Long-Term Correlation between Water Deficit and Quality Markers in HydroSOStainable Almonds

agronomy Article Long-Term Correlation between Water Deficit and Quality Markers in HydroSOStainable Almonds Leontina Lipan 1, Marina Cano-Lamadrid 1, Francisca Hernández 2, Esther Sendra 1, Mireia Corell 3,4, Laura Vázquez-Araújo 5,6 , Alfonso Moriana 3,4 and Ángel A. Carbonell-Barrachina 1,* 1Department of Agro-Food Technology, Research Group “Food Quality and Safety, CSA”, Universidad Miguel Hernández de Elche (UMH), Escuela Politécnica Superior de Orihuela (EPSO), Carretera de Beniel, km 3.2, 03312 Orihuela, Spain; [email protected] (L.L.); [email protected] (M.C.-L.); esther[email protected] (E.S.) 2 Department of Plant Science and Microbiology, Research Group “Plant Production and Technology”, UMH, EPSO, Carretera de Beniel, km 3.2, 03312 Orihuela, Spain; [email protected] 3Departamento de Ciencias Agroforestales, ETSIA, Universidad de Sevilla, Carretera de Utrera, km 1, 41013 Sevilla, Spain; [email protected] (M.C.); [email protected] (A.M.) 4Unidad Asociada al CSIC de Uso sostenible del suelo y el agua en la agricultura (US-IRNAS), Crta de Utrera, km 1, 41013 Sevilla, Spain 5BCC Innovation, Technological Center in Gastronomy, Juan Avelino Barriola 101, 20009 Donostia-San Sebastián, Spain; [email protected] 6Basque Culinary Center, Mondragon Unibersitatea, Juan Avelino Barriola 101, 20009 Donostia-San Sebastián, Spain *Correspondence: [email protected]; Tel.: +34-966-749-754 Received: 22 August 2020; Accepted: 23 September 2020; Published: 25 September 2020   Abstract: Global warming enhances the rainfall and temperature irregularity, producing a collapse in water resources and generating an urgent need for hydro-sustainable thinking in agriculture. The aim of this study was to evaluate the correlation between the water stress of almond trees and quality parameters of fruits, after 3 years of experiments, with the objective of establishing quality markers necessary in the certification process of hydroSOStainable almonds. The results showed positive correlations among the stress integral (SI) and dry weight, color coordinates (L*,a* and b*), minerals (K, Fe, and Zn), organic acids (citric acid), sugars (sucrose, fructose, and total sugars), antioxidant activity, and fatty acids [linoleic acid, polyunsaturated (PUFA)/monounsaturated (MUFA) ratio, PUFA and SFA, among others]. As well as negative correlations of SI with water activity, weight (almond, kernel, and shell), kernel size, minerals (Ca and Mg), fatty acids (oleic acid, oleic/linoleic ratio, MUFA, and PUFA/SFA ratio), and sensory attributes (size, bitterness, astringency, benzaldehyde, and woody). Finally, this research helped to prove key quality parameters that can be used as makers of hydroSOStainable almonds. In addition, it was demonstrated that controlling water stress in almond trees by using deficit irrigation strategies can lead to appropriate yields, improve the product quality, and consequently, lead to a final added value. Keywords: Prunus dulcis; Vairo; water stress; regulated deficit irrigation; sustained deficit irrigation; quality markers 1. Introduction Almonds [Prunus dulcis (Mill.) D.A. Webb] are an economically and nutritionally important agricultural good, widely consumed in the Mediterranean diet either as a snack or as an ingredient for confectionery (turr ó n) and baking [ 1 ]. Almond consumption increased by 1.9% at the end of 2018 Agronomy 2020,10, 1470; doi:10.3390/agronomy10101470 www.mdpi.com/journal/agronomy Agronomy 2020,10, 1470 2 of 22 in Spain, indicating that consumer appreciation for this nut is high and constantly increasing due to its nutrition values, pleasant flavor, and healthy properties [ 2 , 3 ]. Moreover, raising the number of health-conscious consumers, together with environmental and animals care, lactose intolerance, and hypercholesterolemia in consumers, plant-based milk, yogurt, and cheese has grown over the last decade [ 4 ]. For instance, the global almond milk market is predicted to expand 14.3% by 2025; this product being considered a dairy alternative rich in vitamin E and omega 3 and 6 fatty acids. After all, this might be also an important reason that led to almond consumption growth [4–6]. Almond is the third largest crop in terms of surface and the most cultivated tree nut in Spain [ 7 ]. Besides, Spain is the main European almond producer and the second-largest in the world (339,033 t in-shell almonds), after the United States of America (1,872,500 t) [ 8 ]; Andalusia (111,877 t), Aragon (63,235 t), Castilla La-Mancha (53,201 t), and Valencian Community (40,875 t) are the main producing regions [ 9 ]. However, almond production in Spain is relatively low because this crop has been mainly grown in marginal areas where it has traditionally cultivated under restrictive conditions [ 7 ]. The almond tree is a drought-tolerant species, but due to the low yield in rainfed conditions ( 380 kg ha−1 ), irrigation water is necessary to increase its productivity (1842 kg ha−1) [9]. The Mediterranean regions are the most affected areas by water stress due to the scarcity and irregularity of rainfall. Moreover, the highest crop water needs are found in areas that are hot, dry, windy, and sunny due to the growth needs of the plant (foliage expansion, vegetative growth, and fruit yield) [ 10 ]. The water scarcity crisis is considered the biggest global risk for the world economy and it is affecting every continent [ 11 ]. Regarding agricultural sector, there is a consensus about the inadequate management of water resources and the need of achieving an equilibrium between rural development, food security, and environment protection [ 12 ]. The population growth leads to an expansion in intensive food production that alters the environment due to greenhouse gas emissions, soil deterioration, and water stress [ 13 ]. The main impact produced by climate change includes significant alteration in the average temperature and the rainfall irregularity [ 14 ], which leads to a substantially increase in irrigation water demand. In almond farming, climate change can provoke phenological variations on fruit, which may affect the final yield, quality, and marketability [ 15 ]. Consequently, all these changes might lead to a reduction in the productivity of agro-ecosystems, a progressive decline of rural areas, and even, land abandonment [16]. The implementation of sustainable irrigation strategies is an important tool to attenuate these negative aspects. However, these strategies must fulfill two important requirements: (i) causing minimal production losses and (ii) ensuring the final quality of the fruits. Regulated deficit irrigation (RDI) is one of these strategies meant to increase the water productivity with minimal yield losses and consists of reducing the amount of water during the kernel-filling stage in almond orchards [ 17 ]. Sustained deficit irrigation (SDI) is another strategy, which consists of applying a uniform and reduced amount of water during the whole growing cycle, creating a progressive stress in plants throughout the season [18]. Recently, new research lines focused on water resources sustainability have been developed for different crops (almonds, pistachios, olives, etc.), and the foodstuffs produced under controlled water stress conditions are called hydroSOStainable foods [ 19 – 21 ]. However, a variability in crop responses to water stress was reported for these products with the quality parameters being cultivar-, crop-, and year-dependent. Therefore, long-term research to decide which quality parameters are really affected by the waters stress conditions is needed. Consequently, the aim of this study was to correlate water deficit response with quality parameters after 3 years of experiments (2017, 2018, 2019) to identify those parameters that behave in the same way throughout the trials. These results are essential to establish the future hydroSOStainable markers. Agronomy 2020,10, 1470 3 of 22 2. Materials and Methods 2.1. Plant and Experimental Conditions The experiment was performed during 3 growing cycles (2017, 2018, and 2019) in a commercial orchard “La Florida” (37.23 ◦ N, − 5.91 W, Dos Hermanas, Seville, Spain). The almond [P. dulcis (Mill.) D.A. Webb cv. Vairo] orchard was 7 years old at the beginning of the experiment. The tree spacing was an 8 m × 6 m square pattern, while the irrigation system used a drip irrigation line (3.8 L h −1 ) with drippers separated at 0.4 m distance. The weather data for each season were obtained from the “Instituto de Investigaci ó n y Formaci ó n Agraria (IFAPA) Los Palacios” station in the Andalusian weather stations network (Figure 1) located about 6 km away from the experimental orchard. Agronomy 2020, 10 x FOR PEER REVIEW 3 of 23 2. Materials and Methods 2.1. Plant and Experimental Conditions The experiment was performed during 3 growing cycles (2017, 2018, and 2019) in a commercial orchard “La Florida” (37.23° N, −5.91 W, Dos Hermanas, Seville, Spain). The almond [P. dulcis (Mill.) D.A. Webb cv. Vairo] orchard was 7 years old at the beginning of the experiment. The tree spacing was an 8 m × 6 m square pattern, while the irrigation system used a drip irrigation line (3.8 L h−1) with drippers separated at 0.4 m distance. The weather data for each season were obtained from the “Instituto de Investigación y Formación Agraria (IFAPA) Los Palacios” station in the Andalusian weather stations network (Figure 1) located about 6 km away from the experimental orchard. Figure 1. Climatic conditions during the three experimental seasons (2017–2019). (a) Seasonal daily reference evapotranspiration (circles) and rain (bars). (b) Seasonal daily maximum air temperature (white circles) and maximum vapor pressure deficit (VPD) (black circles). Vertical dots lines indicated from right to left each season, the beginning of pit hardening, early recovery, and regular recovery. DOY: day of the year. The data for all 3 seasons were typical of Mediterranean zones, with null rainfall during the summer period and warm winters. The threshold values of midday stem water potential (SWP) were measured weekly, most of the dates, or every ten days using a pressure chamber (PMS Instrument Figure 1. Climatic conditions during the three experimental seasons (2017–2019). ( a ) Seasonal daily reference evapotranspiration (circles) and rain (bars). ( b ) Seasonal daily maximum air temperature (white circles) and maximum vapor pressure deficit (VPD) (black circles). Vertical dots lines indicated from right to left each season, the beginning of pit hardening, early recovery, and regular recovery. DOY: day of the year. Agronomy 2020,10, 1470 4 of 22 The data for all 3 seasons were typical of Mediterranean zones, with null rainfall during the summer period and warm winters. The threshold values of midday stem water potential (SWP) were measured weekly, most of the dates, or every ten days using a pressure chamber (PMS Instrument Company, Albany, OR, USA). These values were used for the irrigation schedule by evaluating the stress level in the plant with the methodology proposed by Myers [ 22 ] according to the following expression Equation (1): SI =|X(ψstem −(−0.2)) ×n(1) where SI was the stress integral, ψstem is the average midday stem water potential for any interval, and nis the number of days in the interval. Most of the measurements were weekly. 2.2. Irrigation Treatments Four irrigation treatments were applied to the experimental plots. Each treatment represents different strategies of farmers in conditions of water scarcity. Moderate RDI is a controlled deficit irrigation in which applied water is lower than full irrigation but restricted considering an accurate water management. Severe RDI (was considered due to the low water availability) represents concentrated irrigation mainly during postharvest. Finally, SDI, is a strategy that was not considered in the phenological stages, and then, postharvest irrigation was very limited. These treatments are described in detail below: • Full irrigation (T1): irrigated to assure the crop needs. Irrigation was daily and irrigation scheduling was performed every week. Water needs were estimated with the crop evapotranspiration (ETc) approach according to Steduto et al. [ 23 ] using reduction coefficients (Kr) around 0.6. In addition, water status was evaluated using midday stem water potential and compared to the McCutchan and Shackel [ 24 ] baseline. When water status was more negative than expected, irrigation was increased by 150% ETc. • Moderate RDI (T2): the water stress was imposed during the kernel-filling period; almond trees were irrigated when SWP was below − 1.5 MPa, and for the rest of the time, trees were irrigated to keep an SWP as the baseline proposed by McCutchan and Shackel [ 24 ]. Equation (2) estimated optimum midday stem water potential in relation with vapor pressure deficit (VPD): SWP =(−0.41)×(−0.12VPD)(2) where: SWP is optimum midday stem water potential (MPa) and VPD is vapor pressure deficit (KPa). • Severe RDI (T3): the same as T2, except that trees were irrigated when SWP was below − 2.0 MPa during kernel filling and maximum seasonal water was considered (120 mm, around 20% ETc). Therefore, after harvest, when total applied water was reached, irrigation stopped. • SDI (T4): the same as T3, but tree water status was not considered. Irrigation was applied in a constant daily rate around 1–2 mm per day. The main differences between both strategies (T3 and T4) was that T4 limited postharvest irrigation more than T3. Harvesting was done with a self-propelled trunk shaker with collector in the mid of August (28 weeks after blossom). The treatments were separately harvested, and almonds were sun-dried until a moisture content lower than 5% was achieved. Later, in-shell almonds were delivered to Miguel Hernández University (Orihuela, Alicante, Spain) for analysis. 2.3. Physical Parameters 2.3.1. Kernel Ratio The ratio between the mass of in-shell almonds and kernel was calculated from 12 kg of whole fruit per treatment and year. Agronomy 2020,10, 1470 5 of 22 2.3.2. Dry Weight and Water Activity For the dry weight content (%) analysis, 2 g of ground almonds (Moulinex grinder AR110830, Alençon, France) were added to an aluminum tray and dried in an oven at 60 ◦ C until a constant weight was reached, while water activity (a w ) was measured by placing the cups with almond (2 g) into an a w meter (Novasina aw-Sprint TH500; Pfaffikon, Zurich, Switzerland) and reading the value. The experiments were done in quadruplicate. 2.3.3. Weight and Size For the morphological parameters, 100 almonds per treatment (25 almonds × 4 trees × treatment × year) were randomly selected and measured in terms of weight and size (length, width, thickness) of both in-shell almond and kernel using a digital caliper (Mitutoyo 500-197-20, Kawasaki, Japan) and a precision scale (Mettler Toledo model AG204, Barcelona, Spain), respectively. 2.3.4. Instrumental Color Color measurements were performed at 25 ± 1 ◦ C using a Minolta Colorimeter CR-300 (Osaka, Japan). Outside color was directly measured on the skin of 100 individual almond kernels per treatment each year. Results were presented as international commission on illumination (CIE) L*,a* and b* color coordinates describing the color in a three-dimensional space as following: L* for the lightness (L*=0 black; L*=100 white), a* for the green-red (a*=red; − a*=green), and b* for the blue-yellow components (b*=yellow; −b*=blue). 2.3.5. Instrumental Texture The texture of 100 almonds per treatment and year was measured using a texture analyzer (Stable Micro Systems, model TA-XT2i, Godalming, UK) with a 30 kg load cell and a probe Volodkevich Bite Jaw (HDP/VB) as following: trigger was placed at 15 g, test speed was 1 mm s −1 over a specific distance of 3 mm. Fracturability (mm), hardness (N), work done to shear (Ns), average force (N), and number of fractures (peaks count) were the parameters analyzed. 2.4. Chemical and Functional Analysis/Parameters 2.4.1. Mineral Content Determination The digestion of 0.5 g of sample with 8 mL of concentrated HNO 3 and 2 mL H 2 O 2 (30%) using a START D Medium Microwave Digestion (SK-10) was first carried out [ 25 ]. Followed by the determination of macro-nutrients (Ca, Mg, and K) and micro-nutrients (Fe, Cu, Mn and Zn) with a Unicam Solaar 969 atomic absorption–emission spectrometer (Unicam Ltd., Cambridge, UK). Calcium, Mg, Fe, Cu, Mn, and Zn was determined by atomic absorption and K by atomic emission. 2.4.2. Organic Acids and Sugars High-performance liquid chromatography (HPLC) was used for organic acids and sugars identification and quantification, as previously described [ 26 ]. For this, 1 g of ground almond was homogenized (Ultra Turrax T18 Basic, IKA ® -Werke GmbH & Co. KG Janke & Kunkel, Staufen, Germany) with 5 mL of 50 mM phosphate buffer (pH =7.8) for 2 min at 11,300 rpm, centrifuged (Sigma 3 − 18 K; Sigma Laborzentrifugen, Osterode and Harz, Germany) at 4 ◦ C and 15,000 rpm for 20 min and filtered (0.45 µ m Millipore membrane filter, Billerica, MA, USA). The supernatant was injected (10 µ L) into a Hewlett Packard (Wilmington, DE, USA) series 1100 (HPLC) using as mobile phase 0.1% orthophosphoric acid elution buffer. Sugars were analyzed using a Supelcogel TM C-610H column (30 cm × 7.8 mm) with a precolumn (Supelguard 5 cm × 4.6 mm; 219 Supelco, Bellefonte, PA, USA) and detected with a refractive index detector (RID). Organic acids were separated as sugars using a diode-array detector (DAD) at 210 nm for the absorbance measurements. Analyses were run in quadruplicate, and results were expressed as g kg−1dry weight (dw). Agronomy 2020,10, 1470 6 of 22 2.4.3. Antioxidant Activity and Total Phenolic Content The antioxidant activity and total phenolic content was carried out both for whole kernel and its blanched skin. For the extraction 0.5 g of finely ground almond were sonicated with 10 mL of extractant [MeOH/H 2 O 2 (80:20, v/v)+1% HCl at 20 ◦ C] for 15 min and stored at 4 ◦ C overnight. The mixture was sonicated again under the same conditions and centrifuged at 10,000 rpm for 10 min. The antioxidant activity of the obtained extract was measured using 3 methods: ABTS •+ [2,2-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid)], DPPH • (2,2-diphenyl-1-picrylhydrazyl), and FRAP (ferric reducing antioxidant power), as previously described by Brand-Williams et al. [ 27 ]. The results were calculated according to the Trolox calibration curve and were expressed as mmol Trolox kg−1. For total phenolic content (TPC) 100 µ L of supernatant was mixed with 200 µ L Folin-Cioc â lteu reagent and 2 mL of H 2 O 2 and was stored at 22 ◦ C for 3 min. Then, 1 mL of 20% Na 2 CO 3 was added, followed by 1 h of incubation at room temperature. The results were calculated with the gallic acid calibration curve and expressed as gallic acid equivalents (GAE), g GAE kg −1 . All measurements were performed in an ultraviolet-visible (UV-vis) spectrophotometer (Helios Gamma model, UVG 1002E; Helios, Cambridge, UK). 2.4.4. Fatty Acids Ground almond (40 mg) was saponified with 100 µ L of dichloromethane (Cl 2 CH 2 ) and 1 mL of sodium methoxide solution and refluxed for 10 min at 90 ◦ C. Later, 1 mL of BF 3 methanolic was added followed by 30 min rest in dark for reaction [ 25 ]. The fatty acids methyl esters (FAMEs) were separated in a Shimadzu GC17A gas chromatography coupled with a flame ionization detector and a DB-23 capillary column (30 m length, 0.25 mm internal diameter, 0.25 µ m film thickness) J&W Scientific, Agilent Technologies using the same conditions, as previously described by Lipan et al. [ 25 ]. The identification of FAMEs peaks was done by comparing the retention times of the FAME Supelco MIX-37 standards. Analysis were carried out in quadruplicate, and the results were expressed as g kg−1concentration, using methyl nonadecanoate (C19:0) as internal standard. 2.5. Descriptive Sensory Analysis Descriptive sensory evaluation was performed following the steps previously published in literature using a trained panel [ 19 ]. Ten highly trained panelists from the Food Quality and Safety Group (Miguel Hern á ndez University of Elche, Orihuela, Alicante, Spain) with ages between 25–62 years (5 women and 5 men) conducted the descriptive analysis. Once the orientation sessions were finished (4), the panel was asked to evaluate the 4 samples corresponding to the irrigation treatments in terms of appearance, basic tastes, and flavor intensities of almond. For this, a structured scale from 0 to 10 (0.5 increments) was used to quantify the intensity of the almond attributes, where 0 represents no intensity and 10 extremely strong. The samples were presented using a randomized block design to avoid biases in individual tasting booths (controlled temperature of 21 ± 2 ◦ C and combined natural/artificial light) equipped with water and unsalted crackers for palate cleaning among samples. The analysis was run in triplicate. 2.6. Statistical Analysis Two-way analysis of variance (ANOVA), using “irrigation treatment” and “year” as factors, followed by Tukey’s multiple range test were carried out in order to decide the parameters to be used for the correlations. Two supplementary tables were added with the mean values of 3 years ( Tables S1 and S2 ). Only those parameters significantly different among treatments were considered for Pearson’s correlations. All statistical analyses were performed using XLSTAT Premium 2016, while Sigma Plot 11 software was used for figures preparation. Statistically differences were considered significant when p<0.05. Agronomy 2020,10, 1470 7 of 22 3. Results and Discussion 3.1. Agronomic Parameters Tables S1 and S2 contains supplementary information about the mean values of 3 years study for all the parameters. As observed, a lower amount of irrigation water was received by the trees’ growth under deficit irrigation strategies, being T3 and T4 the treatments, which received the less amount of irrigation water; this rebound in the plant status can be observed from the stress integral values. Almond trees from T3 and T4 were the most stressed, although the latter (T4) was statistically significant to T2. During the first season, T2 and T3 were the most stressed treatments followed by T4, which was statistically similar to T2. In 2018, lower values of SI were shown for all treatments, which means that the stress in plant was less severe than the other seasons. T3 and T4 were the most stressed treatments, followed by T2, which was statistically correlated with the control and to the other deficit irrigation treatments. Finally, 2019 was the season in which almonds trees met the highest values of water stress, with T3 and T4 having the highest values, followed by T2. As observed, the SI behaved different yearly, however in the last two seasons, T3 and T4 were similar in terms of water stress in plant. The difference between these treatments is that in the former (T3) the stress was applied in the kernel-filling period, while in the latter (T4), the stress was imposed throughout the whole growing cycle, creating a progressively stress in plant rather than in a single phenological phase (kernel filling). Supplementary data also showed the mean values of kernel yield of all 3 seasons to check how the previous parameters (SI and applied water) influenced the fruit yield. A reduction of this parameter was observed in all the treatments growth under DI conditions with no significant differences among them. If each year production is analyzed, no differences among control and DI treatment was registered in the first season. However, a decrease of 2.4-fold was found for these treatments (T2, T3, T4) regarding the control in the second season (with no significant differences among them) and in the third season. A reduction in kernel yield in deficit irrigation treatments was also observed in 2019 season (1.2-fold in T2 and 1.5-fold in T3 and T4), although this time was lower than in 2018 and T2 was significantly similar to the control. Is important to highlight that in 2018, even though T3 and T4 received a lower amount of water than T2, the kernel yield was similar among them, and that in 2019, although T2 received lower amount of water than the control (T1), the kernel yield was significantly similar between them. Pearson’s correlation coefficients (R) among SWP and SI with agronomical and physical parameters is shown in Figure 2. A negative and significant correlation was found between SI and (i) SWP ( R=−0.67 ; p<0.001) and (ii) water activity (R = − 0.39; p<0.01); this means that at higher waters stress values, lower SWP and a w values are obtained. On the other hand, a positive and significant correlation was observed between SI and dry weight (R =0.53; p<0.001) as well as between kernel ratio and applied water (R =0.36; p<0.05). Regarding the water stress effect on kernel yield, the results showed that in the first year it was not affected (R =0.11; p>0.05); however, kernel yield was reduced with water stress during 2018 and 2019 seasons demonstrated by the negative correlations of R = − 0.50; p<0.05 * and R =−0.79; p<0.001 ***, respectively. Agronomy 2020,10, 1470 8 of 22 Agronomy 2020, 10 x FOR PEER REVIEW 8 of 23 Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: R = 1.00; significant (p < 0.05) positive correlation; significant (p < 0.05) negative correlation; positive but not correlated; negative but not correlated. *, **, ***, significant at p < 0.05, 0.01, and 0.001, respectively. SWP = minimum stem water potential; SI = stress integral; AW = applied water; KR = kernel ratio; DW = dry weight; aw = water activity . 3.2. Morphological Parameters Table 1 shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [18], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [29,30]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [21,31]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: Agronomy 2020, 10 x FOR PEER REVIEW 8 of 23 Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: R = 1.00; significant (p < 0.05) positive correlation; significant (p < 0.05) negative correlation; positive but not correlated; negative but not correlated. *, **, ***, significant at p < 0.05, 0.01, and 0.001, respectively. SWP = minimum stem water potential; SI = stress integral; AW = applied water; KR = kernel ratio; DW = dry weight; aw = water activity . 3.2. Morphological Parameters Table 1 shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [18], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [29,30]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [21,31]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no R=1.00; Agronomy 2020, 10 x FOR PEER REVIEW 8 of 23 Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: R = 1.00; significant (p < 0.05) positive correlation; significant (p < 0.05) negative correlation; positive but not correlated; negative but not correlated. *, **, ***, significant at p < 0.05, 0.01, and 0.001, respectively. SWP = minimum stem water potential; SI = stress integral; AW = applied water; KR = kernel ratio; DW = dry weight; aw = water activity . 3.2. Morphological Parameters Table 1 shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [18], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [29,30]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [21,31]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no significant (p<0.05) positive correlation; Agronomy 2020, 10 x FOR PEER REVIEW 8 of 23 Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: R = 1.00; significant (p < 0.05) positive correlation; significant (p < 0.05) negative correlation; positive but not correlated; negative but not correlated. *, **, ***, significant at p < 0.05, 0.01, and 0.001, respectively. SWP = minimum stem water potential; SI = stress integral; AW = applied water; KR = kernel ratio; DW = dry weight; aw = water activity . 3.2. Morphological Parameters Table 1 shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [18], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [29,30]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [21,31]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no significant (p<0.05) negative correlation; Agronomy 2020, 10 x FOR PEER REVIEW 8 of 23 Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: R = 1.00; significant (p < 0.05) positive correlation; significant (p < 0.05) negative correlation; positive but not correlated; negative but not correlated. *, **, ***, significant at p < 0.05, 0.01, and 0.001, respectively. SWP = minimum stem water potential; SI = stress integral; AW = applied water; KR = kernel ratio; DW = dry weight; aw = water activity . 3.2. Morphological Parameters Table 1 shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [18], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [29,30]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [21,31]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no positive but not correlated; Agronomy 2020, 10 x FOR PEER REVIEW 8 of 23 Figure 2. Heat map of correlation matrix of agronomical parameters. Each square indicates Pearson’s correlation coefficient for a pair of data and the color represents the positive or negative correlation as: R = 1.00; significant (p < 0.05) positive correlation; significant (p < 0.05) negative correlation; positive but not correlated; negative but not correlated. *, **, ***, significant at p < 0.05, 0.01, and 0.001, respectively. SWP = minimum stem water potential; SI = stress integral; AW = applied water; KR = kernel ratio; DW = dry weight; aw = water activity . 3.2. Morphological Parameters Table 1 shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [18], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [29,30]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [21,31]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no negative but not correlated. *, **, ***, significant at p<0.05, 0.01, and 0.001, respectively. SWP =minimum stem water potential; SI =stress integral; AW =applied water; KR =kernel ratio; DW =dry weight; aw =water activity. Overall, these results showed that after long-term experiment (3 years), the water stress in almond trees negatively affected the yield but enhanced dry weight. These results suggest that yields differences were related to the number of nuts. Such response could be associated with a postharvest water stress in deficit treatments [ 18 ]. However, it was observed that, depending on the treatment, it can lead to yields statistically similar to the control, which might be a good alternative when water restrictions are below the crop needs. In this way, Moderate RDI (T2) could balance water stress effects, because this treatment could secure enough crown volume, which is very important in the tree yield capacity [ 10 ] and postharvest recovery, which is according to the current data, the most important effect. On the contrary, T3 and T4 results suggest that water status in postharvest would be better. Then, in conditions of very low water availability, irrigation in this period should be preferential and greater than the ones of T3. Besides, the reduction in the moisture content and water activity with water stress are also important outcomes for food industry, because lower values of these parameters help to maintain at minimum the biological reactions, which essential to increase the almonds shelf life [ 28 ]. The obtained Agronomy 2020,10, 1470 9 of 22 results indicate that the use of deficit irrigation in almond trees water management can improve yield and reduce water use. Thus, it contributes to reduce water consumption for irrigation purposes. 3.2. Morphological Parameters Table 1shows the Pearson’s correlation coefficients (R) between SWP and SI with morphological parameters. The SI was negatively correlated with almond, kernel, and shell weight, with kernel length and width, and with almond thickness. This means that weight and size were reduced with the water stress in plant. The conclusions regarding the effect of deficit irrigation on the morphological parameters are widely spread throughout the literature. For instance, similar results were obtained in almond cultivar (cv.) Nonpareil [ 18 ], and no differences were reported for almond cultivars Marta, Guara, Lauranne, Ferragnes, and Texas [ 29 , 30 ]. Additionally, no differences on the morphological parameters were also reported for other crops such as pistachio cv. Kerman and olives cv. Manzanilla if the stress was applied during shell and pit hardening, respectively [ 21 , 31 ]. Finally, an increase in weight and equatorial diameter but a decrease in longitudinal diameter were observed for olives cv. Manzanilla growth under the following RDI conditions: (i) stage I, trees irrigated under non-limited conditions; (ii) stage II, trees under moderate water deficit conditions, they were no irrigated during this period; and (iii) stage III, water applied in order to provide a water status similar to a full irrigated treatment [32]. A significant positive correlation was observed between the SI and color parameters, showing that a higher stress level leads to higher values of L*,a*, and b* coordinates. This means that hydroSOStainable almonds have a lighter color with reddish and yellowish notes (more intense brown color). As the almond color skin is given by the polyphenol profile, which is unique for each cultivar [ 33 ], the increase in color coordinates under water stress conditions might be related to a potential increase in polyphenols. For instance, almond flavonoids have been extensively studied in different plants, and it was concluded that they are decisive pigment in color plants [ 34 ]. The brown almond skin pigment is largely concentrated in the high-molecular weight fraction such as proanthocyanidins, which are the main polyphenols found in almonds that can impart color formation [ 35 ]. A positive correlation between SI and proanthocyanidins (R =0.73; p=0.001) was previously reported in almonds cv. Vairo after one season of experiment. Besides, a* values were also reported to be higher in almonds cv. Vairo, Marta, Guara, Lauranne growth under deficit irrigation conditions after one season [ 25 , 29 ]. Finally, a* was reported to be positively correlated with the contents of nine individual flavonols, total kaempferols, and total flavonols in a study about the relationship between rose petals’ (Rosa spp.) color and polyphenols content [36]. Agronomy 2020,10, 1470 16 of 22 Table 4. Pearson’s correlation coefficients (R) among stem water potential and stress integral with fatty acids. SWP SI C14:0 C16:0 C16:1 C17:0 C17:1 C18:0 C18:1n9 C18:1n7 C18:2 O/L SFA MUFA PUFA PUFA/SFA PUFA/MUFA SWP 1.00 SI −0.67 *** 1.00 C14:0 −0.14 0.73 *** 1.00 C16:0 −0.20 0.81 *** 0.95 *** 1.00 C16:1 −0.13 0.75 *** 0.92 *** 0.96 *** 1.00 C17:0 −0.14 0.69 *** 0.88 *** 0.87 *** 0.86 *** 1.00 C17:1 −0.06 0.65 *** 0.90 *** 0.90 *** 0.85 *** 0.84 *** 1.00 C18:0 −0.20 0.80 *** 0.91 *** 0.97 *** 0.95 *** 0.86 *** 0.86 *** 1.00 C18:1n9 0.22 −0.82 *** −0.94 *** −0.99 *** −0.95 *** −0.86 *** −0.90 *** −0.98 *** 1.00 C18:1n7 −0.17 0.48 *** 0.51 *** 0.55 *** 0.40** 0.47 *** 0.62 *** 0.57 *** −0.60 *** 1.00 C18:2 −0.32 * 0.82 *** 0.86 *** 0.91 *** 0.86 *** 0.76 *** 0.75 *** 0.88 *** −0.93 *** 0.46 *** 1.00 O/L 0.24 −0.82 *** −0.93 *** −0.97 *** −0.93 *** −0.84 *** −0.84 *** −0.95 *** 0.98 *** −0.52 *** −0.98 *** 1.00 SFA −0.21 0.81 *** 0.94 *** 0.99 *** 0.96 *** 0.88 *** 0.89 *** 0.99 *** −0.99 *** 0.55 *** 0.90 *** −0.97 *** 1.00 MUFA 0.27 −0.84 *** −0.92 *** −0.97 *** −0.93 *** −0.84 *** −0.83 *** −0.95 *** 0.98 *** −0.49 *** −0.97 *** 0.99 *** −0.97 *** 1.00 PUFA −0.32 * 0.83 *** 0.86 *** 0.91 *** 0.86 *** 0.76 *** 0.75 *** 0.88 *** −0.93 *** 0.46 *** 1.00 *** −0.98 *** 0.90 *** −0.97 *** 1.00 PUFA/SFA 0.05 −0.65 *** −0.84 *** −0.89 *** −0.90 *** −0.83 *** −0.86 *** −0.91 *** 0.86 *** −0.46 *** −0.64 *** 0.78 *** −0.90 *** 0.79 *** −0.64 *** 1.00 PUFA/MUFA −0.32 * 0.85 *** 0.89 *** 0.94 *** 0.88 *** 0.80 *** 0.79 *** 0.91 *** −0.96 *** 0.50 *** 0.99 *** −0.99 *** 0.94 *** −0.99 ** 0.99 *** −0.70 *** 1.00 *, **, ***, significant at p<0.05, 0.01, and 0.001, respectively. SWP =minimum stem water potential; SI =stress integral; C16:0 (palmitic); C16:1 (palmitoleic); C17:0 (margaric); C17:1 cis (heptadecenoic); C18:0 (stearic); C18:1n9 (oleic); C18:1n7 (cis-vaccenic); C18:2n6 c9,12 (linoleic); O/L (oleic/linoleic); SFA (saturated fatty acids); MUFA (monounsaturated fatty acids); PUFA (polyunsaturated fatty acids). Agronomy 2020,10, 1470 17 of 22 A reduction in oleic, MUFA, and O/L ratio and an increase in linoleic, PUFA, and PUFA/MUFA ratio was also reported in almond cv. Marta, Guara, Lauranne, Ferragnes, Texas; olives cv. Mazanilla; pistachio cv. Kerman; and sunflower cv. Suncross [29,30,42,49,54,55]. The decrease in oleic and increase in linoleic in drought conditions was reported in many studies in different crops, although sometimes was cultivar dependent [ 54 ]. This effect of water stress on these two fatty acids was attributed to the enzyme ∆12 desaturase, which is responsible for the conversion of oleic acid in linoleic under water stress conditions [56]. As observed, PUFA is increased under water stress and similar results were reported in olives cv. Manzanilla [ 57 ] after two years of deficit irrigation. The authors reported that the higher the stress applied during stage III in olives, the greater the linoleic acid concentration and, consequently, (PUFA + MUFA)/SFA ratio, with a correlation of R 2 =0.71 and R 2 =0.84, respectively. An increase in linoleic acid may play an important role in the death of cardiac cells and is an essential fatty acid, which cannot be synthesized by human body [ 29 ]. It was reported that consuming 50 g of almonds under RDI conditions can cover approximately 33% of the daily intake of linoleic acid recommended by the European Food Safety Authority [ 29 ]. The present study showed an increase in PUFA and a decrease in MUFA with water stress, and this led to a low O/L rate. It is well known that a low O/L rate means almonds are more susceptible to oxidation, because this is initiated in the double bonds of PUFA [ 58 ]. However, it was also observed that water stress also enhances compounds with antioxidant activity (polyphenols, α -tocopherol, phytoprostanes, phytofurans, jasmonates, abscisic acid, etc., that are also enhanced by water stress) that might help in maintaining the PUFA in a cell’s membrane, preserving its bioactivity [59]. Saturated fatty acids were also observed to increase in almonds under water stress conditions, and the American Heart Association (AHA) encourages people to replace SFA with MUFA for a healthy lifestyle and low-density lipoprotein (LDL) cholesterol levels reductions. Thus, controlling the stress in almond trees might help to reduce the SFA content, because other studies reported that moderate deficiency did not negatively affected SFA content in almond [ 25 , 29 , 53 ]. Moreover, the levels of SFA in almonds are so low that almonds as well as other nuts fits well in AHA guidelines [ 60 ]. In fact, Food and Drug Administration (FDA) implemented a healthy claim regarding the almonds and other nuts consumption, stating that diets containing ~42.5 g of almonds per day as part of a diet low in saturated fat, and cholesterol may reduce the risk cardiovascular diseases [61]. To conclude this section, the fatty acids were significantly affected by water stress and are good markers of the hydroSOStainable almonds. 3.6. Descriptive Sensory Analysis Table 5shows the Pearson’s correlation coefficients (R) between SI and SWP with sensory attributes. These results highlighted strong negative correlations for the size, bitterness, astringency, benzaldehyde, and woody flavors. Previous studies reported that water stress might enhance the sweetness, nutty, almond ID, and crispiness in almonds cv. Lauranne and pistachio cv. Kerman [ 29 , 31 ]. Thus, an increase in sugars and a decrease in bitterness and astringency with water stress conditions as shown in this study might lead to sweeter almonds. As previously described by Lipan et al. (2019) [ 19 ] and Carbonell-Barrachina et al. (2015) [ 31 ], the purchase choice of international consumers was based on sweetness, almond ID, pistachio ID, and crispiness. These findings together with those that consumers were willing to pay more for hydroSOStainable almonds [ 19 ], pistachios [ 20 ], and table olives [ 62 ], and the functional properties of the bioactive compounds described here encourage the almond farming sector to bet on deficit irrigation strategy to reduce irrigation water and simultaneously increase the functional and sensorial quality of almonds. Agronomy 2020,10, 1470 18 of 22 Table 5. Pearson’s correlation coefficients (R) among stem water potential and stress integral with sensory analysis parameters. SWP SI Color Size Sweet Bitter Astr Nutty Al ID Benz Woody Hardness Crispiness Aftertaste SWP 1.00 SI −0.69 * 1.00 Color 0.24 0.04 1.00 Size 0.35 − 0.90 *** −0.09 1.00 Sweet −0.43 0.35 −0.68 * −0.26 1.00 Bitter 0.12 −0.62 * 0.27 0.78 ** −0.42 1.00 Astr 0.32 −0.70 * 0.12 0.77 ** −0.29 0.51 1.00 Nutty 0.04 −0.39 −0.45 0.83 *** 0.21 0.64 * 0.59 * 1.00 Al ID −0.09 −0.34 −0.84 * 0.40 0.64 * 0.03 0.27 0.78 ** 1.00 Benz 0.09 −0.60 * −0.68 * 0.69 * 0.38 0.26 0.43 0.83 *** 0.83 *** 1.00 Woody 0.16 −0.71* −0.67 * 0.76 ** 0.20 0.39 0.48 0.89 *** 0.82 *** 0.91 *** 1.00 Hardness −0.32 0.03 − 0.81 *** 0.05 0.53 −0.34 0.10 0.36 0.73 ** 0.57 0.59 * 1.00 Crispiness −0.17 −0.12 − 0.95 *** 0.17 0.64 * −0.29 0.05 0.48 0.85 *** 0.71 ** 0.71 ** 0.91 *** 1.00 Aftertaste −0.15 −0.29 − 0.83 *** 0.36 0.51 −0.11 0.31 0.65 * 0.91 *** 0.82 *** 0.81 *** 0.86 *** 0.89 *** 1.00 *, **, ***, significant at p<0.05, 0.01, and 0.001, respectively. SWP =minimum stem water potential; SI =stress integral; Sweet =sweetness; Bitter =bitterness; Astr =astringency; Al ID = almond ID; Benz =benzaldehyde like. Agronomy 2020,10, 1470 19 of 22 4. Conclusions Globally, data presented here showed that water stress affected the functional and sensorial parameters of hydroSOStainable almonds showing positive correlations with dry weight, color coordinates (L*,a*, and b*), minerals (K, Fe, and Zn), organic acids (citric acid), sugars (sucrose, fructose, and total sugars), antioxidant activity, and fatty acids (linoleic, PUFA, SFA, PUFA/MUFA, among others). On the other hand, the water stress in almonds was negatively correlated with kernel yield, water activity, weight (almond, kernel, and shell), size, minerals (Ca and Mg), fatty acids (oleic acids, oleic/linoleic ratio, MUFA, and PUFA/SFA), and sensory attributes (size, bitterness, astringency, benzaldehyde, and woody). Considering that moderate RDI led to kernel yields similar to the control, agricultural sector can save approximately 45% of the irrigation water obtaining high-quality products. The current long-term research helped to demonstrate which quality parameters are really affected by water stress conditions and to clarify which may be essential markers to distinguish hydroSOStainable almonds from other types of almonds. All these findings help the agro-food sector to understand (i) that is possible to increase the water use efficiency generating products with high functional and sensory quality; (ii) the need of controlling the water stress in plants for the best agronomical and quality responses; and (iii) to set up key agronomic and quality markers to control and establish whether the water stress created at the field/orchard significantly affected the quality and functionality of the final edible nuts. Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4395/10/10/1470/s1, Table S1: Mean values of morphological and chemical parameters of irrigation treatments (T1, T2, T3, and T4) for 3 years (2017, 2018, and 2019) and Table S2: Mean values of functional and sensorial parameters of irrigation treatments (T1, T2, T3, and T4) for 3 years (2017, 2018, and 2019). Author Contributions: Conceptualization, L.L. and Á .A.C.-B.; methodology, L.L., F.H., M.C. and A.M.; software, L.L. and L.V.-A.; validation, Á .A.C.-B., A.M. and L.V.-A.; formal analysis, L.L. and M.C.-L.; investigation, L.L. and L.V.-A; resources, Á .A.C.-B. and A.M.; data curation, L.L.; writing—original draft preparation, L.L. and M.C.-L.; writing—review and editing, L.L., M.C., F.H. and E.S.; visualization, L.L. and Á .A.C.-B.; supervision, L.V.-A., E.S. and Á .A.C.-B., project administration, Á .A.C.-B. and A.M.; funding acquisition, Á .A.C.-B. and A.M. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Spanish Government (Ministerio de Ciencia e Innovacion (MCI), Agencia Estatal de Investigacion (AEI), through a coordinated research project (hydroSOS) including the Universidad Miguel Hern á ndez de Elche (AGL2016-75794-C4-1-R, Productos hidroSOStenibles: identificaci ó n de debilidades y fortalezas, optimizaci ó n del procesado, creaci ó n de marca propia, y estudio de su aceptaci ó n en el mercado europeo, hydroSOS foods) and the Universidad de Sevilla (AGL2016-75794-C4-4-R); these projects have been also funded by Fondo Europeo de Desarrollo Regional (FEDER) “Una manera de hacer Europa”, (MCI/AEI/FEDER, UE). Acknowledgments: The author M. Cano-Lamadrid was funded by the Formaci ó n de Profesorado Universitario (FPU) grant from the Spanish Ministry of Education (FPU15/02158). Conflicts of Interest: The authors declare no conflict of interest. References 1. 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