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Agronomic Crops Network

Ohio State University Extension

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Precision Agriculture Technologies

Precision agriculture technologies provide multiple benefits to producers through input savings, improved time, labor and equipment management, and environmental benefits. Common precision agriculture technologies include these:

  • auto-guidance
  • variable-rate technology (VRT)
  • yield monitors
  • automatic section control (ASC) (Figure 12.1)
  • precision meters and downforce on planters
  • drones for scouting and spraying (Figure 12.2)
  • precision soil sampling
  • telematics or wireless connectivity on machinery

High-quality in-cab displays are standard in farm machinery, with most of these technologies coming already embedded on farm machinery being sold today. Other available technologies being used by a few farmers are crop sensors for adjusting fertilizer rates on-the-rate, detect and spray technology (e.g., John Deere’s See & Spray) for applying inputs only to weeds and not the entire field, as well as soil sensors that can adjust planting population and seeding depth on-the-go.

Guidance technology has proven to reduce overlap and input usage and can, on average, save approximately 10% of inputs. Additional benefits of auto-guidance systems include reducing the concentration time needed during driving farm machinery, leading to less fatigue and an increased ability to focus on other tasks. Automaticsection-control (ASC) technology, available for use on sprayers, planters, spreaders, and other application equipment, works by turning sections of application equipment on and off in areas where application has already occurred or off in unwanted areas, such as environmentally sensitive portions of the field like grassed waterways (Figure 12.1).

Figure 12.1. Automatic-section-control (ASC) technology on a planter

Figure 12.2. Drones can be used for spraying and scouting

Technologies such as auto-guidance and AutoSwath systems provide quick, tangible benefits, whereas other precision technologies (and site-specific practices) can offer paybacks but should be evaluated over several years. It can take time to evaluate and determine the value of particular site-specific practices, such as variable-rate fertilizer and seeding, for example.

Yield maps can be used not only to evaluate current and new management practices but also as a data source for development of site-specific management strategies, such as management zones, variable-rate seeding, and nutrient prescription maps. Yield maps have become a foundational spatial layer to evaluate and create annual fertilizer prescription maps for individual fields. Most precision-agriculture service providers today offer profit mapping within software where yield maps are converted to indicate profit, break-even and loss within fields. Further, the adoption of variable-rate technology (VRT) to vary inputs can provide additional savings and yield benefits to producers. Research has indicated that over time, VRT can provide about a 7% savings on phosphorus and potassium applications while being profitable for lime applications. Variable-rate seeding (VRS) in corn and soybeans is becoming more popular, providing either a small yield increase, seed savings, or both to farmers.

As-applied and as-planted maps are helpful in tracking input placement and input rates. Planter displays today can be used to determine—on a row-by-row basis, down to a single seed—where inputs are being placed. Using seed singulation and spacing data, an operator can verify the planter performance of seed and fertilizer placement across fields (Figure 12.3). Other forms of as-applied and planted data include downforce, planter speed, and multi-hybrid placement (Figure 12.4).

These maps can be used to monitor and verify input use, which can help limit excessive placement of seeds, nutrients, and other inputs, but can also trigger the farmer to monitor or adjust equipment, if needed, to continue operating in an efficient and accurate manner.

Figure 12.3. A singulation map indicates where skips, multiples, and good placement of seeds occurred during planting.

Figure 12.4. An applied downforce map shows how much downforce is being applied to the ground from the planter at a given time.

Today, precision technologies help farmers to more easily conduct on-farm research, providing the ability to evaluate inputs, practices, and other management strategies in order to determine value and most profitable return for their operation. For more information, see OSU Extension Ohioline fact sheet FABE–558, Precision Agriculture Tools for On-Farm Research (ohioline.osu.edu/factsheet/ fabe-558). Specifically, the increased development and use of apps have become a useful tool to many farmers. By utilizing apps designed for on-farm data logging, note taking, and research, farmers have the ability to take their data and results into their own hands, making decisions based on hard numbers rather than guessing and hoping for better yields next year. One example of an app designed to aid in on-farm research is Ohio State PLOTS (Figure 12.5). In addition to Ohio State PLOTS, apps like Precision Planting’s FieldView (Figure 12.6) assist the grower in smart scouting by allowing the user to log, store, and map data collected on a field-by-field basis. Learn more about the PLOTS App at agcrops.osu.edu/newsletter/corn-newsletter/2016-31/ ohio-state-plots-here-download-it-today.

Figure 12.5. Ohio State PLOTS, an all-in-one on-farm research support app

Figure 12.6. The FieldView note-taking screen allows the user to place georeferenced pins within a field and take scouting notes and images at each location.

Another precision agriculture technology that aids growers in crop production is the use of aerial imagery for decisionmaking. Imagery options that include thermal, bare soil imagery, normalized difference vegetation index (NDVI), and absolute difference NDVI (ADVI) can be used alone or collectively to support on-farm decisions. For example, Figure 12.7 shows how NDVI imagery was used to remedy an in-field issue with a clogged sprinkler on a pivot irrigation system. By looking at various images of fields throughout the growing season, growers can make realtime management decisions, or decisions that will have an impact on subsequent cropping seasons. Remote sensed imagery is also being used to direct in-season scouting of crops by consultants, leading these people more quickly to problematic areas or different crop conditions within fields.

Figure 12.7. Normalized Difference Vegetation Index (NDVI) imagery from midseason shows a clogged center pivot irrigation system. Upon noticing the heavy red streaking (low vegetative density) in the field, the grower was able to assess the situation and remedy the problem (plugged sprinkler).

Among the several benefits, precision agriculture technologies provide means to simply set up and execute on-farm research, providing valuable feedback to the farm operation. While PA technologies and practices can feel overwhelming and time-consuming to adopt, newcomers should take it slow and adopt new technologies at a comfortable pace.