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Agronomic Crops Network

Ohio State University Extension

CFAES

Benefits of Precision Agriculture

AutoSwath technology provides an average overlap reduction of 4.3%. When AutoSwath is paired with auto-guidance technology, overlap reduction can range from 3% to 35% (on a per-field basis). These savings are dependent upon field size and shape, with higher benefits occurring in large, irregularly shaped fields or fields containing conservation management structures, such as grass waterways and terraces. Moreover, implementing AutoSwath or row-by-row on/off control on planters can further provide yield and harvest loss advantages in corn. Average yield loss across doubleplanted areas can be 17% less in corn with a harvest loss factor of 8.7X in those same double-planted areas. A properly adjusted combine will nominally have a loss of 1 bushel per acre, so double-planted areas could have an 8.7-bushels-per-acre harvest loss.

Additionally, machine data combined with yield data can be used to make crop production decisions, especially in subsequent cropping years.

Bringing the agronomic and machine data together could change decisions about hybrid selection. According to the information in Figure 12.8, Hybrid A demonstrated about a 5-bushels-per-acre advantage; it was a green-stem variety requiring more fuel and engine load to harvest. When determining which Hybrid (A or B) is a better choice, it is important to consider additional costs, such as fuel and engine load. While Hybrid A showed the higher yield, after factoring in additional costs, Hybrid B may have been the better choice for maximum return on investment.

Figure 12.8. A comparison of two hybrid soybean varieties and their respective fuel use, engine load, and field capacity information during harvest is shown

Capturing machine data today through precision agriculture technology makes this type of analysis much easier and begins to provide a richer decision-making environment that also include profit maps (Figure 12.9).. This example also shows how precision agriculture data could begin to help farmers with decisions and thereby add value back to their farm.

Figure 12.9. Profit map indicating profit and loss across a field