Knowing the historical yield patterns of major commodity crops, including the trends and interannual variability, is crucial for understanding the current status, potential and risks in food production in the… Click to show full abstract
Knowing the historical yield patterns of major commodity crops, including the trends and interannual variability, is crucial for understanding the current status, potential and risks in food production in the face of the growing demand for food and climate change. We updated the global dataset of historical yields for major crops (GDHY), which is a hybrid of agricultural census statistics and satellite remote sensing, to cover the 36-year period from 1981 to 2016, with a spatial resolution of 0.5°. Four major crops were considered: maize, rice, wheat and soybean. The updated version 1.3 was developed and then aligned with the earlier version 1.2 to ensure the continuity of the yield time series. Comparisons with different global yield datasets and published results demonstrate that the GDHY-aligned version v1.2 + v1.3 dataset is a valuable source of information on global yields. The aligned version dataset enables users to employ an increased number of yield samples for their analyses, which ultimately increases the confidence in their findings. Measurement(s) yield trait Technology Type(s) satellite imaging • digital curation • computational modeling technique Factor Type(s) year of crop yield data collection Sample Characteristic - Environment area of cropland Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.11903277
               
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