Abstract:
Presented herein is a method for predicting suitable times for performing a crop harvesting operation within a field. The method includes the steps of accessing predicted values for weather, crop, and soil conditions, and then predicting values for one or more additional operation variables indicating operation suitability. The method then predicts suitability for performance of the crop harvesting operation based on the predicted operation variables and selected suitability parameters.

Description:
FIELD OF THE INVENTION  
       [0001]     The present invention relates to the prediction of crop conditions and assessment of suitability for performance of a crop harvesting operation.  
       BACKGROUND OF THE INVENTION  
       [0002]     Land engaged in agriculture is subjected to a number of crop harvesting operations. In order to optimize performance of these operations for efficiency, minimal crop loss, and/or minimal impact on the soil, it is critical that harvest operations be performed when crop, weather, and soil conditions are suitable. In order to aid in planning, a method of predicting suitable times for performing a number of different crop harvesting operations is desirable.  
       SUMMARY OF THE INVENTION  
       [0003]     Presented herein is a method for predicting suitable times for performing a crop harvesting operation. The method includes the steps of accessing predicted values for weather, crop, and soil conditions, and then predicting one or more values for soil characteristics, operation characteristics, and operation effects. Based on these predicted operation variables and selected suitability parameters, the method predicts harvest operation suitability for different points in time. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0004]      FIG. 1  illustrates a farm field having many field nodes.  
         [0005]      FIG. 2  illustrates a first embodiment for the present invention method.  
         [0006]      FIG. 3  illustrates a second embodiment for the present invention method.  
         [0007]      FIG. 4  illustrates a table displaying suitability values for performance of a crop harvesting operation at a single field node on a single day.  
         [0008]      FIG. 5  illustrates a map displaying suitability values for performance of a crop harvesting operation over a single field on a single day.  
         [0009]      FIG. 6  illustrates a graphical displaying suitability values for performance of a crop harvesting operation over a single field for multiple days.  
         [0010]      FIG. 7  illustrates a graphical displaying suitability values for performance of a crop harvesting operation over multiple fields on a single day. 
     
    
     DETAILED DESCRIPTION  
       [0011]      FIG. 1  illustrates a parcel of land, or field  10 , suitable for agricultural use, and under agricultural cultivation. As such, the field  10  may be subjected to crop harvesting operations such as mechanized mowing and combining, as well as human handpicking and animal foraging. Numerous field nodes  12  dispersed throughout field  10  divide the parcel into smaller sample areas. A method presented herein predicts suitability  6  for performing such operations in the field  10  at different points in time, based on operation variables  8  predicted for each field node  12 .  
         [0012]      FIG. 2  illustrates a first embodiment  20  of the present invention whereby the method predicts operation variables  8  indicative of operation performance suitability  6  at field node  12 . The first step  22  in this embodiment  20  is to access values predicted for weather conditions  24  at the node  12 . These predicted weather conditions  24  include values for, but are not limited to, temperature, relative humidity, wind speed, precipitation, and solar radiation. Values for these conditions  24  can be obtained from sources such as the National Weather Service website, operated by the National Oceanic and Atmospheric Administration.  
         [0013]     The second step  102  in this embodiment  20  is to access values predicted for crop conditions  104  at the node  12  at different points in time. These crop conditions  104  include, but are not limited to, crop maturity level and crop moisture content. The third step  26  in this embodiment  20  is to access values predicted for soil conditions  28  at the node  12  at different points in time. These soil conditions  28  include, but are not limited to, soil moisture and soil temperature. To predict values for both crop conditions  104 , and soil conditions  28 , the method may use a dynamic soil model, such as the Precision Agricultural-Landscape Modeling System (PALMS) developed under NASA&#39;s Regional Earth Science Application Center (RESACA) program. This program predicts crop maturity and moisture, and soil moisture and temperature, as well as other variables, based on predicted weather conditions, measured soil conditions, and crop season parameters. This computer program is available under license for research or commercial use through the Wisconsin Alumni Research Foundation.  
         [0014]     The fourth step  30  in this embodiment  20  is to select a soil profile  32  representative of the field node  12 . A soil profile  32  describes a particular soil for which empirical tests have been conducted for this method  20 . A soil profile  32  includes information such as soil type and composition, down to several feet. The fifth step  34  is to select an operation profile  36  representative of the crop harvesting operation to be performed. An operation profile  36  describes a particular operation for which empirical tests have been conducted for this method  20 . Operation profiles  36  include parameters such as operation type, equipment size, machine configuration, and operation speed. The operation profile  36  might also include additional parameters such as crop species and fuel price.  
         [0015]     The sixth step  38  in this embodiment  20  is to predict operation characteristics  40  that are resultant upon performance of the operation under the predicted soil conditions  28 . Operation characteristics  40  are generally indicative of operation suitability  6 , and include, but are not limited to, soil compaction impact (A compaction), soil particle size, tractive efficiency, and fuel consumption. In the illustrated embodiment  20 , these operation characteristics  40  are determined by referring to empirical tables  42  giving values for known soil conditions  28 , soil profile  32 , and operation profile  36 . For example, a table  42  giving values for A compaction may be developed by performing the crop harvesting operation under a number of soil moisture conditions on a test plot having a consistent soil composition. The parameters of the harvesting operation performed define the operation profile  36 , and the composition of the test plot soil defines the soil profile  32 .  
         [0016]     The seventh step  44  in this embodiment  20  is to predict operation effects  46  that are resultant upon performance of the operation, given the predicted operation characteristics  40 . Operation effects  46  are also indicative of operation suitability  6 , and include, but are not limited to, crop yield impact and fuel cost. In the illustrated embodiment  20 , these effects  46  are determined by referring to empirical tables  48  giving values for known operation characteristics  40 , soil profile  32 , and operation profile  36 . For example, a table  48  giving values for crop yield impact may be developed by measuring crop yields under a number of soil compaction levels on a test plot having a consistent soil composition. Examples outlining the development of such tables  48  may be found in  Soybean Growth and Yield as Affected by Subsurface and Subsoil Compaction , J. F. Johnson, et al., Agronomy Journal, Vol. 82, No.  5 , September-October 1990.  
         [0017]      FIG. 3  illustrates a second embodiment  21  of the present invention whereby the method predicts operation variables  8  indicative of operation performance suitability  6  at a node  12  within the field  10 . The first step  22 ′ in this embodiment  21  is to access values predicted for weather conditions  24  at the node  12 , like the first embodiment  20 . The second step  102 ′ in this embodiment  21  is to access values predicted for crop conditions  104  at the node  12  at different points in time, as in the first embodiment  20 . The third step  26 ′ in second embodiment  21  is to access values predicted for soil conditions  28  at the node  12  at different points in time, like the first embodiment  20 . The fourth step  30 ′ in this embodiment  21  is to select a soil profile  32  representative of the field node  12 , like the first embodiment  20 .  
         [0018]     The fifth step  50  in this embodiment  21  is to predict values for soil characteristics  52  for a soil under known soil conditions  28 . The soil characteristic  52  of particular interest in this embodiment is Atterberg Limits. These soil characteristics  52  are determined in the illustrated embodiment  21  by referring to empirical tables  54  giving values for known soil conditions  28  and soil profile  32 . These tables  54  may be generated by performing tests under a number of soil moisture conditions on specimens of soil profiles  32  according to  ASTM D  4318-00 : Standard Test Method for Liquid Limit, Plastic Limit, and Plasticity index of Soils.    
         [0019]     The sixth step  34 ′ in this embodiment  21  is to select an operation profile  36  representative of the crop harvesting operation. The seventh step  38 ′ in this embodiment  21  is to predict operation characteristics  40  that are resultant upon performance of the operation, given the predicted soil characteristics  52 . In the illustrated embodiment  21 , these operation characteristics  40  are determined by referring to empirical tables  56  giving values for known soil characteristics  52 , soil profile  32 , and operation profile  36 . For example, a table  56  giving tractive efficiency and fuel consumption may be developed empirically by performing the crop harvesting operation under a number of Atterberg Limit conditions.  
         [0020]     The eighth step  44 ′ in this embodiment  21  is to predict operation effects  46  that are resultant upon performance of the operation, given the predicted operation characteristics  40 , in the same manner as the first embodiment  20 . Alternatively, the method in this embodiment  21  may determine these operation effects  46  by calculating values based on predicted operation characteristics  40  and operation profile  36 . For example, multiplying fuel consumption, an operation characteristic  40 , by fuel price, an operation profile  36  parameter, predicts fuel cost for the operation.  
         [0021]     The final step  60  of both the first embodiment  20  and second embodiment  21  is to predict operation suitability  6  at the node  12  for several points in time based on the predicted values for the operation variables  8 . For clarity, the operation variables  8  include weather conditions  24 , crop conditions  104 , soil conditions  28 , soil characteristics  52 , operation characteristics  40 , and operation effects  46 .  FIG. 4  illustrates a table  62  showing input and output for a harvest operation suitability algorithm  64 . By selecting suitability parameters  65 , the suitability algorithm  64  calculates suitability values for each operation variable  6  based on the corresponding suitability parameters  66 . These parameters  66  define thresholds at which the operation variable is suitable  68  for the crop harvesting operation, and thresholds beyond which the variable is unsuitable  70 .  
         [0022]     For example, if a value for an operation variable  8  at a given point in time falls within the suitable value thresholds  68 , then the suitability value  6 ′ for that operation variable  8  is 100%. Conversely, if the value for the variable  8  falls outside of the unsuitable value thresholds  70 , then the suitability value  6 ′ for that operation variable  8  is 0%. Finally, if the value for the operation variable  8  falls within the transition range between suitable and unsuitable thresholds, then the suitability value  6 ′ for that operation variable  8  is the fraction between the suitable threshold value  68  and unsuitable threshold value  70 .  FIG. 4  illustrates an example, with suitability parameters  66  for crop moisture having a suitable upper threshold value of 24%, and an unsuitable upper threshold value of 28%. Thus, for the predicted crop moisture I content of 26%, the suitability value  6 ′ for crop moisture content calculates as ((26−24)/(28−14))×100=50%.  
         [0023]     As illustrated, the suitability  66  parameters also include weightings  72  emphasizing relative importance of the operation variables  8  in assessing overall operation suitability  6  for the node  12 . The suitability algorithm  64  calculates overall suitability  6  by multiplying each operation variable suitability value  6 ′ by its corresponding weighting  72  for a weighted suitability value, then dividing the sum of the weighted suitability values by the sum of the weighting values  72 .  FIG. 4  illustrates an example of overall node suitability  6  for performance of a crop harvesting operation, based on predicted weather conditions  24 , crop conditions  104 , and operation characteristics  40 .  
         [0024]     Values for operation variables  8 , operation variable suitability  6 ′, and overall node suitability  6  generated from the foregoing method are available for display  80  in numerous forms.  FIG. 5  shows an example of a map display  80  showing overall node suitability  6  for a crop harvesting operation over an entire farm field  10  on a single day. This figure also shows a summary of operation suitability  6  over the entire field  10  in a bar graph  82  at the bottom of the illustration.  FIG. 6  shows a similar bar graph display  84  showing overall node suitability  6 , but for multiple days in the farm field  10 . This display  84  is especially useful when planning the best day for performance of a crop harvesting operation. Finally,  FIG. 7  illustrates a bar graph display  86  showing overall node suitability  6  for multiple farm fields  10  on a single day. This display  86  is especially useful in selecting alternative fields  10  in which to perform the operation on a given day. It is of interest to note that a field  10  may never be suitable for performance of a particular type of soil engaging operation, given the predicted weather conditions  24 , crop conditions  104 , and soil conditions  28 . Thus, this method becomes useful to assess economic impact of harvest operation timing, irrespective of suitability.  
         [0025]     Having described the illustrated embodiments, it will become apparent that various modifications can be made without departing from the scope of the invention as defined in the accompanying claims.  
       Assignment  
       [0026]     The entire right, title and interest in and to this application and all subject matter disclosed and/or claimed therein, including any and all divisions, continuations, reissues, etc., thereof are, effective as of the date of execution of this application, assigned, transferred, sold and set over by the applicant(s) named herein to Deere &amp; Company, a Delaware corporation having offices at Moline, Ill. 61265, U.S.A., together with all rights to file, and to claim priorities in connection with, corresponding patent applications in any and all foreign countries in the name of Deere &amp; Company or otherwise.