The challenge with these types of maps is they can be rather difficult to build correctly. An accumulative group of errors coming from a variety of components such as GPS system accuracy limitations, use of multiple reaping machines about the exact same areas (Multiple production screens), and time delays on data capture due to hardware capacity, can drive the margin of error exponentially even to the point of rendering it useless. This is why having a suitable process for minimizing errors during data capture, and where the posterior filtering of data that is suspiciously out of place (Outliers) become vital actions.

1. precision agriculture the greatest thing
It is most likely that in case you are directly associated with the Precision Agriculture world at
some point you have discovered about precision agriculture. Just like the tablet computers now,
or the Macarena in the 1990s, precision agriculture is the fact that ineluctable thing that
everybody is talking about and with good reason. Having a guarantee of radically increasing
productivity by integrating 21st century agriculture technology to the farm, one can not help but to
get excited about all the potential advantages. And since precision agriculture relies on improved
on-board computing systems it is possible to expect tomorrow's tractors to more closely resemble
the car than your dad's John Deere from Knight Rider.
The assumption is straightforward; since terrains are not uniform in most of these measurements
such as soil composition, nutritional needs, crop yields, and pest/disease presence, then the
traditional custom of treating them uniformly is hardly perfect. Of course that is too large a task for
people to do with since it demands collecting and examining countless pieces of data. That is
where technology comes into play using a variety of innovative technologies such as GPS
systems, yield monitors, variable speed applicators, and geospatial statistical evaluation software.
Earth composition and production maps
Just like with any successful scientific effort, data that is accurate is required by a great precision
agriculture procedure. A good place to begin is generally by generating production maps and
earth composition of the blocks you would like to analyze. These maps represent the large
numbers of samples which will be the basic input for geospatial statistical analysis software that
can create recommendations for different processes including sowing density, fertilization, and
pest/disease management.
The trouble with these types of maps is that they can be rather difficult to construct right.
Variable rate applications
Their rationale lies behind the fact since we're not using optimal agricultural strategies for each
specific website, then the maximum potential of fields has not yet been reached by attempting to
maximize production, and substantial gains can be achieved. On the opposite side of the fence
we've specialists who believe that due to the fact that a very high level of production has been
accomplished on most harvests, potential gains in production due to site specific management of
fields are marginal and not worth pursuing. The focus of the specialists instead is centered in cost
cutting by reducing waste and over use of agricultural supplies (Seeds, fertilizers, pesticides,
etc.). What one've detected is that actual Precision Agriculture savvy farmers in many instances
have a posture that sits half way between both camps, and so address each subject as a unique
instance that should be medicated individually to determine the best approach.