Groundnut (Arachis hypogaea L.) is one of the most important oilseed crops cultivated in tropical and subtropical regions, contributing significantly to food security, edible oil production and rural livelihoods. It contains about 45-50% oil and 25-30% protein, making it a nutritionally rich crop with high economic value. Globally, groundnut production is affected by several biotic and abiotic stresses, among which diseases caused by soil-borne pathogens are particularly destructive (Deepika et al., 2025).
       
Among these, stem rot and seed rot caused by Sclerotium rolfsii Sacc. (syn. Athelia rolfsii) represent major constraints in groundnut cultivation across diverse agro-climatic regions. The pathogen is widely distributed in tropical and subtropical regions and is capable of infecting more than 500 plant species, highlighting its ecological adaptability and survival potential (Punja, 1985; Deepika et al., 2025). Stem rot is considered one of the most economically important diseases of groundnut, causing severe yield and quality losses worldwide (Mehan et al., 1994; Vamshi et al., 2025). Yield losses due to this disease generally range from 15-70%, but under favourable environmental conditions, losses may exceed 80% (Akgul et al., 2011).
       
The disease manifests at multiple growth stages, beginning with seed rot and seedling blight and progressing to stem rot and pod rot in later stages. Characteristic symptoms include yellowing, wilting, necrosis and the formation of white mycelial mats with mustard-like sclerotia at the collar region of infected plants (Ayyandurai et al., 2022; Deepika et al., 2025). The pathogen survives in soil as sclerotia for extended periods, enabling it to persist across seasons and making management particularly challenging (Bosamia et al., 2020). Environmental factors such as high temperature (25-30°C), moderate soil moisture and sandy soils further favor disease development and epidemic outbreaks (Deepika et al., 2025).
       
Management of S. rolfsii is difficult due to its soil-borne nature, wide host range and long-term survival structures. Conventional management strategies relying solely on fungicides have shown effectiveness but are often associated with environmental hazards, development of resistant pathogen populations and disruption of soil microbial balance (Bonanomi et al., 2018; Meena et al., 2024). Biological control approaches using antagonistic microorganisms such as Trichoderma spp., Pseudomonas fluorescens and Bacillus subtilis have shown promising results in suppressing the pathogen and improving plant growth (Ganesan, 1987; Jacob et al., 2018; Meena et al., 2024; Vamshi et al., 2025).
       
Recent studies emphasize the importance of integrated disease management (IDM) strategies combining chemical, biological and organic approaches for effective control of stem rot. Integration of bioagents with organic amendments such as farmyard manure or vermicompost enhances microbial activity, improves soil health and increases disease suppression efficiency (Nathawat et al., 2025; Vamshi et al., 2025; Hotkar et al., 2026). Such approaches not only reduce disease incidence but also improve yield and sustainability of groundnut production systems (Vamshi et al., 2025).
       
Despite the availability of various management options, variability in pathogen populations, environmental conditions and cropping systems necessitates location-specific evaluation of integrated management strategies. Moreover, limited information is available on the combined management of seed rot and stem rot under field conditions across multiple seasons. Therefore, the present investigation was undertaken to evaluate the effectiveness of different chemical and biological treatments, individually and in combination, for the management of seed rot and stem rot diseases of groundnut under field conditions.

Experimental site and design
 
The field experiment was conducted during Kharif 2024 and 2025 at Main Agricultural Research Station (MARS), University of Agricultural Sciences, Dharwad, Karnataka, India under natural field conditions (sick plot). The experimental site was characterized by typical groundnut-growing agro-climatic conditions, conducive for the development of soil-borne diseases, particularly stem rot caused by Sclerotium rolfsii. The experiment was laid out in a randomized block design (RBD) with nine treatments and three replications. Groundnut was grown following recommended agronomic practices, except for plant protection measures specific to the treatments under study. Standard spacing and crop management practices were maintained uniformly across all treatments.
 
Treatments
 
The treatments consisted of chemical fungicides, bioagents and their combinations, including enriched organic amendments. The details of treatments are presented in Table 1.


 
Preparation and application of bioagents
 
Bioagents (Trichoderma harzianum Rifai and Pseudomonas fluorescens-collected from Institute of organic farming, UAS, Dharwad, Karnataka) were applied as seed treatment by coating seeds uniformly at the specified dose prior to sowing. For enriched FYM treatments, the respective bioagents were mixed thoroughly with well-decomposed farmyard manure and incubated under shade for adequate multiplication before application to soil at sowing.
 
Germination percentage
 
Seed germination was recorded by counting the number of emerged seedlings in each treatment and expressed as percentage.
 
Disease assessment
 
Observations on stem rot incidence (%) were recorded at appropriate crop growth stages by counting the total number of plants and the number of infected plants in each plot. Disease incidence was calculated using the following formula:

 
Yield parameters
 
At harvest, pod yield and haulm yield were recorded from each plot and converted into kg/ha. The pooled data of two seasons were used for analysis and interpretation.
 
Economic analysis
 
Economic parameters such as cost of cultivation, gross returns, net returns and benefit–cost (B:C) ratio were calculated based on prevailing market prices of inputs and produce. Cost and return analysis were conducted following the procedures outlined by Kushwah et al. (2017) and Bhupender et al. (2020). The B:C ratio was computed to determine the economic feasibility of different treatments.

 
Statistical analysis
 
The experimental data obtained from two seasons were subjected to statistical analysis using analysis of variance (ANOVA) appropriate for a randomized block design as described by Panse and Sukhatme (1985). Percentage data on disease incidence were subjected to angular transformation prior to analysis. Treatment means were compared using the critical difference (CD) at 5% level of significance. In addition, correlation, regression and path coefficient analyses were performed to assess relationships among variables and to quantify direct and indirect effects on yield. Multivariate analyses, including principal component analysis (PCA) and cluster analysis, were carried out to understand treatment grouping and trait interactions. All analyses were performed using standard statistical procedures.

Effect of treatments on germination
 
Significant differences among treatments were observed in seed germination across two seasons (Table 2). The highest germination was recorded in T₇ (Seed treatment with (Thiophanate Methyl 45% + Pyraclostrobin 5%) FS @ 2.0 ml/kg seeds) (94.50%), followed by T₈ (Seed treatment with (Imidacloprid 18.5% + Hexaconazole 1.5% FS) 50 FS @ 1.0 ml/kg seeds)  (92.35%) and T₁ (Seed treatment with (Carboxin 37.5 % + Thiram37.5 %) 75WP @ 3.0 g/kg of seeds + Soil drenching with Tebuconazole 25.9EC @ 2.0 ml/litre at 60DAS) (90.51%), indicating the superiority of fungicidal treatments in improving seed health. Bioagent treatments also enhanced germination compared to control, with T₄- (Seed treatment with Trichoderma harzianum @ 10.0 g/kg seeds: POP check) (88.89%) and T₅ (Seed treatment with Trichoderma harzianum @ 10.0 g/kg seeds + FYM enriched with Trichoderma harzianum @ 2.5 kg in 250 kg FYM) (88.35%) showing appreciable improvement. The lowest germination was recorded in the inoculated control (80.33%), confirming the detrimental effect of pathogen inoculation on seedling establishment. Improved germination and reduced stem rot incidence under fungicidal treatments indicate effective suppression of seed- and soil-borne inoculum during early crop stages, which is critical for limiting Sclerotium rolfsii infection and ensuring better crop establishment (Mehan et al., 1994; Akgul et al., 2011; Meena et al., 2024).


 
Effect on stem rot incidence
 
All treatments significantly reduced stem rot incidence compared to the control (Table 2 and Fig 1a). The lowest pooled disease incidence was recorded in T₇ -Seed treatment with (Thiophanate Methyl 45% + Pyraclostrobin 5%) FS @ 2.0 ml/kg seeds (3.43%), followed by T₈- Seed treatment with (Imidacloprid 18.5% + Hexaconazole 1.5% FS) 50 FS @ 1.0 ml/kg seeds (4.27%) and T₁- Seed treatment with (Carboxin 37.5 % + Thiram37.5 %) 75WP @ 3.0 g/kg of seeds + Soil drenching with Tebuconazole  25.9EC @ 2.0 ml/litre at 60DAS (5.60%), demonstrating the higher efficacy of fungicidal treatments. Among bioagents, T₄- Seed treatment with Trichoderma harzianum @ 10.0 g/kg seeds + FYM enriched with Trichoderma harzianum @ 2.5 kg in 250 kg FYM (9.22%) and T₅ (Seed treatment with P. fluorescens @ 10.0 g/kg seeds + FYM enriched with P. fluorescens @ 2.5 kg in 250 kg FYM) (10.18%) were more effective than seed treatment alone, indicating the added benefit of FYM enrichment. The highest disease incidence was recorded in the control (21.38%), clearly indicating severe disease pressure under untreated conditions. The superior performance of thiophanate methyl + pyraclostrobin and imidacloprid + hexaconazole confirms their strong fungitoxic and systemic action against S. rolfsii, consistent with earlier reports demonstrating significant disease reduction through fungicidal seed treatments and integrated modules (Akgul et al., 2011; Hotkar et al., 2026; Vamshi et al., 2025). Among bio-based approaches, the enhanced efficacy of Trichoderma with FYM over seed treatment alone suggests improved rhizosphere competence and persistence of antagonists. Organic amendments are known to stimulate microbial activity and create a suppressive soil environment through mechanisms such as competition, antibiosis and induced systemic resistance (Ganesan, 1987; Bonanomi et al., 2018; Meena et al., 2024). Similar results have been reported on other crops such as chickpea (Basamma et al., 2021; Sangeeta et al., 2022).


 
Effect on pod and haulm yield
 
Pod yield varied significantly among treatments (Table 3), reflecting the impact of disease management on productivity. The highest pooled pod yield was recorded in T₇ (Seed treatment with (Thiophanate Methyl 45% + Pyraclostrobin 5%) FS @ 2.0 ml/kg seeds: 21.69 q/ha), followed by T₈ (Seed treatment with (Imidacloprid 18.5% + Hexaconazole 1.5% FS) 50 FS @ 1.0 ml/kg seeds: 20.52 q/ha) and T₁-Seed treatment with (Carboxin 37.5 % + Thiram37.5 %) 75WP @ 3.0 g/kg of seeds + Soil drenching with Tebuconazole 25.9EC @ 2.0 ml/litre at 60DAS (18.47 q/ha). Bioagent-based treatments also resulted in moderate yield improvement, with T₄ (Seed treatment with Trichoderma harzianum @ 10.0 g/kg seeds + FYM enriched with Trichoderma harzianum @ 2.5 kg in 250 kg FYM: 17.03 q/ha) outperforming T₂ (Seed treatment with Trichoderma harzianum @ 10.0 g/kg seeds) and T₃ (Seed treatment with P. fluorescens @ 10.0 g/kg seeds). The lowest yield was recorded in the control (11.62 q/ha), indicating substantial yield loss due to disease incidence. A similar trend was observed in haulm yield, where T₇ recorded the highest pooled haulm yield (24.42 q/ha), followed by T₈ (23.16 q/ha) and T₁ (21.10 q/ha). Bioagent treatments showed intermediate performance, while the control recorded the lowest haulm yield (15.27 q/ha), further confirming the adverse effect of disease on plant biomass. The strong reduction in disease incidence corresponded with increased pod and haulm yield, indicating a clear inverse relationship between disease severity and productivity, which has been widely reported in groundnut pathosystems (Punja, 1985; Bosamia et al., 2020; Deepika et al., 2025).


 
Economic analysis
 
Economic evaluation (Table 3) revealed that T₁: Seed treatment with (Carboxin 37.5 % + Thiram37.5 % ) 75WP @ 3.0 g/kg of seeds + Soil drenching with Tebuconazole 25.9EC @ 2.0 ml/litre at 60DAS recorded the highest benefit–cost ratio (2.31), followed by T₂ (Seed treatment with Trichoderma harzianum. @ 10.0 g/kg seeds; 2.04) and T₃ (Seed treatment with P. fluorescens @ 10.0 g/kg seeds: 1.95), indicating better economic feasibility of integrated and bioagent-based treatments despite slightly lower yields compared to fungicides. Treatments involving fungicides showed higher yields but relatively higher input costs. The lowest returns were recorded in the control, reflecting the economic loss associated with unmanaged disease conditions.
       
Although fungicides recorded maximum yield, bioagent-based and integrated treatments showed competitive economic returns due to lower input costs and sustained disease suppression. Recent studies emphasize that integrated disease management strategies combining chemical, biological and organic approaches provide more stable and sustainable control of soil-borne pathogens (Bonanomi et al., 2018;  Ayyandurai et al., 2023; Vamshi et al., 2025; Hotkar et al., 2026). Overall, the findings confirm that integration of fungicides with bioagents and organic amendments offers an effective and sustainable approach for managing stem rot and seed rot of groundnut under field conditions.
 
Correlation analysis
 
A strong and highly significant relationship was observed among disease incidence, yield and economic parameters (Fig 1b). Stem rot incidence exhibited a very strong negative correlation with germination (r = -0.98), pod yield (r = -0.96), haulm yield (r = -0.91) and B:C ratio (r = -0.99), indicating that increased disease severity drastically reduces plant establishment, productivity and profitability. Similar correlation patterns between disease severity and yield loss have been reported in groundnut and other crops (Punja, 1985; Bosamia et al., 2020; Meena et al., 2024). Germination showed a strong positive correlation with pod yield (r = 0.96) and B:C ratio (r = 0.98), suggesting that early-stage seed health plays a crucial role in determining final yield and economic returns. Similarly, pod yield was highly correlated with haulm yield (r = 0.98), reflecting uniform biomass accumulation under effective disease management. The near-perfect negative association between disease incidence and B: C ratio (r = -0.99) highlights that economic losses in groundnut are primarily driven by disease pressure. Overall, the results clearly indicate that disease suppression is the central determinant of yield and profitability, confirming the effectiveness of integrated treatments in improving crop performance.


 
Simple regression analysis (Disease vs Pod yield)
 
A strong negative linear relationship was observed between stem rot incidence and pod yield, indicating that disease severity is a major determinant of productivity (Fig. 2). The regression model suggests that each unit increase in disease incidence leads to a substantial decline in yield, highlighting the critical importance of effective disease management. The high coefficient of determination (R² > 0.90) confirms that variation in yield is largely explained by disease incidence. Slope of -0.53 indicates that for every 1% increase in disease, yield reduces by 0.53 q/ha. Such linear relationships between disease intensity and yield loss have been widely documented in soil-borne pathosystems (Akgul et al., 2011; Bosamia et al., 2020).


 
Equation
 
Pod yield = 22.04 - 0.53 × Disease incidence
 
Disease-yield loss model
 
A strong positive linear relationship was observed between stem rot incidence and relative yield loss, indicating that increasing disease severity significantly reduces crop productivity (Fig 3). The regression model showed that each unit increase in disease incidence resulted in a proportional increase in yield loss, with a high coefficient of determination (R² ≈ 0.92), confirming the strong influence of disease on yield reduction. This model quantitatively establishes stem rot as a major limiting factor in groundnut production.


 
Multiple regressions
 
Multiple regression analysis revealed that pod yield was strongly explained by the combined influence of germination, disease incidence, haulm yield and B:C ratio, with a very high coefficient of determination (R² = 0.993), indicating that 99.3% of the variability in yield was accounted for by these variables (Fig 4). The fitted model (Pod yield = -20.67 + 0.27 ×Germination + 0.005 × Disease + 0.60 × Haulm yield + 1.02 × B:C) indicated that haulm yield exerted the most significant positive effect on pod yield (p = 0.004), highlighting biomass production as the primary determinant of yield under disease-managed conditions. Germination showed a positive but moderate contribution, suggesting the importance of early crop establishment. Although disease incidence exhibited a negligible coefficient in the model, this is attributed to strong interrelationships among variables (multicollinearity), as disease effects were indirectly expressed through their influence on germination and yield components. The B:C ratio did not show a direct predictive role due to its dependence on yield. Overall, the results indicate that yield performance is predominantly governed by biomass accumulation and indirectly influenced by disease suppression and crop establishment. This suggests that disease impacts yield primarily through its influence on plant growth and development rather than direct yield reduction, which is consistent with findings of Meena et al., (2024) and Vamshi et al., (2025).


 
Equation
 
Pod yield =-20.67 + 0.27(Germination) + 0.005(Disease) + 0.60(Haulm yield) + 1.02(B:C)
 
PCA (Principal component analysis)
 
Principal component analysis (Fig 5) revealed that most of the variability among treatments was explained by the first principal component (PC1; 96.16%), indicating strong interdependence among measured traits. Positive loadings of germination, pod yield, haulm yield and B:C ratio on PC1, along with negative loading of disease incidence, clearly indicate that these variables are inversely related to disease severity.


       
Treatments with lower disease incidence were clustered on the positive side of PC1, associated with higher yield and economic returns, whereas the control treatment was distinctly separated due to higher disease pressure and lower performance. This pattern confirms that disease suppression is the primary factor governing treatment differentiation and crop productivity. Similar multivariate patterns have been reported in disease management studies, where yield and disease parameters cluster along opposite axes (Bosamia et al., 2020; Deepika et al., 2025).
 
Cluster analysis (Dendrogram)
 
Hierarchical cluster analysis grouped the treatments into distinct clusters based on their overall performance . High-performing treatments (T₇, T₈, T₁ and T₆) were clustered together, indicating similarity in terms of higher germination, lower disease incidence and superior yield. Moderate treatments (T₂, T₃, T₄ and T₅) formed a separate cluster, while the control (T₉) was distinctly separated, reflecting its poor performance. This clustering clearly demonstrates treatment differentiation and validates the superiority of integrated and fungicidal treatments. This clustering reflects treatment efficiency and supports the concept of integrated disease management, as reported by Hotkar et al., (2026) and Vamshi et al., (2025).

The stem rot significantly affects germination, plant growth, yield and economic returns in groundnut under field conditions. Effective disease management resulted in improved seedling establishment, reduced disease incidence and enhanced productivity. Among the treatments evaluated, T₇ (Seed treatment with (Thiophanate Methyl 45% + Pyraclostrobin 5%) FS @ 2.0 ml/kg seeds) and T₈ (Seed treatment with (Imidacloprid 18.5% + Hexaconazole 1.5% FS) 50 FS @ 1.0 ml/kg seeds) consistently recorded lower stem rot incidence, higher germination, superior pod and haulm yield and better economic returns, indicating their effectiveness under disease pressure. Correlation and regression analyses confirmed that disease incidence was negatively associated with yield and related parameters, establishing it as the primary limiting factor in crop productivity. The disease-yield loss model further quantified this relationship, indicating that even small increases in disease severity result in substantial yield loss. Multiple regression and path analysis revealed that haulm yield was the most influential factor contributing to pod yield, while the effect of disease was largely indirect through its influence on plant growth and development. Multivariate analyses, including PCA indicated strong interrelationships among germination, yield and economic traits, with disease incidence showing an opposite trend. Cluster analysis and combined performance index clearly differentiated treatments, identifying T₇ (Seed treatment with (Thiophanate Methyl 45% + Pyraclostrobin 5%) FS @ 2.0 ml/kg seeds), T₈ (Seed treatment with (Imidacloprid 18.5% + Hexaconazole 1.5% FS) 50 FS @ 1.0 ml/kg seeds) and T₁ (Seed treatment with (Carboxin 37.5 % + Thiram37.5 %) 75WP @ 3.0 g/kg of seeds + Soil drenching with Tebuconazole 25.9EC @ 2.0 ml/litre at 60DAS) as superior treatments. In contrast, the inoculated control was statistically separated into an independent cluster, exhibiting significantly higher stem rot incidence and significantly lower yield and economic parameters (P≤ 0.05) compared to all treated plots, confirming its inferior performance under disease pressure. Overall, the study highlights that effective management of stem rot is essential for improving yield and profitability in groundnut. Integrated management approaches combining chemical and biological strategies (Trichoderma sp. seed treatment @10 g/kg seeds and enriched FYM with Trichoderma @ 2.5 kg/250kg FYM) proved more effective and sustainable compared to individual methods. Multivariate and regression-based analyses consistently indicated that disease suppression is the primary determinant of yield and economic performance. The findings provide a comprehensive understanding of disease-yield relationships and offer a scientifically validated basis for selecting effective management practices under field conditions.

The authors acknowledge the facility extended by Department of Plant Pathology AC, Dharwad for isolation and mass multiplication of Sclerotium rolfsii.
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
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The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.