Here are 7 practical lessons for farmers based on the data obtained from AI weather stations:
1. Automate irrigation and save water
AI stations analyze soil moisture, air temperature and evaporation rate in real time.
Lesson: Plan irrigation based on the actual needs of the crop, not on a calendar. This will help reduce water consumption by 18-25% and save the plant from stress.
2. Predict pests and diseases
Relative humidity, temperature and leaf wetness data can identify favorable conditions for the appearance of fungal diseases or pests early.
Lesson: Apply preventive treatments at the right time, which reduces pesticide use and preserves crop quality.
3. Accurately determine planting and harvesting dates
AI studies local microclimates to predict the most favorable soil temperatures for planting and dry weather for harvesting.
Lesson: Adjust planting and harvesting dates based on AI forecasts to avoid unexpected drought or rain.
4. Improve fertilizer efficiency
Applying fertilizer before heavy rain or wind can lead to leaching or wasting of nutrients.
Lesson: Schedule fertilization for a period when the weather is expected to be calm and without precipitation. This will maximize fertilizer absorption into the soil.
5. Improve Spraying Efficiency with Delta T
Delta T (the ratio of temperature to humidity) determines the effective spraying of chemicals or pesticides.
Lesson: If Delta T is high (too hot and dry), stop spraying. This prevents evaporation of the chemicals and improves the quality of the treatment.
6. Protect against extreme weather
AI stations provide advance warning of sudden hail, hailstorms, or intense heat waves.
Lesson: Take action to activate irrigation systems (against hailstorms) or close protective nets when you receive early warning of the threat.
7. Rely on local (hyper-local) information
General weather forecasts (such as phone apps) may not fully reflect the conditions in your field.
Lesson: Trust the data from your own AI station installed in your field. Data from a station 30 km away can lead to the wrong decision for your crops.
Conclusion: By integrating AI weather station data into agricultural practices, farmers can increase yields by up to 25% and significantly reduce production costs.
