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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #358462

Research Project: Improving Irrigation Management and Water Quality for Humid and Sub-humid Climates

Location: Cropping Systems and Water Quality Research

Title: Site specific crop management

item Vories, Earl - Earl

Submitted to: Mid America Farm Grower
Publication Type: Experiment Station
Publication Acceptance Date: 8/8/2018
Publication Date: 8/17/2018
Citation: Vories, E.D. 2018. Site specific crop management. Mid America Farm Grower. 38(33):21a.

Interpretive Summary:

Technical Abstract: Several types of soil and crop sensors are available to aid producers with managing their crops. However, requirements for proper installation and operation, and appropriate interpretation of the results have combined to limit widespread use of many systems. As both the sensor hardware and software improve, the goal of site-specific crop management continues to become more realistic. Images from sensors mounted on satellites are available for purchase; however, clouds can impact the quality of the image and the resolution is generally a function of the cost. With a satellite-based image of normalized difference vegetation index (NDVI) from a cotton field at the Marsh Farm, trends are evident, but more detail is needed for most site-specific management decisions. Using sensors mounted on a center pivot system, the resolution from the individual sensors is much higher; however, the user must interpolate the values for the large areas between the sensors. Adding more sensors or mounting the sensors on a sprayer or other equipment will improve the estimates, but for most practical applications there will always be gaps. On highly variable soils, figuring out what was going on in between the individual sensor passes can be complicated. With sensors mounted on an unmanned aerial vehicle (UAV, or drone), the resolution is high and the whole field was sensed; however, a great deal of skill and computing time was required to “stitch” the data from the individual passes by the UAV into a complete field image. Finally, soil moisture sensors are commonly recommended for making decisions about when to irrigate. Many kinds of sensors are available for a wide range of costs and precision. Measurements were made from the same cotton field discussed earlier from early July through September of last year using time-domain reflectometry (TDR) sensors and granular matrix sensors (GMS). Both types provide much insight into the soil moisture status; however, interpretation of the data from either type is complicated on our highly variable soils.