Efficiency of spatial analyses of field pea variety trials
Several spatial analyses of neighboring plots are now available for improving the precision of variety trials. The objective of this study was to evaluate the efficiency of three commonly used spatial analyses, a nearest neighbor adjustment (NNA), a least squares smoothing (LSS), and a first-order a...
| Autores principales: | , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2004
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/96422 |
| _version_ | 1855514990723727360 |
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| author | Yang, R.C. Ye, T.Z. Blade, S.F. Bandara, M. |
| author_browse | Bandara, M. Blade, S.F. Yang, R.C. Ye, T.Z. |
| author_facet | Yang, R.C. Ye, T.Z. Blade, S.F. Bandara, M. |
| author_sort | Yang, R.C. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Several spatial analyses of neighboring plots are now available for improving the precision of variety trials. The objective of this study was to evaluate the efficiency of three commonly used spatial analyses, a nearest neighbor adjustment (NNA), a least squares smoothing (LSS), and a first-order autoregressive model (AR1), in removing field trends from 157 field pea (Pisum sativum L.) variety trials tested in different growing zones across Alberta, Canada, during 1997 to 2001. All trials were conducted with a randomized complete block (RCB) design with three or four replications. A complete replication (block) was planted in a single field tier. Yield data from each of the 157 trials were subject to the conventional RCB analysis and the three spatial analyses. The LSS, NNA, and AR1 analyses removed an average of 22, 16, and 7% residual variation compared with the RCB analysis, respectively, but the amount of removal by the three analyses varied considerably among the trials. Each spatial analysis achieved more error reduction in 1997 and 1998, where trials contained larger block sizes than in 1999 to 2001, where trials contained smaller block sizes. The efficiency in spatial variation removal was great with large block sizes that involved large numbers of varieties. Furthermore, the LSS and NNA analyses were more effective in such removal than the AR1 analysis. |
| format | Journal Article |
| id | CGSpace96422 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2004 |
| publishDateRange | 2004 |
| publishDateSort | 2004 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace964222024-05-15T05:11:14Z Efficiency of spatial analyses of field pea variety trials Yang, R.C. Ye, T.Z. Blade, S.F. Bandara, M. pea varieties spatial analyses soil fertility Several spatial analyses of neighboring plots are now available for improving the precision of variety trials. The objective of this study was to evaluate the efficiency of three commonly used spatial analyses, a nearest neighbor adjustment (NNA), a least squares smoothing (LSS), and a first-order autoregressive model (AR1), in removing field trends from 157 field pea (Pisum sativum L.) variety trials tested in different growing zones across Alberta, Canada, during 1997 to 2001. All trials were conducted with a randomized complete block (RCB) design with three or four replications. A complete replication (block) was planted in a single field tier. Yield data from each of the 157 trials were subject to the conventional RCB analysis and the three spatial analyses. The LSS, NNA, and AR1 analyses removed an average of 22, 16, and 7% residual variation compared with the RCB analysis, respectively, but the amount of removal by the three analyses varied considerably among the trials. Each spatial analysis achieved more error reduction in 1997 and 1998, where trials contained larger block sizes than in 1999 to 2001, where trials contained smaller block sizes. The efficiency in spatial variation removal was great with large block sizes that involved large numbers of varieties. Furthermore, the LSS and NNA analyses were more effective in such removal than the AR1 analysis. 2004-01 2018-08-09T06:40:40Z 2018-08-09T06:40:40Z Journal Article https://hdl.handle.net/10568/96422 en Limited Access Wiley Yang, R.C., Ye, T.Z., Blade, S.F. & Bandara, M. (2004). Efficiency of spatial analyses of field pea variety trials. Crop Science, 44(1), 49-55. |
| spellingShingle | pea varieties spatial analyses soil fertility Yang, R.C. Ye, T.Z. Blade, S.F. Bandara, M. Efficiency of spatial analyses of field pea variety trials |
| title | Efficiency of spatial analyses of field pea variety trials |
| title_full | Efficiency of spatial analyses of field pea variety trials |
| title_fullStr | Efficiency of spatial analyses of field pea variety trials |
| title_full_unstemmed | Efficiency of spatial analyses of field pea variety trials |
| title_short | Efficiency of spatial analyses of field pea variety trials |
| title_sort | efficiency of spatial analyses of field pea variety trials |
| topic | pea varieties spatial analyses soil fertility |
| url | https://hdl.handle.net/10568/96422 |
| work_keys_str_mv | AT yangrc efficiencyofspatialanalysesoffieldpeavarietytrials AT yetz efficiencyofspatialanalysesoffieldpeavarietytrials AT bladesf efficiencyofspatialanalysesoffieldpeavarietytrials AT bandaram efficiencyofspatialanalysesoffieldpeavarietytrials |