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item Pinson, Shannon
item WILSON, L
item WU, G
item McClung, Anna
item PARK, W

Submitted to: Rice Technical Working Group Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 3/20/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The complex interaction between phenotypic traits and physical and agronomic factors makes it difficult to clearly determine which combination of phenotypic traits will give optimal performance for a particular geographical location. It would be impractical to construct an appropriate field experiment designed to estimate those relations as such a study would drequire collection of laborious detailed data in many years and environments. However, we can use a verified physiologically-based rice population model to estimate the performance of hypothetical combinations of traits under a wide range of physical conditions and thus estimate for breeders the "ideal plant phenotype" or combinations of traits for which to select for any particular environmental condition. The objective of this study is to identify the combination of phenotypic traits that would provide high yield potential in an "average Texas environment". Previous research identified the following five traits which were used in this study: maximum rate of node production, nodal position of the 1st tiller, total number of nodes per main stem, potential flag leaf mass, and number of florets per grain head. All combinations of five different levels of each of these traits were evaluated by the model in three genetic (varietal) backgrounds. The yield impact of all trait combinations was estimated for five planting dates per each of 20 years of weather data (Beaumont, TX, 1979 - 1998) for a total of nearly 1 million simulations. The potential benefit and risk of each hypothetical genotype was thus determined over time, allowing us to determined the "optimum" combination of phenotypic traits that would provide high rice yields over time in multiple years in and around Beaumont, TX.