Predicting carob tree physiological parameters under different irrigation systems using Random Forest and Planet satellite images.

Introduction: In the context of climate change, monitoring the spatial and temporal variability of plant physiological parameters has become increasingly important. Remote spectral imaging and GIS software have shown effectiveness in mapping field variability. Additionally, the application of machine learning techniques, essential for processing large data volumes, has seen a significant rise in agricultural applications. This research was focused on carob tree, a drought-resistant tree crop spread through the Mediterranean basin. The study aimed to develop robust models to predict the net assimilation and stomatal conductance of carob trees and to use these models to analyze seasonal variability and the impact of different irrigation systems. Methods: Planet satellite images were acquired on the day of field data measurement. The reflectance values of Planet spectral bands were used as predictors to develop the models. The study employed the Random Forest modeling approach, and its performances were compared with that of traditional multiple linear regression. Results and discussion: The findings reveal that Random Forest, utilizing Planet spectral bands as predictors, achieved high accuracy in predicting net assimilation (R² = 0.81) and stomatal conductance (R² = 0.70), with the yellow and red spectral regions being particularly influential. Furthermore, the research indicates no significant difference in intrinsic water use efficiency between the various irrigation systems and rainfed conditions. This work highlighted the potential of combining satellite remote sensing and machine learning in precision agriculture, with the goal of the efficient monitoring of physiological parameters.

Appraising water and nutrient recovery for perennial crops irrigated with reclaimed water in Mediterranean areas through an index-based approach.

The use of reclaimed water for agricultural irrigation is among the agronomic practices being increasingly valued by policy-makers, water planners, and regulators to pursue more sustainable resource management in many arid and semi-arid agricultural production areas worldwide. This practice can make additional supply available in water-scarce areas, provide crop nutrients, and reduce the disposal of wastewater to the environment, thus providing considerable agronomic and environmental benefits. However, the process for treated wastewater reuse is complex because of multiple interactions among technical, economic, environmental, and public health related aspects. In this context, the application of quantitative indices capturing agronomic, engineering, and environmental factors and their possible inter-relations enable to appraise the potential benefits and risks of treated wastewater reuse at individual project's scale and for regional policies. The present article describes a quantitative approach that utilizes a set of proposed indices to characterize various aspects affecting water and nutrient recovery for specific combinations between the characteristics of the treatment facility and the attributes of the irrigation district supplied with reclaimed water. The proposed index-based approach was tested on datasets collected for 11 pilot reuse schemes located in the Apulia region of southern Italy with the aim to evaluate the potential for water and nutrient recovery resulting from irrigation with reclaimed water. Results from the data analysis and interpretation showed that the proposed indices enabled to quantify the environmental benefits of irrigation with RW that leads to divert less freshwater from conventional sources and dispose less reclaimed water into natural water receptors, as well as the agronomic advantages of using RW, which can partially fulfill the irrigation and nutrient requirements for the supplied districts' service areas. Overall, the proposed set of indices can provide valuable information for the successful implementation of water reuse policies for irrigated agriculture.

Use of remote sensing to evaluate the effects of environmental factors on soil salinity in a semi-arid area.

The global water crisis, driven by water scarcity and water quality deterioration, is expected to continue and intensify in dry and overpopulated areas, and will play a critical role in meeting future agricultural demands. Sustainability of agriculture irrigated with low quality water will require a comprehensive approach to soil, water, and crop management consisting of site- and situation-specific preventive measures and management strategies. Other problem related with water quality deterioration is soil salinization. Around 1Bha globally are salinized and soil salinization may be accelerating for several reasons including the changing climate. The consequences of climate change on soil salinization need to be monitored and mapped and, in this sense, remote sensing has been successfully applied to soil salinity monitoring. Although many issues remain to be resolved, some as important as the imbalance between ground-based measurements and satellite data. The main objective of this paper was to determine the influence of environmental factors on salinity from natural causes, and its effect on irrigated agriculture with degraded water. The study was developed on Campo de Cartagena, an intensive water-efficient irrigated area which main fruit tree is citrus (30%), a sensible crop to salinity. Nine representative citrus farms were selected, soil samples were analysed and different remote sensing indices and sets of environmental data were applied. Despite the heterogeneity between variables found by the descriptive analysis of the data, the relationship between farms, soil salinity and environmental data showed that applied salinity spectral indices were valid to detect soil salinity in citrus trees. Also, a set of environmental characterization provided useful information to determine the variables that most influence primary salinity in crops. Although the data extracted from spatial analysis indicated that to apply soil salinity predictive models, other variables related to agricultural management practices must be incorporated.

Ripening Indices, Olive Yield and Oil Quality in Response to Irrigation With Saline Reclaimed Water and Deficit Strategies.

The 70% worldwide surface of olive orchards is irrigated. The evaluation of non-conventional water resources and water-saving techniques has gained importance during the last decades in arid and semiarid environments. This study evaluated the effects of irrigation with two water sources: low-cost water DEsalination and SEnsoR Technology (DESERT) desalinated water (DW) ECw ∼1 dS m-1) and reclaimed water (RW) (ECw ∼ 3 dS m-1) combined with two irrigation strategies: full irrigation (FI) (100% of ETc) and regulated deficit irrigation (RDI, 50% of ETc) on fruit yield, ripening indices, and oil yield and quality of olive trees cv Arbosana planted in Mediterranean conditions. Our results showed that RW without water restrictions increased the fruit yield by 35% due to a slight increase in the fruit weight and, mainly, to a greater fruit set than the control trees; although this did not result in a higher oil yield (g tree-1) since the oil content per fruit dry weight was reduced. The RDI strategy did not decrease the fruit yield despite the fact that olive weight tended to decrease, and it increased the oil yield by ∼14.5%. The combination of both stresses (RW and RDI) neither decreased the fruit yield; however, it significantly reduced oil yield (25% less in 2018) since oil content per fruit dry weight was strongly reduced (40%) compared to control trees. Both RDI treatments, regardless water source, determined acidity levels in olive paste lower than in FI treatments; however, it reduced oil extractability and fatty yield. The finding about oil quality indicated that olive exposure to RW, regardless of the water amount, decreased oil quality mainly due to the reduction of oleic acid and the increase of C18:2/C18:3 ratio and peroxides; on the contrary, both RW and RDI improved the total polyphenols. In all cases, the parameters met the legislation. In short, with appropriate management, RW and RDI have great potential to manage oil olive production; nevertheless, studies subjected to long-term use of these techniques should be experienced to ensure the sustainability of oil yields and quality.