Experimental designs and estimation methods for on - farmresearch a simulation study of corn yields at field scale

On-farm experimentation using Precision Agriculture technology enables farmers to make decisions based on data from their fields. Results from on-farm experiments depend on the experimental design and statistical analyses performed. Detailed information about the accuracy of the treatment effect est...

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Detalles Bibliográficos
Otros Autores: Alesso, Carlos Agustín, Cipriotti, Pablo Ariel, Bollero, Germán Alberto, Martín, Nicolás Federico
Formato: Artículo
Lenguaje:Inglés
Materias:
Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2019alesso.pdf
LINK AL EDITOR
Aporte de:Registro referencial: Solicitar el recurso aquí
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245 1 0 |a Experimental designs and estimation methods for on - farmresearch  |b a simulation study of corn yields at field scale 
520 |a On-farm experimentation using Precision Agriculture technology enables farmers to make decisions based on data from their fields. Results from on-farm experiments depend on the experimental design and statistical analyses performed. Detailed information about the accuracy of the treatment effect estimates, and Type I error rates of hypothesis testing under different spatial structure scenarios attained by alternative experimental designs and analysis is required to improve on farm research experiments. Three thousand yield data sets were drawn from 15 random fields simulated by unconditional Gaussian geostatistical simulation technique and were modeled by applying 10 experimental designs and three estimation methods with experimental units ranging from 138 to 9969 m2. No effect of spatial structure, experimental design, and estimation methods was observed on overall mean yield and treatment bias. Unaddressed changes of nugget/sill ratio and range of variogram had a significant effect on estimator efficiency and accuracy with Type I error rates above the nominal rate, which increased with higher spatial autocorrelation. Spatial methods were robust to changes in spatial structure regardless of the design. Randomization of treatment increased the uncertainty of model estimators. In general, the accuracy of treatment effect estimates increased with the number of replications of smaller size. The opposite trend was observed between those estimates and the size of the plots. Analyses showed that the best designs for testing the overall treatment effect in two-treatment experiments would be split-planter, strip-plots, and chessboard because of their size and number of experimental units. 
650 |2 Agrovoc  |9 26 
653 |a CORN YIELDS 
653 |a SPATIAL AUTOCORRELATION 
653 |a EXPERIMENTAL DESIGNS 
653 |a ESTIMATION METHODS 
653 |a SIMULATION STUDY 
700 1 |a Alesso, Carlos Agustín  |u Universidad Nacional del Litoral (FCA-UNL). Facultad de Ciencias Agrarias. Instituto de Ciencias Agropecuarias del Litoral. (ICiAgro Litoral) . Esperanza, Argentina.  |u CONICET - Universidad Nacional del Litoral (FCA-UNL). Facultad de Ciencias Agrarias. Instituto de Ciencias Agropecuarias del Litoral. (ICiAgro Litoral). Esperanza, Argentina.  |9 48420 
700 1 |9 20940  |a Cipriotti, Pablo Ariel  |u Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.  |u CONICET – Universidad de Buenos Aires. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina. 
700 1 |a Bollero, Germán Alberto  |u University of Illinois. Departament of Crop Sciences. Urbana, Illinois, United States.  |9 71461 
700 1 |a Martín, Nicolás Federico  |u University of Illinois. Departament of Crop Sciences. Urbana, Illinois, United States.  |9 73807 
773 0 |t Agronomy Journal  |w SECS000017  |g Vol.3, no.6 (2019), p.2724–2735, tbls., grafs. 
856 |f 2019alesso  |i en reservorio  |q application/pdf  |u http://ri.agro.uba.ar/files/intranet/articulo/2019alesso.pdf  |x ARTI202003 
856 |z LINK AL EDITOR  |u https://www.wiley.com/ 
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