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        "name": "Soil Sciences", 
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        "affiliation": {
          "alternateName": "Department of Plant and Soil Sciences, Mississippi State University, 9555, 39762, Mississippi, MS, USA", 
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            "Department of Plant and Soil Sciences, Mississippi State University, 9555, 39762, Mississippi, MS, USA"
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          "alternateName": "Department of Mathematical Sciences, Clemson University, Clemson, SC, USA", 
          "id": "http://www.grid.ac/institutes/grid.26090.3d", 
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            "Department of Mathematical Sciences, Clemson University, Clemson, SC, USA"
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    "datePublished": "2012-10-25", 
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    "description": "Site-specific crop and soil management has the potential to increase crop production efficiency and decrease environmental impact. Determination of management zones is essential for site-specific management to be successful. These zones delineate portions of the field with the same yield limiting factors such that these factors can be managed independent of the rest of the field. However, spatial and temporal variability can confound zone delineation, thus stability of the zones must be ensured. Zone delineation has typically followed one of two methods. The first method defines areas of the field using the variability in crop yield while the second uses the variability of soil properties that might influence yield. Cluster analysis has commonly been used as a pattern recognition method to identify stable zones based on yield data. After the yield zones have been classified, soil properties can be related to the zones and be managed on a site specific basis. These soil properties can be found using directed sampling, intense soil survey data or some form of remote sensing. The second method of determining management zones used the spatial variability of soil physical or chemical properties to define the management areas. The high cost of intensive soil sampling needed for this method proved to be a limitation. Soil electrical conductivity (ECa) has emerged as an inexpensive way of identifying soil variability and has been used in many studies to relate soil differences to crop yield. These differences were typically related to changes in soil series or soil water availability. While zone delineation has shown to be successful in many crops, there is little information available on zones changes between crops in a rotation.The objectives of this study were to determine if yield classes change between crops within a soybean-corn-soybean rotation and whether soil properties can predict the yield classes or the year-to-year changes. A percentile classification method was used to categorize 3 years of yield in two fields into low, medium and high yield classes. There was significant agreement in yield classifications between years in both fields. Linear discriminant analysis predicted yield class based on soil properties correctly 10\u201366% of the time in Field 1 and in Field 233\u2013100% of the time. There was little consistency in soil properties used to make class predictions in Field 1 but soil apparent electrical conductivity did appear in four of the six discriminant functions. Field 2 had a great deal of consistency in soil parameters that classified yield from year to year. Soil test K and Mg were present in all discriminant functions while Ca, P, texture and ECa were present in five of the six. Of the years where at least one variable was found to be useful in discrimination, ECa was present in both fields. This suggests that the management zones based on these soil properties may increase production efficiency.", 
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        "givenName": "Eric", 
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      "name": "Sustainable Agriculture Reviews", 
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    ], 
    "name": "Crop and Soil Management Zone Delineation Based on Soil Property or Yield Classification", 
    "pagination": "223-240", 
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