Revista Facultad Nacional de Agronomía Medellín

Plant material

Moringa seeds were collected in La Paz, Baja California Sur, México (24° 07'45.47" N and 110° 20'14.72" W). Harvesting was carried out four months before sowing, and the seeds were stored at 5 °C in a domestic refrigerator until use.

Experimental conditions

This research was developed in the Agricultural Field of the Academic Department of Agronomy of the Universidad Autónoma de Baja California Sur under semi-protected greenhouse conditions, covered with 90% residential type shade netting, located at coordinates 24°59'00" N 110°19'04" W. Temperature and humidity variations during the experiment were measured every 6 hours for each variable starting at 6:00 a.m. using a HOBO 8K Pendant, part UA-001-08, and the relative humidity using a VEE GEE digital hydrometer.

The 55-gallon plastic containers were cut in half and used for seed sowing. Eight polyethylene bags (18×26 cm) were then placed inside, containing SOGEMIX-PGM® germination substrate, which consists of fine granulated Sphagnum peat that had been moistened for 24 hours prior to filling the bags. Once filled, the bags were placed on oven-baked red clay bricks (6×12×24 cm), which were completely saturated with water. A 20 cm water film was maintained to make sure there was enough water for the plants.

Experimental design and treatments

The experiment used a completely randomized design with four replications. Treatments included a control (Tnt 1) with no extracts and distilled water irrigation, and three levels of lyophilized Spirulina application: 2 g L^-1 (Tnt 2), 4 g L^-1 (Tnt 3), and 6 g L^-1 (Tnt 4), based on Ak (2012).

Freeze-dried Spirulina powder

Freeze-dried Spirulina powder was obtained through the online store "Estrella del Sur Spice Store" (Estrella del Sur Puebla - Your Online Spice Store - Dried Chilies and Seasonings). The product was imported as "Dried Spirulina Algae Powder" by Organic Herb Trading Co®, the nutritional composition is shown in Table 1.

Table 1: Microalgae powder composition.

Preparation and application of extracts

Spirulina solutions were prepared by weighing 2, 4, and 6 g of lyophilized powder using an AWS Gemini-20 analytical balance. Each amount was then dissolved in one liter of distilled water, resulting in concentrations of 0.2, 0.4, and 0.6%, respectively.

The extract application began 2 days after 100% germination of the seeds and was repeated every 5 days, to complete a total of six applications. Each time, 25 mL of extract was added to the base of the stem of each plant.

Morphological variables

For each of the replicates in each of the treatments, 10 plants were randomly selected. Five were used for morphological measurements, and five for height measurements. Plant growth was monitored by height, and then plants were chosen randomly before applying the extract. In total, 20 plants were measured per treatment.

The height (cm) was considered from the base of the stem to the apical bud, taking the first measurement before the first application of the extract, and then every 5 days for 45 days. After 45 days, leaves were counted, and stem thickness was measured with a digital Vernier at 5 cm above the root collar. The length of the root was measured, from the collar to the cap, and the stem and root length values were used to calculate the stem/root ratio.

The robustness index was calculated by combining plant height and root collar diameter using Equation 1:

Leaves, stems, and roots were collected and dried to constant weight. Then, the dry weight of each fraction was used to calculate quality indices as presented in Equations 2, 3, 4, and 5. The Dickson index (DI) and lignification index (LI) were calculated as described by Equations 6 and 7, respectively.

Dry Matter (DM) yield of leaves and whole plant

Dry weight values of leaves and stems were used to determine the percentage of DM according to the following Equation 8:

Where the FW is the fresh weight of the sample and the DW is the dry weight of the sample.

Morphophysiological variables

After 45 days, the length (cm) and width (average of the base, middle, and apical portions) of the first imparipinnate leaf were measured using a digital Vernier with a precision of 0.01 mm. In each treatment, the mean and longitudinal values of the leaves were determined, and the Leaf Area (LA) was calculated using multiple regression Equations (Table 2).

Table 2: Multiple regression expressions for calculating Leaf Area in each treatment.

From the LA value, the following were calculated: Leaf Area Duration (LAD) and Leaf Area Index (LAI) according to Equations 9 and 10.

Where LA is the leaf area; T1 is the start of plant growth, T2 is at the end of the experiment (45 days) and S is the area of soil covered.

Plant height measurements taken every 5 days after application of the first inoculum were used to estimate the Absolute Growth Rate (AGR) and Relative Growth Rate (RGR), described in Equations 11 and 12.

When relating FA, fresh weight of leaves, stems, roots, and the entire plant as the sum of the weight of the organs mentioned, the following variables are presented in Equations 13, 14, and 15.

Statistical analysis

A one-way ANOVA was performed by Statistic v 12.0, normality of the data was checked using the Kolmogorov-Smirnov test, homogeneity of variance was checked using the Bartlett criterion, and the Duncan test with a 95% confidence interval was used for the comparison of means.

An Analysis of Covariance (ANCOVA) was performed for plant height, with the height before treatment application (Spirulina extracts) as the covariate and final height as the dependent variable. Linear regression and correlation were used to verify the dependence and multicollinearity between the dependent variable and the covariate. The normality and homoscedasticity of the data were tested using the Kolmogorov-Smirnov and Shapiro-Wilk tests, respectively. The analysis was conducted using the following mathematical model (Equation 16):

Where μ is the model average, Ti is i-th treatment; b is the model constant, Xj is j-th height, and e is the estimation error.

Foliar area estimation was developed using multiple regression equations based on the following mathematical model (Equation 17):

Where Y_i is the represents FA as dependent variable, β₀ is Y- intercept or origin coordinate, β₁, β₂, β₃…β_k are slopes of the equation, X_1i is the average effect of the average of the variable leaf length, X_2i is the average effect of the average of the leaf width variable, X_3i is the average effect of the average of the leaf area variable, β_k X_ki is the regression line of Y on X₁, X₂, X₃…… X_k and ε_i is the error for each independent variable.

The analysis was performed using non-linear regressions (Equations 18, 19, and 20) between plant age and height to determine the curve that best fits shoot growth. Non-linear models were used, which are listed below:

Where Y is the growth of the organism over time t, a is the maximum asymptotic growth, when t tends to infinity, b is the curvature parameter that expresses how fast it reaches maximum growth or lag time, c is the growth rate, and T is the time in days.

Where Y is the time response variable (t), a is the maximum growth and determines an asymptotic point, b is the positive number that shifts the model left or right, and c is the sets the intrinsic rate of growth.

Where Y is the length of the individual at time (t), a is the maximum length of the individual (maximum asymptote), c is the curvature parameter that expresses how quickly the length reaches its maximum value and T is the time.

The model selection was based on a high R² value, strong statistical significance, low standard error of the parameters, estimates, the smallest mean square error, and a significant contribution of the equation parameters.

Goodness-of-fit criteria and growth models analysis

Among the goodness-of-fit criteria, an increase in mean square error (MSE) was observed across levels, suggesting that Spirulina extracts influenced growth rates. This effect suggests a direct relationship between applied doses and the availability of nutrients, especially nitrogen. Similarly, studies have shown that microalgae extracts affect plant physiological activity, hormone regulation (Issa et al. 2019), and exposure to polysaccharides and oligosaccharides.

The contribution of the model parameters was highly significant (P=0.001) for the experimental treatments and the control. The latter obtained the lowest explanatory value of the model (R² _adjusted=93%; Figure 2A), while in the experimental treatments, growth promotion was reflected in explanatory fits of the model between 95-97% as described by the Gompertz model (Tjørve and Tjørve 2017).

This behaviour reflects the prioritization of the seed's energy reserves for germination, emergence, and early growth. Moringa seeds are rich in essential oils, which serve as the primary carbohydrate reserve for radicle emergence and initial plant development, like other oil-bearing species (Ledea-Rodríguez et al. 2022). In this context, experimental treatments may have enhanced this process by increasing the availability of enzymatic precursors from trace minerals (Alfadhly et al. 2022), leading to a higher enzymatic activity that supports germination and early growth (Marjanović et al. 2024).

The logistic model (Figure 2B) displayed a convex curve with an exponential trend, improving in fit as the concentration of Spirulina extracts increased. The best fit was observed at 6 g L^-1 (adjusted R²=97%), followed by 4 g L^-1 (90%), while the control and 2 g L^-1 doses showed similar fits (87 and 89%, respectively). These results suggest a direct link to the bioavailability of nutrients, cofactors, and enzymatic precursors in the rhizosphere. According to Shahrajabian et al. (2021), these compounds-amino acids and soluble peptides-promote the synthesis of growth-related metabolites, acting similarly to plant hormones, which supports the validity of the logistic model in this study.

The Von Bertalanffy model showed an R²_adjusted between 91 and 97% fit, ranging from the experimental control to the 6 g L^-1 Spirulina extract dose. Since this model had the highest fit and the best-adjusted descriptors among the three models, it can be inferred that Moringa plants allocate cotyledon reserves to the development of aerial organs while simultaneously maintaining active growth. This behaviour aligns with the premise of the Von Bertalanffy model, which describes growth as a balance between metabolism and catabolism (Bertalanffy 1957). In this context, Spirulina extracts appear to enhance this process by improving enzymatic, metabolic, and hormonal efficiency, while also providing essential trace elements such as Fe, Cu, Zn, and Mn (AlFadhly et al. 2022).

Morphological development of the plant

Morphological analysis of the plant (Figure 3) showed that the average leaf width was the only variable affected by the experimental treatments. Plants that were biostimulated with 4 g L^-1 increased the average leaf width by 13.44 and 16.30% significantly (P<0.05), compared to the absolute control (AC) and those biostimulated with 2 g L^-1, respectively (Figure 3C).

Figure 3: Leaf and stem morphology of M. oleifera plants at 45 days of age biostimulated with Spirulina extract. a, b Values with different superscript letters in each column are significantly different at P<0.05 according to Duncan's test; significance for average leaf width was reached using √(x+2.75).

This result is particularly relevant, as Moringa leaves contain a wide range of biologically significant compounds that are essential for human and animal nutrition. In addition to synthesizing bioactive compounds for plant growth and development through photosynthesis, leaf width expansion is closely linked to growth conditions, especially light intensity and irradiance (Azcón-Bieto and Talón 2013). In this study, the 4 g L^-1 concentration appeared to promote this change, likely due to a hormonal effect. This may be attributed to the extract's diverse composition, which could regulate auxin-sensitive genes, either enhancing or inhibiting their expression.

The remaining morphological variables were not significantly affected by the treatments (P>0.05). The number of leaves ranged from 12.4 to 14.2 (Figure 3A), while leaf length varied between 113.2 and 128.7 mm (Figure 3B). Stem thickness ranged from 4.7 to 5.48 mm (Figure 3D), and the leaf-to-stem ratio remained between 0.39 and 0.45 (Figure 3E), a favorable outcome as it maintains the proportional distribution of these organs, which defines the plant's nutritional value. Dry biomass yield (DBY) (Figure 3F) ranged from 0.41 to 0.69 t DBY ha^-¹ (leaves) and 4.4 to 4.79 t DBY ha^-¹ (whole plant).

Studies on Moringa crops under field conditions report dry matter (DM) yields of up to 6.61 t DM ha^-¹ when fertilized with cattle manure; however, this fertilization method is not ideal for Moringa forage production, as nutrient release is slow (Yalta Vela et al. 2024). Moringa grows rapidly and undergoes early structural modifications, including changes in the leaf-to-stem ratio, making timely nutrient availability crucial for optimal development.

Ledea-Rodríguez et al. 2022 considered the 1:1 ratio ideal for 45-day-old plants, though the leaf-to-stem ratio in this study remained balanced but was below 1. This limitation could potentially be overcome by increasing the concentration of antioxidants or nutrient compounds in the leaves. However, several factors must be considered, including differences in experimental conditions, spatial arrangement of trials, source of raw materials or experimental products (bio-stimulants, biofertilizers, or bio-inputs), soil and climate characteristics (Shahrajabian et al. 2021). Additionally, the genetic origin of the Moringa species plays a crucial role in determining the observed effects and outcomes compared to other studies (Peter et al. 2023).

Some leaf and growth indicators were affected by the Spirulina extracts (Table 3). Plants biostimulated with 2 g L^-1 of extract showed a 34.06 and 70.17% increase in fresh weight (FW) compared to the absolute control (AC) and those treated with 6 g L^-1 (P<0.001).

Table 3: Physiological leaf and growth indicators in 45-day-old M. oleifera plants biostimulated with Spirulina extracts.

The control plants (AC) showed a 12.34% increase in leaf area (LA) compared to those biostimulated with 6 g L^-1 of microalgae extract (P<0.001) (Table 1). This effect was also observed in other variables such as LAF, DFA, and ELA, which were promoted by the 2 g L^-1 treatment compared to the AC. For LAI and DFA, the remaining treatments did not show significant differences (P>0.05) from the AC. However, the plants biostimulated with 2 g L^-1 increased the EFA by 64.8% (P<0.05) compared to those treated with 6 g L^-1. Meanwhile, NAR and LAR did not show any significant differences (P>0.05) in this study. Together, these variables are used to evaluate various agronomic traits that help us understand gas exchange and energy transformation into biomass.

Plants biostimulated with 6 g L^-1 produced 64% more leaves than those treated with 2 g L^-1 (P<0.05). However, no significant differences were found compared to the control plants (AC) (P>0.05). These positive effects are linked to the properties of microalgae cells, as shown in various studies (Parmar et al. 2023), which help improve the physiological and metabolic processes in M. oleifera plants. In this study, doses of 2 and 6 g L^-1 increased the number of leaves while also causing a reduction in leaf size. This could benefit the plant's efficiency by improving gas exchange (Drake et al. 2013), photosynthesis, and its ability to tolerate stress. The morphology and physiology of the leaves have direct implications for leaf structure, as indicated by variables such as leaf area (LA), leaf area index (LAI), duration of leaf area (DLA), and effective leaf area (ELA).

Stems and roots proportion was not significantly affected by the treatments (P>0.05), showing a morphological development that could favor forage production based on the number of leaves and fewer stems, a desired structure for plants used for animal and human consumption. Also, modifications were observed in root morphology and plant quality indicators due to the effects of Spirulina extracts. Plants bio-stimulated with 2 and 4 g L^-1 showed an 18% increase in root collar diameter (P<0.01) (Figure 4A) compared to the control and plants treated with 6 g L^-1.

The increased root collar diameter suggests greater resistance in the plant, enhancing its survival under field and extensive cultivation conditions.

Root thickness was significantly reduced by 33.6% (P<0.001) in plants bio-stimulated with 6 g L^-1 compared to the other experimental treatments and the control plants (AC), with no significant differences observed among the latter (P>0.05) (Figure 4B). No significant differences were found for root length, fresh and dry weight, and the stem/root ratio (P>0.05). Their average values ranged from 75.8 to 90.42 cm (Figure 4C), 32.5 to 74.6 g, and 2.7 to 8.2 g (Figure 4E), and 10.8 to 18.8 mm (Figure 4D), respectively.

Figure 4: Root morphology and quality indices in 45-day-old M. oleifera plants biostimulated with Spirulina extracts. a, b, c Superscript letters with different values in the same row indicate significant differences at P<0.05 according to Duncan's test. *1 Transformed using √(x+5.5); *2 Transformed using √(x). ADB/RDB: Aerial dry biomass/Root dry biomass; ±SE: Standard error.

Regarding the variables that describe seedlings, the robustness index increased by 13-23% with the 6 g L^-1 application compared to the control (AC) and the 2 g L^-1 treatment (P<0.002). In its interpretation, values below 6 are considered robust, while those above 6 are weaker. For this study, these plants likely have low lignin content in their stems, which improves their nutritional value. The lignification and Dickson indexes were not significantly affected by the treatments (P>0.05), with values ranging from 0.15 to 0.16 (Figure 4H) and 4.5 to 6.7 (Figure 4I), respectively.

The results for photosynthetic pigment content as part of the antioxidant profile were encouraging (Figure 5). Chlorophyll α, β, and total chlorophyll levels increased by 7, 16.6, and 11.4%, respectively, for all experimental treatments compared to the control (AC) (P<0.05). The AC showed a higher ratio of chlorophyll α to β, by 14-15%, compared to the 2 and 6 g L^-1 treatments, respectively (P<0.01).

Figure 5: Chlorophyll content in the leaves of 45-day-old M. oleifera plants biostimulated with Spirulina extracts.

Similar results have been reported in Vicia faba L. crops (el-Sheekh and el-Saied A el-D 2000), V. faba and Helianthus (Mohammed et al. 2023), bio-stimulated with marine algae extracts. The effects on photosynthetic pigment content from microalgae extracts are linked to the presence of betaines (Baroud et al. 2019), and their ability to capture ions and increase leaf pigmentation (Mohammed et al. 2023). Other authors associate these effects with the availability of sugars, which serve as structural and storage compounds, respiratory substrates, intermediate metabolites in various metabolic activities, signaling molecules, and transporters (Ciereszko 2018). These compounds contribute to the plant tissue, enhancing new characteristics such as functional food or nutraceutical properties.