Precision Irrigation Method for Oil Crops Based On-demand: A Case Study of Peanuts

In the field management of oil crops such as soybean and peanut, the supply and demand of water and fertilizer are not synchronized, and the decision-making of water and fertilizer application is not accurate, which seriously affects the yield and quality of oil crops. Therefore, a precise irrigation method based on-demand for oil crops has been proposed to achieve dynamic water and fertilizer regulation during the growth process of oil crops. An estimation model for soil relative moisture content at different depths of regional plots was constructed. Through real-time monitoring of meteorological data and combined with each irrigation data, daily estimation of soil relative moisture content at different depths of regional plots was achieved. Taking peanuts as an example, based on the daily relative soil moisture content, weather forecasts and historical meteorological data were integrated to dynamically develop irrigation and fertilization plans for future oil crop growth processes. The results showed that the constructed model for estimating the relative soil moisture content solved the problem of single monitoring point being difficult to represent the soil moisture content of regional plots, and improved the accuracy of irrigation decisions based on the relative soil moisture content of regional plots. Based on the estimation model of relative soil moisture content, the precision irrigation method for oil crops proposed in this article could provide theoretical support and technical means for the precise application of water and fertilizer in field management of oil crops.