Environmental impact of green house gas emissions from the tea industries of northeastern states of India

MotivationTea, derived from the Camellia sinensis plant, holds the position of being the most widely consumed manufactured beverage globally. Its cultivation necessitates specific agro-climatic conditions, leading to its production being confined to select regions, notably including India. India contributes about 20.81% to the world’s tea output. The production and processing of tea leaves to final product consume energy in terms of machinery, fertilizer, irrigation etc. The energy consumption involved in tea production is a pressing concern, given the associated high costs and CO2 emissions resulting from fossil fuel usage. To achieve a net-zero carbon balance, there is need to pay attention towards promoting renewable energy technologies as a means to mitigate the CO2 emissions stemming from fossil fuels in India’s tea sector.ObjectivesAligned with the objective of sustainability through the integration of renewable energy sources, a pilot study was conducted in the primary tea-growing regions of northeastern India during 2021–22. The primary aims of this study were twofold: to gauge the quantity of CO2 emissions originating from conventional energy sources and to explore the feasibility of incorporating renewable energy sources as viable substitutes.Data and methodsData on various inputs used in tea production were collected from Assam and West Bengal states of India by using a stratified random sampling method with equal probability and without replacement.ResultsThe findings of this investigation underscore a noteworthy potential for the adoption of renewable energy, particularly solar energy, within the tea estates situated in the north eastern region of India. Such a transition would yield benefits for both the tea estates themselves and the overall environment

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Not AvailableThe calibration approach is a popular technique for incorporating auxiliary information for estimation of population parameters in survey sampling. In general, the Calibration Approach assumes the availability of population-level auxiliary information. On the contrary, in large scale surveys, it is often the case that population-level data on auxiliary variable is not available, but it is relatively inexpensive to collect. In the present article, in case of non-availability of population-level relatively inexpensive data on auxiliary variable under two stage sampling, we developed product type calibration estimator of the finite population total using double sampling approach along with the sampling variance and variance estimator. The study variable is assumed to be inversely related with the auxiliary variable. Proposed product type calibration estimator was evaluated through a simulation study which showed that the proposed product type calibration estimator was performing efficiently over traditional Narain-Horvitz-Thompson type expansion estimator as well as product estimator of the finite population total in case of two stage sampling involving two phases at both the stages.Not Availabl

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Not AvailableIndia is agriculture based country and has experienced an enormous change in food and nutrition utilization design since the financial change in mid 1990s. Agribusiness is considered as the backbone for Indian economy, therefore Indo Gangetic Plain (IGP) holds vast agricultural importance contributing to major portion to our national income. High financial development rates of Indian economy have neglected to enhance food security in India. The welfare of an expanding economy are not shared equally as the country is still home to one-third of the world’s poor. Hunger in India is considered as a genuine imprint on its development and food security has now evolved as a principal issue. Presently, interest in agriculture, nutrition, and dietary security is a prime worry for the country to accomplish the target of encroachment. An expansive area of Indian population is experiencing lack of healthy sustenance and deficiency of nourishment grains. This paper demonstrates nourishment utilization design across selected social and economic groups in the states coming under IGP region of India which includes West Bengal, Bihar, Uttar Pradesh Punjab and Haryana. The analysis helps in distinguishing the disparities among calorie, protein and fat consumption in IGP region. An attempt has also been made in recognizing socio-economic groups suffering from deficiencies in nutrition consumption.Not Availabl

Estimation of domain mean using two stage sampling in the presence of non-response

Not AvailableThe problem of estimation of domain mean under random response mechanism has been considered when the sampling design is two-stage with two phases at the second stage. A estimator is developed based on the technique of sub sampling of non-respondents. Expressions for the variances of the estimators are developed. Optimum values of sample sizes are obtained by considering a suitable cost function. The percentage reduction in the expected cost of proposed estimators is studied empirically

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Not AvailableContains several lectures related to survey data analyisICA

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Not AvailableThe estimates of area and yield rate of agricultural crops assume prime importance in agricultural statistics. The crop area statistics are collected on complete enumeration basis in land record States and in non-land record States like West Bengal, Odisha and Kerala, area statistics are collected through sample survey. The estimates of yield rates of principal food and non-food crops are obtained on the basis of Crop Cutting Experiments (CCE). During the past few years, a total number of approximately nine lakh CCE covering 52 food and 16 non crops were planned in different States. The number of CCEs is on the rise and leads to different types of non sampling errors, which affect data quality. To tackle such problem, Government of India constituted Vaidyanathan Committee to revamp the system covering 90 thousand CCE in 15 thousand villages. This paper attempts to highlight the detail study and methodology to be followed for improvement of existing system. The estimates of area and yield rate of agricultural crops assume prime importance in agricultural statistics. The crop area statistics are collected on complete enumeration basis in land record States and in non-land record States like West Bengal, Odisha and Kerala, area statistics are collected through sample survey. The estimates of yield rates of principal food and non-food crops are obtained on the basis of Crop Cutting Experiments (CCE). During the past few years, a total number of approximately nine lakh CCE covering 52 food and 16 non crops were planned in different States. The number of CCEs is on the rise and leads to different types of non sampling errors, which affect data quality. To tackle such problem, Government of India constituted Vaidyanathan Committee to revamp the system covering 90 thousand CCE in 15 thousand villages. This paper attempts to highlight the detail study and methodology to be followed for improvement of existin

Use of discriminant function analysis for forecasting crop yield

Not AvailableThe present paper deals with use of discriminant function analysis for developing wheat yield forecast model for Kanpur (India). Discriminant function analysis is a technique of obtaining linear/Quadratic function which discriminates the best among populations and as such, provides qualitative assessment of the probable yield. In this study, quantitative forecasts of yield have been obtained using multiple regression technique taking regressors as weather scores obtained through discriminant function analysis. Time series data of 30 years (1971-2000) have been divided into three categories: congenial, normal and adverse, based on yield distribution. Taking these three groups as three populations, discriminant function analysis has been carried out. Discriminant scores obtained from this have been used as regressors in the modelling. Various strategies of using weekly weather data have been proposed. The models have been used to forecast yield in the subsequent three years 2000-01 to 2002-03 (which were not included in model development). The approach provided reliable yield forecast about two months before harvest

Estimation of domain mean using two stage sampling with sub-sampling of non-respondents.

Not AvailableThe problem of estimation of domain mean in the presence of nonresponse has been considered when the sampling design is two-stage. The response mechanism is assumed to be deterministic. Three different type of estimators based on sub-sampling of non-respondents, collecting data on the sub-sample through specialized efforts, are developed. Expressions for the variances of the estimators are developed. Optimum values of sample sizes are obtained by considering a suitable cost function. The percentage reduction in the expected cost of proposed estimators are studied empirically.Not Availabl

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Not AvailableAgriculture is the key livelihood for the vast majority of population in India. The sector is such a crucial that prosperity of agrarian community is essential for Government/Institutional stability. Therefore, the accurate estimation of production in terms of harvested area and yield are equally important in ensuring the accurate determination of their product. Although the yield estimation gets most of the attention, there are many complexities to the estimation of area that might not be readily apparent. Crop area statistics in most of the states are furnished based on complete enumeration or census method. But, shortage of man power, failure of the primary and revenue staffs to devote adequate time and attention in collection and compilation of data has deteriorated the quality of area statistics as well as increased the time lag in availability of data in hand. In the view of above problem, a well-designed sample survey has the ability to cater the need of accurate crop area information and is especially important in developing countries which have very limited resources to apply to the collection of agricultural data. A pilot experiment conducted by ICAR- Indian Agricultural Statistics Research Institute, New Delhi attempts to estimate district level crop yield based on reduced number of Crop Cutting Experiments (CCEs) while crop acreage estimation has been done through well designed sample survey approach. But, traditional sampling theory has also some limitations in providing reliable and valid estimates particularly for districts with few or negligible sample sizes. To tackle the need of representative crop acreage estimation at disaggregated level, Small Area Estimation (SAE) approach has been considered in this paper. In particular, using Hierarchical Bayes spatial small area model disaggregated level crop area has been estimated for two major crops, rice and wheat respectively in the state of Uttar Pradesh for Agriculture year 2015-16. Estimates produced using SAE technique has acceptable precision level and is a positive attempt of crop acreage estimation at micro or local level through SAE approach in India.Not Availabl