on the read only memory of the tool.
In some instances, correlation data for some of the different types of product maybe stored in chart form whereas other types of correlation data are stored in the form of regression formulas which represent moisture content of a selected type of product as a function of the charted data associated with a different one of the various product types stored in memory. Samples of formulas for certain types of selected product are shown in the following table as a function of charted information of a different product.
Some or all of the correlation data can instead be in the form of an arithmetic formula which has been determined by experimentation to represent moisture content as a function of temperature of the sample, the measured electrical capacitance representation (or dial drum value) of the sample using the moisture tester and the selection as to the type of product being measured. Use of a formulaic representation of the correlation data greatly saves space on the read only memory of the tool.
In some instances, correlation data for some of the different types of product maybe stored in chart form whereas other types of correlation data are stored in the form of regression formulas which represent moisture content of a selected type of product as a function of the charted data associated with a different one of the various product types stored in memory. Samples of formulas for certain types of selected product are shown in the following table as a function of charted information of a different product.
12 Crop Procedure Use the CGC Cranberry Bean Chart #2 with a 2501 Azuki Beans gram sample and subtract 2.5% moisture from the ichart result.
I Use the CGC Pea Bean Chart #2 and subtract 1.1%
Dutch Brown Beans t moisture from the chart result.
Eastern White Use the CGC Dark Red Kidney Beans Chart #2 aid Kidney Beans add 0.5 to the result.
Great Northern I
Use the CGC Pea Bean Chart #2 and subtract 1.4%
White Beans moisture from the chart result.
1 ________________________________________________________________ I Use the CGC Dark Red Kidney Bean Chart #2 and Kintoki Beans I read the results directly.
Light Red Kidney I Use the CGC Dark Red Kidney Beans Chart #2 and Beans read the results directly.
4 n IUse the CGC Pea Bean Chart #2 and subtract 0.A5/0 lOtebo Beans from the chart result.
Use the CGC Pea Bean Chart #2 and subtract 1.1%
1Pin k Beans imoisture from the chart result.
Use the regression formula:
=
% moisture = 0.155 X meter reading + 8.03 + {OA X
1Small Red Beans (22 T)}
sample temperature (C) Sample Size -- 250 grams 15 Use the conversion table and the tough and damp ' Mixed Grain limits of the predominant grain.
The rewriteable memory 22 preferably includes first and second storage locations which are recognized separately by the processor. This permits correlation 20 data from a first portion of the different types of product to be stored in the first location while a remaining or second portion of the correlation data associated with a second portion of the given product are storable in the second location.
Preferably only a small minority of the overall number of products stored are stored in the first location so that the products stored in the first location can be represented as a short 25 list of favourites or more frequently used with commodities which are more readily accessible to the user by being provided as a shorter list of selection to be made.
I Use the CGC Pea Bean Chart #2 and subtract 1.1%
Dutch Brown Beans t moisture from the chart result.
Eastern White Use the CGC Dark Red Kidney Beans Chart #2 aid Kidney Beans add 0.5 to the result.
Great Northern I
Use the CGC Pea Bean Chart #2 and subtract 1.4%
White Beans moisture from the chart result.
1 ________________________________________________________________ I Use the CGC Dark Red Kidney Bean Chart #2 and Kintoki Beans I read the results directly.
Light Red Kidney I Use the CGC Dark Red Kidney Beans Chart #2 and Beans read the results directly.
4 n IUse the CGC Pea Bean Chart #2 and subtract 0.A5/0 lOtebo Beans from the chart result.
Use the CGC Pea Bean Chart #2 and subtract 1.1%
1Pin k Beans imoisture from the chart result.
Use the regression formula:
=
% moisture = 0.155 X meter reading + 8.03 + {OA X
1Small Red Beans (22 T)}
sample temperature (C) Sample Size -- 250 grams 15 Use the conversion table and the tough and damp ' Mixed Grain limits of the predominant grain.
The rewriteable memory 22 preferably includes first and second storage locations which are recognized separately by the processor. This permits correlation 20 data from a first portion of the different types of product to be stored in the first location while a remaining or second portion of the correlation data associated with a second portion of the given product are storable in the second location.
Preferably only a small minority of the overall number of products stored are stored in the first location so that the products stored in the first location can be represented as a short 25 list of favourites or more frequently used with commodities which are more readily accessible to the user by being provided as a shorter list of selection to be made.
13 Less frequently selected commodities can then be stored in the second portion in a much longer list presented to the operator.
The unit will consist of a membrane type keypad for data input and a graphical liquid crystal display (LCD) to present results to the producer.
These components will be housed in an electronic box likely made of some type of ABS
plastic. It will run using a 9 volt battery that will be accessible from the outside of the box.
The producer's first choice will be moisture testing or determination of test weight. If moisture testing, then the commodity will be chosen next followed by inputting the value of the temperature of the sample and the dial drum value from the Model 919 moisture tester. The percent moisture will then be displayed for the producer. If they chose test weight determination then they will choose their commodity and input the number of grams per half litre. This value will then be translated into the pounds per bushel (Canadian), pounds per bushel (United States) and kilograms per hectalitre. These values will then be displayed for the producer to see.
A partial list of commodities to be included in the device to start with are shown in the following table, along with data comprising their associated test sample weights or amounts.
The unit will consist of a membrane type keypad for data input and a graphical liquid crystal display (LCD) to present results to the producer.
These components will be housed in an electronic box likely made of some type of ABS
plastic. It will run using a 9 volt battery that will be accessible from the outside of the box.
The producer's first choice will be moisture testing or determination of test weight. If moisture testing, then the commodity will be chosen next followed by inputting the value of the temperature of the sample and the dial drum value from the Model 919 moisture tester. The percent moisture will then be displayed for the producer. If they chose test weight determination then they will choose their commodity and input the number of grams per half litre. This value will then be translated into the pounds per bushel (Canadian), pounds per bushel (United States) and kilograms per hectalitre. These values will then be displayed for the producer to see.
A partial list of commodities to be included in the device to start with are shown in the following table, along with data comprising their associated test sample weights or amounts.
14 , Class of Grain Weight (grams) Date and table no.
i' Amber durum wheat 250 1990-08,4 i !Barley, 52 kg/hL & over 225 2000-07, 13 !Barley, Lt. Wt, < 52kg/hL 200 1979-rev., 10 1Black beans 250 1977-02, 1 1Brown mustard 250 , 1990-08,8 'Buckwheat 225_ 1978-04,3 !Ganda and rapeseed 250_ 1991-08,5 ;Chick peas 250 1998-07, 1 Corn, low moisture 1250 2000-07, 6 !Corn, high moisture 175 2000-07, 11A
;Corn, test weight correction 175 2002-07, 118 !Canada prairie spring wheat, red and white 250 1990-08, 1 , Cranberry beans 225 2006-07, 2 i , Dark red kidney beans 250 2006-07, 2 !Eastern red wheat 250 1990-07, 1 lEastern red spring wheat 250 2000-07, 1 =
!Eastern hard red winter wheat 250 2000-07, 1 !Eastern soft red winter wheat 250 2000-07, 1 1Eastern white winter wheat 250 2002-07,5 'Extra strong red spring 250 2002-08, 2 1-Fababeans 250 1977-02, 2 Flaxseed and milli 225 1998-07,6 Hard white, spring wheat 250 2005-08, 1 Hulless barley 225 1994-08, 1 Lentils 250 1979-08, 1 i Oats 200 2001-08, 6 _, ____________________________________________ 1Oats, Lt. Wt, < 48kg/hL 140 12003-08, 1 !Oriental mustard 250 1990-07,7 r Pea beans 250 1977-02,2 .
_ _____________________________________________ 1Peas, green & yellow 250 1977-02,2 1Pinto beans 250 1999-07, 1 i Red spring wheat, 66 kg/hL &over 250 1999-08, 10 ; Red spring wheat, <66 kg/hL 225 1979-08, 9 1i Rye 250 1977-08,5 'Safflower seed, calibrate at 73 150 1992-08, 1 1Soft white spring wheat 250 1895-08, 3 1Soybean - 225 2005-07,8 1 _ __________ . Split peas, green & yellow I- 250 1996-07, 1 ' Sunflower seed, calibrate at 73 150 1978-10, 3 r7Triticale 250 1981-08, 1 1Westem winter wheat 250 2002-08, 5 'Yellow mustard 250 1990-08, 6 1Canary Seed - Canary Seed is not a grain under the authority of the Canada Grain Act.
i Nonetheless, to support the marketing of this seed, the Grain Research Laboratory has [developed a conversion table, dated September 1991. Use this table to test a 250 gram I sample.
71-en7;ileed - Hemp seed is not a grain under the authority of the Canada Grain Act.
I Nonetheless, to support the marketing of this seed, the Grain Research Laboratory has I developed a conversion table. Feb. 99, 176 grams, calibrate at 73.
Test weight conversion charts will include the following commodities:
Amber Durum Wheat, Barley, Buckwheat, Corn, Flaxseed, Oats, Rye, Solin, Soybean, Sunflower Seed (Confectionery), Sunflower Seed (Oil), and Wheat.
Since various modifications can be made in my invention as herein above described, and many apparently widely different embodiments of same made, it is intended that all matter contained in the accompanying specification shall be interpreted as illustrative only and not in a limiting sense.
i' Amber durum wheat 250 1990-08,4 i !Barley, 52 kg/hL & over 225 2000-07, 13 !Barley, Lt. Wt, < 52kg/hL 200 1979-rev., 10 1Black beans 250 1977-02, 1 1Brown mustard 250 , 1990-08,8 'Buckwheat 225_ 1978-04,3 !Ganda and rapeseed 250_ 1991-08,5 ;Chick peas 250 1998-07, 1 Corn, low moisture 1250 2000-07, 6 !Corn, high moisture 175 2000-07, 11A
;Corn, test weight correction 175 2002-07, 118 !Canada prairie spring wheat, red and white 250 1990-08, 1 , Cranberry beans 225 2006-07, 2 i , Dark red kidney beans 250 2006-07, 2 !Eastern red wheat 250 1990-07, 1 lEastern red spring wheat 250 2000-07, 1 =
!Eastern hard red winter wheat 250 2000-07, 1 !Eastern soft red winter wheat 250 2000-07, 1 1Eastern white winter wheat 250 2002-07,5 'Extra strong red spring 250 2002-08, 2 1-Fababeans 250 1977-02, 2 Flaxseed and milli 225 1998-07,6 Hard white, spring wheat 250 2005-08, 1 Hulless barley 225 1994-08, 1 Lentils 250 1979-08, 1 i Oats 200 2001-08, 6 _, ____________________________________________ 1Oats, Lt. Wt, < 48kg/hL 140 12003-08, 1 !Oriental mustard 250 1990-07,7 r Pea beans 250 1977-02,2 .
_ _____________________________________________ 1Peas, green & yellow 250 1977-02,2 1Pinto beans 250 1999-07, 1 i Red spring wheat, 66 kg/hL &over 250 1999-08, 10 ; Red spring wheat, <66 kg/hL 225 1979-08, 9 1i Rye 250 1977-08,5 'Safflower seed, calibrate at 73 150 1992-08, 1 1Soft white spring wheat 250 1895-08, 3 1Soybean - 225 2005-07,8 1 _ __________ . Split peas, green & yellow I- 250 1996-07, 1 ' Sunflower seed, calibrate at 73 150 1978-10, 3 r7Triticale 250 1981-08, 1 1Westem winter wheat 250 2002-08, 5 'Yellow mustard 250 1990-08, 6 1Canary Seed - Canary Seed is not a grain under the authority of the Canada Grain Act.
i Nonetheless, to support the marketing of this seed, the Grain Research Laboratory has [developed a conversion table, dated September 1991. Use this table to test a 250 gram I sample.
71-en7;ileed - Hemp seed is not a grain under the authority of the Canada Grain Act.
I Nonetheless, to support the marketing of this seed, the Grain Research Laboratory has I developed a conversion table. Feb. 99, 176 grams, calibrate at 73.
Test weight conversion charts will include the following commodities:
Amber Durum Wheat, Barley, Buckwheat, Corn, Flaxseed, Oats, Rye, Solin, Soybean, Sunflower Seed (Confectionery), Sunflower Seed (Oil), and Wheat.
Since various modifications can be made in my invention as herein above described, and many apparently widely different embodiments of same made, it is intended that all matter contained in the accompanying specification shall be interpreted as illustrative only and not in a limiting sense.
Claims (17)
1. A moisture data conversion apparatus for use with a meter, the meter being arranged to determine an electrical capacitance representation of a sample of a given product, the apparatus comprising:
a portable housing independent of the meter;
a data input supported on the housing including a numeric keypad for manually inputting electrical capacitance representation data of the sample obtained from the meter and for manually inputting temperature data of the sample;
a memory supported on the housing having correlation data stored thereon which correlates electrical capacitance representation data and temperature data to moisture content of the given product;
a processor supported on the housing for determining moisture content of the sample using the electrical capacitance representation data, the temperature data, and the correlation data;
a display supported on the housing for displaying the moisture content of the sample as determined by the processor; and a power source for supplying electrical power to the processor and the display.
a portable housing independent of the meter;
a data input supported on the housing including a numeric keypad for manually inputting electrical capacitance representation data of the sample obtained from the meter and for manually inputting temperature data of the sample;
a memory supported on the housing having correlation data stored thereon which correlates electrical capacitance representation data and temperature data to moisture content of the given product;
a processor supported on the housing for determining moisture content of the sample using the electrical capacitance representation data, the temperature data, and the correlation data;
a display supported on the housing for displaying the moisture content of the sample as determined by the processor; and a power source for supplying electrical power to the processor and the display.
2. The apparatus according to Claim 1 wherein the memory stores correlation data therein associated with a plurality of different given products, and the data input is arranged for receiving product selection data, the processor being arranged to determine moisture content of the sample using the electrical capacitance representation data, the temperature data, the product selection data and the correlation data associated with a selected one of the given products as determined by the product selection data.
3. The apparatus according to Claim 2 wherein the memory includes test weight data indicating test weight of the sample for use with the meter for at least some of the given products, the display being arranged for displaying the test weight data responsive to determination of the selected one of the products.
4. The apparatus according to Claim 1 wherein at least some of the correlation data comprises a formula representing moisture content as a function of electrical capacitance and temperature of a sample of the given product.
5. The apparatus according to Claim 4 wherein the memory stores correlation data associated with a plurality of different given products and wherein the correlation data comprises different formulas associated with the different given products respectively.
6. The apparatus according to Claim 1 wherein at least some of the correlation data comprises a plurality of different moisture content values, each with a respective electrical capacitance representation and temperature associated therewith, and wherein the processor is arranged to determine moisture content by determining which moisture content value is associated with the input electrical capacitance representation data and temperature data of the sample.
7. The apparatus according to Claim 6 wherein some of the correlation data comprises a formula representing moisture content as a function of moisture content values associated with a different one of a plurality of given products.
8. The apparatus according to Claim 6 wherein the processor is arranged to extrapolate moisture content from moisture content values stored in the memory when the electrical capacitance representation data and the temperature data fall outside of a range of electrical capacitance representation and temperature values associated with the respective moisture content values stored in the memory.
9. The apparatus according to Claim 1 wherein the processor is operable in both: i) a moisture content determination mode in which the processor determines moisture content of the sample using the electrical capacitance representation data, the temperature data and the correlation data, and ii) a weight determination mode in which the processor is arranged to display one of a test weight or a conversion of density units responsive to a measured density input into the data input.
10. The apparatus according to Claim 9 wherein the memory includes weight data for a sample of the given product to be tested associated with a plurality of different given products and wherein the processor is arranged to determine the weight data responsive to a selection of one the given products and a measured density of the sample being received by the data input.
11. The apparatus according to Claim 9 wherein the processor is arranged to convert density data which is input into the data input into a plurality of density values each having different units of measurement, the density values being displayed on the display.
12. The apparatus according to Claim 1 wherein the memory comprises a rewritable memory arranged to store determined moisture content for a plurality of different samples and subsequently recall the moisture content of the plurality of different samples.
13. The apparatus according to Claim 12 wherein the memory is arranged to store appended data with each moisture content.
14. The apparatus according to Claim 13 wherein the appended data includes data relating to field conditions or location with which the sample is associated.
15. The apparatus according to Claim 13 wherein the appended data includes an identification of the given product.
16. The apparatus according to Claim 13 wherein the appended data includes a date of moisture content determination by the processor.
17. The apparatus according to Claim 1 wherein the memory stores correlation data therein associated with a plurality of different given products and wherein the memory includes a first location storing correlation data of a first portion of the given products and a second location storing correlation data associated with a second portion of the given products, the first location of the memory being more readily accessible using the data input than the second location.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA2567587A CA2567587C (en) | 2006-10-24 | 2006-10-24 | Crop moisture data conversion tool |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CA2567587A CA2567587C (en) | 2006-10-24 | 2006-10-24 | Crop moisture data conversion tool |
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| Publication Number | Publication Date |
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| CA2567587A1 CA2567587A1 (en) | 2008-04-24 |
| CA2567587C true CA2567587C (en) | 2016-06-28 |
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| CA2567587A Expired - Fee Related CA2567587C (en) | 2006-10-24 | 2006-10-24 | Crop moisture data conversion tool |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| RU2652144C1 (en) * | 2017-02-20 | 2018-04-25 | Николай Евгеньевич Староверов | Soil moisture meter |
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2006
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