Remote Soil Sensing Enhances Precision Farming, Promotes Nutrient Use Efficiency

Remote Soil Sensing Enhances Precision Farming, Promotes Nutrient Use Efficiency

Precision agriculture management requires understanding soil at increasingly finer scales. Conventional soil sampling and laboratory analyses often lack this granularity and can be time consuming and expensive. Remote soil sensing overcomes these shortcomings. Through its collection of spatial data with quicker, cheaper, and less laborious techniques, remote soil sensing has the opportunity to enhance precision farming today.

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More and more companies are offering remote soil sensing programs. For example, Persistence Data Mining’s platform uses remote sensed hyper-spectral imaging to map soil nutrients with a consistently calibrated remote sensor. The technology creates a Normalized Difference Elemental Index (NDEI) map from the imagery. The NDEI relates the reflectance in the near-infrared (NIR) region and short-wave infrared (SWIR) to determine concentration of total nitrogen, phosphorous, potassium, organic matter, and pH.

Remotely sensed imagery of soil offers an attractive alternative to standard soil sampling methods for many reasons. Remotely sensed prescription maps are not affected by inaccuracies inherent in chemical wet lab processing. In-field testing reduces the soil respiration that changes chemical composition during transport and processing. A remote soil sensing program’s correlation analysis shows a significant reduction in user error in the care of samples and sample taking methodology. Further, the imagery data enables uniform sampling across soil types and textures. In addition, derived regression equations, used to estimate soil macronutrient concentrations, have the potential to predict secondary and micronutrients for more precise fertilizer applications.

The remote soil sensing data can be used to develop variable rate nitrogen, phosphorus, and potassium application maps. Farmers achieve fertilizer savings of $15 to $40 per acre using systems such as Persistence Data Mining, as well as 10% to 15% yield increases. These types of systems are also environmentally effective in reducing fertilizer over-application, which leads to runoff and leaching into ground water.

The ag retail sector’s commodification is creating an increasingly flatter environment. We now have the opportunity to replace the weak net margins that commodities generate with creative value-added systems. Persistence Data Mining’s technology is one of those promising value-added systems that wil help you obtain strong net margins. Companies can be successful in a flat environment by enabling their customers with these effective technologies. Those who create value through leadership, collaboration, and creativity will transform the industry.

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Normalized Difference Elemental Index (NDEI) – Wow.. N, P, K, OM and pH? from a soil surface scan? Have not heard that NSEI had the chops to be able to discern this level of detail? I have heard lots about N estimation with this method ie GrenSeeker but never for pH and OM. Please send more information….