The gross photosynthesis rate (A), the apparent quantum efficiency (Φ), photosynthetically active radiation (PAR), the rate of assimilation at saturating light intensity (Amax), and mitochondrial respiration in darkness (Rd) were obtained from the A/PFD curves adjusted to a non-rectangular hyperbole-type equation, according to the procedure described by Lambers et al. [39]. The straight section of the curve was adjusted to a polynomial equation whose intersection on the *x*-axis corresponds to the light compensation point, and the slope is the apparent quantum yield.

### (ii) A/Ci Curves

Measurements were made at light saturation (1500 µmol photons m−2 s −1 ). The relative humidity of the chamber ranged from 40% to 50%, and the leaf temperature was 25 ± 2 ◦C. The CO2 concentrations used were 50, 350, 500, 700, 900, 1200, and 1500 µL L−1 , and the assimilation response to these intensities was adjusted to the Farquhar model [40,41] with PHOTOSYN software (version 1.1.2, Dundee Scientific Ltd., Dundee, UK). Parameters such as the maximum rate of RubisCO activity (Vc,max), the transport of electrons at light saturation (Jmax), and the triose phosphate transport rate (TPU) were obtained from this model, which expresses the ratio of the assimilation rate (A) to the internal concentration of CO2 (C*i* ) for each of the three factors affecting assimilation.

When carboxylation is limited only by the activity of RubisCO, then Wc can be described by the model developed by Farquhar et al. [40], which is based on gaseous exchange measurements.

When the transport of electrons limits photosynthesis due to the effect of RuBP regeneration, Wj can be expressed according to Farquhar and Von Caemmerer [41]. The potential rate of electron transport (*Jp*) was calculated using the expression developed by Harley et al. [42].

#### (iii) Determination of the linear transport rate of electrons

To measure photosystem II (PSII) efficiency, the IRGA 6200 chamber was adapted by introducing a Hansantech PEA modulated pulse fluorometer sensor at one end. The parameters were calculated according to the methodology described by Maxwell and Johnson [43].

Quantum yield (ΦPSII) can be used to calculate the linear transport rate of electrons (*J*), which corresponds to photosynthetic capacity in vivo, according Genty et al. [44]. A factor of 0.84 is assumed for leaf absorbance in C3 plants [45], although this absorbance may change slightly with temperature (this experiment was conducted at foliar temperatures of 25 ± 3 ◦C).

The photochemical energy used for photosynthesis or photochemical quenching (qP) and non-photochemical quenching (NPQ) were calculated using equations described by Genty et al. [44].

#### *2.5. Removal of Stomatal Effects*

To remove the stomatal effect on CO2 assimilation (A), the methodology described by Centritto et al. [15] was used. For this purpose, a set of A/Ci curves were generated for both ecotypes. The procedure employed can be divided into four phases: In phase (I), stomatal restriction (R) was induced by lowering the concentration of CO2 from 350 to 50 µL L−1 and

allowing gs to decrease to values close to 15 mmol m−2 s −1 . Subsequently, in phase (II), the CO2 concentration was raised to 1500 µL L−1 , and measurements of the A/Ci curve were made until 50 µL L−1 . In phase (III), a CO2 concentration of 50 µL L−1 was maintained for a minimum of 40 min, which depended on the stomatal behavior of each ecotype and treatment; in this way, stomatal opening was activated. Phase (IV), the final phase, was initiated once stomatal conductance began to rise above 600 mmol m−2 s −1 . This raised the CO2 concentration to 1500 µL L−1 , and A/Ci was measured with no stomatal restrictions (nR). A value of 600 mmol m−2 s −1 was used based on the data of Jacobsen et al. [26], who reported a gs of 600 mmol H2O m−2 s −1 in quinoa without water restrictions. The times used in each stage are detailed in Table 1.

**Table 1.** Times of application of different concentrations of environmental CO2 to induce the closure and opening of stomata.

#### *2.6. Determination of Mesophyll Conductance (gm)*

Mesophyll conductance (gm) was determined according to the procedure described by Harley et al. [42] using the following parameters: assimilation rate (A), light compensation point (Γ), electron transport rate (J), and dark respiration (Rd).

#### *2.7. Rate Carboxylation and Electron Transport In Vivo*

The RubisCO activity rate at RuBP saturation (Vc,max), the maximum electron transport rate (Jmax), the maximum rate of assimilation at saturating PFD, and CO2 (Amax) and mitochondrial respiration in light per unit of foliar area (Rd) were obtained using the model described by Farquhar et al. [40]. From this model, A was determined using Equation (1):

$$\mathbf{A} = \mathbf{v}\mathbf{c} - 0.5\mathbf{v}\mathbf{o} - \mathbf{R}\mathbf{d} \tag{1}$$

where vc and vo are the rates of carboxylation and oxygenation of RubisCO, respectively, and 0.5 is the stoichiometric relationship between the O2 absorbed by RuBP oxygenase and the photorespiratory evolution of CO2 [41]. Additionally, vc cannot be greater than the minimum rate of carboxylation of RubisCO (Ac), and the rate of electron transport limits the regeneration of RuBP (Aj ).

#### *2.8. Data Analysis*

A 2 × 2 factorial design was used, arranged in completely randomized blocks (Bi ). The first factorial level was NaCl concentration (Cj ) (0 M and 0.4 M NaCl), and the second level was the ecotype (Ak) (Amarilla and Hueque). Each treatment had 6 replications, and

the experimental unit consisted of 2 pots, each with 4 plants (8 plants). Duncan's multiple comparison one-way analysis of variance (ANOVA) was performed using Infostat V 2016 (Universidad de Cordoba, Cordoba, Argentina) *p* < 0.01 was considered significant.

#### **3. Results**

#### *3.1. Stress Indicators*

When comparing the control plants of the two ecotypes, Hueque had a higher concentration of GB in the roots. When exposed to 0.4 M NaCl, the GB content increased in both ecotypes, and it was higher in Hueque. Figure 1a shows that in the salt-tolerant ecotype (Amarilla), the GB content was higher in the leaves than in the roots. In the roots, salt stress had no effect on GB content, whereas in the leaves, GB content increased significantly. The leaf/root ratio of GB content in Amarilla control plants was 3.64, while in stressed plants, it rose slightly to 4.34, which could indicate that this ecotype is not severely stressed by high salinity. In the salt-sensitive ecotype (Hueque), the constitutive concentration of GB was also higher in the leaves than in the roots. In the roots, the salt stress caused a decrease in the GB content; in contrast, GB rose significantly in the leaves. The leaf/root ratio of GB was 2.12 in Hueque control plants and 7.95 in stressed plants, which means that the GB synthesis in leaves was more sensitive to salt signals coming from roots.

**Figure 1.** Effect of salinity on glycine betaine (**a**) and proline (**b**) content in the roots and leaves of quinoa plants. Different letters denote significant differences (*p* ≤ 0.05). Average values were calculated based on 4 samples per treatment (mean ± SE).

The Pro content in the control plants did not differ much between the two ecotypes. Exposure to 0.4 M NaCl increased the Pro content in all tissues tested in both ecotypes, and it was highest in Hueque. Figure 1b shows that in the tolerant ecotype, the content of Pro was significantly higher in the leaves than in the roots under both control and saline conditions. The leaf/root ratio of Pro in control plants was 6.53, and in salt-exposed plants, it fell to 2.53; this decrease was mainly due to the Pro increase in the roots. In Hueque, the content of Pro was greater in the leaves than in the roots. Applying salt did not cause changes in Pro levels in the roots, whereas in leaves, the Pro content rose significantly. The leaf/root ratio of Pro in control plants was 3.02, and when exposed to 0.4 M NaCl, it was 2.40.

#### *3.2. Na+ and K+ Content*

The tolerant ecotype accumulated in root 64.6% more Na+ than the sensitive one in control conditions. Under salt stress, this difference decreased to 33% in both ecotypes because the sensitive ecotype accumulated proportionally more sodium than the tolerant one (7.4 versus 3.4 times, respectively) (Figure 2a). However, the plants showed no changes in the leaf Na+ level, regardless of salt exposure. The K+ content in roots was similar in the control plants of both tolerant and sensitive ecotypes and decreased significantly under salt stress. Under high concentrations of soil salt, the K+ content decreased in the roots and was maintained in the leaves in both ecotypes (Figure 2b).

**Figure 2.** Effect of salinity on the content of Na+ (**a**) and K+ (**b**) in Amarilla and Hueque ecotypes of quinoa. Different letters denote significant differences (*p* ≤ 0.05). Average values were calculated based on 4 samples per treatment (mean ± SE).

### *3.3. Effect of Salinity on CO2 Assimilation under Different Light Intensities*

The A/PFD curves are shown in Figure 3. In the absence of salt stress, both ecotypes had a similar quantum yield performance and assimilation rate at light saturation. The Amax values for Amarilla and Hueque were 9.98 and 9.05 µmol CO2 m−2 s −1 , respectively (Table 2). However, the intensities at which light saturation reached were significantly different between the ecotypes: CO2 assimilation saturated at 957 PAR µm−2 s −1 in Hueque and at 1262 µmol PAR m−2 s −1 in Amarilla (Table 2).

**Table 2.** The effect of salinity on different photosynthetic values of Amax and gs were obtained from curves of Figure 3 determined at the light saturation point and 350 µL CO2 L −1 .

\* Different letters indicate significant differences (*p* ≤ 0.01).

Under saline conditions (0.4 M NaCl), both ecotypes presented a drastic decrease in CO2 assimilation rates with respect to control plants (Figure 3). For example, the decrease in Amax was 37.7% in the tolerant ecotype but 65.1% in the sensitive one (Table 3). On the other hand, at light intensities exceeding the corresponding light saturation point, saline conditions induced photoinhibition in both ecotypes. This was very drastic in the sensitive ecotype, in which assimilation was almost null at 2500 µmol photons m−2 s −1 (Figure 3).

**Figure 3.** CO2 assimilation curves of two quinoa ecotypes subjected to salinity conditions. Empty symbols and continuous lines correspond to treatments without salt, while filled symbols with dotted lines correspond to 0.4 M NaCl treatments. Different letters denote significant differences (*p* ≤ 0.05). Average values were calculated based on 3 leaves taken from 6 plants per treatment (mean ± SE).

The analysis of the main photochemical parameters (Table 3) shows that the photochemical efficiency (ΦPSII) and rate of linear electron transport (J) were negatively affected by salt stress in both ecotypes. ΦPSII decreased by 18.1% for Amarilla and 29.2% for Hueque. J changed by 17.4% and 27.7% for Amarilla and Hueque, respectively.

**Table 3.** Harvested energy efficiency (ΦPSII) and rate of linear electron transport (J).

\* Different letters indicate significant differences (*p* < 0.01).

#### *3.4. Determination of Non-Restrictive (nR) and Restrictive (R) Stomatal Conductance*

Figure 4 shows the evolution of Ci and gs at different timepoints, CO2 concentrations, and NaCl treatments for both ecotypes according to the procedure proposed by Centritto et al. [21]. This enabled us to determine the times and CO2 concentrations required to induce the rates of stomatal conductance, both restrictive (R) and non-restrictive (nR).

**Figure 4.** Curves of each ecotype used to determine the times necessary to induce stomatal opening. The continuous line represents the internal concentration of CO2 (Ci), and the dotted line is stomatal conductance. The line parallel to the *x*-axis represents the minimum limit required for open stomata. Lines parallel to the *y*-axis define the measurement periods. R—measurements with stomatal constraints; nR—measurements with no stomatal constraints. The induction period corresponds to the time interval required to induce stomata opening by applying a concentration of 50 µL CO2 L −1 . Internal concentrations correspond to IRGA measurements with respect to the application of a specific environmental CO2 concentration, applied according to the time sequences described in Table 1.

Once the CO2 concentration was lowered to 50 µL L−1 (phase III), the stomata opened after approximately 1.5 h (90 min). This allowed similar stomatal conductance behaviors to be maintained between non-stress and 0.4 M NaCl conditions in both ecotypes. The maintenance of Ci at values equal to or less than 50 µL L−1 caused a rapid response in the tolerant ecotype in control and saline conditions (Figure 4a,b). Thus, the method initially

reduced the conductance to values close to 0.1 mol H2O m−2 s −1 , which then increased to 1.5 and 1.6 mol H2O m−2 s −1 in the tolerant ecotype (at 0 and 0.4 M NaCl, respectively). In Hueque, the initial value was 0.09 mol H2O m−2 s −1 , which then increased to 1.2 mol H2O m−2 s −1 at 0 M NaCl and 2.1 mol H2O m−2 s −1 at 0.4 M NaCl. It was also observed that Hueque presented a higher gs as well as a greater duration of stomatal opening in saline conditions (Figure 4c,d).

These data are consistent with the assimilation rates observed in plants with stomatal restriction (R) and without stomatal restriction (nR) (Table 4). In the salt-tolerant ecotype under control and nR condition, Amax increased from 13.8 to 21.43 µmol CO2 m −2 s −1 , which means that, in this case, the elimination of the stomatal restriction accounted for 55.7% of the assimilation rate. This effect was repeated in plants subjected to saline stress under the nR condition, but in this case, stomatal restriction accounted for only 25.4% of the increase in Amax (Table 4).

In the sensitive ecotype under non-salt conditions, the elimination of stomatal restriction did not induce a significant increase in Amax (6.7%), which suggests that this ecotype involves another resistance mechanism, such as mesophyll resistance. However, when salt-sensitive plants were treated with salt, elimination of stomatal restriction induced a 41.2% increase in Amax. In both ecotypes, elimination of stomatal restriction induced a decrease in gross respiration under both control and salt stress conditions (Table 4).

**Table 4.** The effect of salinity Amax, Gross Respiration and Carboxylation efficiency parameters of tolerant and sensitive ecotypes of quinoa, obtained from A/Ci curves (Figure 5).

R: with stomatal restriction; nR no stomatal restriction; Amax: Maximum assimilation rate; Gross resp.: Gross respiration (dark and photorespiration); Carbox. Efic.: Carboxylation efficiency; Different letters indicate Significance level (*p* ≤ 0.01).

> The analysis of carboxylation parameters (Table 4) showed that the carboxylation efficiency in Amarilla control plants under non-restrictive stomatal conditions (nR) was not significantly altered (*p* > 0.05). However, in salt-stressed plants with nR, carboxylation efficiency was reduced by 44.1% compared to that observed in control plants, which may be associated with the effect of mesophyll conductance (gm). In the salt-sensitive ecotype, salt stress caused decreases in carboxylation efficiency of 76% and 48% for R and nR, respectively.

> On the other hand, the unaltered maximum rates of RubisCO activity (Vcmax) and Triose Phosphate Transport (TPU) (Table 5) indicate that, in the tolerant ecotype, the reduction in CO2 assimilation caused by salt was not due to RubisCO activity or the supply of inorganic phosphate to chloroplasts. Differently, Vcmax, TPU in Hueque fell by 36.6% and 17.9% in R and nR conditions, respectively, showing that CO2 assimilation was affected by these factors (Table 5).

**Table 5.** The effect of salinity on the main photosynthetic parameters of tolerant and sensitive ecotypes of quinoa using the model of Farquhar et al. (1980).

R: with stomatal restriction; nR without stomatal restriction; Vc,max is: Maximum rate of RubisCO activity; Jmax is the transport of electrons at light saturation and TPU is triose phosphate transport rate. Different letters indicate Significance level (*p* ≤ 0.01).

> The quantum efficiency of PSII (ΦPSII) determined by the ratio of variable fluorescence (FV) and maximum fluorescence (Fm) (FV/FM) did not reveal an effect of salinity on the photochemical components of photosynthesis in either ecotype subjected to salt stress (Table 6). This means that photosystems I and II were not damaged. Therefore, it is unlikely that the decreases in the assimilation of CO2 and TPU are affected by the supply of ATP or NADPH.

**Table 6.** Quantum efficiency of PSII.

\* Different letters indicate significant differences (*p* ≤ 0.01).

#### **4. Discussion**

*4.1. Effect of Salt on Stress Indicators*

With respect to stress indicators, the present results confirm those of the previous studies in quinoa using the same or other ecotypes under similar salt conditions [16,30,46]. Pro accumulation has been reported in several southern Chilean quinoa accessions in response to 300 and 450 mM NaCl; genotypes considered tolerant to salt stress accumulated 3–5-fold more Pro than control plants, while the more sensitive ones exhibited moderate increases [19,46–48]. Several reports on glycophytes and halophytes have indicated that accumulation of GB depends on the genotype and salt stress intensity, and a positive correlation between GB levels and salt tolerance has been reported [49,50]. Our results concur with these previous studies, as increases in the GB and Pro contents were observed in the leaves of both ecotypes in response to salt stress; however, in this case, it was the sensitive ecotype that presented a greater accumulation of both osmolytes. While many studies have indicated a positive relationship between GB and/or Pro accumulation and plant stress tolerance, some have argued that increases in these compounds are a product of, non- adaptive response to, salt stress [16]. In drought-stressed corn, increased ABA content was followed by an elevation in betaine aldehyde dehydrogenase (BADH) activity, leading to GB accumulation [51]. Moreover, BADH and P5CS genes, related to GB and Pro biosynthesis, respectively, were upregulated in response to treatments with salt or chromium combined with salt in quinoa [50,52,53]. In addition, exogenous applications of GB and Pro in crop species such as rice and tomato help mitigate the effects of environmental stresses, including water and salt stress [47], meaning that they may have

a role in adaptive responses to abiotic stresses. The salt-sensitive ecotype (Hueque) had a higher constitutive concentration of GB, and under salt stress conditions, the GB content in leaves was significantly enhanced and was higher than that in Amarilla. Under saline conditions, GB biosynthesis in most plant species occurs in the chloroplast [48]. Thus, GB production may be overstimulated in leaves, thereby increasing the shoot/root ratio of GB, as observed in Hueque. In this salt-sensitive ecotype, high foliar levels of GB may contribute to the maintenance of growth by acting as a nitrogen donor [54], contributing to osmotic homeostasis [55], and protecting the plant from oxidative damage, in combination with Pro [56]. In the sensitive ecotype (Hueque), the situation seems to be similar at the root level because, while GB decreased, Pro increased to levels that were 50% higher than those in the tolerant plant, which maintained its GB content under salt stress.

Our results for Na+ and K+ contents agree with those reported by Adolf et al. [3] in two contrasting quinoa varieties, salt-tolerant and -sensitive, namely, Titicaca and Utusaya, respectively. They found that the Na+ content in the leaves increased drastically in plants treated with 0.4 M NaCl, and the increase was more pronounced in the salt-tolerant plant (Titicaca) compared to the more sensitive one (Utusaya). The significant increase found in leaf Na+ content in these two genotypes could be due to the duration of salt treatment (42 days of salt treatment vs. 15 days in our experimental design).

The salt treatment also caused a significant increase in the K+ concentration in the xylem of both ecotypes, but there were no differences in K+ between treated and untreated plants. Our findings are similar in that there were no differences in leaf K+ content between control and salt-treated plants. Our findings are similar to those reported by Orsini et al. [16] in that there were no differences in leaf K+ content between control and up to 450 mM NaCl salt-treated plants of the coastal ecotype accession BO78. Potassium ions are essential for enzyme activity, protein synthesis, photosynthesis, osmoregulation, transport of phloem solutes, and the maintenance of the cation–anion balance in the cytosol and vacuoles. Recently, K+ was also proposed to be a secondary messenger [57]. Thus, the ability of plants to retain K+ under salt stress has emerged as an important trait for salt tolerance. By contrast, Na+ is toxic in glycophytic plants, but not in halophytes [58]. Sodium ions cause multifactorial responses, such as osmotic stress [59,60], the inhibition of vital enzymes [61,62], and competition with K+ . Under salt stress, accumulated ions, such as Na+ , Cl– , and K+ , are used for osmotic adjustment in the aerial portions of halophytic plants [63], thus facilitating water uptake and transport and, presumably, lowering the metabolic cost required to produce large amounts of organic osmolytes, as previously described by Hariadi et al. for other quinoa genotypes [31].

At the root level, both tolerant and sensitive plants had similar responses in salinity conditions, decreasing the uptake of K+ and increasing the absorption of Na+ ; the latter was especially pronounced in the tolerant ecotype (Amarilla). In some cases, Na+ can replace K+ , particularly in its osmotic functions in vacuoles under K+ starvation conditions. Halophytes require less K+ for growth than glycophytes [1,10], demonstrating a link between the ability to replace K+ with Na+ and salt tolerance [64], which is consistent with the results found in this study, in which the salt-tolerant ecotype had higher levels of Na+ . In barley, a high concentration of Na+ allows plants to osmotically adapt to and maintain turgor under high salinity, which is a metabolically inexpensive mechanism for osmotic adaptation. However, this new Na+/K+ homeostasis could create a greater demand for organic solutes for osmotic adjustment, thereby compromising the energy balance of the plant [65]. In salt-tolerant barley cultivars [66], K+ was reported to be the main contributor to cytoplasmic osmolality, whereas in salt-sensitive genotypes, GB and Pro compensated for reduced cytosolic K+ levels.

### *4.2. CO2 Assimilation and Stomatal and Mesophyll Conductance*

In both ecotypes, the decrease in CO2 assimilation due to salinity was accompanied by a decrease in stomatal conductance. However, this decrease in gs was greater in Hueque, (57%, Table 2), than in Amarilla, where was only 17.4%. These values are consistent with

those reported by Centritto et al. in olive [15] and by Killi and Haworth in quinoa [2]. These authors concluded that the reduction in stomatal conductance in these species is the principal factor in reducing CO2 diffusion, inducing a decrease in the internal CO2 gas pressure and thus reducing the rate of photosynthesis. In Hueque, the magnitude of the decrease in gs (57.3%) due to salt treatment was proportional to the decrease in net CO2 assimilation (65.1%). However, in Amarilla, reduction in CO2 assimilation (37.7%) was not accompanied by a proportional reduction in gs (17.4%). Thus, assuming a direct relationship between CO2 assimilation and gs, in the tolerant ecotype, only 46% of the reduction in CO2 assimilation caused by salt can be explained by the reduction in stomatal conductance. By contrast, in the case of Hueque, 90% of the reduction in CO2 assimilation can be associated to the gs reduction. This finding suggests that in the tolerant ecotype the CO2 assimilation rate depends less on gs than in the case of the sensitive one. This in turn suggests that, in this ecotype, another diffusional mechanism may be involved in controlling CO2 assimilation, such as mesophyll conductance (gm) for example. This possibility is also supported by Bongi and Loreto [19], who indicated that gm was reduced under saline stress conditions in olive.

Despite the different behaviors of the ecotypes, gs was low in both when treated with NaCl, suggesting that Na+ did not interfere with K+ stomatal signaling or guard cell osmoregulation [61], which is consistent with the exclusion of Na+ from salt-stressed quinoa [62]. This concurs with the data shown in Figure 2, which shows that the K+ content of leaves did not change under saline conditions.

Calculations of mesophyll conductance (Table 7) in control conditions indicate that at 350 µL CO2 L −1 and light saturation, gm was 57 mmol H2O m−2 s −1 in Amarilla, representing 18% of gs, but was 38 mmol H2O m−2 s −1 (< 8% gs) in Hueque. This indicates that in favorable conditions, the relative importance of gm in CO2 diffusion is greater in the tolerant ecotype than in the sensitive one. However, with the application of saline stress, the gm values were significantly reduced in both ecotypes, falling by 49% in Amarilla (57 to 29 mmol m−2 s −1 ) and 47% (38 to 20 mmol m−2 s −1 ) in Hueque (Table 7). Nevertheless, these gm values only account for 11% and 10% of gs, respectively, which shows that under salt stress conditions, in both ecotypes, stomatal conductance exerts much greater control over CO2 assimilation, and gm is of marginal importance.

Table 7 also shows gm values obtained under conditions without stomatal restriction. In both ecotypes and conditions (R and nR), the increase in salinity (0.4 M NaCl) caused a reduction in gm, results similar to those found by Delfine et al. [23] in spinach (*Spinacia oleracea*). However, after eliminating stomatal constraints under non-salt conditions, gm increased in both ecotypes, but the change was more significant in the tolerant plants (61% in Amarilla versus 21% in Hueque). This is consistent with Delfine et al. [23], who demonstrated that gm was not irreversible in olive, as we show here for quinoa [2]. On the other hand, under saline conditions and with stomatal restrictions, both ecotypes had gm values that were similar to those obtained without stomatal restriction. This finding confirms that, in quinoa, gm is not a relevant factor in determining the diffusion of CO2 in salt conditions.

**Table 7.** The effect of salinity on mesophyll conductance (gm) determined at the light saturation point, with and without stomatal restriction.

#### *4.3. Effect of Salinity on Non-Diffusional Parameters*

The effect of salinity on CO2 assimilation, measured by the internal CO2 concentration and the effect of diffusion factors, is shown in Figure 5a,b. In both ecotypes stomatal limitations (R) strongly affected assimilation rates, especially upon the addition of 0.4 M NaCl. However, the ecotypes had different responses: while A increased in Amarilla, with the removal of stomatal constraints (nR), Hueque did not show the same response. This is similar to the observations reported in Table 2, which shows that Hueque has little control over stomatal opening mechanisms, which is apparently an important factor in decreasing the CO2 assimilation rate. However, above 900 µmol CO2, Amarilla had a CO2 assimilation rate in saline conditions similar to that of control plants in unrestricted conditions. Thus, the better response of Amarilla may be due to greater photochemical efficiency and greater RubisCO activity, while in Hueque, difficulties arise as a result of diffusion and lower energy efficiency (Tables 5 and 6).

**Figure 5.** Evolution of CO2 assimilation based on internal CO2 concentration in the leaves of the quinoa ecotypes Amarilla (**a**) and Hueque (**b**) under limiting and non-limiting stomatal conditions. Different letters denote significant differences (*p* ≤ 0.01). Average values were calculated based on 3 leaves taken from 6 plants per treatment (mean ± SE).

The results for CO2 assimilation in both ecotypes under restrictive (R) and nonrestrictive (nR) conditions (Figure 4) indicate that, under restrictive conditions, there is little variation between salt-free and saline treatments in the tolerant ecotype (with conductance less than 300 mmol H2O m−2 s −1 ). This result reaffirms earlier observations in this work: in the tolerant ecotype, the assimilation rate does not appear to be limited by stomatal conductance since Amax is only reduced by 7.2%. This is confirmed by the data of the A/Ci curve under non-restrictive conditions (Figure 3). The values show an increase of 55.7% in Amax without salt, whereas with salt, there is a smaller increase in the assimilation rate of 8.7% (Table 5). This result shows that the main limiting factor in the tolerant ecotype is nondiffusional. This finding, in addition to the resistance of the mesophyll, which contributes to the decrease in A, is consistent with the first conclusions of this study (Table 2).

Table 8 shows some photochemical parameters obtained from A/PFD curves: Quantum Requirement (QR), Light compensation points (LCP) and Rate of dark respiration (DR). The obtained values reveal that the quantum requirement rose with salinity, and the increase was greater in Hueque (168%) than in Amarilla (27%). This demonstrates that salt induced a decrease in the effectiveness of photosynthesis in the sensitive ecotype, which was caused by the increase in the QR and decrease in Jmax, Vcmax, and TPU. These results are similar to those found by Killi and Haworth [2], where salinity resulted in a lower Vcmax of RubisCO and a lower Jmax for the regeneration of RuBP.

**Table 8.** Effect of salinity on the QR, LCP and DR of two quinoa ecotypes.

Light compensation point (LCP) also differs between the two ecotypes. Hueque shows virtually no changes with the addition of salt, which together with decreased mitochondrial respiration, could reflect the absence of mechanisms to tolerate salinity. In contrast, the tolerant increased LCP and the mitochondrial respiration, which reflect that this ecotype increases its energy requirements to activate possible mechanisms that allow it to tolerate this environmental stress. The greater tendency towards photoinhibition and the lower LCP of Hueque, reveals an acclimatization to the lower light intensities typical from the southern part of Chile, compared to the high light intensities found in northern highlands where Amarilla is acclimated. To verify this assertion, several photochemical parameters were determined. The data show that control Amarilla and Hueque plants have statistically equal quantum efficiencies. While there is a tendency to decrease ΦPSII, salt application does not cause significant changes in quantum efficiency (FV/Fm) in either ecotype with respect to its respective control.

Table 5 shows the Jmax values found in Amarilla (120–152 µmol m−2 s −1 ) are very similar to the average of 109 C3 species (134 µmol m−2 s −1 ; [67]) but much higher than those found by Centritto et al. [15] in olive trees (79.5 µmol m−2 s −1 ). Killi and Haworth [2] observed values from 72–152 µmol m−2 s −1 in quinoa, and significant falls in saline conditions. In our study, the salt sensitive ecotype has the lower values (72–115 µmol m−2 s −1 ), demonstrating that in this ecotype exposure to saline stress causes reductions in Jmax, and that the decrease in A could also be associated with the transport of electrons. It is striking that comparing this parameter between 0 M and 0.4 M NaCl with and without stomatal restriction produces a significant reduction in Hueque, but not in Amarilla, indicating that the difficulties in the sensitive ecotype could be due to carboxylation, given by an effect on Jmax, which would indicate a problem on the supply of ATP and NADPH. According to Killi and Haworth [2], the reductions in Vcmax found in salt-stressed quinoa would be compatible with the altered carboxylation of RubisCO [68,69] and/or by the reduced content of RubisCO [70]. Salt stress also reduced the regenerative capacity of RuBP in quinoa indicative of reduced RuBP availability [69] and expression [71,72], particularly in salinity.

In the case of Hueque, the parameters evaluated highlight that in addition to the high incidence of gs on the rate of CO2 assimilation, there is also an effect caused by RubisCO, which is seen by comparing carboxylation efficiencies and Vcmax, between salt and control growth conditions. Similarly, Jmax and the TPU also play a role.

The Vcmax values in Amarilla quinoa under control conditions found here were lower (29–33 µmol m−2 s −1 ) than those reported by Wullschleger [67] (average values of 64 µmol m−2 s −1 for 109 species) and Killi and Haworth [2] (values from 60 to 160 µmol m−2 s −1 in quinoa). However, the decreases in Vcmax observed in plants sensitive to saline stress in our study, as well as the results of Killi and Haworth [2] in quinoa treated with salt, indicate that differences in reported values may be associated with the particular characteristics of the different ecotypes used. The tolerant plants had higher Vcmax values than sensitive ecotypes. In this regard, Manter and Kerrigan [73] indicated that, in woody species, the values ranged between 31.2 and 42.2 µmol m−2 s −1 and were associated with low mesophilic conductance, similar to the two Chilean quinoa ecotypes used in our study. In addition, salinity also induced reductions in Vcmax and Jmax, corroborating the loss of photosynthetic ability. The reductions in Vcmax found in quinoa with salt stress are compatible with poor carboxylation by RubisCO [2,69,74].

The ability to maintain intact membranes and photosystems may enable Amarilla to maintain photosynthesis even in saline conditions. In the cells of photosynthetic organisms, salt stress leads to a decrease in cell volume, induces osmotic stress, and inhibits the photosynthetic electron transfer process [75–77], and in *Synechococcus* cells, PSII and PSI are both inactivated due to changes in the K+/Na+ ratio [76]. In our experiments, salt treatment led to a 10.5-fold reduction in the level of K+ in the roots of the salt-tolerant ecotype (Amarilla) and a 34.6-fold reduction in the more sensitive ecotype (Hueque). The lower supply of this element could mean that PSII is more inactivated in Hueque than in Amarilla, as shown by the CO2 assimilation rates (Table 2), resulting in high Na+ and Cl− fluxes into cells, disrupting ion homeostasis, and leading to the accumulation of reactive oxygen species (ROS) [76,78,79], which is associated with membrane lipid peroxidation [80,81] and can adversely affect photosynthesis [81].

Control of oxidation is achieved through the synthesis of antioxidants such as polyphenols, which are divided into several subgroups, among which are the flavonoids (including flavonol glycosides and isoflavones) [82]. Tocopherol and carotenoids are known to be very important for the scavenging of lipid peroxides in *Synechocystis* 6803 [83]. Flavonol glycosides constitute the most abundant phenolics in quinoa seeds and leaves [84]. Several phenolic acids, including hydroxycinnamic acid and hydrobenzoic acid derivatives, have been identified in quinoa seeds and leaves [85]. Furthermore, the highest activity was observed in red-violet quinoa varieties containing both betacyanins and betaxanthins, with significant capacity/activity also exhibited by the yellow ecotype.  Our results show that both ecotypes significantly increase the GB content as a mechanism to protect photosynthetic activity. Some plant varieties are able of biosynthesize GB, exhibiting a greater tolerance to abiotic stress, and often have enhanced growth and yield relative to varieties that do not accumulate GB [86]. The increased GB accumulation mainly occurs in the chloroplast and is responsible for initiating a network of interactions between the plant's photosynthetic apparatus, its "stress" and "growth" hormones, and reactive oxygen species. The increased abiotic stress tolerance of plants able to accumulate GB appears in large part to be due to the ability of chloroplastproduced GB to protect the photosynthetic apparatus [86]. In particular, the accumulation of GB in the chloroplast in response to a stress signal protects enzymes and lipids that are required to maintain both the flow of electrons through thylakoid membranes and the continued assimilation of CO2 [87,88].

It is probable that the Amarilla ecotype also has other mechanisms for membrane protection, such as the presence of trehalose [89]. Trehalose can act as a structural component when incorporated into glycolipids, thereby stabilizing membranes [50,89,90].

#### **5. Conclusions**

The Calvin cycle requires energy inputs that come from the photochemical phase, and the data show that electron transport is not strongly affected in the tolerant ecotype, which had higher J and Jmax values than those found in the sensitive ecotype. This allows NADPH and ATP to maintain their contributions to the production of triose phosphates (TPU), which, according to our results, do not differ from the treatment without salt. This suggests that the Amarilla ecotype maintains its rate of RuBP under salinity conditions. On the other hand, the Quantum Requirement (QR), light compensation points, and the dark respiration rate are increased, which may be the result of an adaptation of the photochemical apparatus through membrane protection, as seen by the increase in GB.

In the sensitive ecotype (Hueque), the CO2 assimilation rate was affected in both the biochemical and photochemical components; in this respect, Vcmax, TPU, Jmax, J, ΦPSII, and QR dramatically decreased. Light compensation points and the dark respiration rate were not affected.

Another mechanism that was activated in the short term in response to salt treatment in both ecotypes was the exclusion of Na+ towards the leaves and growth centers. Both ecotypes retained Na+ in the roots and restricted its entry to the leaves. This mechanism must be associated with the compartmentalization and blocking of excess Na+ not only in the vacuoles of quinoa leaves (tissue tolerance) but also in those of root cells (ion exclusion), mechanisms that are important for protection in response to ionic toxicity induced by salt at the cellular level.

**Author Contributions:** Conceptualization, J.D.-H. and M.P.; methodology, M.P.; formal analysis, J.D.-H.; investigation, J.D.-H.; resources, J.D.-H.; data curation, J.D.-H.; writing—original draft preparation, J.D.-H. and K.B.R.; writing—review and editing, K.B.R.; visualization, K.B.R.; supervision, M.P.; project administration, J.D.-H. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Doctoral Program in Desert and Arid Agriculture, Universidad Arturo Prat and project FONDEQUIP EQM1900088- ANID. K.B.R. was supported by grant PAI 79170093.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in this article.

**Acknowledgments:** We acknowledge Michael Hanford from Universidad of Chile, for providing the translation and discussion support. We kindly thank Alejandro Riquelme of Centro de Estudios Avanzados en Fruticultura. We also appreciate the valuable contributions of the reviewers of this manuscript, they have been very useful to improve its quality.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **Quinoa Productivity and Stability Evaluation through Varietal and Environmental Interaction**

**Elhadji Thiam \* , Asmaa Allaoui and Ouafae Benlhabib \***

Département de Production, Protection et Biotechnologies Végétales, Institut Agronomique et Vétérinaire Hassan II, Rabat B.P 6202, Morocco<EMAIL_ADDRESS>
**\*** Correspondence<EMAIL_ADDRESS>(E.T<EMAIL_ADDRESS>(O.B.)

**Abstract:** *Chenopodium quinoa* is a pseudocereal species identified as a potential crop to mitigate world food security. It has the ability to adapt to diverse agro-ecosystems ranging from sea level to over 4000 masl. Its cultivation in Morocco began in 1999, as it is tolerance to drought, salinity, and frost, and it can grow on marginal soils. It has exceptional nutritional value, as it is rich in proteins, essential amino acids, mineral nutrients, trace elements, vitamins, and unsaturated fatty acids. The present study aims to evaluate the adaptation of 14 quinoa varieties and lines from four different origins through fourteen agro-morphological characters. The experimental trials were conducted at five contrasted agro-climatic sites across the central part of Morocco. The data analysis showed high variability among the tested varieties and between sites for all assessed traits. The Meknes (foot-hill plain) site was the most productive; its grain yield reached 78.6 qx/ha. At the Rabat (coastal land) and Berrechid (continental plain) sites, grain production was respectively 56.4 and 45.9 qx/ha. The SW2 Moroccan line produced the highest grain yield that reached 78.3 qx/ha across sites. The Danish variety Titicaca presented the best harvest index (HI = 0.69) as well as the best "thousand kernel weight" (TGW = 3.4 g). As the mildew infection evaluation, the Vikinga and Titicaca varieties ranked the most sensitive to *Peronospora farinosa*. The germination rates of the harvested seeds were prejudiced by the sites' high temperatures and were low in Tinejdad (oases site) and El Kbab (mountain plateau). The best average germination rate across sites was that of the Puno variety (84.5%). According to the Additive Main effects and Multiplicative Interaction analysis (AMMI), 23% of the grain yield variability is due to the genotype, while 32% is due to the site by the variety interaction contribution to the production variability. AMMI analysis also ranked the varieties according to their productivity and stability value. Accordingly, two varieties that have yielded above the overall average (42.7 qx/ha) are considered stable; those are Riobamba and W11, which is a local selected line. Titicaca, ILLPA, Atlas cultivars and the SW2 local line presented the best grain yield in one of the experimental sites but performed not as well on the others.

**Keywords:** quinoa; agro-morphological traits; genotype × environment interaction; AMMI; yield; stability

### **1. Introduction**

Global warming in recent decades reached a critical level exposing some populations at risk, particularly in terms of the food supply. Food security is also threatened by population growth and rainfall decrease. Grain crops statistics predict a yield decrease between 3.1 and 7.4% for every 1 ◦C temperature increase unless breeders create new varieties for warmer environments [1]. Thus, there is a great challenge to overcome by exploring and expanding new crops that have a better adaptation to the harsh climates.

Quinoa is a pseudocereal native to the Andean highland of the South. It gained worldwide attention because of its tolerance to abiotic stresses [2] such as drought, heat, frost, and salinity [3]. It expends progressively in different parts of the world; it is growing in more than 95 countries [4]. The high resistance to the abiotic stresses in quinoa results from

**Citation:** Thiam, E.; Allaoui, A.; Benlhabib, O. Quinoa Productivity and Stability Evaluation through Varietal and Environmental Interaction. *Plants* **2021**, *10*, 714. https://doi.org/10.3390/ plants10040714

Academic Editor: Cataldo Pulvento Received: 22 December 2020 Accepted: 26 January 2021 Published: 7 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

its vast genetic diversity and harsh environmental conditions prevailing in its zone of origin [5]. It sustains five ecotypes based on their adaptation ability to specific agro-ecological environments: sea level from Southern Chile, Andean valleys, Yungas from the subtropical rainforest, Salar from the Lake Titicaca highland in Southern Bolivia, and Altiplano from the Andean high plateaus (ca. 4000 m) [6].

Quinoa is also known for its high nutritional value; its seeds are exceptionally rich in proteins and essential amino acids. Temperature and photoperiod are the two main factors that affect significantly quinoa production [7]. Quinoa yield is generally insignificant in regions where the temperatures go higher than 32 ◦C [4,8]. According to Bertero et al., [9], the genotype's performance depends largely on the cultivar genetic makeup, the environment, and their interaction. In general, quinoa shows high genotype × environment interaction (GEI) under multi-environments trials (MET). Such significant GEI affects breeding efficiency strength [10]. Understanding and assessing genotype and GEI effects are required to enhance the selection efficiency in crop breeding [11]. Furthermore, MET has the advantage of helping identify genotypes that have large adaptations or the ones that adjust to a specific environment [12].

Several statistical analyses are used to evaluate the yield performance of genotypes across the environments such as the regression coefficient of the GEI effects on the environmental [13], the coefficient of variation (CV) [14], the non-parametric stability [15], the harmonic mean of the genotype relative performance value [16], and the AMMI—Additive Main effects and Multiplicative Interaction model [17]. There are different crops that benefit from these approaches, including corn [18], rice [19], bread wheat [20], maize [21], and quinoa [22,23]. AMMI analysis allowed us to analyze the GEI effects in multi-location trials. This method has the advantage of generating outputs that can help easily diagnose the varietal adaptability and yield stability [24].

Quinoa was selected among half a dozen species as elite to enhance crop diversity of the cropping systems in Morocco. The quinoa introduction's main objective was to improve the food security of mountain sustenance farmers in climate change and overgrazing occurrence. Since then, quinoa became the focus of several studies, germplasm productivity, and adaptation evaluation, screening for diseases and abiotic stresses tolerance, wateruse efficiency and drought tolerance, genetic and molecular characterization, etc. [25–27]. Consequently, quinoa cultivation has expanded across several regions and environments in Morocco; hence, there is a real need to provide well-adapted cultivars to farmers and producers for different regions. Therefore, the main objectives of the present study are to evaluate the productivity and stability of 14 quinoa genotypes (11 varieties and three Moroccan lines) under field conditions at five contrasting environments and to interpret the genotypes adaptation through the tested cropping conditions and through 14 evaluation descriptors.

#### **2. Material and Methods**

We conducted the experiments at five sites during the 2017–2018 cropping seasons. Table 1 summarizes the specifications of the experimental locations, the quinoa genotypes under evaluation, the type of environmental climates (oceanic to semi-desert), and altitude ranges (low to high) of the sites. The field experiment design was a randomized complete block with four replications. The elementary plot size varies according to the available land space for the trial. Six rows represented the elementary plots in Rabat and El Kbab, four rows represented the elementary plots in Berrechid and Tinejdad, and three rows represented the elementary plots in Meknes. The row length was respectively 1.6, 2.0, or 2.5 m with a 0.2, 0.5, or 0.6 m's inter-row spacing. All the cropping tasks (planting, weeding, harvesting, and cleaning seeds) were manual. The fourteen genotypes tested are from different origins: Titicaca, Puno, Vikinga (Quinoa Quality, Regstrup, Denmark), Atlas, Pasto, Riobamba (Wageningen University, Wageningen, The Netherland), ILLPA, Amarilla de Marangani, Altiplano INIA 431, Salcedo INIA, Passankalla INIA 415 (Universidad Nacional Agraria de La Molina, Lima, Peru), and SW2, W11, and W16 (IAV Hassan II,

Rabat, Morocco). We sowed all the genotypes at a rate of 0.66 g/m in February during the cropping season expect El Kbab, which was sowed in April since the snow.

**Table 1.** Location and description of the experiment agro-climatic sites.

The mildew (*Peronospora farinosa*) assessment took place under the natural infection conditions at the vegetative and flowering plant growth stages. We first collected three leaves from three stem levels, the third-bottom, the middle, and the apical per genotype and block, and scored them according to the leaf area surface covered by the fungus [28].

At harvest, we scored the agro-morphological traits. We pulled up separately four rooted plants per elementary plot. Subsequently, we assessed seven IBPGR traits (descriptors International Board for Plant Genetic Resources) that are good in discriminating traits between genotypes or well correlated to the yield in our former screening tests [29,30]. These gathered plant height, stem diameter, root length, panicle length and width, and yield components.

Grain and dry matter yield per plant measurements took place after threshing and drying the seeds at 35 ◦C and brushwood at 70 ◦C immediately. Three samples of one thousand kernels that were weighted were obtained by counting the seeds manually. For the grain diameter, thirty seeds per genotype and per block were measured using a binocular magnifying glass with mm graph paper. Yield and dry matter per hectare were estimated by through the grain yield per plant, plant density, and elementary plot area. Harvest index was calculated as defined below:

HI = (GW/(BW + GW)) × 100)

GW: Grain weight

BW: Brushwood weight

For the germination test, we held three samples of 20 kernels per treatment (genotype × site), washed them in 12% sodium hypochlorite solution, and then placed them at room temperature (20.2 ◦C) in sterilized Petri dishes. Daily recording germinating rate data recording was for ten days.

The database went first through the descriptive analyses and ANOVA test to assess the variability between the genotypes within and between sites. Genotypes homogeneous groups were according Newman–Keuls posthoc test. The Principal Component Analysis [31] and the Additive Main effects and Multiplicative Interaction (AMMI) model [17] performed the genotype stability and productivity. The version 3.5.1 of R software version 3.5.1 is the one used in the analyses. The AMMI model combines both the ANOVA and the PCA. The principal additive effects divide the effect of the GEI into interaction principal component axes (IPCA) provided by the PCA. The calculation of the AMMI Stability Value (ASV) is according to Purchase [32], where Sum of SquareIPCA1 Sum of SquareIPCA2 is the weight given to the IPCA1 value that is equal to the IPCA1 sum of squares divided by the IPCA2 sum of squares. Genotypes with small values of IPCA1, IPCA2, and ASV are more stable across environments. It also means that the genotypes with the ASV close to zero are the most stable ones [32].

#### **3. Results**

Analysis of variance showed a high degree of morphologic and agronomical variability among the genotypes. For all the investigated traits, a significant effect exists except for

the germination rate and the seed size in Rabat and Tinejdad (Table 2). The plant height fluctuates between sites from 34.85 to 127.35 cm at El Kbab and Tinejdad, respectively. The ANOVA reveals the tall size of the Peruvian varieties; Amarilla de Marangani reached 2.30 m at Rabat. Pasto and Vikinga cultivars produced the smallest size plants. At the Meknes site, the Moroccan lines were taller than some Peruvian varieties. Intermediate sizes over the sites were mainly those of Puno and Titicaca, which are the Danish cultivars.

**Table 2.** Agro-morphological traits variance analysis of the quinoa genotypes at the five experiment sites.

\*\*\*, \*\*, \*: significant at 0.1%, 1%, 5% respectively; NS = Non-significant; Gen = Genotype.

Plant dry matter varied between sites, from an average of 2.31 to 53.02 g in respectively El Kbab and Tinejdad; while plant grain average yield ranged from 0.81 to 14.22 g at El Kbab and Meknes, respectively (Table 2). Therefore, plants produced more biomass at Tinejdad and less at El Kbab and more seeds in Meknes than El Kbab. Furthermore, Atlas had the highest grain yield per plant in Meknes, averaging 50.75 g; it also had a good performance in Tinejdad and Berrechid, where its plant grain yields reached 32.17 and 21.38 g, respectively. In Berrechid, Titicaca ranked first with a plant grain yield of 25.19 g. In Rabat, W11 had the best grain yield per plant of 33.06 g, which was followed by both other lines, W16 and SW2 (27.63 and 25.63 g). The Peruvian varieties were the least and even did not produce any seeds in Tinejdad.

The harvest index fluctuated significantly between sites from 0.22 to 0.42. The highest harvest index of 0.69 belongs to Titicaca at Meknes. Puno presents the best harvest indexes of 0.64 and 0.65 at Rabat and Berrechid, respectively (Table 2).

The powdery mildew (*Peronospora farinosa*) sensibility evaluation took place in Rabat and Meknes sites. The reaction to the disease was more pronounced at Rabat (26.84%) than Meknes (17.59%). Four varieties were the most susceptible, Vikinga with 45.50 and 58.50% respectively at Meknes and Rabat, Titicaca with 51.75 and 34.00%, SW2 with 37.25 and 40.50%, and W16 with 43.00 and 33.25%. Pasto and Puno were the most tolerant with 0.50 and 13.25%, and 8.25 and 12.50%, respectively, at Meknes and Rabat (Table 2).

After their harvest and conditioning, collected seeds were placed in Petri dishes for germination to test their viability. The site effect was significant on the germination rate. Thus, the data reveal Meknes and Berrechid as the best sites for seed production; their germination rates exceeded 93%. Rabat recorded a germination rate close to 80% (Table 2). El Kbab and Tinejdad germination rates were below 30%. Puno had the best germination percentage across sites (84.5%) with 100% at Meknes and 50% at Tinejdad.

To assess the varietal variation, principal component analysis (PCA) was performed by considering simultaneously all the variables. The first two principal components explain 72% of the total variability between the 14 genotypes under study. Plant height, stem diameter, dry matter per plant, and harvest index were the major contributors to PC1. Thus, PC1 is considered as a biomass production indicator. The second principal component (PC2) was more related to grain yield per plant, root weight, and plant density, which partially explains the seed production ability per surface unit. The PC3 contributes 10.24% to the total variance; root length, panicle width, grain yield, and plant density present the largest coefficients. The PC4 axis links mainly to the mildew sensitivity (52.41%) and the thousand kernel weight (19.34%). The three first components explained 85.49% of the variability. Thus, these axes were useful to identify homogeneous genotype clusters.

According to the Pearson correlations matrix, the variables that contribute more to the biomass are plant height, stem diameter, root and stem weight, panicle length and width, and plant dry matter. They all are positively correlated to the dry matter and negatively correlated to the harvest index and thousand kernel weight. Genotypes with high growth vigor did not produce much seed; that was the case of the Peruvian cultivars. In Rabat, Passankalla, Salcedo, ILLPA, and Altiplano, dry matter ranged between 14.6 and 19.3 g/plant, while in the Danish cultivars, it varied from 3.9 to 5.2 g. At the same time, the Danish genotypes harvest index (0.62 to 0.64) was higher than the Peruvian ones (0.04 to 0.17).

Grain yield, grain yield per plant, harvest index, and thousand kernel weight are the main variables that are positively correlated. Since plant grain yield correlates negatively to the dry matter, cultivars with moderate growth vigor and a short growth cycle seem more productive under the experimental conditions if we consider the February sowing date. Susceptibility to mildew does not correlate with the other traits; rather, it depends on the environment's climate, mainly temperature and humidity. A strong correlation exists between the plant height and the stem diameter (0.92).

The PCA biplot gathered the 14 genotypes into four clusters (Figure 1). Amarilla de Marangani forms Cluster I (blue) and has high biomass components (plant height, stem diameter, panicle length, and dry matter) as well as a harvest index close to zero. Cluster II (red) includes SW2, W11, W16, and Atlas that have in common relatively low plant density and high grain yield: 63.7 qx/ha on average over the five sites. Cluster III (green) gathers only European cultivars, Titicaca, Puno, Vikinga, Pasto, and Riobamba. This group had relatively low biomass, 7.23 g/plant on average over the five sites. Their cumulative dry matter/plant (36.08 g) does not surpass that of Altiplano (43.15 g). In addition, their harvest index (HI = 0.5) is much higher compared to the other varieties, as is their grain yield average across the sites (49.0 qx/ha). Titicaca seems to have additional special traits than the other cultivars; it has higher yield (72.6 qx/ha), harvest index, and thousand kernel weight, but it is more susceptible to mildew. Cluster IV (yellow) holds Altiplano, Passankalla, Salcedo, and ILLPA Peruvian cultivars; they produced few seeds, an average of 24.5 qx/ha over the five sites; their harvest index is exceedingly low at 0.09 on average, but they are more tolerant to mildew.

In multi-location trials, the selection for grain yield stability involves an estimation of the interaction between the genotypes and the environments (GEI), which is sometimes highly significant. The AMMI analysis on yield facilitates the identification of the most productive and stable genotypes. The analysis of variance (ANOVA) associated with the AMMI model revealed the highly significant sites, genotypes, and interaction effects (Table 3). The environment explains the largest grain yield variability (45.17%) followed by the interaction (31.77%); this indicates the great influence of the selected environments on the cultivars' behavior.

**Figure 1.** Biplot principal component 1 (PC1) × principal component 2 (PC2) of the 14 quinoa genotypes derived from the average linkage cluster analysis.

\*\*\*, \*: significant at 0.1%, 5% respectively.

Furthermore, the first interaction component IPCA1 generated by the model explains 53.4% of the total yield variation, while the second axis justifies an additional 25.4%. Therefore, the IPCA1 vs. grain yield biplot fully describes the quinoa genotypes' behavior as confirmed through its significance (*p*-value = 0.0001).

Figure 2 illustrates the genotypes grain yield across the five sites. Meknes is the most productive site (78.6 qx/ha), while the lowest yielding site is El Kbab (9.5 qx/ha). Meknes, a propitious pluvial zone with an average annual rainfall of 576 mm/year, mean temperature of 19–22 ◦C in May–June, and relative humidity of 60–78%, gave much more auspicious growing conditions. The coastal site of Rabat presented a quite high yield of 56.4 qx/ha. The growing conditions of the oasis site of Tinejdad affected significantly the quinoa genotypes' performance, especially Peruvian cultivars. As a result of the late sowing at El Kbab, the quinoas' reproduction-phase matches the long photoperiod and high-temperature period (37.2–40 ◦C), while almost no irrigation is applied. El Kbab conditions impact the 14 quinoa genotypes and more the Peruvian cultivars.

Figure 2 reveals Meknes and Rabat as the most interactive sites with the first IPCA, since they reached the highest IPCA1 scores of 6.88 and −8.54, respectively.  More than 50% of the genotypes produced over-mean yields; those are W16, Pasto, Riobamba, W11, Puno, Titicaca, Atlas, and SW2. According to Purchase [32], the closer

the genotype score is to the center of the IPCA1 by IPCA2 biplot, the more stable is the genotype, and the opposite is true. The highest yield of 78.3 qx/ha was that of SW2. This local accession reveals low stability; it is placed far from the IPCA1–IPCA2 biplot center (Figure 3). Atlas and Titicaca have significant yields of respectively 75.6 and 72.6 qx/ha and are also unstable. The lowest yields were those of Amarilla de Marangani (0 qx/ha), Passankalla (9.2 qx/ha), and Viking (18.6 qx/ha) (Figure 2). Nevertheless, their stability scores were valuable, of 2.46, 1.88, and 3.09, respectively.

**Figure 2.** Biplot of the first principal component of the interaction (IPCA1) and the grain yield of the 14 quinoa genotypes.

**Figure 3.** Biplot between the first component (IPCA1) and the second component (IPCA2) of the genotype × environment interaction (GEI) interaction for the grain yield of the 14 quinoa genotypes.

Genotypes projection, aside from the environmental vectors, indicated specific interactions. The Figure 3 biplot displays varietal adaptation degree to a specific site. Titicaca is better suited to Berrechid (143.2 qx/ha); ILLPA interacts positively with Meknes envi-

ronment (125.4 qx/ha), as Atlas (143.9 qx/h) and SW2 (160.4 qx/ha) interact with Rabat, where they recorded their best grain yields. W11 (56.0 qx/ha) and Riobamba (50.7 qx/ha) genotypes, with a yield over the total mean, presented good yield stability.

In summary, the AMMI analysis provides the genotypes' productivity and the AMMI Stability Values (ASV), as shown in Figure 4. Both parameters allowed gathering the cultivars into three groups.

The first group includes five cultivars, Altiplano, Riobamba, Passankalla, W11, and Amarilla; these are most stable with ASV scores ranging from 1.40 to 2.46. Two of them, Riobamba and W11, are above the average yield (Figure 4).

The second group gathers Vikinga, Puno, W16, and Pasto genotypes; their ASV stability scores range from 3.09 to 4.75; three among them, Puno, W16, and Pasto, overpass the average yield of 42.7 qx/ha.

The third group gathers Titicaca, Salcedo, ILLPA, Atlas, and SW2; their stability scores are sited between 7.75 and 14.78 ASV values. Atlas and SW2 have the highest productivity of 75.7 and 78.3 qx/ha, respectively. Both accessions were ranked unstable according to their ASV scores (12.1 and 14.8, respectively).

**Figure 4.** Grain yield and evolution of the AMMI stability values (ASV) of the 14 quinoa genotypes.

#### **4. Discussion**

Quinoa is an alternative to global stable food products, such as rice and wheat; it is superior in terms of nutritional value and abiotic stress tolerance [33]. Recently, quinoa cultivars have been widely tested outside the species center of origin in Latin America [4]. Quinoa has great morphological, agronomic, and physiological variability, predisposing it to wide environmental adaptation. This great intraspecific diversity connects to the quinoa five ecotypes of different origins and its allotetraploid status [6]. Hence, there is a real need to consider the effect of environmental factors such as temperature and photoperiod to optimize the introduction of quinoa in new regions [34]. On the other hand, when we select genotypes only for their predicted genotypic productivity, it does not guarantee that they will maintain their performance when cultivated under other environments [35]. Thus, it is difficult to identify consistently superior genotypes across environments when the G × E interaction is highly significant [20]. Therefore, this present study seeks to assess the stability of the grain yield of 14 quinoa genotypes across five agro-ecological zones in Morocco.

The data analyses reveal an important agro-morphological diversity between the genotypes. Peruvian cultivars plants have a large size and tend to produce much biomass. In general, their height is within the range reported by Jacobsen and Stolen [36]. According to these authors, quinoa plant size varies between 0.5 and 3 m with an average of 1 to 1.5 m. Amarilla de Marangani gave the highest plant height (2.30 m) as expected; it belongs to the Inter-Andean valleys' ecotype [37]. Its origin latitudinal score is 13◦3 S. According to Tapia et al. [6], this ecotype grows between 2000 and 4000 m, and it has a high size and late flowering. Generally, plant size is much more variable and depends on the plant branching habit and the inflorescence shape, amaranthiform, or glomeriform [6]. The growth cycle duration explains largely plant size differences between the two groups. European varieties were ready for harvest at least 4 weeks before the Peruvian accessions. Peruvian varieties were still at the flowering stage, even Amarilla de Marangani was at the late vegetative phase when the European cultivars reached their physiological maturity. Amarilla de Marangani is the latest and the tallest among all the varieties.

The growth cycle length seems to have a direct relationship with the photoperiod. According to previous studies conducted by Christiansen et al. [38] and Bertero et al. [7], quinoa is a facultative short-day species rather than qualitative, indicating that regardless of the cultivar adaptation, quinoa can flower under a wide range of day lengths. Thus, genotypes are classified as a short day (12.25 h), long day (14 h), or insensitive, depending on their sensibility to the photoperiod. Bertero [34] reported that long-cycle quinoa cultivars are generally more photoperiod sensitive compared to short-cycle ones. Furthermore, the duration of the phenological phases (emergence to floral initiation, floral initiation to the first anthesis, and first anthesis to physiological maturity) depend on the genotype sensitivity to the photoperiod. Christiansen et al. [38] reveal a significant varietal effect on the leaf and flower nodes initiation when quinoa plants are grown at a long day compared to short-day photoperiods, with Real being the most pronounced reactive cultivar. As Real is a traditional large-seed variety from the Bolivian southern Altiplano, it is late-maturing when compared to the sea level ecotype such as the Danish varieties. Our findings match with these statements. Peruvian late cultivars produce more vegetative organs at the detriment of the seeds. In addition, Bendevis [39], while testing two quinoa cultivars, reported similar adjustments in resource allocation between plants growing under short and long-day photoperiods. They are also in agreement with Dorais and others' [40] conclusions on tomato and sweet pepper crops, stating that an extended photoperiod results in further shoot development and carbohydrate accumulation in leaves over fruit development.

In contrast, when quinoa grows under long photoperiods and high temperatures, it tends to shorten its development cycle. Therefore, plants might reach their physiological maturity even before they complete their development. This should be the case in El Kbab where the plants' size did not exceed 54 cm. It is important to remember that the El Kbab trial was installed 7 weeks later because of the snow, and there was no irrigation stream when the temperature and day length increased. These results confirm the Atkinson and Porter [41] scheme stating that when the growing environment is at risk of high temperature or water stress, plants would hasten their development and form their seeds. Bertero [34] reported that late in the season in the Andes, when water deficit occurs, photoperiodsensitive cultivars are faster in their growth and seed filling, allowing plants to mature before water or temperature becomes restrictive.

Water supplies may also influence plant growth to some extent. All the genotypes were relatively more vigorous in Tinejdad despite the oases type of climate (average temperature 23 ◦C, humidity 33.83%). Indeed, the Tinejdad trail received regular irrigation to meet the plant and the atmosphere demand, which contributed to the expansion of the plant size. In fact, excessive irrigation at the seedling stage improves the plant vigor but does not enhance the grain yield [42].

The origin of the variety appears to impact considerably quinoa seed production. Most Peruvian cultivars produced little or no seeds despite their well-established panicles. They were very late when compared to the other genotypes. Amarilla de Marangani did not

produce any seeds across the five experiment sites. Several tested genotypes are day-length sensitive and classified as short day. Quinoas are also sensitive to temperature; they require between 15 and 20 ◦C for optimal growth. Thus, the growing cycle duration depends on the combination of both factors [43]. Bertero [43] reported that far from the equator, short-day plants become more sensitive to temperature and less sensitive to photoperiod. In 2017, Noulas [44] reported that several Latin American cultivars gave no seeds under the central Greece arid environment. Research conducted also in the US stated that temperatures exceeding 35 ◦C are likely to cause pollen sterility [45]. These facts well justify our current finding on the Peruvian quinoa in the Tinejdad oases. In addition to the high temperatures, a summer-long photoperiod and low air humidity contribute to the seed establishment hindering. On the other hand, the same Peruvian cultivars behave differently at Meknes, where average temperatures are quite mild (19.3 ◦C). In terms of comparison, ILLPA seed production per plant at Meknes (11.19 g) over-passed Titicaca (8.81 g), Vikinga (6.44 g), Pasto (8.12 g), and Riobamba (6.25 g).

The two most important determinant factors to grain yield are biomass accumulation and its partitioning into the storage organ, which is evaluated through the harvest index. Puno had the best harvest indexes of 0.64 and 0.65 at Rabat and Berrechid, respectively. As for Meknes, the highest harvest index of 0.69 was Titicaca's. These well-known quinoa cultivars by farmers recorded the best yield and harvest index at previous experiments. In 2010–2011, Titicaca had the highest harvest index of 0.47 during a trial carried out in the semi-arid region of Bouchane. It is quite low compared to the 2018 exceptional rainy cropping season. Indeed, the 2018 season was particularly favorable for seed production, especially in Meknes. Overall, the varietal harvest indexes ranked between 0.3 and 0.69 for respectively W11 in Tinejdad and Titicaca in Meknes, except for the Peruvian varieties, which experienced problems seed-setting due to heat. The principal component analysis also disclosed the European cultivars group for their high harvest index. Jacobsen [33] reported that quinoa's perfect variety for seed production in northern Europe is the one that matures early and homogeneously. A growing period shorter than 150 days is advantageous. Quinoa should also have a consistently high seed yield, and it should be short and non-branching to facilitate mechanical harvesting. They used primarily Chilean cultivars that are supposed to be the least sensitive or insensitive to photoperiod for seed filling to achieve these goals [34]. The harvest index represents photosynthetic and translocation seed production capacity. It is also sensitive to agronomic practices and environmental conditions [46]. Rojas et al. [47] reported variation in the quinoa harvest index ranging from 0.06 to 0.87.

Thousand kernel weight (TKW) differences were significant between varieties at Rabat and Berrechid. The TKW means fluctuated from 1.17 g for Salcedo in Berrechid and 3.42 g for Titicaca in Berrechid and W11 in Rabat. The favorable pluvial region of Meknes did not discriminate the varieties through their TKW, as 2018 was an exceptional rainy season, and all the cultivars had reached their best seed weight performance.

Recently, multi-location experiments (MTE) became valuable to assess quinoa genotype adaptation in new regions [9,22,23]. According to Gadisa et al. [20], it is difficult to identify consistently superior genotypes across environments when genotype × environment interactions (GEI) are highly significant. In our present case, the GEI effect explains 31.77% of the total grain yield variation compared to the 23.05% genotype effect. As expected through the AMMI analysis, the environment gathers the largest grain yield variability (45.17%), indicating that grain yield depends highly on the environment. These findings are in line with previous conclusions of other research on quinoa, maize, and bread wheat [22].

AMMI Stability Values (ASVs) of the GEI ranks the studied genotypes into three clusters: stable, moderately stable, and unstable (Figure 4). Among the stable genotypes, two (Riobamba and W11) produced more than the overall mean yield of 42.7 t/ha. The moderate stability group gathers three genotypes that exceed the overall average yield: Puno (56.6 qx/ha), W16 (44.7 qx/ha), and Pasto (46.8 qx/ha). Within the unstable group, At-

las and SW2 genotypes had the highest grain yield of 75.6 and 78.3 qx/ha, respectively. Thus, the grain yield of highly productive genotypes is more likely to be influenced by the growing conditions in different environments. Then, AMMI analysis allowed identifying genotype adaption to a specific site. Titicaca suits better to the Berrechid site, while ILLPA is more productive in Meknes. Atlas and SW2 interact positively with Rabat. According to Mohammadi et al. [48], stability should not be the only parameter for selection; usually, stable genotypes would not necessarily reach the highest yield across the experimental stations. Some authors use the Yield Stability Index as the main selection criterion to rank their germplasm [49,50]. In our case, we used the synthetic graph in Figure 4 to interpret both yield and stability criteria.

For cultivar performance evaluation, we calculated grain yield according to its components. Thus, the estimated yields fit within the range 0.00 qx/ha as a minimum for the Amarilla de Marangani cultivar and 78.3 qx/ha as maximum for the SW2 local advanced line with an overall yield of 42.7 qx/ha. Compared to other countries that have recently introduced quinoa cultivation, grain yields are relatively variable probably because of the large diversity of the cultivars, their origins, and the contrasting environments tested. Dost [51] reported 38.7 qx/ha as the highest yield recorded in Egypt, while in Germany, Präger et al. [52] reached a maximum grain yield of 24.3 qx/ha for the Zeno cultivar and Titicaca produced less in the same experiment. Recently, quinoa grain yield in Egypt revealed a maximum of 30.8 qx/ha under irrigation with the Argentinian Regalona cultivar [53]. The relatively high overall yield of 42.7 qx/ha we obtained through our investigation could have three explanations: the performance of selected cultivars used, the intensive care taken to conduct the trials, and the sampling method based on an individual plant. Moreover, Dost [51] reported a maximum yield of 75.0 qx/ha in Lebanon. Another study investigating the genetic variability of 27 lines originating from different parts of the Andean region and South America conducted in the northern part of India had grain yields varying widely between 4.7 and 60.1 qx/ha [30].

#### **5. Conclusions**

The present study allowed detecting the great variability among the 14 quinoa genotypes through the morphological and agronomic traits. It also showed that grain yield is more influenced by the environment and the genotype–environment interaction, and it was able to prove the significance and challenge of evaluating the varietal grain yield stability across the different contrasting sites. According to AMMI analysis, Meknes was the most productive site, followed by Rabat and Berrechid. Riobamba cultivar and W11 local advanced line showed broad adaptation with a grain yield above the overall yield. The Titicaca, ILLPA, Atlas, and SW2 genotypes fitted better in a particular environment. Some Peruvian long-grow cycle cultivars performed less in terms of grain yield because of their sensibility to the photoperiod and high temperatures. Other investigation studies should be held at different sowing dates and agro-climatic zones to be able to select for quinoa growers and farmers adapted cultivars to their local environment and to cover their needs in seeds.

**Author Contributions:** Conceptualization, O.B.; methodology, O.B.; software, E.T.; validation, O.B., and E.T.; formal analysis, E.T.; investigation, E.T. and O.B.; resources, O.B.; data curation, E.T., and A.A.; writing—original draft preparation, E.T.; writing—review and editing, O.B.; visualization, E.T. and O.B.; supervision, O.B.; project administration, O.B.; funding acquisition, O.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded jointly by the FAO, grant number TCP/MOR/3602/C1 and the IAV quinoa program grant number 2129.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Dataset analyzed in this study is publicly available and can be found here: (https://mega.nz/file/iVc00RxA#Rif61fwxFncPLcNoxz-ciO5sJPxq9cojUlA8dZOX7oE).

**Acknowledgments:** The authors would like to acknowledge the FAO for the financial support provided for conducting the field trials under the Project TCP/MOR/3602/C1-Quinoa «Quinoa cultivation Promotion in Morocco».

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Review* **Seed Dormancy and Preharvest Sprouting in Quinoa (***Chenopodium quinoa* **Willd)**

**Emma M. McGinty 1 , Kevin M. Murphy 2 and Amber L. Hauvermale 2,\***

**Abstract:** Quinoa (*Chenopodium quinoa* Willd.) is a culturally significant staple food source that has been grown for thousands of years in South America. Due to its natural drought and salinity tolerance, quinoa has emerged as an agronomically important crop for production in marginal soils, in highly variable climates, and as part of diverse crop rotations. Primary areas of quinoa research have focused on improving resistance to abiotic stresses and disease, improving yields, and increasing nutrition. However, an evolving issue impacting quinoa seed end-use quality is preharvest sprouting (PHS), which is when seeds with little to no dormancy experience a rain event prior to harvest and sprout on the panicle. Far less is understood about the mechanisms that regulate quinoa seed dormancy and seed viability. This review will cover topics including seed dormancy, orthodox and unorthodox dormancy programs, desiccation sensitivity, environmental and hormonal mechanisms that regulate seed dormancy, and breeding and non-breeding strategies for enhancing resistance to PHS in quinoa.

**Keywords:** abscisic acid; desiccation sensitivity; gibberellin; hormone signaling; precocious germination; seed morphology

### **1. Introduction to Quinoa, Cultivars, Breeding Issues, and Preharvest Sprouting**

Quinoa (*Chenopodium quinoa* Willd.) is a pseudocereal originating from the Andes Mountain Range in South America and is a culturally significant staple food source that has been grown for thousands of years [1,2]. Due to its natural drought and salinity tolerance, quinoa has emerged as a favorable crop for production in marginal soils and in highly variable climates [3]). Quinoa's nutrient dense grain is also ideal for supporting human health in diverse global communities, and for this reason, it has agronomic significance in global economies.

There are five distinct quinoa ecotypes that originated from five different localities in South America. The original localities are (1) the valley habitat ranging across Colombia, Ecuador, Peru, and Bolivia, and the ecotype from this region is often tolerant to downy mildew; (2) the altiplano habitat which is near Titicaca Lake on the border of Bolivia and Peru, and the ecotype from this region is tolerant of marginal environments and frost; (3) the salares habitat, ranging across the salt flats of Bolivia and Chile, and the ecotype from this region is tolerant to high salinity; (4) the sea-level habitat, ranging from low-altitude areas of southern and central Chile, and the ecotype from this region is high yielding; (5) the subtropical or yungas habitat, ranging from the low-altitude humid valleys of Bolivia, and this ecotype is known for its late-flowering genotypes [1,3–5]. Until recently, there was limited pedigree information for quinoa, making it more difficult to identify the first quinoa ecotypes cultivated to produce today's modern varieties. However, phenotypic and genotypic clues indicate that modern varieties have little to no seed dormancy, are xerophobic (meaning seeds display desiccation intolerance), and adult plants are salt and

**Citation:** McGinty, E.M.; Murphy, K.M.; Hauvermale, A.L. Seed Dormancy and Preharvest Sprouting in Quinoa (*Chenopodium quinoa* Willd). *Plants* **2021**, *10*, 458. https://doi.org/ 10.3390/plants10030458

Academic Editor: Cataldo Pulvento

Received: 24 December 2020 Accepted: 24 February 2021 Published: 28 February 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

drought tolerant. These phenotypes are likely the result, at least in part, of adaptation to the original environments in which the first varieties were cultivated [1,3]. With the recent sequencing of the quinoa genome, it is expected that genetic tools will help to accelerate major breeding efforts for quinoa improvement focused on abiotic stress resistance, yield, and end-use quality [6].

From a production perspective, traits associated with enhanced plant plasticity that help to mitigate abiotic stress are beneficial for integrating quinoa into diverse cropping systems. For this reason, many research efforts have focused on understanding the genetic mechanisms that regulate abiotic stress responses, leading to drought or salt tolerance in adult quinoa plants [3,7–10]. Additionally, from a management perspective, the weak seed dormancy or in some cases, the absence of dormancy observed in quinoa is a desirable characteristic for integration into diverse crop rotations. This is because seeds that germinate readily are less likely to establish stable volunteer seed banks, requiring little to minimal input for management [11]. However, lack of seed dormancy has led to issues with reduced yields due to premature germination prior to harvest and has revealed a critical gap in knowledge about the regulation of seed dormancy in quinoa. Therefore, this review will define seed dormancy and the hormones involved in regulation, the different seed dormancy programs, the differences between orthodox and unorthodox dormancy programs, desiccation sensitivity, environmental mechanisms that regulate seed dormancy, and strategies for enhancing resistance against preharvest sprouting (PHS) in quinoa.

### **2. Model Systems: A Theoretical Framework for Quinoa Seed Dormancy, Hormone Signaling, and PHS**

Seed dormancy is defined as a state in which seeds fail to germinate after receiving favorable environmental cues [12,13]. Dormancy classification is based on several factors including the developmental state of the embryo at the time of seed dispersal, physical characteristics of the seed, and physiological responses of seeds to environmental stimuli [14]. Historically, primary and secondary dormancy are most often used to describe differences in dormancy types for diverse plant species. Primary dormancy is characterized as dormancy induced on the mother plant during embryo maturation. Unlike primary dormancy, secondary dormancy is caused by the environment rather than inherited from the mother plant and occurs after seed maturation [15]. In addition to primary and secondary dormancy, other studies have revealed five additional subcategories of seed dormancy including physiological, morphological, morphophysiological, physical and combinational dormancy (Table 1) [14–18]. These categories, which may also influence primary and secondary dormancy, illustrate the nuanced and complex nature of dormancy. Seed dormancy and dormancy release are not binary processes but instead are regulated by a complex network of molecular, temporal, and physical cues, which ultimately result in germination [19,20]. The same is undoubtedly true for dormancy regulation in quinoa.

**Table 1.** A summary of recognized seed dormancy categories [15].

Primary dormancy is regulated by the plant hormone abscisic acid (ABA) [19,20]. As a seed transitions from dormancy to germination changes in physiology are largely controlled by the plant hormones, ABA, and gibberellin (GA) [21,22]. The hormone balance theory suggests that after seed maturation, as ABA signaling decreases there is a corresponding increase in GA signaling that leads to germination [23–25]. Many dormancy studies using model systems and cereals have established a clear connection between ABA and GA signaling with seed dormancy and dormancy loss and provide a theoretical framework for dormancy regulation in quinoa. Specifically, these studies have demonstrated the following: (1) higher seed dormancy is associated with higher endogenous ABA levels, and increased gene expression of ABA biosynthesis genes 9-cis-epoxycarotenoid dioxygenase 1 and 2 (*NCED1* and *NCED2*), (2) ABA levels and/or sensitivity decline during dormancy loss with a corresponding increase in sensitivity to GA, (3) at physiological maturity, a lack of seed germination in dormant seeds is associated with GA-insensitivity, and germination in nondormant seeds is stimulated by GA, (4) as dormant seeds after-ripen, dormancy is lost in stages reflected by changes in sensitivity to ABA and GA, and (5) with afterripening seed dormancy loss occurs with decreased ABA hormone levels due to an increased expression of ABA catabolic genes ABA80 -hydroxylase 1 and 2 (*ABA8*0*OH1* and *ABA8*0*OH2*) and increased GA signaling [20,23,26–43]. Similar investigations evaluating dormancy release have demonstrated the following: (1) after-ripening decreases ABA sensitivity and increases GA sensitivity through increased GA biosynthesis and hormone accumulation resulting from GA20-oxidase gene expression, (2) decreased expression of GA2-oxidase, a GA catabolism gene, occurs as dormancy declines, (3) the GA GID1 (GA-INSENSITIVE DWARF1) hormone receptor increases with after-ripening and (4) as dormancy is lost ABA hormone accumulation decreases through increased ABA catabolism [19–21,23,37,38,43–46].

Seed dormancy studies in the Amaranthaceae family, that of which quinoa belongs, suggest that different quinoa varieties proceed through a combination of primary and physiological dormancy, or they have no dormancy (Table 1) [15]. Furthermore, close weedy relative of quinoa, *Chenopodium album* (common lambsquarter), and *Chenopodium berlandieri* were previously described as having primary dormancy [47–49]. Although these studies provide important phenotypic clues about the underlying mechanisms of quinoa seed maturation, dormancy, and germination in a broad sense, they fail to evaluate directly if there are different types of seed dormancy across quinoa varieties. For these reasons, more efforts are needed to implement a unified platform for characterizing and cataloging differences in seed dormancy phenotypes across varieties in a similar fashion as was done to link agronomic characteristics with regional ecotype.

PHS is characterized by the germination of mature seeds on the mother plant due to rain or moisture prior to harvest (Figure 1) [50,51]. PHS is most often described through the lens of primary dormancy loss in model species and crops. Domestication and selective breeding for synchronized seedling emergence and stand establishment in many crops has resulted in decreased primary seed dormancy; seed dormancy mechanisms have been tailored to ensure maximum crop performance within the confines of a specific growing season [50,51]. PHS which results from altered primary dormancy is also known to occur through decreased ABA signaling and increased GA signaling [50]. The shift in the balance of hormone signaling leads to an extended seed germination window that is no longer synchronous with harvest [50–52]. It is important to note that both primary dormancy loss and the absence of seed dormancy increase the likelihood of PHS if rain occurs prior to harvest. However, the two physiological states are not synonymous and are likely regulated at the molecular level in different ways. Moreover, dormancy and PHS are complex traits that are regulated by multiple genes [50,51]. Therefore, to understand why quinoa is susceptible to PHS future studies in quinoa will need to evaluate whether PHS susceptibility is due to disruptions that change the architecture of primary dormancy and ABA and GA signaling or because quinoa seeds lack primary dormancy altogether.

**Figure 1.** Quinoa preharvest sprouting (PHS).. Panels A-C show inflorescences severely impacted by PHS in breeding line '3964′ from the 2015 and 2019 field seasons. Plants from the 2015 field season (**A** and **C**) were grown in Quilcene, WA on Dharma Ridge Farm. Plants from the 2019 field season (**B**) were grown in Skagit Valley, WA. **Figure 1.** Quinoa preharvest sprouting (PHS). Panels A-C show inflorescences severely impacted by PHS in breeding line '39640 from the 2015 and 2019 field seasons. Plants from the 2015 field season (**A**,**C**) were grown in Quilcene, WA on Dharma Ridge Farm. Plants from the 2019 field season (**B**) were grown in Skagit Valley, WA.

the balance of hormone signaling leads to an extended seed germination window that is no longer synchronous with harvest [50–52]. It is important to note that both primary dormancy loss and the absence of seed dormancy increase the likelihood of PHS if rain occurs prior to harvest. However, the two physiological states are not synonymous and are likely regulated at the molecular level in different ways. Moreover, dormancy and PHS are complex traits that are regulated by multiple genes [50,51]. Therefore, to understand why quinoa is susceptible to PHS future studies in quinoa will need to evaluate whether PHS susceptibility is due to disruptions that change the architecture of primary dormancy and ABA and GA signaling or because quinoa seeds lack primary dormancy altogether.

#### **3. Orthodox and Unorthodox Seed Types 3. Orthodox and Unorthodox Seed Types**

Seed dormancy is an evolutionary adaptation that ensures the species survival of natural catastrophes within a specific environment [38]. Dormancy type is also associated with seed type and is different for orthodox versus unorthodox seeds (Figure 2). Orthodox seeds often display primary dormancy, which is marked by six chronological phases of development, including the following: (1) embryo growth and differentiation; (2) seed expansion, reserve storage, and vacuole filling; (3) internal desiccation, organellar de-differentiation, and membrane stabilization; (4) metabolic quiescence; (5) imbibition, reserve mobilization, and resumption of metabolic responses to environmental cues; and (6) germination [52]. Orthodox seeds are desiccation tolerant (DT) remaining viable for long periods of time in low moisture conditions [52]. Environmental cues such as light, temperature, and moisture not only impact the depth of primary dormancy, but they also play an important role in modulating secondary dormancy characteristics and the length of time required for complete dormancy release [38]. Seed dormancy is an evolutionary adaptation that ensures the species survival of natural catastrophes within a specific environment [38]. Dormancy type is also associated with seed type and is different for orthodox versus unorthodox seeds (Figure 2). Orthodox seeds often display primary dormancy, which is marked by six chronological phases of development, including the following: (1) embryo growth and differentiation; (2) seed expansion, reserve storage, and vacuole filling; (3) internal desiccation, organellar de-differentiation, and membrane stabilization; (4) metabolic quiescence; (5) imbibition, reserve mobilization, and resumption of metabolic responses to environmental cues; and (6) germination [52]. Orthodox seeds are desiccation tolerant (DT) remaining viable for long periods of time in low moisture conditions [52]. Environmental cues such as light, temperature, and moisture not only impact the depth of primary dormancy, but they also play an important role in modulating secondary dormancy characteristics and the length of time required for complete dormancy release [38].

Seeds that lack one of the six previously described developmental stages associated with primary dormancy are classified as unorthodox seeds [52]. In many plant species, and weeds, unorthodox or discontinuous dormancy ensures germination only in favorable conditions, and it confers environmental plasticity, or the ability to respond to changing biotic or abiotic environmental factors [53]. Desiccation sensitivity (DS) otherwise known as recalcitrance, and vivipary, are two characteristics of unorthodox seeds [52]. Neither DS nor viviparous seeds display primary dormancy and both lack the third step in development necessary for desiccation tolerance. As a result neither seed type survives in low-moisture environments, or through periods of dry storage or freezing [52]. DS seeds are often from tropical environments, and if there is adequate soil moisture, DS seeds germinate immediately after dispersion [52]. Rather than persist in the seedbank similar to DT/orthodox seeds, DS/unorthodox seeds that do not germinate immediately after dispersion die.

Elizabeth Farnsworth first suggested that quinoa produced "recalcitrant" or unorthodox seeds [52]. This characterization is based on the observation that many quinoa varieties that germinate at physiological maturity in wet environments, do not appear to survive as seeds in the soil, or they form stable seed banks. However, other quinoa germination

studies have demonstrated that dormancy type and seed characteristics vary depending on quinoa variety, with some behaving as orthodox seeds with primary dormancy, while others do not [15,52]. It has also been hypothesized that seed desiccation status, such as primary and secondary dormancy, is the by-product of a plant's natural environment and selection pressure, which is directly tied to the maternal line [54,55]. Additionally, most studies report that quinoa seeds lose their viability in a short time, especially in conditions of high humidity and temperature [56]. Poor seed viability has been largely attributed to poor storage conditions and a lack of uniform storage conditions. Poor seed viability is itself characteristic of many unorthodox seeds and suggests the possibility that desiccation tolerance or insensitivity in quinoa has largely been under-characterized and is largely not understood. Some research has suggested that there is a correlation between desiccation sensitivity, the generation of reactive oxygen species (ROS), and the occurrence of oxidative damage during dehydration in the seed [57,58]. Furthermore, this research suggests that desiccation tolerance depends on the seeds ability to scavenge ROS compounds by antioxidant defense systems [22,57,59]. Interestingly, heat and drought resistance in adult quinoa plants is thought to occur, at least in part, through the mitigation of ROS, and it is associated with increased peroxisome proliferation [3]. If ROS scavenging pathways are also involved in the desiccation status of quinoa seeds, i.e., tolerant or susceptible, then glyoxysome proliferation may be an important indicator for selecting DT quinoa varieties. *Plants* **2021**, *10*, x FOR PEER REVIEW 5 of 14

**Figure 2.** A summary of dormancy types associated with orthodox verses unorthodox seed types. Orthodox seeds display primary dormancy (PD), secondary dormancy (SD), and physical dormancy (PYD). Unorthodox seeds display desiccation sensitivity (DS) and vivipary (V). Specific dormancy programs and changes to these programs have implications for PHS susceptibility or resistance in quinoa. **Figure 2.** A summary of dormancy types associated with orthodox verses unorthodox seed types. Orthodox seeds display primary dormancy (PD), secondary dormancy (SD), and physical dormancy (PYD). Unorthodox seeds display desiccation sensitivity (DS) and vivipary (V). Specific dormancy programs and changes to these programs have implications for PHS susceptibility or resistance in quinoa.

Seeds that lack one of the six previously described developmental stages associated with primary dormancy are classified as unorthodox seeds [52]. In many plant species, and weeds, unorthodox or discontinuous dormancy ensures germination only in favorable conditions, and it confers environmental plasticity, or the ability to respond to changing biotic or abiotic environmental factors [53]. Desiccation sensitivity (DS) otherwise known as recalcitrance, and vivipary, are two characteristics of unorthodox seeds [52]. Neither DS nor viviparous seeds display primary dormancy and both lack the third step in development necessary for desiccation tolerance. As a result neither seed type survives in low-moisture environments, or through periods of dry storage or freezing [52]. DS seeds are often from tropical environments, and if there is adequate soil moisture, DS seeds germinate immediately after dispersion [52]. Rather than persist in the seedbank Viviparous seeds are another group of unorthodox seeds, and they are common in monocot plant families such as Iridaceae (iris family) and Asparagaceae (asparagus family) [58]. Mangroves and corn are also two well-known examples of plants with viviparous seeds [60]. Similar to DS seeds, viviparous seeds have no primary dormancy, have a short viability window, and cannot survive dry storage or freezing [52]. Viviparous seeds also display PHS, although not all seeds that display PHS are viviparous [22,52,56]. Often in the literature, vivipary is used as a synonym for PHS due to the phenotypic similarities between both. However, the molecular architecture of the two seed physiologies is quite different, and to date there have been no studies to evaluate if quinoa PHS results from vivipary, lack of seed dormancy or both [52]. Simple germination screens have routinely been deployed to evaluate characteristic changes in hormone sensitivity associated with primary dormancy and dormancy loss, as

similar to DT/orthodox seeds, DS/unorthodox seeds that do not germinate immediately

thodox seeds [52]. This characterization is based on the observation that many quinoa varieties that germinate at physiological maturity in wet environments, do not appear to survive as seeds in the soil, or they form stable seed banks. However, other quinoa germination studies have demonstrated that dormancy type and seed characteristics vary depending on quinoa variety, with some behaving as orthodox seeds with primary dormancy, while others do not [15,52]. It has also been hypothesized that seed desiccation status, such as primary and secondary dormancy, is the by-product of a plant's natural environment and selection pressure, which is directly tied to the maternal line [54,55]. Additionally, most studies report that quinoa seeds lose their viability in a short time, especially in conditions of high humidity and temperature [56]. Poor seed viability has been largely attributed to poor storage conditions and a lack of uniform storage conditions. Poor seed viability is itself characteristic of many unorthodox seeds and suggests the possibility that desiccation tolerance or insensitivity in quinoa has largely been undercharacterized and is largely not understood. Some research has suggested that there is a correlation between desiccation sensitivity, the generation of reactive oxygen species (ROS), and the occurrence of oxidative damage during dehydration in the seed [57,58].

after dispersion die.

well as the underlying causes of PHS physiology in many plant species. Thus, germination screening platforms will be essential for elucidating underlying mechanisms regulating PHS physiology across diverse quinoa germplasm.

#### **4. Physical Dormancy in Quinoa**

Physical dormancy is an additional subcategory of orthodox dormancy, involving the embryo, seed coat, or both [61–63]. Embryo dormancy is characterized by an external or internal physical or biochemical block that prevents embryo growth and germination [63]. Seed coat-imposed dormancy often occurs in seeds with a hard, impermeable shell that requires physical perforation or damage to germinate [63]. In some populations, it is possible that both embryo and seed coat-imposed dormancy play a role in quinoa germination programs and need to be carefully described to evaluate if and how each contributes to PHS.

In a recent study, seed coat thickness was measured in two varieties of quinoa, Chadmo and 2-Want, to evaluate if differences in observed dormancy occurred because of seed coatimposed dormancy and in turn impacted PHS [64]. 2-Want had a thinner seed coat, while the Chadmo had a thicker seed coat. When the seed coats were perforated, both varieties continued to display a basal level of dormancy. Hormone analysis determined that seed coat thickness negatively correlated with the amount of endogenous ABA leached from the seed during development. Varieties with thinner seed coats leached more ABA and were less dormant than varieties with thicker seed coats. However, in both cases seed coat disruption did not completely alleviate dormancy. This finding suggested that in addition to seed coat-imposed dormancy, some quinoa varieties also have embryo dormancy [64]. This result is important because it suggests that at least in some quinoa varieties, vivipary is not a contributing factor in PHS sensitivity.

In addition to seed coat thickness, seed coat color has also been implicated in the regulation of quinoa seed dormancy and may be associated with ABA signaling mechanisms. The connection between seed coat color and dormancy regulation has been documented in other plant species including cereals such as wheat and barley, which are members of the Amaranthaceae family [48,49,65,66]. Comparisons between red versus white wheats indicate that red seed coat color is associated with stronger seed dormancy [50,67]. Additionally, a study evaluating the role of seed coat color in wheat found a quantitative trait locus (QTL) for PHS in the same location as coat color and suggested that coat color is likely to play an important role in PHS sensitivity or tolerance [68]. Interestingly, studies evaluating the link between seed coat color and dormancy depth in close relatives of quinoa, C. *album*, C. *berlandieri*, and C. *bonus-henricus*, observed that darker seed coat color was associated with stronger dormancy [48,61]. Furthermore, studies exploring differences in dormancy associated with heteromorphic populations of *C. album* found that brown seeds had thinner seed coats, and no primary dormancy. Whereas, black-colored seeds had thicker, and sometimes stronger seed coats, which are thought to act additively to enhance primary dormancy [49]. Likewise, seed coat studies evaluating dormancy in quinoa varieties such as Chadmo and Titicaca indicated that dormancy is stronger in seeds with a darker colored coat [64]. Another study, evaluating the *Suaeda salsa* in Amaranthaceae, found similar results [47]. Brown seeds had higher germination rates and absorbed water better than black seeds [47]. However, a key limitation of these studies is that they only compare dormancy associated with very dark (black or brown) and light seed coats (light brown) and do not evaluate the broader range of seed coat colors that exist in quinoa including those that are yellow, red or pink [69–73]. Therefore, future studies will need to examine the genetic connection between seed coat thickness, color, and ABA signaling mechanisms, as well as associated impacts on dormancy programs across a wide collection of quinoa cultivars.

#### **5. Environmental Regulation of Quinoa Seed Dormancy**

Secondary dormancy is regulated by the environment and is temporally separated from primary dormancy [38]. Environmental factors reported to enhance secondary dor-

mancy in many species, including quinoa, are photoperiod or day length, temperature, precipitation, and altitude [2,3,6,12,71–75]. Environmental factors that influence the depth of secondary dormancy often do so through increased ABA signaling. Interestingly, previous studies investigating abiotic stress responses, specifically those connected to drought and salinity tolerance in adult quinoa plants also proceed through ABA signaling networks [76,77]. However, there is no research that has investigated whether the ABA signaling networks that contribute to abiotic stress tolerance in adult quinoa plants are also involved in modulating PHS physiology during seed germination. However, what is known is that as the photoperiod increases endogenous, ABA and sugar levels increase in quinoa seeds. Increases in endogenous ABA and sugars are important indicators of embryo dormancy and "ripening" [76–78]. Based on these findings, it was concluded that ABA and sugar signaling are possible mechanisms that regulate the photo-adaptability of adult quinoa cultivars [77]. Long photoperiods may also promote stronger dormancy by increasing ABA levels in seeds [52,78–82].

In addition to photoperiod, temperature plays a role in quinoa development, and it likely impacts seed dormancy and germination. In a study addressing how the environment can affect quinoa, two varieties Chadmo and 2-Want, were exposed to different temperatures and photoperiods to gauge germination and dormancy capacity [78]. The authors discovered that high temperatures and long photoperiod days increased dormancy. It was also determined that the temperature window has increased for quinoa, meaning that modern quinoa varieties have adapted to germinate in colder temperatures than their earlier relatives, and that growing environment is the biggest factor impacting seed dormancy [78].

The cultivation of quinoa across diverse regions, including in hot and dry climates, is likely to have contributed to the requirement for higher germination temperatures. However, understanding the relationship between germination rates and temperature is confounded by the fact that quinoa can germinate in a wide array of varying temperatures. One study reported maximum germination rates at 30 ◦C [78]. However, other studies have found that the optimum germination temperature is 37 ◦C [80]. A shift in recent breeding strategies to cultivate quinoa across very diverse environments has likely had a significant impact on plant and seed physiology [76]. The result of changes to breeding practices and environments has resulted in varieties with low dormancy but high adaptability [78]. These results suggest that growth and germination temperatures may have different effects on distinct varieties of quinoa. These results also suggest that these effects may be exacerbated by environments and may have major implications for variations in seed dormancy phenotypes depending on local growing conditions.

Precipitation and altitude also influence quinoa seed dormancy. Its widely known that quinoa is tolerant to drought and mildew, and these desirable characteristics are a direct result of the original growing habitats [3,54]. It is also known that rainfall prior to harvest when seeds are mature may result in PHS. The five original ecotypes come from very diverse environments, with precipitation varying from intense wet mountains to dry sandy regions [3–5,54]. It is important to mention this, because to date, although there have been some studies that have tested how different quinoa varieties respond to varied precipitation and drought treatments, none have directly investigated how precipitation timing near harvest maturity impacts PHS susceptibility.

Seed coat thickness and color, two factors that impact dormancy strength, may also be regulated by the environment. For example, a study evaluating the effect of elevation on seed coat thickness and rates of germination for quinoa's close relative *C. bonus-henricus* found that seeds grown at a lower elevation had thinner seed coats, and increased rates of germination [61]. If seed dormancy mechanisms are conserved in quinoa then it might be expected that varieties grown at higher elevations will have thicker seeds coats, slower rates of germination, and perhaps more seed dormancy than those grown at lower elevations. It is also good to note while looking at color differences, that seeds with thinner seed coats appear to be lighter in color, whereas thicker coats have darker coloration [64].

#### **6. Breeding Strategies to Mitigate PHS in Quinoa**

Research studies in cereals such as wheat and barley, and model plants like *Arabidopsis thaliana* has demonstrated a compelling connection between increased seed dormancy and PHS resistance [3,12,45,52,54,78,83,84]. In the cases of wheat and Arabidopsis, several major and minor quantitative trait loci (QTLs) associated with increased PHS resistance map to regions of the genome containing genes previously characterized as regulators of dormancy and seed coat color [50,68,85,86]. Therefore, breeding for stronger seed dormancy in quinoa seems a promising approach for reducing the risk of crop losses due to PHS. Two strategies currently being used to accomplish this task are 1) to make crosses between quinoa varieties displaying different levels of seed dormancy, and 2) to make crosses between quinoa and wild relatives, such as native lambsquarter (*C. berlandieri*) which is a tetraploid similar to quinoa and has more clearly defined seed dormancy. The primary goals of both approaches have been to create hybrid populations that allow for a better understanding of how seed dormancy and PHS are segregating within a population, and to create PHS resistant germplasm.

In the first strategy, breeders have used Titicaca, a cultivar developed in Demark with higher seed dormancy, and 'Chadmo, QQ065-PI 6148800 , which is a naturally dormant variety originating from the Chiloe island in Chile, to create quinoa populations with increased seed dormancy and PHS resistance [3,64,78,82]. However, despite these efforts, incidences of PHS in both Titicaca and Chadmo have been reported with adequate rainfall prior to harvest, and across diverse growing regions (breeder listening sessions; International Quinoa Conference, 2020). Additionally, hybrid populations created at the Sustainable Seed Systems Laboratory at Washington State University using Chadmo also displayed frequent PHS in the higher rainfall zones of Western WA, despite initially appearing to be resistant (K. Murphy, personal communication). Taken together these results suggest that while many quinoa varieties appear to be susceptible to PHS, with some displaying some form of seed dormancy, there is not a clear connection between the type or level of seed dormancy with level of PHS susceptibility. These results also suggest that the mechanisms of regulation between dormancy and PHS in quinoa may not be analogous to those in cereals or other model plant species. However, with the recent sequencing of the quinoa genome, many genomics-assisted breeding approaches, including QTL analysis, and the molecular characterization of PHS-specific genes, are now possible [6,50].

The second approach developed to increase PHS resistance in quinoa is to introduce the desired dormancy type and level, i.e., primary and strong, by making a wide cross with a genetically compatible relative. The objective of this approach is to add desirable traits that are currently lacking in the existing genetic pool. Selective breeding approaches have been routinely implemented in other crops, using landraces or weedy relatives to increase physiological plasticity to abiotic stresses, and to increase disease resistance [87].

Although classified as an invasive weed species in the United States, *Chenopodium berlandieri,* also known as pitseed goosefoot, is grown as a seed crop in other parts of the world. *C. berlandieri* has emerged as a possible candidate for increasing PHS resistance in quinoa because (1) it is genetically compatible with quinoa and a cross between the two produces viable offspring, and (2) it displays strong orthodox primary seed dormancy, and this dormancy diminishes in a trackable manner over time that would also allow for simultaneous PHS sensitivity screening. Pitseed goosefoot is comprised of two subspecies, *berlandieri* and *nuttaliae*, and ecotypes can be found growing from southern Mexico and Texas, into southwestern and eastern North America, including along the coasts of the Atlantic and Gulf of Mexico [88]. Since pitseed goosefoot was a source of food for centuries in pre-European indigenous cultures in eastern North America, it is adapted to regions of the U.S. where quinoa struggles to grow. Pitseed goosefoot is a potential donor parent of key agronomic traits in quinoa, including heat tolerance, nutritional value, and resistance to PHS.

However, it is important to mention the possible risks associated with this approach, namely the development of germplasm that will establish a robust volunteer seedbank. From an agronomic perspective, two of the most favorable characteristics of existing quinoa

varieties are that they germinate readily and do not survive desiccation, meaning they do not establish weedy seed banks. Hybrid populations generated from wide crosses will serve as essential tools for characterizing dormancy physiology and PHS regulation in quinoa. If used for variety development, future breeding efforts using wide crosses will need to strike a balance between increased seed dormancy and decreased germinability, so as not to trade PHS susceptibility for volunteer seedbank establishment.

In addition to the previously mentioned strategies aimed at increasing PHS resistance through increasing quinoa seed dormancy, another approach is to select for faster maturing varieties. The advantages to this "avoidance strategy" is that neither dormancy status nor PHS sensitivity are factors if harvest time is separated fall rains. However, the challenge with this approach, however, is that it does not address quality issues associated with dormancy, or PHS physiology, relying instead on optimum growing conditions and weather stability. In an age of increasing climate variability, it is unclear how current quinoa production regions might be impacted or how future production systems will need to be tailored to target optimal growing regions.

#### **7. Other Tools for Mitigating PHS in Quinoa**

Breeding for increased resistance to PHS in quinoa is a long-term endeavor taking years to produce new varieties. Given that very little information is understood about quinoa seed dormancy structure and PHS physiology, breeding strategies that rely heavily on the conventional wisdom established for PHS in cereals may be confounded by differences in biological and environmental factors that regulate seed maturation, germination, and viability in pseudocereals. Therefore, future research should also incorporate nonbreeding, short and intermediate-term PHS mitigation strategies that help alleviate the risk of PHS in quinoa. Quinoa seed physiology may fall outside of an orthodox dormancy regime, with varieties displaying weak dormancy to no primary dormancy, DS, as well as a significant decline in seed viability post-harvest [89]. For these reasons, in addition to trying to increase PHS resistance through breeding for increased seed dormancy, it might also be necessary to minimize PHS risks by transiently modulating seed physiology from DS to DT in the field just prior to harvest.

One way to temporarily change seed physiology is by using growth regulators. Paclobutrazol (PAC) is a GA biosynthesis inhibitor historically used to understand the dynamics of GA and ABA signaling networks in dormant and germinating seeds [90]. Previous studies evaluating PAC treatments in quinoa have done so in adult plants and have focused on increasing drought and salt tolerance as well as yield [3,48,83]. In all cases PAC treatments were efficacious for increasing resistance to abiotic stress and for increasing yields and did so through an indirect increase in ABA signaling resulting from decreased GA signaling. Additional work investing the regulation of DS in the seeds of *Citrus limons,* a species without seed dormancy, found that treating freshly harvested seeds with PAC both slowed the rate of seed germination and extended the seed viability window from weeks to months, which are two phenotypes consistent with orthodox seed dormancy [52].

Expression analysis comparing non-treated and PAC-treated seeds demonstrated that in addition to inhibiting GA biosynthesis and signaling genes, PAC treatment also inhibited other phytohormone pathways associated with cell growth, including auxin and ethylene signaling, as well as causing an increase in both endogenous ABA hormone levels and signaling. Furthermore, studies evaluating the efficacy of ABA treatments for mitigating DS in the seeds of *Acer Saccharinum* indicated that ABA alone was able to rescue a DS phenotype through increased ABA-mediated signaling [90]. Analysis of total protein in ABA-treated seeds found that ABA-treated seeds accumulated higher amounts of Late Embryogenesis Associated (LEA) proteins which are associated with seed dormancy and desiccation tolerance [90]. Although PAC is a powerful research tool for understanding dormancy regulation, due to issues with toxicity, it is not suitable for large-scale production systems. However, unlike PAC, ABA is routinely and safely used to stimulate fruit ripening and enhance fruit color in grape production systems [91]. In a similar way, timed ABA treatments just before seed physiological maturity may prove to be powerful tool for enhancing PHS tolerance and increasing seed viability in quinoa through a transient increase in dormancy.

#### **8. Conclusions**

Over the last decade quinoa has emerged as a high-value, nutritious crop to enhance food security; it is artisanal (domestic interest), and it performs well in variable environments and in marginal soils. For these reasons, many research efforts have centered on understanding and improving traits related to abiotic stress tolerance, disease resistance, and yield. In many cases studies have focused on adult plants. Consequently, one largely overlooked area of research has been the study of the mechanisms that regulate quinoa seed dormancy. In the last few growing seasons, across the globe from Rwanda to the Pacific Northwest of the U.S.A., diverse quinoa varieties have been plagued by PHS, including those previously bred for enhanced dormancy. In some instances, untimely rains before harvest have resulted in nearly complete crop losses due to PHS. Therefore, the overall goal of this review paper is to inform breeders and non-breeders alike about the complex physiology leading to PHS in quinoa.

The strategies we believed to be key for understanding the dynamic nature of quinoa seed dormancy and PHS physiology include (1) the development of a high-throughput hormone screening pipeline, to quickly characterize the presence or absence of dormancy, and baseline dormancy strength at physiological maturity, (2) the implementation of a PHS screening platform modeled after those routinely used to evaluate PHS susceptibility in wheat, (3) the development of gene-specific primers to evaluate changes in genes associated with ABA and GA signaling, seed dormancy, PHS tolerance, and desiccation sensitivity/tolerance, and (4) assessing the effects of ABA and PAC treatments on dormancy preservation, seed germination rates, and desiccation tolerance in greenhouse and field trails. These efforts will provide a framework for developing new tools for understanding seed physiology in quinoa and mitigating PHS.

**Author Contributions:** E.M.M. and A.L.H. conceived and drafted the manuscript. K.M.M. and A.L.H. edited the manuscript, and K.M.M. contributed significantly to additional information added to the final manuscript draft. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded in part by the Orville A. Vogel Wheat Research Fund.

**Acknowledgments:** The authors would like to thank attending members of the 2020 International Quinoa Symposium for helpful discussions about issues that impact quinoa seed dormancy.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

## *Article* **A Long Journey of CICA-17 Quinoa Variety to Salinity Conditions in Egypt: Mineral Concentration in the Seeds**

**Juan A. González 1,\*, Leonardo Hinojosa 2 , María I. Mercado 3 , José-Luis Fernández-Turiel 4 , Didier Bazile 5,6 , Graciela I. Ponessa 3 , Sayed Eisa 7 , Daniela A. González 8 , Marta Rejas 4 , Sayed Hussin 7 , Emad H. Abd El-Samad 9 , Ahmed Abdel-Ati 10 and Mohamed E. A. Ebrahim 11**

**Abstract:** Quinoa may be a promising alternative solution for arid regions, and it is necessary to test yield and mineral accumulation in grains under different soil types. Field experiments with *Chenopodium quinoa* (cv. CICA-17) were performed in Egypt in non-saline (electrical conductivity, 1.9 dS m−1 ) and saline (20 dS m−1 ) soils. Thirty-four chemical elements were studied in these crops. Results show different yields and mineral accumulations in the grains. Potassium (K), P, Mg, Ca, Na, Mn, and Fe are the main elements occurring in the quinoa grains, but their concentrations change between both soil types. Besides, soil salinity induced changes in the mineral pattern distribution among the different grain organs. Sodium was detected in the pericarp but not in other tissues. Pericarp structure may be a shield to prevent sodium entry to the underlying tissues but not for chloride, increasing its content in saline conditions. Under saline conditions, yield decreased to near 47%, and grain sizes greater than 1.68 mm were unfavored. Quinoa may serve as a complementary crop in the marginal lands of Egypt. It has an excellent nutrition perspective due to its mineral content and has a high potential to adapt to semi-arid and arid environments.

**Keywords:** *Chenopodium quinoa* Wild.; salinity; mineral concentration; food; extreme environment

### **1. Introduction**

Climate change is a reality, and we already see today its effects on the physiology, growth, and yield of field crops. For instance, the frequency of heatwaves has increased in large areas of the world, and precipitation changes have become more unpredictable [1]. Besides, the climate change effects and the bad agronomic practices have increased the saline soil areas. Salinity limits crop yields due to a reduction in photosynthesis, respiration, and protein synthesis. Around 7% of all land area in the world (1000 million ha) is affected

**Citation:** González, J.A.; Hinojosa, L.; Mercado, M.I.; Fernández-Turiel, J.-L.; Bazile, D.; Ponessa, G.I.; Eisa, S.; González, D.A.; Rejas, M.; Hussin, S.; et al. A Long Journey of CICA-17 Quinoa Variety to Salinity Conditions in Egypt: Mineral Concentration in the Seeds. *Plants* **2021**, *10*, 407. https://doi.org/10.3390/plants1002 0407

Academic Editor: Adriano Sofo

Received: 15 January 2021 Accepted: 16 February 2021 Published: 22 February 2021

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