Browsing by Author "Anand Prakash Singh"

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Effect of 2,4-D on the formation and germination of akinetes in Pithophora oedogonia (mont.) Wittrock
(2009) Anand Prakash Singh; B.R. Chaudhary
Pithophora oedogonia (Mont.) Wittrock (1877), the filamentous green alga was studied by several workers, and contradictory reports exist on spore formation and spore germination in this alga (cf. Agrawal and Sarma, 1983 & Agrawal and Chaudhary, 1988). The present study aims at evaluating the impact of the herbicide 2, 4-Dichlorophenoxy acetic acid (2, 4-D) on the sporulation and akinete germination with a view to evolving strategy for the control of this algal weed causing nuisance in natural water bodies. The study revealed that 2, 4-D at concentrations ranging from 0.1-20 ppm in BBM nutrient solution or agarized medium, the initiation of sporulation showed progressive delay with concomitant decrease in the germination of akinetes. 2, 4-D at and above 30 ppm conc. proved lethal to the alga inhibiting spore formation and germination of the akinetes already developed.
Effect of phosphorus application on arsenic species accumulation and co-deposition of polyphenols in rice grain: Phyto and food safety evaluation
(MDPI AG, 2021) Arghya Chattopadhyay; Anand Prakash Singh; Deepak Kasote; Indrajit Sen; Ahmed Regina
The present study was aimed at exploring the effect of soil application of different concentrations of orthophosphate (P) (0, 10, 20, 30, and 40 mg kg−1 ) on rice agronomic and yield parameters, arsenic (As) species accumulation, and polyphenol levels in the grain of rice grown under As spiked soil (10 mg kg−1 ). The contents of As species (As(V), As (III), MMA and DMA) and polyphenols in rice grain samples were estimated using LC-ICP-MS and LC-MS/MS, respectively. P treatments significantly reduced the toxic effects of As on agronomic parameters such as root weight and length, shoot and spike length, straw, and grain yield. Among the treatments studied, only the treatment of 30 mg kg−1 P helps to decrease the elevated levels of As (V), As (III), and DMA in rice grains due to As application. The study revealed that 30 mg kg−1 was the optimal P application amount to minimize AS accumulation in rice grains and As-linked toxicity on agronomic parameters and chlorophyll biosynthesis. Furthermore, the levels of trans-ferulic acid, chlorogenic acid, caffeic acid, and apigenin-7-glucoside increased in response to accumulation of As in the rice grain. In conclusion, the precise use of phosphorus may help to mitigate arsenic linked phytotoxicity and enhance the food safety aspect of rice grain. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Impact assessment of coal mining induced subsidence on native soil of South Eastern Coal Fields: India
(Springer Science and Business Media Deutschland GmbH, 2020) Ashish Kumar Vishwakarma; Tusarkanta Behera; Rajesh Rai; Ashwani Kumar Sonkar; Anand Prakash Singh; Bal Krishna Shrivastva
Understanding the consequences of mining is most important in order to prevent negative outcomes for the environment as natural systems are used by humans for agriculture/silviculture. The present manuscript deals with the impact of subsidence due to underground coal mining on native soil. Depth-wise changes in soil texture and nutrient components in four layers; 0–15 cm, 16–30 cm, 31–45 cm and 46–60 cm were quantified along the subsidence prone land of the study area in top (within the extension zone; Zone I), middle (within inner-edge zone; Zone II) and bottom (around centre of the subsidence trough; Zone III) of a three and half year mining subsided land and compared it with soil texture and nutrient component status of an adjacent undamaged zone (UZ). An alteration in the Physicochemical characteristics of the soil after subsidence was observed. It had a positive impact on most of the soil characteristic parameters at Zone III. Available nitrogen, phosphorous and potassium (AN, AP and AK) were increased by 13.00%, 44.47% and 26.7%, respectively in 0–15 cm layer; 16.42%, 45.12% and 28.08%, respectively in 16–30 cm layer; 15.74%, 47.45% and 22.97%, respectively in 31–45 cm layer and 14.86%, 38.94% and 18.53%, respectively in 46–60 cm layer. A significant increase in silt + clay content, organic carbon and electrical conductivity were also reported. © 2020, Springer Nature Switzerland AG.
Microbial genes involved in interaction with plants
(Elsevier, 2018) Chandra Bali Patel; Vivek Kumar Singh; Anand Prakash Singh; Mukesh Meena; R.S. Upadhyay
Although microbes are quite small in size and invisible to naked eyes, they play significantly huge role compared to bigger organisms. The most important factors behind this significant and indispensable role are the genes present in the bacterial cell. The genes and gene products of bacterial cells provide them the ability to survive in almost every environmental condition whether favorable or unfavorable. In a strict sense, bacterial cells interact with other organisms for their own benefit, but the ultimate result is either beneficial or harmful to plants and human beings. Nitrogen fixation is one of the most significant phenomena of nature, with an annual nitrogen fixation of about 175 million tons. This huge amount of nitrogen fixation is carried out by the nif gene. Another important aspect of bacterial interaction with plant is the transfer of genes of interest to the plant cell by Agrobacterium tumefaciens. © 2019 Elsevier B.V. All rights reserved.
Soil carbon dynamics in relation to soil surface management and cropping system
(Springer Singapore, 2019) Anand Prakash Singh; Satish Kumar Singh; Sumit Rai; Maneesh Kumar
A high soil organic matter content is synonymous with high-quality agricultural soils, as it affects many soil processes such as microbial activity, nutrient storage and release, water retention and soil aggregate formation. Due pressure on agricultural intensification with improved and science-based technology imposed a challenge to increase agricultural production without accentuating risks of greenhouse gas (GHG) emissions, hence affecting the terrestrial carbon balance, which has been a research focus for more than a half-century. Agricultural practices including soil surface management, crop rotation, residue and tillage management, fertilization, and monoculture affect soil quality, soil organic matter (SOM), and carbon transformation. Consequently, soil surface management practices and cropping system have a major effect on the distribution of C and N and the rates of organic matter decomposition and N mineralization. © Springer Nature Singapore Pte Ltd. 2020.
Spatial variability of arsenic in Indo-Gangetic basin of Varanasi and its cancer risk assessment
(Elsevier Ltd, 2020) Arghya Chattopadhyay; Anand Prakash Singh; Satish Kumar Singh; Arijit Barman; Abhik Patra; Bhabani Prasad Mondal; Koushik Banerjee
The Indo-Gangetic alluvium is prime region for intensive agricultural. In some areas of this region, groundwater is now becoming progressively polluted by contamination with poisonous substances like arsenic. Intensive irrigation with arsenic contaminated ground water in dry spell results in the formation of As(III) which is more toxic. Thus groundwater quality assessment of Gangetic basin has become essential for its safer use. Therefore we under took study on the spatial variability of arsenic by collecting georeferred groundwater samples on grid basis from various water sources like dug well, bore and hand pumps covering the river bank region of Ganga basin. Water quality was investigated through determination pH, EC, TDS, salinity, Na, K, Ca, Mg, SAR, SSP, CO3, HCO3, RSC, Cl, As, Fe, Zn, Mn and Cu, etc. Results pointed severe As contamination in ground water of three sites of the study area. ARC GIS software is now able to process maps along with tabular data and compare them well, to provide the spatial visualization of information and using this tool, the Geographical Information System (GIS) of arsenic was developed. It was noticed from spatial maps that concentration of arsenic was more near the meandering points of Ganga. © 2019 Elsevier Ltd
The machine learning and geostatistical approach for assessment of arsenic contamination levels using physicochemical properties of water
(IWA Publishing, 2023) Arghya Chattopadhyay; Anand Prakash Singh; Siddharth Kumar; Jayadeep Pati; Amitava Rakshit
Arsenic contamination in groundwater due to natural or anthropogenic sources is responsible for carcinogenic and non-carcinogenic risks to humans and the ecosystem. The physicochemical properties of groundwater in the study area were determined in the laboratory using the samples collected across the Varanasi region of Uttar Pradesh, India. This paper analyses the physicochemical properties of water using machine learning, descriptive statistics, geostatistical and spatial analysis. Pearson correlation was used for feature selection and highly correlated features were selected for model creation. Hydrochemical facies of the study area were analyzed and the hyperparameters of machine learning models, i.e., multilayer perceptron, random forest (RF), naïve Bayes, and decision tree were optimized before training and testing the groundwater samples as high (1) or low (0) arsenic contamination levels based on the WHO 10 μg/L guideline value. The overall performance of the models was compared based on accuracy, sensitivity, and specificity value. Among all models, the RF algorithm outclasses other classifiers, as it has a high accuracy of 92.30%, a sensitivity of 100%, and a specificity of 75%. The accuracy result was compared to prior research, and the machine learning model may be used to continually monitor the amount of arsenic pollution in groundwater. © 2023 The Authors.