Soil Water Content Prediction Using Electrical Resistivity Tomography (ERT) in Mediterranean Tree Orchard Soils.

Water scarcity in arid and semiarid regions poses problems for agricultural systems, awakening special interest in the development of deficit irrigation strategies to improve water conservation. Toward this purpose, farmers and technicians must monitor soil water and soluble nutrient contents in real time using simple, rapid and economical techniques through time and space. Thus, this study aimed to achieve the following: (i) create a model that predicts water and soluble nutrient contents in soil profiles using electrical resistivity tomography (ERT); and (ii) apply the model to different woody crops under different irrigation regimes (full irrigation and regulated deficit irrigation (RDI)) to assess the efficiency of the model. Simple nonlinear regression analysis was carried out on water content and on different ion contents using electrical resistivity data as the dependent variable. A predictive model for soil water content was calibrated and validated with the datasets based on exponential decay of a three-parameter equation. Nonetheless, no accurate model was achieved to predict any soluble nutrient. Electrical resistivity images were replaced by soil water images after application of the predictive model for all studied crops. They showed that under RDI situations, soil profiles became drier at depth while plant roots seemed to uptake more water, contributing to reductions in soil water content by the creation of desiccation bulbs. Therefore, the use of ERT combined with application of the validated predictive model could be a sustainable strategy to monitor soil water evolution in soil profiles under irrigated fields, facilitating land irrigation management.

Irriman Platform: Enhancing Farming Sustainability through Cloud Computing Techniques for Irrigation Management.

Crop sustainability is essential for balancing economic development and environmental care, mainly in strong and very competitive regions in the agri-food sector, such as the Region of Murcia in Spain, considered to be the orchard of Europe, despite being a semi-arid area with an important scarcity of fresh water. In this region, farmers apply efficient techniques to minimize supplies and maximize quality and productivity; however, the effects of climate change and the degradation of significant natural environments, such as, the "Mar Menor", the most extent saltwater lagoon of Europe, threatened by resources overexploitation, lead to the search of even better irrigation management techniques to avoid certain effects which could damage the quaternary aquifer connected to such lagoon. This paper describes the Irriman Platform, a system based on Cloud Computing techniques, which includes low-cost wireless data loggers, capable of acquiring data from a wide range of agronomic sensors, and a novel software architecture for safely storing and processing such information, making crop monitoring and irrigation management easier. The proposed platform helps agronomists to optimize irrigation procedures through a usable web-based tool which allows them to elaborate irrigation plans and to evaluate their effectiveness over crops. The system has been deployed in a large number of representative crops, located along near 50,000 ha of the surface, during several phenological cycles. Results demonstrate that the system enables crop monitoring and irrigation optimization, and makes interaction between farmers and agronomists easier.

Greenhouse gas emissions and soil organic matter dynamics in woody crop orchards with different irrigation regimes.

Water scarcity in arid, semiarid and dry regions is a limiting factor for the development of sustainable agriculture. As a consequence, the adoption of new strategies such as regulated deficit irrigation (RDI) to reduce water and energy consumption will be essential. Decreases in irrigation water content may also have positive effects on soil C cycle. Thus, an experiment was setup in three woody crop orchards during two years, with the objective of assessing if RDI can reduce soil CO2 and N2O emissions, modify soil inorganic C and organic C quality and stability and affect soil aggregation. Soil CO2 and N2O emissions were measured every two weeks while soil samplings were carried out every three months. Results indicated that decreases in soil moisture by RDI implementation were related to significant decreases in CO2 emissions in all crops. RDI contributed to an average decrease, compared with full irrigation, of 1088-1664 g CO2 m-2 in the experimental period. Furthermore, CO2 emission was negatively correlated with inorganic C, suggesting the protective effect of soil carbonates towards organic matter. RDI also contributed to significantly decrease soil N2O emissions. However, N2O emission patterns did not directly follow soil moisture patterns and were constant in the experimental period. RDI contributed to an average decrease, compared with full irrigation, of 90-409 mg N2O m-2. No physicochemical property was significantly affected by irrigation regime. Although microbial biomass was not significantly affected by RDI, ß-glucosidase activity was significantly higher under full irrigation during the warm seasons, with significant positive correlation with CO2 emissions. This seems to suggest that a significant fraction of CO2 emitted from soil derives from organic matter degradation, which is limited with low water content. So, RDI could contribute to promote soil C sequestration by reduced greenhouse gas emissions, with no negative effects on soil structure at short-term.

Long-term impact of deficit irrigation on the physical quality of berries in 'Crimson Seedless' table grapes.

BACKGROUND: In table grapes, berry firmness influences consumer acceptance so it is important to avoid berry shattering and dehydration during their post-harvest life. Since studies of irrigation effects on table grape quality are comparatively rare, sensory evaluation aimed to identify high-quality berries obtained under different deficit irrigation treatments. A 3-year study examined the effects of deficit irrigation strategies on some physical quality attributes at harvest, after 28 days of cold storage at 0 °C and after an additional shelf-life period of 3 days at 15 °C. Control vines were irrigated to ensure non-limiting water conditions (110% of crop evapo-transpiration), while both regulated deficit irrigation treatment (RDI) and partial root-zone drying (PRD) treatments applied 35% less water post-veraison. The null irrigation treatment (NI) only received natural precipitation (72% less water than control vines). RESULTS: Total yield and physical quality at harvest were not significantly affected by RDI or PRD. Only severe deficit (NI) decreased berry size, and this treatment had the most dehydrated berries and the worst sensory scores post-harvest. After cold storage, increased berry shattering of the PRD treatment was correlated with lower leaf xylem abscisic acid (ABA) concentration at the time of harvest. Overall quality, especially stem browning, determined the shelf-life, and longer storage duration tended to diminish treatment differences. CONCLUSIONS: Only NI clusters showed lower quality than their irrigated counterparts. Neither RDI nor PRD had any noticeable effect on berry quality at the end of cold storage and shelf-life, with the slight differences detected between these treatments related to stem browning and dehydration. Sensory results were similar in RDI and PRD, which provided grapes that were more acceptable to consumers than the control. Thus, it is possible to decrease irrigation of table grapes without adversely affecting the physical quality of the berries.

Modelling the effect of fruit growth on surface conductance to water vapour diffusion.

BACKGROUND AND AIMS: A model of fruit surface conductance to water vapour diffusion driven by fruit growth is proposed. It computes the total fruit conductance by integrating each of its components: stomata, cuticle and cracks. METHODS: The stomatal conductance is computed from the stomatal density per fruit and the specific stomatal conductance. The cuticular component is equal to the proportion of cuticle per fruit multiplied by its specific conductance. Cracks are assumed to be generated when pulp expansion rate exceeds cuticle expansion rate. A constant percentage of cracks is assumed to heal each day. The proportion of cracks to total fruit surface area multiplied by the specific crack conductance accounts for the crack component. The model was applied to peach fruit (Prunus persica) and its parameters were estimated from field experiments with various crop load and irrigation regimes. KEY RESULTS: The predictions were in good agreement with the experimental measurements and for the different conditions (irrigation and crop load). Total fruit surface conductance decreased during early growth as stomatal density, and hence the contribution of the stomatal conductance, decreased from 80 to 20 % with fruit expansion. Cracks were generated for fruits exhibiting high growth rates during late growth and the crack component could account for up to 60 % of the total conductance during the rapid fruit growth. The cuticular contribution was slightly variable (around 20 %). Sensitivity analysis revealed that simulated conductance was highly affected by stomatal parameters during the early period of growth and by both crack and stomatal parameters during the late period. Large fruit growth rate leads to earlier and greater increase of conductance due to higher crack occurrence. Conversely, low fruit growth rate accounts for a delayed and lower increase of conductance. CONCLUSIONS: By predicting crack occurrence during fruit growth, this model could be helpful in managing cropping practices for integrated plant protection.