Water Stress in Orchards

Pre-visual water stress detection in orchards is potentially extremely valuable to fruit and nut growers. By the time visual water stress symptoms, such as leaf wilting or leaf discoloration, are present in the orchard, some level of economic loss has likely already occurred, depending on the stage of the crop. Soil-level moisture sensors, or  even sap flow sensors, can be very helpful in determining optimum irrigation strategy for orchards, but these tools are limited, because they can only measure the immediate area where the sensor is placed. This is likely not very helpful in determining overall irrigation distribution uniformity, or in detecting areas where there is a problem with irrigation equipment (clogs, or leaks). For this reason, remote sensing may be a useful option for growers.

Advancements in Remote Sensing

Remote sensing, using aerial imagery, in orchards is a very useful tool, especially when covering large amounts of acreage that would be difficult to individually scout every row, on a regular basis. There are several companies (such as CeresMavrx ,Terravion, and others) that offer remote sensing services that are increasingly more affordable for growers. One historical use of remote sensing is thermal imaging to detect difference in temperature through plant canopy, which can be indirectly related  to water use or, potential water need by the plants. However, there are now spectral vegetative plant indices that can use high resolution aerial images to detect water stress, and other plant functions, before any visible symptoms appear, allowing growers a more rapid response time to prevent economic loss.

PRI (Photochemical Reflectance Index)

The Photochemical Reflectance Index (PRI) was developed to help study xanthophyll pigment composition in plants, which can change under stress conditions, such as when photosynthetic rate is limited by water stress. PRI can be derived from spectral imagery and this can be a useful tool in detecting pre-visual water stress in an orchard. Researchers in Spain were able to demonstrate the PRI index, calculated from aerial hyperspectral images of pear and olive orchards, is sensitive to water stress levels in plants. They concluded that this can be a viable option for irrigation scheduling.

Water Stress shown by pri
UAV detection of crop stress using the photochemical-reflectance index (PRI) (left: well irrigated in blue, deficit irrigation in yellow and orange). On the right, PRI levels indicate the stress condition for each tree crown. sPRI: Simulated PRI for nonstress crop conditions based on radiative-transfer modeling. (Zarco-Tejada, et al)

NDVI (Normalized Difference Vegetation Index)

Normalized difference vegetation index (NDVI) is another commonly used index that can be derived from remote sensing, it is typically associated with plant vigor, or “greenness” and can be a useful tool in determining light interception, leaf area, plant biomass. It has recently become more popular as a service for growers. However it’s usefulness as a true water stress indicator is still up for debate. In 2015, a detailed field study concluded the following,

” Practical ground truthing efforts in 2014 growing year have enabled us to conclude that, using a low cost VTOL drone plus COTS RGB/NIR camera pair and performing plain image processing does not lead us to direct correlation to water stress level. However, more recent work (forthcoming) suggests using advanced algorithms based on raw NDVI information can indeed show a correlation to water stress (R2 ≥ 0.9).”

Based on these results, PRI is likely the more useful index from what is currently available, and is potentially a very useful tool for farmers.


Orchard Water Stress Detection Using High-Resolution Imagery. Suarez et al, 2010.

A Detailed Field Study of Direct Correlations Between Ground Truth Crop Water Stress and Normalized Difference Vegetation Index (NDVI) from Small Unmanned Aerial System (sUAS). Zhao et al, 2015.