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Amongst various sources of farm power, electrical power through stored electric energy is a potential source to meet the current challenge in agriculture. At ICAR-IARI, an attempt was made to use battery-power for developing a walk behind equipment with 250-800W DC/BLDCC motors for sowing, weeding, cutting and performing operations on a common platform during 2015-20. The study further led to developing a Versatile Electric Prime Mover for Agriculture (VEPMA) using 1.5 kW BLDC motor with the provision of various attachments that can meet the need of small farmers. The VEPMA is assessed to be an economically viable unit with a saving of 5-liter diesel fuel per ha and 5 to 10 times economical to tractor and power tiller operations. Its adoption in one percent cultivable area (1.4 million ha) in India can result in the net saving of approximately 32 million litres of diesel and reduce 85000 tons of CO2 in the atmosphere.

Indian agriculture is diverse and capable of producing most of the food and horticultural crops of the world. In spite of its top ranking in production of a number of crops including rice, wheat, sugarcane, fruits and vegetables, the stagnancy in productivity and shortage of agricultural produce are two major bottlenecks of Indian agriculture. Several studies suggest a direct correlation between farm mechanization and crop productivity. It saves inputs like seeds and fertilizers by 15-20%, labour requirement and operational time by 20-30%, increases cropping intensity by 5-20% and crop productivity by 10-15%. At present, Indian farmers are adopting farm mechanization at a faster rate in comparison to recent past. Farm power availability from tractors has grown from 0.007 kW/ha in 1960-61 to 1.03 kW/ha in 2013-14 and it is further estimated to reach 3.74 kW/ha by 2032-33. According to the World Bank estimates, half of the total Indian population would be in urban areas by 2050. It is further estimated that the percentage of farm workers of total work force would reduce to 49.9% in 2033 and 25.7% in 2050 from 54.6% in 2011. The share of agricultural workers in total power availability in 1960-61 was about 16.3%, which is going to reduce to 2.3% in 2032-33. The overall level of farm mechanization in the country is only 40-45% and 90% of the total farm power is contributed by mechanical and electrical power sources. To assure timeliness and quality in various field operations, the average farm power availability needs to be increased to a minimum of 2.5 kW/ha by 2020.

Reliable forecast of crop production before the harvest is important for advance planning, formulation and implementation policies dealing with food procurement, its distribution, pricing structure, import and export decisions, and storage and marketing of the agricultural commodities. Weather plays a very important role in crop growth and development. Therefore, model based on weather variables can provide reliable forecast. Weather variables used can be employed for crop production forecast by making appropriate models. In this study, a statistical model is used for crop yield forecast at different growth stages of wheat crop. This model uses maximum and minimum temperature, rainfall, morning and evening relative humidity during crop growing period. The forecast model was developed using generated weather indices as regressors in model. In order to select significant weather variables affecting the yield of crop least absolute shrinkage and selection operator (LASSO) as well as stepwise regression methodology is applied. The result of lasso gives a better result as compared to stepwise regression. The R2 of lasso and stepwise regression are 0.84 and 0.85, respectively. The mean square error (MSE) and root mean square error (RMSE) of Lasso regression were better than stepwise regression, which leads to improvement of crop yield forecasting. It can be inferred that for the data under consideration, lasso works better than stepwise regression for variable selection.

Background: The incidence of uncomplicated psoriasis is 1-3% in the general population. The involvement of palm and sole is seen in 7-14.5% of cases. There are different topicals and systemic therapies available for treating the case of psoriasis but none is satisfactory for longer duration. Aim: The study involved the comparative therapeutic evaluation of the different topical regimens and narrow band ultraviolet B (NB-UVB) therapy in combination with systemic methotrexate. Materials and Methods: The study was held in out-patient department of Skin, VD and Leprosy of B.R.D. Medical College, Gorakhpur, from July 2007 to December 2008. The group included 98 new cases of palmoplantar psoriasis. These cases were divided into eight groups according to the eight regimens involved in the study. The severity of psoriasis was assessed by the ESIF (erythema, scaling, induration and fissuring) score. Results: The study showed that all the regimens had significant response rates. The combination of NB-UVB with systemic methotrexate had maximum response rate (64.85±4.52%) that was statistically significant (paired "t0" at 16d.f. = 33.329, P

A field experiment was conducted during the kharif seasons of 2009 and 2010 at Indian Agricultural Research Institute, New Delhi to study productivity and profitability of aerobic rice as influenced by varieties and integrated nitrogen management. The experimental treatments included 2 rice varieties, viz. Pusa Basmati 1 and Pusa Basmati 1121 and 8 integrated nitrogen management practices, viz. N control (N0); 100% RDN (120 kg N/ha through urea); 75% RDN + 25% N through farmyard manure; 75% RDN + 25% N through green manuring; 75% RDN + 25% N through biofertilizers; 75% RDN + 25% N through vermicompost; 100% N through FYM+GM+BF+VC and 100% N through FYM+GM+BF+VC+ZnSO4. The results showed that rice variety Pusa Basmati 1 out performed Pusa Basmati 1121 in yield attributes, grain yield and harvest indices. Application of recommended dose of nitrogen (RDN) through integrated nitrogen management (INM) approach significantly increased the crop growth parameters, yield attributes, grain as well straw yields and net returns over other INM approaches. Treatment with 100% N by FYM+GM+BF+VC+Zn showed highest crop growth and yield attributes, grain and straw yield and net returns as compared to other integrated nitrogen management treatments, but this treatment was closely followed by 100% N by FYM+GM+BF+VC and 75% RDN + 25% VC during both the years.

IntroductionThe chickpea (Cicer arietinum L.) is well-known for having climate resilience and atmospheric nitrogen fixation ability. Global demand for nitrogenous fertilizer is predicted to increase by 1.4% annually, and the loss of billions of dollars in farm profit has drawn attention to the need for alternative sources of nitrogen. The ability of chickpea to obtain sufficient nitrogen via its symbiotic relationship with Mesorhizobium ciceri is of critical importance in determining the growth and production of chickpea.MethodsTo support findings on nodule formation in chickpea and to map the genomic regions for nodulation, an association panel consisting of 271 genotypes, selected from the global chickpea germplasm including four checks at four locations, was evaluated, and data were recorded for nodulation and 12 yield-related traits. A genome-wide association study (GWAS) was conducted using phenotypic data and genotypic data was extracted from whole-genome resequencing data of chickpea by creating a hap map file consisting of 602,344 single-nucleotide polymorphisms (SNPs) in the working set with best-fit models of association mapping.Results and DiscussionThe GWAS panel was found to be structured with sufficient diversity among the genotypes. Linkage disequilibrium (LD) analysis showed an LD decay value of 37.3 MB, indicating that SNPs within this distance behave as inheritance blocks. A total of 450 and 632 stringent marker–trait associations (MTAs) were identified from the BLINK and FarmCPU models, respectively, for all the traits under study. The 75 novel MTAs identified for nodulation traits were found to be stable. SNP annotations of associated markers were found to be related to various genes including a few auxins encoding as well as nod factor transporter genes. The identified significant MTAs, candidate genes, and associated markers have the potential for use in marker-assisted selection for developing high-nodulation cultivars after validation in the breeding populations.

Abstract Uttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs.

Spatiotemporal snow depth (SD) mapping in the Indian Western Himalayan (WH) region is essential in many applications pertaining to hydrology, natural disaster management, climate, etc. In situ techniques for SD measurement are not sufficient to represent the high spatiotemporal variability in SD in the WH region. Currently, low-frequency passive microwave (PMW) remote-sensing-based algorithms are extensively used to monitor SD at regional and global scales. However, fewer PMW SD estimation studies have been carried out for the WH region to date, which are mainly confined to small subregions of the WH region. In addition, the majority of the available PMW SD models for WH locations are developed using limited data and fewer parameters and therefore cannot be implemented for the entire region. Further, these models have not taken the auxiliary parameters such as location, topography, and snow cover duration (SCD) into consideration and have poor accuracy (particularly in deep snow) and coarse spatial resolution. Considering the high spatiotemporal variability in snow depth characteristics across the WH region, region-wise multifactor models are developed for the first time to estimate SD at a high spatial resolution of 500 m × 500 m for three different WH zones, i.e., Lower Himalayan Zone (LHZ), Middle Himalayan Zone (MHZ), and Upper Himalayan Zone (UHZ). Multifrequency brightness temperature (TB) observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), SCD data, terrain parameters (i.e., elevation, slope, and ruggedness), and geolocation for the winter period (October to March) during 2012–2013 to 2016–2017 are used for developing the SD models for dry snow conditions. Different regression approaches (i.e., linear, logarithmic, reciprocal, and power) are used to develop snow depth models, which are evaluated further to find if any of these models can address the heterogeneous association between SD observations and PMW TB. From the results, it is observed from the analysis that the power regression SD model has improved accuracy in all WH zones with the low root mean square error (RMSE) in the MHZ (i.e., 27.21 cm) compared to the LHZ (32.87 cm) and the UHZ (42.81 cm). The spatial distribution of model-derived SD is highly affected by SCD, terrain parameters, and geolocation parameters and has better SD estimates compared to regional and global products in all zones. Overall results indicate that the proposed multifactor SD models have achieved higher accuracy in deep snowpack (i.e., SD >25 cm) of the WH region compared to previously developed SD models.

DRASTIC method's vulnerability assessment for estimating the potential risk of contamination in shallow groundwater aquifers is the most acceptable technique. The method uses seven parameters, namely, depth to groundwater table, net recharge, aquifer media, soil media, topography, land use and land cover, and hydraulic conductivity to obtain vulnerability index values. These index values are validated with one or a few elements of water characteristics as pollution indicators. In most of the reported studies, the correlation coefficient between the DRASTIC index and the concentration of individual element(s) was low. The present study uses the water quality index (WQI) to correlate with the DRASTIC index value. In this paper, 11 physical and chemical water characteristics data of 31 well locations within the Faridabad District of Haryana, India are utilized to estimate the WQI. The correlation coefficients for single element concentration with DRASTIC index vary between the range of 0.104 to 0.304. The correlation coefficients for the concentration of NO3- and WQI are found to be 0.104 and 0.533, respectively. Thus, the DRASTIC index demonstrates a stronger correlation with the WQI when compared to single element concentration. HIGHLIGHTS In earlier works, the DRASTIC model of groundwater vulnerability assessment has been poorly correlated with the concentration of NO3− in groundwater by researchers.; The current research work finds a better correlation between the DRASTIC index and the water quality index.; The quality of water assessed by these two indices has also been validated by the land use of well/water sampling station locations.;

The radio galaxy NGC 1275, located at the central region of Perseus cluster, is a well-known very high-energy (VHE) gamma-ray emitter. The Major Atmospheric Cherenkov Experiment Telescope has detected two distinct episodes of VHE ( E > 80 GeV) gamma-ray emission from NGC 1275 during 2022 December and 2023 January. The second outburst, observed on 2023 January 10, was the more intense of the two, with flux reaching 58% of the Crab Nebula flux above 80 GeV. The differential energy spectrum measured between 80 GeV and $1.5\,\dot{{\rm{T}}}{\rm{eV}}$ can be described by a power law with a spectral index of Γ = −2.90 ± 0.16 _stat for both flaring events. The broadband spectral energy distribution derived from these flares, along with quasisimultaneous low-energy counterparts, suggests that the observed gamma-ray emission can be explained using a homogeneous single-zone synchrotron self-Compton model. The physical parameters derived from this model for both flaring states are similar. The intermediate state observed between two flaring episodes is explained by a lower Doppler factor or magnetic field, which subsequently returned to its previous value during the high-activity state observed on 2023 January 10.

India Meteorological Department (IMD), Ministry of Earth Sciences (MoES) in collaboration with Indian Council of Agriculture Research (ICAR), State Agriculture Universities (SAUs) , Indian Institute of Technology (IITs) and other organizations is rendering weather forecast based District level Agrometeorological Advisory Service (AAS) for benefits of farmers in the country under the centrally sponsored scheme ‘Atmosphere & Climate Research-Modelling Observing Systems & Services (ACROSS) ’ of MOES. AAS, popularly known as Gramin Krishi Mausam Sewa (GKMS) provides advance weather information along, with crop specific agromet advisories to the farming community by using state of the art instruments and technology through efficient delivering mechanism of the information which ultimately enables farmers to take appropriate actions at farm level. The various components of GKMS viz. observing weather, its monitoring and forecast; crop specific advisory bulletin generation and dissemination; outreach and feedback have been/are being digitized to support integrating all the components of information generation and action suggested linked to these information. An Information and Communication Technology (ICT) based Agromet Decision Support System is developed for automation of the services provided under GKMS. This includes a dynamic framework to link the information of weather forecast, real time weather observation, crop-weather calendar etc. to translate weather forecast into actionable farm advisories for efficient farm level decision making in India. Apart from this, effort is being made to develop recent technology driven tools to estimate future yield of crops and prepare an irrigation schedule without a need of multiple parameters.

The problem of air pollution has ramifications for human health, the environment, and a variety of living sectors. Modern technology has resulted in air pollution and its damaging effects, while also driving the world to make every effort to overcome its negative repercussions. The origin, chemical composition, size, and mode of discharge inside or outdoor environments have all been proven to be air pollutants. Industrial, commercial, mobile, urban, regional, farm, and natural sources of indoor pollutants include cooking and combustion, particle matter rehabilitation, materials used for resources, temperature control, and consumer items, smoking, heating, and organic compounds. Indoor Pollutant Sources Air pollution has an impact on the body, including respiratory systems and heart disorders. Asthmatics, bronchiolitis, lung disease, cardiovascular problems, central nervous system malfunction, and skin conditions are the most common respiratory disorders, as are chronic obstructive pulmonary disease (COPD). The challenges posed by outdoor air pollution are public health risks such as cardiovascular disease, respiratory ailments, COPD, and world-class asymmetry. The impacts of human activities on air quality and climate change may be realized at several sizes, ranging from urban to regional to continental to global. Rapid population growth and increased energy consumption are the principal drivers of massive amounts of hazardous chemicals and greenhouse gases entering the atmosphere, with serious consequences for health and the environment.

Abstract This study tries to elicit the unexplored nexus between the contraceptive failure and abortions in India’s most populous state Uttar Pradesh. Condom being the most used modern method contributes to 47% of all observed episodes in the calendar period. Of all accidental pregnancies occurred because of modern contraceptive failures, 35.2% terminated with induced abortions. Gross failure rate of modern methods is conspicuously higher for urban poor, uneducated women, and marginalized section of population living in urban area. From a total of 7496 episodes of all reversible methods, abortions are estimated as high as 29.2%, whereas for the traditional method it accounts for around 21%. The empirical evidence of induced abortions due to contraceptive failure put serious concern regarding unintended pregnancies and hence discourages fertility intentions among the potential couples.

Rice is an important cereal crop and part of daily diet not only in India but also throughout Asia. Agriculture is highly dependent on the variations in temperature, precipitation and solar radiation and long-term climate patterns. The pattern of changing climate in last 30 years indicate that predictable and possible changes in rainfall and temperature can reduce agriculture outputs and yields particularly for rice and wheat significantly. The main aim of this research paper is to study the Kharif Rice Productivity in Hisar, Haryana under changing climate. The study focuses on the impacts of climate change namely intensity, timings and spatial distribution of rainfall. Kharif rice is more vulnerable to meteorological drought due to growing uncertainties in monsoon rains under the changing climate patterns. The study of seasonal changes in precipitation at decadal scale for observed and CORDEX projected precipitation for the selected region was done to understand the impacts of climate change. Along with this, DSSAT Crop Simulation Model was run to quantify the water stress in the years with more negative rainfall departure and to identify the reasons for variability in yield. DSSAT model was able to simulate phenological events and final grain yield at maturity stage with reasonable accuracy under varied weather conditions. The analysis of the simulated results indicates the association between yield and rainfall amount and its distribution during the season and different phenological growth stages of rice. The results further indicate that water stress at important stages such as Booting, Heading and Flowering majorly impact the final yield.

Aim: The aim of this study is to find out the effect of propofol and its combination with meperidine and pentazocine lactate on certain clinico-anesthetic profiles in dogs. Materials and Methods: 15 apparently healthy mongrel dogs of either sex of about 1 year of age were randomly divided into three groups of five dogs each. The animals of Group I were administered propofol intravenously alone “to effect,” whereas meperidine at 2 mg/kgb.wt. and pentazocine lactate at 2 mg/kg b.wt. were injected intramuscularly 15 min before propofol “to effect” in Groups II and III, respectively. Atropine sulfate at 0.04 mg/kgb.wt. was injected intramuscularly 20 min before each treatment. Rectal temperature, heart rate, respiration rate, and anesthetic indices were recorded before and at 5, 10, 20, 30, and 60 min of induction. Results: As compared to Group I, the animals of Groups II and III exhibited a significant decrease (p

Background: The 'organ distribution' of cancer is often strikingly dissimilar in different groups of population and varies greatly from one community to another and also differs in different communities in the same geographical location, depending on the practices, lifestyles and the influence of deleterious habits like use of tobacco and or alcohol of the people. Among various cancers affecting the human body, oral cancer accounts for nearly one third of it. Objectives: i) To find out the relative frequency of oral cancer in relation to other sites from Hospital Based Cancer Registry (HBCR) ii) To find out the various risk factors associated with oral cancer and iii) To recommend appropriate preventive measures. Methodology: A hospital based retrospective cross sectional study was conducted through case records of oral cancer patients who reported in the year 2013 to Pravara Rural HBCR, Department of Radiotherapy and Oncology, Rural Medical College and Pravara Rural Hospital, Loni, Maharashtra state, India. The case files and registers of oral cancer cases were reviewed to collect personal and clinical data about sex, age, occupation, marital status, education, socioeconomic status, habits like tobacco chewing and cigarette smoking. A predesigned performa (a core form by HBCR programme) was used to collect the data. The statistical analysis was done using SYSTAT for Windows version 12 and categorical data was analysed by using Chi-square test. Results: In all1328 patients of all cancers visited the hospital during the period January 2013 to December 2013. Out of these, 349 (26.28%) were of oral cancer cases. The sex wise distribution revealed 256 (73.25%) among males and 93(26.65%) among females. Mean age of the patients was 54.98 years, ranging from 15- 78 years, 31.23% were more than 65 years of age. The most oral cancer sites among the males and females were those of tongue (37.82%) and buccal mucosa (32.95%) respectively. Tobacco related cancer patients in males were 79% and in females 61% .Conclusion: The present study findings suggest that prevalence of oral cancer is more among tobacco users especially those using tobacco quid which is more common among Indian women which is in line with most of the epidemiological studies about oral cancer in India. There is an urgent need to implement and sustain appropriate preventive measures and oral cancer screening programmes for the communit

The weekly aphid population on timely sown mustard crop and daily weather parameters recorded at ICAR-Directorate of Rapeseed–Mustard Research, Bharatpur and Hisar stations, during rabi seasons of 2003-04 to 2013-14 were used to develop forewarning model for aphid. In most of the cases, the appearance of population and its peak activity occurred during 51 standard meteorological week (SMW) and 8 SMW. The study revealed that the thermal time or growing degree days (GDD) consistently explained the aphid multiplication significantly in all seasons. The impact of other weather parameters on pest population was observed to be significant only in some seasons. The aphid population increased exponentially with increase in GDD. Further, the exponential coefficient varied among the varieties. The population build up was compared with the model predicted values in three common species (Brassica juncea, B. rapa ssp. sarson and B. napus) grown at two stations. The results revealed that the predicted values derived using the model, were in close agreement with those of the observed.