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Yield map errors and their impact on interpolation accuracy

https://doi.org/10.2139/ssrn.6514826
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inferredcites →https://doi.org/10.1002/joc.3829openalex-snapshot
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Spatial variability of crop responses to agronomic inputs in on-farm precision experimentation
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inferredcites →https://doi.org/10.1007/s40808-018-0477-2openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.cageo.2007.05.009openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.cageo.2008.10.011openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.eja.2011.06.004openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.fcr.2009.06.008openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.fcr.2011.01.002openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.fcr.2011.05.021openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.fcr.2012.10.012openalex-snapshot
A ‘small strip’ approach to empirically determining management class yield response functions and calculating the potential financial ‘net wastage’ associated with whole-field uniform-rate fertiliser application
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Responses to precision planting in canola and grain legume crops
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On the relation between soil water holding capacity and dryland crop productivity
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The interpretation of trends from multiple yield maps
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Drivers of within-field spatial and temporal variability of crop yield across the US Midwest
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Precision Agriculture for Grain Production Systems
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Economic benefits of variable rate technology: case studies from Australian grain farms
inferredcites →https://doi.org/10.1080/00401706.1964.10490181openalex-snapshot
Multiple Comparisons Using Rank Sums
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Interpolation type and data computation of crop yield maps is important for precision crop production
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Local Indicators of Spatial Association—LISA
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Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations
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Profitability Maps as an Input for Site-Specific Management Decision Making
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Classification of Crop Yield Variability in Irrigated Production Fields
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Yield Editor: Software for Removing Errors from Crop Yield Maps
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Establishing Management Classes for Broadacre Agricultural Production
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