Multi-Year Study Maize Agrivoltaics Soil Moisture and Maize Information

<p>Soil moisture data is an important feature for agronomic work, and it speaks true for agrivoltaic work as well. This research specifically attempts to link spatial location of shading with changes in soil moisture. However, for a couple of years, the soil moisture data had to be approximated due to lack of/missing data. To do so, a multiple fold Bayesian Regularization Neural Network had to be employed to extrapolate the limited data we had from the latter end of the growing seasons in 2020 and 2021 to the beginning of the seasons. In this repository, one may find the original data, the volumetric water content collected from sensors used on the field. Additionally, the data used for training and extrapolation, which is climatic data downloaded from NREL's NSRDB: National Solar Radiation Database site (https://nsrdb.nrel.gov/). The coordinates were those of the Purdue's Agronomy Center for Research & Education (ACRE) farm with 2 sq.km resolution for the duration of the growing period for each year at an hourly time resolution. While NSRDB gives information for the whole growing season, only the time interval which encompassed the season was used for these data. The variables include: DHI, DNI, Dew Point, Surface Albedo, Wind Speed, Relative Humidity, Temperature, Pressure, GHI, Cloud Type, Solar Zenith, and Precipitable Water. Lastly, the calculated data for the full growing season will be found.</p>

<p>With V.2 out, this will include the plot, location, yield in both bu/acre and kg/ha, height in cm, the silking date and the silking-anthesis interval. These are relevant results to see how the treatment of the experimental setup impacted various crop parameters within an agrivoltaic setting.</p>