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Activity Number:
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154
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Consulting
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| Abstract - #308967 |
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Title:
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Multivariate Exploration and Analysis of Crop Yield Components for Optimal Selection in Honeycomb Designs
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Author(s):
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Andy Mauromoustakos*+ and Vasilia Fasoula and Kevin Thompson
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Companies:
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University of Arkansas and The University of Georgia and University of Arkansas
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Address:
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101 Agriculture Annex, Fayetteville, AR, 72701,
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Keywords:
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Honeycomb Designs ; Parallel Plot ; Spatial Designs ; MANOVA ; PCA ; JMP
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Abstract:
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Honeycomb designs (HD) are a set of systematic designs capable of handling a large number of genetic entries and a large number of replications. The designs sample effectively for environmental diversity by means of large number of moving replicates. There are recently receiving attention in geostatistics literature as a preferred alternative to the popular rectangular grid designs by being more efficient especially in situations with the semivariogram model has a finite range. In the plant breeding literature these designs were developed to carry out efficient selection among genetic entries through the partition of crop yield into three genetic components and efficient selection of the best plants within the selected entries by means of the moving-ring single-plant selection. This paper will focus on the multivariate exploration and analysis of three popular yield components.
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