Abstract
Smart irrigation is one application of digital agriculture that can be used to achieve improved crop yields while saving water and energy. Many variations of smart irrigation can be applied, but there is no consensus among the scientific community as to which method is the best practice. The objective of this research was to evaluate two smart irrigation methods: a soil moisture–based method using sensors and an evapotranspiration- (ET-) based technique. The selected crop was sweet corn. Growth variables (biomass, yield, harvest index, and water productivity) were compared for each of the two methods. Three irrigation regimes were applied for each method: 60%, 90%, and 120% of crop evapotranspiration (ETc) for the ET-based method, and 25%, 30%, and 35% of the total soil moisture for the soil moisture–based method. Corn sap flow was measured in response to the three treatments in the soil moisture–based experiment to measure transpiration. The results showed that the ET-based method is easier to implement with less infrastructure, and it can result in similar yields compared to the soil moisture–based method. Although the fresh yield was 16% higher using the soil moisture–based method, grain yield can be sustained with the ET-based method using 8% less water. Selection of an appropriate irrigation scheduling method should be based on marketable yield: keeping the soil water content near field capacity will result in a higher fresh yield but will not translate into more dry matter. If grain yield is the target, the ET-based method is less expensive and more farmer friendly, but care should be taken to properly estimate irrigation losses to avoid underirrigation. An evaporative stress index (determined using sap flow measurements) of 70% will cause a 22% reduction in fresh sweet corn yield but only a 7% reduction in grain yield. Transpiration peaked when the soil moisture was above 85% of the available water (i.e., at 38% in the calcareous clay soil of the experiment).
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