Journal of Taiwan Agricultural Research

Author:Yuh-Jyuan Lee, Chwen-Ming Yang*, and Chiao-Ling Hsiao

Abstract:

    This study was conducted at Agricultural Research Institute Experimental Farm, Wufeng, Taichung, Taiwan to study effects of climatic conditions on yield of rice (Oryza sativa L. cv. TNG 71).  Rice was transplanted in paddy fields every month from December 2007 to January–August and November 2007 to determine effects of different planting dates on grain yield.  Weather data used for analyses were seasonal accumulated values of daily mean air temperature (A_DMAT), daily irradiance (A_IR), daily sunshine hour (A_DSH), daily precipitation (A_DP), and daily evaporation (A_DE).  Results from correlation matrix between pairs of climatic variables indicated that, in Wufeng, Taichung, A_DMAT was positively correlated with A_IR (r = 0.976***) and A_DSH (r = 0.764**), A_DSH was positively correlated with A_IR (r = 0.785**) and A_DP was negatively related to A_DSH (r = -0.691*).  Both fresh grain yield (FGY) and dry grain yield (DGY) were negatively correlated with A_IR, A_DMAT, and A_DSH.  The correlation coefficients (r) for A_IR, A_DMAT and A_DSH were -0.801**, -0.700* and -0.716*, respectively, for FGY, and were -0.813**, -0.724*, and -0.758*, respectively, for DGY.  Results of multiple linear regression (MLR) analyses between climatic variables and yield-related parameters, including production index (PI), harvest index (HI), fresh grain yield, and dry grain yield, showed that A_IR and A_DMAT were the two weather variables affecting PI (R2 = 0.822, P = 0.002) and HI (R² = 0.823, P = 0.002), whereas A_IR, A_DMAT and A_DE were the three weather variables affecting FGY (R² = 0.814, P = 0.013) and DGY (R² = 0.810, P = 0.014).  This study suggests that A_IR, A_DMAT, and A_DE are the three most critical climatic variables in determining yield of rice cultivar TNG 71 in Wufeng, Taichung, Taiwan.

Key words:Rice, Oryza sativa L., Climatic variables, Yield, Multivariate regression analysis, Multiple linear regression model

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