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Title: SELECTION FOR STABLE HIGH INCOME GROSSING RICE GENOTYPES

Author
item SAMONTE, STANLEY - TAES
item WILSON, L - TAES
item McClung, Anna
item TABIEN, R - TAES

Submitted to: Rice Technical Working Group Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/1/2006
Publication Date: 2/15/2006
Citation: Samonte, S.O., Wilson, L.T., McClung, A.M., Tabien, R.E. 2006. Selection for stable high income grossing rice genotypes. Rice Technical Working Group Meeting Proceedings, February 29 - March 1, 2006, Houston, TX. 2006. CDROM.

Interpretive Summary:

Technical Abstract: Rice breeders aim to develop new cultivars with high grain yield, resistance to stresses, and acceptable grain quality. On the other hand, rice producers aim for maximum income. The objective of this study was to determine the direct effect of whole and total milled rice percentages on gross income using path analysis and to determine the genotypes that produce stable and high expected gross income using GGE biplot analysis. Data from the Uniform Rice Regional Nursery trials on main crop grain yield and the percentages of whole and total milled rice from 47 long grain genotypes that were grown at each of five locations (AR, LA, MO, MS, and TX) during each of three cropping seasons (2001 to 2003) were used in this study. Gross income of each genotype was estimated based on rough rice grain yield, milling yield percentages, market prices of milled rice, and direct and counter-cyclical payments. Path analysis was used to estimate the path coefficients (p) of the direct effect of grain yield and the percentages of whole and total milled rice on rough rice gross income. Genotype and genotype x environment interaction (GGE) biplot analysis was used to identify the highest yielding and highest income grossing genotype(s) for each location. Grain yield had the highest positive direct effect on gross income (p = 0.87). Whole (p = 0.35) and total (p = 0.14) milled rice percentages also had significant positive direct effects on gross income. Grain yield was not correlated with either whole or total milled rice percentages. These indicated that for a genotype to have high gross income, it must have high grain yield and high percentages of whole and total milled rice. The highest yielding genotype was not the highest income grossing genotype in 9 out of 13 environments (location-season combinations) based on GGE biplot analysis. RU0103184 was the highest income grossing genotype in 6 of 13 environments and was the consistent highest income grosser at LA. RU0003178 was the highest income grossing genotype in 4 of 13 environments and was the highest income grosser at MS for two years. In both AR and TX, the highest income grosser varied across years; these were RU0003178 in 2001, RU0001188 in 2002, and RU0103184 in 2003. This study demonstrated the importance and method of estimating rough rice gross income and including it in GGE biplot analysis that identifies the highest income grossing genotype for a specific location.