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

This Article Abstract 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 Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (5) Citing Articles via Google Scholar Google Scholar Articles by Wu, T. Articles by Dutilleul, P. Search for Related Content PubMed Articles by Wu, T. Articles by Dutilleul, P. Agricola Articles by Wu, T. Articles by Dutilleul, P.

Validity and Efficiency of Neighbor Analyses in Comparison with Classical Complete and Incomplete Block Analyses of Field Experiments

^a Nanjing Agricultural University, Nanjing, China
^b Dep. of Plant Science, McGill University, Macdonald Campus, 21,111 Lakeshore Rd., Ste-Anne-de-Bellevue, QC, Canada H9X 3V9

View larger version (69K): [in a new window]   Fig. 1 Contour maps of grain yield (g per unit row) in (left) soybean and (right) wheat uniformity trials. For soybean, the contour interval is 30 g; the lightest shade corresponds to a value of 40 g and the darkest shade, 310 g. For wheat, contour interval is 60 g; the extreme shades correspond to values of 375 and 915 g. The scale used is representative of the true physical size of each field. Source of data: Wu et al. (1995) for soybean and Wiebe (1935) for wheat

View larger version (35K): [in a new window]   Fig. 2 Normalized semivariograms for the residuals of the randomized complete block model (dashed line) and for the first differences (solid line) and second differences (dotted line) of the raw data, by using soybean data sets with v = 60 (no. of dummy varieties). See Tables 1 and 2 for the data set codes and characteristics

View larger version (37K): [in a new window]   Fig. 3 Normalized semivariograms for the residuals of the randomized complete block model (dashed line) and for the first differences (solid line) and second differences (dotted line) of the raw data, by using wheat data sets with v = 60 (no. of dummy varieties). See Tables 1 and 2 for the data set codes and characteristics

View larger version (21K): [in a new window]   Fig. 4 Spatial autocorrelations for the residuals of the randomized complete block model (dashed line) and for the first differences (solid line) and second differences (dotted line) of the raw data for (a) soybean A1, (b) soybean B5, (c) wheat B2, and (d) wheat A3. See Tables 1 and 2 for the data set codes and characteristics

View larger version (21K): [in a new window]   Fig. 5 Relative efficiency in variety effect estimation in relation to the CV and the normalized nugget effect for (a) soybean (v = 60) and the FD-EV model, (b) wheat (v = 25 and 60) and the FD-EV model, (c) soybean (v = 60) and the IB(6) model, and (d) wheat (v = 25 and 60) and the IB(6) or IB(5) model