HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Free Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (6) Citing Articles via Google Scholar Google Scholar Articles by Yang, R.-C. Articles by Bandara, M. Search for Related Content PubMed Articles by Yang, R.-C. Articles by Bandara, M. Agricola Articles by Yang, R.-C. Articles by Bandara, M. Related Collections Statistics Crop Genetics Other Legumes

CROP BREEDING, GENETICS & CYTOLOGY

Efficiency of Spatial Analyses of Field Pea Variety Trials

^a Alberta Agriculture, Food, and Rural Development, Room 300, 7000–113 Street, Edmonton, AB, Canada T6H 5T6, and Dep. of Agricultural, Food, and Nutritional Sci., Univ. of Alberta, Edmonton, AB, Canada T6G 2P5
^b Alberta Agriculture, Food, and Rural Development, Room 300, 7000–113 Street, Edmonton, AB, Canada T6H 5T6
^c Alberta Agriculture, Food, and Rural Development, RR6, 17507 Fort Road, Edmonton, AB, Canada T5B 4K3
^d Alberta Agriculture, Food, and Rural Development, Brooks, AB, Canada T1R 1E6

^* Corresponding author (rong-cai.yang{at}ualberta.ca).

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.

Abbreviations: AR1, first-order autoregressive model • LDF, loss of degrees of freedom • LSS, least squares smoothing • NNA, nearest neighbor adjustment • RCB, randomized complete block • REML, restricted maximum likelihood

This article has been cited by other articles:

				A. N. Kravchenko, G. P. Robertson, S. S. Snap, and A. J. M. Smucker Using Information about Spatial Variability to Improve Estimates of Total Soil Carbon Agron. J., May 3, 2006; 98(3): 823 - 829. [Abstract] [Full Text] [PDF]

				R.-C. Yang, S. F. Blade, J. Crossa, D. Stanton, and M. S. Bandara Identifying Isoyield Environments for Field Pea Production Crop Sci., January 1, 2005; 45(1): 106 - 113. [Abstract] [Full Text] [PDF]