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Adult-onset Still’s disease (AOSD) is a remarkably rare illness. One well-known pathogenic process that results in systemic manifestations is auto-inflammatory disease. We report on a young man who complained of joint pain, sore throat, and a high spiking fever. After a thorough assessment using the Yamaguchi criteria, the patient’s clinical examination, elevated serum ferritin and C-reactive protein (CRP), absence of serologic markers (RA factor, Antinuclear antibody levels), and lymphadenopathy all contributed to the diagnosis of AOSD. He was treated with analgesics, steroids, and disease-modifying anti-rheumatic drugs (DMARDs). Three weeks later, at the follow-up, his symptoms and lab parameters had improved.

Rapid urbanization has caused a worldwide increase in the discharge of wastewater effluent. Although Nepal has a noteworthy history of wastewater management, progress in this field has been hindered by persistent issues. These problems encompass insufficient sewer coverage, deficient treatment and sludge disposal facilities, inadequate treatment infrastructure, lack of coherent institutional frameworks, and a lack of comprehensive planning. This review provides a glimpse into Nepal's current urban wastewater landscape while also offering a concise historical overview of its wastewater management trends. The study gathered data, information from government organizations, as well as related research, review articles, and reports from 1999 to 2023. Our findings reveal that more than 85% of urban households in Nepal rely on onsite sanitation, with limited access to septage treatment facilities. The ratio of wastewater treatment to generation is disconcertingly low, further emphasized by the concentration of centralized treatment plants in the capital city. This low ratio underscores the inadequacy of the existing wastewater system and the novice approaches of the government, which contribute to the poor sewerage facilities in Nepal. This study unequivocally highlights the imperative need for functional and institutional hierarchy emphasizing local communities, substantial changes in resource allocation, governance practices, and technical infrastructure. HIGHLIGHTS Nepal is struggling with urban wastewater challenges due to a lack of infrastructure.; Over 85% of urban households are mainly relying on onsite sanitation systems.; Two of seven provinces provide public sewerage systems covering about 10% of the total households.; Advanced treatment technologies are suggested in conjunction with conventional ones.; Proper resource allocation, good governance, and technical skills enhancement are urgent in countries like Nepal, to achieve SDG-6.;

Abstract An accurate assessment of nitrate leaching is important for efficient fertiliser utilisation and groundwater pollution reduction. However, past studies could not efficiently model nitrate leaching due to utilisation of conventional algorithms. To address the issue, the current research employed advanced machine learning algorithms, viz., Support Vector Machine, Artificial Neural Network, Random Forest, M5 Tree (M5P), Reduced Error Pruning Tree (REPTree) and Response Surface Methodology (RSM) to predict and optimize nitrate leaching. In this study, Urea Super Granules (USG) with three different coatings were used for the experiment in the soil columns, containing 1 kg soil with fertiliser placed in between. Statistical parameters, namely correlation coefficient, Mean Absolute Error, Willmott index, Root Mean Square Error and Nash–Sutcliffe efficiency were used to evaluate the performance of the ML techniques. In addition, a comparison was made in the test set among the machine learning models in which, RSM outperformed the rest of the models irrespective of coating type. Neem oil/ Acacia oil(ml): clay/sulfer (g): age (days) for minimum nitrate leaching was found to be 2.61: 1.67: 2.4 for coating of USG with bentonite clay and neem oil without heating, 2.18: 2: 1 for bentonite clay and neem oil with heating and 1.69: 1.64: 2.18 for coating USG with sulfer and acacia oil. The research would provide guidelines to researchers and policymakers to select the appropriate tool for precise prediction of nitrate leaching, which would optimise the yield and the benefit–cost ratio.

Abstract One of the main challenges for healthy hydrocarbon yields from the production wells is the sand production, and its control assumes significant importance for successful production operations. The prime objective remains to control the sand production without compromising on the fluid flow rates. Sand production is conventionally associated with diverse heterogeneous formations, especially poorly consolidated formations. Scrutinizing fluid flow rates at different orientations of perforations is a valuable analysis in controlling the sand production. This study was conducted to examine the case of sand production in a few development wells from Malleshwaram field of the Krishna Godavari (KG) basin in south India and provide alternatives to arrest this sand production. The influence of oriented perforations on fluid flow rates to minimize sanding tendencies was examined. Sand grain diameter was estimated using the distribution plots of the grain sizes obtained from the photomicrographs, and the average value of the grain size was estimated around 100 μm. The fluid flow model was simulated for actual scenario in the hydrocarbon bearing Nandigama formation using finite element modeling (FEM). Sanding tendencies in these formations were studied at varying depletion rates. Critical draw down pressure (CDDP), which is a function of both critical bottom hole pressure and reservoir pore pressure, for well 1 and well 2 is estimated as 4650 Psi and 3400 Psi, respectively, at 0% depletion. CDDP was used to estimate the onset of sanding, and the flow rate for horizontal perforation was calculated as 0.024548 $${\mathrm{m}}^{3}$$ m 3 /sec. Strength parameters, namely the unconfined compressive strength (UCS) and cohesion, were also investigated in all the wells to decipher the formation strength and a possible linkage to sanding. These results present a completely fresh analysis of the sanding potential and the related parameters responsible for it in these formations. Fluid flow rates for the producing reservoir are studied at different set of oriented and sized perforations. It was observed that a hiked flow rate in horizontal perforations maintains the production in a safe and no-sanding zone. This study provides vital information and a workflow for similar heterogeneous complex formations for designing the well completions, augmenting economic production and reinforcing future reservoir management.

The release of cadmium into the environment is a significant global concern due to its toxicity, non-biodegradability, and persistence in nature. There is an urgent need for effective, eco-friendly, and cost-effective systems for removing Cd because of the many drawbacks of conventional physicochemical techniques. This study investigated the ability of the extremophile red microalgal strain Galdieria sulphuraria CCMEE 5587.1 to tolerate and remove Cd (II) ions at acidic pH in a controlled laboratory environment. Three distinct concentrations of Cd (1.5 mg L−1, 3 mg L−1, and 6 mg L−1) were introduced to the cyanidium medium, and G. sulphuraria cells were introduced in the medium and grown for ten days. Four distinct aspects were identified regarding Cd removal: time course Cd removal, total Cd removal, extracellular Cd removal, and intracellular Cd removal. The inhibitory effects of Cd on G. sulphuraria growth were observed using a daily growth profile. Initial incubation days showed an inhibition of G. sulphuraria growth. In addition, increasing the Cd concentration in the medium decreased the growth rate of G. sulphuraria. Rapid Cd removal occurred on the first day of the experiment, followed by a steady removal of Cd until the last day. The highest total removal efficiency occurred in a medium containing 3 mg L−1 of Cd ions, which was 30%. In contrast, the highest sorption capacity occurred in a medium containing 6 mg L−1 of Cd ions, which was 1.59 mg g−1 of dry biomass. In all media compositions, a major fraction (>80%) of Cd removal occurred via adsorption on the cell surface (extracellular). These results showed that G. sulphuraria cells can remove Cd ions from aqueous solution, which makes them a potential bioremediation option for heavy metal removal.

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3-[RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m−2 s−1), Tr (7.03 m mol H2O m−2 s−1), Gs (0.175 µmol CO2 mol−1 year−1), and Ci (271.7 mol H2O m2 s−1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09–4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08 kg ha−1 m−3). However, economic water productivity (27.5 INR ha−1 m−3) and water-use efficiency (7.6 kg ha−1 mm−1 day−1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63 t ha−1) and biological yield (8.37 t ha−1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agro-ecological regions.

To achieve higher crop yields and maintain environmental conservation, it is imperative to adopt novel agricultural methods that improve both the quantity and quality of produce. The following study focused on investigating the effectiveness of integrated use of biogas slurry and inorganic nutrigation on spinach growth and nutrient uptake through drip irrigation. A field experiment was conducted using a split-plot design; spinach was cultivated with seven different treatments: biogas slurry nutrigation (BSN) (T1), integrated inorganic + organic nutrigation: 40% Recommended dose of fertilizer (RDF) + BSN (T2), 60% RDF + BSN (T3), 80% RDF + BSN (T4), 100% RDF (T5), slurry broadcasting (SB) (T6), and control (T7). The results showed that spinach grown with (T4) 80% RDF + BSN exhibited optimum plant height and leaf count compared to spinach under other treatments and was at par with T5 100% RDF for crop parameters. T5 treated plants demonstrated the longest roots, followed by T4 treated plants. The highest recorded yield of 5.72 tons ha−1 was achieved in treatment T5 with 100% RDF, followed closely by T4 with 80% RDF + BSN at 5.52 tons ha−1 and T3 with 60% RDF + BSN at 5.36 tons ha−1. These three treatments exhibited comparable yields, showcasing the effectiveness of incorporating biogas slurry nutrigation in conjunction with inorganic fertilizer for achieving high spinach yields. In terms of macronutrient content in spinach leaves, significant differences were found for nitrogen (N), phosphorus (P), and potassium (K) contents. Incorporating biogas slurry into the soil modified microbial enzyme activities, specifically dehydrogenase and phosphatase. Normally, alkaline phosphatase shows greater activity than acidic phosphatase, but the addition of biogas slurry equalized the enzymatic activity of both, establishing a harmonized enzymatic profile. Our results suggest that fertilizing spinach with integrated biogas slurry nutrigation (if properly filtered) + inorganic nutrigation through drip nutrigation is a viable strategy for improving the morphological parameters and productivity of spinach while also contributing to environmental preservation and a reduction in production costs.

In this paper, the Kolar River watershed, Madhya Pradesh is taken as the study area. This study area is located in Narmada River in Central India. The data set consists of monthly rainfall of three meteorological stations, Ichhawar, Brijesh Nagar, and Birpur rainfall stations from 2000 to 2018, runoff data at Birpur and temperature data of Sehore district. In this paper, radial basis function neural network models have been studied for generation of rainfall–runoff modeling along with wavelet input and without wavelet input to the RBF neural network. A total of 15 models were developed in this experiment based on various combinations of inputs and spread constant of RBF model. The evaluation criteria for the best models selected are based on R2, AARE, and MSE. The best predicting model among the networks is model 8, which has input of R(t-1), R(t-2), R(t-3), R(t-4), and Q(t-1). For the RBFNN model, the maximum value of R2 is 0.9567 and the lowest values of AARE and MSE are observed. Similarly, for the WRBFNN model, the maximum value of R2 is 0.9889 and the lowest values of AARE and MSE are observed. WRBF performs better than RBF with any data processing techniques which shows the proposed model possesses better predictive capability. HIGHLIGHTS Fifteen ANN model used for analysis.; New data processing technique of wavelets used.; Analysis of Kolar river basin, main tributary of Narmada in Central India.; Radial basis function used for modeling.; Suitable method for data scarce region and semiarid environment.;

Introduction: Diabetes and thyroid disorders are the two most common disorders amongst endocrine diseases. Uncontrolled diabetes mellitus (DM) may disturb thyroid metabolism by disturbing the levels of thyroid hormones in the plasma. This study was undertaken to determine the prevalence and thyroid dysfunction in type 2 diabetic population presenting in a public sector tertiary care teaching hospital. Materials and Methods: This descriptive cross-sectional study was conducted in Civil Hospital Karachi (CHK) in the department of medicine from October 01, 2018, to March 31, 2019. The study population consisted of 317 patients diagnosed with DM type 2 based on American Diabetes Association (ADA) criteria. Patients with fasting blood sugar ≥ 126 mg/dL, or HbA1c >6.5 (%), and 2 h postprandial blood glucose levels >200 mg/dL were included. After a minimum of 8 h of fasting, plasma samples of patients were collected and sent for fasting blood glucose, HbA1c, FT3, FT4, and thyroid-stimulating hormone (TSH). Descriptive statistics were calculated. Post-stratification Chi-squared test was applied, and a P value of ≤ 0.05 was considered significant. Results: Among all enrolled DM type 2 patients, 207 (65.3%) were male with a mean age of 46.54 ± 8.72 years. Mean fasting blood sugar (FBS), random blood sugar (RBS), and HbA1c were 212.76 ± 26.91 (mg/dL), 328.89 ± 52.89 (mg/dL), and 9.43 ± 2.47 (%), respectively. The mean duration of DM was 7.81 ± 3.15 years. Mean FT3, FT4, and TSH were 113.13 ± 44.40 (ng/dL), 7.63 ± 3.11 (mg/dL) and 2.64 ± 2.57 (μIU/mL), respectively. In the present study, 55 (17.4%) patients had subclinical hypothyroidism, 27 (8.5%) had hypothyroidism, 19 (6.0%) had hyperthyroidism, and 16 (5.0%) had subclinical hyperthyroidism. Significant association of thyroid dysfunction was established with age group, female gender, and family history of thyroid dysfunction (P =< 0.001). Conclusion: The prevalence of thyroid dysfunction is higher among patients with type 2 diabetes mellitus (T2DM), in which hypothyroidism was the most common dysfunction with more prevalence among female patients.

With growing urbanization and ongoing development activities, the consumption of heavy metals has been increasing globally. Although heavy metals are vital for the survival of living beings, they can become hazardous when they surpass the permissible limit. The effect of heavy metals varies from normal to acute depending on the individual, so it is necessary to treat the heavy metals before releasing them into the environment. Various conventional treatment technologies have been used based on physical, chemical, and biological methods. However, due to technical and economic constraints and poor sustainability towards the environment, the use of these technologies has been limited. Microalgal-based heavy metal removal has been explored for the past few decades and has been seen as an effective, environment-friendly, and inexpensive method compared to conventional treatment technology. Cyanidiales that belong to red algae have the potential for remediation of heavy metals as they can withstand and tolerate extreme stresses of heat, acid salts, and heavy metals. Cyanidiales are the only photosynthetic organisms that can survive and thrive in acidic mine drainage, where heavy metal contamination is often prevalent. This review focuses on the algal species belonging to three genera of Cyanidiales: Cyanidioschyzon, Cyanidium, and Galdieria. Papers published after 2015 were considered in order to examine these species’ efficiency in heavy metal removal. The result is summarized as maximum removal efficiency at the optimum experimental conditions and based on the parameters affecting the metal ion removal efficiency. This study finds that pH, initial metal concentration, initial algal biomass concentration, algal strains, and growth temperature are the major parameters that affect the heavy metal removal efficiency of Cyanidiales.

Purpose – Business systems are made up of processes. Processes are collection of activities of businesses that results in an output. And when processes become old and inefficient and can’t deliver results they must be redesigned or replaced. Business process reengineering is a tool for transformation of business process and unconstrained reshaping of all business processes. This study uses case and critical literature analysis (CLA) to investigate and focus on the development of business process reengineering (BPR) application concept and its outcome to the industrial set-up (service giving and manufacturing). Approach/methodology – The goal is achieved by case and critical literature analysis (CLA). The case validates its result and justifies its practicality. This study contributed in the context of BPR as a process based management tool for selecting, managing and reengineering selected processes for overall manufacturing or service quality improvement. Findings – In this study, a series of manufacturing processes and a framework for the guidelines of modeling has shown. Core processes of different industries has presented in effective manner. These validates that business process reengineering is a process-based management tool that can deliver both, either redesign or replace inefficient processes, as required, with a breakthrough result. It can be applied to single, group or entire processes comprising the organization. Practical implications – On the basis of presented case study & process modeling guidelines the managers can use BPR to redesign their inefficient processes. Originality/value – This approach suggests adopting BPR at any cost as a tool to improve all business processes as well as overall productivity and performance by managing their whole process. Case study motivates practitioners/managers towards reengineer and manages their business process.

Background: Diagnosing intestinal (Luminal) tuberculosis is challenging due to limited yield of diagnostic modalities like CT scan, colonoscopy with blind ileal biopsies. GeneXpert MTB/RIF (Xpert) assays for diagnosing tuberculosis have been performed in the body secretions with excellent results. Its yield in stool is tested in this study. Objective: The study aims to evaluate the yield of GeneXpert assay in stool of suspected cases of intestinal tuberculosis. Methods: Hundred patients with suspected intestinal tuberculosis underwent routine biochemical tests, radiological investigations, colonoscopy with caecal and blind ileal biopsies for histopathology. Fresh stool samples were collected, processed for DNA extraction, tested using 2:1 ratio of GeneXpert reagent to sample to give positive or negative results for Mycobacterium tuberculosis and Rifampicin resistance. Results: Out of hundred participants, 52% were female. Mean age was 28.21 ± 12.13. CT scan and colonoscopy findings suggestive of TB were present in 47% and 43% participants respectively. GeneXpert in stool was positive in 20% cases. Considering mucosal biopsy with histopathology of intestinal specimens as diagnostic of abdominal Tuberculosis, sensitivity and specificity of GeneXpert was 39.1% and 85.7% respectively. Conclusion: Stool GeneXpert assay offers an alternative approach to detect intestinal tuberculosis rapidly with good diagnostic accuracy. Although it cannot replace the AFB culture and histopathology but contribute for early diagnosis and management. Keywords: Mycobacterium tuberculosis, Nucleic Acid Amplification Techniques, GeneXpert MTB/RIF assay, Ileocaecal tuberculosis

Greenhouses are space-efficient structures used in the production of produce. However, occupational health issues like exposure to chemicals, and physiological and postural stresses are experienced by operators while performing farm activities due to the enclosed environment of the greenhouse. This study assesses chemical exposure and physiological and postural parameters of operators during spraying with two different types of sprayers (Battery-powered knapsack sprayer [Battery sprayer] and AC-powered stationary sprayer [Stationary sprayer]) with two different application techniques (continuous and alternate row). The mean Potential Dermal Exposure (PDE) for a continuous row of spraying was 54 and 70 mL h−1 with battery and stationary sprayers, respectively. However, PDE in alternate row spraying was approximately 16 and 25% less in battery and stationary sprayers than in a continuous row. The upper and left portions of the body had higher exposure compared to the lower and right half portions in all treatments. The ergonomic parameters (physiological and postural assessment) in continuous and alternate row spraying techniques did not differ but varied with the type of sprayer used. Mean values of energy expenditure rate, body part discomfort score, overall discomfort score, and risk index were 210 ± 35 W, 27 ± 2.0, 6.1 ± 0.4, and 1.0, respectively, in the battery sprayer compared to 290 ± 80 W, 35 ± 4.1, 8.3 ± 1.0, and 2.0 in the stationary sprayer. This study concluded that the use of a battery sprayer with an alternate row spraying technique resulted in lower dermal exposure (45 mL h−1) and was ergonomically less demanding. [ABSTRACT FROM AUTHOR]

The release of cadmium into the environment is a significant global concern due to its toxicity, non-biodegradability, and persistence in nature. There is an urgent need for effective, eco-friendly, and cost-effective systems for removing Cd because of the many drawbacks of conventional physicochemical techniques. This study investigated the ability of the extremophile red microalgal strain Galdieria sulphuraria CCMEE 5587.1 to tolerate and remove Cd (II) ions at acidic pH in a controlled laboratory environment. Three distinct concentrations of Cd (1.5 mg L−1, 3 mg L−1, and 6 mg L−1) were introduced to the cyanidium medium, and G. sulphuraria cells were introduced in the medium and grown for ten days. Four distinct aspects were identified regarding Cd removal: time course Cd removal, total Cd removal, extracellular Cd removal, and intracellular Cd removal. The inhibitory effects of Cd on G. sulphuraria growth were observed using a daily growth profile. Initial incubation days showed an inhibition of G. sulphuraria growth. In addition, increasing the Cd concentration in the medium decreased the growth rate of G. sulphuraria. Rapid Cd removal occurred on the first day of the experiment, followed by a steady removal of Cd until the last day. The highest total removal efficiency occurred in a medium containing 3 mg L−1 of Cd ions, which was 30%. In contrast, the highest sorption capacity occurred in a medium containing 6 mg L−1 of Cd ions, which was 1.59 mg g−1 of dry biomass. In all media compositions, a major fraction (>80%) of Cd removal occurred via adsorption on the cell surface (extracellular). These results showed that G. sulphuraria cells can remove Cd ions from aqueous solution, which makes them a potential bioremediation option for heavy metal removal. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is the key macronutrient for sustainable growth and higher productivity of crops. Optimized nitrogen-use-efficiency (NUE) enhances productivity and reduces the environmental impacts as well as input cost of production. NUE can be improved by the site-specific application of nitrogen fertilizer. Variable rate nitrogenous fertilizer can be applied after assessing the real-time status of the plant nitrogen. The assessment of the plant nitrogen can be obtained by various destructive and nondestructive techniques. This article aims to provide a thorough overview of the approaches available for determining plant N levels. The destructive techniques (Kjeldahl method and Dumas combustion) are tedious and time-consuming but more accurate. The most adopted nondestructive methods such as the use of Leaf Color Chart (LCC), digital sensors (SPAD meter, CCM-200, GreenSeeker, Crop Circle and Yara N-Sensor, OptRx® Crop Sensor, ISARIA, CropSpec, Multiplex®) and digital imaging-based techniques of plants are rapid in N level estimation. Nondestructive techniques utilize the optical property of leaves to assess the N level of plants. However, digital sensor-based estimation has certain limitations, including chlorophyll saturation, illumination effect, less accuracy and the high initial cost of instruments. Furthermore, more research should be carried out to overcome these limitations and improve their efficiency. [ABSTRACT FROM AUTHOR]

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3- [RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m-2 s-1), Tr (7.03 m mol H2Om-2 s-1), Gs (0.175 µmol CO2 mol-1 year-1), and Ci (271.7 mol H2O m2 s-1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09-4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08 kg ha-1 m-3). However, economic water productivity (27.5 INR ha-1 m-3) and water-use efficiency (7.6 kg ha-1 mm-1 day-1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63 t ha-1) and biological yield (8.37 t ha-1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agroecological regions. [ABSTRACT FROM AUTHOR]

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3- [RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m-2 s-1), Tr (7.03 m mol H2Om-2 s-1), Gs (0.175 µmol CO2 mol-1 year-1), and Ci (271.7 mol H2O m² s-1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09-4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08 kg ha-1 m-3). However, economic water productivity (27.5 INR ha-1 m-3) and water-use efficiency (7.6 kg ha-1 mm-1 day-1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63 t ha-1) and biological yield (8.37 t ha-1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agroecological regions. [ABSTRACT FROM AUTHOR]