Monday, 7 November 2005
4

This presentation is part of: Small Grain Breeding and Genetics

Impacts of Sample Size, Genotype and Location on the Reliability of the Solvent Retention Capacity Test for Predicting End-Use Quality in Wheat.

Carl Walker, Kimberly Garland Campbell, Brady Carter, and Kimberlee Kidwell.

The Solvent Retention Capacity (SRC) test is used to predict baking quality of wheat (Triticum aestivum) flours extracted from early generation breeding material. To be an effective selection tool, varietal rankings must be stable across environments. The objective of this study was to determine the proportion of variation associated with genotype (G), location (L), and G X L for SRC values from soft white wheat (SWW) varieties grown in the Pacific Northwest. SRC tests were conducted using water, 5% sodium carbonate, 50% sucrose, and 5% lactic acid as solvents, which are indicators of base absorption, hardness, pentosan and gliadin content, and gluten quality, respectively. Samples of 32 spring and winter varieties encompassing the quality range of SWW grown in region were collected from statewide yield trials at six locations representing major agroclimatic zones. Two scales of the SRC test, 5 g and 0.2 g, were conducted to determine if each sample size was equally sensitive to these sources of variation. For the 0.2 g tests, G, L and replication (R) were significant (P<0.01) for all solvents and both growth habit types. G X L was only significant (P<0.001) for spring types tested with lactic acid, and further analyses will be conducted to determine if this leads to significant changes in variety rankings across locations. The highly significant R effect suggests that the 0.2 g results may be strongly influenced by variation introduced by minor deviations in operator methods. In spite of this, the highly significant G and L factors indicate that the 0.2 g test is suitable for use in early generation testing. Similar analyses will be conducted using data from the 5 g SRC tests. Results from 0.2 and 5 g tests will be compared to determine which scale is most suitable for obtaining reliable end-use quality predictions.

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