Abstract:
The current level of sophistication of irrigation scheduling technology is impressive.
However, the utilization of these methods, at least among vegetable growers in the U.S., is extremely low.
This is true even for regions with well-established education and implementation programs.
Although there are some exceptions, adoption of irrigation scheduling technology has in general lagged behind adoption of other new crop management technologies introduced within the past 20 – 30 years.
If we are to improve the situation, it is imperative that the scientific community investigate the primary causes of this under-utilization.
Irrigation research has traditionally focused on agronomic crops, grown in arid environments, and on homogeneous soils.
Unfortunately, scheduling methods derived from this research are impractical for the vast majority of vegetable growers throughout the world.
One reason is the complex cropping pattern of most vegetable farms, and a relatively small land area devoted to any specific crop-planting date-soil combination.
Also, most agronomic models focus on biomass production and harvest index, but mild stress effects on quality and early yield are of primary economic importance for many vegetable producers.
For those in humid regions, rainfall immediately after an irrigation can have negative economic and environmental effects by causing flooding and/or excessive leaching of fertilizers and pesticides.
In the future, more growers will be utilizing microcomputers and/or consultants in their farm operations.
This may help in the implementation of weather-based or electronic sensor-based scheduling methods, particularly if linked to other crop management software.
Ease of use should be the highest priority in future software development.
Recently marketed ceramic soil moisture sensors and evaporation atmometers show improvements with regard to reliability and maintenance requirements, but more field testing will be required.
More basic research is needed in the area of economic and environmental risk assessment associated with rainfall probability, leaching potential, and short-term stress effects on fruit quality and crop maturation.
This information could be incorporated into decision algorithms of scheduling programs, and also be used to inform growers of the costs and benefits of various water management strategies.
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