Integrating Deficit Irrigation Strategies and Soil-Management Systems in Almond Orchards for Resilient Agriculture

Citation: García-Tejero, I.F.; Herencia-Galán, J.F.; Cárceles Rodríguez, B.; Calderón-Pavón, A.; Aldana Navarro, J.; Rubio-Casal, A.E.; Durán Zuazo, V.H. Integrating Deficit Irrigation Strategies and Soil-Management Systems in Almond Orchards for Resilient Agriculture. Agronomy 2024,14, 2288. https:// doi.org/10.3390/agronomy14102288 Academic Editors: El˙ zbieta Harasim and Cezary A. Kwiatkowski Received: 5 September 2024 Revised: 30 September 2024 Accepted: 2 October 2024 Published: 4 October 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). agronomy Article Integrating Deficit Irrigation Strategies and Soil-Management Systems in Almond Orchards for Resilient Agriculture Iván Francisco García-Tejero 1,* , Juan Francisco Herencia-Galán1, Belén Cárceles Rodríguez 2, Abel Calderón-Pavón1, Javier Aldana Navarro 1, Alfredo Emilio Rubio-Casal 3and Víctor Hugo Durán Zuazo 2 1IFAPA Centro “Las Torres”, Carretera Sevilla-Cazalla km 12.2, 41200 Sevilla, Spain; [email protected] (J.F.H.-G.); abel.calder[email protected] (A.C.-P.); [email protected] (J.A.N.) 2IFAPA Centro “Camino de Purchil”, Camino de Purchil s/n, 18004 Granada, Spain; [email protected] (B.C.R.); victor[email protected] (V.H.D.Z.) 3 Department of Plant Biology and Ecology, University of Seville, Av. Reina Mercedes, s/n, 41012 Sevilla, Spain; [email protected] *Correspondence: ivanf.gar[email protected]; Tel.: +34-955045500 Abstract: This work was conducted over three-year monitoring seasons of three almond cultivars (Guara, Marta, and Lauranne) subjected to deficit irrigation in combination with cover crops in a Mediterranean semiarid area (SW, Spain). Four water–soil treatments were evaluated based on the conjunction of two irrigation strategies: fully irrigated (FI), covering 100% of the ET C , and regulated deficit irrigation (RDI), with two soil-management systems: bare soil (BS) and cover crop based on a mixture of vetch (Vicia sativa L.) and oat (Avena sativa L.) (CC). Throughout the study period in trees, the yield, the stem water potential ( Ψstem ), leaf nutrient content (N, P, K, Ca, Mg, Na, Fe, Zn, Mn, and Cu) in soils, organic carbon, microbial biomass, fluoresceine diacetate, and enzymatic activities (dehydrogenase, protease, β -glucosidase, and alkaline phosphatase) were determined. In addition, the dry matter and carbon fixation by plant covers were evaluated. For Guara and Lauranne, yield reductions (22 and 26%, respectively) were found for water-stressed (RDI-CC) plots with respect to non-stressed combination (FI-CC) plots, contrasting with cv. Marta, without a significant impact on productivity in all combinations. That is, the RDI (~3.000 m 3 ha −1 ) strategy enabled acceptable productivity, offering promising possibilities for cultivation performance under water-scarcity scenarios. Important differences in Ψstem could be observed and ascribed to irrigation strategies, especially for Guara and Lauranne, but without significant effects due to the soil-management systems applied. No differences were observed in the tree nutritional status due to the presence or absence of CC; however, its presence increased the fixation of atmospheric carbon, which was not the case under BS conditions. Additionally, CC significantly fostered the microbial processes and enzymatic activities, particularly in upper soil layers (0–10 cm) and with plenty of water supply in FI-CC plots and to a lesser extent in RDI-CC plots, which could encourage prominent aspects for soil quality and health restoration. Thus, the cover crop is congruent with RDI to facilitate soil functionality and water savings in a changing climate, contributing to resilient farming systems in the Mediterranean environment. Keywords: cover crops; deficit irrigation; water stress; soil organic matter; soil microbiology; kernel yield; climate-resilient agriculture 1. Introduction Adaptation strategies to mitigate climate change in Mediterranean agriculture are crucial to ensure food security and reduce the vulnerability of agricultural systems [ 1 ], and this process should include integrated water and soil resources management, the promotion of sustainable agricultural practices, and crop diversification [ 2 – 5 ]. Resilient agriculture is an approach that involves sustainably using natural resources through crop Agronomy 2024,14, 2288. https://doi.org/10.3390/agronomy14102288 https://www.mdpi.com/journal/agronomy Agronomy 2024,14, 2288 2 of 19 and livestock production systems to attain long-term productivity and farm profits under climate variability [6,7]. To address these challenges, the European Union (EU) focuses on the main objective of the Common Agricultural Policy 2021–2027: promoting practices that ensure adaptation and mitigation of climate change through investments, incentives, and improvements of final returns [ 8 ]. The use of different techniques related to sustainable and regenerative agriculture and irrigation water productivity is within this set of required actions. In this sense, the implementation of regulated deficit irrigation (RDI) strategies or the implementation of cover crops (CC) is expected to promote the sustainability, profitability, and viability of Mediterranean agroecosystems [ 9 , 10 ]. These actions are even more necessary in regions where agricultural intensification has provoked soil degradation, as in many rural areas of Southern Europe, where natural resources are becoming even more scarce [11,12]. Recently, European initiatives such as the Green Deal or EU Mission: A soil deal for Europe have discussed agriculture as a potential sector to favor atmosphere C sequestration, improving soil organic carbon (SOC) levels and soil health. As a result of the latest Common Agricultural Policy (CAP) 2023–2027, there has been a growing interest in practices focused on more sustainable agriculture [ 13 – 15 ]. In this line, the optimal management of vegetative covers in woody crops is required to incorporate production systems into one of the ecoregimes (ER) considered in the latest CAP. Although accepting these ERs is voluntary, the budgetary amount considered in the direct aid independent of production (decoupled aid) is the second in terms of amount. It requires incorporating one of the nine ERs considered in the CAP Specific Plan (PEPAC) [ 16 ], especially practices six and seven, which are specifically devoted to woody crops. Particularly, in the Mediterranean region, several works have been conducted to demonstrate the effect of CC, achieving environmental and agronomic benefits [ 10 , 17 , 18 ]. That is, the implementation of CC based on legume (vetch, broad beans, lentils, etc.) plants or a mixture with grasses (barley) has been demonstrated to be an adequate strategy for improving soil quality terms and reducing soil degradation [ 19 , 20 ]. However, the combination of CC with water-saving practices such as RDI can pose a significant challenge, as these could compete with soil water resources, inducing a higher level of stress than that already endured by the crop due to drought conditions, although the final result will be determined by the species and its adaptation capability. In this context, understanding the effects of water scarcity on the soil’s capability to increase the SOC is a key factor in supporting the policy and decision making on strategies to enhance the resilience of agriculture to climate change [ 21 , 22 ]. Moreover, water scarcity is a long-standing issue in Mediterranean countries, as recent years have seen more frequent and prolonged adverse conditions due to the changing climate [ 3 ]. Thus, it is essential to increase awareness of water use efficiency, adapt agroecosystem management to present and future conditions, and prevent scenarios where the resilience capacity is severely limited [23,24]. Almond (Prunus dulcis Mill.) is the second perennial crop in Spain in terms of surface (~760,000 hectares), although its cultivation has traditionally been associated with marginal and rainfed areas [ 25 ]. This crop is considered a drought-tolerant plant, and its capability of adaptation to water-scarcity scenarios offers the possibility of obtaining competitive and sustainable yields when moderate deficit-irrigation strategies are implemented [26,27]. Concretely, previous works have shown that almonds can respond positively to moderate RDI strategies, often without any reduction in yield [ 28 , 29 ]. This optimum capacity of adaptation to situations of moderate water stress is a great advantage, especially when the average water allocation available for this crop is low. In general terms, this supply has not exceeded 3500 m 3 ha −1 in the best cases, while the average water needs for almonds in S Spain are around 7000 m 3 ha −1 [ 30 ]. According to Mirás-Avalos et al. [ 31 ], a threshold of 3500 m 3 ha −1 was established at which almond production values would be seriously affected. In contrast, above this threshold, losses would be drastically reduced and could even reach values very similar to those obtained by the crop under non-water-limiting conditions. However, these results depended greatly on the variety, the management Agronomy 2024,14, 2288 3 of 19 system, the plantation age, the deficit-irrigation strategy, and the duration of stress over several consecutive seasons [32,33]. Given these considerations, its development under “more sustainable agricultural practices”, such as CC incorporation in the fields, must be considered and deeply studied in order to determine if this type of practice could worsen the crop’s yield response when grown under a moderate RDI strategy. It is well-known that one of the most critical periods for the application of water stress in the almond corresponds to its vegetative development and fruit growth [ 34 – 36 ], coinciding with the time of maximum growth and development of CC. Therefore, it could lead to competition for the water stored in the soil, increasing the crop stress situation and negatively affecting productivity. Thus, determining the optimal procedure for integrating the plant covers, particularly for woody crops, remains a significant challenge under water-scarcity conditions when RDI is implemented [ 37 ]. In addition, the conjunction of both strategies (RDI × CC) could enhance climate change mitigation by fixing atmospheric carbon. This approach would also help to restore soil quality and fertility while promoting agroecological biodiversity, as suggested by Ramos et al. [38] and Repullo-Ruibérriz et al. [18]. We hypothesize that an equilibrium between CC and RDI practices can be achieved, allowing us to face the double challenge of adapting to climate change (due to the scarcity of water resources) and mitigation (favoring the sequestering of atmospheric C through the biomass of plant covers) without affecting the almond yield or its nutritional status while improving soil quality and health. Thus, the objective of this study was to evaluate the effects of the application of RDI combined with CC on soil carbon storage, microbial and enzymatic activity, crop water status, and the yield of three almond cultivars (Guara, Marta, and Lauranne) throughout a three-year monitoring season in the Mediterranean environment (SW Spain). 2. Materials and Methods 2.1. Experimental Site The experiment was conducted during three seasons (2021–2023) in an experimental mature almond orchard at the Andalusian Institute of Agricultural and Fisheries Research and Training (IFAPA), located in Alcaládel Río, Seville (SW Spain). Trees were planted in 2016, with three representative almond cultivars (Marta, Guara, and Lauranne) for the study area in the Guadalquivir River basin, and all grafted onto GN15 rootstock. The trees are 6 × 7 m spaced, with drip irrigation using two pipelines with emitters of 2.3 L h −1 . The soil is a typical clayey-loam texture Fluvisol [ 39 ], with a depth of more than 2.5 m, fertile, and a field capacity and permanent wilt point of 0.42 and 0.17 m3m−3, respectively. Climatic classification of the area is attenuated meso-Mediterranean, with an annual potential evapotranspiration (ET 0 ) rate of 1400 mm and an accumulated rainfall of 540 mm (average data corresponding to the last 15 years; obtained from the Andalusian Weather Information Network). 2.2. Field Experimental Design The experimental orchard was formed by four treatments based on a combination of two water-irrigation strategies and two soil-management systems, following a randomized complete block with four replications (Table 1). Accordingly, (i) fully irrigated (FI) trees were irrigated, covering 100% of the irrigation requirements (II.RR), and (ii) the regulated deficit irrigation (RDI) strategy involved irrigation while applying 80% of II.RR during the vegetative stage (from March to June) and post-harvest (from harvesting to the end of October, coinciding with the beginning of autumn rainfall). Additionally, during the kernel-filling stage (from June to mid-August or the beginning of September, just before harvesting), trees were irrigated, applying 40% of II.RR. Each irrigation strategy was subjected to two soil-management systems, which were performed as follows: (i) bare soil (BS), trying to keep the soil without spontaneous plants from February until foliage fall-over, applying two chemical mowing at the beginning of February and June, and (ii) the Agronomy 2024,14, 2288 4 of 19 implementation of cover crop (CC) with a mixture of legumes and cereal (75% Vicia sativa L. + 25% Avena sativa L.), which was planted in autumn after the first rains and mechanically controlled at the beginning of April of the following year (Figure 1). On that date, the cover crop was mowed, and mulch was spread over the soil surface. Punctual herbicide applications were performed to avoid additional competition from spontaneous plants during the maximum water-demand period. Table 1. The experimental treatments based on the irrigation water strategies and soil-management systems used. Natural Resource Strategy and Management Systems Water Full irrigation (100% II.RR) (FI) Regulated deficit irrigation (RDI) Soil Bare soil without cover crops (BS) Cover crop (legume + cereal) (CC) Water and soil treatments FI-BS RDI-BS FI-CC RDI-CC Agronomy 2024, 14, x FOR PEER REVIEW 5 of 20 Figure 1. Experimental plots with different soil-management systems: bare soils (A) and cover crop implementation (B). 2.3. Sampling, Chemical Determinations, and Microbiological and Enzymatic Activity Measurements Table 2 summarizes the different samplings, the timing, and the analysis developed throughout the experimental period. Soil samples were taken for each study season: (i) approximately one month after plant cover mowing (mid-May, approximately); and (ii) and at the end of the season (early October), coinciding with the beginning of leaf pulling and before the autumn sowing of plant cover for the following season. In each sampling, four replications were taken for each treatment (n = 4) and at three different soil depths (0–10, 10–25, and 25–50 cm); the samples taken for each treatment were randomly distributed throughout the experimental plot. Table 2. Sampling, timing, and measurements performed. Samples Timing Measurements Soil Spring (Mid-April) Autumn (October) SOC, MBC, FDA, DH, PROT, AP, GLUC Almond leaves Summer (Mid-June) Mineral status (N, K, P, Na, Ca, Mg, Cu, Zn, Fe, Mn) Almond tree Fortnightly (from April to September) Ψ stem , yield and its components (mid- August) Cover crop Before sowing (April) Dry matter SOC, soil organic carbon; MBC, microbial biomass carbon; FDA, fluoresceine diacetate activity; DH, dehydrogenase; PROT, protease; AP, alkaline phosphatase; GLUC, β-glucosidase; Ψ stem , stem water potential. Figure 1. Experimental plots with different soil-management systems: bare soils (A) and cover crop implementation (B). Irrigation doses were calculated according to the methodology proposed by Allen et al. [ 40 ], obtaining the values of ET 0 by using a weather station close to the experimental orchards (<500 m). The local crop coefficients used during the experimental period ranged from 0.4 to 1.2, according to García-Tejero et al. [ 41 ]. Overall, RDI receives ~50% of the irrigation water supply in FI. Agronomy 2024,14, 2288 5 of 19 Finally, routine almond cultivation techniques were used according to the regulations for integrated production for the study area (Andalusia, SW Spain). In this sense, the experimental orchard annually received NPK complex fertilizer (15-15-15, 250 kg ha −1 ) at pre-flowering, with additional nutrients incorporated until reaching NPK units around 80-45-100; finally, pest and disease products were applied when required. 2.3. Sampling, Chemical Determinations, and Microbiological and Enzymatic Activity Measurements Table 2summarizes the different samplings, the timing, and the analysis developed throughout the experimental period. Soil samples were taken for each study season: (i) approximately one month after plant cover mowing (mid-May, approximately); and (ii) and at the end of the season (early October), coinciding with the beginning of leaf pulling and before the autumn sowing of plant cover for the following season. In each sampling, four replications were taken for each treatment (n= 4) and at three different soil depths (0–10, 10–25, and 25–50 cm); the samples taken for each treatment were randomly distributed throughout the experimental plot. Table 2. Sampling, timing, and measurements performed. Samples Timing Measurements Soil Spring (Mid-April) Autumn (October) SOC, MBC, FDA, DH, PROT, AP, GLUC Almond leaves Summer (Mid-June) Mineral status (N, K, P, Na, Ca, Mg, Cu, Zn, Fe, Mn) Almond tree Fortnightly (from April to September) Ψstem, yield and its components (mid-August) Cover crop Before sowing (April) Dry matter SOC, soil organic carbon; MBC, microbial biomass carbon; FDA, fluoresceine diacetate activity; DH, dehydrogenase; PROT, protease; AP, alkaline phosphatase; GLUC, β-glucosidase; Ψstem, stem water potential. Additionally, before the plant cover was mowed, four replications (n= 4) were taken at random points of the plot using a 0.5 × 0.5 m harrow to determine the accumulated dry matter of the cover crops and its potential for C fixation via above-ground biomass. In addition, coinciding with the beginning of the kernel-filling period, four leaf samples were taken in each almond cultivar and treatment. These samples were taken around the trees, ensuring they corresponded to mature and healthy leaves. The macro- and micronutrients in leaves were determined in accordance with the standard methods for the examination of this type of sample [ 42 ]. The SOC was analyzed following the methodology proposed by Walkley and Black [ 43 ]. Additionally, microbial activity [the hydrolysis of fluorescein diacetate activity (FDA)] was determined, as indicated by Adam and Duncan [ 44 ]. Microbial biomass carbon was analyzed using the fumigation–extraction method [ 45 , 46 ]. Dehydrogenase activity was determined according to Thalmann [ 47 ], and the protease was described by Ladd and Butler [ 48 ]. Finally, alkaline phosphatase activity was analyzed following the Tabatabai and Bremmer [ 49 ] protocols, and β-glucosidase was measured according to Eivazi and Tabatabai [50]. During the irrigation period, measurements of stem water potential ( Ψstem ) were taken at fortnightly intervals at midday (12:00 solar time). For midday Ψstem readings, the standard procedure was bagging (aluminum foil-covered plastic bags) a leaf on the tree at least 15 min before sampling from monitored trees under different treatments; this allowed it to reach equilibrium. Then, the leaves were cut off and placed in a pressure chamber with the petiole protruding out. Concretely, Ψstem was measured using a pressure chamber (Soil Moisture Equipment Corp., Sta. Barbara, CA, USA) in four trees per cultivar and treatment using one leaf per tree (n= 4) in three phenological stages: vegetative (P-I), kernel-filling (P-II), and post-harvest (P-III). Agronomy 2024,14, 2288 6 of 19 At the end of each season, almond production was measured in terms of the in-shell yield. Harvesting operations were performed using a mechanical vibrator and peeling to remove the hull. Later, almonds were air-dried and weighed once they reached a humidity content below 6%. For this, almond samples per monitored tree were weighed. Once the kernel unit weight (with and without the shell) was known, kernel yield was estimated by calculating their ratio. Ultimately, the irrigation water productivity (IWP) was estimated annually and for the whole study period as the almond yield divided by the total seasonal irrigation water applied (kg m−3). 2.4. Statistical Analysis Considering that all of the data were obtained in three consecutive seasons, year-to- year, an exploratory and descriptive analysis of all measurements (the nutritional status of leaves, soil measurements, and dry matter of cover crops) for each treatment was performed, checking the normality and homoscedasticity using XLSTAT Premium 2016 (Addinsoft, New York, NY, USA). After, a one-way analysis of variance (ANOVA) was performed to study the single effect of irrigation treatment and soil management and a two-way ANOVA for multiple effects, with the treatment means separated using the Tukey multiple range test at a 5% significance level. For each cultivar, the kernel yield and its components were analyzed year-to-year (kernel unit weight, the ratio between kernel weight vs. almond weight, and the IWP), applying an ANOVA with Tukey’s test, considering the irrigation treatments, the soil management, and the interactions between them as factors. As all the data were obtained in three different seasons, in order to analyze the dataset for the three seasons (n= 12, 4 replicates per treatment × 3 seasons), dataset normalization for each treatment and cultivar was performed, following the Sterk and Stein [ 51 ] procedures. In this regard, this methodology minimizes the variability associated with the particular conditions in each season to group the values. It allows applying an overall analysis with the entire set of data (n= 12) according to the following equation: XN=Xi Xav annual ×Xav total (1) where XN is the normalized variable for each treatment and cultivar, Xi is the single value obtained for each replication, Xav annual is the average value for a single treatment and cultivar in a year, and Xav total is the average value for a single treatment and cultivar during all the monitored seasons. 3. Results and Discussion 3.1. Crop Water Requirements, Irrigation Doses, Crop Water Status, and Leaf Nutrient Status Table 3presents the crop water requirements and irrigation doses applied during the study period. The FI strategy received irrigation doses between 6060 and 6310 m 3 ha −1 , while the RDI amounts were between 3020 and 3620 m 3 ha −1 , which was approximately 50% of the amount of water provided in the fully irrigated trees. According to the treatment design, the RDI-CC and RDI-BS plots received the same irrigation doses, the only difference being the presence/absence of plant covers. The largest water withholdings in RDI were applied during the kernel-filling period, as was designed for this strategy at the beginning of the experiment. In this stage, during the first year, the RDI received 38% of the irrigation requirements (II.RR.), while during the second and third years of the study, the water allocations in that period were about 35% of the total II.RR. In addition, taking advantage of the early spring rains, the RDI strategy was not subjected to stress situations during vegetative growth, except for the third year of the study, when the rainfall recorded in that period was very low. During the post-harvest period (from mid-August to the end of October) in the first year, there was hardly any stress in the RDI, while in the second and third seasons, this irrigation strategy amounted to 58 and 74% of II.RR. Thus, analyzing the whole dataset, the RDI received during the Agronomy 2024,14, 2288 7 of 19 fruit-growth, kernel-filling, and post-harvest stages amounted to 78, 36, and 70% of the II.RR., respectively, very close to the irrigation strategy initially designed. Table 3. The rainfall, crop water requirements and evapotranspiration, and irrigation doses during the study period in each phenological stage. Strategy II.RR. Rainfall ETCPhenological Stage Season RDI FI (mm) 73 116 85 198 224 P-I 2021 156 397 406 3 408 P-II 79 118 85 79 140 P-III 308 631 576 280 772 Total 67 96 75 164 190 P-I 2022 142 355 412 2 413 P-II 93 155 164 73 215 P-III 302 606 651 239 818 Total 144 184 203 107 278 P-I 2023 124 313 358 25 375 P-II 104 128 141 37 167 P-III 362 625 702 169 820 Total ET C , Crop water evapotranspiration; II.RR., irrigation requirements; FI, fully irrigated; RDI, regulated deficit irrigation; P-I, P-II, and P-III are the three main phenological stages (vegetative, kernel-filling, and postharvest, respectively). Figure 2shows the average values of Ψstem for the three studied seasons in each cultivar and treatment. The greatest differences were found during the kernel-filling period, which were observed for all almond cultivars. Additionally, the presence of plant cover increased these differences; therefore, the lowest Ψstem were detected mainly in RDI-CC plots, with mean values between − 1.5 and − 1.7 MPa for all almond cultivars. In contrast, CC did not seem to affect the crop water status in the FI plot and, in the case of the FI-CC, improved these values with respect to the same treatment under FI-BS ( − 0.68 vs. −1.31 MPa in cv. Guara, − 1.21 vs. − 1.33 MPa in cv. Marta, and − 1.37 vs. −1.42 MPa in cv. Lauranne). This fact was perceptible, and the decrease in soil water content induced by RDI could be triggered in extreme situations, decreasing the Ψstem in almond trees below −2 MPa and stomatal conductance at 0.15 mol m −2 s −1 , as was outlined by Sperling et al. [52]. Throughout the vegetative growth period, even though no major irrigation restrictions were applied in RDI compared to FI, there were significant differences in the crop water status for the three cultivars. Also, throughout the post-harvest period, no significant differences were recorded among treatments in any of the monitored cultivars, showing that, at least during this period, the irrigation restrictions were not reflected, at least in terms of Ψstem , probably because of the lower crop water uptake because of the leaves’ progressive senescence. In relation to the mineral content in leaves, no significant effects were determined for the different treatments. Concretely, the average values of macronutrients (NPK) were similar in the four treatments, comparably observed for micronutrients (Fe, Cu, Zn, and Mn) (Table 4). Minor differences were observed in the Na levels, which were significantly higher for RDI-CC in cv. Guara in comparison to the remaining treatments. With this same logic, higher levels of Ca were denoted in RDI with respect to FI, occurring in the three studied almond cultivars, whereas higher levels in RDI were found for cv. Lauranne in comparison to FI plots for the case of Mg. However, Ca, Mg, and Na are elements highly related to the crop response under drought conditions, and their increase agrees with the presence of an osmoregulatory response when stomatal conductance regulation is low, as is the case for almonds, this being considered an anhysohidric species [53]. Agronomy 2024,14, 2288 8 of 19 Agronomy 2024, 14, x FOR PEER REVIEW 8 of 20 were observed for all almond cultivars. Additionally, the presence of plant cover increased these differences; therefore, the lowest Ψ stem were detected mainly in RDI-CC plots, with mean values between −1.5 and −1.7 MPa for all almond cultivars. In contrast, CC did not seem to affect the crop water status in the FI plot and, in the case of the FI-CC, improved these values with respect to the same treatment under FI-BS (−0.68 vs. −1.31 MPa in cv. Guara, −1.21 vs. −1.33 MPa in cv. Marta, and −1.37 vs. −1.42 MPa in cv. Lauranne). This fact was perceptible, and the decrease in soil water content induced by RDI could be triggered in extreme situations, decreasing the Ψ stem in almond trees below −2 MPa and stomatal conductance at 0.15 mol m −2 s −1 , as was outlined by Sperling et al. [52]. Figure 2. The stem water potential dynamics for each treatment and phenological stage in almond cultivars. FI, full irrigation; RDI, regulated deficit irrigation; BS, bare soil; CC, cover crop. Each value corresponds to the average for the three studied seasons (n = 12). P-I, P-II, and P-III are the three main phenological stages (vegetative, kernel-filling, and post-harvest, respectively). Vertical bars are the standard error. Different letters represent significant treatment differences (p < 0.05) within each phenological period. Throughout the vegetative growth period, even though no major irrigation restrictions were applied in RDI compared to FI, there were significant differences in the crop water status for the three cultivars. Also, throughout the post-harvest period, no Figure 2. The stem water potential dynamics for each treatment and phenological stage in almond cultivars. FI, full irrigation; RDI, regulated deficit irrigation; BS, bare soil; CC, cover crop. Each value corresponds to the average for the three studied seasons (n= 12). P-I, P-II, and P-III are the three main phenological stages (vegetative, kernel-filling, and post-harvest, respectively). Vertical bars are the standard error. Different letters represent significant treatment differences (p< 0.05) within each phenological period. Thus, in general, the potential competition for nutrients by plant covers that could alter the mineral nutrition of the main crop did not occur under our experimental conditions. This was presumably impossible due to the surplus of nutrient inputs associated with important amounts of the mineral fertilizers applied. However, the indisputable advantage attributable to plant cover is that they can regulate these nutrient surpluses by storing and recycling them into their tissues and, at the same time, releasing them from residues in a natural biological cycle, which is absent in bare soil. Agronomy 2024,14, 2288 9 of 19 Table 4. Leaf mineral content for each water soil treatment. Mn (ppm) Cu (ppm) Zn (ppm) Fe (ppm) Na (ppm) %Ca % Mg %K %P %N Treatment Cultivar 39.1 8.6 a 35.3 a 358.8 a 230.8 a 5.2 a 0.7 a 2.2 a 0.14 a 2.8 a FI CC Guara 37.9 a 8.2 a 34.7 a 335.9 a 210.2 a 4.8 a 0.6 a 2.7 a 0.14 a 2.9 a FI BS 33.7 a 9.8 a 35.0 a 397.5 a 320.4 b 7.2 b 0.8 a 2.7 a 0.13 a 2.4 a DI CC 32.4 a 9.9 a 33.7 a 246.9 a 232.8 a 7.0 b 0.8 a 2.6 a 0.13 a 2.1 a DI BS 39.7 a 11.2 a 31.6 a 326.9 a 273.4 a 4.8 a 0.5 a 2.5 a 0.14 a 2.5 a FI CC Marta 38.5 a 8.7 a 33.9 a 298.6 a 254.8 a 5.0 a 0.6 a 2.8 a 0.14 a 2.6 a FI BS 35.6 a 9.4 a 29.6 a 324.5 a 287.8 a 6.7 b 0.8 a 2.5 a 0.12 a 2.3 a DI CC 39.1 a 12.1 a 39.0 a 386.6 a 246.0 a 5.8 b 0.9 a 2.7 a 0.12 a 2.3 a DI BS 34.0 a 9.4 a 34.3 a 384.4 a 305.3 a 4.8 a 0.6 a 2.8 a 0.15 a 2.7 a FI CC Lauranne 35.0 a 11.2 a 33.9 a 272.3 a 260.2 a 4.9 a 0.6 a 2.7 a 0.14 a 2.8 a FI BS 33.1 a 8.7 a 34.1 a 340.1 a 332.8 a 8.2 b 0.9 b 2.7 a 0.13 a 2.3 a DI CC 36.7 a 11.3 a 37.3 a 341.4 a 290.8 a 6.8 b 0.9 b 2.8 a 0.13 a 2.4 a DI BS FI, full irrigation; RDI, regulated deficit irrigation; BS, bare soil; CC, cover crop. Each value corresponds to the average for the three studied seasons (n= 12). Different letters represent significant differences among different treatments (p< 0.05) within each cultivar. 3.2. Cover Crop Dry Mass Production and Atmospheric Carbon Fixation The treatments based on combination of plant covers with both irrigation strategies and its effect on amount of dry mass generated was marked by the rainfall amount during the months after planting, and not so much with the irrigation supply (Figure 3). That is, during the 2021 season, with a cover crop sown in autumn 2020, the average dry mass production was of 6000 and 5000 kg ha −1 in the FI and RDI strategies, respectively. Likewise, during the subsequent seasons, dry matter production by the cover crop was about 1400 and 1800 kg ha −1 in 2022, and 2400 and 2100 kg ha −1 in 2023 for the FI and RDI plots, respectively, with no significant differences in any of monitored seasons. It should be noted that, during 2021, the rainfall recorded from planting the cover crop to harvesting amounted to 323 mm, while during the second and third seasons, this rainfall decreased to 255 and 204 mm, respectively, which would partly explain the lower production of biomass in these seasons. Agronomy 2024, 14, x FOR PEER REVIEW 10 of 20 Figure 3. Average dry matter from plant covers under each irrigation strategy and monitored season for each year. FI, full irrigation; RDI, regulated deficit irrigation; CC, cover crop. Each value corresponds to the average for each treatment and season (n = 4). Vertical bars are the standard error. Different letters represent significant differences among treatments (p < 0.05). These results of dry matter from plant covers correspond to C fixation of 38.4 and 40% for FI-CC and RDI-CC plots, respectively, which imply a C sequestration rate of 1.2 t per hectare for both treatments, evidencing the advantage of this combination for the encouragement of agricultural activity as a climate change-mitigating activity. In this sense, for a Mediterranean environment, the cover crops contributed significantly to CO 2 reduction and recycling of free-unused plant nutrients in woody fruit plantations [54]. Although the purpose of this work was not to elucidate the mechanism of plant cover-induced atmospheric C sequestration nor to appraise C balance in our production system, it was evident that above-ground plant C inputs partly explain the determined soil C gains. When considering the designed treatments, it was clear that the soil C gains and generation of biomass via C fixation were manifested in the plots with plant covers compared to those that were not grown. Therefore, implementing policies that compensate farmers for sequestering C may offset the losses in profits associated with plant cover use and provide incentives for its adoption. 3.3. Soil Organic Carbon, Microbiological Biomass, and Enzymatic Activity Figure 4 shows the SOC and soil microbiological biomass carbon (MBC) contents for each treatment at different soil depths and during early spring and late autumn periods. The highest levels of SOC were determined, especially at the first 10 cm soil depth, following the same trend with higher contents in CC treatments than BS, with a slight increase for autumn samples with respect to the spring ones. In this line, Madejón et al. [55] stated that for a large range of soil types and environmental conditions, no-tillage operations and plant covers can effectively increase SOC rates and foster more favorable conditions, particularly in the upper soil layers. Consequently, an increase in SOC could also encourage an improvement in the water retention capacity in soils [56]. In contrast, for remaining soil depths, a declining pattern for FI-CC and FI-BS plots was found, particularly in the deeper soil layers (25–50 cm). In addition, higher SOC contents were determined in RDI-CC compared to FI-CC at 10–25 and 25–50 cm soil depths, which could be compatible with less organic matter mineralization in the most water-deficient conditions. This fact concorded with the findings of Núñez and Schipanski [57], who reported that water irrigation augments SOC contents in semi-arid agroecosystems. Finally, the amount of SOC stored in the surface soil highly depends on the cumulative effect of plant covers. In this context, Poeplau and Don [58] reported that the C inputs to the soil undergo various transformations depending on the turnover time of the plant residues, and a fraction of the added soil C remains in a stable organic form and contributes to SOC accumulation in the long term. Figure 3. Average dry matter from plant covers under each irrigation strategy and monitored season for each year. FI, full irrigation; RDI, regulated deficit irrigation; CC, cover crop. Each value corresponds to the average for each treatment and season (n= 4). Vertical bars are the standard error. Different letters represent significant differences among treatments (p< 0.05). These results of dry matter from plant covers correspond to C fixation of 38.4 and 40% for FI-CC and RDI-CC plots, respectively, which imply a C sequestration rate of Agronomy 2024,14, 2288 16 of 19 4. Cárceles, R.B.; Durán, Z.V.H.; Soriano, R.M.; García-Tejero, I.F.; Gálvez, R.B.; Cuadros, T.S. 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