Kinnow mandarin production in arid regions is constrained by water-deficit and micronutrient imbalances, particularly iron (Fe) and zinc (Zn). This study evaluated the effects of Fe and Zn deficiency (Fe- and Zn-) and toxicity (Fe + and Zn+) under water-deficit conditions. Eight treatments, including individual and combined Fe/Zn deficiencies and toxicities along with control were assessed under pot conditions. Results revealed that water-deficit combined with Fe and Zn deficiency significantly reduced plant growth, biomass, leaf area, relative water content and chlorophyll concentrations. These effects were more severe under combined deficiencies compared to their individual deficiencies. In contrast, Fe and Zn toxicity enhanced vegetative traits such as leaf area and sprout length but induced abnormal morphogenesis, such as enlarged thorns and water sprouts. Root traits also showed sensitivity to nutrient treatments. Root length and root-shoot ratio increased under Zn toxicity, while specific root length was more severely affected by micronutrients deficiency. Leaf analysis exhibited treatment specific variations, indicating disrupted uptake. Nitrogen and potassium decreased under Fe-Zn deficiency, while phosphorus increased under Zn deficiency but decreased under Zn toxicity. The findings of the study revealed that Fe and Zn status influenced plant performance and nutrient balance under water-deficit conditions, highlighting the importance of balanced micronutrients management in citrus cultivation.

IntroductionLivelihood diversification through appropriate cropping and farming systems plays a crucial role in enhancing income security among rural households in the Jammu region. This study aims to assess the contribution of different cropping and farming systems to livelihood diversification of rural farmers.MethodsA multistage sampling technique was employed to select the sample, and a total of 480 households were randomly chosen for the study. A quantitative approach using a structured questionnaire was adopted for data collection. Analytical tools such as the Cobb–Douglas production function and tabular analysis were used to evaluate efficiency parameters and system performance.ResultsThe study identified 11 predominant farming systems in Jammu, mainly dominated by cereal-based and livestock-based activities. Results from the production function indicated that area under cereals and livestock enterprises had a significant positive influence on farm output. Among the systems analyzed, the Fruits + Livestock + Maize + Vegetables system was found to be the most remunerative in terms of total farm income.DiscussionThe findings highlight that limited access to productive assets compels farmers to rely heavily on non-farm activities for income. Enhancing awareness of improved technologies and improving farmers’ access to credit can significantly boost farm productivity and income stability. Strengthening diversified farming systems is essential for sustainable livelihood improvement in the region.

The sugarcane (Saccharum officinarum L.)-wheat (Triticum aestivum L.) cropping system has caused significant challenges, including groundwater depletion and soil degradation, necessitating the adoption of Integrated Farming Systems (IFS) for diversification and sustainability. The study was carried out during 2021–2024 at ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut, Uttar Pradesh to evaluate an IFS model designed for small and marginal farmers. Spanning 1.38 ha, the model integrates crops, dairy, horticulture, aquaculture, mushroom cultivation, and boundary plantations, emphasizing resource recycling and economic viability. The model demonstrated a high sugarcane equivalent yield (264.1 t/year), with contributions from crops (43%), dairy (29%), horticulture (15%), and fisheries (7%), achieving net annual returns of ₹5,50,090 and a benefit-cost ratio of 3.42. The model also generated 34% higher man-days (774) of annual employment, reducing seasonal unemployment. Components like fisheries, mushroom cultivation, and boundary plantations contributed significantly to income and ecological sustainability. The IFS approach enhanced food and nutritional security by fulfilling household needs and producing marketable surpluses of cereals, fruits, milk, fish, and mushrooms with a marketable surpluses of cereals (92.8%), fruits (94.6%), and milk (93.7%). This comprehensive system offers a sustainable solution to monocropping issues, boosting income and resilience for farm households.

Predicting crop yields, particularly for high-value horticultural crops such as mangos, is critical for optimizing horticultural practices, particularly given the complexity of high-dimensional, nonlinear interactions between agronomic and environmental factors. This research develops an intelligent predictive framework using Artificial Neural Networks (ANNs) and deep learning algorithms to address the challenges of data complexity and temporal variability. The ANN architecture consists of an input layer with eight neurons representing critical agronomic inputs, a hidden layer of ten neurons with a ReLU activation function for non-linearity and a single linear output neuron for yield prediction. The problem is mathematically framed as minimizing the loss function to capture intricate temporal and nonlinear relationships affecting yield, and the model is trained using the back-propagation algorithm. The framework compares feedforward neural networks, recurrent neural networks (RNN), and long short-term memory (LSTM) networks to approximate the nonlinear mappings between inputs and yield. The framework was trained and evaluated using an 80:20 train-test split, achieving a prediction accuracy of 78%, with LSTM outperforming Feedforward Neural Networks (FNNs) and Recurrent Neural Networks (RNNs). The evaluation metrics used include Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2 score, ensuring the reliability of the predictions. The study introduces a desktop GUI user-friendly application developed in a Python (spyder) environment, libraries for yield predictions, and an android mobile app for management practices for farmers and stakeholders. These tools bridge advanced AI methodologies and practical agricultural needs, promoting data-driven decision-making in sustainable farming practices.. KEYWORDS :Predictive analytics, Precision agriculture, Artificial neural networks (ANN), Long short-term memory (LSTM).

This study characterised the variability among 15 Sclerotium rolfsii isolates collected from different host plants by analysing their morphological characteristics, oxalic acid production, mycelial compatibility, and pathogenicity. The isolates exhibited diverse colony morphologies, with radial growth rates ranging from 22.7 to 30.0 mm/day. Colonies were white to off-white in colour and displayed either compact or fluffy growth patterns. Sclerotial production varied significantly, with the majority of isolates producing between 400 and 700, whereas a few formed 100-200 sclerotia per plate. Sclerotia were predominantly spherical, measuring 0.50-2.57 mm in diameter, although isolates SR1 and SR4 produced irregular shapes. Mycelial compatibility testing of 105 pairings revealed 85 compatible interactions and 20 pairings showing antagonism. Based on mycelial interactions, all isolates were grouped into five mycelial compatibility groups (MCGs A-E). Most isolates produced oxalic acid, indicated by a colour shift from blue to yellow in bromophenol blue-amended medium. Oxalic acid production levels correlated positively with both increased mycelial biomass and a reduction in medium pH. The highest oxalic acid concentration (25.55 mM) was recorded for isolate SR15 from Arachis hypogaea. Pathogenicity assays confirmed that all isolates were virulent. Detached leaf assays revealed differences in lesion size and infection timing, whereas pot trials on potato plants showed that isolates from A. hypogaea were the most pathogenic, causing the greatest reduction in tuber weight. A strong positive correlation was observed between oxalic acid production and pathogenicity across isolates.

The study was carried out during 2021–2024 at ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut, Uttar Pradesh to evaluate the impact of Integrated Organic Farming System (IOFS) and Integrated Farming System (IFS) on soil biological properties namely microbial population, enzyme activities, and glomalin levels across cereal, vegetable, fruit and fodder crop systems. IOFS consistently demonstrated superior performance with respect to soil health indicators as compared to IFS. Higher microbial populations (bacteria, fungi, and actinomycetes) were observed under IOFS, particularly in vegetable crops. Soil under cereal crops (food system) showed around 41% increase in bacterial population in IOFS model compared to IFS model. Similarly soils under vegetable system showed 32% increase in fungal population in IOFS model. Enzyme activities, including dehydrogenase, β-glucosidase, urease, and alkaline phosphatase, were significantly higher in IOFS, with notable improvements in fruit and vegetable crops. Fodder system showed greater improvement in dehydrogenase (36.8%) and β-glucosidase (34.7%) under IOFS as compared to IFS. IOFS also showed increased levels of Easily Extractable Glomalin (EEG) and Total Glomalin (TG). Vegetable system showed 32% and 14% improvement in EEG and TG respectively, indicating enhanced arbuscular mycorrhizal fungi activity and potential for carbon and nitrogen sequestration. These findings highlight the benefits of organic nutrient and pest management practices in promoting soil fertility and sustainability.

An experiment was conducted in the Upper Gangetic Plain zone to study the effects of mustard oilcake (MC) application in combination with farm yard manure (FYM) and vermicompost (VC) on wheat growth, yield, and economics in organic farming. Results showed that mustard oilcake significantly improved wheat growth, yield attributes, and productivity. Plant height and tiller number increased by 20.1-44.8% and 22.8-64.9%, respectively, compared to the control. Mustard oilcake application also increased spike weight, number of grains per spike, and for MC treatments 1000-grain weight in wheat. Grain yield was highest with inorganic management, followed by mustard oilcake + biofertilizer, and the lowest in control. Mustard oilcake application improved wheat grain yield by 31.0-136.5% compared to the control. The treatment with a 50% recommended dose of nutrients (RDN) through FYM + 50% RDN through MC + biofertilizer showed the highest net return and benefit-cost ratio. Positive correlations were found between different growth and yield parameters of wheat with mustard oilcake application. Results inferred that integrating mustard oilcake with bulky organic manure can be an effective strategy to improve productivity and profitability in organic farming in the Upper Gangetic Plain zone.

Soil biological characteristics are drastically altered by land degradation. Degradation may reduce the number of microorganisms in the soil. Multiple activities and services provided by grassland ecosystems are impacted by land use change because of the resulting shifts in plant community composition and soil characteristics. A large body of research has examined the geographical and temporal dynamics of bacterial community structure and bacterial responses to human management in grassland ecosystems. As one of the most consequential environmental shifts occurring today, land use modification can affect microbial communities through modifying soil environmental parameters, nutritional conditions, and biological interactions. Whereas, soil microbes play crucial roles in nutrient cycling, organic matter decomposition, disease suppression, and overall soil health. Land degradation practices, such as deforestation, overgrazing, intensive agriculture, and improper land management, can disrupt the balance and diversity of soil microbial communities, leading to negative consequences for ecosystem functioning. To mitigate the negative effects of land degradation on soil microbial communities, sustainable land management practices should be adopted. These practices include soil conservation, reforestation, crop rotation, reduced tillage, organic farming methods, and proper nutrient management. By promoting soil health and restoring ecosystem processes, these approaches can help rebuild and maintain diverse and functional soil microbial communities.The purpose of this review is twofold: (1) to assess the diversity and composition of soil microorganisms in response to distinct land-use scenarios; and (2) to compare the relative importance of environmental factors driving these variations

IntroductionOver the years, smallholder farmers have faced more vulnerability to risk and uncertainty in India due to their dependence on cereal crops. One way to reduce this risk is through diversified agriculture, integrating different practices for efficient resource utilization, and adopting a farming systems approach. An integrated farming system (IFS) is one such technique that provides year-round income from different components of enterprises. However, the decision to adopt IFS may be determined by several characteristics of farmers, which needs to be delineated through impact analysis to harness the benefits of a systems approach.MethodsThis study analyzes the economic effects of integrated farming systems and assesses their determinants, as well as the dietary diversity patterns of farmers in two states of southern India, i.e., Kerala and Tamil Nadu. A multistage sampling technique was used to obtain cross-sectional data from 367 farmers randomly chosen from one district in Kerala and two districts in Tamil Nadu. The participants have Crop + Horticulture + Animal husbandry (45.45%) as their major system, whereas non-participants have Crop + Animal husbandry (44.35%) as their predominant system. Coarsened exact matching and logit regression methods were used to evaluate the economic impacts of IFS and its influencing factors.ResultsThe findings of the study indicate that age, education, livestock holding, access to credit, and plantation area have a positive and significant effect on participation by farmers in the program. The matching results show that adoption of IFS resulted in a significant economic impact, generating an additional gross income of Rs. 36,165 ha−1 and a net income of Rs. 35,852 ha−1 and improving the dietary diversity of farm households by 8.6% as compared to non-adopters.DiscussionThis study suggests that IFS is a promising approach for improving farmers' livelihoods, economic gains, and nutritional security. Therefore, the integrated farming systems models need to be upscaled through the convergence of government schemes in other regions of India to support smallholder farmers' farming.

The injudicious use of synthetic agri-inputs has adversely influenced the soil fertility in tropical and subtropical agriculture with depleted reserves of carbon (C) and nitrogen (N) Assessing dynamics of these nutrient elements and their impacts on crop productivity in irrigated semi-arid cropping systems are immensely influenced by the climate induced crop nutrient responses. Therefore, to comprehend the fundamental mechanisms that govern the carbon and nitrogen dynamics in diverse nutrient management systems is crucial for understanding the effects of climate-induced variations in nutrient availability on crop yield. In this study, surface soil (0–15 cm) samples were collected from four different sources: 100

ContextAgricultural field experiments are costly and time-consuming, and their site-specific nature limits their ability to capture spatial and temporal variability. This hinders the transfer of crop management information across different locations, impeding effective agricultural decision-making. Further, accurate estimates of the benefits and risks of alternative crop and nutrient management options are crucial for effective decision-making in agriculture.ObjectiveThe objective of this study was to utilize the Crop Environment Resource Synthesis CERES-Wheat model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based wheat system. The study aimed to calibrate the model using data from a field experiment conducted during the 2019-20-2020-21 growing seasons and evaluation it with independent data from the year 2021–22.MethodCrop simulation models, such as the Crop Environment Resource Synthesis CERES-Wheat (DSSAT v 4.8), may provide valuable insights into crop growth and nitrogen dynamics, enabling decision makers to understand and manage production risk more effectively.Therefore, the present study employed the CERES-Wheat (DSSAT v 4.8) model and calibrated it using field data, including plant phenological phases, leaf area index, aboveground biomass, and grain yield from the 2019-20-2020-21 growing seasons. An independent dataset from the year 2021–22 was used for model evaluation. The model was used to investigate the relationship between growing degree days (GDD), temperature, nitrate and ammonical concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on wheat yields. The experimental site is situated at ICAR-Indian Agricultural Research Institute (IARI), New Delhi, representing Indian Trans-Gangetic Plains Zone (28o 40’N latitude, 77o 11’E longitude and an altitude of 228 m above sea level). The treatments consist of four nitrogen management options, viz., N0 (zero nitrogen), N150 (150 kg N ha−1 through urea), GS (Green seeker based urea application) and USG (urea super granules @150 kg N ha−1) in two contrasting tillage systems, i.e., CA-based zero tillage (ZT) and conventional tillage (CT).ResultThe outcomes exhibited favorable agreement between the model’s simulations and the observed data for crop phenology (With less than 2 days variation in 50% onset of flowering), grain and biomass yield (Root mean square error; RMSE 336 kg ha−1 and 649 kg ha−1, respectively), and leaf area index (LAI) (RMSE 0.28 & normalized RMSE; nRMSE 6.69%). The model effectively captured the nitrate-N (NO3−-N) dynamics in the soil profile, exhibiting a remarkable concordance with observed data, as evident from its low RMSE = 12.39 kg ha−1 and nRMSE = 13.69%. Moreover, as it successfully simulated the N balance in the production system, the nitrate leaching and ammonia volatilization pattern as described by the model are highly useful to understand these critical phenomena under both conventional tillage (CT) and CA-based Zero Tillage (ZT) treatments.ConclusionThe study concludes that the DSSAT-CERES-Wheat model has significant potential to assess the impacts of tillage and nitrogen management practices on crop growth, yield, and soil nitrogen dynamics in the western Indo-Gangetic Plains (IGP) region. By providing reliable forecasts within the growing season, this modeling approach can facilitate better planning and more efficient resource management.Future implicationsThe successful implementation of the DSSAT-CERES-Wheat model in this study highlights its applicability in assessing crop performance and soil dynamics. Future research should focus on expanding the model’s capabilities by reducing its sensitivity to initial soil nitrogen levels to refine its predictions further. Moreover, the model’s integration with decision support systems and real-time data can enhance its usefulness in aiding agricultural decision-making and supporting sustainable crop management practices.

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

Field experimentation was conducted to evaluate the comparative performance of integrated crop management, organic management and natural farming on crop growth, productivity, profitability and soil health under basmati rice-wheat system in Upper Indo-Gangetic Plains. Treatments comprised of different management practices viz. integrated crop management (ICM), organic management, natural farming (NF) and control (no nutrient) were used in experimentation. Plant height, number of effective tillers, SPAD meter reading, panicle weight, filled grains/panicle, fertility percentage and 1000-grains weight of basmati rice and wheat were observed highest under ICM followed by organic management. A significant reduction in growth and yield attributes was recorded under NF as compared to ICM and organic management. Grain yield of basmati rice was reduced by 15.2%, 51.2% and 53.9% under organic management, NF and control as compared to ICM, respectively. Similarly, 49.5%, 58.6%, and 63.8% reduction in grain yield of wheat was recorded under organic management, NF and control as compared to ICM, respectively. In comparison to ICM, system rice equivalent yield (REY) was reduced by 32.6%, 55.0%, and 59.0% under organic management, NF and control, respectively. Further, net return was 44.1% and 67.2% lower under organic management and NF as compared to ICM, respectively. Highest soil organic carbon (0.60%), available N, P, and K were found in organic management. Significantly highest soil microbial population, glomalin content and different soil enzyme activities were recorded under organic management. Overall, the integrated crop management provided balanced and continuous supply of the nutrient that resulted in higher productivity and profitability of basmati rice-wheat system.

The present study was aimed to characterize the status of organic and conventional farming practices and their impacts on livelihoods in the district of Jammu. A total of 120 farmers were selected using multistage random sampling with 60 practicing organic farming and 60 practicing conventional farming. The impact of organic farming on income generation and employment creation among farmers was evaluated using the matching technique. The results showed that the major farming systems identified in the region were C-H-D and C-D systems. The impact assessment using PSM revealed that organic cultivation had more employment generation opportunities and higher net income compared to conventional farming. Additionally, a constraint-facing index (CFI) indicated that low market prices for output were major constraints for both practices followed by the non-availability of quality input for organic growers and high price of fertilizers for conventional farmers. The study suggested that policymakers should address these constraints in order to promote the adoption of organic agriculture on a large scale and improve farmers’ livelihoods.

In order to assess the genetic diversity and character association, nine early maturing sugarcane clones were studied in 2015-16 and 2016-17 crop seasons under inorganic environment in summer planting regime. The results of the experiment revealed that variety CoPk 05191 had greater genetic distance from CoS 03251 (239.401), CoLk 11201 (227.923) and UP 05125 (201.355), medium genetic distance was between Co 98014 and Co 11201 (224. 618), Co 98014 and UP 05125 (179.927), and Co 98014 and CoS 03251 (178.029). The hybridization between the aforesaid combinations of clone scan produce heterotic and transgressive genotypes with higher cane and sugar yield. The cane yield showed strong positive and highly significant correlation with cane height (r=0.948**), single cane weight (r=0.817**), number of millable canes (r=0.748**), and green top yield (r=0.653**). Being highly correlated with cane yield, the characters like cane height, cane weight, NMC and green top weight need special focus while making selection for higher cane and sugar yield.

Sclerotinia sclerotiorum is an important devastating necrotrophic plant pathogen infecting various horticulture crops in India. The present study aimed to examine the variability among S. sclerotiorum isolates from different hosts by means of mycelial compatibility grouping (MCGs), production of oxalic acid and pathogenicity. The isolates were grouped into eight MCGs (MCG A to MCG H) and the MCG data was used to calculate Shannon’s diversity index ( H ) and Simpson index ( S ). High diversity was detected for the S. sclerotiorum isolates ( H = 1.968, S = 0.845). Most of the isolates produced oxalic acid in potato dextrose agar and potato dextrose broth embedded with bromophenol blue, which was confirmed by changing the media colour from blue to yellow. A deep bright yellow colour with higher luminosity values (37.48, 36.64 and 36.84) was observed in SS1, SS3 (mustard) and SS6 (potato) isolates. The highest oxalic acid production was recorded in potato SS14 (43.25 mM) and mustard SS1 (41.11 mM) isolates, while potato isolate SS10 (10.88 mM) produced lowest oxalic acid. All isolates infect the tested plant leaves; however, lesion size and time required for infection were varied. Positive correlations were observed in S. sclerotiorum mycelial growth vs. luminosity values, mycelial dry weight vs. medium pH and mycelial dry weight vs. oxalic acid accumulation. This study indicates a high level of diversity among the S. sclerotiorum isolates from the different crops with respect to MCG, oxalic acid production and pathogenicity. Further, these results would be helpful in developing management strategies against white mold disease.

Sustainable management of municipal solid waste (MSW) is the utmost importance not only because of the health and environmental concerns but also due to its disposal issues of large quantities of waste generated and to achieve the Sustainable Development Goals (SDGs). Improper management of MSW causes hazards to inhabitants. Environmental and economic implications linked with the proper eco-friendly disposal of modern-day waste, has made it essential to come up with alternative waste management practices. Several studies revealed that approximately 90% of MSW disposed of unscientific manner as open dumps and landfilling, and created severe enigma to human health and the environment as well as contaminating the food chain cycle. It has been observed that urban local bodies (ULBs) in India have a big challenge in handling huge quantities of MSW; due to high density of population and insufficient infrastructure. Door to door collection of waste, methodologies for recycling MSW, and scientific treatments are some of the challenges. Considering these facts, the Union Ministry of Environment, Forests and Climate Change (MoEF&CC) India notified the new Solid Waste Management Rules (SWM), 2016 which would be revamped solid waste management in the country. Several steps of waste management/treatments are being adopted, i.e., incineration, pyrolysis, bio-refining and biogas plants, recycling and composting, composting is a sustainable low-cost option for MSW management, however, very less amount 6–7% of MSW was recycled through it. The present study emphasized a comprehensive review of the characteristics, production, collection, disposal and effective treatment technologies of MSW practiced in India.

The present investigation was carried out during 2021-22 at Acharya Narendra Deva University of Agriculture & Technology, Kumarganj, Ayodhya (Uttar Pradesh). Results revealed that phenotypic characterization of plant growth promoting microbial isolates from rice rhizosphere and phyllosphere have significant effects on physicochemical properties of soil. On the other hand, microbial isolates have a significant effect on microbial biomass carbon (MBC) and total protein content of the soil. Applying microbial isolates has a positive impact on microbial population in terms of total rhizospheric bacterial population (0.77 - 8.4×106 cfu g-1 soil). Whereas, fungal population (1.0 – 51.0 ×103 sfu g-1 and actinomycetes (1.7- 97 ×103 cfu g-1 of soil). Whereas, total number of phyllospheric bacterial population of rice plant leaves and clumps were 0.53- 6.4×106 cfu g-1, leaf fungal population 1.0- 73 ×102 sfu g-1, leaf Actinomycetes population 0.67- 1.2 ×103 cfu g-1. A total of 6 bacterial stains, 2 Actinomycetes and 3 fungal strains were isolated from the rhizospheric soil. Similarly, 4 bacterial stains, 2 Actinomycetes and 2 fungal strains were also isolated from the phyllosphere of the rice field by serial dilution effect on plating techniques. Plant growth promoting (PGP) traits were evaluated. The highest IAA (Indole Acetic Acid) production (23.75μg ml-1) was recorded under the RRS5 (Rice Rhizospheric Sample 5) and followed by RRS3 which was produced at 18.76 μgml-1. The isolated microorganisms can be used as an effective bio inoculant either individually or in different combinations for the formulation of different multi potent biofertilizers for plant growth promotion substances as well as control of plant diseases in rice crop.

The present study aimed to appraise the long-term effects of organics, crop residues, and biofertilisers on soil carbon (C) and nitrogen (N) pools for sustainable crop production and changes in soil quality under long-term organic farming practices. Hence, we studied the soil C and N pools and their sensitivity indices as influenced by a different combination of farmyard manure, vermicompost, biofertilisers, and crop residue of rice, wheat, and mungbean, under long-term rice–wheat–mungbean (RWMCS) and rice–wheat (RWCS) cropping systems in an Inceptisol of India. Total soil organic C increased by 78% and 104% for RWMCS and 94% and 123% for RWCS with FYM + crop residue + biofertilisers and vermicompost + crop residue + biofertilisers, respectively over unfertilised control plots of RWMCS. The highly labile C and microbial biomass C were highly sensitive to management practices compared to total organic C and less labile C fractions. Integrated application of manures and crop residues in FYM + crop residue and VC + crop residue resulted in significantly higher total N, labile N, and mineral N for both cropping systems. Higher values of C and N management indexes were observed with FYM + crop residue + biofertilisers and VC + crop residue + biofertiliser in both cropping systems than other treatments. Integrated use of organic sources had higher N fractions than the unfertilised control plots, indicating that long-term conjoint use of organics, crop residues, and biofertilisers could sustain crop production and soil quality.