Method and system for spatial evaluation of field and crop performance

• US 6,505,146 B1
• Filed: 09/24/1999
• Issued: 01/07/2003
• Est. Priority Date: 09/24/1999
• Status: Expired due to Term

• Current Assignee: Monsanto Technology LLC (Bayer AG)
• Original Assignee: Monsanto Company (Bayer AG)
• Inventors: Blackmer, Tracy M.
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Charioui, Mohamed
• Application Number:
  US09/404,978
• Time in Patent Office: 1,201 Days
• Field of Search: 702/189, 702/35, 702/36, 702/5, 701/213, 701/214, 701/215, 701/50, 701/51, 700/89, 700/86, 340/989, 340/990, 340/991, 340/992, 340/993
• US Class Current: 702/189
• CPC Class Codes: A01B 79/005 Precision agriculture

Abstract

The invention provides a method for analyzing spatial variations in field and crop performance. The method allows analysis of the field and crop performance as a function of various treatment and/or environmental conditions. This method is an advance over the prior art in that it allows better defined, more accurate comparisons of adjacent test areas, eliminating the need for extrapolation of data and avoiding inaccuracies therefrom. Also, the more accurate comparisons allow better characterization of effects due to the environment, such as those caused by genotype by environment (G×E) interaction. The more accurately defined comparison units also lead to improved analysis when comparing to other data layers for non-spatial analysis. The invention also provides a system for carrying out this method. The system preferably includes a device for inputting spatially-referenced data, a memory, an output device, and a processor. The output data may be represented spatially or non-spatially. The information provided by the method and system of the invention will allow farmers to make more informed decisions regarding seed and farming inputs and practices, thereby maximizing agricultural productivity.

Claims

1. A method of determining a difference in the value of a first spatially-variable field characteristic, said method comprising the steps of:

a) preparing a field, wherein said field comprises a first and a second crop test area;

b) obtaining spatially-referenced field characteristic data for a designated region of said field, wherein said region comprises said first and said second crop test areas;

c) designating said spatially-referenced field characteristic data to said first or said second crop test area;

d) defining cells in said first and said second crop test areas, wherein said defining comprises designating length units within said first and said second crop test areas; and

e) comparing said field characteristic data for a first cell from said first crop test area to an adjacent first cell from said second crop test area to identify a difference in the value of said field characteristic data.

2. The method of claim 1, wherein said first and said second crop test areas differ in the genotype of seed planted.

3. The method of claim 2, wherein said first and said second crop test areas comprise seed of the same species but of different varieties.

4. The method of claim 3, wherein said species is selected from the group consisting of wheat, maize, rye, rice, oat, barley, turfgrass, sorghum, sugarcane, millet, tobacco, tomato, potato, soybean, cotton, canola, alfalfa, sunflower, sugarbeets, peanuts, broccoli, carrots, peppers, raspberry, banana, apple, pear, peach, forage grass and hay.

5. The method of claim 4, wherein the species is maize and said first and second crop test areas are planted with different hybrid varieties of said maize.

6. The method of claim 4, wherein the species is soybean.

7. The method of claim 3, wherein said varieties differ in a single locus.

8. The method of claim 3, wherein said varieties differ in at least 2 loci.

9. The method of claim 3, wherein said varieties are hybrid varieties.

10. The method of claim 3, wherein said varieties are inbred varieties.

11. The method of claim 1, further comprising creating a visual representation of said difference.

12. The method of claim 11, wherein said difference is displayed using symbols, wherein said symbols correspond to the magnitude of said difference in said field characteristic data.

13. The method of claim 12, wherein said difference is displayed alphanumerically.

14. The method of claim 11, wherein said difference is displayed using colors corresponding to the magnitude of said difference in said field characteristic data.

15. The method of claim 11, wherein said creating a visual representation comprises creating a graph.

16. The method of claim 11, wherein said visual representation is spatially oriented relative to said designated region of said field.

17. The method of claim 11, wherein said visual representation is non-spatially oriented relative to said designated region of said field.

18. The method of claim 11, wherein said step of obtaining spatially-referenced field characteristic data comprises measuring crop yield.

19. The method of claim 1, wherein said step of obtaining spatially-referenced field characteristic data comprises measuring a crop performance variable.

20. The method of claim 19, wherein said crop performance variable comprises grain moisture.

21. The method of claim 19, wherein crop performance variable comprises protein content.

22. The method of claim 19, wherein said crop performance variable comprises oil content.

23. The method of claim 19, wherein said crop performance variable comprises starch content.

24. The method of claim 19, wherein said crop performance variable comprises plant stand.

25. The method of claim 19, wherein said crop performance variable is selected from the group consisting of plant height, stalk thickness and canopy density.

26. The method of claim 1, wherein said step of obtaining spatially-referenced field characteristic data for a designated region of said field comprises obtaining data for an environmental condition variable and for a crop performance variable.

27. The method of claim 26, comprising the step of calculating a correlation between said environmental condition variable and said crop performance variable.

28. The method of claim 27, wherein said correlation is determined by regressing said environmental condition variable relative to said crop performance variable.

29. The method of claim 26, wherein said environmental condition variable is selected from the group consisting of soil pH, soil moisture, soil fertility, soil type, soil compaction, disease infestation and pest infestation.

30. The method of claim 27, wherein said pest infestation is insect infestation.

31. The method of claim 27, wherein said pest infestation is nematode infestation.

32. The method of claim 1, wherein said spatially-referenced field characteristic data comprises an environmental condition variable.

33. The method of claim 32, wherein said environmental condition variable is selected from the group consisting of soil pH, soil moisture, soil fertility, soil type, soil compaction, disease infestation and pest infestation.

34. The method of claim 33, wherein said pest infestation is insect infestation.

35. The method of claim 33, wherein said pest infestation is nematode infestation.

36. The method of claim 1, wherein said field further comprises a third crop test area.

37. The method of claim 36, wherein said field further comprises a fourth crop test area.

38. The method of claim 37, wherein said field further comprises a fifth crop test area.

39. The method of claim 38 wherein said field further comprises from about 6 to about 30 crop test areas.

40. The method of claim 1, wherein said first and said second crop test areas differ in the method of cultivation.

41. The method of claim 40, wherein said method of cultivation comprises application of plant nutrient factors or soil amendments.

42. The method of claim 40, wherein said method of cultivation comprises application of insecticide.

43. The method of claim 40, wherein said method of cultivation comprises application of herbicide.

44. The method of claim 1, further comprising calculating an average of said spatially-referenced field characteristic data for said cells.

45. The method of claim 44, wherein an outlier cell is identified by comparison to said average and said outlier cell is not compared to an adjacent cell.

46. The method of claim 45, wherein said comparison to the average is made based on the standard of deviation or number of data points of said outlier cell relative to said average.

47. The method of claim 1, wherein said step obtaining spatially-referenced field characteristic data comprises using a yield monitor linked to a georeferencing means.

48. The method of claim 47, wherein said georeferencing means comprises GPS.

49. The method of claim 1, wherein said step of comparing comprises calculating a quantitative difference in said field characteristic data between said first cell and said adjacent first cell.

50. The method of claim 49, wherein said calculating comprises subtracting the value of said field characteristic data for said first cell from the value of said field characteristic data for said adjacent first cell.

51. The method of claim 1, wherein said step obtaining spatially-referenced field characteristic data comprises using remote sensing.

52. The method of claim 1, wherein said step obtaining spatially-referenced field characteristic data comprises using precision agricultural techniques.

53. The method of claim 1, wherein said designating comprises assigning a pass of a combine to said first or said second crop test region.

54. A system for determining a difference in a first spatially-variable field characteristic, comprising:

a) a first input device for receiving spatially-referenced field characteristic data;

b) a second input device for receiving user commands;

c) a processor unit communicating with said first and said second input device to designate said field characteristic data to a first crop test area or a second crop test area according to said user commands, to define cells from said first crop test area or said second crop test area based on the user commands, and to calculate a difference between a first cell from said first crop test area and an adjacent first cell from said second crop test area; and

d) an output device for displaying said difference.

55. The system of claim 54, wherein said first input device is selected from the group consisting of a keyboard, an optical or magnetic disk drive, a touch screen, a voice activated input device and a modem.

56. The system of claim 55, wherein s aid first input device is an optical or magnetic disk drive.

57. The system of claim 54, wherein said second input device is selected from the group consisting of a keyboard, an optical or magnetic disk drive, a touch screen, a voice activated input device and a modem.

58. The system of claim 57, wherein said second input device is a keyboard.

59. The system of claim 54, wherein said output device is selected from the group consisting of a color monitor, a monochrome monitor and a printer.

60. The system of claim 59, wherein said output device printer.

61. A system for determining a difference in a spatially-variable field characteristic, comprising:

a) a first input means for receiving spatially-referenced field characteristic data;

b) a second input means for receiving user commands;

c) a processing means communicating with said first and said second input device to designate said field characteristic data to a first crop test area or a second crop test area according to said user commands, to define cells from said first crop test area or said second crop test area based on the user commands, and to calculate a difference between a first cell from said first crop test area and an adjacent first cell from said second crop test area; and

d) an output means for displaying said difference.

62. The system of claim 61, wherein said first input means is selected from the group consisting of a keyboard, an optical or magnetic disk drive, a touch screen, a voice activated input device and a modem.

63. The system of claim 62, wherein said first input means is an optical or magnetic disk drive.

64. The system of claim 61, wherein said second input means is selected from the group consisting of a keyboard, an optical or magnetic disk drive, a touch screen, a voice activated input device and a modem.

65. The system of claim 64, wherein said second input means is a keyboard.

66. The system of claim 61, wherein said output means is selected from the group consisting of a color monitor, a monochrome monitor and a printer.

67. The system of claim 66, wherein said output means is a printer.

68. The system of claim 61, further defined as comprising a processing means for calculating a correlation between said difference and an environmental condition variable.