Eukaryotic microalgae-bacteria synthetic consortia boost crop productivity and drought tolerance in bread wheat (Triticum aestivum)

Eukaryotic microalgae-bacteria synthetic consortia boost crop productivity and drought tolerance in bread wheat (Triticum aestivum) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Eukaryotic microalgae-bacteria synthetic consortia boost crop productivity and drought tolerance in bread wheat ( Triticum aestivum ) Celeste Molina-Favero, Lara Sanchez Rizza, Angie Melissa Gonzalez Olano, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7311767/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Wheat provides the main source of nourishment for more than 40% of the global population, making it an essential crop. The challenge of properly overseeing crop management to guarantee water efficiency has been enhanced by the increase in rainfall unpredictability caused by climate change. Plant-growth-promoting bacteria (PGPBs) are beneficial microorganisms capable of improving crop yield and adaptability to environmental stresses. Single-celled eukaryotic algae, on the other hand, are comparatively under-studied organisms that exihit plant-biostimulant properties. Our research demonstrates that co-inoculation of Azospirillum argentinensis Az39 with the microalgae Scenedesmus obliquus C1S increases bacterial root colonization and the sole inoculation with microalgae improves germination and post-germinative growth. Field trials conducted during the ENSO phase of 'La Niña,' characterized by drought conditions, revealed a 36% boost in grain yield and a 26.2% improvement in crop water productivity resulting from inoculation with microalgae-PGPB consortia. Moreover, under induced drought conditions, seedlings inoculated with microalgae showed an increase in root dry weight, averaging 50%. Notably, inoculation efficiency was affected by tillage methods. The findings presented herein reveal a promising potential for the development of a novel eukaryotic microalgae-PGPB synthetic consortia inoculant that enhances root colonization by PGPBs and improves wheat crop water productivity under field conditions Agronomy General Microbiology Applied & Industrial Microbiology Agricultural Engineering Agroecology Microalgae Wheat Plant Growth Promoting Rhizobacteria Drought Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights Inoculation of eukaryotic microalga-PGPB synthetic consortia results in a 36% increase in wheat grain yield. Seedlings inoculated with microalgae exhibit improved water status and growth under drought conditions The efficacy of inoculation is influenced by the tillage methods employed prior to sowing. 1. Introduction Wheat is a major worldwide crop, representing over 20% of the calories and proteins harvested worldwide (Shiferaw et al., 2013 ) and providing as the primary food supply for over 40% of the global population (Zhang et al., 2022 ). Contemporary management approaches predominantly depend on the utilization of external inputs, including insecticides for pest and disease management, mineral fertilizers to enhance plant nutrition and biomass, and sometimes irrigation to mitigate water stress circumstances (You et al., 2022 ). The yield of rain-fed crops is linked to the precipitation they receive throughout their growth cycle (Andrade & Satorre, 2015 ). Thus, the careful monitoring of crop management to ensure water efficiency and alleviation of the negative effects of water scarcity, is crucial for sustainable crop production. This challenge is amplified by the anticipated increase in rainfall variability due to climate change, which, in the case of wheat bread, production can decrease up to 60% (Aramburu Merlos et al., 2015 ). In the southern hemisphere, the potential grain surplus due to appropriate irrigation is highly variable due to the influence of the El Niño-Southern Oscillation phenomenon (ENSO). ´El Niño´ phase is reflected as an increase in spring/summer rainfalls and higher summer crop yields, while the opposite occurs with “La Niña” events, which typically result in dry years. In this context, farmers face significant challenges due to environmental unpredictability, since different seasons require different management strategies based on rainfall patterns and timing (Edreira et al., 2018 ). Conservation tillage has gained popularity in recent years due to its efficacy in mitigating soil degradation and enhancing soil water retention (Hashimi et al., 2023 ). No-tillage (NT) systems might have potential benefits over conventional tillage (CT) systems under specific management situations. These advantages encompass a diminished number of machine runs over the field, enhanced aggregate stability, the protective influence of agricultural residues remaining on the soil (Sithole et al., 2019 ), enhancing soil water retention and a greater prevalence of biopores (Blanco-Canqui & Ruis, 2018 ; Hashimi et al., 2023 ). However, when subjected to NT management, certain soils might suffer adverse impacts, including heightened bulk density on the 0–20 cm layer of the soils (Dı́az-Zorita et al. , 2002; Martínez et al., 2008 ), and diminished oxygen diffusion rates (Khan & Science, 1996 ). Plant-growth-promoting bacteria (PGPBs) are a group of rhizospheric beneficial bacteria that have the potential to enhance crop productivity and acclimation to abiotic stress through multiple mechanisms (Bhattacharyya et al. , 2012; Cassán et al., 2014 ). Azospirillum argentinensis has a direct influence on the plant, via the synthesis of several phytohormones, including indole acetic acid (Spaepen et al., 2007 ), abscisic acid (Wu et al., 2025 ), gibberellins (Cohen et al., 2009 ), salicylic acid (Sahoo et al., 2014 ), cytokinin (Zaheer et al., 2022 ) and nitric oxide (NO) (Molina-Favero et al., 2008 ). On the other hand, fluorescent pseudomonads, major inhabitants of the rhizosphere, have both direct and indirect favorable impacts on plant development (Choudhary et al., 2009 ) Pseudomonas strains synthesize a diverse array of chemicals exhibiting antibacterial properties, with 2,4-diacetylphloroglucinol (DAPG) being among the most extensively researched (Weller et al., 2007 ). These PGPBs are presently marketed as inoculants, and strain compatibility is an absolute requirement to achieve increased plant growth promotion by co-inoculation of several PGPBs (Pagnussat et al., 2016 ; Díaz et al., 2023 ). A critical aspect of this strategy is that PGPBs inoculated onto seeds must survive on the dry or semi-dry surface tissues of the seed until appropriate conditions emerge for root colonization. Consequently, inoculants often require adjuvants or seed-coating treatments to enhance their viability (Rocha et al., 2019 ). Although much less studied than bacteria, single-celled eukaryotic algae (commonly known as microalgae) also exhibit plant biostimulant properties. Microalgae are widespread in soils, contributing to their organic carbon content, structure, and moisture. In addition to releasing plant hormones and other growth-stimulating substances, some microalgae produce a complex matrix of EPS. These EPS are believed to shield co-inhabiting bacteria from desiccation and UV radiation, in a microenvironment that provide them with essential nutrients and hormones for their survival and growth, and drive complex mutualistic interactions within microalgae-bacteria consortia (Perera et al., 2022 ). In this sense, when co-cultured, auxins produced by Azospirillum baldaniorum Sp245 mitigate the oxidative stress of the microalgae Scenedesmus obliquus C1S, under both saline stress (Pagnussat et al., 2023 )d deficiency (Pagnussat et al., 2020 ), thereby promoting the growth of the microalgae. Additionally, A. baldaniorum and S. obliquus engage in mixed biofilms, a property which could contribute to the higher rates of bacterial survival observed in co-culture, particularly under salinity stress (Pagnussat et al. 2023 ). Field inoculation of crops with beneficial microorganisms is a sustainable approach to improve crop productivity and stress resilience. Nonetheless, PGPB performance may fluctuate due to environmental variables, microbial competition, and agronomical practices (Bulgarelli et al., 2013 ). In recent studies, tillage practice was identified as the primary factor influencing the microbiome in the rhizosphere (Behr et al., 2024 ). Moreover, on wheat soils, tillage methods have a significant interactive effect with the water regime on root-associated bacterial and fungal populations (Romano et al., 2023 ), underscoring the enduring legacy of tillage practices likely attributable to variations in physical soil properties and chemical composition. This highlights the necessity for additional research to improve inoculation techniques to provide reliable agricultural benefits. Considering the biostimulant properties of microalgal exudates (La Bella et al., 2022 ), we hypothesize that microalgae can offer emergent properties to multispecies PGPB inoculants. In this work, we explored whether microalgae incorporated into bacterial inoculants can (i) favor the survival of bacteria in the rhizosphere, and (ii) improve wheat water productivity under field conditions and different tillage managements. Our results establish, for the first time, the potential of microalgae-bacteria communities as bioinputs for crops in the field, an area that still remains unexplored and holds significant implications for developing novel multi-species inoculants. 2. Materials and Methods 2.1 Microorganisms and growth conditions Scenedesmus obliquus C1S (Do Nascimento et al., 2012 ) and Azospirillum argentinense Az39 and Pseudomonas sp. LSR1 were used as study microorganisms. S. obliquus C1S was routinely cultured in BG11 medium containing 10 mM NaNO 3 as a nitrogen source and 0.42 g x L − 1 NaHCO 3 to buffer CO 2 supplementation. Recombinant fluorescent derivatives of A. argentinense Az39 and Pseudomonas LSR1, Az39-dsRED (Puente et al., 2021 ) and LSR1-eGFP (Maroniche et al., 2018 ) were also used when required. All experiments were initiated with 10 6 cells of S. obliquus C1S, counted under a light microscope (Leica DM500, Germany) on a Newbauer chamber, 10 6 cells of A. argentinensis Az39 and/or Pseudomonas sp. LSR1 (estimated by optical density at 600 nm, OD 600 ) per seed. Starter single-species cultures of Az39 and LSR1 were cultured in Luria-Bertani medium (LB) without salt at 30°C with orbital shaking (150 rpm) for 18 h. Tetracycline at 25 µg mL − 1 was included in the medium for culture of the recombinant fluorescent strains. 2.2 Seed inoculation and root colonization Wheat seeds ( Triticum aestivum (L.) cv. MS INTA 221 (long-cycle cultivar) and cv. MS INTA 819 (short-cycle cultivar) were used for the 2022 campaign and growing chamber trials, and 2024 campaign, respectively. Seeds were superficially sterilized (10 min with 50% sodium hypochlorite) and inoculated with a suspension of microalgae alone, bacteria alone, bacteria consortium, or with a triple consortium (microalgae plus both bacterial strains). For root colonization analysis, the fluorescent bacterial variants were used. Suspensions with microorganism were applied to the seeds at a final inoculation volume of 5 µl per seed, and stored on paper envelopes at 25°C for 24 h before sowing. Root colonization was evaluated 3 d after germination on agar-water plates. Roots were cleaned and crushed in a mortar, and bacterial colony-forming units (CFU). g − 1 were evaluated using the microdrop technique as previously described (Herigstad et al., 2001 ). Roots colonized by fluorescent bacteria (Az39-dsRED and LSR1-eGFP were also directly observed with a Nikon C1 confocal laser microscope. LSR1-egfp and Az39-dsred bacteria were excited/detected at 488/550 nm and 543/ 650 nm, respectively. Images were analyzed using Nikon EZ-C1 Free viewer software. 2.3 Microalgae localization and viability Scenedesmus. obliquus C1S localization and viability were examined in radicle-protruding seeds at one day post-imbibition (1 dpi). Transversal sections of the seed trichomes region, each one one- millimeter thick, were stained with SYTOX Green at a final concentration of 1 µM for 30 min in the dark at 4°C. They were subsequently analyzed using light and fluorescence microscopy with a Nikon E600 microscope, equipped with a B-2A cube that include 450–490 nm excitation and 500–515 nm emission filters, utilizing a 40.0xA/1.25/0.17 oil-immersion Nikon lens. Images were captured using an Olympus DP72 digital camera and Cellsens Entry imaging software. 2.4 Analysis of microalgal phytohormone profile by Ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) Microalgal cells were resuspended in 1.5 mL 1 M NaCl, sonicated at a 50% power-output (Vibra-Cell, model VCX-130, Sonics Inc.) for three cycles of 1 min each (10 sec on, 1 sec off), immediately frozen with liquid nitrogen, and lyophilized. Jasmonic acid (JA), abscisic acid (ABA), salicylic acid (SA), indole-3-acetic acid (IAA), cis-zeatin (cZ), cis-zeatin riboside (cZR), trans-zeatin (tZ), trans-zeatin riboside (tZR), and gibberellic acid (GA 3 ) were extracted using 100 mg of lyophilized microalgae. The samples were processed according to (Giannarelli et al., 2010 ), and the resulting extracts were diluted 10-fold with ultrapure water, filtered through a 0.22 µm nylon filter, and analyzed. Phytohormone concentrations were determined by UHPLC (UHPLC ACQUITY I-Class UPLCTM) coupled to tandem mass spectrometry (XEVO TQ-XS) equipped with an ACQUITY UPLC HSS C18 Column (1.8 µm, 100 x 2.1 mm) (Waters). The mobile phases were water: methanol 95:5 (phase A) and methanol (phase B), both modified with ammonium acetate 0.1 mM and formic acid 0.01% v/v. The flow rate was set at 0.3 mL.min − 1 and the column temperature was 45°C. The chromatographic separation was performed with the following gradient elution conditions: B was 10% (v/v) in 0 − 0.5 min, linearly increased to 90% (v/v) in 0.5 − 11 min; held at 90% for 11 − 12.5 min, and returned to the initial condition in 1.5 min. An auto-sampler was used to inject 10 µL of the samples. The XEVO TQ-XS tandem quadrupole mass spectrometer was operated in positive and negative mode with the electrospray-ionization (ESI) source. The operating parameters were optimized under the following conditions: capillary voltage, 3 kV, ion source temperature 150°C, desolvation temperature 500°C, cone gas flow 150 L. h − 1 , desolvation gas flow 800 L h − 1 (both gases were nitrogen obtained from a nitrogen generator) and collision gas flow 0.15 mL min − 1 (argon gas 99.995% with a pressure of 4.04×10 − 3 mbar in the T-Wave cell). Mass Lynx v 4.2 software (Waters, USA) was used to process quantitative data obtained from calibration standards and samples. The experiments were performed in triplicate. 2.5 Drought stress application, management, and plant sampling In the growth chamber experiments, inoculated seeds were sown in 100 mL plastic pots filled with commercial substrate (Turba Plus, Carluccio) with 20 plants per treatment. Each pot was watered to 100% field capacity (FC) using distilled water until seedlings reached the Zadoks stage 13 (Haun stage 2.6), when a moderate drought stress (MS) corresponding to 40% of FC was applied to each treatment. Watering was withheld until the soil FC reached 40%, and drought stress levels were maintained for 7 d by daily weighing of pots and adding distilled water to compensate for water loss. After 7 d under drought stress, the uppermost, fully expanded leaves from six plants of each treatment were sampled on the 7th day of drought stress. Six leaves from each treatment were used to determine leaf relative water content (RWC). Leaf RWC was determined according to the standard method proposed by Barrs and Weatherly (1962) as RWC = (FW − DW) / (TW − DW), where FW is fresh leaf weight, DW is dry weight, and TW is turgid weight after 24 h floating in distilled water at 4°C in darkness. Four plants from each treatment were used to analyze root and shoot fresh and dry weight. Roots were subsequently scanned to determine total root length (RL), projected area, and the number of forks per root using the WinRHIZO 2007 software (Regent Instruments, Ottawa, Canada). 2.6 Miscellaneous Methods Fresh leaf samples were frozen in liquid nitrogen, powdered with liquid nitrogen, and stored at − 80°C For total sugars and proline determinations. Sugars in frozen leaf samples (100 mg) were extracted using ammoniacal water (pH 8.0) in 100ºC bath for 5 min, followed by centrifugation at 10,000× g for 10 min after cooling. Total soluble sugar was measured colorimetrically by the anthrone method at 620 nm (Pontis, 2016 ; Bader et al., 2024 ). Glucose was used as standard for total soluble sugar measurements. Proline in frozen leaf samples (100 mg) was extracted with 3% (w/v) sulfosalicylic acid, and the extract was centrifuged at 15,200 ×g for 10 minutes. A sample of the clarified extract was combined with sulfosalicylic acid, glacial acetic acid, and acid-ninhydrin and incubated for 1 hour at 96°C. The reaction was halted by placing the tubes on ice. Two milliliters of toluene were incorporated into the mixture, stirred for 20 seconds, and allowed to settle for 5 minutes to facilitate phase separation. The absorbance of toluene (upper layer) was quantified at 520 nm, using toluene as the reference standard. The proline content was quantified utilizing a standard curve according to the methodology established by Bates ( 1973 ). 2.7 Field Trials: experimental design Field trials were conducted in two distinct years, concurrently at three locations without irrigation, under three different agronomic management systems: No-till (NT, site 1, sowing date June 22th, 2022), Agroecological Management (AM, site 2, sowing date June 22th, 2022), and Conventional Management (CM, site 3, sowing date August 1st, 2024). All trials were carried out at the Balcarce Experimental Station of the Instituto Nacional de Tecnología Agropecuaria (INTA) (37°46′ 14″ S; 58°18′ 23″ W; 113 m.a.s.l.) from June 2022 to January 2023 and from August 2024 to January 2025. According to pre-sowing soil analysis, the soil for the three sites was classified as Typic Argiudoll (USDA Taxonomy) and fine thermic Petrocalcic Paleudoll (petrocalcic horizon at 140 cm) with a loamy surface texture and 4.39% organic matter (Site 1), 5.34% organic matter (Site 2) and 4.87% organic matter (Site 3). In site 1, the soil contained 18.4 P 2 O 5 (ppm, 0–20 cm depth), 14.1 N-NO 3 (ppm, 0–20 cm depth), and 8.5 N-NO 3 (ppm, 20–50 cm depth). In site 2, organic manure was applied at sowing, and the soil before planting contained 15.1 P 2 O 5 (ppm, 0–20 cm depth), 22.6 N-NO 3 (ppm, 0–20 cm depth), and 6.3 N-NO 3 (ppm, 20–50 cm depth). In site 3, the soil contained 34 P 2 O 5 (ppm, 0–20 cm depth), 1.36 N-NO 3 (ppm, 0–20 cm depth), and 1.57 N-NO 3 (ppm, 20–50 cm depth). For NT (year 2022, site 1), bread wheat was established in the residue of the preceding crop (soybean). For AM and CM (year 2022, site 1 and 2024, site 3), agronomic field operations before sowing include moldboard plowing to a depth of 30 cm, followed by seedbed preparation with a disc harrow. In site 3, summer crop (soybean) residues were incorporated during plowing. In sites 2 and 3, chemical fallow mulching was performed in the fall of both 2022 and 2024 (Paraquat 2,5 L.ha − 1 ). Dry soil was fertilized at the planting line with 150 kg.ha − 1 of diammonium phosphate and with 408 kg.ha − 1 of nitrogen, as urea distributed in two moments, at tillering and at the beginning of the stem elongation period. Weeds, pests, and fungal diseases were chemically controlled. Each assay consisted of four blocks, each 5 meters long, interspersed by a 2-m path. At sowing, the plots comprised of 7 furrows spaced every 20 cm and 6.5 m long (6.5 x 1.4 m). Each plot was sown with a density of 350 plants.m -1 (high density). Around the experimental blocks, durum wheat was sown to reduce the edge effect in the trial. Harvest was performed mechanically along the five central rows of each plot (5 x 1 m). Daily meteorological data were obtained throughout the test by the meteorological station located in the experimental field (INTA-Balcarce, ESM 1 and ESM 2). Phenological stages, biomass and yield component were determined according to Pask et al. (2012). For each treatment, plant count. m -1 , the number of tillers per plant, dry weight of aerial part and roots, and radical architecture, were analyzed at tillering. Biomass, harvest index, grain yield (GY), and grain quality were analyzed at harvest. Biomass was determined by sampling 2 linear m of each plot and weighing total dry aerial part. Harvest index was calculated as the percentage of total grain weight of the samples after threshing and biomass. Grain weight (GW) was determined by counting a 1,000-grain sample with an electronic counter, weighing it, and dividing the total weight by 1,000. Grain number per ha was then calculated as the quotient between GY and GW × 1,000. Test weight was determined with a 500 mL-Schopper chondrometer. Based on wheat GY and precipitation, CWP was calculated (kg. m − 3 ). 2.8 Statistical analyses For all sites, a randomized blocked design (RBD) was made in which the inoculation factor was analyzed at six levels with 4 repeats. The arrangement of the blocks was planned considering the inclination of the lot. For tilling, discrete data Odds Ratio Pairwise Comparison Analysis was used. One-way analysis of variance (ANOVA) followed by post-hoc Fisher LSD test or Tukey’s test, were used to detect significant differences (p < 0.05) between treatments. All analyses were performed in GraphPad Prism 7.04 or Python software (Odds Ratio Pairwise Comparison Analysis). 3. Results 3.1 Co-inoculation of Azospirillum with microalgae increases bacterial root colonization of wheat plants Since the early interaction between plants and microorganisms can significantly influence seedling establishment, germination and post-germinative growth was evaluated upon microalgal co-inoculation with well-established models of PGPB (Az39 and LSR1). The single inoculation with A. argentinense Az39 delayed germination and early root elongation. Nonetheless, its co-inoculation with Pseudomonas sp. LSR1 not only prevented a delay in germination and growth, but also augmented these processes significantly (Fig. 1 a, d). Likewise, the single inoculation with the microalgae S. obliquus C1S stimulated germination and post-germinative development. Conversely, inoculation with the full community (Az39 + LSR1 + C1S) did not affect the initial seedling growth markedly (Fig. 1 a, d). These results show that each alternative inoculant (single, double, and triple) differentially affects seedling establishment, possibly due to hormone interactions on the seed priming process. A prerequisite for plant-growth-promoting bacteria (PGPB) to promote plant growth is the establishment of a stable bacterial population on the roots (Okon & Labandera-Gonzalez, 1994 ; Creus et al., 2004 ). However, when bacteria are inoculated on dry seeds, their survival and viability often diminish quickly, hindering root colonization (Köhl et al., 2024 ). To determine whether bacterial performance after seed inoculation can be improved by its co-inoculation with microalgae, PGPB root colonization was evaluated in wheat ( Triticum aestivum ) at 3 d post-germination. A. argentinense Az39 root colonization was approximately 10-fold higher when it was co-inoculated with the microalgae (3.19 x 10 6 CFU.g -1 ), either in the presence or absence of Pseudomonas sp. LSR1. Conversely, LSR1 root colonization exhibited consistency, independently of the presence of C1S (Fig. 1 b). As expected, both bacteria were primarily located in the elongation zone, especially on root hairs for Az39, whereas LSR1 exhibited a more uniform distribution (Fig. 1 c). Microalgae localization was also analyzed in imbibed and germinating seeds. As observed in Fig. 2 a and 2 b, microalgae were mostly located within the trichomes of the seed coat during germination, and a release of microalgae into the surrounding medium was also noted. No microalgae were observed on the radicle or the apical axis during the early establishment of seedlings. Microalgae viability was also examined by a dual-fluorescence viability experiment using SYTOX Green along with chlorophyll autofluorescence as a contrast marker, to identify dead and living microalgal cells (Sato et al., 2004 ). As shown in Fig. 2 c, no SYTOX Green fluorescence was observed, indicating that all seed-attached microalgae were viable. S. obliquus phytohormone profile revealed high concentrations of JA and cZ, moderate levels of SA and IAA, and reduced amounts of tZ, cZR, and ABA. GA 3 and tZR were not detected (Fig. 2 d). 3.2 Microalgae inoculation under conventional tillage enhanced wheat tillering and root weight To analyze inoculated wheat treatments performance under agronomic scenarios, both NT and tilling managements were explored. Wheat field experiments were conducted in Balcarce, Buenos Aires, Argentina, in June 2022 with conventional tillage and agroecological management (AM) or NT and in August 2024 under conventional management (CM). The field trials were carried out using a completely randomized design with four repetitions and six inoculation treatments: Az39, C1S, Az39 + C1S, Az39 + LSR1, Az39 + LSR1 + C1S, and control without inoculation. Microalgae inoculation increased wheat tillering under both AM and CM (Fig. 3 a and 3 c). In AM conditions, most of the plants had tillers (Fig. 3 a). Under CM, CM, Az39, and Az39 + LSR1 + C1S treatments also induced higher tillering phenotype in the plants (Fig. 3 c). No significant differences were found in aerial dry weight between the inoculation treatments and the control group (Fig. 3 d, 3 e, and 3 f). However, the root dry weight of C1S-inoculated seedlings under AM was higher than in the non-inoculated ones (Fig. 3 g). Under CM, the roots could not be collected as a whole, rendering them unanalyzable (results not shown). 3.3 Microalgae-PGPB inoculation enhance grain wheat productivity in the field Inoculated plants showed a 36% overall increase in GY by the triple inoculation and a 14% and 26.2% increase in crop water productivity (CWP) under AM and CM, respectively. Notably, the response of wheat GY and several yield components to inoculation treatments was notably affected by tillage practices before sowing. Grain yield and CWP remained unchanged under NT for all treatments and only a slight non-statistically significant increase in GY and CWP was observed with Az39 and Az39 + C1S inoculation under this management (Table 1 and Fig. 4 ). Table 1 shows that the yield components that contribute to the increase in productivity observed with Az39 + LSR1 + C1S under AM and CM differed. Under AM, the number of kernels per spike was 46,6%, 29.9% and 43.7% higher in C1S, C1S + Az39, and Az39 + LSR1 + C1S, respectively, compared to the non-inoculated plants. A marginal enhancement of 2.7% and 3.8% in thousand-grain weight occurred in the Az39 + LSR1 and Az39 + LSR1 + C1S treatments, respectively; however, this variation was not statistically significant. On the other hand, under CM, the number of kernels per spike did not reveal any differences between the inoculated and control plants. But, interestingly, the number of spikes.m -2 in Az39 + LSR1, and Az39 + LSR1 + C1S treated plants were 27.6% and 28.4% higher, respectively. Consequently, the number of grains.m -2 were 25.7% and 34.7% higher for Az39 + LSR1- and Az39 + LSR1 + C1S-treated plants, respectively (Table 1 ). Table 1 Effect of inoculation treatments and field managements on the yield components in wheat Parameter Year Management Uninoculated Az39 C1S Az39 + LSR1 Az39 + C1S Az39 + LSR1 + C1S Number of spikes (spikes. m − 1 ) 2022 AM 338.7 ± 30.7 a 321.6 ± 68.6 ab 247.5 ± 31.1 b 322.5 ± 79.6 ab 292.5 ± 33.4 ab 260.0 ± 46.4 b NT 476.2 ± 115.23 a 675.0 ± 115.0 a 536.2 ± 53.3 a 611.2 ± 56.8 a 538.3 ± 39.2 a 598.8 ± 30.9 a 2024 CM 303.7 ± 49.9 b 336.2 ± 32.6 ab 326.3 ± 60.4 ab 387.5 ± 55.9 a nd 390.0 ± 33.0 a Kernels per spike ( −1 ) 2022 AM 28.1 ± 2.8 b 31.9 ± 3.1 ab 41.2 ± 4.6 a 29.9 ± 1.4 b 36.5 ± 2.2 a 40.4 ± 4.8 a NT 34.6 ± 4.1 ab 30.4 ± 3.9 b 35.7 ± 2.4 a 29.0 ± 4.0 b 36.7 ± 5.0 ab 30.1 ± 1.5 b 2024 CM 21.7 ± 1.5 a 21.8 ± 2.5 a 21.9 ± 3.1 a 21.7 ± 4.0 a nd 22.6 ± 3.1 a Number of grains (m 2 ) 2022 AM 5123 ± 501.5 a 5454 ± 402.4 a 5338 ± 587.7 a 5211 ± 245.0 a 5658 ± 382.1 a 5740 ± 595.5 a NT 4884 ± 568.5 a 5367 ± 632.0 a 5007 ± 357.4 a 4668.± 668.6 a 5466 ± 637.6 a 4583 ± 99.5 a 2024 CM 6529 ± 751.5 b 7393 ± 1458.3 b 7227 ± 2155.3 ab 8205 ± 910.1 ab nd 8794 ± 1243.6 a Test weight (Kg. hl − 1 ) 2022 AM 75.8 ± 0.26 a 76.1 ± 0.3 a 75.8 ± 0.4 a 76.1 ± 0.3 a 75.9 ± 0.2 a 75.6 ± 0.2 a NT 74.3 ± 0.5 b 74.5 ± 0.4 ab 74.5 ± 0.8 a 74.3 ± 0.4 b 74.2 ± 0.4 b 74.4 ± 0.6 ab 2024 CM 81.4 ± 0.5 a 80.9 ± 0.4 a 81.2 ± 0.1 a 81.2 ± 0.2 a nd 81.3 ± 0.4 a 1000-grains weight (g) 2022 AM 36.9 ± 0.6 ab 37.3 ± 1.1 ab 36.7 ± 0.7 b 37.9 ± 0.1 a 37.1 ± 1.2 ab 38.3 ± 0.9 a NT 36.7 ± 0.35 a 36.7 ± 0.9 a 35.8 ± 0.5 a 36.9 ± 1.1 a 36.0 ± 1.2 a 36.4 ± 1.2 a 2024 CM 46.7 ± 0.78 a 45.8 ± 1.5 a 46.9 ± 0.9 a 46.1 ± 1.8 a nd 46.9 ± 1.0 a Grain yield (Kg. ha − 1 ) 2022 AM 1927 ± 196.3 b 2065 ± 111.5 ab 1957 ± 216.0 b 1972 ± 396.2 b 2100 ± 186.3 ab 2244 ± 190.9 a NT 1791 ± 205.7 ab 1964 ± 214.9 a 1791 ± 139.1 b 1724 ± 258.3 b 1964 ± 213.0 a 1709 ± 78.1 b 2024 CM 3046. ± 354.7 b 3406 ± 753.4 b 3402 ± 1069.4 ab 3792 ± 524.2 ab nd 4130 ± 586.6 a Harvest index (%) 2022 AM 36.9 ± 1.9 a 35.9 ± 0.4 a 38.2 ± 1.9 a 36.7 ± 1.2 a 37.8 ± 2.4 a 38.0 ± 1.8 a NT 31.2 ± 0.5 a 25.2 ± 8.1 a 27.0 ± 8.3 a 24.9 ± 7.9 a 33.2 ± 1.1 a 30.2 ± 3.1 a 2024 CM 45.6 ± 0.9 b 47.1 ± 2.2 b 44.4 ± 3.2 b 48.3 ± 1.5 a nd 46.9 ± 2.2 b *Different letters in each row indicate significant differences among treatments at p < 0.05 Historical records from Meteorological Services in Argentina indicated that during 2022 (Buss et al., 2023 ) and 2024 (SMN, 2024), the crop season was under the influence of ´La Niña´ ENSO stage, resulting in significantly reduced precipitation recorded at the INTA weather station during most of the crop cycle (ESM 1). In both 2022 and 2024 crop seasons, water scarcity was especially severe throughout the plant's tillering stage (Zadoks stage 2, mid-September). Consequently, to thoroughly examine the effect of inoculation on drought resilience, wheat plants response under induced drought stress in chamber experiments were studied. 3.4 Microalgae and microalgae-PGPB inoculation confer drought tolerance to wheat seedlings To assess if seed inoculation could promote drought stress resilience, suspensions with Az39, LSR1, C1S, Az39 + LSR1, Az39 + C1S, LSR1 + C1S, or Az39 + LSR1 + C1S were inoculated on dry seeds, which were sown in pots watered at field capacity until seedlings reached the Zadoks stage 2. At this point, seedlings were maintained under moderate drought stress condition (MS) in a growth chamber for 7 d. The relative water content (RWC) of wheat leaves of Az39, LSR1, C1S, Az39 + LSR1, and Az39 + LSR1 + C1S treatments was higher than that of the untreated control (Fig. 5 a). Shoot aerial dry weight was 55% higher in plants treated with Az39, LSR1, or microalgae C1S individually, when compared to the non-inoculated plants (Fig. 5 b). Furthermore, LSR1 and C1S single-inoculation treatments differentially modified the root architecture upon drought stress, increasing the total root length, projected area, and branching (Fig. 5 d, e, f and g). However, in accordance with field experiments, only microalgae-inoculated seedlings significantly increased root dry weight by a mean of 50% (Fig. 5 c). As expected, the osmoprotectants proline and soluble sugars (SS) accumulated in non-inoculated drought-stressed seedlings (Fig. 5 h), indicating a clear drought stress response. In contrast, all inoculation treatments prevented proline accumulation (Fig. 5 h). Conversely, sugars content was diminished in all the treatments containing microalgae and in Az39 single inoculation. 4. Discussion Our findings revealed that co-inoculation with Pseudomonas strain LSR1 or microalgae Scenedesmus obliquus C1S increases Azospirillum argentinensis Az39 root colonization by tenfold (Fig. 1 ). Furthermore, we show that the single inoculation with Azospirillum , presumably due to its ability to produce abscisic acid (ABA), delays germination and early root elongation (Cassán et al., 2020 ). Nonetheless, co-inoculation with LSR1 counteracts this inhibition by Aza39, presumably by an opposite phytohormone effect (Maroniche et al., 2016 ). Notably, inoculation with microalgae also stimulates germination and post-germinative growth. This seed priming phenotype exerted by microalgae inoculation could also be explained by its phytohormone profile, mainly enriched in JA and cis-Zeatin (Fig. 2 ). It has been reported that seed treatment with elicitors like JA or cytokinin can enhance seed germination rate, particularly under stressful conditions (Iqbal et al., 2006 ). These findings provide a new perspective on the properties of eukaryotic microalgae, specifically regarding their hormonal release on seed surfaces, the priming of seedlings, and the introduction of distinctive traits into microalgal-bacterial synthetic consortia formulations, enhancing bacterial root colonization abilities. Field experiments revealed that microalgal inoculation increased wheat tillering and root dry weight. Moreover, a 36% increase in GY and a 26.2% increase in CWP was observed in response to the inoculation with microalgae-PGPB triple consortia. Interestingly, inoculation efficiency is significantly affected by tillage practices before sowing, since GY and CWP remained unchanged under NT for all treatments (Fig. 4 , Table 1 ). Under NT, the top soil exhibits more compaction relative to conventional tillage (Lipiec et al., 1995 ). Physical alterations in soil resulting from no-till practices might adversely impact the development of primary root axes, especially during the early phases of plant development (Ferreira et al., 2021 ). Heightened resistance resulted in an exponential reduction in root length (Martino & Shaykewich, 1994 ). Since root exudates play a crucial role in shaping the soil microbiome, to maximize the functionality of beneficial bacteria, it is essential to apply them to crops in ways that align with environmental conditions that also favors root development. These findings highlight the necessity of evaluating microbial inocula while also taking soil management into account in order to maximize the growth-promoting effects in productive scenarios. The seasons in which we conducted this research on the field represent an interesting case study representing possible future conditions related to climate change. Drought conditions on the vegetative stages of wheat growth (June–September, Fig. 1 S) impacted throughout the South American region in 2022–2023- and -to a lesser extent- in 2024–2025, both under the influence of the ENSO stage ´La Niña´. Between 2019 and 2024, persistent La Niña conditions in Argentina correlated with an exceptional drought, exacerbated by several hot waves throughout the entire country (Lopez-Ramirez et al., 2024 ). In this context, field experiments suggested that wheat plants' resilience to water scarcity under field conditions was enhanced by the Az39 + LSR1 + C1S synthetic community inoculation. Chamber trials under drought stress exhibit a 55% enhancement in aerial dry weight with the sole inoculum of Az39, LSR1, and microalgae C1S. Additionally, as observed under field trials, seedlings inoculated with microalgae exhibited an average increase of 50% in root dry weight and had a greater effect on total length, projected area and higher root branching than non-inoculated plants. Osmoprotectants shelter organisms from stress by acting as osmolytes, and the most important osmolytes found in plants include sugar alcohols, soluble sugars, polyols, proline, and betaine (Mohammadi Alagoz et al., 2023 ). As proline is a thoroughly studied osmoprotectant, its determination represents a very valuable analytical tool to probe the physiological status of plants regarding drought conditions (Mu et al. 2021). In this context, sugar content in drought-stressed plants was diminished in all the treatments containing microalgae. On the other hand, proline levels appear to more closely reflect physiological stress than sugar levels, as plants treated with Az39, LSR1, and C1S have the lowest proline levels, a high relative water content in leaves, and also significantly greater aerial dry weight, indicating an improved water status of the plants. These results show that inoculated plants exhibit reduced proline accumulation, indicating a diminished stress response, potentially mitigated by an alternative mechanism. Overall, the strongest response, in terms of growth enhancement and reduction in stress response under induced drought conditions, was observed with the single inoculation of the microalgae. The detection of microalgae on plant tissues only throughout the initial days post-root emergence (Fig. 2 ) suggests that the phenotypic adjustments and the mitigation of drought stress resulting from microalgae inoculation, at least in growth chamber studies, can be attributed to early seed priming, supported by the increased concentrations of cytokinin and jasmonic acid in the phytohormone profile of the microalgae, in addition to other potential biostimulant metabolites secreted on the seed surface. Alternatively, microalgae released on the soil can exert other beneficial effects on the plant, either by hormonal release, and/or by altering the rhizosphere microbiome. 5. Conclusion The results presented herein demonstrate a promising prospect for the developing of a novel eukaryotic microalgae-PGPB synthetic consortia inoculant that boosts root colonization by PGPBs and enhances wheat crop water productivity under challenging field conditions, acting as a complementary strategy for climate change adaptation to ensure food security. To the best of our knowledge, this study is the first to demonstrate a direct inoculation of eukaryotic microalgae on wheat seeds with growth-promoting properties for plants under drought stress. It is noteworthy that under both growth chamber and field conditions, these microalgae are fully compatible with rhizosphere bacteria, even amplifying their growth-promoting activities. The fact that drought protection under drought stress could be provided by eukaryotic microalgae seed inoculation raises interesting biotechnological ramifications to explore. Further research into the physiological mechanisms behind this stress tolerance prompted by this treatment will present new insights into the use of eukaryotic microalgae in agronomic scenarios. Declarations Acknowledgements The technical assistance of Juan Toledo, Marcio Muñoz, María Verónica Martino, Macarena Pérez-Cenci, and Natalia Almada is gratefully acknowledged. We also thank Marcos Lancia and Victoria Martin for valuable suggestions. No conflicts, informed consent, or human or animal rights are applicable to this study Conflict of Interest The authors declare that they have no conflict of interest. Funding LSR, GM, EdG, LC and LAP are members of CONICET. C.M-F and EdG are members of INTA A.M.G.O. is a CONICET Fellow. C.C. is a retired UNMdP Research Professor. L.A.P. is a Research Professor of UNMdP. 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Agric Water Manage 273:107901 Zaheer MS, Ali HH, Iqbal MA, Erinle KO, Javed T, Iqbal J, Hashmi MIU, Mumtaz MZ, Salama EA (2022) Cytokinin production by Azospirillum brasilense contributes to increase in growth, yield, antioxidant, and physiological systems of wheat (Triticum aestivum L). 13:886041Kalaji HMJFiM Zhang Q, Men X, Hui C, Ge F, Ouyang F (2022) Wheat yield losses from pests and pathogens in China. Agric Ecosyst Environ 326:107821 Additional Declarations The authors declare no competing interests. Supplementary Files Supplementalmaterial.pdf Graphicalabstract.tif Graphical Abstract Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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09:36:46","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":159223,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/10a159dd59f6b893571b87b3.html"},{"id":91973655,"identity":"54368060-43fb-432e-b72f-6e0e69c798dd","added_by":"auto","created_at":"2025-09-23 09:36:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3285027,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGermination, early root growth, and bacterial root colonization in inoculated seedlings. \u003c/strong\u003eThe percentage of seedlings non-germinated (NG), with 0-5, 5-10, or more than 10 mm radicle length after 4 d post-imbibition (dpi), was compared among non-inoculated (ni) and inoculated seedlings (a). \u003cem\u003eA. argentinense \u003c/em\u003eAz39 (left panel) or \u003cem\u003ePseudomonas sp. \u003c/em\u003eLSR1 (right panel) root colonization was measured as CFU. g\u003csup\u003e-1\u003c/sup\u003e of root fresh weight (b).\u0026nbsp; Bacterial strains distribution on the roots of seedlings was analyzed at 5 dpi by confocal laser scanning microscopy (c). Phenotype comparison of seedlings of the different treatments at 5 dpi. Bar scale: 1 cm (d).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/97db79ef505e9e0550bf9541.png"},{"id":91973665,"identity":"c36198be-64ab-4b70-b6cb-418713eeea37","added_by":"auto","created_at":"2025-09-23 09:36:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11462707,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicroalgae localization in germinating seedlings and phytohormone profile. \u003c/strong\u003eMicroalgal localization observed in radicle protruding seeds (1 dpi) with an optical magnifier (a). Transverse sections (1 mm thick) of the trichome region of the seed (b) were stained with SYTOX Green, and both chlorophyll autofluorescence and green fluorescence were analyzed by light and fluorescence microscopy (c). Bar scale: 20 mm (b and c). \u003cem\u003eS. obliquus \u003c/em\u003eC1S phytohormonal profile. Levels of IAA , tZ, cZ, tZR, cZR, SA, JA, ABA and GA\u003csub\u003e3\u003c/sub\u003e were analyzed by UHPLC-MS/MS (d)\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/2aa4989f4f15556fb551eb89.png"},{"id":91975045,"identity":"6d7975d3-6dab-4b28-8fae-5a46dd3c4e31","added_by":"auto","created_at":"2025-09-23 09:52:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":254009,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicroalgae and PGPB-inoculated wheat vegetative growth in the field under different management practices. \u003c/strong\u003eThe percentage of plants with at least one tiller (black) or without tillers (white) was compared among treatments by an Odds Ratio (OR) Pairwise Comparison Analysis in AM (\u003cstrong\u003ea\u003c/strong\u003e), NT (\u003cstrong\u003eb\u003c/strong\u003e), and CM (\u003cstrong\u003ec\u003c/strong\u003e). Aerial (\u003cstrong\u003ed\u003c/strong\u003e, \u003cstrong\u003ee,\u003c/strong\u003e and \u003cstrong\u003ef\u003c/strong\u003e) and root (\u003cstrong\u003eg\u003c/strong\u003e and \u003cstrong\u003eh\u003c/strong\u003e) dry weights in AM (\u003cstrong\u003ed and g\u003c/strong\u003e), NT (\u003cstrong\u003ee \u003c/strong\u003eand\u003cstrong\u003e h\u003c/strong\u003e), and CM (\u003cstrong\u003ef\u003c/strong\u003e) were measured at tillering. One-way ANOVA followed by post-hoc Fisher LSD test was used to detect differences between means. Different letters on the bars indicate significant differences between treatments (p ≤ 0.05)\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/1d4cfa1a9c82fe7c972610da.png"},{"id":91975046,"identity":"c0b6bba4-f3db-4551-ae09-9a23998e8f8f","added_by":"auto","created_at":"2025-09-23 09:52:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":522128,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCrop water productivity under different field managements. \u003c/strong\u003eThe CWP of wheat was measured under AM (a), NT (b) and CM (c). One-way ANOVA followed by the post-hoc Fisher LSD test was used to detect differences between means. Different letters on the bars indicate significant differences between treatments (p ≤ 0.05).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/3f5be86630d504d414da6323.png"},{"id":91973661,"identity":"036eeafc-7af6-4570-98c1-198c8cf4e396","added_by":"auto","created_at":"2025-09-23 09:36:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2081147,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDrought stress response of inoculated wheat seedlings. \u003c/strong\u003eAnalysis of RWC (a), aerial (b) and root (c) dry weight, total root length (d), projected area (e), and number of forks (f). Representative scan images of treated roots are also shown (g). \u0026nbsp;Proline (h) and soluble sugar content (i) in the aerial portion were measured. Data were statistically analyzed by one-way ANOVA. Different letters on the histograms indicate significant differences according to Tukey's post-test (p ≤ 0.05).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/4714bbec3eb1394e2ea832a3.png"},{"id":91984937,"identity":"de791310-7e75-490c-8629-dcdf8d131e06","added_by":"auto","created_at":"2025-09-23 11:48:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17461404,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/308b0a30-1ffe-4fda-8efc-f1b375fee1e3.pdf"},{"id":91973658,"identity":"c049fe55-4ff8-4c83-ae17-28e9c6959c5a","added_by":"auto","created_at":"2025-09-23 09:36:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":151891,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/04b9ef3372c634ec9fdadc84.pdf"},{"id":91974734,"identity":"5b81bf20-caa2-478c-a5dc-69905560709a","added_by":"auto","created_at":"2025-09-23 09:44:45","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1070144,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical Abstract\u003c/p\u003e","description":"","filename":"Graphicalabstract.tif","url":"https://assets-eu.researchsquare.com/files/rs-7311767/v1/08f2911f9f64cf1ac37539ae.tif"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEukaryotic microalgae-bacteria synthetic consortia boost crop productivity and drought tolerance in bread wheat (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTriticum aestivum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eInoculation of eukaryotic microalga-PGPB synthetic consortia results in a 36% increase in wheat grain yield.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSeedlings inoculated with microalgae exhibit improved water status and growth under drought conditions\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;The efficacy of inoculation is influenced by the tillage methods employed prior to sowing.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eWheat is a major worldwide crop, representing over 20% of the calories and proteins harvested worldwide (Shiferaw et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and providing as the primary food supply for over 40% of the global population (Zhang et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Contemporary management approaches predominantly depend on the utilization of external inputs, including insecticides for pest and disease management, mineral fertilizers to enhance plant nutrition and biomass, and sometimes irrigation to mitigate water stress circumstances (You et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The yield of rain-fed crops is linked to the precipitation they receive throughout their growth cycle (Andrade \u0026amp; Satorre, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Thus, the careful monitoring of crop management to ensure water efficiency and alleviation of the negative effects of water scarcity, is crucial for sustainable crop production. This challenge is amplified by the anticipated increase in rainfall variability due to climate change, which, in the case of wheat bread, production can decrease up to 60% (Aramburu Merlos et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In the southern hemisphere, the potential grain surplus due to appropriate irrigation is highly variable due to the influence of the El Ni\u0026ntilde;o-Southern Oscillation phenomenon (ENSO). \u0026acute;El Ni\u0026ntilde;o\u0026acute; phase is reflected as an increase in spring/summer rainfalls and higher summer crop yields, while the opposite occurs with \u0026ldquo;La Ni\u0026ntilde;a\u0026rdquo; events, which typically result in dry years. In this context, farmers face significant challenges due to environmental unpredictability, since different seasons require different management strategies based on rainfall patterns and timing (Edreira et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Conservation tillage has gained popularity in recent years due to its efficacy in mitigating soil degradation and enhancing soil water retention (Hashimi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). No-tillage (NT) systems might have potential benefits over conventional tillage (CT) systems under specific management situations. These advantages encompass a diminished number of machine runs over the field, enhanced aggregate stability, the protective influence of agricultural residues remaining on the soil (Sithole et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), enhancing soil water retention and a greater prevalence of biopores (Blanco-Canqui \u0026amp; Ruis, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hashimi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, when subjected to NT management, certain soils might suffer adverse impacts, including heightened bulk density on the 0\u0026ndash;20 cm layer of the soils (Dı́az-Zorita \u003cem\u003eet al.\u003c/em\u003e, 2002; Mart\u0026iacute;nez et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and diminished oxygen diffusion rates (Khan \u0026amp; Science, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1996\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePlant-growth-promoting bacteria (PGPBs) are a group of rhizospheric beneficial bacteria that have the potential to enhance crop productivity and acclimation to abiotic stress through multiple mechanisms (Bhattacharyya \u003cem\u003eet al.\u003c/em\u003e, 2012; Cass\u0026aacute;n et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). \u003cem\u003eAzospirillum argentinensis\u003c/em\u003e has a direct influence on the plant, via the synthesis of several phytohormones, including indole acetic acid (Spaepen et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), abscisic acid (Wu et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), gibberellins (Cohen et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), salicylic acid (Sahoo et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), cytokinin (Zaheer et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and nitric oxide (NO) (Molina-Favero et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). On the other hand, fluorescent pseudomonads, major inhabitants of the rhizosphere, have both direct and indirect favorable impacts on plant development (Choudhary et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) Pseudomonas strains synthesize a diverse array of chemicals exhibiting antibacterial properties, with 2,4-diacetylphloroglucinol (DAPG) being among the most extensively researched (Weller et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These PGPBs are presently marketed as inoculants, and strain compatibility is an absolute requirement to achieve increased plant growth promotion by co-inoculation of several PGPBs (Pagnussat et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; D\u0026iacute;az et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A critical aspect of this strategy is that PGPBs inoculated onto seeds must survive on the dry or semi-dry surface tissues of the seed until appropriate conditions emerge for root colonization. Consequently, inoculants often require adjuvants or seed-coating treatments to enhance their viability (Rocha et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough much less studied than bacteria, single-celled eukaryotic algae (commonly known as microalgae) also exhibit plant biostimulant properties. Microalgae are widespread in soils, contributing to their organic carbon content, structure, and moisture. In addition to releasing plant hormones and other growth-stimulating substances, some microalgae produce a complex matrix of EPS. These EPS are believed to shield co-inhabiting bacteria from desiccation and UV radiation, in a microenvironment that provide them with essential nutrients and hormones for their survival and growth, and drive complex mutualistic interactions within microalgae-bacteria consortia (Perera et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this sense, when co-cultured, auxins produced by \u003cem\u003eAzospirillum baldaniorum\u003c/em\u003e Sp245 mitigate the oxidative stress of the microalgae \u003cem\u003eScenedesmus obliquus\u003c/em\u003e C1S, under both saline stress (Pagnussat et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)d deficiency (Pagnussat et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), thereby promoting the growth of the microalgae. Additionally, \u003cem\u003eA. baldaniorum\u003c/em\u003e and \u003cem\u003eS. obliquus\u003c/em\u003e engage in mixed biofilms, a property which could contribute to the higher rates of bacterial survival observed in co-culture, particularly under salinity stress (Pagnussat et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eField inoculation of crops with beneficial microorganisms is a sustainable approach to improve crop productivity and stress resilience. Nonetheless, PGPB performance may fluctuate due to environmental variables, microbial competition, and agronomical practices (Bulgarelli et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In recent studies, tillage practice was identified as the primary factor influencing the microbiome in the rhizosphere (Behr et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Moreover, on wheat soils, tillage methods have a significant interactive effect with the water regime on root-associated bacterial and fungal populations (Romano et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), underscoring the enduring legacy of tillage practices likely attributable to variations in physical soil properties and chemical composition. This highlights the necessity for additional research to improve inoculation techniques to provide reliable agricultural benefits.\u003c/p\u003e\u003cp\u003eConsidering the biostimulant properties of microalgal exudates (La Bella et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), we hypothesize that microalgae can offer emergent properties to multispecies PGPB inoculants. In this work, we explored whether microalgae incorporated into bacterial inoculants can (i) favor the survival of bacteria in the rhizosphere, and (ii) improve wheat water productivity under field conditions and different tillage managements. Our results establish, for the first time, the potential of microalgae-bacteria communities as bioinputs for crops in the field, an area that still remains unexplored and holds significant implications for developing novel multi-species inoculants.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Microorganisms and growth conditions\u003c/h2\u003e\u003cp\u003e\u003cem\u003eScenedesmus obliquus\u003c/em\u003e C1S (Do Nascimento et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and \u003cem\u003eAzospirillum argentinense\u003c/em\u003e Az39 and \u003cem\u003ePseudomonas\u003c/em\u003e sp. LSR1 were used as study microorganisms. \u003cem\u003eS. obliquus\u003c/em\u003e C1S was routinely cultured in BG11 medium containing 10 mM NaNO\u003csub\u003e3\u003c/sub\u003e as a nitrogen source and 0.42 g x L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e NaHCO\u003csub\u003e3\u003c/sub\u003e to buffer CO\u003csub\u003e2\u003c/sub\u003e supplementation. Recombinant fluorescent derivatives of \u003cem\u003eA. argentinense\u003c/em\u003e Az39 and \u003cem\u003ePseudomonas\u003c/em\u003e LSR1, Az39-dsRED (Puente et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and LSR1-eGFP (Maroniche et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) were also used when required. All experiments were initiated with 10\u003csup\u003e6\u003c/sup\u003e cells of \u003cem\u003eS. obliquus\u003c/em\u003e C1S, counted under a light microscope (Leica DM500, Germany) on a Newbauer chamber, 10\u003csup\u003e6\u003c/sup\u003e cells of \u003cem\u003eA. argentinensis\u003c/em\u003e Az39 and/or \u003cem\u003ePseudomonas sp.\u003c/em\u003e LSR1 (estimated by optical density at 600 nm, OD\u003csub\u003e600\u003c/sub\u003e) per seed. Starter single-species cultures of Az39 and LSR1 were cultured in Luria-Bertani medium (LB) without salt at 30\u0026deg;C with orbital shaking (150 rpm) for 18 h. Tetracycline at 25 \u0026micro;g mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was included in the medium for culture of the recombinant fluorescent strains.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Seed inoculation and root colonization\u003c/h2\u003e\u003cp\u003eWheat seeds (\u003cem\u003eTriticum aestivum\u003c/em\u003e (L.) cv. MS INTA 221 (long-cycle cultivar) and cv. MS INTA 819 (short-cycle cultivar) were used for the 2022 campaign and growing chamber trials, and 2024 campaign, respectively. Seeds were superficially sterilized (10 min with 50% sodium hypochlorite) and inoculated with a suspension of microalgae alone, bacteria alone, bacteria consortium, or with a triple consortium (microalgae plus both bacterial strains). For root colonization analysis, the fluorescent bacterial variants were used. Suspensions with microorganism were applied to the seeds at a final inoculation volume of 5 \u0026micro;l per seed, and stored on paper envelopes at 25\u0026deg;C for 24 h before sowing.\u003c/p\u003e\u003cp\u003eRoot colonization was evaluated 3 d after germination on agar-water plates. Roots were cleaned and crushed in a mortar, and bacterial colony-forming units (CFU). g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e were evaluated using the microdrop technique as previously described (Herigstad et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Roots colonized by fluorescent bacteria (Az39-dsRED and LSR1-eGFP were also directly observed with a Nikon C1 confocal laser microscope. LSR1-egfp and Az39-dsred bacteria were excited/detected at 488/550 nm and 543/ 650 nm, respectively. Images were analyzed using Nikon EZ-C1 Free viewer software.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Microalgae localization and viability\u003c/h2\u003e\u003cp\u003e\u003cem\u003eScenedesmus. obliquus\u003c/em\u003e C1S localization and viability were examined in radicle-protruding seeds at one day post-imbibition (1 dpi). Transversal sections of the seed trichomes region, each one one- millimeter thick, were stained with SYTOX Green at a final concentration of 1 \u0026micro;M for 30 min in the dark at 4\u0026deg;C. They were subsequently analyzed using light and fluorescence microscopy with a Nikon E600 microscope, equipped with a B-2A cube that include 450\u0026ndash;490 nm excitation and 500\u0026ndash;515 nm emission filters, utilizing a 40.0xA/1.25/0.17 oil-immersion Nikon lens. Images were captured using an Olympus DP72 digital camera and Cellsens Entry imaging software.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Analysis of microalgal phytohormone profile by Ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS)\u003c/h2\u003e\u003cp\u003eMicroalgal cells were resuspended in 1.5 mL 1 M NaCl, sonicated at a 50% power-output (Vibra-Cell, model VCX-130, Sonics Inc.) for three cycles of 1 min each (10 sec on, 1 sec off), immediately frozen with liquid nitrogen, and lyophilized. Jasmonic acid (JA), abscisic acid (ABA), salicylic acid (SA), indole-3-acetic acid (IAA), cis-zeatin (cZ), cis-zeatin riboside (cZR), trans-zeatin (tZ), trans-zeatin riboside (tZR), and gibberellic acid (GA\u003csub\u003e3\u003c/sub\u003e) were extracted using 100 mg of lyophilized microalgae. The samples were processed according to (Giannarelli et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and the resulting extracts were diluted 10-fold with ultrapure water, filtered through a 0.22 \u0026micro;m nylon filter, and analyzed. Phytohormone concentrations were determined by UHPLC (UHPLC ACQUITY I-Class UPLCTM) coupled to tandem mass spectrometry (XEVO TQ-XS) equipped with an ACQUITY UPLC HSS C18 Column (1.8 \u0026micro;m, 100 x 2.1 mm) (Waters). The mobile phases were water: methanol 95:5 (phase A) and methanol (phase B), both modified with ammonium acetate 0.1 mM and formic acid 0.01% v/v. The flow rate was set at 0.3 mL.min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and the column temperature was 45\u0026deg;C. The chromatographic separation was performed with the following gradient elution conditions: B was 10% (v/v) in 0\u0026thinsp;\u0026minus;\u0026thinsp;0.5 min, linearly increased to 90% (v/v) in 0.5\u0026thinsp;\u0026minus;\u0026thinsp;11 min; held at 90% for 11\u0026thinsp;\u0026minus;\u0026thinsp;12.5 min, and returned to the initial condition in 1.5 min.\u003c/p\u003e\u003cp\u003eAn auto-sampler was used to inject 10 \u0026micro;L of the samples. The XEVO TQ-XS tandem quadrupole mass spectrometer was operated in positive and negative mode with the electrospray-ionization (ESI) source. The operating parameters were optimized under the following conditions: capillary voltage, 3 kV, ion source temperature 150\u0026deg;C, desolvation temperature 500\u0026deg;C, cone gas flow 150 L. h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, desolvation gas flow 800 L h\u0026thinsp;\u0026minus;\u0026thinsp;1 (both gases were nitrogen obtained from a nitrogen generator) and collision gas flow 0.15 mL min\u0026thinsp;\u0026minus;\u0026thinsp;1 (argon gas 99.995% with a pressure of 4.04\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;3 mbar in the T-Wave cell). Mass Lynx v 4.2 software (Waters, USA) was used to process quantitative data obtained from calibration standards and samples. The experiments were performed in triplicate.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Drought stress application, management, and plant sampling\u003c/h2\u003e\u003cp\u003eIn the growth chamber experiments, inoculated seeds were sown in 100 mL plastic pots filled with commercial substrate (Turba Plus, Carluccio) with 20 plants per treatment. Each pot was watered to 100% field capacity (FC) using distilled water until seedlings reached the Zadoks stage 13 (Haun stage 2.6), when a moderate drought stress (MS) corresponding to 40% of FC was applied to each treatment. Watering was withheld until the soil FC reached 40%, and drought stress levels were maintained for 7 d by daily weighing of pots and adding distilled water to compensate for water loss.\u003c/p\u003e\u003cp\u003eAfter 7 d under drought stress, the uppermost, fully expanded leaves from six plants of each treatment were sampled on the 7th day of drought stress. Six leaves from each treatment were used to determine leaf relative water content (RWC). Leaf RWC was determined according to the standard method proposed by Barrs and Weatherly (1962) as RWC = (FW\u0026thinsp;\u0026minus;\u0026thinsp;DW) / (TW\u0026thinsp;\u0026minus;\u0026thinsp;DW), where FW is fresh leaf weight, DW is dry weight, and TW is turgid weight after 24 h floating in distilled water at 4\u0026deg;C in darkness. Four plants from each treatment were used to analyze root and shoot fresh and dry weight. Roots were subsequently scanned to determine total root length (RL), projected area, and the number of forks per root using the WinRHIZO 2007 software (Regent Instruments, Ottawa, Canada).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Miscellaneous Methods\u003c/h2\u003e\u003cp\u003eFresh leaf samples were frozen in liquid nitrogen, powdered with liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C For total sugars and proline determinations.\u003c/p\u003e\u003cp\u003eSugars in frozen leaf samples (100 mg) were extracted using ammoniacal water (pH 8.0) in 100\u0026ordm;C bath for 5 min, followed by centrifugation at 10,000\u0026times;\u003cem\u003eg\u003c/em\u003e for 10 min after cooling. Total soluble sugar was measured colorimetrically by the anthrone method at 620 nm (Pontis, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Bader et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Glucose was used as standard for total soluble sugar measurements.\u003c/p\u003e\u003cp\u003eProline in frozen leaf samples (100 mg) was extracted with 3% (w/v) sulfosalicylic acid, and the extract was centrifuged at 15,200\u003cem\u003e\u0026times;g\u003c/em\u003e for 10 minutes. A sample of the clarified extract was combined with sulfosalicylic acid, glacial acetic acid, and acid-ninhydrin and incubated for 1 hour at 96\u0026deg;C. The reaction was halted by placing the tubes on ice. Two milliliters of toluene were incorporated into the mixture, stirred for 20 seconds, and allowed to settle for 5 minutes to facilitate phase separation. The absorbance of toluene (upper layer) was quantified at 520 nm, using toluene as the reference standard. The proline content was quantified utilizing a standard curve according to the methodology established by Bates (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1973\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Field Trials: experimental design\u003c/h2\u003e\u003cp\u003eField trials were conducted in two distinct years, concurrently at three locations without irrigation, under three different agronomic management systems: No-till (NT, site 1, sowing date June 22th, 2022), Agroecological Management (AM, site 2, sowing date June 22th, 2022), and Conventional Management (CM, site 3, sowing date August 1st, 2024). All trials were carried out at the Balcarce Experimental Station of the Instituto Nacional de Tecnolog\u0026iacute;a Agropecuaria (INTA) (37\u0026deg;46\u0026prime; 14\u0026Prime; S; 58\u0026deg;18\u0026prime; 23\u0026Prime; W; 113 m.a.s.l.) from June 2022 to January 2023 and from August 2024 to January 2025. According to pre-sowing soil analysis, the soil for the three sites was classified \u003cem\u003eas Typic Argiudoll\u003c/em\u003e (USDA Taxonomy) and fine thermic Petrocalcic Paleudoll (petrocalcic horizon at 140 cm) with a loamy surface texture and 4.39% organic matter (Site 1), 5.34% organic matter (Site 2) and 4.87% organic matter (Site 3). In site 1, the soil contained 18.4 P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e (ppm, 0\u0026ndash;20 cm depth), 14.1 N-NO\u003csub\u003e3\u003c/sub\u003e (ppm, 0\u0026ndash;20 cm depth), and 8.5 N-NO\u003csub\u003e3\u003c/sub\u003e (ppm, 20\u0026ndash;50 cm depth). In site 2, organic manure was applied at sowing, and the soil before planting contained 15.1 P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e (ppm, 0\u0026ndash;20 cm depth), 22.6 N-NO\u003csub\u003e3\u003c/sub\u003e (ppm, 0\u0026ndash;20 cm depth), and 6.3 N-NO\u003csub\u003e3\u003c/sub\u003e (ppm, 20\u0026ndash;50 cm depth). In site 3, the soil contained 34 P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e (ppm, 0\u0026ndash;20 cm depth), 1.36 N-NO\u003csub\u003e3\u003c/sub\u003e (ppm, 0\u0026ndash;20 cm depth), and 1.57 N-NO\u003csub\u003e3\u003c/sub\u003e (ppm, 20\u0026ndash;50 cm depth). For NT (year 2022, site 1), bread wheat was established in the residue of the preceding crop (soybean). For AM and CM (year 2022, site 1 and 2024, site 3), agronomic field operations before sowing include moldboard plowing to a depth of 30 cm, followed by seedbed preparation with a disc harrow. In site 3, summer crop (soybean) residues were incorporated during plowing. In sites 2 and 3, chemical fallow mulching was performed in the fall of both 2022 and 2024 (Paraquat 2,5 L.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Dry soil was fertilized at the planting line with 150 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of diammonium phosphate and with 408 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of nitrogen, as urea distributed in two moments, at tillering and at the beginning of the stem elongation period. Weeds, pests, and fungal diseases were chemically controlled.\u003c/p\u003e\u003cp\u003eEach assay consisted of four blocks, each 5 meters long, interspersed by a 2-m path. At sowing, the plots comprised of 7 furrows spaced every 20 cm and 6.5 m long (6.5 x 1.4 m). Each plot was sown with a density of 350 plants.m\u003csup\u003e-1\u003c/sup\u003e (high density). Around the experimental blocks, durum wheat was sown to reduce the edge effect in the trial. Harvest was performed mechanically along the five central rows of each plot (5 x 1 m). Daily meteorological data were obtained throughout the test by the meteorological station located in the experimental field (INTA-Balcarce, ESM 1 and ESM 2). Phenological stages, biomass and yield component were determined according to Pask et al. (2012). For each treatment, plant count. m\u003csup\u003e-1\u003c/sup\u003e, the number of tillers per plant, dry weight of aerial part and roots, and radical architecture, were analyzed at tillering. Biomass, harvest index, grain yield (GY), and grain quality were analyzed at harvest. Biomass was determined by sampling 2 linear m of each plot and weighing total dry aerial part. Harvest index was calculated as the percentage of total grain weight of the samples after threshing and biomass. Grain weight (GW) was determined by counting a 1,000-grain sample with an electronic counter, weighing it, and dividing the total weight by 1,000. Grain number per ha was then calculated as the quotient between GY and GW \u0026times; 1,000. Test weight was determined with a 500 mL-Schopper chondrometer. Based on wheat GY and precipitation, CWP was calculated (kg. m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Statistical analyses\u003c/h2\u003e\u003cp\u003eFor all sites, a randomized blocked design (RBD) was made in which the inoculation factor was analyzed at six levels with 4 repeats. The arrangement of the blocks was planned considering the inclination of the lot. For tilling, discrete data Odds Ratio Pairwise Comparison Analysis was used. One-way analysis of variance (ANOVA) followed by post-hoc Fisher LSD test or Tukey\u0026rsquo;s test, were used to detect significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between treatments. All analyses were performed in GraphPad Prism 7.04 or Python software (Odds Ratio Pairwise Comparison Analysis).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Co-inoculation of \u003cem\u003eAzospirillum\u003c/em\u003e with microalgae increases bacterial root colonization of wheat plants\u003c/h2\u003e\u003cp\u003eSince the early interaction between plants and microorganisms can significantly influence seedling establishment, germination and post-germinative growth was evaluated upon microalgal co-inoculation with well-established models of PGPB (Az39 and LSR1). The single inoculation with \u003cem\u003eA. argentinense\u003c/em\u003e Az39 delayed germination and early root elongation. Nonetheless, its co-inoculation with \u003cem\u003ePseudomonas\u003c/em\u003e sp. LSR1 not only prevented a delay in germination and growth, but also augmented these processes significantly (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, d). Likewise, the single inoculation with the microalgae \u003cem\u003eS. obliquus\u003c/em\u003e C1S stimulated germination and post-germinative development. Conversely, inoculation with the full community (Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S) did not affect the initial seedling growth markedly (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, d). These results show that each alternative inoculant (single, double, and triple) differentially affects seedling establishment, possibly due to hormone interactions on the seed priming process.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA prerequisite for plant-growth-promoting bacteria (PGPB) to promote plant growth is the establishment of a stable bacterial population on the roots (Okon \u0026amp; Labandera-Gonzalez, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Creus et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). However, when bacteria are inoculated on dry seeds, their survival and viability often diminish quickly, hindering root colonization (K\u0026ouml;hl et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To determine whether bacterial performance after seed inoculation can be improved by its co-inoculation with microalgae, PGPB root colonization was evaluated in wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e) at 3 d post-germination. \u003cem\u003eA. argentinense\u003c/em\u003e Az39 root colonization was approximately 10-fold higher when it was co-inoculated with the microalgae (3.19 x 10\u003csup\u003e6\u003c/sup\u003e CFU.g\u003csup\u003e-1\u003c/sup\u003e), either in the presence or absence of \u003cem\u003ePseudomonas\u003c/em\u003e sp. LSR1. Conversely, LSR1 root colonization exhibited consistency, independently of the presence of C1S (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). As expected, both bacteria were primarily located in the elongation zone, especially on root hairs for Az39, whereas LSR1 exhibited a more uniform distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Microalgae localization was also analyzed in imbibed and germinating seeds. As observed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, microalgae were mostly located within the trichomes of the seed coat during germination, and a release of microalgae into the surrounding medium was also noted. No microalgae were observed on the radicle or the apical axis during the early establishment of seedlings. Microalgae viability was also examined by a dual-fluorescence viability experiment using SYTOX Green along with chlorophyll autofluorescence as a contrast marker, to identify dead and living microalgal cells (Sato et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, no SYTOX Green fluorescence was observed, indicating that all seed-attached microalgae were viable. \u003cem\u003eS. obliquus\u003c/em\u003e phytohormone profile revealed high concentrations of JA and cZ, moderate levels of SA and IAA, and reduced amounts of tZ, cZR, and ABA. GA\u003csub\u003e3\u003c/sub\u003e and tZR were not detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Microalgae inoculation under conventional tillage enhanced wheat tillering and root weight\u003c/h2\u003e\u003cp\u003eTo analyze inoculated wheat treatments performance under agronomic scenarios, both NT and tilling managements were explored. Wheat field experiments were conducted in Balcarce, Buenos Aires, Argentina, in June 2022 with conventional tillage and agroecological management (AM) or NT and in August 2024 under conventional management (CM). The field trials were carried out using a completely randomized design with four repetitions and six inoculation treatments: Az39, C1S, Az39\u0026thinsp;+\u0026thinsp;C1S, Az39\u0026thinsp;+\u0026thinsp;LSR1, Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S, and control without inoculation.\u003c/p\u003e\u003cp\u003eMicroalgae inoculation increased wheat tillering under both AM and CM (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). In AM conditions, most of the plants had tillers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Under CM, CM, Az39, and Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S treatments also induced higher tillering phenotype in the plants (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). No significant differences were found in aerial dry weight between the inoculation treatments and the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). However, the root dry weight of C1S-inoculated seedlings under AM was higher than in the non-inoculated ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg). Under CM, the roots could not be collected as a whole, rendering them unanalyzable (results not shown).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Microalgae-PGPB inoculation enhance grain wheat productivity in the field\u003c/h2\u003e\u003cp\u003eInoculated plants showed a 36% overall increase in GY by the triple inoculation and a 14% and 26.2% increase in crop water productivity (CWP) under AM and CM, respectively. Notably, the response of wheat GY and several yield components to inoculation treatments was notably affected by tillage practices before sowing. Grain yield and CWP remained unchanged under NT for all treatments and only a slight non-statistically significant increase in GY and CWP was observed with Az39 and Az39\u0026thinsp;+\u0026thinsp;C1S inoculation under this management (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that the yield components that contribute to the increase in productivity observed with Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S under AM and CM differed. Under AM, the number of kernels per spike was 46,6%, 29.9% and 43.7% higher in C1S, C1S\u0026thinsp;+\u0026thinsp;Az39, and Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S, respectively, compared to the non-inoculated plants. A marginal enhancement of 2.7% and 3.8% in thousand-grain weight occurred in the Az39\u0026thinsp;+\u0026thinsp;LSR1 and Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S treatments, respectively; however, this variation was not statistically significant.\u003c/p\u003e\u003cp\u003eOn the other hand, under CM, the number of kernels per spike did not reveal any differences between the inoculated and control plants. But, interestingly, the number of spikes.m\u003csup\u003e-2\u003c/sup\u003e in Az39\u0026thinsp;+\u0026thinsp;LSR1, and Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S treated plants were 27.6% and 28.4% higher, respectively. Consequently, the number of grains.m\u003csup\u003e-2\u003c/sup\u003e were 25.7% and 34.7% higher for Az39\u0026thinsp;+\u0026thinsp;LSR1- and Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S-treated plants, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffect of inoculation treatments and field managements on the yield components in wheat\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eManagement\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUninoculated\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAz39\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eC1S\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAz39\u0026thinsp;+\u0026thinsp;LSR1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAz39\u0026thinsp;+\u0026thinsp;C1S\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAz39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eNumber of spikes (spikes. m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e338.7\u0026thinsp;\u0026plusmn;\u0026thinsp;30.7 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e321.6\u0026thinsp;\u0026plusmn;\u0026thinsp;68.6 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e247.5\u0026thinsp;\u0026plusmn;\u0026thinsp;31.1 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e322.5\u0026thinsp;\u0026plusmn;\u0026thinsp;79.6 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e292.5\u0026thinsp;\u0026plusmn;\u0026thinsp;33.4 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e260.0\u0026thinsp;\u0026plusmn;\u0026thinsp;46.4 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e476.2\u0026thinsp;\u0026plusmn;\u0026thinsp;115.23 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e675.0\u0026thinsp;\u0026plusmn;\u0026thinsp;115.0 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e536.2\u0026thinsp;\u0026plusmn;\u0026thinsp;53.3 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e611.2\u0026thinsp;\u0026plusmn;\u0026thinsp;56.8 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e538.3\u0026thinsp;\u0026plusmn;\u0026thinsp;39.2 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e598.8\u0026thinsp;\u0026plusmn;\u0026thinsp;30.9 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e303.7\u0026thinsp;\u0026plusmn;\u0026thinsp;49.9 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e336.2\u0026thinsp;\u0026plusmn;\u0026thinsp;32.6 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e326.3\u0026thinsp;\u0026plusmn;\u0026thinsp;60.4 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e387.5\u0026thinsp;\u0026plusmn;\u0026thinsp;55.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e390.0\u0026thinsp;\u0026plusmn;\u0026thinsp;33.0 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eKernels per spike (\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e40.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e35.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e21.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e22.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eNumber of grains (m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5123\u0026thinsp;\u0026plusmn;\u0026thinsp;501.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5454\u0026thinsp;\u0026plusmn;\u0026thinsp;402.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5338\u0026thinsp;\u0026plusmn;\u0026thinsp;587.7 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5211\u0026thinsp;\u0026plusmn;\u0026thinsp;245.0 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5658\u0026thinsp;\u0026plusmn;\u0026thinsp;382.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5740\u0026thinsp;\u0026plusmn;\u0026thinsp;595.5 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4884\u0026thinsp;\u0026plusmn;\u0026thinsp;568.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5367\u0026thinsp;\u0026plusmn;\u0026thinsp;632.0 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5007\u0026thinsp;\u0026plusmn;\u0026thinsp;357.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4668.\u0026plusmn; 668.6 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5466\u0026thinsp;\u0026plusmn;\u0026thinsp;637.6 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4583\u0026thinsp;\u0026plusmn;\u0026thinsp;99.5 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6529\u0026thinsp;\u0026plusmn;\u0026thinsp;751.5 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7393\u0026thinsp;\u0026plusmn;\u0026thinsp;1458.3 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7227\u0026thinsp;\u0026plusmn;\u0026thinsp;2155.3 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8205\u0026thinsp;\u0026plusmn;\u0026thinsp;910.1 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e8794\u0026thinsp;\u0026plusmn;\u0026thinsp;1243.6 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eTest weight (Kg. hl\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e76.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e75.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e74.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e74.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e74.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e74.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e74.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 ab\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e81.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e81.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e81.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e1000-grains weight (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e37.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e38.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e36.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e46.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e46.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e46.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eGrain yield (Kg. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1927\u0026thinsp;\u0026plusmn;\u0026thinsp;196.3 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2065\u0026thinsp;\u0026plusmn;\u0026thinsp;111.5 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1957\u0026thinsp;\u0026plusmn;\u0026thinsp;216.0 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1972\u0026thinsp;\u0026plusmn;\u0026thinsp;396.2 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2100\u0026thinsp;\u0026plusmn;\u0026thinsp;186.3 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2244\u0026thinsp;\u0026plusmn;\u0026thinsp;190.9 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1791\u0026thinsp;\u0026plusmn;\u0026thinsp;205.7 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1964\u0026thinsp;\u0026plusmn;\u0026thinsp;214.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1791\u0026thinsp;\u0026plusmn;\u0026thinsp;139.1 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1724\u0026thinsp;\u0026plusmn;\u0026thinsp;258.3 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1964\u0026thinsp;\u0026plusmn;\u0026thinsp;213.0 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1709\u0026thinsp;\u0026plusmn;\u0026thinsp;78.1 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3046. \u0026plusmn; 354.7 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3406\u0026thinsp;\u0026plusmn;\u0026thinsp;753.4 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3402\u0026thinsp;\u0026plusmn;\u0026thinsp;1069.4 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3792\u0026thinsp;\u0026plusmn;\u0026thinsp;524.2 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4130\u0026thinsp;\u0026plusmn;\u0026thinsp;586.6 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eHarvest index (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e37.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e38.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e33.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e30.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e44.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003end\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e46.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Different letters in each row indicate significant differences among treatments at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHistorical records from Meteorological Services in Argentina indicated that during 2022 (Buss et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and 2024 (SMN, 2024), the crop season was under the influence of \u0026acute;La Ni\u0026ntilde;a\u0026acute; ENSO stage, resulting in significantly reduced precipitation recorded at the INTA weather station during most of the crop cycle (ESM 1).\u003c/p\u003e\u003cp\u003eIn both 2022 and 2024 crop seasons, water scarcity was especially severe throughout the plant's tillering stage (Zadoks stage 2, mid-September). Consequently, to thoroughly examine the effect of inoculation on drought resilience, wheat plants response under induced drought stress in chamber experiments were studied.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Microalgae and microalgae-PGPB inoculation confer drought tolerance to wheat seedlings\u003c/h2\u003e\u003cp\u003eTo assess if seed inoculation could promote drought stress resilience, suspensions with Az39, LSR1, C1S, Az39\u0026thinsp;+\u0026thinsp;LSR1, Az39\u0026thinsp;+\u0026thinsp;C1S, LSR1\u0026thinsp;+\u0026thinsp;C1S, or Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S were inoculated on dry seeds, which were sown in pots watered at field capacity until seedlings reached the Zadoks stage 2. At this point, seedlings were maintained under moderate drought stress condition (MS) in a growth chamber for 7 d. The relative water content (RWC) of wheat leaves of Az39, LSR1, C1S, Az39\u0026thinsp;+\u0026thinsp;LSR1, and Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S treatments was higher than that of the untreated control (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Shoot aerial dry weight was 55% higher in plants treated with Az39, LSR1, or microalgae C1S individually, when compared to the non-inoculated plants (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Furthermore, LSR1 and C1S single-inoculation treatments differentially modified the root architecture upon drought stress, increasing the total root length, projected area, and branching (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, e, f and g). However, in accordance with field experiments, only microalgae-inoculated seedlings significantly increased root dry weight by a mean of 50% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003eAs expected, the osmoprotectants proline and soluble sugars (SS) accumulated in non-inoculated drought-stressed seedlings (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh), indicating a clear drought stress response. In contrast, all inoculation treatments prevented proline accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh). Conversely, sugars content was diminished in all the treatments containing microalgae and in Az39 single inoculation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur findings revealed that co-inoculation with \u003cem\u003ePseudomonas\u003c/em\u003e strain LSR1 or microalgae \u003cem\u003eScenedesmus obliquus\u003c/em\u003e C1S increases \u003cem\u003eAzospirillum argentinensis\u003c/em\u003e Az39 root colonization by tenfold (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, we show that the single inoculation with \u003cem\u003eAzospirillum\u003c/em\u003e, presumably due to its ability to produce abscisic acid (ABA), delays germination and early root elongation (Cass\u0026aacute;n et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Nonetheless, co-inoculation with LSR1 counteracts this inhibition by Aza39, presumably by an opposite phytohormone effect (Maroniche et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Notably, inoculation with microalgae also stimulates germination and post-germinative growth. This seed priming phenotype exerted by microalgae inoculation could also be explained by its phytohormone profile, mainly enriched in JA and cis-Zeatin (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). It has been reported that seed treatment with elicitors like JA or cytokinin can enhance seed germination rate, particularly under stressful conditions (Iqbal et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). These findings provide a new perspective on the properties of eukaryotic microalgae, specifically regarding their hormonal release on seed surfaces, the priming of seedlings, and the introduction of distinctive traits into microalgal-bacterial synthetic consortia formulations, enhancing bacterial root colonization abilities.\u003c/p\u003e\u003cp\u003eField experiments revealed that microalgal inoculation increased wheat tillering and root dry weight. Moreover, a 36% increase in GY and a 26.2% increase in CWP was observed in response to the inoculation with microalgae-PGPB triple consortia. Interestingly, inoculation efficiency is significantly affected by tillage practices before sowing, since GY and CWP remained unchanged under NT for all treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Under NT, the top soil exhibits more compaction relative to conventional tillage (Lipiec et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Physical alterations in soil resulting from no-till practices might adversely impact the development of primary root axes, especially during the early phases of plant development (Ferreira et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Heightened resistance resulted in an exponential reduction in root length (Martino \u0026amp; Shaykewich, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Since root exudates play a crucial role in shaping the soil microbiome, to maximize the functionality of beneficial bacteria, it is essential to apply them to crops in ways that align with environmental conditions that also favors root development. These findings highlight the necessity of evaluating microbial inocula while also taking soil management into account in order to maximize the growth-promoting effects in productive scenarios.\u003c/p\u003e\u003cp\u003eThe seasons in which we conducted this research on the field represent an interesting case study representing possible future conditions related to climate change. Drought conditions on the vegetative stages of wheat growth (June\u0026ndash;September, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eS) impacted throughout the South American region in 2022\u0026ndash;2023- and -to a lesser extent- in 2024\u0026ndash;2025, both under the influence of the ENSO stage \u0026acute;La Ni\u0026ntilde;a\u0026acute;. Between 2019 and 2024, persistent La Ni\u0026ntilde;a conditions in Argentina correlated with an exceptional drought, exacerbated by several hot waves throughout the entire country (Lopez-Ramirez et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this context, field experiments suggested that wheat plants' resilience to water scarcity under field conditions was enhanced by the Az39\u0026thinsp;+\u0026thinsp;LSR1\u0026thinsp;+\u0026thinsp;C1S synthetic community inoculation. Chamber trials under drought stress exhibit a 55% enhancement in aerial dry weight with the sole inoculum of Az39, LSR1, and microalgae C1S. Additionally, as observed under field trials, seedlings inoculated with microalgae exhibited an average increase of 50% in root dry weight and had a greater effect on total length, projected area and higher root branching than non-inoculated plants.\u003c/p\u003e\u003cp\u003eOsmoprotectants shelter organisms from stress by acting as osmolytes, and the most important osmolytes found in plants include sugar alcohols, soluble sugars, polyols, proline, and betaine (Mohammadi Alagoz et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As proline is a thoroughly studied osmoprotectant, its determination represents a very valuable analytical tool to probe the physiological status of plants regarding drought conditions (Mu et al. 2021). In this context, sugar content in drought-stressed plants was diminished in all the treatments containing microalgae. On the other hand, proline levels appear to more closely reflect physiological stress than sugar levels, as plants treated with Az39, LSR1, and C1S have the lowest proline levels, a high relative water content in leaves, and also significantly greater aerial dry weight, indicating an improved water status of the plants. These results show that inoculated plants exhibit reduced proline accumulation, indicating a diminished stress response, potentially mitigated by an alternative mechanism.\u003c/p\u003e\u003cp\u003eOverall, the strongest response, in terms of growth enhancement and reduction in stress response under induced drought conditions, was observed with the single inoculation of the microalgae. The detection of microalgae on plant tissues only throughout the initial days post-root emergence (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) suggests that the phenotypic adjustments and the mitigation of drought stress resulting from microalgae inoculation, at least in growth chamber studies, can be attributed to early seed priming, supported by the increased concentrations of cytokinin and jasmonic acid in the phytohormone profile of the microalgae, in addition to other potential biostimulant metabolites secreted on the seed surface.\u003c/p\u003e\u003cp\u003eAlternatively, microalgae released on the soil can exert other beneficial effects on the plant, either by hormonal release, and/or by altering the rhizosphere microbiome.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe results presented herein demonstrate a promising prospect for the developing of a novel eukaryotic microalgae-PGPB synthetic consortia inoculant that boosts root colonization by PGPBs and enhances wheat crop water productivity under challenging field conditions, acting as a complementary strategy for climate change adaptation to ensure food security. To the best of our knowledge, this study is the first to demonstrate a direct inoculation of eukaryotic microalgae on wheat seeds with growth-promoting properties for plants under drought stress. It is noteworthy that under both growth chamber and field conditions, these microalgae are fully compatible with rhizosphere bacteria, even amplifying their growth-promoting activities. The fact that drought protection under drought stress could be provided by eukaryotic microalgae seed inoculation raises interesting biotechnological ramifications to explore. Further research into the physiological mechanisms behind this stress tolerance prompted by this treatment will present new insights into the use of eukaryotic microalgae in agronomic scenarios.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe technical assistance of Juan Toledo, Marcio Mu\u0026ntilde;oz, Mar\u0026iacute;a Ver\u0026oacute;nica Martino, Macarena P\u0026eacute;rez-Cenci, and Natalia Almada is gratefully acknowledged. We also thank Marcos Lancia and Victoria Martin for valuable suggestions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo conflicts, informed consent, or human or animal rights are applicable to this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLSR, GM, EdG, LC and LAP are members of CONICET. C.M-F and EdG are members of INTA\u003c/p\u003e\n\u003cp\u003eA.M.G.O. is a CONICET Fellow. C.C. is a retired UNMdP Research Professor. L.A.P. is a Research Professor of UNMdP. This research was funded by CONICET [grant PIBAA 28720210100984CO]; by Universidad Nacional de Mar del Plata (UNMdP) LAP [grant AGR725/24 and grant AGR 685/22] and the Agencia Nacional de Promoci\u0026oacute;n Cient\u0026iacute;fica y Tecnol\u0026oacute;gica, Argentina (ANPCyT), CC [grant PICT2019-2186], and LC grant PICT2018-3382 and grant PICT-2021-CAT-II-00136]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndrade JF, Satorre EH (2015) Single and double crop systems in the Argentine Pampas: Environmental determinants of annual grain yield. Field Crops Res 177:137\u0026ndash;147\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAramburu Merlos F, Monz\u0026oacute;n J, Andrade F, Grassini P (2015) Rendimientos potenciales y brechas de rendimiento. 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Agric Ecosyst Environ 326:107821\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"National University of Mar del Plata","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Microalgae, Wheat, Plant Growth Promoting Rhizobacteria, Drought","lastPublishedDoi":"10.21203/rs.3.rs-7311767/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7311767/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWheat provides the main source of nourishment for more than 40% of the global population, making it an essential crop. The challenge of properly overseeing crop management to guarantee water efficiency has been enhanced by the increase in rainfall unpredictability caused by climate change. Plant-growth-promoting bacteria (PGPBs) are beneficial microorganisms capable of improving crop yield and adaptability to environmental stresses. Single-celled eukaryotic algae, on the other hand, are comparatively under-studied organisms that exihit plant-biostimulant properties. Our research demonstrates that co-inoculation of \u003cem\u003eAzospirillum argentinensis\u003c/em\u003e Az39 with the microalgae \u003cem\u003eScenedesmus obliquus C1S\u003c/em\u003e increases bacterial root colonization and the sole inoculation with microalgae improves germination and post-germinative growth. Field trials conducted during the ENSO phase of 'La Ni\u0026ntilde;a,' characterized by drought conditions, revealed a 36% boost in grain yield and a 26.2% improvement in crop water productivity resulting from inoculation with microalgae-PGPB consortia. Moreover, under induced drought conditions, seedlings inoculated with microalgae showed an increase in root dry weight, averaging 50%. Notably, inoculation efficiency was affected by tillage methods. The findings presented herein reveal a promising potential for the development of a novel eukaryotic microalgae-PGPB synthetic consortia inoculant that enhances root colonization by PGPBs and improves wheat crop water productivity under field conditions\u003c/p\u003e","manuscriptTitle":"Eukaryotic microalgae-bacteria synthetic consortia boost crop productivity and drought tolerance in bread wheat (Triticum aestivum)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 09:36:41","doi":"10.21203/rs.3.rs-7311767/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"653dd212-b4a9-4c0c-b824-191fd9b41902","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55062007,"name":"Agronomy"},{"id":55062008,"name":"General Microbiology"},{"id":55062009,"name":"Applied \u0026 Industrial Microbiology"},{"id":55062010,"name":"Agricultural Engineering"},{"id":55062011,"name":"Agroecology"}],"tags":[],"updatedAt":"2025-09-23T09:36:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 09:36:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7311767","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7311767","identity":"rs-7311767","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}