Agricultural Research最新文献

{"title":"Temporal Dimensions of Climate-Smart Agriculture Practices in Africa: A Systematic Literature Review","authors":"Amri S. Yusuph,&nbsp;Emmanuel F. Nzunda,&nbsp;Sixbert K. Mourice,&nbsp;Tommy Dalgaard","doi":"10.1007/s40003-026-01012-3","DOIUrl":"10.1007/s40003-026-01012-3","url":null,"abstract":"<div><p>Climate-smart agriculture (CSA) has emerged as a promising strategy for sustainably addressing the impacts of climate change by enhancing productivity and adaptability, reducing greenhouse gas (GHG) emissions, and ensuring food security. While research has examined the benefits, effects, and barriers to the widespread adoption of CSA practices, knowledge of the temporal perspective influencing adoption decisions in Africa remains limited. This study aims to identify the most widely adopted CSA practices, understand how farmers’ temporal perspectives shape decision-making, and examine the influence of financial, institutional, market, and policy mechanisms on CSA adoption. The study examined 55 core articles on CSA in Africa, using the PRISMA framework to search for and select the documents. Data were obtained from the Web of Science and Scopus databases. The findings revealed a diverse range of CSA practices implemented in different countries across Africa. These include conservation agriculture (63%), agroforestry (49%), improved crop varieties (41%), Integrated Soil Fertility Management (ISFM) (23%), and mixed cropping (14%). Farmers’ temporal perspectives, including long-, medium-, and short-term decision-making, economic considerations, risk perception, perceived behaviour, and historical experience, significantly influence the adoption of CSA practices. The review also presents evidence from studies showing how financial, institutional, policy, and market mechanisms can promote wider adoption of CSA practices. These include market prices, subsidies, rural finance, and training and information. Policymakers and stakeholders should consider temporal perspectives, as well as financial and other incentive mechanisms, when promoting the use of CSA practices to ensure a more sustainable and resilient agricultural system in Africa.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1497 - 1508"},"PeriodicalIF":1.5,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Suppressive Impact of Mycorrhizal Fungi (Rhizophagus irregularis and Piriformospora indica) on Root-Knot Nematode (Meloidogyne incognita) in Lettuce","authors":"Eman El-Remaly","doi":"10.1007/s40003-026-01013-2","DOIUrl":"10.1007/s40003-026-01013-2","url":null,"abstract":"<div><p>This study was performed to evaluate <i>Rhizophagus irregularis</i> and <i>Piriformospora indica</i> as safe alternatives for suppressing the root-knot nematode, <i>Meloidogyne incognita</i>, on lettuce cv. Salinas. The primary aim was to assess the effects of individual and combined applications of these fungi on reducing nematode infestation and enhancing lettuce yield and quality. The combined application exhibited strong nematicidal activity against <i>M. incognita</i>, with efficacy comparable to chemical nematicides. Results showed that the mixed inoculation treatment significantly enhanced plant growth, yield, and enzymatic activity in both the plants and soil. The highest yield increase was observed in the combined treatment, rising from 28,400 heads in the control to 37,025 heads. The combined application of the biological agents significantly suppressed nematode populations. The reproduction factor (RF) was reduced from 1.24 to 0.33. This was accompanied by an 81.08% reduction in gall numbers, a 67.90% reduction in egg masses, and a 94.75% reduction in fecundity. The dual application of <i>R. irregularis</i> and <i>P. indica</i> significantly enhanced lettuce growth, productivity, antioxidant and soil enzyme activities. Consequently, utilizing this biological control for managing <i>M. incognita</i> is recommended. This approach supports sustainable agricultural systems by promoting human health, preserving ecological balance, and maintaining beneficial soil microbial communities.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1593 - 1604"},"PeriodicalIF":1.5,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the Soil Aggregation, Carbon Fractions, and Enzyme Activities in Oil Palm Monoculture and Oil Palm with Cocoa Intercropping","authors":"R. P. Premalatha,&nbsp;K. Ramachandrudu,&nbsp;K. Suresh,&nbsp;K. Manorama,&nbsp;V. Chandrakala,&nbsp;L. Gowthami","doi":"10.1007/s40003-026-01004-3","DOIUrl":"10.1007/s40003-026-01004-3","url":null,"abstract":"<div><p>Intercropping is a sustainable management practice that simultaneously addresses the economic challenges of delayed income associated with plantation crops and the ecological challenges of soil health. While intercropping is known to enhance sustainability, the specific impacts of cocoa intercropping on soil aggregation and carbon dynamics in Indian oil palm plantations remain unclear. This study evaluated the hypothesis that cocoa intercropping improves soil physical and biochemical properties compared to oil palm monoculture across different sampling points and depths. Our results indicated that oil palm with cocoa intercropping significantly increased the proportion of microaggregates (0.053–0.25 mm), small macroaggregates (0.25–2 mm), large macroaggregates (&gt; 2 mm) and water-stable aggregates compared to the monoculture. These improvements were most pronounced in the basins of the intercropped system, driven by higher aggregate-associated soil organic matter and increased enzyme activities. In contrast, the interspace of monoculture showed a higher proportion of silt + clay fractions. Non-labile carbon accounted for over 90% of total organic carbon, representing a high proportion of recalcitrant carbon in the soil, while intercropping significantly enhanced both the labile and non-labile fractions. These findings demonstrate that cocoa intercropping acts as a sustainable management practice to rejuvenate soil structure and increase aggregate stability in tropical oil palm plantations, improving soil health and economic returns for farmers.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1720 - 1733"},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antimicrobial Plant Protein Patatin: Identification and In-Silico Analysis Through Phylogenetics and Molecular Docking","authors":"Sarah Tariq,&nbsp;Binish Khaliq,&nbsp;Hina Shaheen,&nbsp;Ahmad Riaz,&nbsp;Sumaira Rubbani,&nbsp;Muhammad Sajid Hamid Akash,&nbsp;Amjad Hussain,&nbsp;Muhammad Imran,&nbsp;Muhammad Arslan Javed,&nbsp;Ahmed Akrem,&nbsp;Sohaib Mehmood,&nbsp;Sajjad Azam","doi":"10.1007/s40003-026-01020-3","DOIUrl":"10.1007/s40003-026-01020-3","url":null,"abstract":"<div><p>Over the past decade, plant-derived proteins have gained attention as potential reservoirs of antimicrobial agents due to their efficacy and safety. This study focuses on <i>Solanum tuberosum</i> patatin (<i>St</i>P), a major storage protein from potato (<i>Solanum tuberosum</i> L.), known for its possible antibacterial properties. <i>St</i>P was extracted using ammonium sulphate precipitation, quantified via the Bradford assay, and confirmed by SDS-PAGE, revealing a single 42 kDa band. Sequence analysis indicated a theoretical isoelectric point of 5.05, suggesting pH sensitivity. Physicochemical profiling showed low hydrophobicity, room temperature stability, an aliphatic index of 83.73, and an instability index of 32. Structural modeling revealed three potential ligand-binding sites, with one prominent site exhibiting a large surface area and volume. Molecular docking demonstrated strong binding affinities (ΔG − 7.9 to − 12.5 kcal/mol) of <i>St</i>P with N-acetyl-<i>β</i>-<i>D</i>-glucosamine and <i>β</i>-glucan—key components of microbial cell walls. Antimicrobial testing of purified <i>St</i>P showed notable antifungal activity against <i>Sclerotinia sclerotiorum</i> and <i>Aspergillus niger</i>, with significant zones of inhibition. In contrast, antibacterial effects against <i>Pseudomonas aeruginosa</i> and <i>Staphylococcus aureus</i> were mild. These findings support the potential of <i>St</i>P as a candidate for antimicrobial applications, particularly in combating fungal pathogens.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1687 - 1697"},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Field Evaluation of Pseudomonas-Based Inocula on Maize Growth Traits and Yield Components in a Milpa System: A PGPR Alternative to Synthetic Fetilizers","authors":"Blanca Rojas-Sánchez,&nbsp;Ma. del Carmen Orozco-Mosqueda,&nbsp;Gustavo Santoyo","doi":"10.1007/s40003-026-01005-2","DOIUrl":"10.1007/s40003-026-01005-2","url":null,"abstract":"<div><p>The milpa is a Mesoamerican agroecological polyculture that faces productivity limitations due to environmental factors, and the use of plant growth-promoting rhizobacteria (PGPR) represents a promising strategy to mitigate these stressors. In this study, we evaluated the impact of a bioinoculant based on <i>Pseudomonas fluorescens</i> UM270, applied in liquid form and encapsulated in alginate beads, on the growth and production of <i>Zea mays</i> within a milpa system associated with <i>Phaseolus vulgaris</i> and <i>Cucurbita</i> spp. Both formulations improved maize growth, significantly enhancing chlorophyll content, plant height, root development, and biomass. The liquid bioinoculant increased maize yield by 35–37% compared to uninoculated plants, while the encapsulated formulation increased it by 43–44%. In the milpa system, yield increases were 24–25% and 15–17% for the liquid and encapsulated treatments, respectively. Compared with diammonium phosphate (DAP), maize production increased by 21–54% under bioinoculation treatments. The combination of bioinoculants with DAP was compatible, resulting in 37–45% yield increases, while <i>P. vulgaris</i> and <i>Cucurbita</i> spp. showed no significant yield changes, except when DAP was applied in combination with the bacterial inoculum. Differences among treatments were assessed by one-way ANOVA followed by Tukey’s HSD test (<i>P</i> ≤ 0.05). These findings highlight the consistency of a field-applied bioinoculant based on <i>P. fluorescens</i> UM270, regardless of the formulation method, as a sustainable biotechnological tool to improve maize productivity in the milpa system and as a potential alternative to synthetic fertilizers.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1734 - 1745"},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Sensor Placement for Subsurface Drip Irrigation in Sugarcane Using HYDRUS Simulations","authors":"Amina Raheja,&nbsp;Sunil Garg,&nbsp;Pooja Goyal,&nbsp;Rakesh Sharda","doi":"10.1007/s40003-026-01008-z","DOIUrl":"10.1007/s40003-026-01008-z","url":null,"abstract":"<div><p>Through this study, we aim to identify the precise position for the placement of soil moisture sensor, representative of the entire root zone in case of sub-surface drip irrigated (SDI) sugarcane. The sugarcane crop was raised in sandy-loam textured soil under SDI with drip laterals placed at varying sub-surface depths i.e. 20 cm, 25 cm, and 30 cm) from the soil surface, moisture readings were taken through gravimetric method during the initial crop growth period of 43 days to calibrate and validate the HYDRUS-2D model. The wetting pattern was observed across 12 nodes covering the 4 vertical depths i.e. 10 cm above the drip depth, at the drip depth and 20 and 40 cm below the drip depth and 3 lateral positions i.e. 10, 20 and 30 cm away from the dripper. The calibrated model was then used to test its accuracy at various nodes for the rest of the crop growth season. The statistical analysis between observed and simulated moisture levels at different lateral depths yielded promising a coefficient of determination (R²) ranging from 0.76 to 0.85, Root Mean Squared Error between 0.004 and 0.015, Relative Absolute Error from 0.43 to 0.90, and Mean Absolute Percentage Error spanning 3.48 to 8.67. Analysis of moisture distribution post-irrigation revealed that deeper emitter depths (25 cm and 30 cm) exhibited higher moisture retention after 24 h, which particularly benefits deep-rooted crops and causes lower evaporation losses. Maximum moisture variation was observed at node 5, where the volumetric moisture content ranged between 0.20 and 0.24 cm³/cm³ at 1 h to 0.16–0.18, 0.14–0.15, 0.12–0.13 and 0.11–0.12 cm³/cm³ at 4, 8, 16 and 24 h respectively after irrigation for different subsurface drip depths. Based on the observations as well as simulated wetting patterns, it was suggested that a peripheral distance of 10 cm from the emitter captures the maximum soil moisture variation and thus, is optimal for the placement of moisture sensor for real-time moisture sensing and irrigation scheduling irrespective of the subsurface lateral depth. The HYDRUS-2D model demonstrated precision in simulating moisture profiles, emphasizing its critical role for sensor placement in optimizing irrigation.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1760 - 1773"},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy and Carbon Footprints with Operational Cost Analysis of Various Paddy Straw Management Machinery in North-Western India","authors":"Swapnil Choudhary,&nbsp;Ganesh Upadhyay,&nbsp;Neeraj Kumar,&nbsp;Naresh Sihag,&nbsp;Bharat Patel,&nbsp;Vijaya Rani","doi":"10.1007/s40003-026-01010-5","DOIUrl":"10.1007/s40003-026-01010-5","url":null,"abstract":"<div><p>Managing paddy straw is a significant challenge in north-western India due to the large residue generated annually from rice cultivation. This study was undertaken to evaluate energy and carbon footprints with economic analysis of various paddy straw management practices being followed in this region. The research, carried out over three rice harvest seasons (2022–2024), aimed to assess 13 different in-situ and ex-situ practices used for straw management. The in-situ management was further categorized into surface retention, partial, and complete incorporation. The results indicate that surface retention, particularly through Zero-till and Happy seeder machines, offers the most energy-efficient and cost-effective solutions, significantly reducing both operational costs and carbon emissions compared to straw incorporation machinery. The Zero-till drill practice, was the most energy-efficient and cost-effective, with the lowest energy consumption (399 MJ/ha), carbon emissions (5 kg-CE/ha), and operational cost (15.14 $/ha). In contrast, complete incorporation, such as with the Mulcher + Plough + Rotavator + Zero-till drill, resulted in highest energy use (3460 MJ/ha), carbon emissions (45 kg-CE/ha), and cost (117.59 $/ha). Super seeder provided a more efficient alternative with moderate energy consumption (1709 MJ/ha) and lower emissions (22 kg-CE/ha, 72 kg-CO₂e/ha). Partial incorporation using the Smart seeder offered a balanced approach, reducing energy and emissions while maintaining lower costs. The results indicate that surface retention and partial incorporation practices are the most sustainable approaches in terms of environmental and economic performance, while straw incorporation, although beneficial for soil fertility, come with higher energy demands, carbon emissions, and operational costs.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1774 - 1786"},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can AI-Based Crop Health Monitoring and Predictive Analytics Attain Sustainable Crop Production?","authors":"Ruchi Mittal,&nbsp;Megha Bhushan","doi":"10.1007/s40003-026-01007-0","DOIUrl":"10.1007/s40003-026-01007-0","url":null,"abstract":"<div><p>Sustainable agriculture is critical towards providing food security in the world and at the same time dealing with environmental degradation as well as shortages of resources. The loss of soil biodiversity, an increased resistance of pests and pathogens, and general decrease in crop yield have been contributed by traditional farming methods especially excessive use of agrochemicals. The deployment of cloud computing and remote sensing through the combination of artificial intelligence (AI) has allowed the expansion and scope of smart agriculture to reach cost-effective and responsive solutions to various farming settings. Nevertheless, the existing literature does not usually consider the potential of these technologies combined and does not provide a comprehensive approach to the implementation of these technologies in the synergy of their application. This review carries out extensive discussion of AI-based sustainable crop production by combining cloud computing and remote sensors. It discusses how smart sensors, satellite and aerial imaging platforms and cloud-based data infrastructures play a vital role in the development of crop health monitoring and predictive analytics. The major issues such as the heterogeneity of data, false positives, and the interpretability of the AI models are discussed critically. The areas of future research are also proposed to aid in creating multi-modal, robust, and interpretable AI systems that can propel sustainable, intelligent, and resilient agricultural ecosystems.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1469 - 1481"},"PeriodicalIF":1.5,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40003-026-01007-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Throughput Phenotyping of Faba Bean Crop Using Remote Sensing Technologies and Data Analytics: A Systematic Assessment of Status and Trends Over Past Decade","authors":"Pius Jjagwe,&nbsp;Abhilash K. Chandel,&nbsp;Maria Balota","doi":"10.1007/s40003-026-01009-y","DOIUrl":"10.1007/s40003-026-01009-y","url":null,"abstract":"<div><p>Faba bean (<i>Vicia faba</i> L.) is a widely cultivated legume in temperate regions, valued for human consumption, animal feed, hay production, and as a cover crop. Improving faba bean productivity requires accurate characterization of morphological and physiological traits that govern crop performance and yield. Although conventional phenotyping methods are available, they are often constrained by high cost, limited accuracy, and insufficient spatial and temporal coverage. In recent years, high-throughput phenotyping (HTP) approaches have shown potential to overcome these limitations. HTP integrates sensors, unoccupied aerial and ground vehicles, and imaging systems to enable rapid, and non-destructive monitoring of crop traits at high spatiotemporal resolution. Despite increasing adoption of HTP, no study has comprehensively compared and synthesized these methods for faba beans, therefore is the goal of this study with emphasis on advanced sensing and data analytics including machine learning (ML) and deep learning (DL). A systematic evaluation of 24 peer-reviewed articles from an initial pool of 381 publications between 2015 and 2025, identified research trends, performance benchmarks, and integration challenges with HTP-based faba bean characterization. Substantial increase in faba bean HTP studies has been noted after 2021, with ML approaches dominating current applications (37.5%). Most studies have relied on small datasets, single-season experiments, and limited environmental variability, restricting model robustness and scalability. Such limitations, research gaps, and future directions are also outlined to support reliable, and scalable phenotyping for improved faba bean production.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1482 - 1496"},"PeriodicalIF":1.5,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40003-026-01009-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of PGPB Consortia to Reduce Nitrogen Fertilization in Oilseed Rape (Brassica Napus) Under Field Conditions","authors":"Jakub Dobrzyński,&nbsp;Zuzanna Jakubowska,&nbsp;Iryna Kulkova,&nbsp;Piotr Nowotnik,&nbsp;Aleksandra Naziębło,&nbsp;Adrianna Antosik,&nbsp;Monika Sitarek-Andrzejczyk,&nbsp;Kamila Kaźmierczak-Benec,&nbsp;Łukasz Rzadkiewa,&nbsp;Magdalena Szpytma,&nbsp;Barbara Wróbel","doi":"10.1007/s40003-026-01006-1","DOIUrl":"10.1007/s40003-026-01006-1","url":null,"abstract":"<div><p>Oilseed rape (<i>Brassica napus L</i>.) is a globally important crop, but its high nitrogen (N) demand raises environmental concerns. Plant growth-promoting bacteria (PGPB) may offer a sustainable alternative to reduce mineral fertilization while maintaining yield and seed quality. The main aim of this study is to evaluate the potential of two bacterial consortia: P1A (<i>Pseudomonas</i> sp. G31 + <i>Azotobacter</i> sp. PBC2) and P2A (<i>Pseudomonas</i> sp. KR227 + <i>Azotobacte</i>r sp. PBC1) to enable a 30% reduction in N fertilization under field conditions in temperate transitional climate (Poland). The experiment included treatments with full nitrogen (100%N), reduced nitrogen fertilization (70%N) combined with bacterial consortia, and an uninoculated control. For the determination of soil, plant, and seed parameters, spectrophotometric, chromatographic, and standard analytical methods were applied. Dehydrogenase activity was significantly enhanced in soils treated with 70% N + P1A, while chlorophyll (<i>a</i> + <i>b</i>) content in plant leaves reached its highest levels under full nitrogen fertilization and remained elevated in 70%N + PGPB treatments compared to uninoculated control. Primarily results showed that 70%N + bacterial consortia achieved slightly higher seed yield and thousand-seed weight (TSW) compared to control and full N fertilization (100% N), with TSW significantly higher than the control. Seed quality parameters - oil content, fatty acid profile, and NPK levels - remained largely unaffected by fertilization strategy, suggesting that PGPB can sustain seed quality even with reduced N inputs. In addition, soil inoculation with P2A consortium counteracted the acidification caused by N fertilizer. These findings demonstrate that integrating PGPB with 70%N fertilization maintains productivity while aligning with sustainable agriculture goals, offering a viable strategy to lower synthetic N use in oilseed rape cultivation.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":"15 3","pages":"1746 - 1759"},"PeriodicalIF":1.5,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40003-026-01006-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148903560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}