Original Research
Frontiers in Soil Science ·
Volume 6 - 2026 | https://doi.org/10.3389/fsoil.2026.1895897
Effects of biofertilizers under varying irrigation regimes on soybean productivity and soil fertility in arid agroecosystems
- Ulugbek Nematov1
- Subhana Shahmaliyeva2
- Bakhtiyar Matyakubov3
- Khayrullo Tursunov1
- Dilorom Yormatova4
- Anvarjon Karabayev1
- Zokir Tajiyev5
- Makhbuba Khayitova3
- Nodirbek Mirfozilov1
- Dilfuzaxon Karimova1
- Madinaxon Turdiyeva1
- Buta Xushvaktov6
- Oybek Normuratov7
- Shohruh Ahmadov8
- Jamilakhon Ermakova1
- Ifoda Akhmedkhodjaeva9
- Botir Khaitov10*corresponding author
- 1Andijan Institute of Agriculture and Agrotechnologies, Andijan, Uzbekistan
- 2Water and Amelioration Scientific Research Institute Public Legal Entity, Baku, Azerbaijan
- 3Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, Uzbekistan
- 4State University of World Languages, Tashkent, Uzbekistan
- 5Urgench State University, Urgench, Uzbekistan
- 6Samarkand State Architecture and Construction University named after M. Ulugbek, Samarkand, Uzbekistan
- 7Termez State University, Termezt, Uzbekistan
- 8Bukhara State Pedagogical Institute, Bukhara, Uzbekistan
- 9The Branch of the Russian State University of Oil and Gaz named after Ivan M.Gubkin in Tashkent, Tashkent, Uzbekistan
- 10Tashkent State Agrarian University, Tashkent, Uzbekistan
Abstract
Climate change and water scarcity in arid agroecosystems necessitate optimized irrigation and fertilization strategies to sustain crop production and soil health. This study investigated the effect of irrigation regimes (Fc 70–70–70%, 70–80–70%, and 80–80–80%) and Rhizotorphin biopreparation on soybean (Glycine max (L.) cv. Orzu) growth during 2023–2024 growing seasons under typical meadow-gray soil conditions of the Fergana Valley, Uzbekistan. The experiment was conducted under three irrigation regimes (Fc 70–70–70%, Fc 70–80–70%, and Fc 80–80–80%), arranged without biotreatment (T1, T2, T3) and with biotreatment (T4, T5, T6), replicated three times in a factorial design structure. This study aimed to evaluate the interaction between irrigation regimes and biofertilizer application on soybean productivity cultivated as a second crop, while simultaneously enhancing soil health. The results demonstrated that soybean biomass increased with higher irrigation norms, whereas the highest yield and grain quality traits were achieved under the moderate irrigation regime combined with Rhizotorphin treatment (T5). Notably, the highest soybean grain yield (2.12 Mg ha -1) and quality were achieved under the 70-80-70% irrigation regime combined with Rhizotorphin treatment (T5). Additionally, water productivity (WP) was also maximized in T5 (0.88 kg m −3), followed by T4 (0.81 kg m -3), whereas excessive irrigation in T6 reduced efficiency despite high biomass accumulation. Treatments without biofertilizer (T1–T3) produced lower seed output (58.3–61.4%) and smaller seed size (141.8–143.9 g per 1000 seeds), with oil content ranging from 22.3–23.2% and protein levels between 38.4–43.6%. In contrast, biofertilizer treatments (T4–T6) consistently improved seed quality traits. Likewise, nitrogen (N), phosphorus (P), and potassium (K) content in plant tissues were significantly higher under the combined effect (T5). Overall, considering climate change concerns, especially in arid climates, the integrated use of optimal irrigation regime with biotreatment can enhance soybean grain yield, improve soil fertility, and promote both economic and ecological sustainability.
Keywords
Introduction
Soybean (Glycine max L.) is a globally important leguminous crop, valued for its high protein and oil content in seeds. This crop is also well-known for contribution to soil health and diversified cropping systems, thereby plays strategic importance role in ensuring global food security and sustainable agricultural development (1). Beyond its economic role, soybeans enhance soil fertility through biological nitrogen fixation, thereby reducing dependence on synthetic fertilizers (1). The global demand for soybeans has expanded rapidly in recent decades, driven by food, feed, and industrial uses. Yet sustaining soybean productivity under climate uncertainty remains a critical challenge, particularly in regions with fragile agroecosystems. As a result, producers face increasing challenges in maintaining soybean productivity due to enhanced vulnerability to climate variability, reduced irrigation efficiency and declined soil fertility (2).
Uzbekistan, situated in Central Asia, faces arid to semi-arid climatic conditions, limited precipitation, and high evapotranspiration rates. Agriculture in the region is constrained by water scarcity, soil degradation, salinity, reduced organic matter, nutrient depletion, and temperature extremes (3). Climate variability further complicates agricultural production, with unpredictable rainfall patterns and increased vulnerability of cropping systems. Crop production in this region relies heavily on chemical inputs, underscoring the need for their strategic and efficient use (4). Soybean cultivation is relatively new in Uzbekistan compared with traditional crops such as cotton, wheat, and maize. Its successful introduction requires adaptive strategies, including improved nutrient management and irrigation techniques that enhance resilience and ensure sustainable yields under stress conditions.
Among innovative approaches, biofertilizers containing beneficial soil bacteria, fungi, or consortia, represent a promising method to enhance crop productivity and soil health. These biocompounds improve nutrient availability, stimulate plant productivity and enhance soil biological activity (5). Additionally, they play a dual role in legumes such as soybean, facilitating nitrogen fixation through symbiotic rhizobia, and mobilize nutrients such as phosphorus and potassium, which are critical under nutrient-deficient soils. Moreover, microbial inoculants can improve plant tolerance to salinity, drought, and temperature extremes, while restoring soil health by increasing organic matter turnover, microbial diversity, and enzymatic activity (6, 7). Numerous microorganisms have been reported to produce phytohormones and exert beneficial effects on plant growth, thereby enhancing climate resilience and crop output (8). In the context of climate challenges in arid agroecosystems, biofertilizers align with climate-smart technologies and national priorities for sustainable intensification and reduced environmental footprint (9).
Despite significant global advances in biofertilizer application on soybean, field-based evidence remains scarce for arid ecosystem of Central Asia, particularly Uzbekistan. Critical gaps include the lack of region-specific data on soybean responses to microbial inoculants under arid soils, limited understanding of combined inoculation strategies integrated with agricultural practices, and insufficient exploration of biofertilizer performance under water-scarce conditions. Addressing these gaps is essential to establish soybean as a viable crop in Uzbekistan’s climate-stressed environments and to advance sustainable nutrient management practices. Following the government initiatives and site-specific conditions, cultivating soybeans as a secondary crop provides the opportunity to harvest twice from the same area and naturally enrich the soil with nitrogen. It is well known that the soybean–Bradyrhizobium symbiosis has been shown to fix nitrogen at rates approaching 300 kg N ha−1 under favorable field conditions (10).
The individual contributions of irrigation techniques and biofertilizers to improving soybean productivity and soil health are already well established. Nevertheless, the optimization of irrigation regimes and nutrient management practices, as well as their interactive effects on soybean productivity and soil health under the meadow gray soil conditions of the Fergana Valley, have not yet been sufficiently studied. Growing evidence from recent studies also suggests that proper management of water and nutrient regimes during the soybean’s vegetation period directly affects not only crop productivity but also improves soil physical and chemical properties, enriches soil biological activity (11, 12). This in turn, opens promising pathways for the biological restoration of degraded soils and reduces water consumption without compromising yield, while contributing to the development of strategies for sustainable land use.
The primary objective of this study is to evaluate the effectiveness of the applied biofertilizer in combination with different irrigation regimes on soybean growth attributes, yield components, and seed quality. It further analyzes nutrient uptake dynamics, with particular emphasis on nitrogen fixation efficiency, and evaluates soil fertility parameters such as organic matter content, available nutrient forms, and microbial activity under the challenging climatic conditions of Uzbekistan. Furthermore, this study determines the potential of biofertilizers and water management techniques as climate-smart interventions to strengthen resilience and promote the sustainability of soybean production systems in arid ecosystems.
Materials and methods
Climate condition
Field experiments were conducted during 2023–2024 growing seasons at the experimental farm of the Andijan Institute of Agriculture and Agrotechnologies, located in Andijan, Uzbekistan (40.783° N, 72.350° E). The site lies within the Ferghana Valley, a region characterized by a continental climate with hot, dry summers and cold winters (Figure 1). Average annual precipitation is relatively low (200–250 mm). Snowfall is occasional but contributes to soil moisture recharge, supporting early spring vegetation growth. The sub-humid climate regime is marked by moderate precipitation concentrated in winter and spring, while summers remain predominantly dry. Seasonal contrasts between cold winters and hot summers create significant thermal amplitude, shaping the agro-ecological conditions of the valley. These climatic features necessitate adaptive management practices, including irrigation scheduling and crop diversification, to mitigate risks associated with variability. These conditions provide a representative setting for evaluating soybean performance and biofertilizer application under the climatic and edaphic challenges typical of Uzbekistan’s irrigated farming systems.

Soil analysis
The soils of the experimental area are predominantly alluvial-meadow types, moderately fertile but prone to salinity and organic matter depletion under intensive cultivation. The soils of the experimental site belong to the category of irrigated meadow gray soils. The depth of groundwater is 1.5-2.0 meters. Soil analysis revealed a gradual decline in humus content and nutrient concentrations with increasing depth (Table 1). The surface horizon (0–10 cm) contained the highest levels of humus (1.21%), nitrogen (0.148%), and available nutrients, including 20.5 mg/kg NO3 and 220 mg/kg K2O. In contrast, deeper layers (30–50 cm) showed markedly lower values, with humus reduced to 0.75% and available NO3 and K2O dropping to 5.1 mg/kg and 100 mg/kg, respectively. These results highlight the nutrient-rich nature of the topsoil and the progressive depletion of organic matter and available forms of phosphorus and potassium with depth.
Table 1. Soil chemical composition.
| Soil horizons (cm) | Humus (%) | N (%) | P (%) | K (%) | Available forms, mg/kg | ||
|---|---|---|---|---|---|---|---|
| N-NO3 | P2O5 | K2O | |||||
| 0-10 | 1.21 | 0.148 | 0.228 | 2.0 | 20.5 | 26.0 | 220 |
| 10-20 | 1.08 | 0.139 | 0.160 | 1.83 | 18.1 | 17.4 | 180 |
| 20-30 | 0.99 | 0.120 | 0.150 | 1.83 | 6.5 | 14.8 | 100 |
| 30-50 | 0.75 | 0.096 | 0.110 | 1.74 | 5.1 | 14.6 | 100 |
Plant material
For this study, soybean (Glycine max (L.) Merr.) cv. “Orzu” was selected, as it is well adapted to the agroclimatic conditions of the Ferghana Valley. This cultivar is recognized for its tolerance to heat and drought stress, consistently exhibiting stable yield performance and desirable seed quality traits under variable environments. Farmers in the region value “Orzu” for its resilience and balanced productivity, making it a reliable choice in areas where water scarcity and high summer temperatures pose significant constraints. The vegetation period of the medium-to-late maturing “Orzu” variety generally spans 120–125 days, with the growing season extending from late April or early May until October, depending on prevailing weather conditions. Soybeans were planted as a secondary crop after harvesting winter wheat. Planting depth ranged from 3–4 cm to 5–6 cm, depending on the soil’s mechanical composition. Under favorable irrigated conditions of the Ferghana Valley, “Orzu” has demonstrated a yield potential of approximately 2.5–3.0 tons per hectare, while maintaining high protein content and stable performance across seasons.
Microbial biofertilizer
Rhizotorphin is produced in Uzbekistan by the Uzbek Scientific Research Institute of Soil Science and Agrochemistry, Tashkent, Uzbekistan. Soybean seeds were inoculated with Rhizotorphin (Rhizobium based biofertilizer) before sowing to ensure effective nodulation and biological nitrogen fixation under the challenging agro-climatic conditions in Uzbekistan. This biocompound (Rhizotorphin) is produced to contain ≥1 × 108 CFU/g of viable Rhizobium cells. Rhizotorphin was selected because it contains regionally adapted Rhizobium strains capable of establishing symbiosis with soybean roots. The recommended dose of the biocompound ensures effective colonization of the rhizosphere and subsequent nodulation. 200 mL of this biocompound was diluted in 10 L water and and thoroughly mixed with 100 kg of soybean seeds immediately prior to planting to ensure effective colonization of the rhizosphere. Inoculation was performed by coating seeds with the microbial preparation, followed by air-drying in the shade to preserve the inoculant’s viability. The use of Rhizotorphin was particularly relevant given the degraded soils in the study area, where conventional fertilization alone is insufficient to sustain productivity. This approach was expected to improve germination, root development, and nutrient uptake, while simultaneously enriching soil microbial activity. Thus, Rhizotorphin application was used in this research as a climate-smart intervention to evaluate the symbiotic effectiveness on soybean growth, yield, and soil fertility.
Experimental design
The experiment’s total land area was 0.2 hectares, of which each plot measured 96 square meters (4.8 m x 20 m, or 8 rows, each measuring 0.6 m in width and 20 m in length). Each plot’s accounting area measured 24 square meters. The experiment was set out in three replications using a factorial design structure (Table 2).
Table 2. Experiment layout.
| Treatments | Irrigation regime Fc | Applied water (m3 ha-1) | Irrigation management | Biofertilizer treatment |
|---|---|---|---|---|
| T1 | 70-70-70% | 2100 | During the vegetation period, soil moisture was maintained at not less than 70% relative to Fc. | No biotreatment |
| T2 | 70-80-70% | 2400 | Soil moisture was increased to 80% during the plant’s flowering and pod formation period. | |
| T3 | 80-80-80% | 2600 | A high moisture regime was maintained throughout the entire growth period. | |
| T4 | 70-70-70% | 2100 | During the vegetation period, soil moisture was maintained at not less than 70% relative to Fc. | Bacterial treatment |
| T5 | 70-80-70% | 2400 | Soil moisture was increased to 80% during the plant’s flowering and pod formation period. | |
| T6 | 80-80-80% | 2600 | A high moisture regime was maintained throughout the entire growth period. |
The experiment evaluated soybean responses under three irrigation regimes (Fc 70–70–70%, Fc 70–80–70%, and Fc 80–80–80%), applied with and without bacterial inoculation, resulting in six treatment combinations. To determine the water-physical properties of the soil, before setting up the experiment, the soil’s field capacity (Fc) was determined using the water filling method in 9 m2 (3×3 m) plots. Irrigation timing was determined based on determining actual soil moisture by thermostat-weight method (in the 0–30 cm layer, taking samples from 5 points) and using a tensiometer.
The recommended dose of chemical fertilizer for soybean was 100:80:60 kg ha−1 NPK. Half of the nitrogen and the full doses of P2O5 and K2O were applied at sowing using ammonium nitrate (34%), superphosphate (17%), and muriate of potash (52%), respectively. The remaining half dose of nitrogen was applied at the first irrigation. In line with regional agronomic practices, crop protection, weeding, and other standard management measures were consistently implemented in each plot. Conducting scientific research in field conditions was carried out based on “Methods of Conducting Field Experiments” (13). Biometric indicators and yield elements of soybeans were determined according to the “State Variety Testing of Agricultural Crops” methodology.
Data collection and chemical analysis
The morphological parameters of soybean plants including fresh and dry weight, shoot and root length, leaf fresh and dry weight, leaf area and weight were analysed. Randomly selected soybean samples were used to record root and shoot length. Fresh biomass was weighed, and dry biomass was determined separately after oven-drying at 65 °C. Soil organic matter and available phosphate were analyzed using the Tyurin and Lancaster methods (14). Phosphorus determination was carried out with a Carl Zeiss flame photometer (model Carl-Zeiss, Jena, Germany) following the procedure described by Horneck and Hanson (15). Potassium content was measured using an inductively coupled plasma spectrophotometer. The total nitrogen difference (TND) method was used in calculating N fixed by soybean from the atmosphere (Ndfa). In this method, Ndfa was determined by deducting the total N of the nonfixing (noninoculated) soybean from the total N accumulated by the nitrogen-fixing (inoculated) soybean (16).
The total oil content was determined using a Soxhlet extractor in accordance with official methods (17). Seed protein content was assessed by neutron activation analysis (18).
Leaf area measurements were taken from five representative plants per treatment using a LI-COR 3100 leaf area meter. Field observations were conducted across several phenological growth stages, including measurements of plant height (in centimeters), number of branches per plant. To estimate dry matter accumulation, destructive samples were collected from each plot area and dried in a lab oven at 60 °C until a constant weight was achieved.
Dried plant samples were ground and passed through a 2-mm sieve prior to chemical analysis. A mixture of 1 mL concentrated sulfuric acid and 10 mL of 50% perchloric acid was added to 0.5 g of the sample in a digestion tube, followed by heating on a hot plate to facilitate decomposition. Total nitrogen (N), phosphorus (P2O5), and potassium (K2O) concentrations were determined using Kjeldahl distillation, the Vanadate method, and inductively coupled plasma spectrophotometry, respectively (14).
The total water consumption of the soybean field was calculated based on the “water balance” equation:
E=(Nh+J+Mo)−Wn,
where Nh is irrigation norm, J is precipitation, Mo is soil moisture reserves, and Wn is soil moisture at the end of vegetation.
The amount of nutrients (NPK) in soil and soybean plant composition was analyzed using agrochemical research methods.
The applied equiation for determining Water Productivity (WP):
WP=Crop Yield (kg/ha)Water Used (m³/ha)
Harvest Index (HI) were determined with the following equation:
HI=Crop Yield (kg/ha)Total Above Ground Biomass (kg/ha)
Nutrient return to the soil was calculated as the product of crop residue biomass and its nutrient concentration, expressed per unit area. The following equation is used: Nutrient Return (kg/ha)=Residue Biomass (kg/ha)×Nutrient Concentration (%)÷100.
Statistical analysis
Analysis of variance (ANOVA) was conducted with the CropStat 2.7. Statistical software program 19, and treatment means were compared using the least significant difference (LSD) test at the 5% level of significance (p< 0.05). The applied biofertilizer and irrigation regimes were considered as fixed effects, while random effects were replication (block), year, and interactions with year. The year effect was not significant, which allowed for pooling the values before the statistical analysis.
Results
Soybean yield and grain quality under various irrigation regimes and biofertilizer treatment
The experiment revealed distinct variations in soybean productivity when biofertilizer treatments were applied under different irrigation regimes (Table 3). Treatments without biofertilizer (T1–T3) produced lower grain yields, ranging from 1.43 to 1.54 Mg ha−1. In contrast, biofertilizer application (T4–T6) significantly enhanced soybean grain yield, increasing by 19.5% under T4 (70-70-70% irrigation regime), 37.6% under T5 (70-80-70%) and 37.7% under T6 (80-80-80%) as compared to their relevant control. A similar trend was observed in total biomass, ranging from 5.28 to 5.75 Mg ha−1 in the untreated plots and from 6.6 to 7.5 Mg ha−1 in the biotreatments. The highest productivity was recorded in T5 (7.418 Mg ha−1 biomass, 2.12 Mg ha−1 grain yield), indicating that the moderate irrigation regime combined with biofertilizer provided the most favorable condition for crop development.
Table 3. Soybean productivity under various irrigation regimes and biofertilizer treatment.
| Treatments | Total biomass,Mg ha-1 | Grain yield(Mg ha-1) | Biomass(Mg ha-1) | Harvest index(HI) | Water productivity(kg m-3) |
|---|---|---|---|---|---|
| T1 | 5.28e | 1.43e | 3.853c | 0.27c | 0.68c |
| T2 | 5.52d | 1.54d | 3.982c | 0.28b | 0.64d |
| T3 | 5.75c | 1.51d | 4.241c | 0.26d | 0.58e |
| T4 | 6.608b | 1.71c | 4.898bc | 0.26d | 0.81b |
| T5 | 7.418a | 2.12a | 5.298a | 0.29a | 0.88a |
| T6 | 7.497a | 2.08b | 5.417b | 0.28b | 0.80b |
| LSD05 | 0.214 | 0.031 | 1.16 | 0.008 | 0.033 |
Means separated by the same lowercase letter (a to f) in each column were not significantly different among treatments at p<0.05.
HI values ranged from 0.26 to 0.29, with the highest efficiency observed in T5, suggesting improved assimilate partitioning toward grain production under biofertilizer treatment in combination with the moderate irrigation (70-80-70%) regime. WP was also maximized in T5 (0.88 kg m-3), followed by T4 (0.81 kg m-3), whereas excessive irrigation in T6 reduced efficiency despite high biomass accumulation. Treatments without biofertilizer showed lower WP (0.58–0.68 kg m-3) confirming the substantial role of the applied microbial inoculant in enhancing WP. Statistical analysis (LSD0.05 = 0.031 for grain yield and 0.008 for WP) confirmed significant differences among treatments, with biofertilizer-treated plots consistently outperforming controls. Overall, the results highlight that moderate irrigation (70-80-70%) regime combined with biofertilizer application is the most effective strategy for maximizing soybean yield, biomass, and water productivity. This integrated approach supports climate-smart agriculture by reducing water demand while sustaining high productivity, aligning with sustainable land management and resilience objectives.
WP remained low in the absence of biofertilizer treatment, with a value of 0.68 kg/m3 under the Fc 70–70–70% regime. Increasing the irrigation norm was generally associated with further declines in WP. Under these conditions, soybean plants were unable to fully express their yield potential due to water scarcity stress. At the Fc 70–80–70% regime, WP decreased to 0.64 kg/m3, and a further reduction was observed under the Fc 80–80–80% regime, where WP reached 0.58 kg/m3. The primary reason for this decline was the continuous maintenance of high soil moisture through frequent irrigation, which led to excessive water consumption. However, yield increases did not keep pace with the higher water input, resulting in inefficient resource use and suggesting unnecessary water wastage.
The results indicate that seed quality parameters were significantly influenced by irrigation regime and biofertilizer application (Table 4). Treatments without biofertilizer (T1–T3) produced lower seed output (58.3–61.4%) and smaller seed size (141.8–143.9 g per 1000 seeds), with oil content ranging from 22.3–23.2% and protein levels between 38.4–43.6%. In contrast, biofertilizer treatments (T4–T6) consistently improved seed quality traits. The highest seed output was observed in T5 (63.0%), accompanied by the greatest seed weight (147.9 g per 1000 seeds), oil content (25.5%), and protein concentration (46.3%). T6 also showed strong performance, with seed output of 62.7% and high protein content (46.1%), though slightly lower oil accumulation compared to T5.
Table 4. Seed quality under various irrigation regimes and biofertilizer treatment.
| Treatments | Seed output(%) | Weight of 1000seeds (g) | Oil(%) | Protein(%) |
|---|---|---|---|---|
| T1 | 58.3d | 141.8c | 22.3c | 38.4e |
| T2 | 61.4b | 143.9bc | 23.2bc | 43.6c |
| T3 | 60.8bc | 142.6c | 22.8c | 42.2d |
| T4 | 61.4b | 145.7b | 24.3b | 45.1b |
| T5 | 63.0a | 147.9a | 25.5a | 46.3a |
| T6 | 62.7ab | 146.7ab | 24.9ab | 46.1ab |
| LSD05 | 2.34 | 1.91 | 1.13 | 1.15 |
Means separated by the same lowercase letter (a to e) in each column were not significantly different among treatments at p<0.05.
The improvements in seed quality traits under biofertilizer treatments suggest enhanced nutrient assimilation and metabolic efficiency. Oil content increased by approximately 3% between T1 and T5, while protein concentration rose by nearly 8%, highlighting the synergistic effect of biofertilizer and optimized irrigation. Statistical separation of means confirmed that differences among treatments were significant at p<0.05, particularly for seed output and seed weight.
Overall, the findings demonstrate that biofertilizer application under the moderate irrigation (70-80-70%) regime (T5) provides the most favorable balance of seed yield, size, and nutritional quality. This integrated management strategy not only enhances productivity but also improves the nutritional value of soybean seeds, supporting sustainable intensification and climate-smart agricultural practices.
Soybean growth and development under various irrigation regimes and biofertilizer treatment
The data reveal that soybean growth characteristics were markedly influenced by irrigation regime and biofertilizer application (Table 5). Plant height increased progressively across treatments, from 63.0 cm in T1 to 88.7 cm in T6, with statistically significant differences confirmed by the LSD0.05 value of 2.11 cm. This trend indicates that enhanced irrigation combined with biofertilizer treatment promoted vegetative development and canopy expansion. Fresh and dry plant weights followed a similar pattern, rising from 106.5 g and 48 g in T1 to 164.5 g and 78 g in T6, respectively, reflecting improved biomass accumulation under favorable water and nutrient conditions.
Table 5. The effect of various irrigation regimes and biofertilizer treatment on soybean growth parameters (height, fresh and dry weight, leaf area).
| Treatments | Plant height (сm) | Fresh weight of plants (g) | Dry weight of plants (g) | Leaf area of plant (m2) |
|---|---|---|---|---|
| T1 | 63.0d | 106.5f | 48.5e | 0.24d |
| T2 | 74.2c | 117.8e | 54.7d | 0.26c |
| T3 | 78.7bc | 129.4d | 60.5c | 0.27c |
| T4 | 80.7b | 139.4c | 64.8b | 0.32b |
| T5 | 84.7ab | 148.6b | 76.3ab | 0.34ab |
| T6 | 88.7a | 164.5a | 78.4a | 0.35a |
| LSD05 | 3.11 | 6.5 | 2.44 | 0.014 |
Means separated by the same lowercase letter (a to d) in each column were not significantly different among treatments at p< 0.05.
Leaf area also expanded consistently, ranging from 0.24 m2 in T1 to 0.35 m2 in T6. The increase in leaf area under biofertilizer treatments (T4–T6) suggests enhanced photosynthetic capacity, which likely contributed to higher biomass and yield observed in previous tables. The combination of moderate irrigation and biofertilizer (T5) provided a balanced improvement, with plant height of 84.7 cm, fresh weight of 148.6 g, dry weight of 76 g, and leaf area of 0.34 m2, indicating optimal vegetative growth without excessive resource input.
Overall, the results demonstrate that biofertilizer application under adequate irrigation regimes significantly improves soybean morphological traits, including plant height, biomass accumulation, and leaf area development. These improvements in vegetative parameters are consistent with enhanced yield and seed quality outcomes, underscoring the importance of integrated water and nutrient management in soybean production. The findings support climate-smart agricultural practices by showing that moderate irrigation combined with biofertilizer optimizes growth efficiency while maintaining sustainability.
It was demonstrated that the amount of root and stubble residues remaining in the soil after harvest are directly dependent on the applied agrotechnology.
The data in Table 6 demonstrate that biomass accumulation was significantly influenced by irrigation regimes and biofertilizer treatments across both the budding and flowering stages. At the budding stage, treatment T1 recorded the lowest biomass (7.91 g m−2 day−1), while T5 achieved the highest value (8.77 g m−2 day−1), representing a 10.9% increase relative to the control. Biotreatments in combination with irrigation regimes resulted in progressive improvements, with increases of 7.96% in T4 and 8.98% in T6, reflecting a consistent positive response to enhanced water and nutrient management.
Table 6. Effects of various irrigation regimes and biofertilizer treatment on biomass accumulation (g m−2 per day).
| Treatments | Budding stage | Difference | Flowering stage | Difference | ||
|---|---|---|---|---|---|---|
| g M2 | % | g/M2 | % | |||
| T1 | 7.91d | – | – | 10.8d | – | – |
| T2 | 8.07c | 0.16 | 2.02 | 11.2c | 0.4 | 3.70 |
| T3 | 8.42bc | 0.51 | 6.45 | 11.3bc | 0.5 | 4.63 |
| T4 | 8.54b | 0.63 | 7.96 | 11.4b | 0.6 | 5.56 |
| T5 | 8.77a | 0.86 | 10.87 | 12.6a | 1.8 | 16.67 |
| T6 | 8.66ab | 0.78 | 8.98 | 12.1ab | 1.3 | 12.04 |
| LSD05 | 0.21 | 0.58 |
Means separated by same lower case letter (a to d) in each column were not significantly different among treatments at p<0.05.
During the flowering stage, similar trends were observed. T1 remained lowest (10.8 g m−2 day−1), whereas T5 reached 12.6 g m−2 day−1, corresponding to a 16.7% increase. Biofertilizer treatments T4 also displayed good gains (5.6%), while T6 also performed well (12.1 g m−2 day−1), though slightly below T5. The LSD0.05 values (0.21 at budding and 0.58 at flowering) confirm that these differences are statistically significant, particularly between the control and the higher-performing treatments.
Overall, the results highlight that combined irrigation optimization and biofertilizer application substantially enhance biomass accumulation, with T5 consistently outperforming other treatments. This suggests that integrated management practices not only improve early vegetative growth but also sustain higher productivity during reproductive development.
Residue returned and soil fertility
The results demonstrate that irrigation regime and biofertilizer application significantly influenced the quantity of crop residues and the associated nutrient return to the soil (Table 7). Straw and root residues increased progressively across treatments, from 1.47 Mg ha−1 in T1 to 2.25 Mg ha−1 in T5, reflecting enhanced biomass production under improved management. Consequently, the amount of nutrients recycled through residues also increased. Nitrogen return increased from 19.3 kg ha−1 in T1 to 31.3 kg ha−1 in T5, while phosphorus and potassium rose from 5.0 to 9.2 kg ha−1 and 3.8 to 7.7 kg ha−1, respectively. These increments highlight the role of biofertilizer in improving nutrient assimilation and subsequent recycling through crop residues.
Table 7. Nutrients returned to the soil by crop residues and Ndfa (averaged across 2023–2024 growing seasons).
| Treatments | Straw residueMg ha-1 | Root residue Mg ha-1 | Total Mg ha-1 | Nutrients returned with soybean residues(kg ha-1) | Ndfa (kg ha-1) | Total nutrient amount(kg ha-1) | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| N | P | K | N | P | K | |||||
| T1 | 1.03c | 0.44c | 1.47d | 19.3e | 5.0e | 3.8e | 0 | 19.3e | 5.0c | 3.8d |
| T2 | 1.11bc | 0.5b | 1.61c | 21.4d | 5.6d | 4.2d | 0 | 21.4d | 5.6c | 4.2dd |
| T3 | 1.14bc | 0.56b | 1.7c | 21.3d | 6.6c | 4.8c | 0 | 21.3d | 6.6b | 4.8c |
| T4 | 1.21b | 0.52b | 1.73 | 23.0c | 6.7c | 5.0c | 40.6c | 63.6c | 6.7b | 5.0c |
| T5 | 1.54a | 0.71a | 2.25a | 31.3a | 9.2a | 7.7a | 62.9a | 94.2a | 9.2a | 7.7a |
| T6 | 1.48ab | 0.65ab | 2.13b | 28.8a | 8.7b | 6.8b | 51.9b | 80.7b | 8.7ab | 6.8b |
| LSD05 | 0.13 | 0.13 | 0.011 | 1.06 | 0.45 | 0.41 | 5.4 | 5.6 | 1.2 | 0.8 |
Means marked with different letters represent significant differences (p< 0.05).
The application of the biocompound under the moderate irrigation regime resulted in the highest biological nitrogen fixation (Ndfa), reaching 62.9 kg ha−1 in T5. This was followed by 51.9 kg ha−1 in T6, where full irrigation was combined with biofertilizer application. Likewise, the highest total nitrogen contribution (94.2 kg ha−1) was recorded in T5, followed by 80.7 kg ha−1 in T6, confirming that biofertilizer application substantially increased nitrogen fixation process in the soil. Statistical separation of means (p< 0.05) confirmed significant differences among treatments, particularly for nitrogen, phosphorus, and potassium returns.
Overall, the findings indicate that the moderate irrigation regime combined with biofertilizer application (T5) maximized nutrient recycling through enhanced biological nitrogen fixation. This integrated management strategy not only improved soybean productivity but also contributed to soil fertility restoration, supporting long-term sustainability of cropping systems. The results emphasize the dual benefit of biofertilizer: enhancing plant nutrition during growth and enriching soil nutrient pools post-harvest, thereby aligning with climate-smart and regenerative agricultural practices.
Research results showed that soybean productivity and the amount of organic residues remaining in the soil after harvest were directly dependent on applied agrotechnical measures, particularly biofertilizer application and the applied optimal irrigation regime. Plant residues contained 1.31% N, 0.34% P, 0.26% K, 0.46% Ca and 0.17 Mg under T1, while these indicators were increased with optimization irrigation regime and biofertilizer application (Table 8).
Table 8. Effects of the applied treatments on total nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) concentrations on soybean vegetative organs.
| Treatments | N | P | K | Ca | Mg |
|---|---|---|---|---|---|
| T1 | 1.31c | 0.34c | 0.26d | 0.46c | 0.17d |
| T2 | 1.33b | 0.35c | 0.26d | 0.47c | 0.17d |
| T3 | 1.35b | 0.39b | 0.28c | 0.50b | 0.18cd |
| T4 | 1.33b | 0.39b | 0.29c | 0.57ab | 0.19c |
| T5 | 1.39a | 0.41a | 0.34a | 0.67a | 0.24a |
| T6 | 1.35b | 0.41a | 0.32b | 0.62a | 0.21b |
| LSD05 | 0.03 | 0.016 | 0.011 | 0.06 | 0.015 |
Means separated by same lower case letter (a to d) in each column were not significantly different among treatments at p<0.05.
The nutrient composition of soybean vegetative organs was significantly affected by irrigation regime and biofertilizer application. Nitrogen concentration increased from 1.31% in T1 to 1.39% in T5, with statistically significant differences confirmed by the LSD0.05 value of 0.03. Treatments with biofertilizer (T4–T6) consistently showed higher nitrogen accumulation compared to non-treated controls, indicating improved nitrogen assimilation and enhanced vegetative growth. Phosphorus content followed a similar trend, rising from 0.34% in T1 to 0.41% in T5 and T6, suggesting that biofertilizer application facilitated greater uptake of this essential macronutrient.
Potassium concentration was lowest in T1 (0.26%) and highest in T5 (0.34%), with significant differences among treatments (LSD0.05 = 0.011). The increase in potassium under biofertilizer treatments is particularly important, as potassium plays a critical role in osmotic regulation, enzyme activation, and stress tolerance. Essential nutrients such as calcium and magnesium concentrations also improved under biofertilizer application. Calcium rose from 0.46% in T1 to 0.67% in T5, while magnesium increased from 0.17% in T1 to 0.24% in T5, both showing statistically significant differences. These results highlight the synergistic effect of biofertilizer and irrigation in enhancing nutrient uptake efficiency.
The dynamics of nodule formation clearly demonstrate the synergistic effect of irrigation regimes and biofertilizer application. Under sole irrigation treatments (70-70-70%, 70-80-70%, and 80-80-80%), nodule numbers remained relatively low, ranging from 0.7 to 2.3 nodules per plant across the bud, flowering, and pod-forming stages. This baseline indicates that water management alone provides limited stimulation of nodulation.
In contrast, the addition of biofertilizer markedly enhanced nodule development (Figure 2). At T4, nodules increased to 9.5, 10.4, and 11.6 per plant across successive stages, representing more than a ten-fold improvement compared to irrigation alone. Similarly, soybeans under T6 produced 10.2 nodules at budding, 13.4 at flowering, and 17.8 at pod formation, highlighting the combined benefit of moderate irrigation adjustment with biofertilizer inoculation. The most pronounced effect was observed under T5, where nodules reached 13.1, 17.8, and 22.1 per plant, underscoring the strong positive interaction between optimal irrigation and microbial supplementation.

Overall, these results confirm that biofertilizer application substantially amplifies nodulation beyond the effect of irrigation alone, with the highest response achieved under the 70-80-70% + B regime. This pattern suggests that adequate soil moisture not only supports plant growth but also enhances rhizobial activity and symbiotic efficiency, thereby improving nitrogen fixation potential.
Discussion
In this study, soybean treated with biofertilizer exhibited substantial increases in both vegetative and generative organs, depending on the irrigation regime in the meadow-gray soils of the Fergana Valley. The results demonstrate that soybean productivity and its contribution to soil fertility depend not only on biological inputs but also on the application of an optimal irrigation regime. The application of biofertilizer under the moderate irrigation (70-80-70%) regime (T5) provided the most favorable conditions for soybean growth, yielding the highest biomass (7.42 Mg ha−1) and grain yield (2.12 Mg ha−1). This treatment also achieved the greatest water productivity (0.88 kg m−3) and harvest index (0.29), indicating efficient assimilate partitioning toward grain production. In contrast, excessive irrigation under T6, while producing slightly higher biomass, did not translate into superior yield or efficiency, underscoring the trade-off between vegetative growth and resource-use efficiency. Treatments without biofertilizer consistently showed lower yield and water productivity, confirming the critical role of microbial inoculation in enhancing nutrient cycling and water productivity. The superior performance of T5 suggests that moderate irrigation optimizes soil aeration, reduces nutrient leaching, and promotes effective nodulation and nitrogen fixation compared to higher irrigation amount. Numerous studies have demonstrated that beneficial microorganisms enhance plant nutrition by either facilitating nutrient uptake or increasing nutrient availability within the rhizosphere (20). These findings highlight that balanced water management combined with biofertilizer application can sustain high productivity while conserving water resources (21).
While soybeans exhibit only moderate moisture requirements during the early stages of growth (up to emergence), their demand for water increases sharply during flowering and pod formation. Elevating soil moisture to 80% of field capacity during these stages enhanced photosynthetic activity and created optimal conditions for protein synthesis. As numerous studies have demonstrated that water scarcity negatively impacts soybean grain quality and the activity of symbiotic nodule bacteria (22, 23).
Specifically, 70% during the pre-flowering period, increasing moisture to 80% during the flowering and pod formation period, improved the plant’s transpiration process. The WP coefficient increased by 12-15% under T5 and reached the highest level (0.88 kg m3). Increasing moisture to the Fc 80-80-80% regime increased water consumption but led to a decrease in efficiency (0.80 kg m3). Based on the above, it can be emphasized that the advantage of soybean cultivation in the Fergana Valley with a 70-80-70% irrigation regime combined with biofertilizer has been clearly demonstrated as an economic model. This model not only saves water but also enables farmers to obtain maximum profit.
The Rhizotorphin biopreparation used in this field researches facilitated to increase biological nitrogen fixation (BNF) in the soil. Application of the Rhizobium group bacteria not only improved the plant’s nitrogen supply but also caused the formation of organic nitrogen reserves in the soil. The 1.39% nitrogen content in soybean vegetative parts under T5 testified to soybean’s high potential for assimilating atmospheric nitrogen. This indicator has been reflected in field research as being ecologically safe and economically cost-effective compared to traditional mineral fertilization systems (24). These findings align with previous reports demonstrating the beneficial role of bioactive compounds in enhancing soil physical structure, chemical properties, microbial functioning, and nutrient availability (25).
The number of nodules per plant is regarded as a key determinant directly contributing to the exploitation of yield potential in leguminous crops. The data clearly indicate that nodule formation was significantly influenced by the applied agricultural practices (26). It is well-known that plant growth-promoting effect of the applied biofertilizer may be due to the secretion of growth-promoting hormones. This phytohormone regulates multiple processes in plant growth and development and plays a pivotal role in shaping root architecture, including the initiation of lateral roots and the differentiation of root vascular tissues (27). Recent studies concluded that Rhizobium strains will be useful in association with indigenous beneficial microbes because of their synergy in plant growth, nodulation, and productivity of soybean (28). This confirmed that Rhizobium strain could be produced as biofertilizer proven effectiveness on soybean.
One of the main elements in the field observation process was the highest amount of crop residues left in the soil due to the applied techniques. Although the nutrient content in crop residues increased with the increase of irrigation amount, whereas the biofertilizer application also contributed to enhanced biomass accumulations (the total biomass, root and stubble amount). The higher biomass ensured the balance of competition between plants development and resource use efficiency. These results are in accordance with the findings of Allanov et al. (29).
Data analysis shows that biofertilizer application in combination with optimal irrigation regime (70-80-70%) not only develop the plant’s vegetative mass but also intensify the activity of nodule bacteria in the root system. Under the moderately irrigated regime (70-80-70%), the decomposition of root residues and the accumulation of nutrient reserves were enhanced, thereby contributing positively to the soil nutrient pool. In contrast, under the low irrigation regime, reduced root and stubble biomass led to lower overall NPK reserves in the soil. As a result, the return of pure nitrogen and other mineral nutrients to the soil was diminished. Differences in nodulation to biofertilizer treatment across the applied irrigation regimes further reflected crop-specific interactions between nutrient availability, microbial activity, soil chemical and physical properties which can influence plant growth and productivity (30). This can be explained by several complementary physicochemical and biological advantages of the integrated techniques used in this study.
Field scientific research results showed that the NPK content in root and stubble residues were higher under 70-80-70% irrigation regime coupled with the biotreatment which was explained by its climate resilience and adaptation to local soil-climatic conditions (31). Regarding the practical significance of field research, a ready nutrient source in the soil for crops planted after soybean harvest was achieved. The high NPK content in root and stubble composition under T5 serves to improve the water-physical properties of the soil and increase the resistance of the next crop to cold and diseases, which is the relevance of this particular research. As seen in this study, soybean not only a source of high-quality protein and oil but also an incomparable “biological ameliorant” for naturally restoring soil fertility (32).
This work provides empirical evidence from real farming contexts, making the findings directly applicable to regional agricultural practices. The study contributes to scientific advancement by generating new insights into microbial–legume interactions under stress conditions, offers practical relevance by providing farmers eco-friendly alternatives to chemical fertilizers. Through these uncommon features, microbial inoculants offer a nature based approach to enhancing crop resilience against climate-related challenges during growth, particularly under the influence of both abiotic and biotic stress factors (33). Amid global climate change and increasing water scarcity, preventing land degradation while achieving high crop yields through nature-based solutions represents one of the most urgent challenges for crop production (34). BNF is an essential component of nature based solution for sustainable agriculture by reducing reliance on synthetic nitrogen inputs (35).
In summary, soybean cultivation in Fergana Valley represents both an opportunity and a challenge. The integration of innovative techniques into soybean production systems offers a pathway to strengthen crop resilience, enhance nutrient efficiency, and restore soil health under climate stress. By addressing critical knowledge gaps and providing region-specific evidence, this study advances the understanding of sustainable soybean production in arid environments and contributes to broader efforts toward climate-smart agriculture.
Conclusions
The experiment provided clear scientific evidence that the moderate (70–80–70%) irrigation in combination with the Rhizotorphin treatment produced the most favorable condition for soybean growth and development in arid environment of Fergana Valley. This setting allowed to obtain high soybean yield (2.12 Mg ha−1) and better grain quality, while improved soil quality indicators. In addition, this integrated treatment allowed for saving water resources by up to 15% and ensured the highest WP (0.88 kg/m3) while water has become a limited resource in this arid region. Although the high irrigation regime (80–80–80%) resulted in greater biomass accumulation, the moderate regime (70–80–70%) produced higher soybean yields, enhanced organic matter retention in the soil, and consequently improved soil fertility. Moreover, biological nitrogen fixation was intensified under the moderate irrigation regime through the stimulated activity of nodule bacteria following Rhizotorphin application. Due to certain limitations such as a single location experiment, a limited duration, and under specific soil conditions the generalizability of the findings remains restricted. Therefore, future research should incorporate multi-location and multi-season trials across diverse soil types and climatic contexts.
Based on the field research results, the most effective model for soybean cultivation as a secondary crop under Fergana Valley conditions was the moderately irrigated regime (70-80-70%) combined with Rhizotorphin application. This model enabled water saving, naturally restore soil fertility, and obtain high-quality soybean grain yields in the face of climate change and water scarcity.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Footnotes
Edited by: Marko Vincekovic, University of Zagreb, Croatia
Reviewed by: S.M. Mofijul Islam, Bangladesh Rice Research Institute, Bangladesh
Zahra Najafi Vafa, Postdoc Career Development Initiative, Netherlands
Statements
- Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- Funding
The author(s) declared that financial support was not received for this work and/or its publication.
- Data availability
The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.
- Author contributions
UN: Writing – original draft, Writing – review & editing, Formal analysis, Data curation, Conceptualization. SS: Writing – review & editing, Writing – original draft, Project administration, Methodology, Software. BM: Supervision, Writing – review & editing, Validation, Writing – original draft, Conceptualization. KT: Writing – original draft, Resources, Methodology, Funding acquisition, Writing – review & editing. DY: Writing – original draft, Resources, Writing – review & editing, Project administration, Data curation. AK: Funding acquisition, Formal analysis, Conceptualization, Writing – review & editing, Writing – original draft. ZT: Data curation, Formal analysis, Writing – original draft, Funding acquisition, Writing – review & editing. MK: Writing – review & editing, Writing – original draft, Project administration, Supervision, Visualization. NM: Writing – original draft, Conceptualization, Methodology, Formal analysis, Writing – review & editing. DK: Methodology, Writing – review & editing, Funding acquisition, Project administration, Writing – original draft. MT: Writing – review & editing, Formal Analysis, Writing – original draft, Methodology, Investigation. BX: Methodology, Conceptualization, Writing – original draft, Validation, Writing – review & editing. ON: Writing – original draft, Writing – review & editing, Methodology, Software. SA: Writing – original draft, Writing – review & editing, Data curation, Methodology. JE: Writing – original draft, Writing – review & editing, Data curation, Validation. IA: Writing – original draft, Writing – review & editing, Methodology, Formal analysis. BK: Writing – review & editing, Writing – original draft, Methodology, Conceptualization, Project administration.
References
- 1 Yerkuatov R, Sydyk D, Kenenbayev S, Turebayeva S, Kazybaeva A, Nurbekov A. Innovative nutrient management practices for soybean production in southern Kazakhstan. Front Sustain Food Syst. (2026) 10: 1704644. doi: doi:10.3389/fsufs.2026.1704644
- 2 Nurbekov A, Kosimov M, Shaumarov M, Khaitov B, Qodirova D, Mardonov H. Short crop rotation under no-till improves crop productivity and soil quality in salt affected areas. Agronomy. (2023) 13: 2974. doi: doi:10.3390/agronomy13122974
- 3 Israilov I, Sindarov O, Salomov S, Khayitov K, Bobokulov S, Begmatov I. Agronomic efficiency of nano-integrated nutrient management on cotton yield traits under arid farming conditions. Front Sustain Food Syst. (2025) 9: 1695604. doi: doi:10.3389/fsufs.2025.1695604
- 4 Umarov S, Nurbekov A, Nishanov N, Kosimov M, Bobomurotov S, Umarov M. Land degradation in Uzbekistan: key challenges and sustainable solutions. Front Sustain Food Syst. (2025) 9: 1676403. doi: doi:10.3389/fsufs.2025.1676403
- 5 Khaitov B, Abdumuxtorov S, Amanturdiev S, Kholliyev A, Norboyeva U, Adizova K. Integrating conservation practices and microbial inoculation in wheat–mungbean sequential cropping systems under dryland conditions. Front Sustain Food Syst. (2026) 10: 1784923. doi: doi:10.3389/fsufs.2026.1784923
- 6 Daryanto S, Fu B, Zhao W, Wang S, Jacinthe P-A, Wang L. Ecosystem service provision of grain legume and cereal intercropping in Africa. Agric Syst. (2020) 178: 102761. doi: doi:10.1016/j.agsy.2019.102761
- 7 Israilov I, Sheraliev K, Abdalova G, Iminov A, Allanov K, Karimov A. Interactive effects of nitrogen fertilization and Bradyrhizobium japonicum on agronomical traits of soybean in salt-affected soils. Turk J Field Crops. (2023) 28: 15 – 25.
- 8 Htwe AZ, Moh SM, Moe K, Yamakawa T. Effects of co-inoculation of Bradyrhizobium japonicum SAY3-7 and Streptomyces griseoflavus P4 on plant growth, nodulation, nitrogen fixation, nutrient uptake, and yield of soybean under field conditions. Soil Sci Plant Nutr. (2018) 64: 222–9.
- 9 Nurbekov A, Umarov S, Azizov S, Umarov M, Khaitov B, Khalilova L. Arid irrigated winter wheat and soybean cropping under conservation tillage systems. Front Sustain Food Syst. (2025) 9: 1512277. doi: doi:10.3389/fsufs.2025.1512277
- 10 Ntambo MS, Chilinda IS, Taruvinga A, Hafeez S, Anwar T, Sharif R. The effect of rhizobium inoculation with nitrogen fertilizer on growth and yield of soybeans (Glycine max L.). Int J Biosci. (2017) 10: 163–72.
- 11 Matyakubov B, Nurov D, Beshimov S. Review of calculation methods for determining the total evaporation of irrigated agricultural fields. Eur J Agric Rural Educ. (2022) 3: 38 – 43.
- 12 Karimov A, Khalikov B, Isaev S, Sindarov O, Khayitov K, Avliyakulov M. Efficiency of drip irrigation in amaranth production using the HYDRUS-1D model. Front Sustain Food Syst. (2025) 9: 1612679. doi: doi:10.3389/fsufs.2025.1612679
- 13 Methods of conducting field experiments. Tashkent: Uzbek Cotton Research Institute (2007).
- 14 NIAST. Method of Soil and Plant Analysis. Suwon, Republic of Korea: National Institute of Agricultural Science and Technology (2000).
- 15 Horneck DA, Hanson D. Determination of potassium and sodium by flame emission spectrophotometry. In: Handbook of Reference Methods for Plant Analysis, Boca Raton, Florida: CRC Press vol. 19. (1998). p. 153–5.
- 16 Danso SKA. Assessment of biological nitrogen fixation. Fertil Res. (1995) 42: 33 – 41. doi: doi:10.1007/978-94-009-1706-4_4
- 17 Januszewska A, Siedlecka EM, Glamowski P, Tomasiak I. Determination of oil content in rapeseeds using Soxhlet extraction and pulsed nuclear magnetic resonance spectrometry. PN-EN ISO 659. (1999).
- 18 Prenger EM, Ostezan A, Mian MR, Stupar RM, Glenn T, Li Z. Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean. Theor Appl Genet. (2019) 132: 2965–83. doi: doi:10.1007/s00122-019-03399-w
- 19 CropStat 2.7. Statistical Software Program (2015). Philippines: International Rice Research Institute. Available online at: www.bbi.irri.org/products (Accessed March 21, 2026).
- 20 Gulshan T, Verma A, Ayoub L, Sharma J, Sharma T, Bhadu A. Increasing nutrient use efficiency in crops through biofertilizers. Pharma Innovation J. (2022) 11: 2003–10.
- 21 França ACF, Coelho RD, da Silva Gundim A, de Oliveira Costa J, Quiloango-Chimarro CA. Effects of different irrigation scheduling methods on physiology, yield, and irrigation water productivity of soybean varieties. Agric Water Manage. (2024) 293: 108709.
- 22 Aydinsakir K. Yield and quality characteristics of drip-irrigated soybean under different irrigation levels. Agron J. (2018) 110: 1473–81.
- 23 Morbidini F, Barrera W, Zanin G, Verdi L, Camarotto C, Ghinassi G. The state of the art on deficit irrigation in soybean. Irrig Drain. (2024) 73: 757–69. doi: doi:10.1002/ird.2903
- 24 Nurbekov A, Kosimov M, Islamov S, Khaitov B, Qodirova D, Yuldasheva Z. No-till, crop residue management and winter wheat-based crop rotation strategies under rainfed environment. Front Agron. (2024) 6: 1453976. doi: doi:10.3389/fagro.2024.1453976
- 25 Shabbir U, Tyagi A, Ham HJ, Elahi F, Oh DH. Effect of fermentation on the bioactive compounds of the black soybean and their anti-Alzheimer’s activity. Front Nutr. (2022) 9: 880361. doi: doi:10.3389/fnut.2022.880361
- 26 Kholikova M, Babakhanova D, Rakhmatullayeva A, Khamrayev R, Abdrashitova E, Xojamkulova Y. Evaluation of yield and yield attributes traits of soybean (Glycine max L. Merr.) varieties in Uzbekistan. J Wildl Biodivers. (2024) 8: 260–8.
- 27 Li XY, Wang JH, Lin X, Chen ZQ. Effect of irrigation and fertilization on soybean growth and yield in different soil types. Mol Soil Biol. (2024) 15: 216–26. doi: doi:10.5376/msb.2024.15.0022
- 28 Zeleke K, Nendel C. Yield response and water productivity of soybean (Glycine max L.) to deficit irrigation and sowing time in south-eastern Australia. Agric Water Manage. (2024) 296: 108815. doi: doi:10.1016/j.agwat.2024.108815
- 29 Allanov K, Sheraliev K, Ulugov C, Ahmurzayev S, Sottorov O, Khaitov B. Integrated effects of mulching treatment and nitrogen fertilization on cotton performance under dryland agriculture. Commun Soil Sci Plant Anal. (2019) 50: 1907–18. doi: doi:10.1080/00103624.2019.1648496
- 30 Barati V, Ghadiri H, Zand-Parsa S, Karimian N. Nitrogen and water use efficiencies and yield response of barley cultivars under different irrigation and nitrogen regimes in a semi-arid Mediterranean climate. Arch Agron Soil Sci. (2015) 61: 15 – 32. doi: doi:10.1080/03650340.2014.921286
- 31 Matyakubov B, Yakhyoev O, Karabayev A, Altmishev A. The importance of field research in efficient water use in Kashkadarya region. Bio Web Conferences. (2025) 151: 4021. doi: doi:10.1051/bioconf/202515104021
- 32 Namozov F, Islamov S, Atabaev M, Allanov K, Karimov A, Khaitov B. Agronomic performance of soybean with Bradyrhizobium inoculation in double-cropped farming. Agriculture. (2022) 12: 855–64. doi: doi:10.3390/agriculture12060855
- 33 Khaitov B, Allanov K, Islam KR, Park KW. Bio-inoculant improves nitrogen-use efficiency and cotton yield in saline soils. J Plant Nutr Soil Sci. (2019) 182: 393 – 400. doi: doi:10.1002/jpln.201800063
- 34 Kim VV, Narimanov AA. Increasing the productivity and quality of vegetable soybeans in using various growth stimulants in Uzbekistan. Int J Innov Eng Res Technol. (2020) 7: 80–4.
- 35 Freiria GH, Gonçalves LSA, Gomes GR, Furlan FF, Lima WF, Prete CEC. Yield, proteins, bioactive compounds and minerals in food-type soybean grains in different environments. Agrária-Revista Bras Ciências Agrárias. (2020) 15: 1 – 9. doi: doi:10.5039/agraria.v15i2a7410
Citation
Nematov, U., et al. (2026). Effects of biofertilizers under varying irrigation regimes on soybean productivity and soil fertility in arid agroecosystems. Frontiers in Soil Science, Volume 6. https://doi.org/
- Received
- Accepted
- Published
- Volume
- 6 - 2026
Copyright
Copyright © 2026 Nematov, Shahmaliyeva, Matyakubov, Tursunov, Yormatova, Karabayev, Tajiyev, Khayitova, Mirfozilov, Karimova, Turdiyeva, Xushvaktov, Normuratov, Ahmadov, Ermakova, Akhmedkhodjaeva and Khaitov.
License: https://creativecommons.org/licenses/by/4.0/
*Correspondence: Botir Khaitov
Article metrics
- Views
- 0
- Downloads
- 0
- Citations
- 0
- Shares
- 0
