Articles
Sustainable irrigation and nitrogen management of fertigated vegetable crops
Article number
1150_52
Pages
363 – 378
Language
English
Abstract
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.
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.
Authors
R.B. Thompson, L. Incrocci, W. Voogt, A. Pardossi, J.J. Magán
Keywords
crop monitoring, decision support systems, optical sensors, simulation models, soil analysis
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