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Article

Synergic Effects of the Microbial Consortium and Amino Acid-Based Growth Promoter in Sunflower Productivity Under Water-Deficit Conditions

by
Alexander Calero Hurtado
1,2,*,
Kolima Peña Calzada
3,
José Vitor Botter Fasoli
4,
Janet Jiménez
5 and
Lianny Sánchez López
6
1
Centro Universitario Municipal de Taguasco, Universidad de Sancti Spíritus “José Martí Pérez” (UNISS), Zaza del Medio, Sancti Spíritus 62300, Cuba
2
Programa de Pós-Graduação em Biologia Vegetal, Departamento de Botânica e Ecologia, Instituto de Biociências, Universidade Federal de Mato Grosso, Cuiabá 78060-900, MT, Brazil
3
Facultad de Ciencias Agropecuarias, Universidad de Sancti Spíritus “José Martí Pérez” (UNISS), Sancti Spíritus 60100, Cuba
4
Programa de Pós-Graduação em Ecologia e Conservação da Biodiversidade, Instituto de Biociências, Universidade Federal de Mato Grosso, Cuiabá 78060-900, MT, Brazil
5
Unidad de Desarrollo e Innovación-Centro de Estudios de Energía y Procesos Industriales, Universidad de Sancti Spíritus “José Martí Pérez” (UNISS), Sancti Spíritus 60100, Cuba
6
Colégio Técnico da UFMG (COLTEC), Universidade Federal de Minas Gerais (UFMG), Belo Horizonte 31270-901, MG, Brazil
*
Author to whom correspondence should be addressed.
Water 2025, 17(9), 1365; https://doi.org/10.3390/w17091365
Submission received: 9 April 2025 / Revised: 29 April 2025 / Accepted: 29 April 2025 / Published: 1 May 2025
(This article belongs to the Section Soil and Water)

Abstract

:
Water deficit is a global problem, restricting worldwide food production, and climate change has exacerbated these conditions. Therefore, the objective of this study was to investigate the beneficial effects of the combined inoculation with the microbial consortium and foliar spraying with a mixture of amino acid-based growth promoter in improving morpho-physiological and productive responses of the sunflower (Helianthus annuus L.) under water-deficit conditions. The field experiment involved three microbial consortium (MC) concentrations (MC-uninoculated, MC inoculation at 100 mL m−2, MC inoculation at 200 mL m−2), and two mixture of amino acid-based growth promoter (AAGB) doses (AAGB at 0.25 and AAGB at 0.50 L ha−1) in a split-plot design with five replications for improving sunflower growth, physiological and yield responses under water-deficit conditions. The findings of this study highlight the synergic role between microbial consortium and foliar spraying of a mixture of amino acid-based growth promoter in regulating the drought-stress response of sunflower, suggesting that they are involved in morphophysiological responses, thereby increasing sunflower productivity and quality. Lastly, the use of the best strategy to mitigate the adverse effects of water deficit could permit new management alternatives to increase food production and sustainable agriculture.

1. Introduction

Climate change frequently impacts attempts to maintain and improve food production in various areas. Food security is impacted by the more severe yield reactions to rising temperatures, rising carbon dioxide levels, and changes in water availability, salinity, and insect infestations [1]. Climate change negatively affects water resources, with agriculture being the largest global water user, significantly influenced by population growth and socioeconomic development [2]. Extreme fluctuations in temperature and precipitation significantly impact plant-water physiological processes [3,4]. Consequently, increasing agricultural water scarcity may jeopardize food production and, in turn, threaten food security, particularly for impoverished populations [5].
Water deficit is a multidimensional stressor that affects plants at several organizational levels. Drought causes fundamental changes in water interactions, metabolic and physiological processes, membrane structure, and the ultrastructure of subcellular organelles [6]. In addition, water deficit restrains plant growth and may inhibit plant respiration, photosynthesis, and stomatal movement, impacting plant growth and metabolic function [5]. Additionally, other indicators of water deficiency include reduced plant height, wilting leaves, decreased leaf quantity, smaller surface area, and leaf senescence. These factors lead to shortened cell expansion and enlargement, increased leaf shedding, and reduced mitosis, which directly disrupt plant photosynthesis and yield [2]. Moreover, drought stress reduces cuticle thickness, which increases plant water evaporation [7]. Furthermore, low water availability directly decreases photosynthesis by lowering CO2 availability, limiting the diffusion of stomata and mesophyll [8].
Plants have evolved several mechanisms against water scarcity, including tolerance, drought escape, and avoidance of tissue and cell dehydration. In addition, plants activate several key mechanisms, including morphological and structural changes, drought-resistant gene expression, hormone synthesis, and osmolyte production [7]. The primary strategy for reducing drought stress is to maintain cell turgor during osmotic adjustment (OA), which allows for water absorption and the preservation of plant metabolic activity, boosting growth and production [9]. Likewise, the accumulation of suitable osmolytes (i.e., proline and glycine betaine) is a key process by which plants attenuate drought stress [10]. Furthermore, the osmotic kind of cytoplasm is largely controlled by organic osmotic regulating agents, including amine compounds (glycine betaine and polyamines), amino acid compounds (proline), and solutes such as trehalose, fructan, and mannitol [11].
Sunflowers are an essential, sustainable crop for seed and oil production. Despite being a relatively drought-tolerant crop, extreme water shortage reduces growth, seed, and oil production [12]. Moderate to severe water deficiencies decrease leaf area, leaf chlorophyll content, photosynthesis and ultimately lower grain yield. Several studies highlight that water deficit affects the sunflower’s morphological (e.g., reduced growth parameters like plant height, leaf area, etc.), physiological, and biochemical aspects (i.e., photosynthesis, water relations, nutrient uptake, and oxidative damage), and a reduced yield and oil quality [7]. Actually, numerous options are becoming popular as efficient ways to reduce drought stress in different plant species, such as drought-resistant crop varieties, innovative biotechnological techniques like CRISPR-Cas9 genome editing and microbial biotechnology, sustainable agricultural methods like conservation tillage, intercropping, and crop residue management, as well as biostimulants, beneficial nutrients, or alternative growth enhancers [13].
Biostimulants play an important role in mitigating drought stress by enhancing root growth and water uptake, water use efficiency, and activating biochemical and genetic pathways, which contribute to eco-friendly farming practices [14,15]. A biostimulant refers to a substance or microorganism that enhances plant nutrition and increases tolerance to abiotic stress, thereby ultimately boosting plant productivity [16]. Microbial biostimulants include mycorrhizal and non-mycorrhizal fungi, bacterial endosymbionts (like Rhizobium), and plant growth-promoting rhizobacteria (PGPR), which have a dual role as both biocontrol and biostimulant effects [17]. Furthermore, the MC lessens the effects of drought stress on sustainable farming by enhancing root performance, boosting metabolic processes, nutrient uptake, and soil interactions [18]. Moreover, among the most significant impacts of using MC is the capacity to fix nitrogen and nutrient solubilization (e.g., phosphorus), which increases nutrient availability to growing plants [14,19]. Furthermore, the application of MC has been shown to improve growth and productivity in drought-stressed plants, including maize [20], wheat [21], and rice [22].
Growth-promoting substances play a vital role in attenuating drought stress in plants. These substances can be applied exogenously or produced by PGPR to support sustainable agriculture in drought-prone areas [23]. These substances include phytohormones (like auxins, gibberellins, cytokinins, and abscisic acid), amino acids [e.g., proline, glycine betaine, γ-aminobutyric acid (GABA), arginine, glutamate, and chitosan], and mineral elements (i.e., nitrogen, calcium, and silicon), which enhance plant physiological and biochemical responses during water scarcity [24]. Among these compounds, amino acids are biologically active substances that stimulate plant growth and increase plant responses to biotic and abiotic stresses [25]. Exogenous application of amino acids induces drought tolerance in plants following several mechanisms: (i) increasing osmotic adjustment by increasing proline and glycine betaine accumulation, which maintains cell turgor; (ii) regulation of the antioxidant enzymatic and non-enzymatic activities due to over oxidative stress; (iii) improving nutrient uptake, and (iv) activation of many stress-response genes, enhancing stress signaling and adaptation [26].
These mechanisms make amino acid-based growth promoters and MC one viable strategy for improving plant tolerance to water-deficit conditions. Although their individual effects are well documented. However, their synergistic potential under combined application remains underexplored, this study aimed to investigate the combined effects of the MC inoculation and foliar spraying of a mixture of amino acid-based growth promoters on morpho-physiological traits and productive responses in sunflower plants under water-deficit conditions.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

Helianthus annuus ‘Caburé-15’ plants were employed in the field experiment from January to May 2024 at the research area of Agroindustrial Sugar Company “Melanio Hernández”, Tuinucu (22°00′56″ N 79°24′49″ W), Sancti Spíritus, Cuba. All agronomic practices, including soil preparation, weeding, and furrowing, were performed on the land before seed preparation. Seeds were selected by uniform color and size and placed manually at the furrow bottom in groups of two to three per space, according to the prepared sowing distances. Ten days after emergence, uniform thinning was conducted to reduce the number of plants and retain only one plant per location for establishment, resulting in approximately 40,000 plants ha−1. Throughout the experiment, daily measurements of temperature, relative humidity, and precipitation were recorded (Figure 1).

2.2. Experimental Design

The field measuring 90.00 m × 10.00 m was divided into thirty plots, each with dimensions of 10 m × 3 m, while maintaining a distance of 1.00 m between the plots. The experiment was carried out as a split-plot, in a randomized complete block design with five replications. Main plots were three MC concentrations [0 (MC-uninoculated), 100, 200 mL m−2]. Subplots were two mixtures of AAGB (0.25 and 0.50 L ha−1) with a size of 5.00 m2.

2.3. Amino Acid and MC Treatments and Water-Deficit Conditions

Following seed sowing, MC was inoculated in the furrow at 100 and 200 mL m−2 and promptly covered with soil [27,28]. For the foliar spraying (see details in Figure 1), sunflower plants were sprayed from the bottom to the top with both doses of 0.25 and 0.50 L ha−1 AAGP every seven days between 8:30 and 9:30 a.m., after the dew had evaporated and wind drift was avoided. Foliar spraying was started in the vegetative stage V2 and ended on V8 [29]. MC and AAGP treatments were applied with backpack sprayer 16 L (Matabi, Goizper Group, Antzuola, Spain). In our research, we avoided irrigation following seed sowing to simulate water-deficit conditions, depending exclusively on natural rainfall for impact assessment. After 96 DAS, we recorded the first rainfall of 2.8 mm, and the total rainfall was 15.52 mm until the end of the experiment (see Figure 1).

2.4. Amino Acids and MC Composition

Aspartic acid (1.6% m/m), Arginine (2.5% m/m), Glycine (2.4% m/m), and Tryptophan (0.5% m/m) are mainly a mixture of the AAGP composition (commercialized as VIUSID® agro, Catalysis, Madrid, Spain) [24,25]. The microbial consortium is composed of the following bacteria species: Bacillus subtilis nato B/23-45-10 (5.4 × 104 colony forming units (CFU)/mL), Lactobacillus bulgaricum B/103-4-1 (3.6 × 104 CFU/mL), and Saccharomyces cereviciae L-25-7-12 (22.3 × 105 CFU/mL), with a quality certificate distributed by the Instituto Cubano de Investigaciones de Derivados de la Caña de Azúcar (ICIDCA), Cuba, with R-ID-B-Prot-01-01 code [27].

2.5. Sampling Procedures

Sampling (10 randomized plants per plot) was measured at different crop growth stages, including the vegetative growth and maturity/harvest in the useful area per plot. At 30 and 60 days after seeding (DAS), the following growth parameters were determined: Plant height (PH, cm) was measured from the stem base to apical tip with a millimeter tape. Relative Growth (RG) was determined using PH at 30 and 60 DAS using the following equation:
RG = (PH2 − PH1)/PH1
where RG is plant relative growth; PH1 is plant height measured at day 30 DAS, and PH2 is plant height measured at day 40 DAS.
Leaf area index (LAI, cm2) was calculated in 10 plants per plot according to the following Equation (2):
LAI = ∑ (l × w) × f
where: l is the length of each leaf; w is the width of each leaf; and f is the constant factor equal to 0.66 previously determined by Kemp [30]. Total chlorophyll content (TCC, SPAD values) was measured with a portable chlorophyll meter (model TYS-B, Lab Equipment—hinotek, Shangai, China) on leaf +1 between 10:00–11:00 a.m.
The leaf relative water content (LRWC) of sunflower plants was determined following the method of Barrs and Weatherley [31]. Briefly, six leaf disks (0.5 cm in diameter) were obtained from the middle of fully developed leaves. Then, leaf fresh mass (FW) samples were measured, and leaf disks were immersed in distilled water using a Petri dish for 6 h. After this time, the leaf disks were removed and blotted dry, and then the leaf turgid mass (TM) was measured. The samples were then dried to a constant weight in an oven at 60 °C, and dry mass (DM) was measured. Finally, the LRWC of the leaf was calculated using Equation (3):
LRWC (%) = [(FM − DM)/(TM − DM)] × 100
Aboveground biomass (AB) was determined at 30 and 60 DAS, respectively. In both periods, the stems and leaves of 10 plants per plot were collected and placed into paper sacks. Then they were dried using a forced ventilation oven (MJW WS 100, Memmert’s, Berlin, Germany) at 60 °C until constant dry mass was obtained. Subsequently, the aboveground biomass (AB) was weighed in a digital microscale (0.1 mg; CPA224S, Sartorius, Göttingen, Germany).
Growth indices were determined as described as follows: leaf area ratio (LAR, cm2 g−1) was calculated as expressed by the Santos et al. [32] method (Equation (4)). Net Assimilation Rate (NAR, g cm2 week−1) and relative growth rate (RGR, g g−1 week−1) were calculated using the previously method of Kozlowski et al. [33], equations 5 and 6, respectively, where LA1 and LA2 are leaf areas at 30 and 60 DAS, DM1 and DM2 are the dry mass at 30 and 60 DAS, and t1 and t2 are the dates of sampling (i.e., 30 and 60 DAS).
LAR= ½ (LA1/AB1+LA2/AB2)
NAR = ((DM2 − DM1)/(t2 − t1)) × (ln LA2 − ln LA1)/(LA2 − LA1)
RGR = NAR × LAR
Plants were harvested at physiological maturity stage (R9, 115 DAS), and the following production parameters were assessed: Total seeds per head (SH), full seeds per head (FSH), and empty seeds per head (ESH) were performed by direct counting in each head. Seed mass per head (SMH, g) was carried out by weighing all seeds of each head in a micro scale (model BS 124S and precision ± 0.01 g). Yield (SY, t ha−1) was determined using the seed mass and the number of plants ha−1.

2.6. Data Analysis

Growth and productivity parameters were tested for normality and homogeneity of variance with the Shapiro-Wilk and Levene tests, respectively. After assuming the previous test, the data were analyzed by a two-way ANOVA. Then, if the Fisher test (F) showed significance (p < 0.05), the Tukey test was employed to compare the averages (p < 0.05). All statistical analyses were conducted using R software version 4.3 [34].

3. Results

3.1. Impact of MC and AAGB Treatments on Sunflower Growth Under Water-Deficit Conditions

Combined MC and AAGB treatments showed significant interaction on plant height (PH, p < 0.01) at 30 and 60 DAS (Figure 2a,b) and relative growth (RG, p < 0.01) (Figure 2c). At both 30 and 60 DAS, the PH was significantly (p < 0.01) greater in the 0.50 L ha−1 of AAGB treatment compared to the 0.25 L ha−1 treatment in all MC treatments (Figure 2a,b). On the other hand, at 30 DAS, the 100 mL m−2 of MC treatment significantly (p < 0.01) increased the PH by 24% and 16% under 0.25 L ha−1 of AAGP and by 19% and 10% under 0.50 L ha−1 of AAGP compared to the MC-uninoculated and 200 mL m−2 treatments, respectively. However, the PH was higher by 10% in the 200 mL m−2 MC treatments over the MC-uninoculated (p < 0.01; Figure 2a). Similarly, at 60 DAS, the PH was higher in plants inoculated with 100 mL m−2 of MC by 29% and 19% under 0.25 L ha−1 of AAGP treatment and by 23% and 14% under 0.50 L ha−1 of AAGP treatment, respectively, compared to the MC-uninoculated and 200 mL m−2 treatments. Nonetheless, the PH was increased significantly (p < 0.05) in the 200 mL m−2 of MC treatment with respect to the MC-uninoculated under both 0.25 and 0.50 L ha−1 of AAGP treatments (Figure 2b). We also observed that RG followed a similar response pattern to PH during the assessed period (p < 0.05; Figure 2c).
In sunflower plants, the leaf area index (LAI) showed a significant (p < 0.05) interaction between AAGP and MC treatments both at 30 and 60 DAS (Figure 3a,b). At 30 and 60 DAS, the LAI was significantly (p < 0.01) higher in the 0.50 L ha−1 AAGP treatment than in the 0.25 L ha−1 AAGP treatment in all MC treatments (Figure 3a,b). Similarly, the higher LAI at 30 DAS was achieved under 100 mL m−2 of MC treatment at both AAGP doses, with increases of 26% and 10% under 0.25 L ha−1 of AAGP treatment and of 17% and 11% under 0.50 L ha−1 of AAGP treatment, respectively, compared to the MC-uninoculated and 200 mL m−2 treatments. However, plants inoculated with 200 mL m−2) showed significant (p < 0.05) effects in comparison with the MC-uninoculated plants (Figure 3a,b).
The aboveground biomass (AB) accumulation showed a significant (p < 0.05) interaction during both sunflower growth periods (30 and 60 DAS) under different AAGP and MC treatments (Figure 3c,d). In addition, at 30 and 60 DAS, the AB accumulation increased significantly (p < 0.05) due to the application of 0.50 L ha−1 of AAGP when compared with the application of 0.25 L ha−1 of AAGP in all MC concentrations (Figure 3c,d). Additionally, at 30 DAS, the AB in the 100 mL m−2 of MC treatment significantly (p < 0.01) increased by 32% and 13% in 0.25 L ha−1 of AAGP and by 31% and 17% in 0.50 L ha−1 of AAGP, respectively, In all MC treatments (Figure 3c). Nonetheless, at 60 DAS, the AB was higher in the 100 mL m−2 of MC treatment by 22% and 10% under 0.25 L ha−1 of AAGP and 19% and 12% under the 0.50 L ha−1 of AAGP treatment than in MC-uninoculated and 200 mL m−2 of MC treatments, respectively (Figure 3d). Furthermore, the AB was significantly (p < 0.01) higher in the 200 mL m−2 of MC treatment than in the MC-uninoculated plants on both AAGP treatments (Figure 3c,d).
The growth index showed significant (p < 0.05) interaction on sunflower plants under the 30 to 60 DAS period (Figure 4). Net assimilation rate (NAR), leaf area rate (LAR), and relative growth rate (RGR) showed a similar response pattern during the sunflower growth period evaluated (Figure 4a–c). In addition, applying 0.50 L ha−1 of AAGP showed higher increase in NAR, LAR, and RGR than in 0.25 L ha−1 of AAGP treatment in all MC concentrations (Figure 4a–c). Likewise, in both AAGP treatments, the NAR, LAR, and RGR in the 100 mL m−2 of MC treatment were significantly (p < 0.05) increased compared to the MC-uninoculated and 100 mL m−2 of MC treatments (Figure 4a–c).
For the total chlorophyll content (TCC), there was a significant (p < 0.05) interaction between AAGP and MC treatments in both 30 and 60 DAS (Figure 5a,b). Also, applying 0.50 L ha−1 of AAGP promoted higher TCC with a significant (p < 0.01) difference than in 0.25 L ha−1 of AAGP treatment in all MC treatments (Figure 5a,b). Similarly, the TCC was significantly (p < 0.05) increased in the 100 mL m−2 of MC compared to the MC-uninoculated and 200 mL m−2 of MC treatments at both 30 and 60 DAS. Whereas, the TCC in both AAGP was higher in the 200 mL m−2 of MC treatment than in the MC-uninoculated treatment (Figure 5a,b). Additionally, leaf relative water content (LRWC) showed significant (p < 0.01) interaction between AAGP and MC treatments (Figure 5c). The LWRC was higher in the 0.50 L ha−1 of AAGP treatment in all MC treatments and showed a significant (p < 0.01) difference than in 0.25 L ha−1 of AAGP treatment (Figure 5c). Meanwhile, in the two AAGP treatments, the TCC showed similar effect in the 100 and 200 mL m−2 of MC treatments and were significantly (p < 0.01) higher than in the MC-uninoculated treatment (Figure 5c).

3.2. Impact of MC and AAGB Treatments on Sunflower Productivity Under Water-Deficit Conditions

Seed production is an essential component of yield. We observed that the average seed per head (SPH) showed a significant (p < 0.01) interaction between AAGP and MC treatments (Figure 6a–c). The total seeds per head (TSH), full seeds per head (FSH), and empty seeds per head (ESH) were significantly (p < 0.01) higher under 0.25 L ha−1 of AAGP treatment in all MC concentrations than in the 0.50 L ha−1 of AAGP treatment (Figure 6a–c). Moreover, the TSH and FSH were significantly increased in the 100 mL m−2 of MC treatment in comparison with the MC-uninoculated and 200 mL m−2 of MC treatments in both AAGP treatments (Figure 6a,b). Furthermore, in the two AAGP treatments, the ESH was significantly (p < 0.01) lower in the 100 mL m−2 of MC treatment than in the MC-uninoculated and 200 mL m−2 of MC treatments. At the same time, the ESH showed higher ESH in the 200 mL m−2 of MC treatment than in the MC-uninoculated treatment (Figure 6c).
The data presented in Figure 7 indicated a significant interaction between MC and AAGP treatments on seed mass per head (p < 0.01, SMH) and seed yield (p < 0.01, SY). The SMH was significantly (p < 0.01) increased in the 0.25 L ha−1 of AAGP treatment compared to the 0.25 L ha−1 AAGP treatment in all MC treatments (Figure 7a). Also, in all AAGP treatments, the SMH was higher in the 100 mL m−2 of MC treatment than in the other MC treatments. However, at the same time, under 200 mL m−2 of MC treatment, the SMH was significantly (p < 0.01) increased when compared to the MC-uninoculated treatment (Figure 7a). Consequently, the SY was higher by 0.25 L ha−1 of AAGP treatment in all MC concentrations than in the 0.25 L ha−1 of AAGP treatment in all AAGP treatments (p < 0.01; Figure 7b). Additionally, the SY was increased in the 100 mL m−2 of MC treatment by 22% and 12% under 0.25 L ha−1 of AAGP treatment and by 39% and 14% under 0.50 L ha−1 of AAGP treatment, respectively, compared to the MC-uninoculated and 200 mL m−2 of MC treatments. Furthermore, this last treatment (200 mL m−2 of MC) exhibited higher SY than in the MC-uninoculated treatment (p < 0.01; Figure 7b).

4. Discussion

Water scarcity or drought is one of the environmental factors that most suppresses or limits plant growth and development. The first symptom that plants show is an overall decrease in external morphology [35]. In agreement with our findings, previous studies have shown that drought stress decreases sunflower growth [36,37,38]. The plant growth is significantly affected by water deficit, which is associated with cell growth and leaf senescence [7]. Additionally, the plant growth reduction under drought is highlighted by impaired mitosis, increased leaf shedding, decreased cell expansion and leaf area, increased thickness, and enhanced tissue density [39]. A key strategy to promote plant growth in water-deficit conditions is soil or seed inoculation with microbial consortia. In this context, the first beneficial effects of MC inoculation on attenuating the adverse effects of drought stress can be observed by improving the external morphological structure of plants (i.e., plant height, longer internodes, leaf size, among others) [18,20]. A possible explanation for this phenomenon is that MC enhances nutrient solubility and availability, resulting in improved plant growth characteristics [20]. Additionally, MC can modulate endogenous hormonal levels, such as auxin, cytokinin, and gibberellin, which promote the growth of plant roots and shoots [40]. Similarly, MC can secrete the enzyme 1-aminocyclopropane-1-carboxylate deaminase, resulting in enhanced plant growth [41]. Also, soil inoculation with microbial consortia causes higher leaf size, stem extension, and root proliferation under water restriction [18]. Additionally, MC formed an associated synergistic effect on enhancing plant external structure, which is observable in the root and shoot length, leaf area, and root and shoot biomass [20].
An additional important approach to enhance plant growth under drought stress is the foliar application of a mixture of AAGP. In this context, alterations in plant morphology resulting from AAGP application can be seen in internode length [42]. In addition, utilizing a combination of AAGP greatly enhances the LAI, which is associated with plant assimilation and transpiration improvement [22]. Recent studies have shown that applying exogenous amino acids improves leaf area due to increasing leaf turgor pressure, canopy temperature, and availability of photoassimilates [25,26]. Despite the limited research focused on the combined foliar application of an AAGP under drought conditions. The growth of sunflowers improved under drought conditions with foliar spraying of AAGP because certain amino acids helping with nitrogen metabolism and support plant functions during drought stress, probably help improve protein production, which is essential for cell growth and lengthening in both shoot and root tissues [43]. Another beneficial effect of foliar application of AAGP in attenuating drought stress is probably by increasing the glycine betaine accumulation in leaf tissues, helping to maintain turgor pressure, protect cellular structures (like membranes and proteins), and facilitate water uptake [44]. Additionally, the rise of the hormone auxin (indole-3-acetic acid), which is mainly recognized for regulating growth is another role of exogenous AAGP can contribute to plant confrontation of drought stress [44]. Furthermore, the positive changes in sunflower aboveground biomass production from foliar spraying a mixture of AABG under water restriction conditions can be attributed to enhancements in plant structure and morphology.
A lower soil water content decreased the photosynthetic rate and increased the transpiration rate [20,21,40]. In our study, foliar spraying of a mixture of AAGP increased growth indices such as LAR, NAR, and RGR, which helps to understand the beneficial effects of exogenous application of AAGP mixture in plant growth and productivity. Similar trends were reported in crops grown in water-deficient conditions [45]. The beneficial effects of applying amino acids on sorghum growth provide stress-specific compensations, preserving photosynthetic efficiency in water-deficient situations by improving antioxidant, osmoprotection, and nutritional mechanisms [46]. This amino acid combination may have enabled continuing photochemistry by balancing cellular dehydration effects in leaf tissues [7]. In addition, utilizing a combination of AAGP greatly enhances the LAI and AB, which are associated with plant assimilation and transpiration improvement, leading to amelioration of plant tolerance to water-deficit conditions [27].
Sunflower growth parameters were further increased by combined MC inoculation and foliar spraying of AAGP mixture under water deficit conditions. These positive effects of the combined MC and AAGB treatments in ameliorating sunflower growth are directly related to increasing the PH, RG, LAI, AB, NAR, LAR, and RGR (Figure 2, Figure 3, Figure 4 and Figure 5). As far as we are aware, this is the first report on the effectiveness of combined MC and AAGB treatments in ameliorating drought damage in sunflowers. There are several possible explanations for these facts. Previous research has indicated that the presence of both MC and AAGP enhances root surface area, thereby facilitating plants’ ability to effectively absorb and utilize nutrients and water, which is crucial for plant growth and survival during drought conditions [23,25]. These synergistic effects on sunflower growth under water-deficit environments are due to the stimulation of the plant’s hormone production, improving nutrient availability and uptake, increasing osmolyte accumulation, and also activating essential metabolic pathways and positively regulating genes related to carotenoids and lipids, carbon fixation, and modifying antioxidant enzymatic activities [47]. Similar synergistic effects on enhancing crop yield and quality with microbial consortia combined with biostimulants have been previously reported in water-restricted environments [48,49]. Therefore, this dual approach addresses the improvement of plant morphology (external structure), leading to enhanced plant growth and resilience under drought.
Chlorophyll is a vital and operative pigment in photosynthesis and can replicate the plant growth status and the degree of stress. Water deficit tends to reduce chlorophyll content, which causes changes in photosynthetic function [50]. In addition, drought stress is known to reduce chlorophyll levels in plants. Similar findings were reported previously in different plant species such as maize [20], wheat [21], and tomato [40]. In the current study, MC inoculation enhanced the TCC under water-deficit conditions. This increasing TCC by MC inoculation can be by lengthening roots, increasing branching, and adding more root hairs, resulting in a bigger surface area for nutrient and water uptake and favoring plant growth [49]. Another probable mechanism to explain this fact is that MC produces phytohormones that help roots grow and develop and also improve stomatal closure to save water while not overly reducing photosynthesis and chlorophyll production [35]. Furthermore, MC can influence the expression of plant genes involved in drought tolerance, including those related to chlorophyll biosynthesis and protection [51].
Chlorophyll content plays a crucial role in crop growth and development. Our results showed that exogenous application of AAGP mixture improves the TCC, which is crucial for chlorophyll biosynthesis [39]. The beneficial effects of increasing chlorophyll content due to the AAGP mixture applications can be justified by the decrease in chloroplast biogenesis, which reduces chlorophyll degradation and interrupts leaf senescence [52]. Moreover, some of these amino acids are the fundamental building blocks of proteins, including those crucial for the synthesis and maintenance of enzymes involved in chlorophyll biosynthesis [26]. Additionally, glycine is involved in the synthesis of porphyrin rings, the core structure of chlorophyll molecules, and tryptophan is a precursor for the synthesis of auxin, promoting leaf area expansion, which can indirectly increase total chlorophyll content [53]. Furthermore, glycine and aspartic acid can enhance nutrient uptake and assimilation, which are vital for maintaining photosynthetic efficiency and chlorophyll content [54].
Enhancing the morphophysiological mechanisms through a different method is crucial for plant confrontation with drought stress. Under water-deficient circumstances, the current study found that foliar spraying an AAGP mixture and applying MC inoculation together increased TCC content more than either method alone. This combination’s positive benefits on increased TCC in drought-affected sunflower plants are most likely the result of improved growth factors such as PH, LAI, AB, NAR, LAR, and RGR (Figure 2, Figure 3, Figure 4 and Figure 5). These positive changes possibly increase photosynthetic efficiency due to activating key mechanisms such as phytohormone biosynthesis, nutrient uptake and translocation, osmoprotection, and enzymatic antioxidants, among others [53,55]. The synergistic effects of combining MC with a mixture of AAGP can improve nutrient availability and may enable the plant to utilize them more effectively for chlorophyll synthesis during drought stress. Furthermore, the integration of MC inoculation with foliar spraying of AAGP may constitute an effective technique for sustainable agriculture under water-deficient conditions.
The leaf relative water content (LRWC) exhibited a declining tendency in an environment with insufficient water. Sunflower plants have shown similar response patterns in a previous study [56]. Conversely, MC plays a significant role in enhancing the LRWC of plants under drought conditions, leading to improved root length, surface area, and the development of finer roots and root hairs, which allows plants to explore a larger soil volume for water and nutrient uptake [35]. Similarly, certain bacteria within the MC can produce exopolysaccharides, which help to improve soil structure and water retention around the roots, resulting in an increase in water availability that directly benefits the plant’s relative water content [51]. Likewise, MC can influence the modulation of some phytohormones that play a crucial role in drought response. For instance, increasing abscisic acid triggers stomatal closure, reducing water loss through transpiration [48]. Besides promoting auxin and cytokinin production, leading to stimulated root development and cell division, indirectly contributing to better water acquisition [40]. Finally, ACC deaminase synthesis lowers ethylene levels while preserving root development and water uptake [57].
Drought stress specifically affects leaf relative water content and water potential due to open stomata induction and increasing transpiration rates. In this context, foliar spraying of an AAGP mixture increases LRWC in sunflower plants under drought conditions (Figure 4c). These positive effects could be attributed to increased soil nutrient availability, which is associated with increased cellular osmotic potential [56]. In addition, certain amino acids can regulate stomatal opening in plant growth under water deficit conditions to avoid water loss, which is another important mechanism to maintain LRWC [25]. Moreover, under stress, arginine may be transformed into proline, which indirectly improves osmoprotection, and glycine can build up in plant cells, which helps to reduce osmotic potential and facilitate water uptake [53,58]. Similarly, this AAGP mix application appears to have a favorable effect on drought stress reduction via enhancing morphophysiological processes. Further experimental research would be required to confirm these potential advantages and find appropriate application strategies.
Actually, we need sustainable agricultural alternatives to cope with drought effects. In this context, the combination of MC and AAGP biostimulants resulted in improved LRWC. These beneficial effects of this combination in maintaining high LRWC are most likely due to improvements in plant morphophysiological parameters such as PH, LAI, AB, NAR, LAR, RGR, and TCC. Internal processes are also activated, such as increasing osmolytes accumulation (i.e., glycine, proline), nutrient uptake and accumulation, decreasing ROS through enzymatic and non-enzymatic scavenging, phytohormone signaling [18,59]. Furthermore, the combination of MC and AAGP applications could be considered an important ecological strategy for sustainable and resilient agriculture under water deficit conditions.
Water deficit reduces sunflower yield and quality. It was previously observed that applying drought conditions affected yield components and significantly decreased sunflower yield [12,56]. A lower SMH and a larger ESH production led to a reduced SY under drought stress, which is a frequent phenomenon that was shown in this study (Figure 5 and Figure 6). On the other hand, MC inoculation and AAGP foliar treatment both increased SPH at the individual level, which in turn raised SY. These positive effects might be explained by the fact that both biostimulants enhance the morphophysiological and productive characteristics of sunflowers. MC inoculation has provided information on similar response mechanisms for reducing drought stress in many plant species [20] and exogenous amino acids application [25,26]. Additionally, our study found that, compared to their solo application, the combined MC inoculation and AAGP combination treatments further elevated TSH, FSH, SMP, and SY in sunflower-stressed plants (Figure 5 and Figure 6). The ability of the combined biostimulants to enhance physiological responses (TCC and LRWC) and growth parameters (PH, RG, LAI, AB, NAR, LAR, and RGR) can be used to explain this occurrence. Another likely explanation is that both biostimulants can improve phytohormone signaling, root systems, and nutrient uptake, which help plants deal with drought stress [44]. The synergistic combination between this specific MC and this particular AAGP mix may uncover unknown advantages due to intricate interactions at the morphophysiological levels, leading to a more effective and sustainable method for mitigating drought-induced yield losses. Therefore, these favorable effects of MC inoculation and AAGP combinations constitute the first study to give morphophysiological evidence of the alleviation of drought stress in sunflower plants, which are aligned with the following Sustainable Development Goals (SDGs, United Nations), such as no poverty, zero hunger, good health and well-being, clean water and sanitation, industry, innovation and infrastructure, sustainable cities and communities, responsible consumption and production, climate action, life below water, life on land, and peace, justice, and strong institutions.

5. Conclusions

Adopting alternative, more sustainable, and environmentally friendly agriculture practices has been well recognized. The findings of this study suggest that the combination of a microbial consortium and foliar application of a mixture of amino acid-based growth promoter significantly improved the productive components and yield of ‘Cabré-15’ sunflower under drought stress. Moreover, the results indicate that the combined application of both biostimulants increased morphophysiological responses through plant height, leaf area, aboveground biomass, growth index, total chlorophyll content, and leaf relative water content. Additionally, recognizing the most effective strategies for mitigating the negative impacts of water deficit will enable the development of new management alternatives for sustainable and resilient agriculture. We highlight future research areas, including the comparison among different plant densities, using biofertilizers, testing the effectiveness of rhizobacteria inoculants, and exploring specific combinations of these options to support sustainable food production and tackle water scarcity. Further, understanding the molecular mechanisms that enable a plant to defend itself requires the use of new analytical techniques like proteome and metabolome.

Author Contributions

Conceptualization, A.C.H. and K.P.C.; methodology, A.C.H. and J.J.; software, A.C.H., J.V.B.F. and L.S.L.; validation, A.C.H., K.P.C. and L.S.L.; formal analysis, A.C.H. and J.J; investigation, A.C.H., L.S.L., K.P.C., J.J. and J.V.B.F.; resources, A.C.H.; data curation, A.C.H.; writing—original draft preparation, A.C.H.; writing—review and editing, A.C.H., K.P.C., J.V.B.F., J.J. and L.S.L.; visualization, L.S.L. and J.V.B.F.; supervision, A.C.H.; project administration, A.C.H.; funding acquisition, A.C.H. and K.P.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Oficina de Gestión de Fondos y Proyectos Internacionales and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), grant numbers PN211LH012-36 and 88887.975003/2024-00, respectively. The APC was funded by Catalysis S.A., Spain.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

We thank Catalysis S.A. enterprise and Labiofam Sancti Spiritus Enterprise for kindly providing the bioproducts VIUSID® agro and microbial consortium, respectively.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AAGPAmino acid-based growth promoter
AAAmino acid
MCMicrobial cons
FFischer values
AA × MCAA–MC interaction
PHPlant height
RGRelative growth
NARNet assimilation rate
LARLeaf area ratio
RGRRelative growth rate
TCCTotal chlorophyll content
LRWCLeaf relative water content
TSHTotal seeds per head
FSHFull seeds per head
ESHEmpty seeds per head
SPHSeed mass per head
SYSeed yield
ROSReactive oxygen species

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Figure 1. Daily average values for climatic variables, including (a) minimum temperature (TMin, °C), mean temperature (TMed, °C), maximum temperature (TMax, °C), (b) minimum relative humidity (RhMin, %), mean relative humidity (RhMed, %), maximum relative humidity (RhMax, %), and accumulated rainfall over 24 h (Rf, mm).
Figure 1. Daily average values for climatic variables, including (a) minimum temperature (TMin, °C), mean temperature (TMed, °C), maximum temperature (TMax, °C), (b) minimum relative humidity (RhMin, %), mean relative humidity (RhMed, %), maximum relative humidity (RhMax, %), and accumulated rainfall over 24 h (Rf, mm).
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Figure 2. Average of plant height at 30 DAS (a); plant height at 60 DAS (b) and relative growth (c) observed in sunflower plants in function of two doses of a mixture of AAGP (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA—MC interaction; F: Fischer values. Values are expressed as mean (n = 5) ± standard deviation (SD). Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences between AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
Figure 2. Average of plant height at 30 DAS (a); plant height at 60 DAS (b) and relative growth (c) observed in sunflower plants in function of two doses of a mixture of AAGP (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA—MC interaction; F: Fischer values. Values are expressed as mean (n = 5) ± standard deviation (SD). Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences between AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
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Figure 3. Leaf area index at 30 DAS (a), leaf area index at 60 DAS (b), aboveground biomass at 30 DAS (c), and aboveground biomass at 60 DAS (d) observed in sunflower plants in function of two doses of a mixture of AAGP (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA—MC interaction; F: Fisher values. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences in AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
Figure 3. Leaf area index at 30 DAS (a), leaf area index at 60 DAS (b), aboveground biomass at 30 DAS (c), and aboveground biomass at 60 DAS (d) observed in sunflower plants in function of two doses of a mixture of AAGP (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA—MC interaction; F: Fisher values. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences in AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
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Figure 4. Net assimilation rate (a), leaf area ratio (b), and relative growth rate (c) determined in sunflower plants in function of two AAGP doses (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA–MC interaction; F: Fischer values; NAR: net assimilation rate; LAR: leaf area ratio; RGR: relative growth rate. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences between AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
Figure 4. Net assimilation rate (a), leaf area ratio (b), and relative growth rate (c) determined in sunflower plants in function of two AAGP doses (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA–MC interaction; F: Fischer values; NAR: net assimilation rate; LAR: leaf area ratio; RGR: relative growth rate. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences between AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
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Figure 5. Total chlorophyll content at 30 (a), Total chlorophyll content at 60 DAS (b), and leaf relative water content at 60 DAS (c) observed in sunflower plants in function of two AAGP doses (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA–MC interaction; F: Fischer values; TCC: total chlorophyll content; LRWC: leaf relative water content. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences in AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
Figure 5. Total chlorophyll content at 30 (a), Total chlorophyll content at 60 DAS (b), and leaf relative water content at 60 DAS (c) observed in sunflower plants in function of two AAGP doses (0.25 and 0.50 L ha−1) and three MC concentrations (0, 100, and 200 mL m−2), Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; AA: amino acids; AA × MC: AA–MC interaction; F: Fischer values; TCC: total chlorophyll content; LRWC: leaf relative water content. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical AAGP doses, respectively. Capital letters (e.g., A, B) denote significant differences in AAGP doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). *: p < 0.05 or **: p < 0.01, according to the two-way ANOVA.
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Figure 6. Total seeds per head (a), full seeds per head (b), and empty seeds per head (c) observed in sunflower plants in function of two doses of a mixture of AAGP (0.25 and 0.50 L ha−1) doses and three MC consortium concentrations (0, 100, and 200 mL m−2), during a 115-days experimental period, Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; TSH: total seeds per head; FSH: full seeds per head; ESH: empty seeds per head. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical amino acid doses, respectively. Capital letters (e.g., A, B) denote significant differences in amino acid doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). **: p < 0.01, according to the two-way ANOVA.
Figure 6. Total seeds per head (a), full seeds per head (b), and empty seeds per head (c) observed in sunflower plants in function of two doses of a mixture of AAGP (0.25 and 0.50 L ha−1) doses and three MC consortium concentrations (0, 100, and 200 mL m−2), during a 115-days experimental period, Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; TSH: total seeds per head; FSH: full seeds per head; ESH: empty seeds per head. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical amino acid doses, respectively. Capital letters (e.g., A, B) denote significant differences in amino acid doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). **: p < 0.01, according to the two-way ANOVA.
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Figure 7. Seed mass per head (a) and yield production (b) in sunflower plants in function of two amino acid doses (AAGP; 0.25 and 0.50 L ha−1) and three microbial consortium concentrations (MC; 0, 100, and 200 mL m−2), during a 115-day experimental period, Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; Fischer values; AA × MC: AA—MC interaction; AA: amino acids; F: Fischer values. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical amino acid doses, respectively. Capital letters (e.g., A, B) denote significant differences in amino acid doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). **: p < 0.01, according to the two-way ANOVA.
Figure 7. Seed mass per head (a) and yield production (b) in sunflower plants in function of two amino acid doses (AAGP; 0.25 and 0.50 L ha−1) and three microbial consortium concentrations (MC; 0, 100, and 200 mL m−2), during a 115-day experimental period, Tuinucu, Cuba. AAGP: mixture of amino acid-based growth promoter; MC: microbial consortium; Fischer values; AA × MC: AA—MC interaction; AA: amino acids; F: Fischer values. Values are expressed as mean (n = 5) ± SD. Lowercase letters (e.g., a, b, c) or bold lowercase letters (e.g., a, b, c) indicate significant differences among MC concentrations at identical amino acid doses, respectively. Capital letters (e.g., A, B) denote significant differences in amino acid doses at identical MC concentrations, as determined by Tukey’s test (p < 0.05). **: p < 0.01, according to the two-way ANOVA.
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MDPI and ACS Style

Calero Hurtado, A.; Peña Calzada, K.; Fasoli, J.V.B.; Jiménez, J.; Sánchez López, L. Synergic Effects of the Microbial Consortium and Amino Acid-Based Growth Promoter in Sunflower Productivity Under Water-Deficit Conditions. Water 2025, 17, 1365. https://doi.org/10.3390/w17091365

AMA Style

Calero Hurtado A, Peña Calzada K, Fasoli JVB, Jiménez J, Sánchez López L. Synergic Effects of the Microbial Consortium and Amino Acid-Based Growth Promoter in Sunflower Productivity Under Water-Deficit Conditions. Water. 2025; 17(9):1365. https://doi.org/10.3390/w17091365

Chicago/Turabian Style

Calero Hurtado, Alexander, Kolima Peña Calzada, José Vitor Botter Fasoli, Janet Jiménez, and Lianny Sánchez López. 2025. "Synergic Effects of the Microbial Consortium and Amino Acid-Based Growth Promoter in Sunflower Productivity Under Water-Deficit Conditions" Water 17, no. 9: 1365. https://doi.org/10.3390/w17091365

APA Style

Calero Hurtado, A., Peña Calzada, K., Fasoli, J. V. B., Jiménez, J., & Sánchez López, L. (2025). Synergic Effects of the Microbial Consortium and Amino Acid-Based Growth Promoter in Sunflower Productivity Under Water-Deficit Conditions. Water, 17(9), 1365. https://doi.org/10.3390/w17091365

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