Some common types of data in crop farming
There are many different types of data related to crop farming, but some of them are more common that other. In this Agtech Letter we walk you through some of the areas where data is available together with examples of what can be measured.
Briefs about data and how its used
In this and some following Agtech Letters, we will give examples and list some of the most common types of data related to crop farming. Furthermore, we will also divide them into categories to create a structure around data and how to approach the task of bringing order to your crop farming data. The purpose is to give you a good intuition on what types of data that are available, and to highlight important aspects with different types of data.
Crop farming is a farming business that generates huge amounts of data, both on the farm and by other stakeholders in the food agri-food industry. As a farmer, you can use the available data to make smarter decisions to make the operations more efficient and effective. Even if the goals for each farmer is probably quite unique, but from a economical point-of-view it more or less always comes down to achieving a high-yielding and resilient crop while spending as little as possible on inputs, wages, and other costs. It’s simply the classical optimization problem of maximizing profits while keeping the operational risks at an acceptable level. Data is one of the cornerstones in solving this optimization problem from one day to another.
Data collected in crop farming operations are often stored and managed in a Farm Management Information System, or FMIS in brief. We won’t go in to details on FMIS in this Agtech Letter, but we simply note that they are a good tool for creating structure in your farm data and there are lots of good alternatives available on the market today. The details are left for a future Agtech Letter or Agtech Deep Dive.
The first data category is SOIL & FIELD
A common category of crop farming data is all information about the fields and the soil used for producing crops. This information could be as simple as the field’s name and borders, but data that is much more complex than this is also common. In this Agtech Letter we list some of types of data that be believe are both fairly common and could provide you with lot’s of good insights into your field and farming conditions.
Soil texture
The soil consists of different fractions, or collections, of particle sizes ranging from very fine dust to larger sand particles. There are several international systems for determining soil texture, but some common ones use the fractions clay, silt, and sand. By measuring how much of each fraction the soil consists of it is possible to compute a categorical soil texture such as “clay”, “sandy clay”, “loam”, “silty clay loam”, and several others.
Nutrients
The soil contains several different nutrients that are necessary for the crop to grow. It’s quite common to collect data on nutrient levels for macro nutrients such as phosphorous (P) and potassium (K), but also data for micro nutrient such as sulfur (S) and magnesium (Mg) can be collected using soil sampling techniques where soil is collected at different positions on the field and analyzed by a specialized laboratory.
Drainage
A field that have a suitable drainage system in good shape will be set for a high-yielding and drought-resistant crop, whereas a failing drainage system will make the crop much more affected by the crop season weather. Collecting data about the drainage system is useful for analyzing crop yields and plan for new drainage.
Soil organic matter
The soil contains organic material from earlier crops, vegetation, and other decayed organic matter. The content of soil organic matter is an important parameter in for example fertilization planning, but also when choosing crop, variety, and tillage methods. A use-case for this type of data that is more common today is carbon credits for storing carbon in the soil. Hence, data on soil organic matter can be important to your farming operations.
The second category is CROP
The next important category of crop farming data is the ones directly related to the crop itself. Examples include the type of crop and the variety, but also more detailed data can be collected on a regular basis to aid in the decision making. In this Agtech Letter we list some of the important types that are also fairly common.
Yield data
Data on how much yield that each field is producing has been collected ever since farming started, but with today’s technology it is possible to get precise measurements with high resolution. Common resolutions used today are ranging from storing the total amount of yield from the complete farm, to creating high-resolution yield maps from the GPS logging system in a modern combine harvester.
Biomass
The biomass of a crop can be seen as a measure of how lush and healthy a crop is, and often the biomass data can be related to other parameters such as nitrogen uptake and yield potential. How well the parameters are related and correlated varies, but nevertheless data about the biomass of the crop is important for decision about how to manage the crop during the season.
Pest and diseases
The crop can be affected by different pests and diseases during the crop season. By collecting data about the existence and amount of pests and diseases, it is possible to make data-driven decisions on what actions to take to protect the crop. Furthermore, it can also be used to analyze the effects of a treatment and plan for the next crop season by taking the diseases into account.
Weeds
Data about what types of weeds are found in the field, how much weeds there are, and when it starts to grow can be used to become more precise in your weed treatments. By collecting data over several years it will be possible to determine a good strategy for weed treatment based on data.
The third category is ACTIONS & INPUTS
The third category collects data that are related to the different actions and inputs that are applied to the crop during the season. This category includes many different types and here we list some of them to illustrate.
Soil tillage
Information about what types of tillage application that has been made, with what parameters, and when it was done are all important data to consider when making decision about the crop farming. Furthermore, it is also important when analyzing the crop production, and when reporting to government agencies and other stakeholders.
Seeding & Planting
Data about the seeding and planting, such as seed rates, seed depth, and seed date are all important to analyze and plan your crop farming. Together with other types of data such as weather data, it is possible to for example evaluate the effects of precipitation and soil temperature for the establishment of the crop.
Fertilization
Collecting and storing data on all fertilization applications that has been done on a field is directly useful to keep track of the total amount of nutrients applied to the crop during the season. But it is also important to be able to analyze and follow the effects from fertilization on the achieved crop yields.
Treatments
In many parts of the world there are regulations on what treatments that are allowed, when they are allowed, how much inputs that are allowed to use, and more. Hence, collecting data about treatments are necessary to comply with regulations, but the data is also useful to analyze effects of inputs and plan for the next crop season.
The fourth category is EXTERNAL FACTORS
The fourth and last category covers all external factors that are affecting the crop production directly or indirectly. We present some of the types to illustrate what we consider external factors, but this category includes many types.
Temperature
The air temperature is one of the most interesting external factors related to the weather, and the availability of reliable and high-quality temperature data on a farm can be used to decide on timing of inputs, estimation of risks for pests and diseases, etc.
Precipitation
As for temperature, the precipitation is also one of the most important external factors related to the weather. Both the amount of precipitation and the timing are important to know about to plan coming actions for fertilization, irrigation, and similar.
Crop damages
Many crop farmers experience more or less damages on crops from wild animals such as wild boars, deers, and geese. Collecting data on the crop damages to quantify and report the damages can be used both for planning actions to mitigate the problem, but also to get refunds from insurances or lower land rents.
Market prices
Optimizing your crop farming operations in a good way does not always mean you should aim for a maximum yield, since the cost for inputs and revenues from grain trade needs to be considered as well. Hence, market data for input and product prices are also important since they affect your decisions.
We aim at building a data map for agriculture
By categorizing crop farming data in intuitive groups, we are aiming at creating a data map that includes the important types of data that are available in farming operations. The purpose with this is to give you a better understanding and overview of different types of data that are available, which makes it easier to stay up-to-date on the development that is happening in the agri-food business today.
In the next few Agtech Letters, we will dig deeper into each category of data and individual types of data that we consider to be particularly important to know about. Some examples are yield maps, satellite images for biomass, weed maps, and similar types of data.
Once we start talking about all data that is available, it is also important to understand how it is collected in practice, where and how it is stored, and how to transform it into useful insights or actions. We will touch some of these questions when we dig into more details about different types of data. However, already now a brief answer can be given to the questions since often data is often collected using some type of sensor or by digitizing analog maps and spreadsheets, and almost always the data is stored on a cloud platform that is integrated to one or more digital services that can be used to analyze and manage data. But let’s dig into these questions later on!
Agtechers' Actions
Make a list of the data that is most important for you to collect, and why they are important. And then you start collecting them in a structured way to help you reach your goals.
In the next Agtech Letter we will dig into the data about the soil and field.
