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Article

Integration of Biostimulants Alongside Various Advanced Nitrogen Fertilization Practices Improve the Yield, Quality, and Sustainability of Malting Barley in Mediterranean Conditions

by
Loukas Orfeas Loukakis
1,
Kyriakos D. Giannoulis
2,*,
Eleftheria Garoufali
1,
Theoni Karaviti
1,
Kyriaki Sotirakoglou
3,
Vasileios Kotoulas
4,
Panagiota Papastylianou
1 and
Garyfalia Economou
1
1
Faculty of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
2
Department of Agriculture Crop Production and Rural Environment, University of Thessaly, Fytokou St., 38446 Volos, Greece
3
Laboratory of Mathematics and Theoretical Mechanics, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
4
Athenian Brewery S.A., 102 Kifissos Avenue, 10210 Athens, Greece
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(10), 2417; https://doi.org/10.3390/agronomy15102417
Submission received: 2 September 2025 / Revised: 1 October 2025 / Accepted: 15 October 2025 / Published: 18 October 2025
(This article belongs to the Section Soil and Plant Nutrition)
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Abstract

Barley (Hordeum vulgare L.) is a key cereal crop for malting and brewing, where grain plumpness and optimal grain protein concentration (GPC) are essential quality traits. This study investigated the combined effects of nitrogen fertilization strategies and a seaweed-based biostimulant (Ascophyllum nodosum extract) on malting barley production across four environments in Thessaly, Greece, over two growing seasons. Treatments included urea (U), urea with biostimulant (U + B), urea with urease inhibitor (UI), urea with urease inhibitor and biostimulant (UI + B), and a control (no fertilization). Applications were tested on genotype G20 at mid-development (Z30–33) and genotype G45 at an earlier stage (Z24–30). UI + B treatment consistently enhanced yield by up to 71%, thousand-grain weight by 27%, and spikelets per square meter by 75% relative to the control, with responses influenced by genotype and environment. Grain fractions > 2.8 mm increased by up to 22% under UI + B, while GPC remained within the optimal malting range (9.5–11.5%). Early-stage applications produced strong benefits overall. Principal component analysis distinguished treatment effects, with UI + B samples clustering consistently apart from controls. These results demonstrate that combining biostimulants with urease inhibitors can simultaneously improve yield, quality, and sustainability in malting barley, supporting reduced nitrogen input in Mediterranean systems.

1. Introduction

Barley (Hordeum vulgare L.) stands as one of the most important cereal crops globally, serving both food and feed sectors and occupying a particularly crucial role in the malting and brewing industries [1,2]. The economic value of barley for malting purposes depends on key quality attributes, notably mean grain size, grain size distribution, and grain protein concentration [3,4]. Among these, grain plumpness holds particular significance, with larger kernels positively correlated with malt extract yield—directly impacting beer production volume and profitability [3,4,5,6]. However, achieving consistently high kernel size remains challenging, particularly under Mediterranean and other stress-prone environments where thin grains are often produced.
Grain protein concentration (GPC) is another decisive quality parameter. Optimal GPC, typically ranging between 9% and 12%, is required to ensure proper enzymatic activity during malting, efficient yeast nutrition, and high extract yield [7,8,9]. Both deficient and excessive protein levels compromise malting quality, emphasizing the necessity of precise agronomic and genetic control. Moreover, grain size is a critical quality criterion, with acceptable standards typically requiring more than 90% of kernels to be retained above a 2.2 mm sieve [10]. Grain plumpness ensures higher malt extract yield and is closely linked to overall brewing performance [3,11].
The yield and quality performance of barley is significantly affected by the interactions among genotype, environment, and treatment [5,12,13]. Phenotypic plasticity, defined as the environmentally responsive generation of various phenotypes from a single genotype [14], is crucial for the adaptation of barley to a range of environmental conditions. Genotypes exhibiting high stability are valuable for securing predictable yields under stress-prone environments, while those with pronounced plasticity may exploit favorable conditions to achieve superior performance [5,15].
Nevertheless, efforts to simultaneously improve grain yield and quality face significant biological constraints. Compensatory relationships between yield components, such as the negative association between grain size and protein concentration, often impede progress [5,16]. Abiotic stresses, including drought, extreme temperatures, and nutrient deficiencies, further exacerbate these challenges, particularly under rainfed and marginal agricultural systems [17,18].
Among agronomic factors, nitrogen (N) management is particularly influential. Nitrogen is crucial for the growth of plants; however, the nitrogen use efficiency (NUE) in cereal crops remains relatively low, with recovery rates of applied nitrogen varying between 26% and 68% [19]. Low NUE not only limits yield potential but also leads to environmental degradation through nitrate leaching, ammonia volatilization, and nitrous oxide (N2O) emissions [20,21]. It is essential to implement management strategies to mitigate N2O emissions in agriculture [21], it being a potent greenhouse gas with a global warming potential 265 times that of carbon dioxide [19].
Effective nitrogen management aims to optimize yield and quality while minimizing environmental impacts. Excessive application of Ν increases GPC beyond acceptable limits for malting, thereby reducing extract yields and product quality [7]. On the other hand, insufficient application may compromise yield and soil health, particularly in intensive cropping systems [19]. Moreover, climatic variability, particularly rainfall patterns following fertilizer application, exerts a strong influence on nitrogen dynamics, uptake efficiency, and final grain attributes [9,22].
The “4R” nutrient stewardship framework—applying the right fertilizer source at the right rate, time, and place—has been advocated to enhance NUE and environmental sustainability [19,23]. However, the practical application remains challenging, particularly due to the growing unpredictability of weather patterns influenced by climate change.
Urea, representing about 80% of the straight nitrogen fertilizer market, remains the most widely applied nitrogen form due to its high nitrogen content and affordability [24,25]. However, urea is prone to rapid hydrolysis into ammonium, resulting in substantial ammonia (NH3) volatilization losses. The application of urease inhibitors (UIs) presents an effective strategy to slow hydrolysis, enhancing nitrogen retention and reducing emissions [24,25,26]. The literature suggests that UIs can decrease NH3 losses by up to 94%, although their impact on grain yield remains modest and context-dependent [25,27,28,29].
Subsequent progress involves breeding techniques and genetic engineering approaches designed to enhance intrinsic NUE characteristics. Selective breeding has focused on traits such as greater root length or surface area, increased above-ground biomass, higher harvest index, and enhanced photosynthetic capacity [30,31,32,33,34,35]. Genetic modification strategies have also been employed to manipulate genes associated with nitrogen uptake, assimilation, and remobilization [36,37,38,39,40]. Nonetheless, the majority of these genetically modified plants have primarily been tested in controlled or hydroponic settings, leaving their efficacy in diverse field conditions unverified [38,41,42].
An additional avenue for improving crop performance under reduced nitrogen inputs involves the application of biostimulants, which in most cases are plant-derived products. Biostimulants are defined as biological substances or microorganisms applied to plants to enhance nutrient efficiency, stress tolerance, and/or crop quality traits [43,44,45]. Seaweed extracts, particularly from Ascophyllum nodosum, have emerged as leading products in the biostimulant market due to their wide range of beneficial effects on plant physiology [46,47,48,49,50].
Seaweed extracts contain complex mixtures of bioactive compounds, including phytohormones (cytokinins, auxins, abscisic acid), polysaccharides, amino acids, vitamins, and phenolic compounds [47,51,52]. These compounds are reported to improve plant vigor, promote root development, enhance photosynthetic activity, delay senescence, and increase tolerance to abiotic stresses such as drought, salinity, and temperature extremes [50,53,54,55]. In cereals such as barley, the application of seaweed extracts has been associated with increases in grain yield and reductions in grain nitrogen content, suggesting a potential dual benefit for both yield and malting quality optimization [7].
Despite the promising results, the adoption of seaweed-based biostimulants in cereal production faces challenges. Variability in product composition, inconsistency in crop responses, and limited large-scale field data hinder broader commercial uptake [48,50]. Standardization of biostimulant formulations and rigorous agronomic validation under diverse field conditions are necessary to fully realize their potential benefits.
Building on the promising outcomes observed with the use of urease inhibitors and biostimulants in enhancing NUE, we hypothesize that further optimization of barley production sustainability can be achieved by integrating biostimulant applications with advanced nitrogen fertilization strategies. This hypothesis is grounded in evidence suggesting that biostimulants, particularly seaweed-based extracts, not only improve plant nutrient uptake and stress resilience but may also modulate grain protein concentration and increase grain yield under reduced nitrogen regimes [7,48,50]. Furthermore, combining biostimulants with enhanced efficiency fertilizers, such as those incorporating urease inhibitors, could synergistically reduce nitrogen losses while maintaining or even improving crop performance [24,25]. Therefore, the aim of this study was to evaluate the combined effects of applying a biostimulant (seaweed extract) and different nitrogen fertilization approaches (i.e., common urea, urea with a urease inhibitor) at different distinct growth stages of malting barley cultivation, under varying climatic conditions, focusing on both quantitative and qualitative characteristics.

2. Materials and Methods

2.1. Site Description

The experiments were carried out for two growing seasons (2022–2023 and 2023–2024) in two areas of Thessaly with different climatic conditions, namely Farsala and Almyros, in commercial fields. Due to the different climatic conditions encountered in the two areas, the area of Farsala will be referred to as Environment 1 (E1) (39°15′44″ N 22°28′34″ E) and Environment 2 (E2) (39°14′57″ N 22°29′34″ E) for the growing seasons 2022- 2023 and 2023–2024, respectively. Similarly, for the Almyros area, Environment 3 (E3) (39°09′22″ N 22°47′02″ E) and Environment 4 (E4) (39°12′22″ N 22°42′49″ E) for the 2022–2023 and 2023–2024 growing seasons, respectively. Sowing took place on 19 November, 20 November, 1 December, and 2 December for E1, E2, E3, and E4, respectively. Seeding rate was 180 kg per hectare, with row spacing of 12 cm. Two malting barley genotypes were evaluated: G20 as early-maturing and G45 (Ackermann Saatzucht GmbH & Co. KG, Irlbach, Germany) as late-maturing. The previous cultivations were malting barley for E1 and E3 and vetch and watermelon for E2 and E4, respectively. Soil properties are presented in Table 1. A total of 40 kg N/ha and 40 kg P2O5/ha were applied in basic fertilization (20-20-0 + 22SO3) in all environments. Finally, harvest took place on 10 June 2023, 2 June 2024, 25 May 2023, and 25 May 2024 for E1, E2, E3, and E4, respectively, at seed moisture of 9% to 11.5%.

2.2. Treatments and Experimental Design

The experiments were arranged in a randomized complete block design (RCB), with three replicates in each treatment. The plot size for each treatment was 40 m2 in E1 and E2 and 39 m in E3 and E4. The treatments applied as surface fertilization were as follows: (i) common sulfur urea (U), (ii) common sulfur urea with addition of biostimulant (U + B), (iii) urea with urease inhibitor (UI), (iv) urea with urease inhibitor with addition of biostimulant (UI + B) and (v) without surface fertilization as a control. For the treatments using common sulfur urea, 90 kg N/ha was applied (40-0-0 +14 SO3). For the treatments with urea with urease inhibitor, 75 kg N/ha was applied (40-0-0 + 5.7 S). The biostimulant that was used came from Ascophyllum nodosum extracts (ANE) from marine algae Goëmar GA142 (0-31-5). The dosage applied was 1 L/ha with a 1:50 dilution.
The N rate for the U treatment was set at 90 kg N ha−1, corresponding to the locally recommended dose for malting barley. For the UI treatment, a reduced rate of 75 kg N ha−1 was applied, since the use of a urease inhibitor is expected to improve nitrogen use efficiency by limiting volatilization losses and prolonging N availability. This design enabled direct comparison of the conventional practice with a potentially more sustainable strategy based on reduced N inputs. The rationale for testing a reduced N rate with urease inhibitors is also supported by previous findings from the Laboratory of Agronomy at the Agricultural University of Athens, which demonstrated that lower N inputs combined with inhibitors can maintain yield and grain quality while improving nitrogen use efficiency (unpublished data, currently under preparation for publication).
The application of the biostimulant was conducted at the end of tillering (Z24) and the application of the surface fertilizer at the beginning of stem elongation (Z30), regarding G45, and these will be considered to be early stages of application. For G20, applications of biostimulant were performed at the beginning of stem elongation (Z30) and surface fertilization at mid-stem elongation (Z32), and these applications are considered to have been applied at mid-stages.

2.3. Measurements

2.3.1. Growth Rate

To determine the Growth Rate, the phenology of the two genotypes was monitored every 10 days from the beginning of tillering to the stage of anthesis and every 5 days from anthesis to harvesting, utilizing the scale of Zadoks et al. [56], following the average phenology in each plot.

2.3.2. Yield and Yield Components

To determine yield and its components, 6 quadrats of 0.25 m2 were manually sampled from each plot following a “Z” pattern. The data regarding aboveground biomass, Yield, and Harvest Index (HI) were derived from these samples, subsequently converted to tn/ha. Spikes/m2 were determined from the samples in each plot. To determine the number of grains per spike, ten spikes were randomly chosen from each sample. The thousand-grain weight (TGW) was determined from three samples per plot, consisting of 100 clean grains, which were counted, and their weight was raised to 1000 grains. For the determination of yields and TGW, the humidity of the grains was deduced to be 11% in all samples.

2.3.3. Grain Size

The Analytica EBC “Sieving test for Barley” method was used for the determination of grain size fraction using a screening machine equipped with three slotted sieves with different diameters (2.8 mm, 2.5 mm and 2.2 mm). Three samples of 100 g of grains per plot were placed on the top sieve (2.8 mm) and shaken for 5 min. Then, the grains that remained in each sieve were weighed in a presession scale (0.01 g). Each sample followed a classification into three grain fractions: >2.8 mm, >2.5 mm (retention fraction), and >2.2 mm (maltable fraction).

2.3.4. Grain Protein Content

Grain Protein Content (GPC) was determined from 3 samples per plot and from measuring the nitrogen content using the Kjeldahl method and multiplying the results with factor 6.25.

2.4. Statistical Analysis

Prior to conducting ANOVA, standardized residuals were examined with the Shapiro–Wilk test to check whether the data followed normal distribution. This was followed by a general ANOVA on the pooled data to determine the effects of Environments, Genotypes, Treatments, and their interactions on the yield and qualitative traits using Tukey’s multiple range test. In addition, Principal Component Analysis (PCA) was performed to explore the multivariate structure of treatment responses across different environments and application stages in malting barley. The analysis included 10 agronomic and quality-related traits: aboveground biomass, grain yield, spikelets per square meter, thousand-grain weight (TGW), harvest index (HI), grains per spike, grain protein content (GPC), maltable fraction, retention fraction, and grain size fraction > 2.8 mm. Two separate Principal Component Analyses (PCA) were conducted, corresponding to the two application stages of treatment: early stages and mid-stages. Each analysis included 80 observations, derived from factorial combinations of treatments, genotypes, and environments. All statistical analyses, data visualization and modeling for PCA were performed using JMP Pro, version 18 (SAS Institute Inc., Cary, NC, USA, 2023). Significant differences between treatment means were compared using the protected least significant difference (LSD) procedure at p < 0.05.

3. Results

3.1. Meteorological Data

Regarding the climatic conditions, significant differences were observed between the regions and growing seasons. In the 2022–2023 growing season, E1 exhibited ideal conditions for malting barley cultivation, while at E3, the conditions were considered unfavorable for the Thessaly region (Figure 1A). E3, the average temperature was higher by 2.13 °C to 5.32 °C throughout the growing season compared to E1 (Figure 1A,C). Maximum temperature (Tmax) did not show significant differences between the two regions, with temperatures ranging from 9.21 °C to 26.78 °C at Environment 1 and from 10.2 °C to 25.5 °C at E3 (Figure 1A,C). In the second growing season, E4 presented more favorable conditions for the cultivation of barley. Regarding average air temperature (Tmean), no differences were found between the two regions, with temperatures ranging from 3.68 °C to 24.3 °C at E2 and from 4.13 °C to 20.1 °C at E4 (Figure 1D). The recorded total precipitation was 291.4 mm, 258.7 mm, 276 mm, and 334.4 mm at E1,E2,E3, and E4, respectively (Figure 1A–D).

3.2. Impact of Treatments on Quantitative Traits

The statistical analysis revealed a significant effect of the environment on aboveground biomass, yield, harvest index (HI), number of spikelets per square meter, and the weight of thousand-grain (TGW), but there was no significant effect on grains per spike (Table 2). Both genotypes and treatments had a significant impact on all quantitative traits (p-value < 0.01). Furthermore, interactions between the factors Environment*Genotype (G*E) significantly influenced all yield components (Table 2). The interactions of the factors Environment × Treatment (E × T) and Genotype × Treatment (G × T) did not affect aboveground biomass, HI, spikelets per square meter, or TGW (Table 2). The interaction of all three factors (E × G × T) played a significant role in aboveground biomass, yield, spikelets per square meter, and grains per spike.
Among the environments, E1 exhibited higher values for aboveground biomass, yield, spikelets per square meter, and TGW in G20 and G45. The lowest values for quantitative traits were observed in E4 for G45 and in E2 for G20 (Table 3). According to Tukey’s HSD (p < 0.05), both genotype and treatment had significant effects on the quantitative traits, with statistically significant differences detected in all cases (Table 3 and Table 4).

3.2.1. Effects of Biostimulant and Fertilization at Early Stages on Quantitative Traits

The biostimulant ANE and surface fertilization treatments were applied at the mid-tillering stage (Z24) and at the beginning of stem elongation (Z30), respectively, on G45. The UI + B treatment was the most effective across all environments. Specifically, in favorable conditions (E1), G45 showed increases compared to the control in aboveground biomass (53.88%), yield (64.94%), spikelets per square meter (47.4%), TGW (22.37%), and grains per spike (15.22%) (Table 3). In E4, which presented the lowest overall values, UI + B led to increases in G45 of 76.82% for aboveground biomass, 78.51% for yield, 50.37% for spikelets per square meter, 16.89% for TGW, and 9.61% for grains per spike.
Across environments, U, U + B, and UI produced largely similar values for most quantitative traits. Exceptions were observed for genotype G45, where TGW was significantly higher under UI compared with U in E1 and E2, and yield was significantly greater under UI than U in E4. Even in cases without statistical significance, a consistent tendency for improved performance under UI was evident, particularly in yield (up to 53.05%) and TGW (16.94%) in E1, and spikelets per square meter (up to 42.54%) in E4 (Table 3).

3.2.2. Effects of Biostimulant and Fertilization at Mid-Stages on Quantitative Traits

The biostimulant (ANE) was applied at the onset of stem elongation (Z30–31), while surface fertilization was performed at mid-stem elongation (Z32–33) in genotype G20. According to Tukey’s HSD, most treatments did not differ significantly, with the control consistently showing the lowest values. Nevertheless, UI + B and U + B demonstrated the greatest effectiveness for G20 across environments (Table 3).
For genotype G20, Tukey’s HSD indicated significant differences only for grains per spike in E1 and TGW in E2, where UI + B achieved the highest values. Nevertheless, U + B consistently improved aboveground biomass and spikelets per square meter across environments. The strongest responses were recorded in E2, with aboveground biomass increasing by 89.82% and spikelets per square meter by 62.28% relative to the control. Even under favorable conditions in E1, substantial increases of 53.23% and 27.77% were observed (Table 3).
In contrast, yield, TGW, and grains per spike were most effectively enhanced by the UI + B treatment for G20. Specifically, in E1, UI + B led to increases of up to 45.06% in yield, 17.26% in TGW, and 12.24% in grains per spike compared to the control. In E2, the same treatment significantly improved yield (92.22%), harvest index (HI) (17.78%), TGW (16.57%), and grains per spike (10.37%) for G20 (Table 3). In E3 and E4, the UI + B treatment remained the most effective for G20. However, in E4, the control treatment exhibited the highest HI value for G20 (Table 3).

3.3. Impact of Treatments on Qualitative Traits

Ensuring the quality characteristics of malting barley cultivation is a primary objective for the brewing industry. Aiming to more precise investigation of the optimal fertilization scheme on the key qualitative traits (GPC and maltable fraction). Aiming to more precisely investigate the optimal fertilization scheme on the key qualitative traits (GPC and maltable fraction), there were two additional criteria evaluated beyond the desired criterion for malting (>2.2 mm) in terms of the grain size. Specifically, retention fraction (>2.5 mm) and grain sizes greater than 2.8 mm were considered. Statistical analysis revealed that all three factors (environment, genotype, and treatment) had a significant effect on all quality traits examined (p-value < 0.0001) (Table 4). Significant two-factor interactions (E × G, E × T, and G × T) were observed. Furthermore, three-factor interactions, as well as interactions involving all factors, also showed significant effects on all quality traits (p-value < 0.0001) (Table 4).
A three-way ANOVA across environments was conducted to evaluate the effects of genotype and treatment on qualitative traits. Both factors significantly influenced GPC and grain size (p < 0.0001), except for the effect of genotype on maltable fraction in E3 (p < 0.01). A significant G × T interaction was also detected for all qualitative traits, with the exception of maltable fraction in E3 (Table 5). Maltable fraction, retention fraction, and grains > 2.8 mm were generally higher in E1 and E3, while the lowest values were observed in E4 (Table 5). For GPC, E1 recorded the highest values, although still within the acceptable malting range. In contrast, environments E2, E3, and E4 did not show consistent trends. Notably, the UI + B treatment maintained GPC close to the desired levels across environments (Table 5).

3.3.1. Effects of Biostimulant and Fertilization at Early Stages on Qualitative Traits

The UI + B treatment helped the early-maturing genotype G45 to achieve relative stability in quality characteristics when the biostimulant ANE and surface fertilization were applied at the mid-tillering stage (Z24) and at the beginning of stem elongation (Z30), respectively. Specifically, under favorable conditions (E1), this treatment significantly increased the maltable fraction by 2.75%, the retention fraction by 6.13%, and the grain size fraction > 2.8 mm by 22.24% compared to the control (Table 5). The lowest values in the sieving test were observed in E4. However, UI + B still demonstrated the highest percentage increase in maltable fraction, retention fraction, and grain size > 2.8 mm in G45, with increases of 11.89%, 27.25%, and 0.24%, respectively (Table 5). In Environments 2 and 3, UI + B exhibited the highest values for all three traits, reaching the desired thresholds for the malting industry. Only in the retention fraction did G45 fail to meet the desired limits in E2. Additionally, in the same environment, grain size > 2.8 mm was significantly lower compared to E3. Under the UI + B treatment, grain protein content (GPC) met the desirable limits in all environments for G45, with the exception of E2, where GPC values approached the lower boundary of the acceptable range (Table 5). Among the other treatments, UI also enhanced grain quality, with percentage increases in maltable fraction, retention fraction, and grain size > 2.8 mm reaching 7.2%, 26.39%, and 0.22%, respectively, in G45 under E4 conditions. In E1, E2, and E3, this treatment also achieved the desired limits for grain size, except for the retention fraction in E2. Furthermore, GPC remained within acceptable levels in E2 for G45 (Table 5).

3.3.2. Effects of Biostimulant and Fertilization at Mid-Stages on Qualitative Traits

The UI + B and U + B treatments had a more pronounced effect on the qualitative traits of the very early genotype G20, as the biostimulant ANE was applied at the beginning of stem elongation (Z30–31) and surface fertilization at mid-stem elongation (Z32–33). A differential response was observed between treatments, with G20 responding more favorably to UI + B. Whether grains were maltable did not differ significantly among U, U + B, UI, and UI + B treatments, with all values remaining within the acceptable industry range across environments. Under favorable conditions (E1), the UI + B treatment led to a 19.31% increase in grain size > 2.8 mm and a 6.06% increase in retention fraction compared to the control (Table 5). The highest values for both traits were observed in E3. Although the lowest values for all grain size categories were recorded in E4, UI + B treatment still increased these values in G20 by 9.61% for maltable grain, 9.43% for retention fraction, and 9.28% for grain size > 2.8 mm relative to the control. Regarding grain protein content (GPC), G20 showed relative stability across all treatments (U, U + B, UI, UI + B), but only the UI + B treatment consistently met the acceptable GPC limits across all environments (Table 5).
Among the other treatments, U + B and UI had similar effects on grain quality traits in G20. According to Tukey’s HSD, differences were observed for grain size greater than 2.8 mm in E2 and E4, and for GPC in E2 and E3 (Table 5).

3.4. Principal Component Analysis

Principal Component Analysis (PCA) was conducted to assess the multivariate response of treatment effects on quantitative and qualitative traits when applied at early and mid-stages. The analysis was based on 10 quantitative traits, including aboveground biomass, grain yield, spikelets per square meter, thousand-grain weight (TGW), harvest index (HI), grains per spike, grain protein content (GPC), maltable fraction, retention fraction, and grain size fractions > 2.8 mm. A total of 80 observations were included in each analysis.
At the first application stage (Z30–31), the first two principal components explained 73.3% of the total variance (PC1: 55.5%, PC2: 17.8%) (Figure 2A). In the second stage (Z32–33), the total variance explained was 64.1% (PC1: 45.8%, PC2: 18.3%) (Figure 2B). In both PCAs, the control treatment (C) was clearly separated along PC1 from the other treatments, suggesting a consistently distinct performance pattern across multiple traits. Treatments including surface fertilization and/or biostimulants (U, UI, U + B, UI + B) clustered on the positive side of PC1, indicating a shared and favorable effect on early plant development.
At early stages, treatments formed a more compact cluster, indicating a uniform multivariate response to early application. In contrast, the PCA at mid-stages showed greater dispersion among treatments, particularly along PC2, suggesting the emergence of additional variation, possibly due to environment-dependent responses or genotype-by-treatment interactions (Figure 2B).
Overall, the PCA results suggest that biostimulant and fertilization treatments, particularly UI + B, consistently enhanced early plant performance regardless of application timing. However, application at earlier stages appeared to produce a more cohesive and pronounced multivariate response, underscoring the importance of timing in optimizing early crop vigor.

4. Discussion

The results of the present study provide a detailed investigation of the impact of climatic conditions, treatment stage (represented by the different genotypes), and fertilization treatments on both the yield and quality traits of malting barley. Five treatments were applied: simple urea (U), U with biostimulant Ascophyllum nodosum extract (ANE) (U + B), urea with urease inhibitor (UI), UI combined with biostimulant ANE (UI + B), and control, without surface fertilization or ANE, across four environments, using two genotypes (G20 and G45). The findings underscore the complex interplay between environmental factors, genotypic characteristics, and agronomic practices in determining barley productivity and quality.
Grain yield was evaluated alongside key yield components (aboveground biomass, harvest index, spikelets*m−2, grains per spike) [57], while for malting barley, additional quality criteria such as grain protein content (GPC) and grain size had to be satisfied to meet industry standards. The findings of this study highlight the importance of selecting both an appropriate genotype and a suitable fertilization strategy to approach the specific needs and the high-quality targets of the malting industry. Specifically, grain protein content (GPC) is a critical quality trait in malting barley, with an optimal range between 9.5% and 11.5%, while the retention fraction, defined as the proportion of grains larger than 2.5 mm should exceed 90% to ensure acceptable malt quality [9]. In E1, favorable climatic conditions benefited both genotypes, with G45 achieving the highest yield and quality. This performance could be attributed to the combination of moderate rainfall (291.4 mm), mild mean temperature (11.17 °C), and cooler conditions during grain filling, consistent with previous reports [58,59]. For G20, which was at an earlier developmental stage during fertilization, the timely availability of nitrogen was crucial, as the crop showed high demand for rapid uptake. In contrast, E4 produced the lowest values, especially for G45. Although rainfall was adequate (334.4 mm), heavy precipitation in early May (33.9 mm) caused lodging, while excess water during vegetative stages promoted excessive plant height and increased its susceptibility to lodging. G20 was similarly affected, with both yield and grain size reduced by lodging just before harvest. E2 presented an intermediate scenario. Lower rainfall during vegetative growth resulted in shorter, more lodging-resistant plants. However, in both G45 and G20, drought stress during grain filling limited carbohydrate accumulation, leading to smaller grain size despite stable nitrogen content [19]. These outcomes confirm that temperature extremes and rainfall strongly influence the yield components and quality traits in barley [60,61,62,63,64,65].
Urease inhibitor (UI) improved nitrogen use efficiency (NUE) by reducing ammonia volatilization, a major loss pathway in alkaline soils across all experimental sites [26,66,67]. Applied at early stages, during tillering and stem elongation, it increased nitrogen availability at peak demand, enhancing biomass, yield, and traits such as aboveground biomass and thousand-grain weight (TGW), as confirmed by PCA. Similar benefits of NBPT, the most widely used urease inhibitor, have been reported in barley [66], wheat [26], and temperate grasslands [18,67,68], where it significantly reduced NH3 emissions and improved crop yield and nitrogen uptake [67,69,70,71]. These findings confirm that early application of UI proved most effective at ensuring adequate nitrogen supply during the critical period of vegetative stages, supporting tiller survival, spikelet formation, and potential grain set [72,73,74].
At mid-stages, however, by the time plants approached heading, nitrogen uptake rates between the UI and simple urea treatments tended to converge, a pattern also reported in other cereal studies [25,26,65]. The PCA results confirmed this shift, showing greater dispersion among treatments and indicating that genotype and environmental variability were more influential than fertilizer form at this stage. In barley, the “critical period” for nitrogen concentration occurs immediately before heading, when major yield components are already established [75]. This explains why late UI applications had little impact on yield traits, as nitrogen uptake was likely already saturated. Genotypic differences also played a role: fast-developing genotypes such as G20 appeared less responsive to delay nitrogen release, while slower-developing varieties may have taken greater advantage of prolonged nitrogen availability. Similar patterns have been reported in wheat, where fertilization timing significantly affected biomass, yield, and NUE traits [76,77]. Fertilizer type further influenced these dynamics: urea provides rapid nitrogen release, whereas urease inhibitors ensure a slower, more gradual supply [78,79]. At advanced stages of stem elongation, however, this delayed availability is less effective, as assimilates are preferentially allocated to tiller survival rather than spike development, creating trade-offs between spikelets per square meter and grains per spike [80].
Overall, the evidence indicates that UI is most effective when applied at early stages of crop development where it enhances NUE, aboveground biomass, and yield potential by reducing nitrogen losses and aligning nutrient availability with plant demand. In later stages, its effects are less pronounced and more dependent on genotype and environment, highlighting the timing of application in maximizing the advantages of urease inhibition.
The biostimulant (ANE) exhibited broad and consistent benefits across both developmental stages, in contrast to the stage-dependent effects observed with the urease inhibitor, whose effects were more stage-dependent. At early stages, particularly at tillering and stem elongation, ANE enhanced root development, promoted tiller formation, and increased thousand-grain weight (TGW). These improvements in nutrient uptake efficiency contributed to greater yield potential, particularly under stressful conditions. The PCA confirmed these findings, as ANE-treated plots clustered closely together, reflecting their uniform positive impact on early vigor traits. The physiological basis of these responses is linked to hormonal regulation: cytokinins stimulate cell division and modify apical dominance, while auxins enhance cell elongation and stem growth [55,81,82,83,84,85]. Consistent with these findings, previous studies have identified tillering and stem elongation as the most effective stages for seaweed extract application, where ANE promotes crop growth and, at the same time, enables reductions in nitrogen input in comparison to the use of conventional high-N fertilization regimes [82].
The positive effects observed in this study can be mechanistically explained by the diverse bioactive compounds present in ANE. These extracts contain polysaccharides (e.g., alginates, laminarins, fucoidans), polyphenols, betaines, and phytohormone-like molecules (auxins, cytokinins, abscisic acid analogs) [83]. Polysaccharides function as elicitors of defense pathways, improving osmotic balance and antioxidant capacity under abiotic stress, thereby contributing to greater tolerance to lodging and heat [86]. Polyphenols and betaines mitigate oxidative damage and stabilize membranes, supporting resilience during grain filling [87]. The hormone-like molecules present in ANE are consistent with the hormonal mechanisms already described above, providing additional support for the observed improvements in tillering, grain filling, TGW, and stress tolerance. Collectively, these signaling and protective compounds offer a biochemical basis for the consistent phenotypic benefits of ANE across environments and developmental stages.
At mid-stages, ANE continued to exert positive effects, particularly by enhancing tolerance to heat and lodging stress. In the present study, the application of ANE (UI + B and U + B) at stem elongation (Z30–Z32) significantly improved both yield and quality traits, with especially pronounced responses in G20. This genotype–treatment interaction suggests that biostimulant efficiency is linked to phenological stage and emphasizes the importance of tailoring application strategies to genotype-specific dynamics [88,89]. Comparable evidence from barley and wheat indicates that mid-stage seaweed extract applications maintain yield stability under suboptimal conditions [81,82,83,84], largely through the uptake and translocation of bioactive compounds that regulate hormonal signaling in target tissues. These molecules activate antioxidant defenses, secondary metabolism, osmotic adjustment, and morphological adaptations that strengthen plant responses to abiotic stress [63,90,91].
In terms of quality, ANE generally promoted grain plumpness across treatments, with the UI + B combination showing the most pronounced increases in TGW and retention fraction. Grain protein content (GPC) generally remained within malting standards across treatments, highlighting the importance of managing both yield and quality simultaneously for the brewing industry [3,92]. These results align with reports that ANE enhances starch accumulation, malt extract potential, and nutrient uptake efficiency in cereals such as barley, wheat, and maize [82,83,93]. Although previous studies noted an inverse relationship between GPC and grain size due to differential sensitivity to post-anthesis stress [16,19,94], the present findings suggest that genotype and environmental conditions exerted a stronger influence [95,96,97].
Taken together, these results demonstrate that ANE enhances barley productivity through a dual role: stimulating early vigor and yield components, while preserving grain size and quality at later stages under variable conditions. This highlights its potential as a strategic input in malting barley systems, complementing both conventional fertilization and urease inhibitors. However, important knowledge gaps remain regarding the specific mechanisms by which ANEs influence nitrogen uptake and assimilation under reduced-N conditions [98,99]. In addition, practical challenges persist for the integration of biostimulants into current farming systems, particularly with respect to application method, timing, and dosage [98,100,101].
The combined treatment (UI + B) produced the most consistent and synergistic improvements across environments and genotypes. At early stages, during tillering and stem elongation, UI + B significantly increased biomass, yield, and grain plumpness, even when applied at a reduced nitrogen rate (15 kg N/ha). The PCA further confirmed its strong and uniform influence, as UI + B treatments were clearly separated from both the control and other fertilization strategies. The observed synergy may be attributed to complementary mechanisms: UI prolongs nitrogen availability, while ANE enhances root activity and nutrient uptake, optimizing NUE. Together, these processes optimize nitrogen use efficiency (NUE) and early vigor, thereby supporting high yield potential with lower fertilizer input [102,103].
At mid-stages, UI + B continued to deliver advantages by stabilizing grain protein content (GPC) within the optimal malting range and improving grain retention fraction, even under unfavorable conditions, such as the lodging observed in E4. For G20, UI + B enhanced TGW and retention fraction during stem elongation, often outperforming U + B. While both biostimulant-based treatments improved mid-stage growth, the inclusion of UI ensured greater consistency across environments. Notably, UI + B was the only treatment that overcame this typical trade-off, maintaining both grain size and GPC within desirable malting standards [3,92]. This dual benefit highlights its unique ability to safeguard yield and malting quality simultaneously.
Genotypic responses further underscored the effectiveness of UI + B. Under these treatments, G45 showed the greatest benefits in favorable environments, while G20 exhibited greater stability under stress. Genotype responses further highlighted the effectiveness of UI + B. These patterns suggest that the combination of UI and biostimulant can mitigate genotype sensitivity to environmental variability, ensuring reliable performance across contrasting growing conditions.
PCA corroborated these findings, with UI + B consistently separated from the control and other treatments at early stages. At mid-stages, treatment variability increased, but UI + B consistently retained the most favorable position in ordination space. The clear separation of the control treatment along PC1 highlighted the essential role of fertilization and biostimulant inputs in achieving both yield and malting quality. Overall, these results indicate that early applications provide the most uniform improvements, while mid-stage applications, though more variable, remain critical for stabilizing grain quality.

5. Conclusions

This study highlights the critical influence of environmental conditions, genotype characteristics, and nitrogen management strategies on the productivity and quality of malting barley. The combination of urease inhibitor-treated urea and a seaweed-based biostimulant (UI + B) consistently improved grain yield and grain size, while maintaining grain protein concentration (GPC) within industry-acceptable limits across diverse environments. At early application stages (Z24–Z30), the UI + B treatment was particularly effective for G45, significantly enhancing both yield and qualitative traits even under challenging climatic conditions. Conversely, mid-stage applications (Z30–33) demonstrated a genotype-dependent effect, with UI + B benefiting G20. Principal Component Analysis (PCA) underscored the importance of treatment timing and genotype adaptability in differentiating multivariate performance patterns. The PCA effectively revealed distinct separation between the control and treated samples, with UI + B-treated plots consistently clustering based on favorable agronomic and quality traits. While biostimulant application consistently improved grain plumpness, treatment efficacy varied depending on the phenological stage and environmental stress conditions. Overall, the integration of biostimulants with enhanced-efficiency fertilizers offers a promising agronomic strategy for improving barley yield and malting quality, while also supporting more sustainable nitrogen management. Future research should aim to refine biostimulant application protocols, deepen understanding of genotype-specific responses, and validate these findings under a broader range of environmental conditions to further optimize malting barley production systems.

Author Contributions

Conceptualization, L.O.L.; methodology, K.D.G. and P.P.; validation, L.O.L. and K.D.G.; formal analysis, L.O.L. and K.S.; investigation, L.O.L.; data curation, L.O.L. and E.G.; writing—original draft preparation, L.O.L.; writing—review and editing, L.O.L. and K.D.G.; visualization, T.K.; supervision, G.E. and P.P.; project administration, G.E.; funding acquisition, V.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Athenian Brewery S.A. and CLIMPACT (support for enhancing the operation of the National Network for Climate Change), financed by the National Development Program, General Secretariat of Research and Innovation, Greece (2023NA11900001). The APC was funded by Athenian Brewery S.A. and CLIMPACT.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to the fact that this specific data will be used in L.O.L.’s PhD thesis, the author would prefer privacy.

Conflicts of Interest

Author V.K. was employed by the company Athenian Brewery S.A. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that this study received funding from Athenian Brewery S.A. and CLIMPACT. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

Abbreviations

The following abbreviations are used in this manuscript:
GPCGrain Protein Content
UIUrease Inhibitor
UI + BUrea with Urease Inhibitor and Biostimulan
UUrea
U + BUrea with Biostimulant
ANEAscophyllum nodosum Extract
TGWThousand-Grain Weight
RCBRandomized Complete Block design
PCAPrincipal Component Analysis
LSDLeast Significant Difference
E1, E2, E3, E4Experimental Environments (different locations/seasons in Thessaly)

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Agronomy 15 02417 g001
Figure 1. Diagrams with the meteorological data by environment with (A–D), Environment 1, Environment 2, Environment 3 and Environment 4, respectively. Temperature (°C), maximum, minimum, and average, and precipitation (mm) of the genotypes per decade during the biological cycle are shown. Arrows denote key phenological stages: T = Tillering; S = Stem elongation; A = Anthesis; G = Grain filling.
Figure 1. Diagrams with the meteorological data by environment with (A–D), Environment 1, Environment 2, Environment 3 and Environment 4, respectively. Temperature (°C), maximum, minimum, and average, and precipitation (mm) of the genotypes per decade during the biological cycle are shown. Arrows denote key phenological stages: T = Tillering; S = Stem elongation; A = Anthesis; G = Grain filling.
Agronomy 15 02417 g001
Agronomy 15 02417 g002aAgronomy 15 02417 g002b
Figure 2. Principal component analysis (PCA) conducted for all traits, quantitative and qualitative, based on (A) early and (B) mid-stages of biostimulant and surface fertilization application. Total number of samples was 80 in 4 environments for the genotype G45. Red dots correspond to a treatment and the black dots the 10 variables were yield, aboveground biomass, harvest index (HI), thousand-grain weight (TGW), spikelets m−2 (Spikelets), grains spike−1 (Grains Spike), grain protein content (GPC), maltable fraction, retention fraction (Retention), and grain size greater than 2.8 mm. U = Urea, U + B = Urea and biostimulant Ascophyllum nodosom extract, UI = Urea with inhibitor urease, UI + B = Urea with inhibitor urease and biostimulant Ascophyllum nodosom extract and C = Control without surface fertilization.
Figure 2. Principal component analysis (PCA) conducted for all traits, quantitative and qualitative, based on (A) early and (B) mid-stages of biostimulant and surface fertilization application. Total number of samples was 80 in 4 environments for the genotype G45. Red dots correspond to a treatment and the black dots the 10 variables were yield, aboveground biomass, harvest index (HI), thousand-grain weight (TGW), spikelets m−2 (Spikelets), grains spike−1 (Grains Spike), grain protein content (GPC), maltable fraction, retention fraction (Retention), and grain size greater than 2.8 mm. U = Urea, U + B = Urea and biostimulant Ascophyllum nodosom extract, UI = Urea with inhibitor urease, UI + B = Urea with inhibitor urease and biostimulant Ascophyllum nodosom extract and C = Control without surface fertilization.
Agronomy 15 02417 g002aAgronomy 15 02417 g002b
Table 1. Soil physicochemical properties at the four experimental environments (E1–E4). E1 = 2022, Farsala; E2 = 2023, Farsala; E3 = 2022, Almyros; E4 = 2023, Almyros. Values represent measurements of organic matter content, pH, total nitrogen, available phosphorus, and exchangeable potassium.
Table 1. Soil physicochemical properties at the four experimental environments (E1–E4). E1 = 2022, Farsala; E2 = 2023, Farsala; E3 = 2022, Almyros; E4 = 2023, Almyros. Values represent measurements of organic matter content, pH, total nitrogen, available phosphorus, and exchangeable potassium.
Soil Properties
Soil
Texture		Organic
Matter (%)		pHTotal
Nitrogen (%)		Phosphorus (ppm)Potassium (ppm)
E1Clay2.027.050.14720.12266
E2Clay2.347.100.16123.66224
E3Clay loam1.957.200.13319.57172
E4Clay loam1.867.220.12916.53281
Table 2. Interaction of environment (E), genotype (G), and treatment (T) on quantitative traits (aboveground biomass, yield, harvest index (HI), spikelets per square meter and grains spike−1). Data were analyzed using three-way ANOVA (E × G × T). Significant differences were determined with Tukey’s HSD test at p < 0.05.
Table 2. Interaction of environment (E), genotype (G), and treatment (T) on quantitative traits (aboveground biomass, yield, harvest index (HI), spikelets per square meter and grains spike−1). Data were analyzed using three-way ANOVA (E × G × T). Significant differences were determined with Tukey’s HSD test at p < 0.05.
Quantitative Traits
Aboveground BiomassYieldHISpikelets m−2TGWGrains Spike−1
Environment (E)***************ns
Genotype (G)******************
Treatment (T)***************
E × G*****************
E × T*********nsns***
G × Tns**ns*******
E ×G × T*****ns******
*** p < 0.001, ** p < 0.01, * p < 0.05, and ns: no significant.
Table 3. (a) Effects of nitrogen treatments with or without biostimulant on aboveground biomass and yield of two barley genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for interactions E × G, E × T, and G × T are reported below the table for each trait. (b) Effects of nitrogen treatments with or without biostimulant on the harvest index (HI) and spikelets m−2 of two barley genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for interactions: E × G, E × T, and G × T are reported below the table for each trait. (c) Effects of nitrogen treatments with or without biostimulant on thousand-grain weight (TGW) and grains spike−1 of two barley genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for interactions E × G, E × T, and G × T are reported below the table for each trait.
Table 3. (a) Effects of nitrogen treatments with or without biostimulant on aboveground biomass and yield of two barley genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for interactions E × G, E × T, and G × T are reported below the table for each trait. (b) Effects of nitrogen treatments with or without biostimulant on the harvest index (HI) and spikelets m−2 of two barley genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for interactions: E × G, E × T, and G × T are reported below the table for each trait. (c) Effects of nitrogen treatments with or without biostimulant on thousand-grain weight (TGW) and grains spike−1 of two barley genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for interactions E × G, E × T, and G × T are reported below the table for each trait.
a
Aboveground Biomass (tnha−1)Yield (tnha−1)
E1E2E3E4E1E2E3E4
G45U12.856.4611.256.76.683.196.133.28
U + B158.2411.986.743.56.993.49
UI12.258.4511.38.627.183.687.073.52
UI + B13.859.4512.059.467.624.027.364.32
Control95.519.655.354.622.514.912.42
Μean12.597.6211.237.636.573.386.493.41
G20U137.2512.412.165.263.445.434.63
U + B14.2510.6312.6514.175.434.245.734.65
UI13.18.4612.1510.085.333.355.683.65
UI + B14.29.2412.3513.545.734.945.884.69
Control9.35.610.459.033.952.573.863.49
Mean12.778.2412.0011.805.143.715.324.22
Tukey E × G(0.05)0.640.26
Tukey E × T(0.05)1.200.49
Tukey G × T(0.05)0.750.31
b
HISpikeletsm−2
E1E2E3E4E1E2E3E4
G45U0.520.430.550.49745423657448
U + B0.450.430.580.44822476736546
UI0.580.470.630.40834478691583
UI + B0.550.510.620.46880535768615
Control0.510.440.510.49597371543409
Μean0.520.460.580.46776457679520
G20U0.410.470.440.38582368531552
U + B0.380.390.450.32623456567584
UI0.410.390.440.36576410522480
UI + B0.400.530.490.30612486546551
Control0.420.450.370.39479281500467
Mean0.400.450.440.35574400533527
Tukey E × G(0.05)0.0335.05
Tukey E × T(0.05)0.0565.11
Tukey G × T(0.05)0.0340.95
c
TGWGrains Spike−1
E1E2E3E4E1E2E3E4
G45U38.8035.6138.5935.429.527.827.528.3
U + B42.4839.4539.9735.728272828.8
UI44.1740.5240.2236.9229.327.728.328.8
UI + B46.2242.4041.6438.2628283128.5
Control37.7734.6535.6432.7324.326.22526
Μean41.8938.5339.2135.8027.827.328.028.1
G20U44.2143.9240.9940.7530.228.230.328
U + B44.6644.4043.1142.8527.530.531.230
UI44.7144.4941.2040.9527.829.82929.2
UI + B47.1346.9243.8643.6731.53131.332
Control40.4940.2537.5237.324.52722.827.3
Mean44.2444.0041.3441.1028.329.328.929.3
Tukey E × G(0.05)0.930.74
Tukey E × T(0.05)1.721.38
Tukey G × T(0.05)1.080.87
(a) Values are means of four replicates. Tukey HSD at p < 0.05 for Environment × Genotype (E × G), Environment × Treatment (E × T), and Genotype × Treatment (G × T) interactions are reported below each trait. Means exceeding these thresholds differ significantly. (b) Values are means of four replicates. Tukey HSD at p < 0.05 for Environment × Genotype (E × G), Environment × Treatment (E × T), and Genotype × Treatment (G × T) interactions are reported below each trait. Means exceeding these thresholds differ significantly. (c) Values are means of four replicates. Tukey HSD at p < 0.05 for Environment × Genotype (E × G), Environment × Treatment (E × T), and Genotype × Treatment (G × T) interactions are reported below each trait. Means exceeding these thresholds differ significantly.
Table 4. Interaction of environment (E), genotype (G), and treatment (T) on qualitative traits (grain protein content (GPC) and sieving test parameters). Data were analyzed using three-way ANOVA (E × G × T). Significant differences were determined with Tukey’s HSD test at p < 0.05.
Table 4. Interaction of environment (E), genotype (G), and treatment (T) on qualitative traits (grain protein content (GPC) and sieving test parameters). Data were analyzed using three-way ANOVA (E × G × T). Significant differences were determined with Tukey’s HSD test at p < 0.05.
Qualitative Traits
GPCMaltable (>2.2 mm)Retention (>2.5 mm)>2.8 mm
Environment (E)************
Genotype (G)************
Treatment (T)************
E × G************
E × T************
G × T************
E × G × T************
*** p < 0.001.
Table 5. (a) Effects of nitrogen treatments with or without biostimulant on grain protein concentration (GPC) and maltable fraction (>2.2 mm) for two genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for E × G, E × T, and G × T interactions are reported below the table for each trait. (b) Effects of nitrogen treatments with or without biostimulant on retention fraction (>2.5 mm) and grain size > 2.8 mm for two genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for E × G, E × T, and G × T interactions are reported below the table for each trait.
Table 5. (a) Effects of nitrogen treatments with or without biostimulant on grain protein concentration (GPC) and maltable fraction (>2.2 mm) for two genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for E × G, E × T, and G × T interactions are reported below the table for each trait. (b) Effects of nitrogen treatments with or without biostimulant on retention fraction (>2.5 mm) and grain size > 2.8 mm for two genotypes (G45 and G20) across four environments (E1–E4). Values are means of four replicates. Tukey’s HSD at p < 0.05 for E × G, E × T, and G × T interactions are reported below the table for each trait.
a
GPC (%)Maltable (>2.2 mm) (%)
E1E2E3E4E1E2E3E4
G45U7.969.789.4611.0698.3192.0598.8975.45
U + B8.6110.3411.229.0998.9392.2898.9976.53
UI9.7711.089.2811.9998.9792.3598.9881.88
UI + B10.3310.4710.7110.2599.0693.5899.0686.57
Control6.957.447.667.9596.3188.8598.4374.68
Μean8.729.829.6710.0798.3291.8298.8778.98
G20U9.9511.7113.5510.6998.5995.3798.6994.41
U + B9.8811.9510.7011.8598.9996.7298.795.79
UI9.8012.789.8912.7399.0397.2198.8296.02
UI + B10.9511.3911.3110.9399.0997.6198.8995.62
Control8.189.089.409.1496.4894.8698.1286.01
Mean9.7511.3810.9711.0798.4496.3598.6493.57
Tukey E × G(0.05)0.210.93
Tukey E × T(0.05)0.401.73
Tukey G × T(0.05)0.251.09
b
Retention (>2.5 mm) (%)>2.8 mm (%)
E1E2E3E4E1E2E3E4
G45U87.6149.8288.6222.4656.826.4654.631.91
U + B89.4553.2989.3129.2960.068.6657.373.80
UI89.7967.1790.5537.9961.3911.2859.150.93
UI + B90.6770.0398.7438.9164.4212.6162.110.95
Control84.5440.6284.0411.6642.185.5741.710.71
Μean88.4156.1790.2528.0656.978.9254.991.66
G20U86.8384.3392.4874.4560.7428.7367.124.40
U + B89.5186.4392.9577.1565.0731.8469.0926.11
UI89.7989.6593.2477.7866.1150.7470.417.35
UI + B90.4790.5993.7179.8767.4056.5672.4527.44
Control84.4166.3388.2168.3548.097.4952.6615.12
Mean88.2083.4792.1275.461.4835.0766.3422.08
Tukey E × G(0.05)1.170.98
Tukey E × T(0.05)2.181.82
Tukey G × T(0.05)1.371.15
(a) Values are means of four replicates. Tukey HSD at p < 0.05 for Environment × Genotype (E × G), Environment × Treatment (E × T), and Genotype × Treatment (G × T) interactions are reported below each trait. Means exceeding these thresholds differ significantly. (b) Values are means of four replicates. Tukey HSD at p < 0.05 for Environment*Genotype (E × G), Environment × Treatment (E × T), and Genotype × Treatment (G × T) interactions are reported below each trait. Means exceeding these thresholds differ significantly.
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Loukakis, L.O.; Giannoulis, K.D.; Garoufali, E.; Karaviti, T.; Sotirakoglou, K.; Kotoulas, V.; Papastylianou, P.; Economou, G. Integration of Biostimulants Alongside Various Advanced Nitrogen Fertilization Practices Improve the Yield, Quality, and Sustainability of Malting Barley in Mediterranean Conditions. Agronomy 2025, 15, 2417. https://doi.org/10.3390/agronomy15102417

AMA Style

Loukakis LO, Giannoulis KD, Garoufali E, Karaviti T, Sotirakoglou K, Kotoulas V, Papastylianou P, Economou G. Integration of Biostimulants Alongside Various Advanced Nitrogen Fertilization Practices Improve the Yield, Quality, and Sustainability of Malting Barley in Mediterranean Conditions. Agronomy. 2025; 15(10):2417. https://doi.org/10.3390/agronomy15102417

Chicago/Turabian Style

Loukakis, Loukas Orfeas, Kyriakos D. Giannoulis, Eleftheria Garoufali, Theoni Karaviti, Kyriaki Sotirakoglou, Vasileios Kotoulas, Panagiota Papastylianou, and Garyfalia Economou. 2025. "Integration of Biostimulants Alongside Various Advanced Nitrogen Fertilization Practices Improve the Yield, Quality, and Sustainability of Malting Barley in Mediterranean Conditions" Agronomy 15, no. 10: 2417. https://doi.org/10.3390/agronomy15102417

APA Style

Loukakis, L. O., Giannoulis, K. D., Garoufali, E., Karaviti, T., Sotirakoglou, K., Kotoulas, V., Papastylianou, P., & Economou, G. (2025). Integration of Biostimulants Alongside Various Advanced Nitrogen Fertilization Practices Improve the Yield, Quality, and Sustainability of Malting Barley in Mediterranean Conditions. Agronomy, 15(10), 2417. https://doi.org/10.3390/agronomy15102417

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