Collecting and recording data in the field
Something happens in the field every day: rain falls, leaves get spots, the soil dries out. In this lesson you will learn to record these things regularly.
- You will get to know the five main sources of farm data.
- You will sort out which data comes from which source.
- You will enter a field observation correctly in a record form.
Where does data come from?
In smart farming, the first step is collecting data. Data comes from several sources. Each source answers a different question.
Measures moisture, temperature and salinity (EC) in the root zone.
Records temperature, humidity, wind and rainfall. ET₀, which is used to work out water needs, is calculated from these data.
Shows the whole field from above. You find the weak zones on the map.
What you see with your own eyes: leaf spots, pests, the crop's growth stage, soil structure.
Records of fertiliser, pesticides, irrigation, harvest and sales. They show what you did and what came of it.
Three rules of good records
- Write down the place and time
Every measurement should have a date and a plot number next to it. Data without a location will not fit on a map.
- Look at the trend, not a single value
One day's reading can mislead you. Follow how it changes over the days.
- Check the sensor with your own eyes
If you see a sudden jump, go to the field. The sensor may have moved.
Training scenario; not a real measurement. Imagine a hazelnut orchard of 18 decares (da; 1 da = 1,000 m²). The orchard is divided into three plots. Plot 2 has a soil moisture sensor, and there is a weather station nearby. According to TARIMKON training material, the main risks in Sakarya are the humid climate, sudden heavy rain and disease pressure.
First, sort the data by source.
Which source does the data come from?
Training scenario; not a real measurement. Sort the data from the hazelnut orchard in Sakarya by source.
Now record what you saw on a morning walk round the orchard.
Field observation record
Training scenario; not a real measurement. The details are in the box below; fill in the record completely.
More detail: data type, measurement frequency and quality
How often? Soil moisture and air temperature are measured every few minutes. Evaporation and transpiration (ET) and total rainfall are followed daily. Growth stage and yield estimates are followed season by season.
In what form? Sensor and weather station data come in rows and columns, that is, as a table. Satellite and drone images are not tables; they are processed with software. Data that carries location information is called spatial data.
What makes data good? It should be accurate, arrive without gaps, arrive on time and be able to show differences within the field.
How does a sensor measure? Moisture sensors use the electrical properties of the soil (conductivity, dielectric constant). This is why they need adjusting to your soil (calibration). The sensor location should represent the plot as a whole.
In short
- Farm data comes from five main sources; each one answers a different question.
- Write the date, the plot and the data source on every record.
- Follow sensor readings as a trend and check them by eye in the field.
References
- TARIMKON LMS, MODÜL 2 ders metni: Veri toplama yöntemleri ve araçları. [MODULE 2 lesson text: data collection methods and tools]
- TARIMKON training material: Sulama Sistemleri (Akıllı Sulama Sistemlerinde Veri Okuma, Yorumlama ve Uygulama Örnekleri), 2026. [TARIMKON training material: Irrigation Systems; reading and interpreting data in smart irrigation]
- TARIMKON training material: Tarımda Veri ve Teknoloji (Tarımsal Sayısallaşma: IoT, Sensör Teknolojileri, Yapay Zeka İçin Veri Altyapıları), 2026. [TARIMKON training material: Data and Technology in Agriculture; IoT, sensors and data infrastructure for AI]
- TARIMKON training material: Akıllı Tarım Teknikleri ve Teknolojileri II, 2026. [TARIMKON training material: Smart Farming Techniques and Technologies II]
- TARIMKON training material: İklim Değişikliği ve Doğal Kaynaklar: Uyum ve Sürdürülebilirlik (hedef iller için risk profilleri). [TARIMKON training material: Climate Change and Natural Resources; risk profiles for the target provinces]
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