Sustainable irrigation and nitrogen management of fertigated vegetable crops.

Fertigation in combination with drip irrigation is being increasingly used in vegetable crop production. From a nutrient management perspective, this combination provides the technical capacity for precise nitrogen (N) nutrition, both spatially and temporally. With these systems, N and other nutrients can be spoon-fed to crops, through frequent applications of small amounts, to the immediate root zone as required by the crop. In commercial farming practice, management of combined drip/fertigation systems generally does not take advantage of this potential for precise N management. As is common in commercial farming, management of both irrigation and N with drip/fertigation systems is generally based on growersRSQUO experience, with the objective of avoiding deficiencies that may limit production. Because of frequent N application, the established improved nutrient management strategies, based on infrequent soil testing, pre-plant and one or two side-dress applications, are of limited value. With drip/fertigation, dynamic N management approaches are required so that the capacity for frequent small applications can be fully exploited to provide (a) site and season specific management and (b) dynamic responses to temporal N requirements. Dynamic irrigation management is required for the same reasons. Modelling and monitoring approaches and combinations of the two enable exploitation of the technical capacity for precise N and irrigation management. Decision support systems (DSS) based on simple simulation models with limited data inputs can provide crop specific plans of daily N and irrigation requirements. The use of soil moisture sensors is an effective and proven monitoring approach for irrigation management. For monitoring of soil/crop N status, soil monitoring through regular sampling of soil-water extracts and soil solution is being used, and crop/plant monitoring approaches such as with proximal optical sensors and petiole sap analysis are promising methods.