5 research outputs found

    Random Forests for Global and Regional Crop Yield Predictions - Fig 1

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    <p><b>Study regions: global wheat mega-environments (A), US maize producing counties (B), and northeastern seaboard region (NESR) (C).</b> All 12 wheat mega-environments are shown with different colors (A). Maize grain yield by the US counties in 2013 surveyed by USDA-NASS is visualized using different shades with darker shades representing higher yields (B). The NESR includes 433 counties of Connecticut, Delaware, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, and West Virginia. The red dots indicate the location of the data points, where weather stations exist. Point type data was used for this region (C).</p

    Random Forests model performance for test datasets.

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    <p>Observed vs. predicted plots are shown for four case studies: (A) global wheat grain yield, (B) US maize grain yield over 30 years, (C) potato wet tuber yield in northeastern seaboard region (NESR), and (D) maize silage yield in NESR The dashed lines indicate 1:1 relation and the solid line represents linear regression between the observations and predictions made for test datasets. The linear regression equation for the solid line is provided along with <i>RMSE</i>, <i>EF</i>, <i>d</i>, and Pearson’s <i>r</i>.</p

    Partial dependence plots for the top ranked predictor variable from variable importance measures of Random Forests models.

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    <p>(A) N fertilization rate (NFERT) in global wheat grain yield predictions, (B) year (YR) in the 30-year US maize grain yields, (C) Latitude (<i>lat</i>) for potato wet tuber yields in northeastern seaboard region (NESR), and (D) <i>lat</i> for maize silage yield in NESR. The <i>Y</i>-axis of each plot indicates the average of all of the possible model predictions for the <i>X</i> predictor value. The <i>X</i>-axis hash marks indicate deciles.</p
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