In agriculture, yield mapping is a method that uses GPS data to assess factors, including farm/crop yield and moisture levels in a particular field. It may also be referred to as yield monitoring.
It was created in the 1990s and used a mix of GPS and tangible sensors such as speedometers to monitor farm yields, grain elevator performance, and combine speed all at the same time.
Meanwhile, monitors of yield are a vital component of many different site-specific management strategies. Yield maps, also known as yield monitors’ visual and analytical outcomes, inspire innovative research and may offer trustworthy answers to properly executed on-farm experiments.
Yield monitors (also known as yield gages) measure the amount of crop produced. The feedback provided by yield maps allows for determining the impacts of controlled inputs like fertilizer & lime, seed & pesticides, and artistic techniques like tillage, irrigation, and drainage.
When utilized in conjunction with a combine that is also fitted with a differentially-corrected global positioning system (DGPS) receiver, a yield monitor is at its most effective.
The yield monitor data system concurrently records yield, grain moisture, and position data. These are the fundamental crop yield data that are required to make yield maps.
A yield map will include a variety of colors and shades, and each one will reflect a diverse range of productivity or crop production. Yield maps help gain a more excellent knowledge of the magnitude and position of yield variability within a field.
Investigating the qualities of the soil and the field’s other aspects should be done since there are patterns of variability. “Yield maps validate the recollections that you should have had” is a phrase that has been repeated several times.
What is Yield in Agriculture?
The quantity of seeds or grains that may be harvested from a particular land area is referred to as the yield. The most common units of measurement for it are kilos per hectare or bushels per acre.
Using an indicator such as the average farm yield per acre helps examine a farmer’s agricultural production on a specific field over a certain length of time.
Because it represents the outcome of all of the labor and resources put by agrarians in the growth of plants in their fields, it is regarded as perhaps the most essential gauge of each farmer’s competence.
A permanent and visible record of the harvested yields may be provided through yield maps. On the other hand, the variability in yield from a single year does not give sufficient information to identify long-term patterns in productivity.
During the analysis process, it is necessary to consider variables such as the fertility of the soil, the amount of rainfall, and the weed pressure.
Ensure you save the raw crop yield data used to create the maps in at least two different secure locations.
Although you have previously created a map, you may need the original data again while either implementing new management and decision-making software or updating computer systems.
As more years of data become accessible, there will be more confidence in comprehending the factors that produce variability, and the value of historical data will skyrocket.
The examination of long-term production records may help evaluate the productivity and viability of soil and the suitability of the cultural methods employed to cultivate a crop.
Even while variations in soil types or soil qualities are often the cause of yield variance within a field, weather patterns typically significantly influence variability.
The first three to five years of yield data collection should be deemed to have limited significance since not enough information will have been gathered to account for the variability in yield caused by weather.
How Is Farm/Crop Yield Calculated In Agriculture?
Typically, farmers would count how much of a specific crop has been harvested from a particular area before estimating the crop’s yield. After that, the crop that has been gathered is given a weight, and the crop yield of the whole farm is projected from that sample.
Suppose a wheat farmer recorded 30 heads per foot squared, and each head included 24 seeds. Now, if they assumed that 1,000 kernels weighed 35 grams, then the yield approximated using the simple method would be 30 times 24 times 35 times 0.04356, which equals 1,097 kilograms per acre.
Again, remember that this estimate is based on the assumption that the weight of 1,000 kernels is 35 grams. In addition, since one bushel of wheat weighs 27.215 kilograms, we calculated that the expected yield would be 40 bushels per acre (1097 divided by 27.215).
The term “crop yield” may also refer to the number of seeds produced by the plant. For instance, if one grain of wheat resulted in three other grains of wheat, the yield would be 1:3. “Agricultural production” is also sometimes used interchangeably with “farm/crop yield.”
Note: In a global economy, this data is essential to determine whether or not the crops that are grown will sufficiently offer food for a state’s food supply, animal feed, and energy sources.
Farm/Crop Yield Data Features
Here we discuss some of the significant farm yield data features.
The More Comprehensive Analyses
To carry out multi-layer analysis, you must first compile numerous layers of data into a single map and then search for connections between the various data layers.
It should be possible to produce combined productivity zones by using vegetation indices derived from satellite images, topography, and data from equipment, including yield, electrical properties, moisture levels, and others, as well as the findings of agrochemical analysis and 3D maps.
Automatic Visualization
To provide a better comprehension of the field’s variability and the development of management zones, the raw crop yield data should have been transformed into a gradient uniformly distributed picture.
Each of the yield file characteristics may be seen in graphical form, including moisture, yield mass, yield volume (wet and dry), downforce, fuel consumption, etc.
Correction of Raw Data
A unique point in the field may get smoothed out (for instance, working over a portion of the combined header that is less than its whole width). You should be able to adjust isolated zones and polygons while producing farm yield data based on zones.
Construction of Prescription Maps
Prescription maps give input rates for specific zones of a field. These maps are derived using various spatial data, like soil nutrient concentrations and historical yields.
Closing Remarks
It is only possible to illustrate yield variability via yield maps. Their accuracy is only as good as the data used to create them. To collect reliable data, monitors need to have their settings properly configured and be reviewed often.
To understand the factors that contribute to variability, the crop yield data from maps, along with those from soil tests, scouting notes, and other observations, should be utilized.
Farmers are equipped with the information necessary to make better management choices, which have a good impact on the environment and result in increased production and profitability. This knowledge may get achieved via site-specific crop management.
