Table 2 Advantages and disadvantages of smart irrigation-related methods.
Method | Advantages | Disadvantages | References |
|---|---|---|---|
Soil water content | Simple to install Highly precise Various commercial systems are available Measurements can help to smoothly determine water needs Certain sensors, such as capacitance and time domain sensors can be integrated in automation system with relative ease. | Soil variability requires the use of numerous sensors It is challenging to choose a location that accurately represents the root zone Sensors do not typically assess the water status directly at the root surface, which is influenced by evaporative demand Data logger integration is expensive. | |
Soil matric potential | Simple to install Highly precise Various commercial systems are available. | Soil variability requires the use of numerous sensors It is challenging to choose a location that accurately represents the root zone Regular maintenance is required Salinity and temperature may affect sensors’ performance Sensors do not typically assess the water status directly at the root surface, which is influenced by evaporative demand. | |
Crop evapotranspiration | Simple to install Provides directly usable data to manage water. | Less precise than carrying out a direct measurement to the plant (e.g. through sap flow) Requires accurate local weather data Accurate crop coefficients are essential for evapotranspiration estimation, which is influenced by crop growth and root depth As it is prone to readings drifts (errors), regular calibration is necessary. | |
Sap flow | Highly responsive. | Provides only indirect estimates of changes in conductance, as flow heavily depends on atmospheric conditions. | |
CWSI | Scalable for large crop areas, particularly with imaging technology The most simple form of thermometers are inexpensive and portable Compatible with continuous monitoring purposes. | Requires sophisticated instrumentation and technical expertise Calibration is needed for each tree and to determine irrigation control thresholds. | |
Stem Water Potential | Measures the pressure component of water potential, essential for xylem water flow and cell functions like growth Technologies (e.g. microtensiometers) compatible with IoT, suitable for automation strategies, as well as for continuous and direct measurements are already available. | Instruments must be handled with care and are typically expensive. | |
Leaf Turgor | Effective in detecting daily turgor variations and water stress, providing clear readings under ideal conditions. | Can be inaccurate during severe water deficit and requires frequent sensor replacements anticipating physiological changes. | |
Dendrometry | Changes in tissue water content are simpler to measure and to automate, when compared to water potential sensors Commercial sensors that measure small-scale structural features are available. | Instrumentation is generally complex or expensive, which constitutes a challenge to scalability Integration involves issues related to environmental variability, calibration requirements, and data interpretability. | |
Water reservoirs instrumentation | Level sensors allow to optimize water use. | Susceptibility to external interference, such as objects, dust, and other environmental elements can compromise the accuracy of sensor. |
