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ON THE VARIATION OF YIELD VARIANCE WITH PLOT SIZE
Biometrika, 1956The problem examined is that of evaluating the spatial covariance function of yield density, from a knowledge of the way yield variance varies with plot size and shape. Results are obtained in ? 3 for several kinds of plot. Results are also obtained (?4) on the dependence of the yield variance on plot geometry for very small and very large plots ...
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FENAMIPHOS LOSSES UNDER SIMULATED RAINFALL: PLOT SIZE EFFECTS
Transactions of the ASAE, 2004The purpose of this study was to compare two commonly used runoff experimental methods, which have different scales, on measurements of runoff and associated fenamiphos and metabolite losses over a 2-year period. Methods used were 15 m wide by 43 m long (645 m2) mesoplots and 1.8 m wide by 3 m long (5.4 m2) microplots, under simulated rainfall (25 mm
null R. D. Wauchope +8 more
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Rattan inventory: determining plot shape and size
1996Increased recognition of the importance of non-timber forest products has led to a need to develop inventory methods for these species. One of the most valuable non-timber forest products are rattans, the stems of climbing palms belonging to the sub-family Calamoideae and the basis of a furniture industry worth an estimated U.S.$ 6.5 billion per annum ...
Stockdale, M, Wright, H
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Early Stage Sugarcane Selection Using Different Plot Sizes
Crop Science, 2007Most sugarcane (Saccharum spp.) cultivar development programs use single‐row plots in their first clonal trials. We hypothesized that a larger plot size would increase the accuracy of selection and compared selection efficiencies of 1.82‐, 3.35‐, and 4.88‐m single‐row plots.
Scott B. Milligan +3 more
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Estimating top height with variable plot sizes
Canadian Journal of Forest Research, 1998Conventional top height estimates are biased if the area of the sample plot differs from that on which the definition is based. Sources of bias include a sampling selection effect and spatial autocorrelation. The problem was studied in relation to the use of data sets with varying spatial detail for modelling Douglas-fir (Pseudotsuga menziesii (Mirb.)
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Rank-size plots, Zipf’s law, and scaling
1997Rank-size plots, also called Zipf plots, have a role to play in representing statistical data. The method is somewhat peculiar, but throws light on one aspect of the notions of concentration. This chapter’s first goals are to define those plots and show that they are of two kinds.
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The size and shape of the test plots
1995Ideal trial fields (in the open or in glasshouses) provide uniform growing conditions across their whole area. Such trial fields do not exist if their area is ‘somewhat large’. Then the trial field contains relatively better and poorer sections. These sections may change in time; their contours may depend on the crop.
Izak Bos, Peter Caligari
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Increasing the size and complexity of discrete 2D metallosupramolecules
Nature Reviews Materials, 2021Heng Wang, Yiming Li, Na Li
exaly
Recent progress in understanding, diagnosing, and treating hepatocellular carcinoma
Ca-A Cancer Journal for Clinicians, 2012Anne Covey
exaly