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In this study, a soil moisture-based wireless sensor network (SM-WSN) was transferred to support irrigation management at field scale. This smart irrigation service comes from a necessity and willingness to upgrade the regional weather-based decision support system of the Tuscany region (Italy). The sensor network was designed, hydrologically, and agronomically validated in a commercial pear orchard during four growing seasons (2019–2022). Initially, the micro irrigation system was assessed based on its water distribution uniformity (DU) performance. Then, a zoning analysis was carried out to delineate homogeneous areas according to the normalized difference vegetation index (NDVI) and soil bulk electrical conductivity (ECb). Unlike the ordinary irrigation scheduling applied in the farm, the smart system allowed maintaining the soil water content within a pre-defined optimal range, in which the upper and lower limits corresponded respectively to the soil field capacity and the threshold below which water stress occurs. Based on the smart irrigation management, a water-saving up to 50 % of the total water supplied with the ordinary scheduling was achieved during the investigated growing seasons. Moreover, the quality of the productions (i.e., °Brix, fruit size and flesh firmness) was in line with the standard market reference values. Consequently, the adoption of the new technology, which aims to identify the most appropriate irrigation management, has the potential to generate positive economic returns and reduce environmental impacts.

This survey comprehensively examines the public irrigation decision support systems (IDSS) in Italy, offering a detailed description, analysis and evaluation of their features. The study investigates the agrometeorological networks and infrastructures that support Italian IDSS, providing a clearer understanding of the national context. The evaluation criteria include relevant factors such as soil moisture monitoring, crop water requirements (CWR) estimation models, biophysical parameters along with their spatial and temporal resolutions, irrigation planning and decision support visualization. Additionally, the assessment covers accessibility, scalability and interoperability of these systems. The survey also highlights the strengths and weaknesses of various IDSS, such as IRRIFRAME, IRRISIAS and IRTO, discussing their operational methodologies, data integration and regional coverage. The aim is to provide insights that facilitate advancements in sustainable irrigation management practices and address key challenges for future developments at both regional and national levels. This comprehensive evaluation seeks to enhance the effectiveness of IDSS in promoting sustainable water management in agriculture across Italy.

In the area under tree rows of alley cropping systems, coarse plant material as well as pruning material or stones may be present, so the use of a mower equipped with chains as cutting a tool could be advantageous. A mower designed for under-row weed control in orchards, equipped with an automatic tree-skipping mechanism, was modified by replacing blades with chains with the aim of evaluating its performance in an alley cropping system. A first trial was carried out in an open field to preliminarily compare the chain mower with the version equipped with blades in relation to different settings of working speed (1.6 and 2.4 km·h−1) and rotation speed of the cutting tool (1830 and 2500 rpm). Weed biomass reduction, weed cover reduction, weed height reduction, weed biomass regrowth, and clipping size were assessed. In a second trial, the performance of the mowers with different setting configurations was assessed in an alley cropping system under a more critical environmental condition for mowing, i.e., the presence of dew. Weed biomass reduction, weed cover reduction, weed height reduction, and the mowers’ field capacity with different working speed settings were assessed. No major differences emerged between the mowers and the chain mower performance was comparable to that of the standard blade mower. The setting with the high working speed and high rotation speed of the cutting tool turns out to be the best compromise, obtaining a weed biomass reduction of 59.6%, a weed cover reduction of 40.9%, and a higher field capacity compared to the setting with the low working speed, with an increase of 47.9%.

The experiments were conducted in a fully-productive olive orchard (cv. Frantoio) at the experimental farm of University of Pisa at Venturina (Italy) in 2015 to assess the ability of an unmanned aerial vehicle (UAV) equipped with RGB-NIR cameras to estimate leaf area index (LAI), tree height, canopy diameter and canopy volume of olive trees that were either irrigated or rainfed. Irrigated trees received water 4-5 days a week (1348 m3 ha-1), whereas the rainfed ones received a single irrigation of 19 m3 ha-1 to relieve the extreme stress. The flight altitude was 70 m above ground level (AGL), except for one flight (50 m AGL). The Normalized Difference Vegetation Index (NDVI) was calculated by means of the map algebra technique. Canopy volume, canopy height and diameter were obtained from the digital surface model (DSM) obtained through automatic aerial triangulation, bundle block adjustment and camera calibration methods. The NDVI estimated on the day of the year (DOY) 130 was linearly correlated with both LAI and leaf chlorophyll measured on the same date (R2 = 0.78 and 0.80, respectively). The correlation between the on ground measured canopy volumes and the ones by the UAV-RGB camera techniques yielded an R2 of 0.71-0.86. The monthly canopy volume increment estimated from UAV surveys between (DOY) 130 and 244 was highly correlated with the daily water stress integral of rainfed trees (R2 = 0.99). The effect of water stress on the seasonal pattern of canopy growth was detected by these techniques in correspondence of the maximum level of stress experienced by the rainfed trees. The highest level of accuracy (RMSE = 0.16 m) in canopy height estimation was obtained when the flight altitude was 50 m AGL, yielding an R2 value of 0.87 and an almost 1:1 ratio of measured versus estimated canopy height.

The work aimed to discriminate among different soil management treatments in terms of beneficial effects by high-resolution thermal and spectral vegetation imagery using an unmanned aerial vehicle and open-source GIS software. Five soil management treatments were applied in two organic vineyards (cv. Sangiovese) from Chianti Classico terroir (Tuscany, Italy) during two experimental years. The treatments tested consisted of conventional tillage, spontaneous vegetation, pigeon bean (Vicia faba var. minor Beck) incorporated in spring, mixture of barley (Hordeum vulgare L.) and clover (Trifolium squarrosum L.) incorporated or left as dead mulch in late spring. The images acquired remotely were analyzed through map-algebra and map-statistics in QGIS and correlated with field ecophysiological measurements. The surface temperature, crop water stress index (CWSI) and normalized difference vegetation index (NDVI) of each vine row under treatments were compared based on frequency distribution functions and statistics descriptors of position. The spectral vegetation and thermal-based indices were significantly correlated with the respective leaf area index (R2 = 0.89) and stem water potential measurements (R2 = 0.59), and thus are an expression of the crop vigor and water status. The gravel and active limestone soil components determined the spatial variability of vine biophysical (e.g., canopy vigor) and physiological characteristics (e.g., vine chlorophyll content) in both farms. The vine canopy surface temperature, and CWSI were lower on the spontaneous and pigeon bean treatments in both farms, thus evidencing less physiological stress on the vine rows derived from the cover crop residual effect. In conclusion, the proposed methodology showed the capacity to discriminate across soil management practices and map the spatial variability within vineyards. The methodology could serve as a simple and non-invasive tool for precision soil management in rainfed vineyards to guide producers on using the most efficient and profitable practice.

Anthocyanic morphs are generally less efficient in terms of carbon gain, but, in turn, are more photoprotected than anthocyanin-less ones. To date, mature leaves of different morphs or leaves at different developmental stages within the same species have generally been compared, whereas there is a lack of knowledge regarding different stages of development of red vs. green leaves. Leaves (1-, 7-, and 13-week-old) of red- (RLP) and green-leafed (GLP) Prunus in terms of photosynthetic rate, carbon metabolism and photoprotective mechanisms were compared to test whether anthocyanin-equipped leaves perform better than anthocyanin-less leaves and whether photoprotection is the primary role of epidermally-located anthocyanins, using for the first time a recently-developed parameter of chlorophyll fluorescence (qPd). GLP leaves had a higher photosynthetic rate in 1- and 7-week-old leaves, but RLP leaves performed better at an early stage of senescence and had a longer leaf lifespan. Anthocyanins contributed to leaf photoprotection throughout the leaf development, but were tightly coordinated with carotenoids. Besides photoprotecting, we propose that epidermal anthocyanins may be principally synthetized to maintain an efficient carbon-sink strength in young and senescent leaves, thus extending the RLP leaf lifespan.

Actual evapotranspiration is assessed via surface energy balance at an hourly rate. However, a robust estimation of daily evapotranspiration from hourly values is required. Outcomes of surface energy balance are frequently determined via measures of eddy covariance latent heat flux. Surface energy balance can be applied on images acquired at different times and spatial resolutions. In addition, hourly actual evapotranspiration needs to be integrated at a daily rate for operational uses. Questions arise whether the validation of surface energy balance models can benefit from complementary in situ measures of latent heat flux and sap flow transpiration. Here, validation was driven by image acquisition time, spatial resolution, and temporal integration. Thermal and optical images were collected with a proximity-sensing platform on an olive orchard at different acquisition times. Actual latent heat fluxes from canopy and sap flux at tree trunks were measured with a flux tower and heat dissipation probes. The latent heat fluxes were then further analyzed. A surface energy balance was applied over proximity sensing images re-sampled at different spatial resolutions with resulting latent heat fluxes compared to in situ ones. A time lag was observed and quantified between actual latent heat fluxes from canopy and sap flux at the tree trunk. Results also indicate that a pixel resolution comparable to the average canopy size was suitable for estimating the actual evapotranspiration via a single source surface energy balance model. Images should not be acquired at the beginning or the end of the diurnal period. Findings imply that sap flow transpiration can be used to measure surface energy balance at a daily rate or when images are found at an hourly rate near noon, and the existing time lag between the latent heat flux at the canopy and the sap flow at the trunk does not need to be taken into account.

The knowledge of soil water content (SWC) dynamics in the upper soil layer is important for several hydrological processes. Due to the difficulty of assessing the spatial and temporal SWC dynamics in the field, some model-based approaches have been proposed during the last decade. The main objective of this work was to assess the performance of two approaches to estimate SWC in the upper soil layer under field conditions: the physically-based thermal inertia and the Hydrus model. Their validity was firstly assessed under controlled laboratory conditions. Thermal inertia was firstly validated in laboratory conditions using the transient line heat source (TLHS) method. Then, it was applied in situ to analyze the dynamics of soil thermal properties under two extreme conditions of soil-water status (well-watered and air-dry), using proximity remote-sensed data. The model performance was assessed using sensor-based measurements of soil water content acquired through frequency (FDR) and time domain reflectometry (TDR). During the laboratory experiment, the Root Mean Square Error (RMSE) was 0.02 m3 m−3 for the Hydrus model and 0.05 m3 m−3 for the TLHS model approach. On the other hand, during the in situ experiment, the temporal variability of SWCs simulated by the Hydrus model and the corresponding values measured by the TDR method evidenced good agreement (RMSE ranging between 0.01 and 0.005 m3 m−3). Similarly, the average of the SWCs derived from the thermal diffusion model was fairly close to those estimated by Hydrus (spatially averaged RMSE ranging between 0.03 and 0.02 m3 m−3).