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Deficit Irrigation and Its Implications for HydroSOStainable Almond Production

Iván Francisco García-Tejero
Leontina Lipan
Saray Gutiérrez-Gordillo
Víctor Hugo Durán Zuazo
I. Jančo
F. Hernández
Belén Cárceles Rodríguez
3 and
Ángel Antonio Carbonell-Barrachina
Centro IFAPA “Las Torres”. Ctra. Sevilla-Cazalla, km 12.2, Alcalá del Río, 41200 Sevilla, Spain
Department of Agro-Food Technology, University Miguel Hernández-EPSO, Carretera de Beniel, km 3.2, Orihuela, 03312 Alicante, Spain
Centro IFAPA “Camino de Purchil”, Camino de Purchil s/n, 18004 Granada, Spain
Department of Chemistry, Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra, Tr.A. Hlinku 2, 949 76 Nitra, Slovakia
Department of Plant Science and Microbiology, University Miguel Hernández-EPSO, Carretera de Beniel, km 3.2, Orihuela, 03312 Alicante, Spain
Author to whom correspondence should be addressed.
These authors had an equally contribution.
Agronomy 2020, 10(11), 1632;
Submission received: 1 October 2020 / Revised: 20 October 2020 / Accepted: 21 October 2020 / Published: 23 October 2020
(This article belongs to the Special Issue Optimizing Plant Water Use Efficiency for a Sustainable Environment)


Deficit irrigation (DI) strategies are considered essential in many arid and semi-arid areas of Mediterranean countries for proper water management under drought conditions. This fact is even more necessary in crops such as almond (Prunus dulcis Mill.), which in the last recent years has been progressively introduced in irrigated areas. An essential aspect to be considered would be the ability to improve fruit-quality parameters when DI strategies are imposed, which can boost the final almond price and ensure the sustainability and competitiveness of this crop. This work examines the effects of sustained deficit irrigation (SDI) on three almond cultivars (Marta, Guara, and Lauranne) on parameters related to almond functionality, aroma and sensory profile, which consequently influence its marketability and consumers acceptance. SDI strategies allowed the improvement of physical parameters such as unit weight, kernel length, kernel thickness or color. Moreover, higher total phenolic compounds, organic acids and sugars were found in SDI almonds. Finally, the highest concentrations of volatile compounds were obtained under SDI, this being a clear advantage in relation to almond flavor. Thus, moderate SDI strategy offered relevant improvements in parameters regarding the marketability, by enhancing the final added value of hydroSOStainable almonds with respect to those cultivated under full irrigation conditions.

1. Introduction

Water is the most limiting natural resource for sustainable agricultural development in arid and semi-arid areas of Mediterranean and more specifically under climate change scenarios [1]. In this regard, several works have reported the impact of climate change on agriculture [2,3], concluding that crop water demand will increase substantially due to higher evapotranspiration rates, temporal variability of rainfall or heat weaves events [4].
Within these scenarios, implementing drought-tolerant crops in irrigated zones and the application of deficit irrigation (DI) strategies are being considered, especially in the last few years [5,6]. Developing water-saving strategies in Mediterranean woody crops involves many considerations relative to environmental constraints, sustainable yields, and product marketability. However, these must be deeply studied, establishing the most profitable strategies to maximize the fruit production, minimizing the irrigation water consumption and maintaining (or even improving) the fruit quality.
Almond (Prunus dulcis Mill.) is the largest tree nut crop, and the world surface dedicated to its cultivation during 2018 amounted to 2,071,884 ha, with Spain being the country with the largest area devoted to this crop, with 657,768 ha, followed by the USA, with 441,107 ha [7]. However, in production terms, relevant differences are found, with 1,872,500 and 339,033 t for the USA and Spain, respectively. Moreover, for the period 2010–2018 in the USA (3500–5608 kg ha−1) and Spain (279–515 kg ha−1), the production per area were highly different. In 2018, the Mediterranean basin (Spain, Italy, Greece, Syria, Tunisia, Argelia and Morocco) produced roughly 29% of the world almond production, with most plantations under rainfed conditions and located in marginal areas. In Spain, the almond cultivation is mainly concentrated in Andalusia (S Spain) (31% of total area), and since approximately 85% of almond crops are rainfed, this provokes important fluctuations in productivity [8].
Today, the increase in almond prices from 2014 to 2019, when it reached an average price of 5€ per kg [9], has resulted in an increase of surface devoted to almond cultivation with different techniques [10], explicitly in irrigated areas that were traditionally occupied by other crops (cereals, cotton and sunflower, among others) [11]. This increase in cultivated area under irrigation from 2014 to 2018 amounted to 25% by using new cultivars [12], which allows to obtain higher yields (>1500 kg ha−1) than those from traditional rainfed plantations (150–500 kg ha−1) [13].
By taking into consideration the advantage of the positive adaptation of almond to drought scenarios [14,15], and its sharp phenology, many authors have reported the positive responses and opportunities of DI for almond cultivation, obtaining competitive yields under moderate-to-severe water stress situations [16,17,18,19].
Recently, a novelty research line, focused on food production under hydro-sustainable strategies (hydroSOStainable products), has been successfully developed [20,21,22]. This also showed advantages of different Mediterranean crops, with significant improvements in the fruit quality, sensory profile and consumer acceptance in crops such as pistachios [23], olives [24] and almonds [25]. In this context, there is in an interest in those characteristics or parameters of raw almonds related to their marketability that could be affected by DI strategies. In other words, the main limitation of DI implementation is ultimately the yield reduction (in comparison to the potential rate when almond is grown under full-irrigated conditions), affecting the plantation viability and its competitiveness. In this regard, Lipan et al. [25,26] reported relevant results, concluding that some fruit-quality parameters could be improved (or at least not affected) when DI strategies are imposed. If that is the case, these kinds of strategies would encourage the product marketability and the consumer acceptance, allowing a recovering in terms of final price, minimizing the losses when these are analyzed in monetary terms. In addition, many aspects are still not clear, such as if these effects would be similar for the new high-yielding cultivars or the dependence in relation to the irrigation strategy imposed or crop physiological status during the water stress period.
On the other hand, consumer appreciation, and hence, almond marketability, can be determined by a wide number of variables that could be classified into physical and chemical parameters, all of them determining the sensory appreciation and the almond appeal. Raw almonds are mainly composed by fats (44–61%), proteins (16–23%) and dietary fiber (11–14%) and high concentrations of vitamin E [27,28]. Despite these being the main compounds of raw almonds, their influence in taste receptors is negligible. In this line, other compounds, more related to flavor properties and sensory and chemical characteristics, can be found. According to Civille et al. [29] the main taste properties of raw almonds are mainly defined by astringency and sweetness degree, and to a lesser extent, the tactile dimensions (almond texture) [30]; this is the highest variability in almond flavor related to odor-active volatiles compounds. That is, volatile compounds are responsible of characteristic flavor properties of raw and processed almonds and contribute to their high consumer acceptance [25,31]. In particular, benzaldehyde is one of the main volatiles in bitter almonds, but its presence in sweet almonds is very variable (highly cultivar dependent), and, overall, it is found in very low concentrations [32]. Despite these low concentrations, its presence is responsible of the typical almond flavor and derivates such as marzipan [33].
Considering that the hydroSOStainable almond production could be a key factor for sustainable development in a semiarid Mediterranean environment; the objective of this study was to evaluate the effects of sustained deficit irrigation strategies and almond cultivars on the main physico-chemical parameters involved in nut sensory profile and improvements in marketability.

2. Material and Methods

2.1. Plant Material, Growing Conditions and Experimental Design

The trial was conducted during 2019 in a commercial orchard of almonds (Prunus dulcis Mill., cvs Guara, Marta and Lauranne), grafted onto GN15 rootstock, and located in the Guadalquivir river basin (37°30′27.4′′ N; 5°55′48.7′′ O) (Seville, SW Spain) (Figure 1). The plantation contained seven-year-old almond trees, 8 × 6 m spaced and drip irrigated by using two pipelines with emitters of 2.3 L h−1. The soil is a silty loam typical Fluvisol [34], more than 2 m deep, fertile and with an organic matter content of 15.0 g kg−1. Roots were located predominately in the first 50 cm of soil, corresponding to the intended wetting depth, although these exceed more than one meter in depth. The climatology in the study area is attenuated meso-Mediterranean, with an annual reference evapotranspiration rate (ET0) of 1400 mm and an annual rainfall of 540 mm, mainly distributed from October to April. More details about the experimental site can be found in Gutiérrez-Gordillo et al. [35].
Three irrigation treatments were designed: (i) a full-irrigated treatment (FI), which received 100% of irrigation requirements (IR) during the irrigation period, and two sustained-deficit irrigation treatments, which received 75% (SDI75) and 65% (SDI65) of IR. Irrigation was applied from April to October, the IR being estimated according to the methodology proposed by Allen et al. [36], obtaining the values of ET0 by using a weather station installed in the same experimental orchard (Davis Advance Pro2, Davis Instruments, Valencia, Spain). The local crop coefficients used during the experimental period ranged from 0.4 to 1.2, according to the results obtained by García-Tejero et al. [37].

2.2. Field Measurements

Physiological response to different irrigation doses was evaluated throughout measurements of leaf water potential (Ψleaf) in shaded leaves, these readings being taken between 12:00 and13:30 GTM, and on a weekly basis. Measurements of Ψleaf were developed by using a pressure chamber (Soil Moisture Equipment Corp., Sta. Barbara, CA, USA), monitoring eight trees per irrigation treatment (two leaves per tree), located in the north side of the tree and being totally mature, fresh and shaded, at 1.5 m of height. These readings were used to quantify the water stress supported by the crop for each week and the whole kernel-filling period by means of the stress integral (ΨInt), following the methodology proposed by Myers [38] (Equation (1)). This index allows to quantify the effect of water stress provided by the water restriction beyond its temporal distribution, integrating the global stress supported by the crop in comparison to the punctual measurements:
ψ I n t = | ( ψ l e a f a v ( ψ l e a f m a x ) ) ·   n | .
where ΨInt is the stress integral in terms of Ψleaf values, ψ l e a f a v is the average leaf water potential for any interval (in our case, for each week), ψ l e a f m a x is the maximum value of Ψleaf weekly registered, during the experimental period and n is the days numbers within each interval, in our case n = 7.
At the end of each season, monitored trees (eight per cultivar and irrigation strategy) were harvested. This process was carried out by using a mechanic vibrator to throw the almond on the ground (previously covered with a plastic mesh). Collected almonds were processed with a mechanic peeling to remove the hull. Finally, once cleaned, almonds were left to air dry and weighed once reached a humidity content around 6%. Around 3 kg of in-shell almonds were sent to Miguel Hernández University for quality and sensory analysis, where the main morphological, physical and chemical parameters were analyzed (Figure 2).

2.3. Morphological and Physical Parameters

The ratio between the mass of in-shell almonds and kernel was calculated from ~1 kg of nuts per cultivar and irrigation treatment. Additionally, 225 almonds (25 samples × 3 varieties × 3 treatments) were randomly selected and analyzed by measuring the weight and size (length, width and thickness) of almonds (both in-shell and kernel) using a digital caliper (Mitutoyo 500-197-20, Kawasaki, Japan) and a scale (Mettler Toledo model AG204, Barcelona, Spain), respectively.
A Minolta Colorimeter CR-300 (Minolta, Osaka, Japan) was used to perform the color measurements in 75 kernels per each variety. This colorimeter uses a D65 illuminant and a 10° observer as references. The color was provided as CIEL*a*b* coordinates defining the color in a three-dimensional space and it was expressed in three numerical values, which includes 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).

2.4. Chemical Composition

2.4.1. Total Sugars

Sugars were determined using a high-performance liquid chromatography (HPLC) equipment. The extraction consisted of 1 g of grinded almond in a Moulinex grinder (AR110830) for 10 s, homogenized with 5 mL of phosphate buffer with an homogenizer (Ultra Turrax T18 Basic) over 2 min at 11.3 rpm, while the tube was maintained in an ice bath and after it was centrifuged for 20 min at 15,000 rpm and 4 °C (Sigma 3–18 K; Sigma Laborzentrifugen, Osterode and Harz, Germany) followed by filtration and injection in the HPLC equipment. Sugar content was determined by using a Supelcogel TM C-610H column (30 cm × 7.8 mm) with a pre-column (Supelguard 5 cm × 4.6 mm; Supelco, Bellefonte, PA, USA) and it was detected by a refractive index detector (RID). Organic acid absorbance was measured at 210 nm in the same HPLC condition using a diode-array detector (DAD). Analyses were triplicated and results were expressed as g kg−1 dry weight.

2.4.2. Volatile Compounds

For the extraction of the volatile compounds, headspace solid phase microextraction (HS-SPME) was used. Ground almond (1 g) was added to a hermetic vial with polypropylene cap and PTFE (polytetrafluoroethylene)/silicone septa, together with 500 µL salty water (12.5% NaCl) and 2.5 μL of 2-acethylthiazole (1000 mg L−1) internal standard, needed for the semi-quantification of the volatile compounds. To simulate the mouth temperature, the vial was heated in a laboratory hot plate up to 50 °C. When the temperature was reached and was stable, a 50/30 μm Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber was introduced in the headspace of the vial for 35 min. A gas chromatograph Shimadzu GC-17A (Shimadzu Corporation, Kyoto, Japan) coupled with mass spectrometer (MS) detector Shimadzu QP-5050A were used for isolation and identification of the volatile compounds. The Gas Chromatography—Mass Spectrometry (GC-MS) was equipped with a SLB-5ms Fused Silica Capillary Column of 30 m × 0.25 mm × 0.25 µm film thickness, 5% diphenyl and 95% dimethyl siloxane (Supelco Analytical). Helium was used as gas carrier at a flow rate of 0.9 mL min−1 in a split ratio of 1:5. The oven program was: (a) initial temperature 50 °C, (b) rate of 4.0 °C min−1 to 130 °C, (c) rate of 10 °C min−1 from 130 °C to 180 °C, (d) rate of 20 °C from 180 °C to 280 °C. The injector and the detector were held at 250 °C. The identification of the volatile compounds was performed using three methods: (a) retention indices, (b) GC-MS retention times of authentic chemicals and (c) mass spectra compounds were extracted using HS-SPME.
Simultaneously, the quantification of the volatile compounds was done on a gas chromatograph, Shimadzu 2010, with a flame ionization detector (FID). The column and chromatographic conditions were those previously reported for the GC-MS analysis. The injector temperature was 200 °C and nitrogen was used as carrier gas (1 mL min−1). The quantification was obtained from electronic integration measurements using flame ionization detection (FID). 2-Acethylthiazole (2.5 μL of 1000 mg L−1) was used as internal standard.

2.5. Descriptive Sensory Analysis

The descriptive sensory analysis was held by a trained panel with a 10 highly qualified panelists from the Food Quality and Safety Group (Miguel Hernández University of Elche, Orihuela, Alicante, Spain). The descriptive sensory analysis was performed to estimate if the significant differences among treatments were found. Although the panelists were highly trained, having more than 600 h of experience with different types of food products, three orientation sessions were done prior to almond tasting, where the panelists were trained with reference products for each attribute according to the lexicon previously described by Lipan et al. [25]. The samples were served in odor-free 30 mL covered plastic cup and randomly coded with three digits. To clean the palate between samples, water and unsalted crackers were served. The descriptive test was performed in a special tasting room with individual booths (controlled temperature of 21 ± 1 °C and combined natural/artificial light), and to collect panelists’ evaluations, ballot charts were used. The samples were presented based on a randomized block design to avoid biases. Numerical scale from 0 to 10 was used by the panelists to quantify the intensity of the almond attributes, where 0 represents no intensity and 10 extremely strong with a 0.5 increment (Figure 2).

2.6. Statistical Analysis

The stress integral of Ψleaf and yield were analyzed by Sigma Plot statistical software (version 12.5, Systat Software, Inc., San Jose, CA, USA). Initially, a descriptive analysis for each treatment and cultivar was done, applying a Levene’s test to check the variance homogeneity of the whole of data. Once completed, a one-way analysis of variance (ANOVA) was performed to determine whether there were statistical differences (p < 0.05) between irrigation treatments and within each cultivar, applying a Tukey’s test to find the differences among them.
Relating to the quality and sensorial parameters, a two-way analysis of variance (ANOVA) was performed, with the cultivar and irrigation being the two factors. Moreover, a Tukey’s multiple range test was carried out to establish the means that were significantly different from each other. XLSTAT Premium 2016 (Addinsoft, New York, NY, USA) was used to perform statistically significant differences, with a significant level p < 0.05.

3. Results and Discussion

3.1. Irrigation Doses, Crop Physiological and Yield Response

Table 1 summarizes the climatic conditions throughout the experiment with cumulative rainfall and crop evapotranspiration (ETC) of 85 and 840 mm, respectively. According to the registered data, the water irrigation amount for FI, SDI75 and SDI65 was 770, 574 and 516 mm, respectively.
The irrigation doses imposed different physiological responses and yield reductions were observed in the SDI strategies with respect to FI (Table 2). The cv. Marta reported higher values of ΨInt in SDI65 (197 MPa) compared to that registered in FI (179 MPa), with intermediate values for SDI75 (188 MPa). These differences were even more pronounced for cv. Guara with ΨInt values in SDI treatments (~210 MPa) significantly higher than in FI (194 MPa). Finally, cv. Lauranne did not register variations among treatments for ΨInt with values of 194 MPa.
In line with the physiological pattern previously described, the studied cultivars also presented yield reductions. In this regard, cvs. such as Marta and Lauranne did not showed significant variations among treatments, while cv. Guara was reduced about 8 and 17% in SDI75 and SDI65, respectively (Table 2).
Taking into consideration the obtained results, the water stress promoted different physiological and yield responses depending on the studied cultivar. In this regard, Gomes-Laranjo et al. [39] also reported different physiological responses of almond cultivars when they were subjected to deficit-irrigation strategies, concluding that cv. Lauranne would be less sensitive to irrigation restrictions than other cultivars. More recently, Gutiérrez-Gordillo et al. [17] revealed that cv. Marta evidenced a stronger stomatal control as compared to cvs. Guara and Lauranne, when subjected to regulated deficit-irrigation strategies. On the contrary, cv. Guara would show a minor conservative behavior, being able to maximize the gas-exchange rates when subjected to water restriction.
However, as observed in the present study, Guara was the most sensitive cultivar growth under SDI conditions. This point is especially remarkable considering that this cultivar presented very positive responses when water restrictions were applied during the kernel-filling period [40,41]. This means that the final response to water stress would be determined by the effect of water restriction, cultivar and deficit-irrigation strategy. Similar results were also reported by Alegre et al. [42], who obtained higher yield reductions in cv. Guara as compared to cv. Lauranne, when they were subjected to severe SDI (~2500 m3 ha−1). Moreover, Miarnau et al. [43] suggested that under SDI strategies, with irrigation applications around 2000 m3 ha−1, cv. Marta would be able to reach higher productions (1850 kg ha−1) than those obtained by cv. Guara (1200 kg ha−1) when using similar irrigation doses. Thus, these results would reinforce the statement that cv. Marta would be able to activate a physiological prevention mechanism to mitigate the water stress, leading to a higher yield than cv. Guara.

3.2. Morphological and Physical Parameters

Table 3 displays the main results related to the effects of irrigation doses and cultivar on the physical and morphological properties of raw almonds. Both irrigation treatments and cultivars offered significant differences on the weight, size and physical parameters. In relation to the almond weight, cv. Marta stood out, comparing to cvs. Guara and Lauranne. More evident were the improvements fixed in the almond weight from SDI65 trees regarding to SDI75 and FI treatments. These differences were also found in the morphological parameters, with higher values in SDI65 for kernel length, the whole thickness and kernel thickness. As was expected, these morphological differences were even more pronounced between cultivars. Thus, cvs. Marta and Lauranne offered a more lengthened morphology in comparison to cv. Guara. In relation to the kernel color coordinates, significant differences between cultivars and treatments were observed. Thus, SDI75 and SDI65 registered higher values of L*, a* and b* that evidenced lighter, redder and yellower almonds than FI and with even greater values of chroma, which means a higher color intensity of samples perceived by humans. Instrumental color was also affected by the cultivar, with Guara being the cultivar with the highest values of L*, a*, b* and chroma, whereas cvs. Lauranne and Marta showed a higher similarity between them for these parameters.
In relation to the interaction between irrigation dose × cultivar, all the studied parameters reported significant differences. For cv. Marta, the most notable effects related to the irrigation doses were found for the almond size, with higher values of kernel thickness and length. Moreover, this cultivar registered lower values of L*, a*, b* and chroma for SDI65, while SDI75 was mainly similar to FI almonds. More interesting were the irrigation effects in cv. Guara with significant improvements in the almond and kernel weight for SDI65 compared to SDI75 and FI. Within this cultivar, SDI65 presented higher values of L*, b* and chroma, while SDI75 generated almonds with a greater hardness and crispiness. Finally, regarding cv. Lauranne, higher values of almond weight and color on SDI65 were observed, although the weight improvements were more pronounced in the almond shell.

3.3. Total Sugars and Phenolic Content

The total sugars (TSC) and total phenolic (TPC) contents are shown in Table 4. High significant effects were observed in response to the studied cultivars and irrigation dose imposed. Regarding the TSC, the highest values were reached in almonds under water stress conditions, with SDI75 and SDI65 having a TSC of 62.9 and 62.2 g kg−1, respectively, which increased ~19% with regard to almonds growth under full-irrigated conditions. The cvs. Guara and Lauranne registered the highest values of sugars with ~1.4-fold higher than cv. Marta. Comparing all cultivars and irrigation treatments the highest values were reached by cv. Guara under SDI75 (76.1 g kg−1), followed by cv. Guara under SDI65 (68.4 g kg−1) and cv. Lauranne under SDI75 and SDI65 (65.1 and 64.7 g kg−1, respectively). Thus, SDI conditions led to higher total contents of sugar in all cultivars as compared to fully irrigated trees. As previously reported, raw almonds contain a variable amount of sugars, highlighting sucrose, glucose and fructose [27], whose concentrations are significantly affected by both water stress and cultivar [26]; and hence, their concentrations can vary depending on the water management applied during the fruit development. The increase of sugars in the fruits under stress circumstances is mainly related to the osmotic adjustment, initiated to adapt the plant to dry and saline stress by accumulation of solutes rich in hydroxyl (-OH) groups (sugars, proline etc.) in the cytoplasm [44] and to the induction of the growth inhibitor abscisic acid, inducing the accumulation of osmotically active compounds, which help to protect the cells from harm [45]. Sugars are key compounds in the basic sweet taste of almonds, this fact being important for consumer acceptance [25,46] and essential in the aroma profile of toasted almonds, because these are precursors of aroma compounds formation during thermal processing [47].
On the other hand, the total phenolic content (TPC) expressed as gallic acid equivalent (GAE) was significantly raised by the SDI treatments with an increase of 28% regarding the FI almonds. Additionally, cv. Lauranne registered the highest values (3.68 g GAE kg−1), followed by cv. Guara (3.50 g GAE kg−1) and cv. Marta (3.40 g GAE kg−1), proving the cultivar effect for the TPC. Focusing on the interaction between the irrigation dose and cultivar, the highest TPC values were reached by cv. Guara in SDI65 and cv. Lauranne in SDI75 conditions (5.06 g GAE kg−1 and 4.86 g GAE kg−1, respectively), being the lowest values obtained by cvs. Marta and Guara under FI (2.79 and 2.29 g GAE kg−1) and cv. Lauranne under SDI65 conditions (2.37 g GAE kg−1). These results agreed with the study by Lipan et al., who found a positive correlation between TPC and water stress in almonds [31]. Moreover, Horner [48] reported that water stress in trees generates an increase in phenolic compounds precursors (free phenylalanine) and their synthesis could be more sensitive in moderate water stress circumstances.
Overall, the water stress in plants decrease the turgor pressure, increase the ion toxicity and inhibits the photosynthesis [49], which leads to the activation of the antioxidant defense system to deal with reactive oxygen species (ROS). The trigger of many defense mechanisms, including the increase in antioxidants to enhance plant tolerance to water stress is mainly done by plant phytohormones [49]. Almond polyphenols are mostly found in skin and are responsible of the kernel color and astringency [50]. In this line, Monagas et al. [51] identified flavonol monomers as well as oligomers up to seven units as the most abundant type of flavonoids in almond skin; moreover, the intensity of the astringency depended on the polymerization degree [52].

3.4. Volatile Compounds

Using NIST libraries and Kovats Index values (REF), a total of 35 volatile compounds were identified and presented in Table 5, together with their retention times, retention indices, and their odor descriptors. These include 10 alcohols, 13 alkanes, five terpenes, four aldehydes, one ketone, one acid and one ester. Significant differences (p < 0.001) were promoted by the effect of both irrigation and cultivar (Table 6) factors, with the highest values for V2 and V16 to V34 under SDI65 treatment, whereas V4–V9, V12, V14, V15, V17 and V35 reached the highest values under SDI75 treatment. According to this and attending to the sum (total volatile compounds content), SDI75 was able to increase the volatile compounds. By contrast, the SDI65 strategy reflected a reduction in the whole amount, which is significantly lower than that obtained under moderate SDI75, which confirms the theory about the quadratic equation of Horner [48], who reported a reduction in fruit chemical compounds when the stress threshold is exceeded. Additionally, differences among cultivars were also found, with Marta and Guara being the cultivars that registered the highest values of the total volatiles. However, focusing the attention in the most abundant compounds (V15 and V17), the highest amounts of benzaldehyde (V15) were registered for SDI75 (in terms of irrigation treatment) and Guara (in terms of cultivar) (Table 6). Regarding to pentamethyl heptane, which might be a degradation product of fatty acids, the highest amounts were found for the SDI strategies and cv. Marta.
Regarding the interaction irrigation × cultivar the highest contents of benzaldehyde were reached by cvs. Marta and Guara both under RDI75. For the case of pentamethyl heptane the highest values were found for cv. Marta under SDI75, cv. Guara under FI, and cv. Lauranne under SDI65. Finally, and considering the total volatiles, the highest values were registered by cv. Marta under RDI75, followed by cv. Guara under FI and cv. Lauranne under SDI65.
Alcohols were the most abundant volatile compounds found in the present experiment. In this line, Kwak et al. [32] reported that alcohols are the main volatiles in raw almonds (cv. Nonpareil) and are released by enzymatic reactions. These compounds might contribute to the typical raw sweet aroma of almonds and an increase in its concentration may improve consumer acceptance [31,32]. In the present study, the highest content of alcohols was reached by the SDI75 treatment (296 µg kg−1), followed by FI (288 µg kg−1) and it was reduced by SDI65 (243 µg kg−1). Regarding the cultivar effect, cv. Lauranne recorded the highest values of alcohols followed by cvs. Marta and Guara with 310, 296 and 220 µg kg−1, respectively.
The presence of alkanes, alkenes, acids and aldehydes are mainly related to the oxidative decomposition of the triglyceride and fatty acid components [56]. The oxidation of polyunsaturated fatty acids generates monohydroperoxides, which are precursors of volatile aldehydes such as hexanal, octanal, nonanal and decanal [57]. In the present study, only hexanal, hexenal and nonanal were identified, with values between 112 and 131 µg kg−1 with the lowest content corresponding to the SDI65 and SDI75 treatments and the highest one to the FI treatment. In this way, Yang et al. [54] when studying the roasted almond shelf life concluded that hexanal and nonanal concentrations should be less than 2140 and 5970 µg kg−1, respectively, at the endpoint of shelf life to be suitable for their consumption. Thus, the relatively low experimental contents of hexanal and nonanal are indicative of the freshness of the samples under study.
Benzaldehyde is released from amygdalin, its precursor, by enzymatic hydrolysis, which is a cyanogenic glycoside naturally produced in almond [32]. Moreover, benzaldehyde is a characteristic aroma compound of wild/bitter almonds with a low odor threshold and it is found in a lower concentration in sweet almonds, but it is cultivar dependent [47,58]. In this context, the concentration of benzaldehyde in cvs. Vairo and Nonpareil was reported to be below that needed to affect the aroma of the almonds [31,47]. In the present study, the benzaldehyde content for cv. Lauranne (31 µg kg−1) was similar to that reported for cv. Vairo [31]. However, a greater content of this compound was registered by cv. Marta (419 µg kg−1) and even higher by cv. Guara (542 µg kg−1). Thus, DI strategies significantly affected the benzaldehyde concentration, which was increased by SDI75 (465 µg kg−1), but decreased in more severe conditions of water stress such as SDI65 (235 µg kg−1) when compared to FI almonds (292 µg kg−1). This fact suggests that the benzaldehyde was cultivar and irrigation treatment dependent, which convert it in an alleged marker for cultivar and hydroSOStainable identification.

3.5. Descriptive Sensory Profile

Descriptive sensory analysis was conducted to quantify the hypothetical effects of cultivars and irrigation doses on the almond sensory profiles. In this sense, 15 attributes were considered, and in general, significant differences both affected by cultivar and irrigation were found (Table 7). Regarding the DI treatments, panelists found that FI and SDI75 almonds had an intense red-brown color, which agreed with instrumental data, which also showed the highest values for the a* coordinate (FI = 19.1a; SDI75 = 18.9ab; SDI65 = 18.2b), indicating that almonds from FI and SDI75 were more reddish than those from SDI65. Regarding the size, even though the instrumental measurements were statistically significant the trained panel did not detect significant differences for these parameters among irrigation treatments. Similar findings were revealed by Lipan et al. [46] and Carbonell-Barrachina et al. [23] on hydroSOStainable almonds and pistachios, respectively, where no significant differences on sensory size were detected.
Regarding the flavor attributes, higher intensity of sweetness, aromatics reminiscent of almond (almond ID) and benzaldehyde-like notes were found for SDI65 almonds; these results proved that these particular almonds are those having the most intense, typical almond flavor. As shown, the benzaldehyde perception by human was in the contrast with the volatile compound concentration, which was higher in the SDI75 in comparison to FI. However, the human perception regarding the sweetness was in agreement with the results of total sugar (Table 4), showing a higher sweetness and sugar content in almonds cultivated under deficit irrigation conditions.
Differences were also detected among cultivars in several attributes such as outer color, size, sweetness, overall nuts, almond ID and benzaldehyde notes. For instance, cvs. Lauranne and Guara had a more intense color as compared to cv. Marta. Regarding flavor, cv. Lauranne, showed the highest values of sweetness, nutty and almond flavors, followed by cvs. Guara and Marta. The highest value of benzaldehyde flavor was achieved by Guara (2.9) followed by cvs. Lauranne (1.7) and Marta (1.4), which agreed with the volatiles content in which cv. Guara registered the higher content of the benzaldehyde compound (Table 6). Considering the irrigation effects within each cultivar, the most relevant results were registered on the flavor attributes for cvs. Guara and Lauranne, which reached the highest values of sweetness, overall nuts, almond ID and benzaldehyde flavors in the DI strategies. On the contrary, a very different response was found in cv. Marta, which presented lower values in terms of almond taste for the SDI treatments, which is interesting in order to define the differential responses in terms of cultivar when a deficit irrigation strategy is imposed.
Although not many affective studies have been conducted using almond, Lipan et al. [25] concluded that both Spanish and Romanian consumers considered the almond ID (aromatics reminiscent of almond) and sweetness as the main attributes that control the consumer preferences. Moreover, sweetness, flavor, texture and price were the most relevant parameters in the CATA questionnaire when consumers were asked about their buying drivers. Taking into consideration the obtained results in this work, almond ID and sweetness were parameters that reached significant improvements when SDI was imposed, and it would reinforce the statement that water savings strategies in almond crop would help to obtain a final product with a higher acceptance by consumers. Thus, hydroSOStainable almonds with a final added value would allow to recover the economic losses caused by yield reductions, offering a product with a higher competitiveness and marketability (Figure 3), as has been corroborated by authors such as Lipan et al. [46], who concluded that consumers were willing to pay an extra amount of money for the hydroSOStainable almonds.

4. Conclusions

This work highlights the main effects of irrigation in three almond cultivars in terms of the morphological, physicochemical and sensory parameters when this crop is subjected to sustained-deficit irrigation treatments. The findings allow us to conclude that almonds subjected to moderate sustained water stress improved substantially the most important features (sugars, total phenolic content and volatiles) related to the sensory profile and, probably, consumer acceptance. These results supported that all the monitored parameters besides water irrigation amounts are also cultivar-dependent, which determines the need of characterization of each cultivar growth under deficit irrigation conditions. Moreover, this study displayed the advantages of these strategies and opened the possibility of showcasing those hydroSOStainable products that have been obtained within a framework of water scarcity and sustainable use of natural resources. Thus, the findings prove the importance of considering the cultivar effect when these strategies are being imposed, not only in terms of final yield, but also from a nut quality perspective.

Author Contributions

Writing: I.F.G.-T., L.L. and S.G.-G.; Conception or design: I.F.G.-T., L.L. and S.G.-G. Acquisition, analysis, and interpretation of data: I.F.G.-T, L.L., S.G.-G., I.J., F.H. and Á.A.C.-B.; Critical revision of the manuscript for important intellectual content: Á.A.C.-B., V.H.D.Z. and B.C.R.; Statistical analysis: L.L. and I.F.G.-T.; Reagents/materials/analysis tools contribution: L.L., I.J., F.H., B.C.R. and Á.A.C.-B. All authors have read and agree to the published version of the manuscript.


This work has been partially sponsored by the research project “Impact of climate change and adaptation measures (INNOVA-Climate)” (AVA.AVA2019.051) both co-financed by the European Regional Development Fund (ERDF) within the Operational Programme Andalusia 2014–2020 “Andalucía is moving with Europe” and the Spanish Ministry of Economy, Industry and Competitiveness; through the research project (hydroSOS mark) including the Universidad Miguel Hernández de Elche (AGL2016-75794-C4-1-R, hydroSOS foods) and the Universidad de Sevilla (AGL2016-75794-C4-4-R). The author S. Gutiérrez-Gordillo has a contract co-financed by the National Institute of Agrarian and Food Research and technology (FPI-INIA 2016) and European Social Fund (ESF) “The European Social Fund invests in your future.”

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Experimental almond orchard (A) and cvs. Marta (B), Guara (C) and Lauranne (D).
Figure 1. Experimental almond orchard (A) and cvs. Marta (B), Guara (C) and Lauranne (D).
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Figure 2. Scales reference used by trained panel to evaluate the almond appearance in this study.
Figure 2. Scales reference used by trained panel to evaluate the almond appearance in this study.
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Figure 3. HydroSOStainable almonds: towards an equilibrium among water savings, optimum yields and quality parameters supported by marketability and sensory profile. ↑, increase.
Figure 3. HydroSOStainable almonds: towards an equilibrium among water savings, optimum yields and quality parameters supported by marketability and sensory profile. ↑, increase.
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Table 1. Monthly average values of weather parameters and irrigation doses during the study period.
Table 1. Monthly average values of weather parameters and irrigation doses during the study period.
Tmax (°C)22.230.431.334.536.532.427.6
Tmin (°C)
Tav (°C)19.821.522.725.826.923.818.9
RHmax (%)97.885.
RHmin (%)39.823.323.425.318.727.632.9
RHav (%)72.252.351.455.445.954.463.2
Rad (MJ m−2)
Rainfall (mm)
ETo (mm)111.0198.0202.9238.7170.1121.076.4
ETC (mm)441191352151799746
Irrigation (mm)
Tmax, Tmin, Tav, maximum, minimum and average air temperature; RHmax, RHmin, RHav, maximum, minimum and average relative humidity; Rad, solar radiation; ET0, reference evapotranspiration; ETC, crop evapotranspiration rate; FI, SDI75, SDI65, full-irrigated and sustained-deficit irrigation at 75 and 65% of irrigation requirements, respectively.
Table 2. Integral stress (ΨInt) values and almond yield for the different cultivars and irrigation treatments.
Table 2. Integral stress (ΨInt) values and almond yield for the different cultivars and irrigation treatments.
CultivarΨInt (MPa day)
Almond yield (kg ha−1)
Values (average of eight replications; n = 8) within a same row, and followed by different letters, show significant differences between treatments and within each cultivar, according to Tukey’s test (p < 0.05). FI, SDI75 and SDI65, full-irrigated and sustained-deficit irrigation at 75 and 65% of irrigation requirements, respectively.
Table 3. Morphology and instrumental color of raw almonds as affected by deficit treatment and almond cultivar.
Table 3. Morphology and instrumental color of raw almonds as affected by deficit treatment and almond cultivar.
Weight (g)Size (mm)Kernel Color Coordinates
Irrigation × Cultivar***********************************NS
Tukey Multiple Range Test
FI3.19ab1.08b2.11ab30.722.2b21.4 13.315.0b8.30a45.9b19.1a29.9b35.6b60.4
cv. Marta3.49a1.19a2.30a30.2ab23.1a20.3c12.8b14.8b8.34a47.3b17.9b32.1b36.8b60.4
cv. Guara2.92b1.07b1.85c29.8b21.6c22.7a13.5a15.9a8.43a49.4a19.2a35.0a40.1a64.1
cv. Lauranne3.22ab1.05b2.17b30.9a22.4b21.5b13.4a14.6b7.97b46.6b19.1a32.2b37.5b58.9
Irrigation × Cultivar
cv. Marta
cv. Guara
cv. Lauranne
NS, not significant at p < 0.05; ** and *** significant at p < 0.01, and 0.001, respectively. Values (average of 25 replication) followed by the same letter, within the same column and factor, were not significantly different (p < 0.05), according to Tukey’s least significant difference test. WL, Whole Length; KL, Kernel Length; WW, Whole Width; KW, Kernel Width; WT, Whole Thickness; KT, Kernel Thickness; L*, a*, b*, Color coordinates; C, Chroma. FI, SDI75, SDI65, full-irrigated and sustained-deficit irrigation at 75 and 65% of irrigation requirements, respectively.
Table 4. Impact of deficit irrigation on total phenolic (TPC) and sugars contents (TSC).
Table 4. Impact of deficit irrigation on total phenolic (TPC) and sugars contents (TSC).
TSC (g kg−1)TPC (g GAE kg−1)
Irrigation × Cultivar******
Tukey Multiple Range Test
Irrigation × Cultivar
cv. Marta
cv. Guara
cv. Lauranne
—Analysis of variance test (ANOVA), *** significant at p < 0.001; GAE, Gallic Acid Equivalent; Values (average of three replications) followed by the same letter, within the same column and factor, were not significantly different (p > 0.05), according to Tukey’s least significant difference test. FI, SDI75, SDI65, full-irrigated and sustained-deficit irrigation at 75 and 65% of irrigation requirements, respectively.
Table 5. Volatile compounds profile in raw studied almonds cultivars, retention index and main odor and aroma descriptors.
Table 5. Volatile compounds profile in raw studied almonds cultivars, retention index and main odor and aroma descriptors.
CodeCompoundChemical FamilyRT (min)Retention Index Odor Descriptor
V13-Methyl-2-butanolAlcohol1.65699700Musty, alcoholic, vegetable, cider, cocoa, cheesy 1
V2Acetoin Ketone1.765702707Sweet, buttery, creamy, dairy, milky, fatty 1
V3Acetic acid ¥Acid2.083717630Pungent, acidic, cheesy, vinegar1
V43-HexenolAlcohol2.548739746Green, leafy, floral, petal, oily, earthy 1
V51-PentanolAlcohol3.053764762Pungent, fermented, bready, yeasty, winey, solvent-like 1
V62-PentenolAlcohol3.097767767Fermented, ripe banana, apple 1
V8Octane Alkane3.805800800
V9HexanalAldehyde3.905805804Fresh green fatty aldehydic grassy leafy fruity sweaty 1
V10(2E)-2-Octene Alkene4.057812815
V11(2E)-2-HexenalAldehyde4.457831825Green, banana, aldehydic, fatty, cheesy 1
V12Nonane Alkane5.903900900Gasoline 1
V13ɑ-PineneTerpene6.924934933Sharp, warm, resinous, fresh, pine 1
V14CitronelleneTerpene7.241945945Citronellol, herbal, citrus, terpenic 1
V15BenzaldehydeAldehyde7.963970967Almond, fruity, powdery, nutty, cherry, sweet, bitter 1
V16HeptanolAlcohol8.435986977Musty, leafy green, fruity, apple, banana and nutty and fatty notes 1
V172,2,4,6,6-Pentamethyl heptane ¥Alkane8.627991997
V18Decane Alkane8.8710001000
V192-OctanolAlcohol9.19210101010Fresh, spicy, green, woody, herbal earthy 1
V20LimoneneTerpene9.9710321034Citrus, orange, sweet, fresh, peely 1
V212-Ethyl-hexanolAlcohol10.04410341030Citrus, fresh, floral oily sweet 1
V223,5,5-Trimethyl-hexanol Alcohol10.51310481048Green, floral, camphoreous, woody, melon, berry.
V23ButanoateEster10.83910581054Fruity, pineapple odor 1
V24UndecaneAlkane12.33311001100Waxy, fruity, creamy, fatty, orris, floral, pineapple 1
V25LinaloolTerpene12.52511061106Citrus, orange, floral, terpy, rose 1
V26NonanalAldehyde12.86211151107Waxy, aldehydic, citrus, green lemon peel, orange peel 1
V27Octyl-formate Alkane13.68311361128Fruity, rose, orange, waxy, cumber 1
V281-NonanolAlcohol15.42511851181Fresh, clean, fatty, floral, rose, orange, dusty, wet, oily 1
V29(2Z)-2-DodeceneAlkene15.70111931193Pleasant odor 2
V313,7-Dimethyl-1-octanol ¥Alcohol16.28312091190Aldehydic citrus, rosy and green woody notes 1
V33TetradecaneAlkane22.514011400Mild waxy 1
V34PentadecanolAlcohol27.99317701772Mild alcohol odor 2
V35Geranyl linaloolTerpene29.93320392034Mild floral rose balsam 1
¥ tentatively identified (identification only based on spectral database); RT, retention time; NIST [53]; 1 Company [54]; 2 NCBI [55].
Table 6. Volatile compounds are based on the use of 2-acethyl thiazole as internal standard in raw almonds.
Table 6. Volatile compounds are based on the use of 2-acethyl thiazole as internal standard in raw almonds.
ANOVA IrrigationCultivarIrrigation × Cultivar
CodeIrrigationCultivarIrrigation × CultivarFIRDI75RDI65MartaGuaraLaurannecv. Martacv. Guaracv. Lauranne
(µg kg−1)
—Analysis of variance test (ANOVA), ***, significant at p < 0.001; Values (mean of three replications) followed by the same letter within the same row were not significantly different (p < 0.05), according to Tukey’s least significant difference test. FI, SDI75 and SDI65, full-irrigated and sustained-deficit irrigation at 75 and 65% of irrigation requirements, respectively.
Table 7. Descriptive sensory analysis of raw almonds as affected by deficit irrigation. Scale used ranged from 0 = no intensity to 10 = extremely strong intensity.
Table 7. Descriptive sensory analysis of raw almonds as affected by deficit irrigation. Scale used ranged from 0 = no intensity to 10 = extremely strong intensity.
Outer ColorSizeRoughnessSweetnessBitternessAstringencyOverall NutsAlmond IDBenzaldehyde LikeWoody
Irrigation × Cultivar************NSNS*********NS
Tukey’s Multiple Range Test
Lauranne3.0a2.7b3.75.3a0.90.65.7 a5.2a1.7b1.6
Irrigation × Cultivar
cv. Marta
cv. Guara
FI4.9a2.8abc4.1ab4.0b1.20.54.4ab3.6bc2.4 abc2.1
SDI751.5bc2.1c5.1a4.1b1.80.94.9ab4.8ab2.9 ab1.3
cv. Lauranne
NS, not significant at p < 0.05; *** significant at p < 0.001; Values (mean of 10 trained panelists) followed by the same letter, within the same column, were not significantly different (p > 0.05), according to Tukey’s least significant difference test. FI, SDI75 and SDI65, full-irrigated and sustained-deficit irrigation at 75 and 65% of irrigation requirements, respectively. Almond ID, aromatics reminiscent of almond.
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García-Tejero, I.F.; Lipan, L.; Gutiérrez-Gordillo, S.; Durán Zuazo, V.H.; Jančo, I.; Hernández, F.; Cárceles Rodríguez, B.; Carbonell-Barrachina, Á.A. Deficit Irrigation and Its Implications for HydroSOStainable Almond Production. Agronomy 2020, 10, 1632.

AMA Style

García-Tejero IF, Lipan L, Gutiérrez-Gordillo S, Durán Zuazo VH, Jančo I, Hernández F, Cárceles Rodríguez B, Carbonell-Barrachina ÁA. Deficit Irrigation and Its Implications for HydroSOStainable Almond Production. Agronomy. 2020; 10(11):1632.

Chicago/Turabian Style

García-Tejero, Iván Francisco, Leontina Lipan, Saray Gutiérrez-Gordillo, Víctor Hugo Durán Zuazo, I. Jančo, F. Hernández, Belén Cárceles Rodríguez, and Ángel Antonio Carbonell-Barrachina. 2020. "Deficit Irrigation and Its Implications for HydroSOStainable Almond Production" Agronomy 10, no. 11: 1632.

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