Smart Irrigation with the Agrivate Algorithm: Precision, Economy and Optimal Yield

Agrivate has developed an advanced irrigation algorithm that uses data from agro-meteorological stations and soil moisture sensors to manage irrigation precisely for every tree. This is achieved by calculating reference evapotranspiration (ETo) and applying deficit irrigation, delivering economy, improved yield and superior quality.

Calculating ETo with an agro-meteorological station

Reference evapotranspiration (ETo) is a key factor in determining a crop's irrigation needs. It represents the water lost through evaporation from the soil and transpiration by plants. The Agrivate agro-meteorological station collects real-time data such as temperature, humidity, solar radiation and wind speed. This data feeds the algorithm, which calculates ETo using established models such as the Penman-Monteith equation, accurately determining how much water the crop needs.

Building accurate irrigation data and applying deficit irrigation

Based on the calculated ETo and the crop's specific requirements, the Agrivate algorithm sets the optimal irrigation schedule for each tree. Deficit irrigation is then applied, supplying less water than the crop's full potential in order to save water without reducing yield. This approach not only cuts irrigation costs but also boosts product quality, since some crops respond well to controlled water stress.

The role of soil moisture sensors

Soil moisture sensors play a critical role in tracking the soil's water status. Placed at strategic points, they provide real-time data on the soil's water content. This information allows irrigation schedules to be fine-tuned, ensuring the crop is watered at the right moment. Continuous soil-moisture monitoring avoids both over- and under-irrigation, supporting plant health and efficient use of water resources.

Overall, Agrivate's integrated approach combines cutting-edge technology and scientific methods to optimise irrigation. This leads to significant water savings, lower production costs and better quality and quantity of the harvest.