Abstract

DEL VALLE-MORENO, Juan et al. Estimate of Rice Crop Yield (Oryza sativa L.) in Function of Different Climatic Variables. Rev Cie Téc Agr [online]. 2020, vol.29, n.3, pp. 97-102.  Epub Sep 01, 2020. ISSN 2071-0054.

The definition of regression models for estimating the productivity of irrigated rice arises from the analysis of the relationship between the decrease in rice crop yields (Oryza sativa L) and climatic variables in certain fixed growth periods. For this reason, this work was intended to estimate the crop yield of irrigated rice varieties based on different climatic variables. Crop yield data were taken from experimental trials conducted by the Grains Territorial Research Station Sur del Jíbaro (belonging to the Grain Research Institute). Further, in the grain ripening phenophase, data on climatic variables were collected: air temperature (maximum, minimum, average) and relative humidity. The statistical processing was executed in the SPSS software version 21 on Windows by means of the multiple linear regression analysis (stepwise method) and once the regression equations were obtained, the estimation of the crop yield by interpolation was executed. The results showed that the variables air temperature and relative humidity have a significant effect on the crop yield of rice in Cuba and with the increase in the temperature by 1 ° C of the maximum and minimum temperature, there are effects that range between 4% and 11% in rice crop yield.

Keywords : climatic change; crop forecasting; regression analysis; stepwise regression.

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