Plant-based and remote sensing for water status monitoring of orchard crops: Systematic review and meta-analysis

Agricultural sustainability in many parts of the world is facing significant challenges due to water scarcity and the adverse effects of climate change. Agriculture uses 70 % of the total freshwater, and irrigation sustains 40 % of the global food supply. Various plant monitoring technologies and irrigation techniques were developed to improve the efficiency of agricultural water use. Although their benefits are widely acknowledged, conflicting findings and inconclusive results emerge when assessing their performances and effectiveness in monitoring plant water status. A systematic review using a rigorous protocol for research question formulation and eligibility criteria definition was conducted with the aim of assessing, from published literature, the performance of various plant (tree) based sensors for water stress monitoring. Initially, 496 articles were collected from four leading search engines for scientific peer-reviewed papers., the number of relevant manuscripts was narrowed to 124, using strict inclusion and exclusion criteria, from which meta-analysis was conducted and reported. Results showed that most studies were conducted in Spain and the USA, focusing on olive, peach, and almond cultivation. Crop Water Stress Index showed a better correlation with stomatal conductance (gs) (R-2 = 0.76) and with leaf water potential (psi L) (R-2 = 0.75) compared to Xylem Water Potential (psi S) (R-2 = 0.6). Maximum Daily Shrinkage (MDS) showed a coefficient of determination with WS equivalent to 0.68. On the remote sensing side, the most commonly used indices are the Normalized Difference Vegetation Index (NDVI) (n=22), Photochemical Reflectance Index (PRI) (n=11), and canopy temperature (n =94) with better correlation with WS for PRI and thermal. However, the finding is not conclusive due to the complexity of plant water relations and the influence of other factors such as environmental conditions, canopy structure, nutrient deficiencies, and plant diseases.