Search Results (23)

The La Mancha region (a semi-arid area of southeast Spain) hosts the world’s highest concentration of vineyards and is also one of the regions with the largest areas devoted to almond tree cultivation. Viticulture and nut fruit trees (mainly almonds) are one of the region’s principal sources of economic revenue. The Two-Source Energy Balance (TSEB) model can assist management of water resources. A simplified version of the TSEB approach (STSEB) was previously tested in a vineyard and almonds to estimate sensible heat (H) and latent heat (LE) fluxes using a parallel scheme method based on the Monin–Obukov similarity theory (MOST). This study introduces a method based on Surface Renewal (SR) theory to partition the sensible heat flux using low-frequency measurements as input. The latter was friendlier than the parallel MOST method under unstable conditions and than the series SR and MOST methods. The objective was to compare the MOST and SR models within a parallel scheme method. During the 2014 and 2015 growing season, measurements were collected in a 4 ha row crop drip-irrigated Tempranillo vineyard. Hourly sensible heat flux measured by an eddy covariance (EC) system and evapotranspiration (ET) registered by a 9 m² monolithic large weighting lysimeter were used as a reference. ET estimates were obtained as a residual of the energy balance equation (known as the residual method) using three methods for estimating sensible heat flux, H_SR, H_MOST and H_EC, yielding ET_SR-RE, ET_MOST-RE and ET_EC-RE, respectively. For sensible heat flux, the index of agreement (IA expressed in %) for 2014 and 2015 was 93% and 83%, respectively, using SR, and 84% and 78%, respectively, for MOST. This represents a 6–10% improvement using SR. For evapotranspiration, the ET_SR-RE and ET_MOST-RE IA showed similar performance in both years (around 88%), while ET_EC-RE yielded the best results (92% and 89% for 2014 and 2015, respectively). In addition, half-hourly EC fluxes, during the growing season of 2017, were used as a reference in an almond orchard. The SR sensible heat flux performed better (IA = 93%) than MOST (IA = 86%) in this case, whereas for the latent heat flux, the residual method performed the best, resulting in an IA of 81% for SR and of 78% for MOST. Overall, SR performed better than MOST, particularly under unstable conditions with wind speeds above 1 ms⁻¹. Full article

Evapotranspiration and crop coefficients are key variables for designing efficient irrigation strategies in tree crops, yet standard tabulated coefficients derived for mature, fully covering orchards often fail to represent the water use of young, high-density hazelnut systems. In recent years, updated crop coefficients for temperate fruit trees, including hazelnut, and transpiration-based models have been proposed, while several studies have successfully linked Vegetation Indices and thermal metrics to single and basal crop coefficients in vineyards, orchards and field crops. However, no information is available on the use of UAV-derived spectral and thermal indices to estimate crop coefficients in high-density hazelnut orchards. This study compares crop coefficients obtained from traditional approaches (the FAO56 single crop coefficient, a transpiration-based coefficient, and ground cover reduction factors) with coefficients estimated from UAV-derived Normalized Difference Water Index (NDWI) and Crop Water Stress Index (CWSI) in a subsurface-drip-irrigated hazelnut orchard (cv. Tonda Francescana^®) with two planting densities (625 and 1250 trees ha⁻¹) in central Italy. Multispectral and thermal UAV surveys carried out between 2021 and 2024 were used to derive canopy geometrical traits, ground cover, NDWI, and CWSI, while a local weather station provided reference evapotranspiration. Empirical relationships were calibrated between crop coefficients and ground cover, NDWI, and CWSI, and mid-season coefficients were applied to estimate daily crop evapotranspiration, which was then compared with the irrigation volumes supplied during the 2024 season. The standard FAO56 crop coefficient (Kc = 0.9) overestimated evapotranspiration, especially at the lower planting density, whereas ground cover-based reduction factors recalibrated for hazelnut and the transpiration-based coefficient provided estimates more consistent with the applied irrigation. UAV-based NDWI- and CWSI-derived crop coefficients produced mid-season values close to those obtained with the transpiration-based method for both planting densities, confirming that spectral and thermal information can effectively capture the combined effects of canopy development and water status. These results indicate that combining traditional methods with UAV-derived indices offers a flexible framework to refine crop coefficients in high-density hazelnut orchards and support more accurate and spatially explicit irrigation scheduling. Full article

Agriculture faces growing pressure to optimize water use, particularly in woody perennial crops where irrigation systems are installed once and seldom redesigned despite changes in canopy structure, soil conditions, or plant mortality. Such static layouts may accumulate inefficiencies over time. This study introduces a decision support system (DSS) that evaluates the hydraulic adequacy of existing irrigation systems using two new concepts: the Resource Overutilization Ratio (ROR) and the Irrigation Ecolabel. The ROR quantifies the deviation between the actual discharge of an installed irrigation network and the theoretical discharge required from crop water needs and user-defined scheduling assumptions, while the ecolabel translates this value into an intuitive A+++–D scale inspired by EU energy labels. Crop water demand was estimated using the FAO-56 Penman–Monteith method and adjusted using canopy cover derived from UAV-based canopy height models. A vineyard case study in Galicia (Spain) serves an example to illustrate the potential of the DSS. Firstly, using a fixed canopy cover, the FAO-based workflow indicated moderate oversizing, whereas secondly, UAV-derived canopy measurements revealed substantially higher oversizing, highlighting the limitations of non-spatial or user-estimated canopy inputs. This contrast (A+ vs. D rating) illustrates the diagnostic value of integrating high-resolution geospatial information when canopy variability is present. The DSS, released as open-source software, provides a transparent and reproducible framework to help farmers, irrigation managers, and policymakers assess whether existing drip systems are hydraulically oversized and to benchmark system performance across fields or management scenarios. Rather than serving as an irrigation scheduler, the DSS functions as a standardized diagnostic tool for identifying oversizing and supporting more efficient use of water, energy, and materials in perennial cropping systems. Full article

How accurately do Sentinel-2 (S2) images describe vine row spatial variability? Can they produce effective management zones (MZs) for precision viticulture? S2 and UAV datasets acquired over two years for different drip-irrigated vineyards in the Colli Morenici region (northern Italy) were used to assess the actual need to use UAV-NDVI maps instead of S2 images to obtain effective MZ maps. First, the correlation between S2 and UAV-NDVI values was investigated. Secondly, contingency matrices and dichotomous tables (considering UAV-MZ maps as a reference) were developed to compare MZ maps produced using S2 and UAV imagery. Moreover, data on grape production and quality were analyzed through linear discrimination analyses (LDA) to evaluate the effectiveness of S2-MZs and UAV-MZs to explain spatial variability in yield and quality data. The outcomes highlight that S2 images can be quite good tools to manage fertilization based on the within-field vigor variability, of which they capture the main features. Nevertheless, as S2-MZs with low and high vigor were over-estimated, S2-MZ maps cannot be used for high-accuracy input management. From the LDA results, the UAV-MZs appeared slightly more performant than the S2-MZs in explaining the variability in grape quality and yield, especially in the case of low-vigor MZs. Full article

Climate variability in Mediterranean viticultural areas, primarily attributed to climate change, will significantly impact water requirements, consequently leading to changes in irrigation management. The primary aim of this study was to assess the response of the Tempranillo and Cabernet Sauvignon grape varieties when subjected to deficit drip irrigation (RDI), in comparison to non-irrigation (NI), during various climatic years. The defined irrigation strategies involved water application equivalent to 35% and 80% of the (ET0 (reference crop evapotranspiration) × Kc (crop coefficient)). The ecophysiology of both grapevines was evaluated through the measurement of stomatal conductance (gs), sap flow, transpiration, leaf water potential (LWP), and CO₂ assimilation (A). Additionally, essential parameters including the crop coefficient (Kc), transpiration, and intrinsic water use efficiency were calculated. The information gathered from the pressure–volume curves of Cabernet Sauvignon and Tempranillo encompassed the osmotic potential at full turgor (γπ100), osmotic potential at turgor loss or 0 turgor (γπ0), water content at turgor loss (CHR0), modulus of elasticity (ε), and water potential at turgor loss 0 (γ_H0). The results enable a precise estimation of the water requirements for irrigation, contributing to a deeper understanding of the physiological responses of both varieties. This comprehension aids in assessing the sustainability of these vineyards amidst unexpected changes in the global mean surface temperature. Full article

The Scholander-type pressure chamber to measure midday stem water potential (MSWP) has been widely used to schedule irrigation in commercial vineyards. However, the limited number of sites that can be evaluated using the pressure chamber makes it difficult to evaluate the spatial variability of vineyard water status. As an alternative, several authors have suggested using the crop water stress index (CWSI) based on low-cost thermal infrared (TIR) sensors to estimate the MSWP. Therefore, this study aimed to develop a low-cost wireless infrared sensor network (WISN) to monitor the spatial variability of MSWPs in a drip-irrigated Cabernet Sauvignon vineyard under two levels of water stress. For this study, the MLX90614 sensor was used to measure canopy temperature (Tc), and thus compute the CWSI. The results indicated that good performance of the MLX90614 infrared thermometers was observed under laboratory and vineyard conditions with root mean square error (RMSE) and mean absolute error (MAE) values being less than 1.0 °C. Finally, a good nonlinear correlation between the MSWP and CWSI (R² = 0.72) was observed, allowing the development of intra-vineyard spatial variability maps of MSWP using the low-cost wireless infrared sensor network. Full article

The efficient management of irrigation water can affect crop profitability quite significantly. The application of precision irrigation based on soil monitoring can help manage water resources. In viticulture, the irrigation technique is thought to strongly influence grape ripening and the final grape composition. In this study, an irrigation decision support system was compared to a surface drip irrigation system in a commercial vineyard located in Andrea (Southern Italy) planted with Vitis vinifera cv. Montepulciano. We aimed to investigate the ability of the DSS to save water while maintaining an acceptable yield and quality of the grapes. To allow for the comparison, eco-physiological as well as yield parameters were measured during the irrigation periods in both irrigation systems over two years (2019 and 2020). The results indicate that the vines grown using the DSS treatment were less stressed compared to the plants grown using farm irrigation in both years. The yield attributes showed slight or no significant differences between the treatments. The quality results showed no significant differences between the treatments in both years. Our results indicate that with savings of 10% and 17% of the irrigation water in the first and second year, respectively, the DSS was able to maintain good yield and quality levels as compared to the farm irrigation system. These two-year results provide a promising implementation of its use in precision irrigation. Full article

This study focuses on assessing the accuracy of supervised machine learning regression algorithms (MLAs) in predicting actual crop evapotranspiration (ETc act) for a deficit irrigated vineyard of Vitis vinifera cv. Tempranillo, influenced by a typical Mediterranean climate. The standard approach of using the Food and Agriculture Organization (FAO) crop evapotranspiration under standard conditions (FAO-56 Kc-ET₀) to estimate ETc act for irrigation purposes faces limitations in row-based, sparse, and drip irrigated crops with large, exposed soil areas, due to data requirements and potential shortcomings. One significant challenge is the accurate estimation of the basal crop coefficient (Kcb), which can be influenced by incorrect estimations of the effective transpiring leaf area and surface resistance. The research results demonstrate that the tested MLAs can accurately estimate ETc act for the vineyard with minimal errors. The Root-Mean-Square Error (RMSE) values were found to be in the range of 0.019 to 0.030 mm·h⁻¹. Additionally, the obtained MLAs reduced data requirements, which suggests their feasibility to be used to optimize sustainable irrigation management in vineyards and other row crops. The positive outcomes of the study highlight the potential advantages of employing MLAs for precise and efficient estimation of crop evapotranspiration, leading to improved water management practices in vineyards. This could promote the adoption of more sustainable and resource-efficient irrigation strategies, particularly in regions with Mediterranean climates. Full article

To optimise sector design in drip irrigation systems, a two-stage procedure is presented and applied in a commercial vineyard plot. Soil apparent electrical conductivity (ECa) mapping and soil purposive sampling are the two stages on which the proposal is based. Briefly, ECa data to wet bulb depth provided by the VERIS 3100 soil sensor were mapped before planting using block ordinary kriging. Looking for simplicity and practicality, only two ECa classes were delineated from the ECa map (k-means algorithm) to delimit two potential soil classes within the plot with possible different properties in terms of potential soil water content and/or soil water regime. Contrasting the difference between ECa classes (through discriminant analysis of soil properties at different systematic sampling locations), irrigation sectors were then designed in size and shape to match the previous soil zoning. Taking advantage of the points used for soil sampling, two of these locations were finally selected as candidates to install moisture sensors according to the purposive soil sampling theory. As these two spatial points are expectedly the most representative of each soil class, moisture information in these areas can be taken as a basis for better decision-making for vineyard irrigation management. Full article

Superabsorbent polymers (SAPs) addition to soil enhances the properties of soil and increase plant yields. Investigation of the efficacy of SAPs to reduce the rate of mineral fertilizers and produce high-quality grapes was the study’s main goal. This investigation was carried out for three seasons (2019, 2020, and 2021) in a private vineyard located in El-Menofia Governorate, Egypt. Autumn Royal grapevines were grafted on Freedom. The vines were seven years old and grown in newly reclaimed sandy soil irrigated by drip irrigation. Several concentrations of polyacrylamide polymer (50, 75, and 100 g/vine/three years) were applied to the examined soil with nitrogen and potassium fertilization rates of 100%, 75%, and 50% of the recommended rate of fertilizer. The data revealed that increasing the amount of applied polymer significantly improved bud burst and fruitful buds percentages; growth parameters; total leaf chlorophyll content; N, P, and K percentages in leaves; and yield. Thus, the most effective method for increasing fruit production was to apply 45 units of N and 75 units of K per feddan, along with 70 kg per feddan of soil conditioner, which is safe for humans and improves the physical and chemical properties of the soil. This treatment considers the impact of SAPs on the preservation of nutrients. Full article

The rapid and accurate acquisition of nitrogen, phosphorus and potassium nutrient contents in grape leaves is critical for improving grape yields and quality and for industrial development. In this study, crop growth was non-destructively monitored based on unmanned aerial vehicle (UAV) remote sensing technology. Three irrigation levels (W1, W2 and W3) and four fertilization levels (F3, F2, F1 and F0) were set in this study, and drip irrigation fertilization treatments adopted a complete block design. A correlation analysis was conducted using UAV multispectral image data obtained from 2019 to 2021 and the field-measured leaf nitrogen content (LNC), leaf potassium content (LKC) and leaf phosphorus content (LPC) values; from the results, the vegetation indices (VIs) that were sensitive to LNC, LKC and LPC were determined. By combining spectral indices with partial least squares (PLS), random forest (RF), support vector machine (SVM) and extreme learning machine (ELM) machine-learning algorithms, prediction models were established. Finally, the optimal combinations of spectral variables and machine learning models for predicting LNC, LPC and LKC in each grape growth period were determined. The results showed that: (1) there were high demands for nitrogen during the new shoot growth and flowering periods, potassium was the main nutrient absorbed in the fruit expansion period, and phosphorus was the main nutrient absorbed in the veraison and maturity periods; (2) combining multiple spectral variables with the RF, SVM and ELM models could result in improved LNC, LPC and LKC predictions. The optimal prediction model determination coefficient (R²) derived during the new shoot growth period was above 0.65, and that obtained during the other growth periods was above 0.75. The relative root mean square error (RRMSE) of the above models was below 0.20, and the Willmott consistency index (WIA) was above 0.88. In conclusion, UAV multispectral images have good application effects when predicting nutrient contents in grape leaves. This study can provide technical support for accurate vineyard nutrient management using UAV platforms. Full article

In semi-arid areas, vineyards grown for winemaking are usually mildly irrigated by drip irrigation systems in a manner maintaining drought stress. This practice ensures the proper development of vegetative and reproductive organs on the one hand, and on the other, the development of high-quality grapes which can be hampered by overly abundant water application. In previous work, we have developed and demonstrated an irrigation model suitable for high-quality grape production in semi-arid areas. Here, we tackle the question of proper irrigation initiation dates—should one wait for vines to develop drought stress before the initiation of irrigation, or rather commence irrigation earlier? Our results show that vines which undergo initial irrigation late in the growing season tend to develop a lower midday stem water potential even after irrigation initiation. In addition, these vines tend to produce a lower number of bunches per vine and smaller berry size, leading to lower yields. The wine produced from the late-irrigated treatments had a higher phenolic content, primarily due to higher levels of catechin and epicatechin. Their levels increased as irrigation initiation dates were delayed, while caffeic acid levels showed an opposite trend. Late irrigation also led to higher color intensities compared to those of irrigation at earlier stages, due to higher levels of most anthocyanins. Finally, we show that the overall wine sensory score, representing its overall quality, was approximately five points higher for wines made from delayed irrigation treatments compared to wines made from early season irrigation treatments. Full article

Vineyards represent complex Mediterranean agrosystems that deliver significant ecosystem services to society. Yet, many vine-growers still need to assimilate the importance of crop and soil management to the conservation of soil and water resources. The main objective of this study was to evaluate water use and the water balance terms in rainfed and irrigated vineyards in Italy and Portugal, respectively, in both cases aiming at the sustainability of natural resources use. The SIMDualKc model is used for both sites after calibration and validation by fitting soil water content measurements. The Italian case study focused on the impacts of inter-row conservation management in hillslope vineyards while the Portuguese case study analyzed irrigation water management under scarcity in flat vineyards. For the Italian vineyards, the model results focused on the evapotranspiration fluxes and their partition, control of surface runoff, and soil water recharge provided by the inter-row soil management using cover crops. Model results of the Portuguese case study showed the need for improving irrigation water use and the terms of water balance, namely referring to percolation and soil water evaporation. Both case studies further demonstrated the advantages of using computational tools to better cope with climate variability in the Mediterranean region and made evident the benefits of improved crop and soil management practices in counteracting land degradation and valuing the use and conservation of natural resources. Full article

In semi-arid vineyard agroecosystems, highly vulnerable in the context of climate change, the soil organic matter (OM) content is crucial to the improvement of soil fertility and grape productivity. The impact of OM, from compost and animal manure, on soil properties (e.g., pH, oxidisable organic C, organic N, NH₄⁺-N and NO₃⁻-N), grape yield and direct greenhouse gas (GHG) emission in vineyards was assessed. For this purpose, two wine grape varieties were chosen and managed differently: with a rain-fed non-trellising vineyard of Monastrell, a drip-irrigated trellising vineyard of Monastrell and a drip-irrigated trellising vineyard of Cabernet Sauvignon. The studied fertiliser treatments were without organic amendments (C), sheep/goat manure (SGM) and distillery organic waste compost (DC). The SGM and DC treatments were applied at a rate of 4600 kg ha⁻¹ (fresh weight, FW) and 5000 kg ha⁻¹ FW, respectively. The use of organic amendments improved soil fertility and grape yield, especially in the drip-irrigated trellising vineyards. Increased CO₂ emissions were coincident with higher grape yields and manure application (maximum CO₂ emissions = 1518 mg C-CO₂ m⁻² d⁻¹). In contrast, N₂O emissions, mainly produced through nitrification, were decreased in the plots showing higher grape production (minimum N₂O emissions = −0.090 mg N₂O-N m⁻² d⁻¹). In all plots, the CH₄ fluxes were negative during most of the experiment (−1.073−0.403 mg CH₄-C m⁻² d⁻¹), indicating that these ecosystems can represent a significant sink for atmospheric CH₄. According to our results, the optimal vineyard management, considering soil properties, yield and GHG mitigation together, was the use of compost in a drip-irrigated trellising vineyard with the grape variety Monastrell. Full article

Site-specific irrigation management for perennial crops such as grape requires water use assessments at high spatiotemporal resolution. In this study, small unmanned-aerial-system (UAS)-based imaging was used with a modified mapping evapotranspiration at high resolution with internalized calibration (METRIC) energy balance model to map water use (UASM-ET approach) of a commercial, surface, and direct-root-zone (DRZ) drip-irrigated vineyard. Four irrigation treatments, 100%, 80%, 60%, and 40%, of commercial rate (CR) were also applied, with the CR estimated using soil moisture data and a non-stressed average crop coefficient of 0.5. Fourteen campaigns were conducted in the 2018 and 2019 seasons to collect multispectral (ground sampling distance (GSD): 7 cm/pixel) and thermal imaging (GSD: 13 cm/pixel) data. Six of those campaigns were near Landsat 7/8 satellite overpass of the field site. Weather inputs were obtained from a nearby WSU-AgWeatherNet station (1 km). First, UASM-ET estimates were compared to those derived from soil water balance (SWB) and conventional Landsat-METRIC (LM) approaches. Overall, UASM-ET (2.70 ± 1.03 mm day⁻¹ [mean ± std. dev.]) was higher than SWB-ET (1.80 ± 0.98 mm day⁻¹). However, both estimates had a significant linear correlation (r = 0.64–0.81, p < 0.01). For the days of satellite overpass, UASM-ET was statistically similar to LM-ET, with mean absolute normalized ET departures (ET_d,MAN) of 4.30% and a mean r of 0.83 (p < 0.01). The study also extracted spatial canopy transpiration (UASM-T) maps by segmenting the soil background from the UASM-ET, which had strong correlation with the estimates derived by the standard basal crop coefficient approach (T_d,MAN = 14%, r = 0.95, p < 0.01). The UASM-T maps were then used to quantify water use differences in the DRZ-irrigated grapevines. Canopy transpiration (T) was statistically significant among the irrigation treatments and was highest for grapevines irrigated at 100% or 80% of the CR, followed by 60% and 40% of the CR (p < 0.01). Reference T fraction (T_rF) curves established from the UASM-T maps showed a notable effect of irrigation treatment rates. The total water use of grapevines estimated using interpolated T_rF curves was highest for treatments of 100% (425 and 320 mm for the 2018 and 2019 seasons, respectively), followed by 80% (420 and 317 mm), 60% (391 and 318 mm), and 40% (370 and 304 mm) of the CR. Such estimates were within 5% to 11% of the SWB-based water use calculations. The UASM-T-estimated water use was not the same as the actual amount of water applied in the two seasons, probably because DRZ-irrigated vines might have developed deeper or lateral roots to fulfill water requirements outside the irrigated soil volume. Overall, results highlight the usefulness of high-resolution imagery toward site-specific water use management of grapevines. Full article