Abstract
Improvement in water use efficiency of crops is a key component in addressing the increasing global water demand. The time and depth of the soil water monitoring are essential when defining the amount of water to be applied to irrigated crops. Precision irrigation (PI) is a relatively new concept in agriculture, and it provides a vast potential for enhancing water use efficiency, while maintaining or increasing grain yield. Neutron probes (NPs) have consistently been used as a robust and accurate method to estimate soil water content (SWC). Remote sensing derived vegetation indices have been successfully used to estimate variability of Leaf Area Index and biomass, which are related to root water uptake. Crop yield has not been evaluated on a basis of SWC, as explained by NPs in time and at different depths. The objectives of this study were (1) to determine the optimal time and depth of SWC and its relationship to maize grain yield (2) to determine if satellite-derived vegetation indices coupled with SWC could further improve the relationship between maize grain yield and SWC. Soil water and remote sensing data were collected throughout the crop season and analyzed. The results from the automated model selection of SWC readings, used to assess maize yield, consistently selected three dates spread around reproductive growth stages for most depths (p value < 0.05). SWC readings at the 90 cm depth had the highest correlation with maize yield, followed closely by the 120 cm. When coupled with remote sensing data, models improved by adding vegetation indices representing the crop health status at V9, right before tasseling. Thus, SWC monitoring at reproductive stages combined with vegetation indices could be a tool for improving maize irrigation management.
Highlights
An accurate understanding of soil water content behavior is important for soil hydrological research in areas, such as irrigation scheduling and site-specific agriculture [1]
The transformation of the Neutron count ratios (NCR) values improved the explanation of the yield variance, and were polynomial transformation of the NCR values improved the explanation of the yield variance, and used as inputs for further analyses
From the correlation analysis between single Neutron probes (NPs) readings and yield values, there was a trend consisting of higher correlation (r2 of 0.71 at Day of the year (DOY) 240) after tasseling
Summary
An accurate understanding of soil water content behavior is important for soil hydrological research in areas, such as irrigation scheduling and site-specific agriculture [1]. Part of the solution for sustainable productivity is the improvement of water use efficiency. It is important to irrigate when the yield response to water is at maximum. Plant water use efficiency (WUE) is defined as the amount of carbon gained per unit of water and used on a unit of land area [2]. The impact of a water deficit on the WUE varies throughout the growing season depending on how sensitive the crop is at that specific growth stage. Both, the amount of water availability, as well as the timing of water availability, are critical
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