A multiple regression model for predicting groundnut (Arachis hypogea L.) yields in arid zones using weather parameters. (477)
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Keywords

Multiple regression model
Groundnut
Arid zones
Weather parameters

How to Cite

A multiple regression model for predicting groundnut (Arachis hypogea L.) yields in arid zones using weather parameters. (477). (1998). Tropical Agriculture, 75(4). https://journals.sta.uwi.edu/ojs/index.php/ta/article/view/1619

Abstract

The weather parameters used in developing a simulation model for predicting groundnut (Arachis hypogaea L.) pod yields under rainfed conditions were total rainfall (mm), total number of rainy days, total number of dry days, and maximum and minimum temperatures (°C) for the period from pod development to maturity. A comparison of simulation and observed pod yields of groundnut in 1992 and 1993 showed that a multiple regression simulation model can be used to estimate the pod yields under rainfed conditions with a reasonable degree of accuracy even before crop harvest. A close relationship between pod yields and weather parameters was established (R2 = 0.93). A simulation model was developed with the data for 1992 and 1993 and the model was found to be a suitable fit for the arid region of Anantapur.
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