Post-processing methods to eliminate erroneous grain yield measurements: review and directions for future development

Yield mapping is increasingly used in agricultural management. The distributions produced from the majority of these datasets are non-normal and can be misleading if used in the decision making process. Numerous studies over the last 25 years, published in various formats, have highlighted the sources of errors that contribute to this non-normality and have proposed a variety of post-processing methods to reduce their effect. A comprehensive cataloging of the types of errors present and methods used to remove them as well as the approaches to and effects of post-processing error removal is needed. This review identifies four types of yield mapping measurement errors: issues associated with harvesting dynamics of the combine harvester, the continuous measurement of moisture and yield, the accuracy of positional data and errors caused by the harvester operator. Methods to remove errors range from simple thresholds to complex routines that incorporate harvest position and local yield variation. The benefits of applying filters have focused on the removal of erroneous yield variation based on simple descriptive statistics, the creation of yield distributions that show greater normality and the decrease of the nugget-variance relationship and prediction variance estimated in yield map interpolation. Publication of these parameters should accompany the interpolated yield map for both unprocessed and post-processed datasets to provide an insight into the reliability of the collected measurements and the effectiveness of the routines implemented. Examples from commercial growers in Western Australia are used to reinforce the review’s findings and highlight the potential for extensions to current methods to remove errors associated with harvester speed, narrow finishes and harvester turns and overlaps. This paper suggests extending the current routine implementation of error removal towards an automated post-processing system.

[1]  B. S. Blackmore,et al.  Yield Mapping; Errors and Algorithms , 2015 .

[2]  P. C. Robert,et al.  Creating yield maps from yield monitor data using Multi-Purpose Grid Mapping (MPGM). , 2000 .

[3]  J. V. Stafford,et al.  Limitations on the spatial resolution of yield mapping for combinable crops , 1997 .

[4]  Bjarne Joernsgaard,et al.  Intra-field yield variation over crops and years , 2003 .

[5]  Lei Tian,et al.  Time Shift Evaluation to Improve Yield Map Quality , 2001 .

[6]  S. Asseng,et al.  Determining the Causes of Spatial and Temporal Variability of Wheat Yields at Sub-field Scale Using a New Method of Upscaling a Crop Model , 2006, Plant and Soil.

[7]  Terry W. Griffin,et al.  Yield Monitor Data Analysis Protocol: A Primer in the Management and Analysis of Precision Agriculture Data , 2007 .

[8]  Sindhu George,et al.  Principles of Geographic Information Systems , 2002 .

[9]  Ardian Harri,et al.  Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality , 2009 .

[10]  John V. Stafford,et al.  Precision agriculture '15 , 2015 .

[11]  Kenneth A. Sudduth,et al.  Yield Editor: Software for Removing Errors from Crop Yield Maps , 2007 .

[12]  Brett Whelan,et al.  Establishing Management Classes for Broadacre Agricultural Production , 2007 .

[13]  J. L. Ping,et al.  Processing of Yield Map Data , 2005, Precision Agriculture.

[14]  Craig L. Dobbins,et al.  Spatial analysis of yield monitor data: case studies of on-farm trials and farm management decision making , 2008, Precision Agriculture.

[15]  Dong-Hoon Lee,et al.  Automated Yield Map Delay Identification Using Phase Correlation Methodology , 2012 .

[16]  John P. Fulton,et al.  Post processing correction to improve the accuracy of yield monitor data in grain crops. , 2004 .

[17]  Michael Robertson,et al.  Within-field variability of wheat yield and economic implications for spatially variable nutrient management , 2008 .

[18]  H. D. Kutzbach,et al.  Investigations on a particular yield mapping system for combine harvesters , 1996 .

[19]  Sun-Ok Chung,et al.  Determining yield monitoring system delay time with geostatistical and data segmentation approaches , 2002 .

[20]  Lars Thylén,et al.  The Control of Errors in Momentary Yield Data from Combine Harvesters , 1996 .

[21]  John P. Fulton,et al.  Grain yield monitor flow sensor accuracy for simulated varying field slopes. , 2009 .

[22]  Kenneth A. Sudduth,et al.  Comparison of sensors and techniques for crop yield mapping , 1996 .

[23]  Clyde W. Fraisse,et al.  Vector method for determining harvest area using combine position data , 1999 .

[24]  Sukant K. Misra,et al.  ARE CROP YIELDS NORMALLY DISTRIBUTED , 2001 .

[25]  J. Stafford,et al.  An algorithm for automatic detection and elimination of defective yield data. , 2003 .

[26]  Jonathan Cohen.  Statistical Methods in Soil and Land Resource Survey , 1992 .

[27]  J. V. Stafford,et al.  Mapping and interpreting the yield variation in cereal crops , 1996 .

[28]  Markus Demmel,et al.  Relative accuracy of different yield mapping systems installed on a single combine harvester. , 2003 .

[29]  J. Hoffman.  Numerical Methods for Engineers and Scientists , 2018 .

[30]  Graciela Metternicht,et al.  Comparing the performance of techniques to improve the quality of yield maps , 2005 .

[31]  Yanji Wang,et al.  A harvest area measurement system based on ultrasonic sensors and DGPS for yield map correction , 2010, Precision Agriculture.

[32]  Thomas S. Colvin,et al.  Grain Yield Mapping: Yield Sensing, Yield Reconstruction, and Errors , 2002, Precision Agriculture.

[33]  Markus Demmel,et al.  Effect of interpolation methods and filtering on the quality of yieldmaps. , 2005 .

[34]  Simon Blackmore,et al.  Remedial Correction of Yield Map Data , 2004, Precision Agriculture.

[35]  J. Atwood,et al.  Are Crop Yields Normally Distributed? A Reexamination , 2003 .

[36]  P. C. Robert,et al.  An expert filter removing erroneous yield data. , 2000 .

[37]  Gérard Lachapelle,et al.  Building a Yield Map from Geo‐referenced Harvest Measurements , 2015 .

[38]  S. Misra,et al.  Crop‐Yield Distributions Revisited , 2003 .

[39]  P. D. T. O'Connor,et al.  Statistical methods for engineers and scientists (2nd edn), Robert M. Bethea, Benjamin S. Duran and Thomas L. Boullion, Marcel Dekker. 1985. No. of pages: 698 , 1986 .

[40]  W. E. Larson,et al.  Perils of Monitoring Grain Yield On-The-Go , 1995 .

[41]  Kenneth A. Sudduth,et al.  Analysis of errors affecting yield map accuracy. , 2004 .

[42]  Lars Thylén,et al.  Monitoring wheat protein content on-harvester : Australian experiences , 2005 .

[43]  R. M. Bethea,et al.  Statistical Methods for Engineers and Scientists. , 1985 .

[44]  Achim Dobermann,et al.  Screening Yield Monitor Data Improves Grain Yield Maps , 2004 .

[45]  Stephen W. Searcy,et al.  YIELD DATA FILTERING TECHNIQUES FOR IMPROVED MAP ACCURACY , 2001 .

[46]  B. M. Whelan,et al.  VESPER – SPATIAL PREDICTION SOFTWARE FOR PRECISION AGRICULTURE , 2002 .

[47]  David A. Hennessy,et al.  Crop Yield Skewness and the Normal Distribution , 2009 .

[48]  Shufeng Han,et al.  A bitmap method for determining effective combine cut width in yield mapping. , 1997 .

[49]  Thomas S. Colvin,et al.  An Evaluation of the Response of Yield Monitors and Combines to Varying Yields , 2002, Precision Agriculture.