Ranjit Paul | Indian Agricultural Statistics Research Institute (original) (raw)

Papers by Ranjit Paul

Research paper thumbnail of Automating yellow rust disease identification in wheat using artificial intelligence

The Indian Journal of Agricultural Sciences

Plant disease has long been one of the major threats to world food security due to reduction in t... 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 paper thumbnail of Machine Learning Techniques for Phenology Assessment of Sugarcane Using Conjunctive SAR and Optical Data

Remote Sensing

Crop phenology monitoring is a necessary action for precision agriculture. Sentinel-1 and Sentine... 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 paper thumbnail of Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India

PLOS ONE

Background Price forecasting of perishable crop like vegetables has importance implications to th... 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 paper thumbnail of Wavelet Decomposition and Machine Learning Technique for Predicting Occurrence of Spiders in Pigeon Pea

Agronomy

Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven a... 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 paper thumbnail of Forecasting of Price of Rice in India Using Long-Memory Time-Series Model

National Academy Science Letters, 2020

Price forecasting of agricultural commodities plays an important role in efficient planning and f... more Price forecasting of agricultural commodities plays an important role in efficient planning and formulation of executive decisions. In this study, an attempt has been made to apply autoregressive fractionally integrated moving average (ARFIMA) model to the daily all India maximum, minimum and modal wholesale price data of rice in order to capture the observed long-run persistency. The price series under consideration are stationary, but there is a significant presence of long memory in the price data. Accordingly, ARFIMA model is applied to obtain the forecasts and window-based evaluation of forecasting is carried out with the help of relative mean absolute percentage error, root mean square error and mean absolute error. To this end, a comparative study has also been made between the best fitted ARFIMA model and the best fitted ARIMA model and it is observed that ARFIMA model outperforms the usual ARIMA model.

Research paper thumbnail of Exploring Student Academic Performance Using Data Mining Tools

International Journal of Emerging Technologies in Learning (iJET), 2020

Most of the educational institutes nowadays benefited from the hidden knowledge extracted from th... 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 paper thumbnail of Analysis of trend in area, production and productivity of okra (Abelmoschus esculentus) in India

Current Horticulture, 2019

The analysis of production and area under okra (Abelmoschus esculentus Linn.) in India showed a p... 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 paper thumbnail of Paradigm shift of contamination risk of six heavy metals in tea (Camellia sinensis L.) growing soil: A new approach influenced by inorganic and organic amendments

Journal of hazardous materials, Jan 22, 2017

The present study provides several contamination and ecological risk indices for selected metals ... 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 paper thumbnail of Agricultural Trade Structure and Linkages in SAARC: An Empirical Investigation

Agricultural Economics Research Review, 2015

Since regional associations and free trade are perceived to be welfare-enhancing, this paper has ... more Since regional associations and free trade are perceived to be welfare-enhancing, this paper has examined the structure and flow of trade among SAARC economies. The study has revealed that India alone accounts for 74 per cent of the agricultural exports from the region and 55 per cent of the agricultural imports of the region. Cotton, cereals, fish & crustaceans, and tea & beverages have emerged as the most exported commodities accounting for more than 50 per cent share of exports from SAARC countries to the world. Animal or vegetable fat, cotton and rubber are the most imported commodities by SAARC. India enjoys comparative advantage in exports of cotton, cereals, fish and tea, while Pakistan has a greater comparative advantage in export of cotton and cereals. A unidirectional causality has been observed between gross domestic product (GDP) and agricultural exports, where agricultural exports Granger cause GDP and not vice versa. A one-way causal relationship has also been observed between agricultural GDP and agricultural exports. This indicates that growth in agricultural exports has contributed to the overall and agricultural growth in India. The study has suggested that Indian trade policy environment needs to be made more favourable for attracting foreign buyers and making Indian exports competitive globally.

Research paper thumbnail of Micronutrients (B, Co, Cu, Fe, Mn, Mo, and Zn) content in made tea (Camellia sinensisL.) and tea infusion with health prospect: A critical review

Critical Reviews in Food Science and Nutrition, 2015

Tea (Camellia sinensis L.) is a perennial acidophilic crop, and known to be a non-alcoholic stimu... 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 paper thumbnail of Aluminium dynamics from soil to tea plant (Camellia sinensis L.): is it enhanced by municipal solid waste compost application?

Chemosphere, 2015

Application of municipal solid waste compost (MSWC) in tea (Camellia sinensis L.) cultivation can... 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 paper thumbnail of How Price Signals in Pulses are Transmitted across Regions and Value Chain? Examining Horizontal and Vertical Market Price Integration for Major Pulses in India

Agricultural Economics Research Review, 2016

The paper has applied time series model to investigate the wholesale and retail price market inte... more The paper has applied time series model to investigate the wholesale and retail price market integration of major pulses (tur, gram, moong, urad, masoor) in five major regions namely north zone (NZ), south zone (SZ), east zone (EZ), west zone (WZ) and north east zone (NEZ) in the country based on their volume of production. The study has shown that there exists a strong cointegration among the wholesale as well as retail prices of these major pulses, although the cointegration varies. In addition to the horizontal cointegration, the vertical cointegration between the wholesale and retail prices of different pulses has also been investigated. Different causal relationships have been found between wholesale and retail prices in these five zones. The application of vector error correction model (VECM) has indicated that all the error correction terms (ECTs) are negative and most of these terms are statistically significant, implying that the system once in dis-equilibrium tries to come back to the equilibrium situation. The study has also used Impulse response analysis which shows that change in wholesale prices of these five pulses in one zone will cause change in wholesale prices in other zones. The paper has concluded that price signals are transmitted across regions indicating that price changes in one zone are consistently related to price changes in other zones and are able to influence the prices in other zones. However, the direction and intensity of price changes may be affected by the dynamic linkages between the demand and supply of pulses. The study has provided an interesting insight for policy makers, and for contributing to improve the information precision to predict the price movements used by marketing operators for their strategies and by policy makers for designing the suitable marketing strategies to bring more efficiency across the markets.

Research paper thumbnail of Asymmetric Price Transmission: A Case of Wheat in India

Agriculture, 2022

In the present paper, horizontal and vertical integration was carried out on the wholesale and re... 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 paper thumbnail of Statistical modelling for forecasting of wheat yield based on weather variables

The Indian Journal of Agricultural Sciences, 2013

Research paper thumbnail of Comparative Assessment of Copper, Iron, and Zinc Contents in Selected Indian (Assam) and South African (Thohoyandou) Tea (Camellia sinensis L.) Samples and Their Infusion: A Quest for Health Risks to Consumer

Biological trace element research, Jan 23, 2016

The current study aims to assess the infusion pattern of three important micronutrients namely co... 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...

Research paper thumbnail of Robust Analysis of Block Designs: A New Objective Function

Research paper thumbnail of M-estimation in block designs

Research paper thumbnail of Major Soil Chemical Properties of Upper Assam: the Worldwide Fascinating Tea (Camellia sinensis L.) Producing Region in India

Pedosphere, Mar 13, 2014

ABSTRACT A study was taken up to understand the major chemical properties of tea (Camellia sinens... 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 paper thumbnail of An Empirical Investigation of Arima and Garch Models in Agricultural Price Forecasting

Economic Affairs, 2014

The present study deals with time series models which are non-structural-mechanical in nature. Th... more The present study deals with time series models which are non-structural-mechanical in nature. The Box Jenkins Autoregressive integrated moving average (ARIMA) and Generalized autoregressive conditional heteroscedastic (GARCH) models are studied and applied for modeling and forecasting of spot prices of Gram at Delhi market. Augmented Dickey Fuller (ADF) test is used for testing the stationarity of the series. ARCH-LM test is used for testing the volatility. It is found that ARIMA model cannot capture the volatility present in the data set whereas GARCH model has successfully captured the volatility. Root Mean square error (RMSE), Mean absolute error (MAE) and Mean absolute prediction error (MAPE) were computed. The GARCH (1,1) was found to be a better model in forecasting spot price of Gram. The values for RMSE, MAE and MAPE obtained were smaller than those in ARIMA (0,1,1) model. The AIC and SIC values from GARCH model were smaller than that from ARIMA model. Therefore, it shows that GARCH is a better model than ARIMA for estimating daily price of Gram. production and marketing decisions and to the policy makers for administering commodity proGrams and assessing market impacts of domestic or international events. Monitoring commodity price can play a major role on the overall macroeconomic performance of a country. Therefore, the commodity price forecast is a key input to macroeconomic policy planning and formulation.

Research paper thumbnail of Autoregressive Conditional Heteroscedastic (Arch) Family of Models for Describing Volatility

Abstract—By means of the ARCH (Auto-regressive Conditional Heteroscedasticity) and its modified m... more Abstract—By 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 paper thumbnail of Automating yellow rust disease identification in wheat using artificial intelligence

The Indian Journal of Agricultural Sciences

Plant disease has long been one of the major threats to world food security due to reduction in t... 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 paper thumbnail of Machine Learning Techniques for Phenology Assessment of Sugarcane Using Conjunctive SAR and Optical Data

Remote Sensing

Crop phenology monitoring is a necessary action for precision agriculture. Sentinel-1 and Sentine... 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 paper thumbnail of Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India

PLOS ONE

Background Price forecasting of perishable crop like vegetables has importance implications to th... 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 paper thumbnail of Wavelet Decomposition and Machine Learning Technique for Predicting Occurrence of Spiders in Pigeon Pea

Agronomy

Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven a... 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 paper thumbnail of Forecasting of Price of Rice in India Using Long-Memory Time-Series Model

National Academy Science Letters, 2020

Price forecasting of agricultural commodities plays an important role in efficient planning and f... more Price forecasting of agricultural commodities plays an important role in efficient planning and formulation of executive decisions. In this study, an attempt has been made to apply autoregressive fractionally integrated moving average (ARFIMA) model to the daily all India maximum, minimum and modal wholesale price data of rice in order to capture the observed long-run persistency. The price series under consideration are stationary, but there is a significant presence of long memory in the price data. Accordingly, ARFIMA model is applied to obtain the forecasts and window-based evaluation of forecasting is carried out with the help of relative mean absolute percentage error, root mean square error and mean absolute error. To this end, a comparative study has also been made between the best fitted ARFIMA model and the best fitted ARIMA model and it is observed that ARFIMA model outperforms the usual ARIMA model.

Research paper thumbnail of Exploring Student Academic Performance Using Data Mining Tools

International Journal of Emerging Technologies in Learning (iJET), 2020

Most of the educational institutes nowadays benefited from the hidden knowledge extracted from th... 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 paper thumbnail of Analysis of trend in area, production and productivity of okra (Abelmoschus esculentus) in India

Current Horticulture, 2019

The analysis of production and area under okra (Abelmoschus esculentus Linn.) in India showed a p... 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 paper thumbnail of Paradigm shift of contamination risk of six heavy metals in tea (Camellia sinensis L.) growing soil: A new approach influenced by inorganic and organic amendments

Journal of hazardous materials, Jan 22, 2017

The present study provides several contamination and ecological risk indices for selected metals ... 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 paper thumbnail of Agricultural Trade Structure and Linkages in SAARC: An Empirical Investigation

Agricultural Economics Research Review, 2015

Since regional associations and free trade are perceived to be welfare-enhancing, this paper has ... more Since regional associations and free trade are perceived to be welfare-enhancing, this paper has examined the structure and flow of trade among SAARC economies. The study has revealed that India alone accounts for 74 per cent of the agricultural exports from the region and 55 per cent of the agricultural imports of the region. Cotton, cereals, fish & crustaceans, and tea & beverages have emerged as the most exported commodities accounting for more than 50 per cent share of exports from SAARC countries to the world. Animal or vegetable fat, cotton and rubber are the most imported commodities by SAARC. India enjoys comparative advantage in exports of cotton, cereals, fish and tea, while Pakistan has a greater comparative advantage in export of cotton and cereals. A unidirectional causality has been observed between gross domestic product (GDP) and agricultural exports, where agricultural exports Granger cause GDP and not vice versa. A one-way causal relationship has also been observed between agricultural GDP and agricultural exports. This indicates that growth in agricultural exports has contributed to the overall and agricultural growth in India. The study has suggested that Indian trade policy environment needs to be made more favourable for attracting foreign buyers and making Indian exports competitive globally.

Research paper thumbnail of Micronutrients (B, Co, Cu, Fe, Mn, Mo, and Zn) content in made tea (Camellia sinensisL.) and tea infusion with health prospect: A critical review

Critical Reviews in Food Science and Nutrition, 2015

Tea (Camellia sinensis L.) is a perennial acidophilic crop, and known to be a non-alcoholic stimu... 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 paper thumbnail of Aluminium dynamics from soil to tea plant (Camellia sinensis L.): is it enhanced by municipal solid waste compost application?

Chemosphere, 2015

Application of municipal solid waste compost (MSWC) in tea (Camellia sinensis L.) cultivation can... 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 paper thumbnail of How Price Signals in Pulses are Transmitted across Regions and Value Chain? Examining Horizontal and Vertical Market Price Integration for Major Pulses in India

Agricultural Economics Research Review, 2016

The paper has applied time series model to investigate the wholesale and retail price market inte... more The paper has applied time series model to investigate the wholesale and retail price market integration of major pulses (tur, gram, moong, urad, masoor) in five major regions namely north zone (NZ), south zone (SZ), east zone (EZ), west zone (WZ) and north east zone (NEZ) in the country based on their volume of production. The study has shown that there exists a strong cointegration among the wholesale as well as retail prices of these major pulses, although the cointegration varies. In addition to the horizontal cointegration, the vertical cointegration between the wholesale and retail prices of different pulses has also been investigated. Different causal relationships have been found between wholesale and retail prices in these five zones. The application of vector error correction model (VECM) has indicated that all the error correction terms (ECTs) are negative and most of these terms are statistically significant, implying that the system once in dis-equilibrium tries to come back to the equilibrium situation. The study has also used Impulse response analysis which shows that change in wholesale prices of these five pulses in one zone will cause change in wholesale prices in other zones. The paper has concluded that price signals are transmitted across regions indicating that price changes in one zone are consistently related to price changes in other zones and are able to influence the prices in other zones. However, the direction and intensity of price changes may be affected by the dynamic linkages between the demand and supply of pulses. The study has provided an interesting insight for policy makers, and for contributing to improve the information precision to predict the price movements used by marketing operators for their strategies and by policy makers for designing the suitable marketing strategies to bring more efficiency across the markets.

Research paper thumbnail of Asymmetric Price Transmission: A Case of Wheat in India

Agriculture, 2022

In the present paper, horizontal and vertical integration was carried out on the wholesale and re... 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 paper thumbnail of Statistical modelling for forecasting of wheat yield based on weather variables

The Indian Journal of Agricultural Sciences, 2013

Research paper thumbnail of Comparative Assessment of Copper, Iron, and Zinc Contents in Selected Indian (Assam) and South African (Thohoyandou) Tea (Camellia sinensis L.) Samples and Their Infusion: A Quest for Health Risks to Consumer

Biological trace element research, Jan 23, 2016

The current study aims to assess the infusion pattern of three important micronutrients namely co... 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...

Research paper thumbnail of Robust Analysis of Block Designs: A New Objective Function

Research paper thumbnail of M-estimation in block designs

Research paper thumbnail of Major Soil Chemical Properties of Upper Assam: the Worldwide Fascinating Tea (Camellia sinensis L.) Producing Region in India

Pedosphere, Mar 13, 2014

ABSTRACT A study was taken up to understand the major chemical properties of tea (Camellia sinens... 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 paper thumbnail of An Empirical Investigation of Arima and Garch Models in Agricultural Price Forecasting

Economic Affairs, 2014

The present study deals with time series models which are non-structural-mechanical in nature. Th... more The present study deals with time series models which are non-structural-mechanical in nature. The Box Jenkins Autoregressive integrated moving average (ARIMA) and Generalized autoregressive conditional heteroscedastic (GARCH) models are studied and applied for modeling and forecasting of spot prices of Gram at Delhi market. Augmented Dickey Fuller (ADF) test is used for testing the stationarity of the series. ARCH-LM test is used for testing the volatility. It is found that ARIMA model cannot capture the volatility present in the data set whereas GARCH model has successfully captured the volatility. Root Mean square error (RMSE), Mean absolute error (MAE) and Mean absolute prediction error (MAPE) were computed. The GARCH (1,1) was found to be a better model in forecasting spot price of Gram. The values for RMSE, MAE and MAPE obtained were smaller than those in ARIMA (0,1,1) model. The AIC and SIC values from GARCH model were smaller than that from ARIMA model. Therefore, it shows that GARCH is a better model than ARIMA for estimating daily price of Gram. production and marketing decisions and to the policy makers for administering commodity proGrams and assessing market impacts of domestic or international events. Monitoring commodity price can play a major role on the overall macroeconomic performance of a country. Therefore, the commodity price forecast is a key input to macroeconomic policy planning and formulation.

Research paper thumbnail of Autoregressive Conditional Heteroscedastic (Arch) Family of Models for Describing Volatility

Abstract—By means of the ARCH (Auto-regressive Conditional Heteroscedasticity) and its modified m... more Abstract—By 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 ...