European Journal of Sustainable Agroecosystems

Background: The combination of declining water sources and worsening rainfall variations has resulted in the strain that has never been seen before on irrigated agriculture. Analytics that use sensors to measure plant water status have become a key element in the innovations aimed at finding a suitable compromise between productivity and water efficiency in agriculture.

Objective: This article provides an overview of the available literature on the concept of the technologies utilizing sensors to assess plant water status, including soil-based, plant-based, and remote canopy measurement methods, as well as how these technologies can become part of IoT- and AI-enabled smart irrigation systems. Sources of literature: In order to identify the suitable records published between 2015 and 2025, an organized search was conducted across the Scopus, Web of Science, PubMed, Google Scholar databases, and websites of relevant government and international organizations, in addition to methodological papers published before 2015. As part of the systematic review, 66 records were evaluated for full text, out of which 34 met the conditions for inclusion and were used for the thematic synthesis.

Key conclusions: The existing literature shows that there is not a single type of sensor that would be able to provide a universal standard for assessing moisture levels in plants; however, sensors measuring soil moisture (capacitive sensors, time domain reflectometers, tensiometers) are said to be cheap but indirect; while sensors measuring plant sap flow or bark expansion (the movements of the trunk) provide direct but labor-intensive results of water measurement, remote sensing methods (infrared thermography, thermal imaging) allow for scalable evaluation but complicate the calibration process. It has been acknowledged that using this array of sensors within IoT frameworks allows using up to 40% less irrigation water without decreasing the yield.

The ongoing lack of standardized calibration standards that apply to all soil types and cultivars, limited field evidence from multiple years and sites, the difficulty in integrating different types of sensor data, and unresolved issues regarding cybersecurity and interoperability for using sensors for agriculture on small farms are persistent gaps in the knowledge.

In conclusion, while the technology behind the sensor-based plant water status evaluation is relatively mature, its application is hindered by some fragmentation in real-life practices; therefore, future studies should focus on creating a comprehensive and affordable sensing systems based on multi-modal data combination and unified calibration standards.