Browsing by Author "Ram Kumar Singh"

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An overview of remote sensing technology in forest management
(Elsevier, 2025) Aishwarya; Meenu V.V.N.L.Sudha Rani; Preeti Kumari; Pankaj Lavania; Garima Gupta; Prabhat Tiwari; Ram Kumar Singh; Manoj Kumar; Manmohan J.R. Dobriyal; Manish Srivastav; Pavan Kumar
Remote sensing technology has revolutionized the field of forest management, offering unparalleled capabilities for monitoring, assessing, and managing forested landscapes. This overview paper explores the diverse applications and advancements of remote sensing techniques in forest management. It delves into the various remote sensing technologies, including satellite imaging, LiDAR (Light Detection and Ranging), and drones equipped with high-resolution cameras, highlighting their roles in data collection, analysis, and interpretation. This chapter discusses the utilization of remote sensing data for forest inventory, species identification, habitat assessment, and monitoring of forest disturbances such as wildfires, pests, and diseases. Furthermore, it emphasizes the integration of remote sensing with Geographic Information Systems (GIS) and machine learning algorithms for enhanced accuracy in mapping, modeling, and decision-making processes. Challenges and limitations inherent in remote sensing applications within forest management are also addressed, including issues related to data accuracy, processing techniques, and cost-effectiveness. Additionally, the paper explores future trends and potential advancements in remote sensing technology, emphasizing the need for continued research and development to further improve its efficacy in sustainable forest management practices. This chapter aims to provide a comprehensive understanding of the role and significance of remote sensing technology in modern forest management, emphasizing its potential to contribute to informed decision-making, conservation efforts, and the sustainable utilization of forest resources. © 2026 Elsevier Inc. All rights reserved..
Application of geospatial technology in agricultural water management
(Elsevier, 2020) Ram Kumar Singh; Pavan Kumar; Semonti Mukherjee; Swati Suman; Varsha Pandey; Prashant K. Srivastava
The geospatial technology is an emerging technique to study real earth geographic information using Geographical Information System (GIS), Remote Sensing (RS) and other ground information from various devices and instruments. In this chapter, various geospatial process-based techniques segregated into two different categories, i.e., conventional and advanced, are provided for agricultural water management. The descriptions of several approaches are provided to understand the role of geospatial technology in agricultural water management. Most of the approaches are based on remote sensing and GIS in correspondence with statistical learning techniques that can be possibly used for agricultural water management. © 2021 Elsevier Inc. All rights reserved.
BIOCHEMICAL AND MOLECULAR CHARACTERIZATION OF NATIVE Bradyrhizobium STRAINS ISOLATED FROM PIGEON PEA ROOT NODULES OF EASTERN INDIA
(ACS Publisher, 2025) S. Dasaratha Kumar; Shiv Charan Kumar; Preeti Lata Singh; Umakant Banjare; Ashwani Kumar Upadhyay; Nootan Singh; Arun Kumar Patel; Shikha Yadav; Nitish Ranjan Prakash; Vishal K. Tyagi; Mona Nagargade; Ram Kumar Singh
Pigeon pea (Cajanus cajan) is a major legume in Eastern India, contributing to the nutritional security and soil fertility through symbiosis with Bradyrhizobium spp. However, the efficiency of native strains under local conditions remains poorly understood. This study aimed to isolate, characterize, and identify native isolates from pigeon pea root nodules, and to evaluate their symbiotic efficiency and plant growth-promoting traits. Fourteen bacterial isolates were obtained, of which 12 belonged to Bradyrhizobium spp., while isolates S5 and S15 were identified as Pseudomonas azotoformans and Paenibacillus amylolyticus, respectively. All Bradyrhizobium isolates tested positive for catalase, oxidase, nitrate reductase, and nitrogenase activity. Isolates S9, S3, S6, S13, and S1 showed significantly higher nitrogenase activity as compared to the other isolates. Plant growth-promoting assays revealed phosphate solubilisation, zinc solubilization, and potassium solubilization in ten, eight and five isolates, respectively. Eleven isolates produced siderophores and all of these synthesized indole-3-acetic acid (IAA). Notably, isolate S6 (Bradyrhizobium yuanmingense) exhibited all PGPR traits and high nitrogenase activity, identifying it as the most promising isolate. Isolates S3, S1, and S9 also demonstrated strong potential. These results demonstrated the value of efficient native isolates as region-specific bioinoculants for pigeon pea, reducing reliance on chemical fertilizers and promoting sustainable agriculture. © 2025, ACS Publisher. All rights reserved.
Classification of forest stands based on tree crown morphology and dimensions
(Elsevier, 2025) Pavan Kumar; Hukum Singh; Manoj Kumar; Aishwarya; Narine Hakobayan; Manish Srivastav; Ram Kumar Singh
Accurately classifying forest stands is vital for effective forest management, ecological research, and conservation. This research explores the classification of forest stands based on tree crown morphology and dimensions, aiming to find a reliable method for categorizing forest stands through detailed analysis of tree crown characteristics. Tree crowns—the top part of trees composed of branches and leaves—serve as key indicators of forest structure and health. By examining various morphological features and dimensions of tree crowns, including their shape, size, and density, our study presents a refined classification system applicable to diverse forest ecosystems. This research not only enhances our understanding of forest stand dynamics but also provides practical tools for forest management and biodiversity preservation. © 2026 Elsevier Inc. All rights reserved..
Common foods for boosting human immunity: A review
(John Wiley and Sons Inc, 2023) Deo Narayan Singh; Jitendra Singh Bohra; Tej Pratap Dubey; Pushp Raj Shivahre; Ram Kumar Singh; Tejbal Singh; Deepak Kumar Jaiswal
We are frequently exposed to potentially harmful microbes of various types on a daily basis. Our immune system is an amazing collection of unique organs and cells that defends us from hazardous germs as well as certain diseases. It plays a crucial role in protecting the body against external invaders, including bacteria, viruses, and parasites. Maintaining a healthy immune system requires consuming a balanced diet that provides a variety of macro- and micronutrients. By consuming sufficient amounts of water, minerals such as zinc and magnesium, micronutrients, herbs, and foods rich in vitamins C, D, and E, and adopting a healthy lifestyle, one can enhance their health and immunity, and prevent infections. This article provides a comprehensive review of the scientific literature on common foods known for their potential to boost human immunity. The review begins by discussing the various components of the immune system and their functions. It then delves into the current understanding of how nutrition can influence immune response, highlighting the importance of a well-balanced diet in supporting optimal immune function. The article presents an extensive analysis of a range of common foods that have been studied for their immune-boosting properties. These foods include fruits, vegetables, whole grains, and animal-based foods. Each food category is explored in terms of its specific nutrients and bioactive compounds that contribute to immune support. Foods such as milk, eggs, fruits, leafy greens, and spices like onion, garlic, and turmeric contain beneficial compounds that can enhance the immune system's function, activate and inhibit immune cells, and interfere with multiple pathways that eventually lead to improved immune responses and defense. The available literature on the issue was accessed via online resources and evaluated thoroughly as a methodology for preparing this manuscript. © 2023 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC.
Effect of trichoderma and hydrogel on growth, yield and yield attributes of direct seeded rice (Oryza sativa) under rainfed condition
(Indian Council of Agricultural Research, 2019) Avijit Sen; Ram Kumar Singh; Deshraj Yadaw; Puja Kumari; V.K. Srivastava; Pravin Kumar Upadhyay; Ardith Sankar; Jyotipraksh Mishra; Ajoy Das; Najam Waris Zaidi; Manzoor Hussain Dar
A trial was conducted both in field and pot during the kharif season of 2015 at Banaras Hindu University, India to study the effect of hydrogel in combination with bio-agent on the performance of rice under rainfed condition. The field trial consisting of IR64 and DRR42 and Trichoderma and hydrogel making 10 treatments altogether was laid out in a Randomized Complete Block Design (RCBD) while in case of pot it was a factorial experiment. DRR42 + hydrogel (seed coating)+Trichoderma (seed treatment @ 12 g/kg) recorded higher yield (2.83 t ha -1 ) which was 43.76% higher than control but it remained at par with IR64. In the pot experiment hydrogel (seed coating)+Trichoderma (seed treatment) and hydrogel soil application registered higher RGR, CGR, root length, root weight. Survival of plants after imposition of drought at 60 days after sowing (DAS) was also found to be longer under the same treatments. © 2019 Indian Council of Agricultural Research. All Rights Reserved.
Effect of Zinc, Iron and Manganese Levels on Quality, Micro and Macro Nutrients Content of Rice and Their Relationship with Yield
(Taylor and Francis Inc., 2017) Ashok Kumar; Avijit Sen; Pravin Kumar Upadhyay; Ram Kumar Singh
A field trial comprising three levels of zinc (Zn) 0, 5 and 10 kg ha-1, three levels of iron (Fe) 0, 15 and 30 kg ha-1 and three levels of manganese (Mn) 0, 5 and 10 kg ha-1 was carried out during the rainy seasons of 200 8 and 2009 at Varanasi, to study their effects on macro and micro nutrients content, yields and quality of rice variety HUBR 2–1. The experiment was conducted in 33 partial confounding with two replications. Half doses of all the micronutrients were applied as basal and the rest half through foliar application at different intervals. Among the treatments, Zn at 10 kg ha-1, iron at 15 kg ha-1 and Mn at 5 kg ha-1 recorded the maximum yield of rice. A similar trend was observed in all the quality parameters of rice. Individually Zn, Fe and Mn registered, respectively, 12.05, 8.60 and 4.46% more yield than the control. © 2017 Taylor & Francis.
Efficient Herbicide Delivery through a Conjugate Gel Formulation for the Mortality of Broad Leaf Weeds
(American Chemical Society, 2022) Reshu Bhardwaj; Om Prakash; Shivam Tiwari; Preeti Maiti; Sandipta Ghosh; Ram Kumar Singh; Pralay Maiti
Carfentrazone-ethyl is embedded in guar gum to prepare a polymer-herbicide conjugate gel formulation for a sustained release of the active ingredient (a.i.). The sprayable gel formulation was optimized at 0.5% (w/v) concentration. Strong interactions of the prepared composition of the polymer-herbicide conjugate system are shown through spectroscopic techniques, depicting the peak broadening of hydrophilic -OH bonds in the herbicide at 1743 cm-1, shifting to 1730 cm-1in the polymer-herbicide sample. There is a broadening and shifting of the peak at 329 nm for the n → π∗ transition at 335 nm in the polymer-herbicide conjugate system in UV spectra. Differential scanning calorimetric measurements show a lowering of endothermic melting peaks to 242 and 303 °C in the polymer-herbicide conjugate. X-ray diffraction studies showed a sharp diffraction peak of the pure polymer at a 2θ of ∼20.3°, while broadening and shifting of the peak position to a 2θ of ∼20.8° were observed after adding the herbicide. Diffusion of the active ingredient in the polymer-herbicide conjugate resulted in much greater coverage (most of the weed leaf stomata (>95%)) than conventional spraying. The efficacy of both the polymer-herbicide formulation and herbicide at different doses in weed nurseries showed significantly higher weed mortality in Anagallis arvensis (95.4%), Chenopodium album (∼97%), and Ageratum conyzoides (93.16%) treated with the polymer-herbicide formulation @ 20 g a.i. ha-1. Narrow SPAD readings range of A. arvensis (0.1-30.6) and that of C. album (0-5) were observed in the polymer-herbicide formulation @ 20 g a.i. ha-1was at par with the conventional formulation @ 30 g a.i. ha-1. Less regeneration in a weed nursery of A. arvensis (27%), C. album (77%), and A. conyzoides (49%) treated with gel formulations @ 20 g a.i. ha-1was observed, which was significantly lower than those in conventional herbicides. © 2022 American Chemical Society. All rights reserved.
Herbicide and irrigation management options in conventionally-tilled wheat: deciphering water and energy budgeting, and grain and monetary output in north-Indian plains
(Nature Research, 2025) Sunil Kumar Verma; Chandra Bhushan; Sudhir Kumar S. Rajpoot; Richa Chaudhary; Ramawatar Narayan Meena; Sanjeev K. Kashyap; Vijay Sai Pratap; Peeyush Kumar Jaysawal; Sukhchain B. Singh; Ram Kumar Singh; Deepak Kumar Yadav
In South Asia, declining water tables due to increased irrigation and labor shortages for manual weeding pose significant challenges for wheat production. Additionally, herbicide resistance, often resulting from poor management practices, further complicates weed problems. The objective of this study was to assess the impacts of traditional irrigation regimens (IRs) and herbicide application on wheat crops. The findings showed that when irrigation was applied at 100 mm CPE (IR4), and at 40 mm CPE (IR1), different combinations of herbicide to weed managment were tested. In comparison to the other treatments, application of irrigation at 40 mm cumulative pan evaporation (IR1) along with the Pendimethalin1000 g ha−1 (pre-em) in combination with clodinafop-propargyl 10% + metribuzin 22% + sulfosulfuron 4.2% at a rate of 1125 g ha−1 at 30 DAS (WM1) produced the best results in terms of crop yields, economic returns, relative water content, consumptive use, rate of water use, water use efficiency, water productivity, energy input–output, energy returns, energy productivity, energy intensity, specific energy, energy efficiency, maximum field capacity, available soil water, and soil profile moisture extraction pattern. The only exceptions were Pendimethalin1000g ha−1 (pre-em) combined with carfentrazone ethyl 20% + sulfosulfuron 25%WG), at the rate of 100 g ha−1 at 30 DAS (WM2) and the weed-free treatment (WM5), where the differences were not statistically significant. The yield of wheat grain (14.26 kg ha−1) and straw (14.41 kg ha−1) decreased as the unit dry matter production of weeds increased. The study recommends exploring additional weed control strategies and irrigation management options in future improve wheat yields in conventionally-tilled systems. © The Author(s) 2024.
Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology
(Nature Research, 2021) Ram Kumar Singh; Martin Drews; Manuel De la Sen; Prashant Kumar Srivastava; Bambang H. Trisasongko; Manoj Kumar; Manish Kumar Pandey; Akash Anand; S.S. Singh; A.K. Pandey; Manmohan Dobriyal; Meenu Rani; Pavan Kumar
The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections. © 2021, The Author(s).
Hydrogel-based Trichoderma formulation effects on different varieties of rice under rainfed condition of Indo-Gangetic Plains
(Springer Science and Business Media B.V., 2022) K. Dujeshwer; Ram Kumar Singh; Hanuman Singh Jatav; Rajendra Lakpale; Mujahid Khan; Vishnu D. Rajput; Tatiana Minkina
Increased global CO2 emissions may result in erratic weather conditions, especially uncertain, pertaining to rainfall uncertainties and temperature anomalies, and could reduce India’s overall rice production by 3–10% under medium- to high-emission scenarios. The water crises nowadays have been prioritized as one of the top five global risks. Further, the uncertainties in rice production due to climate change will be more than just rice yield reductions. Several adoption strategies such as direct seeding, selecting water stress-tolerant varieties, enhancing soil water-holding capacity and improving crop management practices, are suggested to address the risks of rice production. Keeping in view the above fact, a field experiment was initiated during kharif season of 2015 and 2016 at Agricultural Research Farm (BHU), Varanasi, Uttar Pradesh (India), to assess the effect of super-absorbent polymer (hydrogel) and Trichoderma in rice varieties with six hydrogel-based Trichoderma-formulated treatments. The results indicated that Trichoderma was found effective in improving crop growth, yield, nutrient uptake and water use efficiency with the application of hydrogel. It was also found that soil amendment with hydrogel at 2 g m−2 and sowing of Trichoderma-treated seed at 10 g kg−1 seed significantly improved the crop growth parameters (viz. shoot dry weight by 6.45%), yield parameters (viz. number of productive tillers by 12.32%, number of grains per panicle by 8.26%), nutrients uptake and water use efficiency (by 24.15%) over control. The present study reveals that the use of hydrogel with Trichoderma fungus is found effective in enhancing the growth and yield parameters of rice in Indo-Gangetic Plains (IGPs). © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
Model-based ensembles: Lessons learned from retrospective analysis of COVID-19 infection forecasts across 10 countries
(Elsevier B.V., 2022) Martin Drews; Pavan Kumar; Ram Kumar Singh; Manuel De La Sen; Sati Shankar Singh; Ajai Kumar Pandey; Manoj Kumar; Meenu Rani; Prashant Kumar Srivastava
Mathematical models of different types and data intensities are highly used by researchers, epidemiologists, and national authorities to explore the inherently unpredictable progression of COVID-19, including the effects of different non-pharmaceutical interventions. Regardless of model complexity, forecasts of future COVID-19 infections, deaths and hospitalization are associated with large uncertainties, and critically depend on the quality of the training data, and in particular how well the recorded national or regional numbers of infections, deaths and recoveries reflect the the actual situation. In turn, this depends on, e.g., local test and abatement strategies, treatment capacities and available technologies. Other influencing factors including temperature and humidity, which are suggested by several authors to affect the spread of COVID-19 in some countries, are generally only considered by the most complex models and further serve to inflate the uncertainty. Here we use comparative and retrospective analyses to illuminate the aggregated effect of these systematic biases on ensemble-based model forecasts. We compare the actual progression of active infections across ten of the most affected countries in the world until late November 2020 with “re-forecasts” produced by two of the most commonly used model types: (i) a compartment-type, susceptible–infected–removed (SIR) model; and (ii) a statistical (Holt-Winters) time series model. We specifically examine the sensitivity of the model parameters, estimated systematically from different subsets of the data and thereby different time windows, to illustrate the associated implications for short- to medium-term forecasting and for probabilistic projections based on (single) model ensembles as inspired by, e.g., weather forecasting and climate research. Our findings portray considerable variations in forecasting skill in between the ten countries and demonstrate that individual model predictions are highly sensitive to parameter assumptions. Significant skill is generally only confirmed for short-term forecasts (up to a few weeks) with some variation across locations and periods. © 2021 The Authors
Multi-level impacts of the COVID-19 lockdown on agricultural systems in India: The case of Uttar Pradesh
(Elsevier Ltd, 2021) Pavan Kumar; S.S. Singh; A.K. Pandey; Ram Kumar Singh; Prashant Kumar Srivastava; Manoj Kumar; Shantanu Kumar Dubey; Uma Sah; Rajiv Nandan; Susheel Kumar Singh; Priyanshi Agrawal; Akanksha Kushwaha; Meenu Rani; Jayanta Kumar Biswas; Martin Drews
When on March 24, 2020 the Government of India ordered a complete lockdown of the country as a response to the COVID-19 pandemic, it had serious unwanted implications for farmers and the supply chains for agricultural produce. This was magnified by the fact that, as typically in developing countries, India's economy is strongly based on farming, industrialization of its agricultural systems being only modest. This paper reports on the various consequences of the COVID-19 lockdown for farming systems in India, including the economy, taking into account the associated emergency responses of state and national governments. Combining quantitative and qualitative sources of information with a focus on the Indian state of Uttar Pradesh, including expert elicitation and a survey of farmers, the paper identifies and analyzes the different factors that contributed to the severe disruption of farming systems and the agricultural sector as a whole following the lockdown. Among other issues, our study finds that the lack of migrant labor in some regions and a surplus of workers in others greatly affected the April harvest, leading to a decline in agricultural wages in some communities and an increase in others, as well as to critical losses of produce. Moreover, the partial closure of rural markets and procurement options, combined with the insufficient supply of products, led to shortages of food supplies and dramatically increased prices, which particularly affected urban dwellers and the poor. We argue that the lessons learned from the COVID-19 crisis could fuel the development of new sustainable agro-policies and decision-making in response not only to future pandemics but also to the sustainable development of agricultural systems in India and in developing countries in general. © 2020 Elsevier Ltd
Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor
(Springer Science and Business Media B.V., 2024) Pavan Kumar; Aishwarya; Prashant Kumar Srivastava; Manish Kumar Pandey; Akash Anand; Jayanta Kumar Biswas; Martin Drews; Manmohan Dobriyal; Ram Kumar Singh; Manuel De la Sen; Sati Shankar Singh; Ajai Kumar Pandey; Manoj Kumar; Meenu Rani
There has been a long-lasting impact of the lockdown imposed due to COVID-19 on several fronts. One such front is climate which has seen several implications. The consequences of climate change owing to this lockdown need to be explored taking into consideration various climatic indicators. Further impact on a local and global level would help the policymakers in drafting effective rules for handling challenges of climate change. For in-depth understanding, a temporal study is being conducted in a phased manner in the New Delhi region taking NO2 concentration and utilizing statistical methods to elaborate the quality of air during the lockdown and compared with a pre-lockdown period. In situ mean values of the NO2 concentration were taken for four different dates, viz. 4th February, 4th March, 4th April, and 25th April 2020. These concentrations were then compared with the Sentinel (5p) data across 36 locations in New Delhi which are found to be promising. The results indicated that the air quality has been improved maximum in Eastern Delhi and the NO2 concentrations were reduced by one-fourth than the pre-lockdown period, and thus, reduced activities due to lockdown have had a significant impact. The result also indicates the preciseness of Sentinel (5p) for NO2 concentrations. © The Author(s), under exclusive licence to Springer Nature B.V. 2023.
Optimization of Process and Physico-Chemical Properties of Ready-to-Serve (RTS) Beverage of Cane Juice with Curd
(2012) Ram Kumar Singh; Alok Jha; Chandan Kumar Singh; Kanchan Singh
Sugarcane juice was extracted in the month of February from matured fresh sugarcane variety CoS 95255, which was raised using standard agronomical practices. Juice was extracted after though cleaning of cane stalks using standard methods. Cane juice from sugarcane variety was used in this study having 18.3-19.5 0brix total soluble solid (TSS), 0.13-0.18 % acidity, 6.05-6.16 mg/100 g ascorbic acid, 59.14-63.18 0brix sucrose, 5.1-5.4 pH and 4.36-5.43 0brix reducing sugar. The proportions of sugarcane juice with curd in the RTS beverage was optimized using various cane juice to curd proportions. Sugarcane juice with curd was preserved and packed in 200 ml glass bottles and kept for different storage periods (0, 5, 15 and 20 days). Beverages prepared from 4:1 proportion of juice: curd were found superior after 15 days of storage. © 2012 Society for Sugar Research & Promotion.
Performance of baby corn (Zea mays) under different fertility levels and planting methods and its residual effect on sorghum (Sorghum bicolor)
(Indian Society of Agronomy, 2015) Marwan Manea; Avijit Sen; Ashok Kumar; Pravin Kumar Upadhyay; Yashwant Singh; Vinod Kumar Srivastava; Ram Kumar Singh
A field trial was conducted at Varanasi during 2010–11 and 2011–12, to study the effect of fertility levels and planting methods on growth, yield, nutrient uptake and economics of baby corn (Zea mays L.) and its residual biomass incorporation effect on sorghum [Sorghum bicolor (L.) Moench]. The experiment was carried out in a spiltplot design with 4 replications. The main plots were allocated with fertility levels F0 (no fertilizer as control), F1 (75, 19.64, 37.35, 20 and 5), F2 (150, 39.28, 74.71, 40 and 10) and F3 (225, 46.76, 112.06, 60 and 15) kg/ha of N, P, K, S and Zn and sub-plots with combinations of 2 planting methods (flat bed and raised bed) and 2 varieties viz; (‘Pro-Agro 4212’ and ‘Sweet Corn Sugar 75’). Application of 225, 46.76, 112.06, 60 and 15 kg/ha of N, P, K, S and Zn fertility level significantly increased plant growth, yield, yield attributes and nutrient removal over rest of the treatments. Overall, this particular fertility level registered 55.0% more yield (without husk) than control. Among the sub-plot treatments raised bed planting recorded the highest plant height, leaf-area Index, dry-matter production, nutrient removal and registered 12.5% more baby corn yield (without husk) than flat bed, while ‘Pro-Agro 4212’ also recorded the same and registered 18.8% more baby corn yield (without husk) than Sweet Corn ‘Sugar 75’. Further, 225, 46.76, 112.06, 60 and 15 kg/ha fertility levels applied to previous crop increased the sorghum grain yield by (33.3%) over the control. © 2015 Indian Society of Agronomy. All rights reserved.
Potassium Simulation Using HYDRUS-1D with Satellite-Derived Meteorological Data under Boro Rice Cultivation
(MDPI, 2023) Ayushi Gupta; Manika Gupta; Prashant K. Srivastava; George P. Petropoulos; Ram Kumar Singh
Potassium (K) is a critical nutrient for crops, as it is a major constituent in fertilizer formulations. With increasing concentrations of K in agricultural soil, it is necessary to understand its movement and retention in the soil. Sub-surface modeling is an alternative method to overcome the exhausting and uneconomical methods to study and determine the actual concentration of K in soil. HYDRUS-1D is considered an effective finite-element model which is suitable for sub-surface modeling. This model requires the input of ground-station meteorological (GM) data taken at a daily timestep for the simulation period. It can be a limiting factor in the absence of ground stations. The study compares K predictions in surface and sub-surface soil layers under Boro rice cultivation obtained with the usage of different meteorological datasets. Thus, the main hypothesis of the study was to validate that, in the absence of GM data, satellite-based meteorological data could be utilized for simulating the K concentration in soil. The two meteorological datasets that are considered in the study included the GM and satellite-derived NASA-Power (NP) meteorological datasets. The usage of a satellite meteorological product at a field scale may help in applying the method to other regions where GM data is not available. The numerical model results were validated with field experiments from four experimental fields which included varied K doses. The concentration in soil was assessed at the regular depths (0–5, 5–10, 10–15, 15–30, 30–45 and 45–60 cm), and at various stages of crop growth, from bare soil and sowing, to the tillering stages. The concentration of K was measured in the laboratory and also simulated through the optimized model. The modeled values were compared with measured values statistically using relative root mean square error (RMSER) and Nash–Sutcliffe modeling efficiency (E) for simulating K concentration in the soil for the Boro rice cropping pattern with both GM data and NP data. The model was found most suitable for the 0–30 cm depth on all days and for all treatment variations. © 2023 by the authors.
Scientific validation of indigenous organic formulation-panchagavya for sustaining rice productivity and residual effect in rice-lentil system under hot semi-arid eco-region of middle indo-gangetic plains
(National Institute of Science Communication and Information Resources (NISCAIR), 2019) Pravin Kumar Upadhyay; Avijit Sen; Sanjay Singh Rathore; Bipin Kumar; Ram Kumar Singh; Saroj Kumar Prasad; Ardith Sankar
Combined application of organic source of nutrient and inorganic fertilizers increases nutrient synchrony and reduces losses leading to sustainable productivity. With this concept in mind a field trial was conducted at Varanasi, India during 2013–14 and 2014–15, to evaluate and validate the efficiency and efficacy of panchagavya (blend of five cow products i.e. dung, ghee, curd, urine and milk) in combination with recommended doses of fertilizers (RDF) on rice yield, soil microbial population, soil microbial biomass carbon (SMBC), soil enzymatic activity and their residual effects on lentil. Application of panchagavya (D4-seedling root dip + one spray at 30 days after transplanting-DAT @ 6% + application through irrigation water at 60 DAT) produced higher productive tillers/m2, number of filled spikelets/panicle, leaf area index (LAI), grain yield, soil bacterial and fungal population, SMBC and dehydrogenase activity. Application of 100% RDF significantly increased grain yield (5935 kg/ha) but 120% RDF recorded the highest straw yield (8283 kg/ha) and biological yield. Residual effect of panchagavya at D4 level resulted in higher (19.1% over control) seed yield of lentil. However, conjunctive use of 100% RDF and D4 ensured maximum net return (1194.9 $/ha).Therefore, use of indigenous product i.e. panchagavya in combination with fertilizer can be inferred to improve soil health, ascertain high productivity, profitability and sustainability in rice-lentil production, while preserving natural resource base under hot semi-arid eco-region of middle Indo-Gangetic Plains (IGP). © 2019, National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.
Short-term statistical forecasts of COVID-19 infections in India
(Institute of Electrical and Electronics Engineers Inc., 2020) Ram Kumar Singh; Martin Drews; Manuel de la Sen; Manoj Kumar; Sati Shankar Singh; Ajai Kumar Pandey; Prashant Kumar Srivastava; Manmohan Dobriyal; Meenu Rani; Preeti Kumari; Pavan Kumar
COVID-19 cases in India have been steadily increasing since January 30, 2020 and have led to a government-imposed lockdown across the country to curtail community transmission with significant impacts on societal systems. Forecasts using mathematical-epidemiological models have played and continue to play an important role in assessing the probability of COVID-19 infection under specific conditions and are urgently needed to prepare health systems for coping with this pandemic. In many instances, however, access to dedicated and updated information, in particular at regional administrative levels, is surprisingly scarce considering its evident importance and provides a hindrance for the implementation of sustainable coping strategies. Here we demonstrate the performance of an easily transferable statistical model based on the classic Holt-Winters method as means of providing COVID-19 forecasts for India at different administrative levels. Based on daily time series of accumulated infections, active infections and deaths, we use our statistical model to provide 48-days forecasts (28 September to 15 November 2020) of these quantities in India, assuming little or no change in national coping strategies. Using these results alongside a complementary SIR model, we find that one-third of the Indian population could eventually be infected by COVID-19, and that a complete recovery from COVID-19 will happen only after an estimated 450 days from January 2020. Further, our SIR model suggests that the pandemic is likely to peak in India during the first week of November 2020. © This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
Soil Health, Energy Budget, and Rice Productivity as Influenced by Cow Products Application With Fertilizers Under South Asian Eastern Indo-Gangetic Plains Zone
(Frontiers Media S.A., 2022) Pravin Kumar Upadhyay; Avijit Sen; Yashwant Singh; Ram Kumar Singh; Saroj Kumar Prasad; Ardith Sankar; Vinod Kumar Singh; S.K. Dutta; Rakesh Kumar; Sanjay Singh Rathore; Kapila Shekhawat; Subhash Babu; Rajiv Kumar Singh; Bipin Kumar; Abir Dey; G.A. Rajanna; Ramesh Kulshekaran
The comprehensive use of organic, inorganic, and biological components of nutrient management in rice ecologies can potentially address the twin challenges of declining factor productivity and deteriorating soil health. A field study was thus conducted at Varanasi, India during the year 2013–14 and 2014–15 to assess the effect of the recommended dose of fertilizers (RDF) along with cow product (blends of 5 cow by-products i.e., dung, ghee, curd, urine, and milk that is known as panchagavya) on soil health, energy budget, and rice productivity. The results revealed that the inclusion of panchagavya as seedling root dip + 6% spray at 30 days after transplanting (DAT) + an application with irrigation water (15 l ha−1) at 60 DAT (D4) along with 100% RDF (F3) noted significantly higher rice grain yield (6.34 t ha−1) and higher dehydrogenase activity. However, the soil bacterial and actinomycetes population, soil microbial biomass carbon (SMBC), urease, and alkaline phosphatase activities were significantly higher with D4 along with 120% RDF (F4). Carbon output (5,608 kg CO2 eq ha−1), energy use parameters viz. energy output (187,867 MJ ha−1), net energy returns (164,319 MJ ha−1), and energy intensity valuation (5.08 MJ (Figure presented.)) were significantly higher under F4. However, the energy ratio (8.68), energy productivity (0.292 kg MJ−1), and energy profitability (7.68) remained highest with 80% RDF (F2), while the highest carbohydrate equivalent yield (4,641 kg mha−1) was produced under F3. The combination of F3 with D4 resulted in the highest productivity, optimum energy balance, and maintaining soil quality. Therefore, a judicious combination of cow product (panchagavya) with RDF was found to improve the rice productivity, energy profitability, and soil quality under south Asian eastern Indo-Gangetic Plains (IGPs). Copyright © 2022 Upadhyay, Sen, Singh, Singh, Prasad, Sankar, Singh, Dutta, Kumar, Rathore, Shekhawat, Babu, Singh, Kumar, Dey, Rajanna and Kulshekaran.