Browsing by Author "Seema"

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Application of VIS-NIR spectroscopy for estimation of soil organic carbon using different spectral preprocessing techniques and multivariate methods in the middle Indo-Gangetic plains of India
(Elsevier B.V., 2020) Seema; A.K. Ghosh; B.S. Das; N. Reddy
Soil organic carbon (SOC) is the main source of soil nutrients, which are essential for the growth and development of agricultural crops. Precise and quick quantification of SOC is of utmost importance in crop husbandry and soil health/carbon sequestration quantification. In order to evaluate visible and near-infrared diffuse reflectance spectroscopy (VIS-NIR) as an alternative to precise and quick method of quantification of SOC in the Indo-Gangetic plains, 280 soil samples were collected covering Inceptisols, Entisols and Alfisols and their spectra recorded. Six preprocessing techniques ((reflectance, absorbance, multiplicative scatter correction (MSC), standard normal variate (SNV), Savitzky–Golay smoothing first derivative (SG-FD) and Savitzky–Golay smoothing second derivative (SG-SD)) and four multivariate methods (partial least-squares regression (PLSR), random forest (RF), support vector regression (SVR) and multivariate adaptive regression splines (MARS)) were evaluated to predict SOC from VIS-NIR spectra. The considerable prediction accuracy and robustness were achieved using the PLSR model (RV2 = 0.73, RMSEV = 0.07, and RPDV = 1.90), RF model (RV2 = 0.69, RMSEV = 0.07, and RPDV = 1.74), SVR model (RV2 = 0.57, RMSEV = 0.08), and RPDV = 1.50), and MARS model (RV2 = 0.63, RMSEV = 0.10, and RPDV = 1.05). Findings from this study identified the reliability of SOC determinations by examining how preprocessing techniques and multivariate methods affect spectral analyses. © 2020 Elsevier B.V.
Changes in degree of phosphorus saturation and risk of P loss upon twelve years of manuring and reduced tillage
(Elsevier B.V., 2021) Satya Narayana Pradhan; A.K. Ghosh; Seema; Shankar Ram; Yogesh Pal; Chandini Pradhan
Adoption of minimum tillage and application of fertilizer integrated with farmyard manure in the long-term has been envisaged to sustain rice-based cropping systems in the Indo-Gangetic plains of India. However, substitution of mineral fertilizer based on crop N requirement results not only in increase of the total P load but also in the distribution of P fractions and soil properties that influence P adsorption. A twelve year old experiment consisting of two tillage (conventional, CT and minimum, MT tillage) and three fertilization treatments (100% inorganic fertilization, IF, 100 and 50% organic fertilization, OF) was examined to unravel the relationship between tillage and manuring effects on distribution of soil P forms vis-à-vis soil test P and how it relates to degree of P saturation (DPS). Reduced tillage intensity and organic fertilization resulted in increase of all P fractions and soluble P. Olsen-P varied from 3.4 to 59.4 mg kg−1 and was exponentially (NH4F-P/NaOH-P) or linearly (Occ-P/H2SO4-P) related to P fractions by direct or indirect effects. Increase in pH and total organic carbon coupled with increase in P load especially in OF and MT treatments resulted in decrease in the P maximum adsorption capacity (PMAC) and P bonding energy of the soil. Consequently, the degree of phosphorus saturation increased with decrease in PMAC and a change point was noted at 13.62% DPS above which soluble P increased more rapidly. Olsen P, which is used as an index of P availability, increased with reduction of tillage and organic manure addition and was closely associated with all the P fractions and DPS. The Olsen P at the change point DPS was 50.4 mg kg−1 which indicated risk of P losses and hence could be used as an index for risk assessment and identify soils that need to be managed agronomically and environmentally to avoid P losses to the environment. © 2021 Elsevier B.V.
Characterization and classification of alluvium derived soils under different land uses in varanasi district of Uttar Pradesh
(IndianJournals.com, 2019) Seema; A.K. Ghosh
[No abstract available]
Characterization and fertility assessment of soils of chandauli district of eastern uttar pradesh for sustainable land use planning
(Indian Council of Agricultural Research, 2020) Seema; A.K. Ghosh; Sunita Yadav
Seven typical pedons representing major landforms in semi-arid and sub-tropical ecosystem of Chandauli district of Uttar Pradesh, viz. plains, mid lands and uplands developed from alluvium parent material under varying land uses were studied for their morphological characteristics, physical and chemical properties and soil classification. The colour of the soils ranged from light brown grey to brownish yellow red with a dominant hue of 10YR. These soils were acidic to moderately alkaline (pH 4.8 to 8.4) in reaction, non-saline, moderately deep to very deep and had isohyperthermic temperature and udic soil moisture regime. Texture and total organic carbon (TOC) ranged from silty loam to silty clay loam and 0.1 to 29.7 kg/ha respectively. Soils were medium in phosphorus (6.8 to 24.2 kg/ha) and available potassium (159 to 376 kg/ha ). All the pedons had ochric epipedon and underlain by cambic horizon (PI to P4) within the control section and as such they come under order Inceptisols, whereas profile 5 to profile 7 have argillic horizon so they come under order Alfisols. All soils of the study area fall in agricultural land under land capability classes III and IV having limitations of slope and erosion. On the basis of major soil constraints and potentials, suitable land use plan has been suggested. © 2020 Indian Council of Agricultural Research. All rights reserved.
Characterization and Fertility Assessment of Soils of Mirzapur District of Eastern Uttar Pradesh for Sustainable Land Use Planning
(Indian journals, 2021) Seema; A.K. Ghosh; Sunita Yadav; Preeti Singh; Aradhana Thakur
Ten typical pedons representing major landforms in semi-arid and sub-tropical ecosystem of Mirzapur district of Uttar Pradesh viz., plains, mid lands and uplands developed from alluvium parent material under varying land uses were studied for their morphological characteristics, physical and chemical properties and soil classification. The colour of the soils ranged from light brown grey to brownish yellow and dark brown with a dominant hue of 10YR. These soils were acidic to moderately alkaline (pH 6.0 to 8.6) in reaction, non-saline, moderately deep to very deep and had isohyperthermic temperature and udic soil moisture regime. Texture and total organic carbon (TOC) ranged from loam to clay loam and 0.3 to 19.9 g kg-1, respectively. Soils were lower to medium range in phosphorus (4.0 to 18.0 kg ha-1) and available potassium (96 to 299 kg ha-1). All the pedons had ochric epipedon and underlain by cambic horizon (P3, P4, P7, P8, P9 and P10) within the control section and as such they come under order Inceptisols whereas P1, P2, P5 and P6 have argillic horizon so they come under order Alfisols. All soils of the study area fall in agricultural land under land capability classes III and IV having limitations of slope and erosion. On the basis of major soil constraints and potentials, suitable land use plan has been suggested. © 2021, Indian journals. All rights reserved.
Deterministic and geostatistical models for predicting soil organic carbon in a 60 ha farm on Inceptisol in Varanasi, India
(Elsevier B.V., 2021) Biswabara Sahu; Amlan Kumar Ghosh; Seema
Soil organic carbon (SOC) is the regulatory soil property for soil fertility. The SOC status and its variability pattern can be studied through spatial interpolation techniques. In the current study we compared deterministic (Inverse Distance Weightage, IDW), geostatistical (spherical and exponential kriging (OK) and Empirical Bayesian Kriging, EBK) and Machine Learning (Random Forest, RF, Support Vector Machine, SVM) method for samples collected at four grid spacings (20, 40, 60 and 80 m) to find out the combination of best interpolation method and sample spacing to produce a variability map for SOC. Geostatistical models with corresponding highest R2 (31.9%), Lin CCC (0.49) and Pearson Correlation Coefficient (0.57) performed better than deterministic and machine learning models. A more precise prediction technique of geostatistical methods than deterministic interpolation may be due to differences in weightage calculation technique and a higher biasness in terms of Mean Error associated with IDW as compared to EBK. The presence of higher local uncertainty and lack of auxiliary supporting parameters e.g., crop and nutrient management) made ML (R2 19.4%, 21.7% in case of RF and SVM respectively) to be a poor predictor than EBK. Among the six interpolation methods, EBK was found to be the best interpolation method in each sample grid spacing [31.9% (p < 0.001), 10.5% (p < 0.01), 13.5% (p < 0.01), 10.5% (p < 0.05)]. Better simulation technique of variogram generation through EBK makes it the best fit model among the three geostatistical techniques. A 20 m grid spacing was found to be the best minimum spacing for studying SOC at a small scale as a higher density sampling could better capture the variability pattern of a heterogenous field having moderate autocorrelation. High local variability and lack of covariates have resulted in poor performance of ML as compared to kriging. However, the prediction performance of models can be improved by using covariate data which has a high correlation with soil properties combined with intense sampling in regions of high variability. © 2021 Elsevier B.V.
Effect of nitrogen and poultry manure on yield and nutrients uptake by maize (Zea mays)
(Indian Council of Agricultural Research, 2019) Sunita Yadav; Ramawatar Meena; Seema; Sandeep Kumar; D.K. Sharma
From this study we can conclude that significantly increase the yield of maize due to integrated nitrogen management could be further attributed to increased growth and vigour of plant as evident from increased growth attributes. So, the treatment combinations (T10) of 125 kg/ ha Nitrogen through inorganics plus 10 t/ha poultry manure through organics were having significant difference as compared to all other. This might be due to ready supply of nutrients through inorganic in the initial stages of crop growth and slow release of nitrogen and steady supply of other nutrients over an extended period of crop growth by organics. Organics have a priming effect on the release of nitrogen from inorganic fertilizer. Moreover, thoroughly decomposed organics were used in these treatments which might have mobilized native nutrients from soils. Poultry manure showed higher yield and yield attributing characters due to faster mineralization of nitrogen with its narrow C:N ratio (15:1-20:1) as evident by its chemical composition. The proper dose of poultry manure can be used as a source of organic manure for sustainable maize production. © 2019 Indian Council of Agricultural Research. All rights reserved.
Evaluation of ground water quality and health risk assessment due to nitrate and fluoride in the Middle Indo-Gangetic plains of India
(Bellwether Publishing, Ltd., 2020) Jitendra Maurya; Satya Narayana Pradhan; Seema; A.K. Ghosh
Fluoride and nitrate are the most widespread toxic pollutant elements present in groundwaters in large parts of India. The study assessed the groundwater quality and non-carcinogenic health risk due to fluoride and nitrate. Groundwaters were alkaline in reaction with the predominance of sulfate > bicarbonate > chloride > nitrate > fluoride. About 83.8% of the samples were poor in water quality and 77 and 93% of the samples had nitrate and fluoride content above the permissible limit for drinking. Principal component analysis suggested that alkaline pH of groundwater was due to presence of high bicarbonate and low calcium concentration (resulting from precipitation of calcium as calcium carbonate), that also favored release of fluoride. Cluster analysis indicated a common source of anions and cations (Na, Ca and Cl) and the influence of anthropogenic activities in groundwater nitrate contamination; but a geogenic source for fluoride and the influence of alkaline water on weathering of fluoride bearing minerals. The hazard quotient for infant, children and adults due to nitrate was 2.8, 2.19 and 2.0 and due to fluoride was 3.39, 2.64 and 2.42 respectively and 99% of the samples were above the cumulative hazard index implicating that groundwater was unsafe for drinking. © 2020 Taylor & Francis Group, LLC.
Rapid Prediction of Soil Electrical Conductivity in the Middle Indo-Gangetic Plains of India
(Indian journals, 2025) Seema; Amlan Kumar Ghosh; Preeti Lata Singh; Rekha Sodani; Shalini Sharma; Satya Narayana Pradhan; Biswabara Sahu
Salts in the root zone have high spatial variability, change rapidly and adversely affect soil quality and crop productivity. In contrast to the time-intensive traditional methods for measuring electrical conductivity (EC), visible-near infrared (Vis-NIR) and mid-infrared (MIR) spectroscopy provide faster alternatives that can assist in creating strategies to reduce negative impacts on soil and plants. Soils were collected from the Indo-Gangetic Plains and analysed for EC1:2.5 using conventional method. There was a wide variation in EC measured by the conventional method. So Partial Least Squares Regression (PLSR) was used to predict soil EC from spectral data, with the data divided into calibration (70%) and validation (30%) datasets. The partial least square regression (PLSR), random forest (RF), support vector regression (SVR) and multivariate adaptive regression splines (MARS) both in Vis-NIR and MIR region during calibration. The predictive performance of PLSR, RF, SVR, and MARS models for EC1:2.5 in the Vis-NIR range showed PLSR as the best model (R² = 0.84, RMSE = 0.21, RPD = 2.44). In the MIR range, RF was considered fairly good (R² = 0.52, RMSE = 0.20, RPD = 1.43). Vis-NIR spectroscopy with PLSR algorithm predicted EC better than MIR spectroscopy and would be the method of choice for rapid estimation and prediction of EC in the study region. © 2025, Indian journals. All rights reserved.
Regional soil organic carbon prediction models based on a multivariate analysis of the Mid-infrared hyperspectral data in the middle Indo-Gangetic plains of India
(Elsevier B.V., 2022) Seema; A.K. Ghosh; Kuntal Mouli Hati; Nishant Kumar Sinha; Nilimesh Mridha; Biswabara Sahu
Soil organic carbon (SOC) sequestration provides an opportunity to mitigate climate change impacts, since soils are the largest store of terrestrial carbon. Accurate estimates of SOC content across landscapes are therefore important to monitor and manage efficiently these SOC stocks. Mid-infrared (MIR) spectroscopy has been increasingly applied as a rapid, cost-effective, and accurate method for predictive soil analysis. This study assessed the performance of MIR spectroscopy for SOC prediction at a regional scale in the Indo-Gangetic plains, 280 soil samples were collected covering Inceptisols, Entisols and Alfisols and their spectra recorded. Five preprocessing techniques ((absorbance, multiplicative scatter correction (MSC), standard normal variate (SNV), Savitzky–Golay smoothing first derivative (SG-FD) and Savitzky–Golay smoothing second derivative (SG-SD)) and four multivariate methods (partial least-squares regression (PLSR), random forest (RF), support vector regression (SVR) and multivariate adaptive regression splines (MARS)) were evaluated to predict SOC from MIR spectra. The considerable prediction accuracy and robustness were achieved using the PLSR model (RV2 = 0.78, RMSEV = 0.04, and RPDV = 2.07), RF model (RV2 = 0.65, RMSEV = 0.09, and RPDV = 1.01), SVR model (RV2 = 0.65, RMSEV = 0.09, and RPDV = 1.12), and MARS model (RV2 = 0.67, RMSEV = 0.09, and RPDV = 1.20). Findings from this study identified the reliability of SOC determinations by examining how preprocessing techniques and multivariate methods affect spectral analyses. © 2022 Elsevier B.V.
Revegetating Mine Soils with Different Tree Species Influences Molecular Characteristics of Soil Organic Matter
(Taylor and Francis Ltd., 2024) Preeti Singh; A.K. Ghosh; Santosh Kumar; Manoj Kumar; Sunita Yadav; Mona Nagargade; Seema
Although molecular characterization of soil organic carbon is crucial for understanding its dynamics, studies on reclaimed coal mine soil are comparatively limited. Therefore, the primary objective of this study was to ascertain the influence of tree species on the soil organic carbon content and molecular characteristics of soil organic carbon in a chronosequence of reclaimed coal mine soil. To investigate the effects of reclamation time on soil organic carbon characteristics, a chronosequence of three coal mine soil was used, each exhibiting different ages of reclamation: 8, 14, and 25 years. Along a re-vegetation age gradient of 8 to 25 years, the total soil organic carbon content increased. Within the 25 years of restored soil, the FTIR absorption intensities were lowest within the range of 2,920 and 2,850 cm−1, while they were highest within the range of 1,685, 1,425, and 1,285 cm−1which indicates presence of aromatic C=C. This shows that aromatic compounds contributed more significantly to the composition of soil organic carbon compared to aliphatic structures. Based on molecular characteristics, it is suggested that the soil organic carbon in 25-year old revegetated coal mine soil consists of aromatic and recalcitrant carbon. Among three tree species Dalbergia sissoo can be used for reclamation as quality and quantity of carbon found was higher under this tree species. In conclusion, the results indicated that the molecular properties of soil organic carbon were extremely important for understanding the dynamics of soil organic carbon in a restored coal mine soil chronosequence. © 2024 Taylor & Francis Group, LLC.
Spatial variability of soil properties of Mirzapur district of Uttar Pradesh
(Indian Council of Agricultural Research, 2020) Seema; A.K. Ghosh; Aradhanathakur; Sunita Yadav
To assess the chemical characterization of soils of Mirzapur District of Uttar Pradesh, the present investigation was undertaken using GPS and GIS techniques. In this study, 625 georeferenced soil samples were collected from different block of Mirzapur following random sampling approach in month of September-Decmber 2018. The soil samples were analyzed for different chemical parameters and the data along with GPS reading were used for the preparation of soil thematic maps using interpolation method and the interpolated maps were analysed with geostatistical parameters and the corresponding kriging maps for pH, electrical conductivity (EC), soil organic carbon (SOC), and available nitrogen, phosphorus, potassium and cationic micronutrients (Zn, Fe, Cu, Mn of cations) were prepared. The soil thematic maps clearly shown that a major area of the Mirzapur was alkaline, non-saline, low in OC, medium in available Potassium. The mean content of soil pH, EC, Organic Carbon, available Nitrogen, phosphorus and Potassium in surface soils were 7.5, 0.09 dS/m, 5.4 g/ kg, 128.08, 37.01 and 338.65 kg/ha respectively. © 2020 Indian Council of Agricultural Research. All rights reserved.
Suitability of zinc-enriched spinach (Spinacea oleracea L.) for human consumption
(IndianJournals.com, 2017) Seema; R. Meena; R. Sodani; Sunita Yadav; S.S. Jatav; S.P. Goswami
Zinc (Zn) is one of the essential micronutrients for human beings, and its deficiency affects the health adversely. At the same time, excessive intake of Zn may cause several physiological diseases and disorders. Hence, risk to human health from intake of Zn-enriched spinach (Spinacea oleracea L.) was assessed in terms of hazard quotient (HQ). In a pot culture experiment, spinach was grown on soil treated with four levels of Zn (0, 5, 20 and 40 mg Zn kg-1) and three levels of organics (control, 3% farmyard manure and 3% poultry manure). Results indicated that Zn content in first cutting of spinach was 66.0 to 152.9 mg kg-1 across the treatments with a mean value of 99.9 mg kg-1. Similar kind of enrichment was recorded in case of second cutting. A substantial increase in daily dietary intake of Zn through consumption of this leafy green vegetable was projected by application of Zn along with organics. The values of HQ varied from 0.05 to 0.11 and 0.07 to 0.17 for first cutting and second cutting, respectively. For intake of Zn through consumption of this vegetable, soil application of Zn up to 20 mg kg-1 was considered safe taking 0.5 as guide value of HQ. © 2017, IndianJournals.com. All rights reserved.