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Agriculture Bioinformatics
Computer Applications
Design of Experiments
Forecasting & Agriculture Systems Modelling
Statistical Genetics
About Staff

Sample Survey Division
 

Division of Sample Surveys has developed various sampling methodologies for estimation of important parameters in agriculture. The sampling methodologies developed in the division are being used in the entire country as well as some of the developing countries. Development of suitable sample survey methodologies for estimation of various parameters in crops, livestock, fisheries production and allied fields have always been one of the most important activities of the division from the very beginning. The division was instrumental in the development of sample survey methodology for crop production estimation through crop cutting approach which formed a sound objective method of estimating crop production in the country, estimation of livestock numbers, products and attendant practices, the extent of cultivation and production of fruits and vegetables, estimation of plantation crops like areca nut, coconut, cashew nut, estimation of fish catch both from marine and inland resources, estimation of cost of production of crops as well as livestock products, evaluation studies such as assessment of development programmes like IADP, HYVP, dairy improvement programmes, etc. were other important contributions of the Institute. Most of the methodologies evolved by the division are being adopted for estimation of respective commodities by the concerned departments in the various states and this work is being coordinated by the Directorate of Economics and Statistics and other concerned Wings of the Ministry of Agriculture, Government of India. Some of these methodologies have been internationally used

Head- Sample Survey

Dr. Tauqueer Ahmad

Ph.: +91-11-25841475
E-mail: tauqueer[dot]ahmad[at]icar[dot]
gov[dot]in

 

The division has made significant contributions in many areas of basic research in sampling techniques such as successive sampling, systematic sampling, cluster sampling, component sampling, sampling with varying probabilities, controlled selection, non-sampling errors, various methods of estimation such as ratio and regression methods, analysis of survey data, etc. The use of combinatorics (or experimental designs) in sample surveys has also led to some useful contributions, particularly for variance estimation in large scale complex surveys and varying probability selection procedures. Useful contributions have also been made in the categorical data analysis and variance estimation using re-sampling techniques like Jackknife technique and Balanced Repeated Replications. Studies on small area estimation for local-level planning and regression analysis of survey data have also been taken up.

Besides this the division has the expertise to provide Consultancy services in Sample surveys for Estimation of parameters of Interest in Crop, Livestock, Fisheries, Horticultural Crops, Vegetables and Allied fields, estimation of Area and Production, Cost of Production Studies, Assessment and Evaluation Studies, Post Production Studies, and Application of Remote Sensing and GIS in Agricultural surveys.

Mandate

  • To evolve sample survey techniques for estimation of various parameters of interest relating to crops, livestock, fishery, forestry and allied fields and to develop techniques for analysis of survey data

Thrust Areas

  • Application of Remote Sensing and Geographical Information System
  • Small Area Estimation
  • Area & Production Estimation
  • Cost of Production Studies
  • Assessment and Evaluation Studies
  • Harvest and Post Harvest Losses
  • Analysis of Complex Surveys

Institute Funded

  • Modelling and forecasting for time-to-event analysis in Agriculture.
  • Statistical Approaches for Analysis of Zero-inflated and Over-dispersed Counts Data and their Applications in Single-cell Studies.
  • Development of Machine learning models and Bayesian network for discovery of Nucleic acid-binding protein and their application in disease/pest surveillance.
  • An effective approach for combining time series and deep learning models
  • #Potential irrigated area An effective approach for combining time series and deep learning models mapping through remotely sensed high resolution data.
  • Modeling and construction of transcriptional regulatory networks using time-series gene expression data (2017)
  • Estimation of Heritability under correlated errors (2016)
  • Estimation of Breeding Value Using Longitudinal Data (2016)
  • A study on STAR and SV families of nonlinear time-series models for describing cyclicity and volatility in Agriculture. (2015)
  • A study on modeling and forecasting of time-series with long memory process. (2015)
  • Development of Methodology of Estimation of compound Growth Rate and Its Web Based Solutions. I.A.S.R.I., New Delhi. (2013)
  • Development of Weather-based Crop Yield Forecasting Models using GARCH and Wavelet Techniques. I.A.S.R.I., New Delhi. (2013)
  • A study of Stochastic Volatility Models Through Particle Filtering. I.A.S.R.I., New Delhi. (2013)
  • Estimation of breeding value using generalized estimation equation and Bayesian Approach
  • A study on detection and interpretation of expression quantitative trait loci (eQTL) mapping

Externally Funded

  • Doubling Farmers’ Income in India by 2021-22: Estimating Farm Income and Facilitating the Implementation of Strategic Framework.
  • Modeling Insect Pests and Diseases Under Climate Change and Development of Digital Tools for Pest Management National Innovations in Climate Resilient Agriculture (NICRA).
  • Leveraging Institutional Innovations for Inclusive and Market led Agricultural Growth in Eastern India
  • Production system agribusiness and institutions” Component 3: “Market Information System.
  • Stochastic differential equation models and their applications to agriculture. Funded by SERB, DST, Government of India: CCPI
  • Creation of Policy and Strategy Cell (PSC) at ICAR-NIAP for Doubling Farmers’ Income in India by 2021-22: Estimating Farm Income and Facilitating the Implementation of Strategic Framework
  • Modelling insect pests and diseases under climate change and development  of digital tools for pest management (National Initiative on climate resilient agriculture (NICRA), Government of India)
  • Elucidating the mechanism of pashmina fibre development: An OMICS approach.
  • Studying Dynamics of market integration and price transmission of agricultural commodities
  • Statistical approach for genome-wide association studies and genomic selection for multiple traits in Structured plant and Animal population
  • Creation of Policy and Strategy Cell (PSC) at ICAR-NIAP for Doubling Farmers’ Income in India by 2021-22: Estimating Farm Income and Facilitating the Implementation of Strategic Framework
  • Modelling insect pests and diseases under climate change and development of digital tools for pest management
  • Study of Long Memory and Periodicities in Climate Variables in Different Meteorological Subdivisions of India
  • Leveraging Institutional Innovations for Inclusive and Market led Agricultural Growth in Eastern India
  • Creating a fully characterized genetic resource pipeline for mustard improvement programme in India
  • Metagenomic profiling for assessing microbial biodiversity in River Ganga for ecosystem health monitoring
  • Exploring the Epigenetic Control of Heat Stress Responses in Wheat for Characterizing the regulatory Networks Associated with Thermotolerance
  • Modeling and construction of transcriptional regulatory networks using time-series gene expression data (2017)

Prachi Misra Sahoo

 Principal Scientist

  Prachi[dot]sahoo[at]icar[dot]gov[dot]in

Kaustav Aditya

 Senior Scientist

  Kaustav[dot]aditya[at]icar[dot]gov[dot]in

Ankur Biswas

 Senior Scientist

  ankur[dot]biswas[at]icar[dot]gov[dot]in

Raju Kumard

 Scientist

  raju[dot]kumar[at]icar[dot]gov[dot]in

Deepak Singh

  Scientist

  deepaksingh2112[at]gmail[dot]com

Rahul Banerjee

  Scientist

 rahul[dot]banerjee[at]icar[dot]gov[dot]in

Bharti

  Scientist

  bharti[dot]bharti[at]icar[dot]gov[dot]in

Pankaj Das

  Scientist

  pankaj[dot]das2[at]icar[dot]gov[dot]in

Neelam Chandra

 Assistant Chief Technical Officer

  neelam[dot]chandra[at]icar[dot]gov[dot]in

Manoj Kumar

 Senior Technical Officer

  manoj[dot]kumar[at]icar[dot]gov[dot]in

Manish Kumar

 Technical Assistant

  manish[dot]kumar4[at]icar[dot]gov[dot]in

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