- Delhi, Delhi, India
Plant disease has long been one of the major threats to world food security due to reduction in the crop yield and quality. Accurate and precise diagnosis of plant diseases has been a significant challenge. Cost-effective automated... more
Plant disease has long been one of the major threats to world food security due to reduction in the crop yield and quality. Accurate and precise diagnosis of plant diseases has been a significant challenge. Cost-effective automated computational systems for disease diagnosis would facilitate advancements in agriculture. The objective of this paper is to explore computer vision based Artificial Intelligence method for automating the identification of yellow rust disease and improve the accuracy of plant disease identification. The dataset of 2000 images of wheat leaf were collected in the real life experimental conditions of ICAR-Indian Agricultural Research Institute, New Delhi in the crop season during January-April, 2019. Based on our experiment, we propose a deep learning-based approach to detect healthy leaves and yellow rust infected leaves in the wheat crop. The experiments are implemented in python with PyCharm IDE, utilizing the Keras deep learning library backend with Tenso...
Research Interests:
Crop phenology monitoring is a necessary action for precision agriculture. Sentinel-1 and Sentinel-2 satellites provide us with the opportunity to monitor crop phenology at a high spatial resolution with high accuracy. The main objective... more
Crop phenology monitoring is a necessary action for precision agriculture. Sentinel-1 and Sentinel-2 satellites provide us with the opportunity to monitor crop phenology at a high spatial resolution with high accuracy. The main objective of this study was to examine the potential of the Sentinel-1 and Sentinel-2 data and their combination for monitoring sugarcane phenological stages and evaluate the temporal behaviour of Sentinel-1 parameters and Sentinel-2 indices. Seven machine learning models, namely logistic regression, decision tree, random forest, artificial neural network, support vector machine, naïve Bayes, and fuzzy rule based systems, were implemented, and their predictive performance was compared. Accuracy, precision, specificity, sensitivity or recall, F score, area under curve of receiver operating characteristic and kappa value were used as performance metrics. The research was carried out in the Indo-Gangetic alluvial plains in the districts of Hisar and Jind, Haryan...
Research Interests:
Background Price forecasting of perishable crop like vegetables has importance implications to the farmers, traders as well as consumers. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby... more
Background Price forecasting of perishable crop like vegetables has importance implications to the farmers, traders as well as consumers. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. The farmers can use the information to make choices around the timing of marketing. For forecasting price of agricultural commodities, several statistical models have been applied in past but those models have their own limitations in terms of assumptions. Methods In recent times, Machine Learning (ML) techniques have been much successful in modeling time series data. Though, numerous empirical studies have shown that ML approaches outperform time series models in forecasting time series, but their application in forecasting vegetables prices in India is scared. In the present investigation, an attempt has been made to explore efficient ML algorithms e.g. Generalized Neural Network (GRNN), Support...
Research Interests:
Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven agro-climatic zones of India was studied in addition to development of forecast models with their comparisons on performance. Considering the... more
Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven agro-climatic zones of India was studied in addition to development of forecast models with their comparisons on performance. Considering the non-normal and nonlinear nature of time series data of spiders, non-parametric techniques were applied with developed algorithm based on combinations of wavelet–regression and wavelet–artificial neural network (ANN) models. Haar wavelet filter decomposed each of the series to extract the actual signal from the noisy data. Prediction accuracy of developed models, viz., multiple regression, wavelet–regression, and wavelet–ANN, tested using root mean square error (RMSE) and mean absolute percentage error (MAPE), indicated better performance of wavelet–ANN model. Diebold Mariano (DM) test also confirmed that the prediction accuracy of wavelet–ANN model, and hence its use to forecast spiders in conjunction with the values of pest–defender ratios, would n...
Research Interests:
Research Interests:
Most of the educational institutes nowadays benefited from the hidden knowledge extracted from the datasets of their students, instructors and educational settings. The education system has gone through a paradigm shift from a traditional... more
Most of the educational institutes nowadays benefited from the hidden knowledge extracted from the datasets of their students, instructors and educational settings. The education system has gone through a paradigm shift from a traditional system to smart learning environments and from a teacher-centric system to context-aware any time anywhere student-centric approach. In this changing scenario, we have undertaken a study to investigate the results, grades and patterns of the students of North Lakhimpur College. The paper aims to evaluate the quality of learning on the basis of 19249 grades received from 758 students in 511 courses, included in the curriculum of 3 study programmes.
Research Interests:
The analysis of production and area under okra (Abelmoschus esculentus Linn.) in India showed a perceptible trend in growing preference of okra crops among farmers. There is a decline in growth rate of yield of okra. The analysis also... more
The analysis of production and area under okra (Abelmoschus esculentus Linn.) in India showed a perceptible trend in growing preference of okra crops among farmers. There is a decline in growth rate of yield of okra. The analysis also showed that though there is a steady increase in the area as well in production under okra crops. The growth rate as well as forecasting from 2017–18 to 2020–21 showed the increasing trend. Graphical representation also showed the increasing trend of okra.
Research Interests:
The present study provides several contamination and ecological risk indices for selected metals (Cd, Cr, Cu, Mn, Ni and Zn) in tea (Camellia sinensis L.; cv. S.3A/3) growing soil influenced by lower to higher doses of inorganic and... more
The present study provides several contamination and ecological risk indices for selected metals (Cd, Cr, Cu, Mn, Ni and Zn) in tea (Camellia sinensis L.; cv. S.3A/3) growing soil influenced by lower to higher doses of inorganic and organic amendments. While ecological risk indices were applied, it was observed that same treatment showed different risk levels but contamination risk status did not vary significantly. All the indices showed significant correlation with heavy metals' concentration in young shoots of tea plants. As the indices characterized experimental soils with different extents of contamination, it would be important to standardize the indices with long term experiments followed by generation of new index. Therefore, we formulated a new contamination index named as Tea Research Association Heavy Metal Contamination Index (TRAHMCI) for tea growing soils. TRAHMCI is based on the probable change of metal status in soil with progress of growth of tea plant. This cou...
Research Interests:
Research Interests:
Tea (Camellia sinensis L.) is a perennial acidophilic crop, and known to be a non-alcoholic stimulating beverage that is most widely consumed after water. The aim of this review paper is to provide a detailed documentation of selected... more
Tea (Camellia sinensis L.) is a perennial acidophilic crop, and known to be a non-alcoholic stimulating beverage that is most widely consumed after water. The aim of this review paper is to provide a detailed documentation of selected micronutrient contents, viz. boron (B), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), molybdenum (Mo) and zinc (Zn) in made tea and tea infusion. Available data from the literature were used to calculate human health aspect associated with the consumption of tea infusion. A wide range of micronutrients reported in both made tea and tea infusion could be the major sources of micronutrients for human. The content of B, Co, Cu, Fe, Mn, Mo and Zn in made tea are ranged from 3.04 to 58.44 μg g(-1), below detectable limit (BDL) to 122.4 μg g(-1), BDL to 602 μg g(-1), 0.275 to 13040 μg g(-1), 0.004 to 15866 μg g(-1), 0.04 to 570.80 μg g(-1) and 0.01 to 1120 μg g(-1), respectively. Only 3.2 μg L(-1) to 7.25 mg L(-1), 0.01 μg L(-1) to 7 μg L(-1), 3.80 μg L(-1) to 6.13 mg L(-1), 135.59 μg L(-1)-11.05 mg L(-1), 0.05 μg L(-1) to 1980.34 mg L(-1), 0.012 to 3.78 μg L(-1) and 1.12 μg L(-1) to 2.32 μg L(-1) of B, Co, Cu, Fe, Mn, Mo and Zn respectively are found in tea infusion which are lower than the prescribed limit of micronutrients in drinking water by World Health Organization. Furthermore, micronutrient contents in tea infusion depends on infusion procedure as well as on the instrument used for analysis. The proportion of micronutrients found in different tea types are 1.0-88.9% for B, 10-60% for Co, 2.0-97.8% for Cu, 67.8-89.9% for Fe, 71.0-87.4% for Mn, 13.3-34% for Mo and 34.9-83% for Zn. From the results it can also be concluded that cosumption of three cups of tea infusion per day does not have any adverse effect on human health with respect to the referred micronutrients rather got benifical effects to human.
Research Interests:
Application of municipal solid waste compost (MSWC) in tea (Camellia sinensis L.) cultivation can increase the fertility status of soils and thus enhance the plant growth. The present study attempts at application of MSWC in tea (TV1 and... more
Application of municipal solid waste compost (MSWC) in tea (Camellia sinensis L.) cultivation can increase the fertility status of soils and thus enhance the plant growth. The present study attempts at application of MSWC in tea (TV1 and TV23 clones) cultivation to assess the effect of different doses of MSWC on growth and translocation potential of Al on this plant as well as fate of Al in soil, through the calculation of a risk assessment code (RAC). The sequential extraction of Al in MSWC amended soils showed that the fractionation of Al in soil changed after compost application, with an overall increase of the fractions associated to with Fe-Mn oxides, organic and of the residual fraction. The accumulation of Al in different parts ofC. sinensisL., grown on MSWC amended soil effected an overall increased growth of the plant with increasing doses of MSWC. According to RAC, Al falls in medium to high risk, though no adverse effect on plant health was observed. Tea plants were found...
Research Interests:
Research Interests:
In the present paper, horizontal and vertical integration was carried out on the wholesale and retail prices of wheat in the major markets of India. On confirming cointegration between the wholesale and retail prices of wheat in all... more
In the present paper, horizontal and vertical integration was carried out on the wholesale and retail prices of wheat in the major markets of India. On confirming cointegration between the wholesale and retail prices of wheat in all needs, the vector error correction model (VECM) was applied to find the speed of adjustment in the corresponding price channel. The results revealed that price signals are transmitted across regions, indicating that price changes in one market are consistently related to price changes in markets and can influence the prices in other markets. In addition to studying cointegration, threshold autoregressive (TAR) and Momentum TAR (MTAR) models were applied to test for asymmetric cointegration. Hasen and Seo’s test was used to test for the presence of threshold cointegration. It revealed a significant presence of asymmetric and nonlinear cointegration in many markets. Accordingly, a threshold VECM (TVECM) model with two regimes was applied. The results indic...
Research Interests:
Research Interests:
The current study aims to assess the infusion pattern of three important micronutrients namely copper (Cu), iron (Fe), and zinc (Zn) contents from black tea samples produced in Assam (India) and Thohoyandou (South Africa). Average daily... more
The current study aims to assess the infusion pattern of three important micronutrients namely copper (Cu), iron (Fe), and zinc (Zn) contents from black tea samples produced in Assam (India) and Thohoyandou (South Africa). Average daily intakes and hazardous quotient were reported for these micronutrients. Total content for Cu, Fe, and Zn varied from 2.25 to 48.82 mg kg(-1), 14.75 to 148.18 mg kg(-1), and 28.48 to 106.68 mg kg(-1), respectively. The average contents of each of the three micronutrients were higher in tea leaves samples collected from South Africa than those from India while the contents in tea infusions in Indian samples were higher than in South African tea samples. Results of this study revealed that the consumption of 600 mL tea infusion produced from 24 g of made tea per day may be beneficial to human in terms of these micronutrients content. Application of nonparametric tests revealed that most of the data sets do not satisfy the normality assumptions. Hence, th...
ABSTRACT A study was taken up to understand the major chemical properties of tea (Camellia sinensis L.) growing soils at Dibrugarh and Tinsukia districts in the state of Assam, India. Altogether 991 surface soil samples were collected and... more
ABSTRACT A study was taken up to understand the major chemical properties of tea (Camellia sinensis L.) growing soils at Dibrugarh and Tinsukia districts in the state of Assam, India. Altogether 991 surface soil samples were collected and analyzed from 15 large tea estates (TEs). Soil pH ranged from 3.61 to 6.8. Total organic carbon and total nitrogen ranged from 0.237 to 4.73 % and 0.024 to 0.360% respectively. All soils were sufficiently rich in plant-available K (as K2O) which ranged from 127.71 to 252.33 mg kg -1, since the amount prescribed for optimum tea yield is > 100 mg kg-1. Plant-available S among soil samples widely varied from 4 mg kg-1 to 129 mg kg-1. Relationship between variables were studied with Pearson’s correlation analysis. A multivariate technique like Hierarchical clustering analysis was applied for homogenous grouping of different TEs based on soil chemical parameters and it is observed that the 15 TEs could be classified in three distinct groups. The three groups consist of 6, 8 and 1 TEs respectively. Based on Kolmogorov-Smirnov (K-S) test, nineteen best fitted theoretical probability distributions were found out for different soil chemical properties.
Research Interests:
Research Interests:
AbstractBy means of the ARCH (Auto-regressive Conditional Heteroscedasticity) and its modified models, this paper presents an empirical analysis of the volatility heteroscedasticity and the resilience to external shocks for China... more
AbstractBy means of the ARCH (Auto-regressive Conditional Heteroscedasticity) and its modified models, this paper presents an empirical analysis of the volatility heteroscedasticity and the resilience to external shocks for China emerging stock market in the past three years based on the ...
Research Interests:
Research Interests:
Although, compost is the store house of different plant nutrients, there is a concern for low amount of major nutrients especially nitrogen content in prepared compost. The present study deals with preparation of compost by using... more
Although, compost is the store house of different plant nutrients, there is a concern for low amount of major nutrients especially nitrogen content in prepared compost. The present study deals with preparation of compost by using agricultural wastes with struvite (MgNH4PO4·6H2O) along with termite mound. Among four composting mixtures, 50kg termite mound and 2.5kg struvite with crop residues (stover of ground nut: 361.65kg; soybean: 354.59kg; potato: 357.67kg and mustard: 373.19kg) and cow dung (84.90kg) formed a good quality compost within 70days of composting having nitrogen, phosphorus and potassium as 21.59, 3.98 and 34.6gkg(-1), respectively. Multivariate analysis of variance revealed significant differences among the composts. The four composts formed two (pit 1, pit 2 and pit 3, pit 4) different groups. Two principal components expressed more than 97% of the total variability. Hierarchical cluster analysis resulted two homogeneous groups of composts.
Research Interests: Soil, Agriculture, Multidisciplinary, Animals, Isoptera, and 3 moreIndustrial Waste, Phosphates, and Maturity
Research Interests:
... Indian lac export data Himadri Ghosh, Ranjit Kumar Paul and Prajneshu ∗ ... 2.1. The model Functional-coefficient autoregressive (FCAR) nonparametric nonlinear time-series model, introduced by Chen and Tsay [4], admits the form Xt =... more
... Indian lac export data Himadri Ghosh, Ranjit Kumar Paul and Prajneshu ∗ ... 2.1. The model Functional-coefficient autoregressive (FCAR) nonparametric nonlinear time-series model, introduced by Chen and Tsay [4], admits the form Xt = a1(Xt−d)Xt−1 + ... + ap(Xt−d)Xt−p + εt (1) ...
Research Interests:
Modeling and forecasting of India’s spices export data, which exhibits a volatile behavior, is first attempted through the Box-Jenkins autoregressive integrated moving average (ARIMA) approach. Subsequently, generalized autoregressive... more
Modeling and forecasting of India’s spices export data, which exhibits a volatile behavior, is first attempted through the Box-Jenkins autoregressive integrated moving average (ARIMA) approach. Subsequently, generalized autoregressive conditional heteroscedastic (GARCH) nonlinear time-series models along with their estimation procedures are thoroughly studied. The Lagrange multiplier test for testing the presence of autoregressive conditional heteroscedastic (ARCH) effects is also discussed. The GARCH model is employed for modeling and forecasting of the data. A comparative study of the fitted ARIMA and GARCH models is carried out from the viewpoint of dynamic one-step ahead forecast error variance along with the mean square prediction error (MSPE), mean absolute prediction error (MAPE) and relative mean absolute prediction error (RMAPE). The SAS and EViews, Ver. 4, software packages, along with computer programs in C are used for data analysis. Superiority of the GARCH model over t...
Research Interests:
Effect of Municipal solid waste compost (MSWC) application on tea (Camellia sinensis L.) cultivation (TV1 and TV23 clones) was studied with respect to biomass yield, soil nickel (Ni) risk, Ni uptake and transfer to tea infusion.... more
Effect of Municipal solid waste compost (MSWC) application on tea (Camellia sinensis L.) cultivation (TV1 and TV23 clones) was studied with respect to biomass yield, soil nickel (Ni) risk, Ni uptake and transfer to tea infusion. Application of MSWC @ 2 to 6 t ha-1 in Ni contaminated soil lowered the risk assessment code by increasing non-labile Ni pool. Reduced Ni translocation factor from root to stem to leaf led to low Ni accumulation in leaf indicating high Ni tolerance ability of tea. Tea infusions from TV1 and TV23 clones with soil MSWC application up to 10 t ha-1 showed leaf Ni contents below permissible limit i.e. non-detectable to 1.2 μg L-1 and 0.01 to 1.1 μg L-1 respectively. MSWC could therefore be a valuable alternative for soil amendment subject to non-enhancement of soil Ni storage on long-term use. The one-way analysis of variance along with Duncan’s multiple range tests showed significant differences between pair of treatments. Hierarchical cluster analysis revealed ...
Research Interests:
Research Interests:
ABSTRACT
Research Interests:
Research Interests:
ABSTRACT
Research Interests:
Although, compost is the store house of different plant nutrients, there is a concern for low amount of major nutrients especially nitrogen content in prepared compost. The present study deals with preparation of compost by using... more
Although, compost is the store house of different plant nutrients, there is a concern for low amount of major nutrients especially nitrogen content in prepared compost. The present study deals with preparation of compost by using agricultural wastes with struvite (MgNH4PO4·6H2O) along with termite mound. Among four composting mixtures, 50kg termite mound and 2.5kg struvite with crop residues (stover of ground nut: 361.65kg; soybean: 354.59kg; potato: 357.67kg and mustard: 373.19kg) and cow dung (84.90kg) formed a good quality compost within 70days of composting having nitrogen, phosphorus and potassium as 21.59, 3.98 and 34.6gkg(-1), respectively. Multivariate analysis of variance revealed significant differences among the composts. The four composts formed two (pit 1, pit 2 and pit 3, pit 4) different groups. Two principal components expressed more than 97% of the total variability. Hierarchical cluster analysis resulted two homogeneous groups of composts.
Research Interests: Soil, Agriculture, Multidisciplinary, Animals, Isoptera, and 3 moreIndustrial Waste, Phosphates, and Maturity
Amongst Asian countries India is one of the most vulnerable countries to climate change. During the past century, surface temperature in India has shown a significant increasing trend. In this paper, we have investigated behavior of mean... more
Amongst Asian countries India is one of the most vulnerable countries to climate change. During the past century, surface temperature in India has shown a significant increasing trend. In this paper, we have investigated behavior of mean monthly temperature during the period 1901-2001 over four agroclimatic zones of India and also tried to detect structural change in the temperature series. A structural break in the series has been observed at the national as well regional levels between 1970 and 1980. An analysis of trends before and after the structural break shows a significant increase in July temperature in the arid zone since 1972.
Research Interests:
Accelerated solvent extraction (ASE) is applied for the extraction of carotenoids from orange carrot and the extraction parameters were optimized. Two carotenoids, lutein and β-carotene, are selected as the validation process. Hildebrand... more
Accelerated solvent extraction (ASE) is applied for the extraction of carotenoids from orange carrot and the extraction parameters were optimized. Two carotenoids, lutein and β-carotene, are selected as the validation process. Hildebrand solubility parameters and dielectric constant of solvents were taken into consideration in selecting solvent mixture. The effects of various experimental parameters, such as temperature, static time, drying agent etc., on the ASE extraction efficiency are investigated systematically. Interactions among the variables were also studied. Furthermore, two carotenoids were analyzed and characterized by LC-ESI MS. The study concluded that Hildebrand solubility parameter approach may be applicable for less polar bioactive molecules like carotenoids. The properties of solvent and extraction temperature are found to be the most important parameters affecting the ASE extraction efficiency of thermolabile natural compounds.
Research Interests:
ABSTRACT A study was taken up to understand the major chemical properties of tea (Camellia sinensis L.) growing soils at Dibrugarh and Tinsukia districts in the state of Assam, India. Altogether 991 surface soil samples were collected and... more
ABSTRACT A study was taken up to understand the major chemical properties of tea (Camellia sinensis L.) growing soils at Dibrugarh and Tinsukia districts in the state of Assam, India. Altogether 991 surface soil samples were collected and analyzed from 15 large tea estates (TEs). Soil pH ranged from 3.61 to 6.8. Total organic carbon and total nitrogen ranged from 0.237 to 4.73 % and 0.024 to 0.360% respectively. All soils were sufficiently rich in plant-available K (as K2O) which ranged from 127.71 to 252.33 mg kg -1, since the amount prescribed for optimum tea yield is > 100 mg kg-1. Plant-available S among soil samples widely varied from 4 mg kg-1 to 129 mg kg-1. Relationship between variables were studied with Pearson’s correlation analysis. A multivariate technique like Hierarchical clustering analysis was applied for homogenous grouping of different TEs based on soil chemical parameters and it is observed that the 15 TEs could be classified in three distinct groups. The three groups consist of 6, 8 and 1 TEs respectively. Based on Kolmogorov-Smirnov (K-S) test, nineteen best fitted theoretical probability distributions were found out for different soil chemical properties.
Research Interests:
ABSTRACT The nature of selected soil-chemical and microbial properties influenced by tsunami affected and non-affected areas along the border areas of the alluvial Andaman Island in India were investigated. Soils of these areas have... more
ABSTRACT The nature of selected soil-chemical and microbial properties influenced by tsunami affected and non-affected areas along the border areas of the alluvial Andaman Island in India were investigated. Soils of these areas have turned saline and saline-sodic due to the ingression of sea water. The electrical conductivity of the saturation extract of the surface soil varied from 11.2 to 23.8 dS m−1 in 2005, and it was decreased to 0.8–10.3 dS m−1 in 2006 due to the heavy rain in the following year after the tsunami. Soil quality indicators, like microbial biomass C, microbial metabolic quotient, microbial respiration quotient and fluorescein diacetate hydrolyzing activity, decreased in the tsunami affected soil in 2005, but slightly increased in 2006. All microbial parameters were significantly negatively correlated with the electrical conductivity, sodium absorption ratio and exchangeable sodium percentage. Suppression of microbial biomass and their activities in the soils due to the increased-salinity is of great agronomic significance and needs suitable intervention for sustainable crop production. Significant differences were found in soil-chemical and microbial characteristics between tsunami affected and non-affected areas. Hierarchical clustering algorithm on the basis of different soil-chemical and microbial characteristics revealed that there is significant difference in grouping between tsunami affected and non-affected zones. From this study, it can be concluded that the sea water ingression detrimentally influenced the microbial properties of tsunami affected soil.
Research Interests:
ABSTRACT Major chemical properties of tea-growing soils are of paramount importance for better management in a sustainable fashion. Therefore, this study was carried out to understand the major soil chemical properties of major tea... more
ABSTRACT Major chemical properties of tea-growing soils are of paramount importance for better management in a sustainable fashion. Therefore, this study was carried out to understand the major soil chemical properties of major tea (Camellia sinensis L.)-growing areas, Dibrugarh and Tinsukia districts, in the state of Assam, India. A total of 991 surface soil samples were collected from 15 large tea estates (TEs) for analysis of their major chemical properties. Soil pH ranged from 3.61 to 6.81. Total organic carbon and total nitrogen ranged from 2.4 to 47.3 and 0.24 to 3.60 g kg−1, respectively. All soils were sufficiently rich in plant-available potassium (as K2O), which ranged from 127.71 to 252.33 mg kg−1, exceeding the amount prescribed for optimum tea yield of ≥ 100 mg kg−1. Plant-available sulfur among soil samples widely varied from 4 to 129 mg kg−1. Results of hierarchical clustering analysis for homogenous grouping of the 15 TEs based on soil chemical properties showed that the 15 TEs could be classified into three distinct groups which consisted of 6, 8 and 1 TEs, respectively. Based on the Kolmogorov-Smirnov (K-S) test, the best fitted theoretical probability distributions were found out for different soil chemical properties. It could be concluded that a balanced fertilizer application would be needed as a part of tea improvement program using soil chemical test.