Statistical aspects of on-farm experimentation

This paper reviews options for the design and analysis of on-farm experiments. It covers both older approaches that have been popular since the Green Revolution, and more recent developments made possible by the availability of online monitoring systems as used in precision farming. The roles of randomisation as well as of geostatistical methods of analysis for these kinds of experiments are critically discussed. Two case studies are provided for illustration.

[1]  Markus Gandorfer,et al.  A conceptual framework for judging the precision agriculture hypothesis with regard to site-specific nitrogen application , 2009, Precision Agriculture.

[2]  R. G. V. Bramley,et al.  Enhancing the value of field experimentation through whole-of-block designs , 2010, Precision Agriculture.

[3]  R C Littell,et al.  Statistical analysis of repeated measures data using SAS procedures. , 1998, Journal of animal science.

[4]  S. E. Cook,et al.  Field-Scale Experiments for Site-Specific Crop Management. Part II: A Geostatistical Analysis , 2004, Precision Agriculture.

[5]  S Senn,et al.  Repeated measures in clinical trials: simple strategies for analysis using summary measures. , 2000, Statistics in medicine.

[6]  A. F. Troyer,et al.  Statistical methods in seed corn product selection , 1988 .

[7]  J. van der Ploeg,et al.  Interpretation of results from on-farm experiments: manure-nitrogen recovery on grassland as affected by manure quality and application technique. 1. An agronomic analysis , 2007 .

[8]  H. Piepho,et al.  Efficient phosphorus application strategies for increased crop production in sub-Saharan West Africa , 2001 .

[9]  R. Mead,et al.  The Design of Experiments: Statistical Principles for Practical Applications. , 1989 .

[10]  Terrance M. Hurley,et al.  Estimating site-specific nitrogen crop response functions: A conceptual framework and geostatistical model , 2003 .

[11]  Geert Molenberghs,et al.  Nonlinear Models for Longitudinal Data , 2009 .

[12]  Cathy Hawes,et al.  Design, analysis and statistical power of the Farm-Scale Evaluations of genetically modified herbicide-tolerant crops , 2003 .

[13]  R. Littell,et al.  ON-FARM EXPERIMENTS WITH MAIZE-MUCUNA SYSTEMS IN THE LOS TUXTLAS REGION OF VERACRUZ, MEXICO. I. MUCUNA BIOMASS AND MAIZE GRAIN YIELD , 2003, Experimental Agriculture.

[14]  Viacheslav I. Adamchuk,et al.  Classification of Crop Yield Variability in Irrigated Production Fields , 2003 .

[15]  ON-FARM EXPERIMENTS ON INTEGRATED NUTRIENT MANAGEMENT IN RICE-WHEAT CROPPING SYSTEMS , 2001, Experimental Agriculture.

[16]  Richard E. Plant Comparison of Means of Spatial Data in Unreplicated Field Trials , 2007 .

[17]  Farmer-directed on-farm experimentation examining the impact of companion planting barley and oats on timothyalfalfa forage establishment in central Newfoundland , 2004 .

[18]  M. Talbot Yield variability of crop varieties in the U.K. , 1984, The Journal of Agricultural Science.

[19]  Douglas H. Johnson The many faces of replication , 2006 .

[20]  R. G. Petersen,et al.  Agricultural Field Experiments: Design and Analysis , 1994 .

[21]  Hans-Peter Piepho,et al.  Methods for Comparing the Yield Stability of Cropping Systems , 1998 .

[22]  A. F. Troyer,et al.  Heterosis decreasing in hybrids: yield test inbreds. , 2009 .

[23]  Weikai Yan,et al.  On‐Farm Strip Trials vs. Replicated Performance Trials for Cultivar Evaluation , 2002 .

[24]  Brian R. Cullis,et al.  Accounting for natural and extraneous variation in the analysis of field experiments , 1997 .

[25]  H. Piepho,et al.  Stability analysis of farmer participatory trials for conservation agriculture using mixed models , 2011 .

[26]  J. Perry,et al.  Design of the farm‐scale evaluations of genetically modified herbicide‐tolerant crops , 2003 .

[27]  Hans-Peter Piepho,et al.  Nearest Neighbour Adjustment and Linear Variance Models in Plant Breeding Trials , 2008, Biometrical journal. Biometrische Zeitschrift.

[28]  P. Hildebrand Modified stability analysis of Farmer managed, on-farm trials , 1984 .

[29]  B. Cullis,et al.  Applications: The Analysis of Crop Variety Evaluation Data in Australia , 2001 .

[30]  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.

[31]  Achim Dobermann,et al.  Creating Spatially Contiguous Yield Classes for Site‐Specific Management , 2003 .

[32]  R. Gerhards,et al.  An on-farm approach to quantify yield variation and to derive decision rules for site-specific weed management , 2008, Precision Agriculture.

[33]  Jeffrey Willers,et al.  Designing experiments to evaluate the effectiveness of precision agricultural practices on research fields: part 1 concepts for their formulation , 2010, Oper. Res..

[34]  Jeffrey G. White,et al.  Spatial Analysis of Precision Agriculture Treatments in Randomized Complete Blocks: Guidelines for Covariance Model Selection , 2005 .

[35]  Dayton M. Lambert,et al.  A Comparison of Four Spatial Regression Models for Yield Monitor Data: A Case Study from Argentina , 2004, Precision Agriculture.

[36]  Are neighbour methods preferable to analysis of variance for completely systematic designs? ‘Silly designs are silly!’ , 1995 .

[37]  S. E. Cook,et al.  Field-Scale Experiments for Site-Specific Crop Management. Part I: Design Considerations , 2004, Precision Agriculture.

[38]  R. M. Lark,et al.  The geostatistical analysis of experiments at the landscape-scale , 2006 .

[39]  S Czajka,et al.  Analyzing Multi‐environment Variety Trials Using Randomization‐Derived Mixed Models , 2005, Biometrics.

[40]  S. Wuest,et al.  Increasing Plot Length Reduces Experimental Error of On-Farm Tests , 1994 .

[41]  Michael Edward Hohn,et al.  An Introduction to Applied Geostatistics: by Edward H. Isaaks and R. Mohan Srivastava, 1989, Oxford University Press, New York, 561 p., ISBN 0-19-505012-6, ISBN 0-19-505013-4 (paperback), $55.00 cloth, $35.00 paper (US) , 1991 .

[42]  Monirul Islam,et al.  REML IS AN EFFECTIVE ANALYSIS FOR MIXED MODELLING OF UNBALANCED ON-FARM VARIETAL TRIALS , 2009, Experimental Agriculture.

[43]  R. M. Lark,et al.  A Method to Investigate Within‐Field Variation of the Response of Combinable Crops to an Input , 2003 .

[44]  MAIZE YIELDS RESPONSE TO APPLICATION OF ORGANIC AND INORGANIC INPUT UNDER ON-STATION AND ON-FARM EXPERIMENTS IN CENTRAL KENYA , 2009, Experimental Agriculture.

[45]  R. Littell,et al.  ON-FARM EXPERIMENTS WITH MAIZE-MUCUNA SYSTEMS IN THE LOS TUXTLAS REGION OF VERACRUZ, SOUTHERN MEXICO. II. MUCUNA VARIETY EVALUATION AND SUBSEQUENT MAIZE GRAIN YIELD , 2003, Experimental Agriculture.

[46]  David R. Cox,et al.  Randomization in the Design of Experiments , 2009 .

[47]  R. J. Baker,et al.  Selection response in subdivided target regions , 2000 .

[48]  J. Riley,et al.  ASPECTS OF DESIGN OF ON-FARM FERTILIZER TRIALS , 1998, Experimental Agriculture.

[49]  H. Piepho,et al.  Model selection and its consequences for different split-plot designs with spatial covariance and trend. , 2010 .

[50]  Charles G. OHara,et al.  Defining the experimental unit for the design and analysis of site-specific experiments in commercial cotton fields , 2008 .

[51]  G. Robinson That BLUP is a Good Thing: The Estimation of Random Effects , 1991 .

[52]  R. Chambers The Origins and Practice of Participatory Rural Appraisal * ROBERT CHAMBERS ? , 1994 .

[53]  Hans-Peter Piepho,et al.  A Mixed Modelling Approach for Randomized Experiments with Repeated Measures , 2004 .

[54]  Hans-Peter Piepho,et al.  Analysis of a randomized block design with unequal subclass numbers , 1997 .

[55]  H. Piepho,et al.  Best Linear Unbiased Prediction of Cultivar Effects for Subdivided Target Regions , 2005 .

[56]  R. Wolfinger Covariance structure selection in general mixed models , 1993 .

[57]  H. Piepho,et al.  Comparison of Weighting in Two‐Stage Analysis of Plant Breeding Trials , 2009 .

[58]  Robert Chambers,et al.  Rapid rural appraisal: rationale and repertoire , 1981 .