1. Introduction
The Agastache mexicana subspecies mexicana (Amm) is an aromatic plant belonging to the Lamiaceae family, which has 72 species with antifungal activity. Most particular among them are genera Clinopodium sp. L., Lavandula sp. L., Mentha sp., Thymbra sp. L., and Thymus sp. L. [1,2,3]. The Amm is found in the following geographical locations: warm, semi-warm, temperate, cold, tropical forest, deciduous, sub-deciduous, evergreen and thorny, cloudy mountain, and pine-oak environments, from 1600 to 3900 m above sea level (MASL) [4]. Amm is distributed in Puebla, México, Guerrero, Jalisco, and Michoacán (UNAM, 2009). The extract taken from Amm aerial parts contains high amounts of glycosylated and non-glycosylated flavonoids and is used with mild adverse effects in traditional medicine for mental disorders [5,6,7]. It has been shown that doses with respect to a body mass of 0.01–10.00 mL/kg can trigger an anxiolytic effect and a more significant sedative effect in those with a body mass above 10 mL/kg [8]. Therefore, Amm can be used as a tranquilizer and sleep inducer. Finally, some research has investigated these plant’s vegetative anatomy and essential oils [4,9].
In medicinal plants, light and dark can affect a seed’s germination, growth, and survival of seedlings and plants. For instance, in Withania somnifera, seeds with three different regimes (continuous light, continuous darkness, and alternate light/dark) [10], and in Marrubium vulgare L., different light colors (white, red, far-red, and blue) were used to determine the effect when seeds sprouted [11]. In traditional Chinese medicine, to determine the optimum light intensity for growing species such as Polygalaceae (Polygala fallax Hernsl), AS is used at 50, 70, and 90% levels [12]. The shading tolerance of other plants at two sites is described by two components: mortality in shading and height growth in high light. At low light intensity, beech showed the most negligible mortality, while maple was the highest, and ash was between the two [13]. On the other hand, the effect on the rhizome and root yield in Actaea racemose and Cimicifuga racemosa has been studied in a shading house or bio-space [14].
In experimental drought and salt stress conditions, the use of SiO2 has demonstrated enhanced crop yield and seed vigor in relation to medicinal plants and herbs—this includes crops (Zea mays L., Phaseolus vulgaris L.), medicinal plants (Hyssopus officinalis L. and Nigella sativa L.), and weeds (Amaranthus retroflexus L. and Taraxacum officinale F. H. Wigg) [15,16,17].
Different SiO2 concentrations are useful for seedling survival under low, moderate, and severe stress conditions. When seedlings are pretreated with high concentrations of SiO2, the results show that gas exchange, photosynthesis, stomatal conductance, and transpiration rate are significantly less impacted by extreme drought stress [18].
Plant roots absorb SiO2 through the xylem, while the aerial parts employ passive diffusion. Thus, silicic acid [Si(OH)₄] accompanies the transpiration flow through mechanisms that transpose among species, including their genetic bases [19]. In these cases, SiO2 accumulates, ranging between 0.1 and 10% m/m of the plant´s dry mass [20,21]. Specifically, monocotyledonous plants collect more SiO2 than dicotyledonous plants [22]. SiO2 triggers growth and has the best effect on plants such as “chile piquín” (Capsicum annuum L. var. glabriusculum) [23]. The fertilization of oil palms with SiO2 achieved a higher yield of green leaves than those without SiO2 [24]. Si can be absorbed into the soil in different ways and fertilized to improve the yield of crops under salt stress [15]. Si can also be absorbed as silicic acid [SiOx(OH)4−2x]n while it is in a truly aqueous solution (such as monosilicic acid, orthosilicic acid, and disilicic acid). These different molecules can coexist in a dynamic equilibrium. Thus, the system is static as crystals are produced.
Drought resistance is defined as the integrated capability of plants to respond to and adapt to a harsh environment caused by drought stress conditions. This capability is a sophisticated trait related to adaptations at different levels, ranging from plant morphology and anatomical structures to physiological and biochemical properties [25].
The soil´s physical properties regarding its ability to retain and conduct water are determining factors for water absorption, which, in turn, are required for germination. An excess of water tends to suffocate the embryonic axis due to a lack of oxygen, preventing the entry of air and trapping water between seed tissues during the imbibition process. In these cases, the seed does not germinate, and even if the radicle does sprout, the seedling dies immediately. On the other hand, the most vigorous seeds can germinate in a wide range of water levels in soil: a capacity that increases with the physiological aging of the seed [26].
In plants, soil waterlogging or submergence triggers hypoxia (low-oxygen stress), thus reducing and inhibiting the gas exchange between the plant and soil. Soaking the roots induces nutrient and intermediate metabolite losses. This significant abiotic stress also harms plant growth, development, distribution, and productivity; however, plants have evolved morphological, physiological, and biochemical adaptations to survive low-oxygen stress. In addition, plants frequently experience physiological hypoxia in specific tissues and organs, such as the shoot and root apical meristem, lateral root primordia, and crown galls, due to limited diffusion or the rapid consumption of O2 in conjunction with high energy demands [27]. Oxygen limitations also cause changes in the soil that are physical, chemical, and biological (organic acids, gaseous hydrocarbons, methane, and sulfides). Waterlogging hinders the active absorption of mineral nutrients and the use of mineral ions.
The field capacity is defined as the water content (or moisture content when the water does not flow via gravity) retained on the soil after being saturated with water. Additionally, the permanent wilting point is the hydric potential of the soil, where the leaf does not recover its turgidity. When the soil does not receive water input, or when it is smaller, evaporation from the soil is faster, and its extraction via the roots causes water to decrease until it reaches a level where the roots can no longer extract water from the soil. A discussion of the plant´s permanent wilting point is also worthwhile. It is necessary to know the water quantity or hydric demand that Amm plants need. However, this depends on factors such as the phenological state, water-holding capacity (of the soil as well), and evapotranspiration. Indeed, it is essential to determine when to irrigate and how much water should be supplied to replace the water absorbed by the plant and the evaporated water. Therefore, it is necessary to know the field capacity of the soil along with the permanent wilting point.
Currently, Amm is found in nature. Its natural environment is that of low temperatures with high relative humidity. These days, especially because of climate change, its propagation in other environments is crucial to avoid shortage or extinction. It has not been confirmed if shading favors its germination and growth. As of yet, no study has proven that Amm can accumulate SiO2. This research was cross-sectional, observational, and completely randomized. Our working hypothesis was that applying multifactorial treatments bis water irrigation and AS levels, besides different SiO2 concentrations mixed into the Amm crop soil, could significantly affect response variables such as emergence, mortality, and survival. This research thus aimed to measure the response of Amm to achieve survival under unfavorable conditions such as low nutrient levels and water stress for different SiO2 and AS levels. Until now, no research of this kind has been carried out on Amm.
2. Materials and Methods
2.1. Experimental Place and Amm Seeds
Our experiment was conducted in a completely randomized manner. The experimental field was located in the facilities of the Tuxpan Experimental Unit in the Faculty of Agricultural and Environmental Sciences of the Autonomous University of Guerrero in Iguala de la Independencia, Guerrero, Mexico. The Agastache mexicana subspecies of mexicana seeds were obtained from Puebla, México. Survival measurements were taken every week during the experimental period.
2.2. Preparation of Substrate and the Sown Seed
First, Canadian peat was selected due to its low nutritional quantity in order to find out if SiO2 powder influenced Amm under drought stress. The technical characteristics were as follows: unsterilized, pH = 8.5 (measured with potentiometer), vermiculite at 10% m/m, the electric conductivity at 0.6–0.8 mmhos/cm, moisture content at 45–50%, organic material of 68–82%, ash content of 18–32%, and water-retention capacity of 8x–10x (w/w based on dry weight). The proportion of fiber was as follows: coarse—19–24%, 9 U.S., medium—22–39%, 20 U.S., and fine—38–54%, 100 U.S.
The SiO2 (Trademark Diatomix) used had the following properties according to the technical data sheet: a 92% amorphous silicon cation exchange capacity (C.E.C.) of 60.0 meq/100 g, a release rate of [Si(OH)4] 46 mg/L, pH of 8.8, a moisture-retention capacity of 254%, the electrical conductivity of 0.1 dS/m, a surface area of 27 m2/g, the appearance of fine white powder, and a density of 0.12 g/mL, and retention of 1.0% (mesh 325); therefore, the particle size was lower than 44 microns. The SiO2 powder weight was calculated using the weight of peat moss as a reference to obtain four SiO2 levels: 0.0, 0.2, 0.4, and 0.8%.
Both ingredients were mixed manually until the mixture was homogeneous.
The mixture must have a consistency that prevents water from dripping through one´s hands. Thus, it is necessary to have a very specific water content. In order to achieve this, the water was added gradually in 1 mL, 5 mL, and 100 mL tubes until the desired consistency was reached. Finally, the peat moss was 1.4148 kg, and water was 1.886 L at every level of SiO2. Four trays (67 × 33 × 6.5 cm) with 200 cavities were used. The quantity of the substrate was calculated to fill the 20 wells or cavities with every level of SiO2 with 4 repetitions. In every cavity, one seed was sown at a depth three times that of the seed size. Two rows were left between every level to avoid substrate migration with different SiO2 levels in other cavities.
Table 1 summarizes 12 treatments in which 2 input factors were combined with 3 levels of AS and 4 levels of SiO2, respectively, to measure the emergence, mortality, and survival of Amm. A factorial interaction was studied to measure the AS and SiO2 effects and their interaction.
2.3. Preparation of Bio-Space
This research was conducted in a bio-space that measured 7 × 12 × 9 m (height × length × width). It was an open space covered with commercial plastic film, had a water storage system, and pumped water from a well to an automatized sprinkler irrigation system: three table-kind micro-bio-spaces with metallic structural elements. The trays with seed planting were collocated on wooden beams (four repetitions on three tables) as a means of separation, allowing the free flow of water out of the cavity.
2.4. Calculating Water Irrigation
First, an irrigation pump was activated to store water and calculate its volume and time. The pump was also programmed with a Steren timer, model TEMP-08E, in order to automate the water irrigation system, which was of an entirely random design. There were six water sprinklers on top of every table distributed along its length, which hung at a height of 1 m. This system was established for every stage; irrigation occurred twice every day to achieve the quantity of water required per day, as seen in Table 2. (Note: Figure S1 can be consulted to see details about (a) Seed size; (b) enlarged seed; (c) trays with sown seeds; (d) bio-space; (e,f) seedlings; (g) plant.)
2.5. Statistics Analysis and Formulas
We conducted a statistical analysis to assess the effect of AS and SiO2 on the response variables’ emergence, mortality, and survival. We used a two-factorial design at random, which assumed the identical, independent homogeneity of variances and normal distribution of the errors. Tukey’s mean comparison test (p-value < 0.05) was used to identify significant differences between the treatments τ1-τ12. In turn, we used SAS software V.9.0 and Origin software to plot the Figures.
Table 3 contains the mathematical ratios (formulas) used to measure the following: seed emergence percentage (SE), mortality percentage (MP), survival percentage (SP), Mortality Index (MI), and emergence peak value. In Section 3, these values are used to explain the effect of AS, SiO2, and water stress on Amm in a bio-space.
3. Results and Discussion
3.1. Statistical Results
Table 4 summarizes the statistical results of the two-factorial design. The results showed statistical significance at the p-value and mean for mortality and survival and were statistically non-significant for emergence in all interactions. The design of the experiment guaranteed the independence of the observations. The model adjusted for emergence fulfilled the assumptions of normality (Shapiro–Wilk, p = 0.10) and the homogeneity of variances (Bartlett, p = 0.63). Similarly, the model adjusted for mortality fulfilled the assumptions of normality (Shapiro–Wilk, p = 0.84) and the homogeneity of variances (Bartlett, p = 0.06). The model adjusted for survival also fulfilled the assumptions of normality (Shapiro–Wilk, p = 0.18) and homogeneity of variances (Bartlett, p = 0.06). The above arguments allow us to trust the results obtained. The interaction of AS*SiO2 was not statistically significant for emergence (p = 0.76), mortality (p = 0.82), and survival (p = 0.75) (Table 5).
3.2. Emergence Results
Emergence is considered when the cotyledons appear in epigeal germination. Figure 1a–d plot the seed emergence profile of Amm for the AS and SiO2 levels. Figure 1a,b show a dairy profile, and Figure 1c,d show a cumulative profile. According to Figure 1a,c, the seeds needed enough shading to emerge. It is possible that shading creates a homogeneous humidity condition, allowing the germination of seeds almost simultaneously, or light creates a heterogeneous condition that causes adverse conditions for seed germination. Emergence would, thus, be different and slower. For 87 and 94% of the AS levels, the beginning and maximum emergence peaks were on days 6 and 9, respectively, and 38% of AS was on day 12. According to Figure 1b,d, SiO2 can trigger the emergence of the seeds with the hardest shell or with exogenous dormancy. The following are particularly noteworthy: (1) when AS is low, the beginning, maximum peak, and emergence of seeds are the slowest; (2) the final quantity of seed emergence is different at every AS and SiO2 level; (3) the maximum peaks mostly occur during days 9 and 10; (4) the number of seeds experiencing emergence do not coincide graphically after the extrapolation of curves. Before the maximum peak (from left to right), there is a previous peak in 1a and 1b; after the maximum peak, there are two peaks at every SiO2 level (ascendant–descendant–ascendant movements) and only one at every AS level. It is possible that the seed’s food reserves were weak when emerging, so they did not survive long, even under favorable light conditions.
When the emergence seed percentage (SE) and the emergent peak value were the highest, the peak day had the smallest value among several values; see Table 6 (treatments τ8 and τ9). This fact has been proposed to indicate different maturity levels in a seed lot. The Pearson correlation coefficient was calculated with a formula in Excel software; between the peak day and emergent peak, the result was −0.68, which is in accordance with another result where the same coefficient was −0.60 [28].
Seed viability is determined by the genetic characteristics of the parent plant, their climatic conditions at different stages (flowering, development, and fruit ripening), and the degree of maturity of the seed at harvest and handling [29]. Amm seeds are from basipetal plants. Thus, they vary in size, weight, reserves, quantity of nutrients, and maturation times.
3.3. Emergence, Mortality, and Survival Results
Figure 2, Figure 3a–b and Figure 4a–c are explained in this section. Here, the horizontal upper axis and vertical right axis in blue color represent the experimental time (days) or stages from Stage 1 (S1) to Stage 6 (S6) and the water irrigation in the stairway profile, respectively.
In Figure 2, the horizontal bottom axis and vertical left axis in black describe the accumulated number of emerging seeds (with the accumulative normal curve “S” profile in orange), in addition to the mortality and survival of seedlings and plants (with the accumulative normal curve “S” double profile in red and green, respectively). The expression “general experimental behavior” suggests the consideration of the simultaneous effect of AS and SiO2 levels under the same water irrigation profiles. It is important to note that in S1, waterlogging stress is the primary cause of seedling mortality. In S6, drought stress is the most significant cause of seedling mortality. In S2–S5, seedling mortality increases more slowly.
Our explanation of Figure 2 can be seen in Table 7, numerically describing points A, B, and C. Also of note is Table 8, which represents each stage of water irrigation associated with a hypothetical factor that we describe later. The Mortality Index (MI) is considered an output factor.
In Figure 3a–b and Figure 4a–c, the horizontal bottom and vertical left axes in black describe the mortality number and survival percentage, respectively. It is important to note that the water irrigation profile, AS, and SiO2 levels affect the “S” double profile in different ways.
3.4. Hypothetical Analysis
This section proposes some hypotheses to our findings. In the following, we aim to suggest future research.
3.4.1. Stage 1 (S1) Waterlogging
With waterlogging, the irrigation level is very high. Waterlogging stress triggers the cellular seed wall to soften. As such, there is very low germination (not in sensu stricto) and the quick mortality of seedlings and plants. The main issue with these conditions is the decrease in oxygen; hypoxia reduces the growth and development of the roots (reduced quantity, size, and thickness), and it affects seeds, seedlings, and plants with more effect on factors at 38% AS and 0.0% SiO2 levels (see S1 in Figure 3a,b). In research regarding Zea mays, waterlogging stress, and anaerobic conditions trigger a decrease in Redox potential and oxygen dissolution in water and soil by promoting pathogens in the substrate. Diseases thus appear (damping off in Rhizoctonia Solani and Phytophthora) [30,31]. Yet, when SiO2 is mixed with soil, it functions as a rhizosphere (a volume of the soil solution in contact and accessible via the uptake mechanisms of plant roots) and works as a seed’s inoculation process [32]. Effectively, the most vigorous seedlings and plants can survive due to environmental adaptation. Plants tolerate waterlogging stress in various ways, such as transporting and supplying oxygen and increasing the number of thin roots in the most superficial soil. They also maintain an aerobic condition and transport photosynthetic oxygen to the plant via the stomata through a “space-gas continuum” in the tissues or develop aerenchyma tissue, which is formed preferentially in the roots, although it is also possibly formed in rhizomes, stems, and leaves. Another coping mechanism is the transport of gases via a convection to the part submerged in water (gas that enters the plant above the water table) and with an outlet to the atmosphere in plants with rhizomes; also, from the respiratory aspect, CO2 does not compensate for the influx of oxygen with its diffusion into the atmosphere but remains dissolved in water and is lost in the transpiration flow or is released into soil water [26].
3.4.2. Stage 2 (S2) Latest Waterlogging and Early Field Capacity
Seedlings and plants can still grow, maturing and hardening together, even while experiencing a lower level of irrigation. Artificial shading forestalls the mortality process, although the field capacity has not yet been achieved, as it is just beginning to drain the excess water from the S1. The highest accumulated mortality corresponds to shading levels at AS = 38%, indicating that the shading level provided by the commercial plastic of the bio-space does not favor plant survival. In addition, the 0.4% SiO2 level is associated with an accumulated mortality higher than the other levels. It is important to note that until the end of this stage, the mortality rate due to shading levels of 87% and 94% is very low and similar at both levels.
3.4.3. Stage 3 (S3) Field Capacity
Mortality almost stops or remains very low at the shade level of 38%, which indicates the effect of waterlogging in S1 conditions on its survival in S2. Therefore, we are able to propose that the leaves and roots of the surviving plants are well-developed and grow. Thus, the field capacity is optimal for this level of irrigation due to water retention (a product of porosity, texture, and substrate structure), which allows the adequate transpiration and oxygenation of seedlings and plants. A few plants were observed to drop their leaves. No wilting was observed in the upper layer of the plant.
3.4.4. Stage 4 (S4) Low Drought Stress and Available Water Capacity
Here, the mortality rate increased five times. However, the SP increased by only 0.7%, while the level of stress could be described as low, the soil humidity was lower, and the roots absorbed water present in the soil with greater difficulty. This result reinforces the hypothesis of transitioning from a state of field capacity associated with low stress to a state of available water capacity associated with increased drought stress. When watered daily for two sessions, the roots absorbed water in a relatively short time. It was observed that all the plants recovered their leaves. No wilting was observed on the main stem. In addition to irrigation, the soil maintained a certain available water capacity.
3.4.5. Stage 5 (S5) Moderate Drought Stress, an Incipient Permanent Wilting Point, and the Beginning of Epinasty
Mortality is accelerated by a lower level of irrigation, especially in plants with a shading level of 38%. Stress can be classified as moderate. For the first time, the trend of percentage survival at the 0.8% SiO2 level fell below percentage survival at the 0.2% SiO2 level. It was observed that some plants dropped their leaves while others began withering in their upper layers. At this stage, it can be said that the permanent wilting point began. The available water capacity was exhausted.
3.4.6. Stage 6 (S6) Severe Drought Stress, Permanent Wilting Point, Epinasty, and Final Survival
Here, the survival percentage dropped in the most pronounced way of the entire experiment. By focusing on plants with a 38% shading level and 0.0% and 0.8% SiO2 levels, which, in previous stages (although it is not the subject of this article), were the tallest, it ensured that the water demand for their survival was greater (treatments τ1, τ7, and τ10).
It was observed that some plants had a wilted upper layer. Others clearly presented epinasty, while others dropped their leaves again. Thus, one can speak of severe stress due to drought as the soil was at the point of permanent wilting.
In short, in the context of waterlogging stress, the most vigorous seeds show a capacity to germinate in a wide range of water levels in the soil: a capacity that increases with the physiological aging of the seed. Reducing the metabolic rate and using reserve carbohydrates (starch and sucrose) in latency periods with little storage of proteins and lipids are strategies to survive in flooded soil [26].
Now, in the context of resistance to drought stress, the most vigorous roots are responsible for plant survival; however, the water use efficiency approach can help to focus on a wide range of physiological and morphological attributes to evaluate their importance [33].
Water demand is determined by transpiration. Under conditions of low field capacity and high evaporative stomatal activity due to the effects of low shading levels, plants are likely to survive. However, with high radiation and a greater amount of light, the death of the plant is effectively certain [34].
In the experimentation of tree species with different treatments of induced drought paired with minimal, moderate, and intense amounts of light, the results showed that those treatments with the lowest amount of light survived more because soil moisture was better conserved [35].
After applying SiO2 in the substrate or soil for survival, the effect in the rhizosphere was as expected before stages S5 and S6. However, increased plant growth at the 0.8% SiO2 level caused the plant to fail to survive under low available water and permanent wilting point conditions. These results are not shown here. The following can be said about the treatments: (a) MI’s highest values were at the 0.8% SiO2 level and all levels of AS in S6 because plants store SiO2 in their roots [18], and (b) MI’s lowest values were reached at S3–S5 for all levels of SiO2 and S3, respectively. Additionally, in a contradictory result, the low mortality may be due to the growth and vigorous root system effect. Plants, to survive, develop more extensive, deeper, and thicker roots [36,37,38].
3.5. Results by Treatment
Each treatment was evaluated in terms of the number of surviving plants in Figure 5a and the percentage that survived in Figure 5b once the seedlings had emerged. As can be seen, the τ8 treatment (0.4% SiO2 and 87% AS) yielded the highest number of plants that survived adverse conditions; however, in proportion to the emerged seedlings, the τ6 treatment (0.2% SiO2 and 94 AS%) had the highest value.
This section also discusses a method for explaining the hypothetical effect of both AS and SiO2 if they could interact with the best characteristics of each other. It develops the survival efficiency under water stress indexes Sef1 and Sef2, respectively. Table 9 shows SP and SE values for every SiO2 and AS level (fractional numbers). Then, Figure 6 plots the interpolation profile calculated by employing the multiplication of Sef1 and Sef1 values (for every AS level vs. every SiO2 level). The product between both represents the efficiency of the plants to survive or the Index of Survival Efficiency Under Water Stress (SIef). The SIef value is non-dimensional.
Therefore, the hypothetical interaction of SiO2 and AS levels is the best, with 0.4% SiO2 and 97% AS levels. This result demonstrates that the application of these input factors would have the most favorable effect on the survival of Amm plants under conditions of no waterlogging and good field capacity.
3.6. Future Researches
Our research provides an opportunity to perform the Amm vigor test vis à vis the number of leaves and the length of roots. It may also be fruitful to measure the field capacity and permanent wilting point. We may also measure the different biochemical changes when Amm is cultivated in both bio-spaces as well as in open fields. Furthermore, it would be interesting to examine this using a SiO2 micronutrient mixed with water and applied to the soil directly, as well as test the functional genomics and metabolomics of seedlings germinated under 0.0% and 0.4% SiO2 levels.
4. Conclusions
This manuscript researches the effects of multifactorial treatments on the behavior of the Agastache mexicana subspecies mexicana. The results constitute, undoubtedly, a vigor test of the seed lot, given that they were subjected to conditions including (a) the use of peat moss with a low level of nutrients, (b) no sterilization, and (c) water stress (waterlogging and drought). The application of AS and SiO2 supported plant survival. The emergence and mortality of seeds begin in S1 and, therefore, were a result of a test seed’s vigor due to the waterlogging effect. When conditions changed toward the drought effect, mortality increased slowly, describing an “S” double profile. The maturation and growth of seedlings and plants occurred because they developed more extensive, deeper, and thicker roots and supported the best use of water despite low-level nutrients in the substrate, as demonstrated by survival. Our final survival percentages were 15.4, 82.0, and 78.5% for AS levels of 38, 87, and 94%, respectively, and 58.3, 67.2, 64.2, and 51.5% for SiO2 levels of 0.0, 0.2, 0.4, and 0.8%, respectively. Finally, the hypothetical interaction of treatments yielded a result of 94% AS and 0.4% SiO2 as the best SIef value.
Conceptualization by J.R.-M. and R.S.-G.; Methodology by M.A.G.-S. and T.d.J.A.-Z.; Software by J.L.F.-M.; Validation of data by M.T.Z.-Á., K.A.A.-C., R.U.-P. and E.J.D.-N.; Formal Analysis by J.R.-M., J.L.F.-M., B.C.-L., E.J.D.-N. and I.M.-V.; Investigation by M.A.G.-S., T.d.J.A.-Z., R.S.-G. and J.M.-B.; Resources by J.L.F.-M., K.A.A.-C., B.C.-L., E.J.D.-N. and J.M.-B.; Data curation by R.U.-P., J.R.-M., M.T.Z.-Á., K.A.A.-C. and I.M.-V.; Writing by J.R.-M.; Writing—review and editing by J.L.F.-M.; Visualization by T.d.J.A.-Z.; Supervision by M.A.G.-S., M.T.Z.-Á. and K.A.A.-C.; Project Administration by M.A.G.-S., T.d.J.A.-Z., M.T.Z.-Á. and K.A.A.-C.; Funding Acquisition by R.U.-P. and M.A.G.-S. All authors have read and agreed to the published version of the manuscript.
We thank CONACyT for supporting this manuscript via project 3981370 as well as the research stay from Judith Morales Barrera. We are also grateful to the Instituto Politécnico Nacional, the Unidad CICATA Legaria, SIP-20231292, the authors want to honor CICATA-IPN Legaria for its 27th Anniversary; and the Universidad Autónoma de Guerrero, Facultad de Ciencias Agropecuarias y Ambientales. We are also grateful to Diatomix Company for its supply and advice on using SiO2. We also thank the master, Uriel Hernández Ramirez, for their support of this article. We appreciate the advice of engineer Emmanuel González from COSMOCEL. Finally, we are especially grateful to Kevin M. Anzzolin of Christopher Newport University, a lecturer of Spanish, for polishing the English redaction and to Flaviano Godinez Jaimes due to his support in the very valuable statistical analysis.
The authors declare no conflict of interest.
Footnotes
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Enlarge this image.Figure 1. The emergence of seeds’ dairy profile: (a) AS levels, (b) SiO2 levels. (c) AS levels in accumulated way, (d) SiO2 levels in accumulated way.
Enlarge this image.Figure 3. Mortality of plants’ double-S profile: (a) AS levels and (b) SiO2 levels.
Enlarge this image.Figure 5. Survival results by treatment are shown through (a) The number of plants and (b) The percentage of plants surviving after emergence.
Enlarge this image.Figure 6. For SIef, the efficiency values to survive can be seen. The hypothetical interaction AS = 94% and SiO2 = 0.4% had the highest value.
Treatment numbers. Input factors are three AS levels and four SiO2 levels.
| Treatments | ||||
|---|---|---|---|---|
| AS (%) | SiO2 (%) | |||
| 0.0 | 0.2 | 0.4 | 0.8 | |
| 38 | τ1 | τ4 | τ7 | τ10 |
| 87 | τ2 | τ5 | τ8 | τ11 |
| 94 | τ3 | τ6 | τ9 | τ12 |
Water irrigation profile for every experimental stage.
| Stage | S1 | S2 | S3 | S4 | S5 | S6 |
|---|---|---|---|---|---|---|
| Duration (days) | 23 | 13 | 7 | 7 | 7 | 15 |
| Accumulated (days) | 24 | 37 | 44 | 51 | 58 | 73 |
| Water irrigation (mm/day) | 7.82 | 5.86 | 3.91 | 1.95 | 1.39 | 1.11 |
Ratios to explain output factors.
| Output Factor | Ratio |
|---|---|
| SE | # emergence of seeds/# total seeds per level |
| MP | (# dead plants/total emergence of seeds)*100 |
| SP | (# survival plants/total emergence of seeds)*100 |
| MI | # dead plants/# days by stage |
| Emergence peak value | Accumulated number of seed emergences/correspondent day |
Statistical analysis: emergence, mortality, and survival values are shown for input factor interactions, AS, SiO2, and treatments.
| Output Factor |
Emergence | Mortality | Survival | ||||
|---|---|---|---|---|---|---|---|
| Level or |
** p-Value < 0.05 | Mean | p-Value < 0.05 | Mean | p-Value < 0.05 | Mean | |
| AS*SiO2 |
Whole levels | 0.76 | --- | 0.82 | --- | 0.75 | --- |
| AS (%) | 38 | 0.62 | 5.68 a | 0.0001 * | 4.81 a | 0.0001 * | 0.87 b |
| 87 | 6.25 a | 1.12 b | 5.12 a | ||||
| 94 | 6.68 a | 1.43 b | 5.25 a | ||||
| SiO2 (%) | 0.0 | 0.09 | 7.0 a | 0.32 | 2.91 a | 0.15 | 4.08 a |
| 0.2 | 4.83 a | 1.58 a | 3.25 a | ||||
| 0.4 | 7.50 a | 2.66 a | 4.83 a | ||||
| 0.8 | 5.5 a | 2.66 a | 2.83 a | ||||
| Treatments | τ1 | 0.45 | 7.25 a | 0.0006 * | 6.0 a | 0.0003 * | 1.25 bc |
| τ2 | 6.25 a | 1.50 bac | 4.75 bac | ||||
| τ3 | 7.50 a | 1.25 bc | 6.25 ba | ||||
| τ4 | 4.00 a | 3.75 bac | 0.25 c | ||||
| τ5 | 4.75 a | 0.50 c | 4.25 bac | ||||
| τ6 | 5.75 a | 0.50 c | 5.25 bac | ||||
| τ7 | 5.50 a | 4.25 bac | 1.25 bc | ||||
| τ8 | 8.75 a | 1.75 bac | 7.0 a | ||||
| τ9 | 8.25 a | 2.0 bac | 6.25 ba | ||||
| τ10 | 6.0 a | 5.25 ba | 0.75 bc | ||||
| τ11 | 5.25 a | 0.75 bc | 4.50 bac | ||||
| τ12 | 5.25 a | 2.0 bac | 3.25 bac | ||||
Note. ** p-value, * significant statistical value and mean. In Tukey’s test, the same letter means no statistically significant difference among the means.
Summary of Degree of Freedom (DF), Sum of Squares (SS), Mean Square (MS), and F valor (F) for AS, SiO2, and AS*SiO2 interactions. Output factors: emergence (E), mortality (M), and survival (S).
| Source | DF | SS | MS | F | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| E | M | S | E | M | S | E | M | S | E | M | S | |
| AS | 2 | 2 | 2 | 8.04 | 133.79 | 198.5 | 4.02 | 66.89 | 99.25 | 0.49 | 19.18 | 19.57 |
| SiO2 | 3 | 3 | 3 | 56.25 | 12.75 | 28.5 | 18.75 | 4.25 | 9.5 | 2.29 | 1.21 | 1.87 |
| AS*SiO2 | 6 | 6 | 6 | 27.62 | 9.87 | 17.5 | 4.6 | 1.64 | 2.91 | 0.56 | 0.47 | 0.57 |
| Error | - | - | - | 36 | 36 | 36 | 294 | 125.5 | 182.5 | 8.16 | 3.48 | 5.06 |
Summary of the results of emergent seeds for AS and SiO2 levels and treatments 1–12.
| Input Factor Level/Treatment | Total Seeds per Level/Treatment Sown (#) | Emergence Seeds (#) | SE (%) | Emergent Peak Value | Peak Day |
|---|---|---|---|---|---|
| 38% AS | 320 | 91 | 28.4 | 5.80 | 12 |
| 87% AS | 320 | 100 | 31.3 | 8.50 | 9 |
| 94% AS | 320 | 107 | 33.4 | 8.54 | 9 |
| 0.0% SiO2 | 240 | 84 | 35.0 | 5.69 | 9 |
| 0.2% SiO2 | 240 | 58 | 24.2 | 4.25 | 9 |
| 0.4% SiO2 | 240 | 90 | 37.5 | 6.41 | 10 |
| 0.8% SiO2 | 240 | 66 | 27.5 | 4.75 | 10 |
| τ1 | 80 | 29 | 36.2 | 1.86 | 12 |
| τ2 | 80 | 25 | 31.2 | 2.11 | 9 |
| τ3 | 80 | 30 | 37.5 | 2.33 | 9 |
| τ4 | 80 | 16 | 20.0 | 1.00 | 10 |
| τ5 | 80 | 19 | 23.7 | 1.60 | 9 |
| τ6 | 80 | 23 | 28.7 | 2.00 | 9 |
| τ7 | 80 | 22 | 27.5 | 1.47 | 13 |
| τ8 | 80 | 35 | 43.7 | 3.00 | 8 |
| τ9 | 80 | 33 | 41.2 | 2.90 | 6 |
| τ10 | 80 | 24 | 30.0 | 1.64 | 12 |
| τ11 | 80 | 21 | 26.2 | 1.90 | 9 |
| τ12 | 80 | 21 | 26.2 | 1.62 | 10 |
Note. The emergence peak value is also known as emergence energy. The day when the maximum quantity of seedlings emerges is known as the peak day.
Critical points of emergence, mortality, and survival.
| Point | Day | Total Emergent Seedlings | Total Mortality | Total Survival | Description |
|---|---|---|---|---|---|
| A | 6 | 31 | 0 | 31 | Beginning emergence |
| B | 17 | 293 | 11 | 282 | Beginning mortality |
| C | 24 | 298 | 39 | 253 | Finishing emergence |
Experimental stages and hypothetical factors that explain the output factors: emergence, mortality, and survival.
| Stage | Hypothetical Factor | Description of the Stage | Mortality Index |
|---|---|---|---|
| S1 | W | Waterlogging | 1.35 |
| S2 | W + FC | Waterlogging and beginning of field capacity | 1.46 |
| S3 | FC | Field capacity | 0.29 |
| S4 | LDS | Low drought stress | 1.43 |
| S5 | MDS | Moderate drought stress, an incipient permanent wilting point, and the beginning of epinasty | 2.0 |
| S6 | SDS + PPW | Severe drought stress, permanent wilting point, epinasty, and final survival | 2.8 |
The survival efficiency of SiO2 and AS levels.
| Silicon Dioxide Effect | |||
| SiO2% | SP | SE | Sef1 |
| 0 | 0.58 | 0.35 | 0.20 |
| 0.2 | 0.67 | 0.23 | 0.15 |
| 0.4 | 0.64 | 0.38 | 0.24 |
| 0.8 | 0.52 | 0.28 | 0.14 |
| Artificial shading effect | |||
| AS% | SP | SE | Sef2 |
| 38 | 0.15 | 0.28 | 0.04 |
| 87 | 0.82 | 0.31 | 0.25 |
| 94 | 0.79 | 0.33 | 0.26 |
Supplementary Materials
The following supporting information can be downloaded at:
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; Tania de Jesús Adame-Zambrano 4
; Edgar Jesús Delgado-Núñez 2 ; Zagaceta-Álvarez, María Teresa 5 ; Aguilar-Cruz, Karen Alicia 6 ; Urbieta-Parrazales, Romeo 7 ; Miranda-Viramontes, Isaias 3 ; Morales-Barrera, Judith 1 ; Sevilla-García, Rufina 2 ; Gruintal-Santos, Miguel Angel 1 1 Unidad Tuxpan, Facultad de Ciencias Agropecuarias y Ambientales, Universidad Autónoma de Guerrero, km 2.5 Carretera Iguala-Tuxpan, Iguala de la Independencia 40101, Mexico;
2 Facultad de Ciencias Agropecuarias y Ambientales, Universidad Autónoma de Guerrero, Periférico Poniente s/n, Iguala de la Independencia 40010, Mexico;
3 Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada Unidad Legaria, Instituto Politécnico Nacional, Miguel Hidalgo 11500, Mexico;
4 Centro Regional de Educación Superior Campus Zona Norte, Universidad Autónoma de Guerrero, Carretera Taxco-Iguala km 42 s/n, Taxco el viejo 40323, Mexico;
5 Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Azcapotzalco, Instituto Politécnico Nacional, Av. Las Granjas 682, Col. Santa Catarina, Alcaldía Azcapotzalco 02550, Mexico;
6 Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Zacatenco, Instituto Politécnico Nacional, Unidad Adolfo López Mateos Av. Luis Enrique Erro s/n, Zacatenco, Gustavo A. Madero 07738, Mexico;
7 Instituto Politécnico Nacional, Centro de Investigación en Cómputo (CIC-IPN), Av. Juan de Dios Bátiz, Esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Alcaldía, Gustavo A. Madero 07738, Mexico;