Forecasting & Agricultural Systems Modelling

Dr. Kamalesh Narain Singh
Head(A)
Phone (O).: (011)-25847121-24
Kn.Singh@icar.gov.in

About Us

Division of Forecasting and Agricultural Systems Modeling (F&ASM) deals with basic and applied research in statistical modeling and forecasting of agricultural and environmental phenomena with special emphasis on methodogical and computational aspects to cater to the needs of various stakeholders viz., subject matter specialists, researchers, and scientists, fellow statisticians, policy makers, in the National Agricultural Research System. The major objective of the division is to undertake research, teaching and training in the field of forecasting and agricultural systems modeling including econometric modeling and impact assessment studies in agriculture.

To meet these objectives, so far, new theoretical and improved and modified approaches of the existing ones have been developed. Various models and methodologies have been employed and /or developed which come under the gamut of regression, stochastic, time series and data mining. During initial years, the emphasis was more on forecasting of crop statistics mainly relating to its production and yield and also on forewarning of crop pests and diseases. Over the years, the division has adapted itself to the changing scenario and demands of the present era. In recent years, work is also being carried out using machine learning techniques. The division is engaged in developing various advanced linear and non-linear time series models in agriculture. Studies on technology forecasting for envisioning the main areas of research and key technologies in various domains of agriculture is a continuing activity. In addition, work is being carried out on multivariate time series using advanced modeling techniques apart from studies using aforementioned approaches. The scientists of the division are also involved in research related to spatio-temporal modeling of time series data and Bayesian time series modeling. Impact assessment studies and econometric modeling are also being conducted in this division. Scientists are also involved in senior certificate, post graduate and doctoral level teaching and refresher training programmes. Scientists also provide advisory and consultancy services to students, scientists and policy makers of the country.

Mandate

  • To undertake research, teaching and training in the field of forecasting and agricultural systems modeling.

Thrust Areas

  • Development of forecast models for agricultural systems covering agriculture, horticulture, veterinary sciences, dairy, poultry, fisheries, etc.
  • Development of forewarning systems for crop pests and diseases.
  • Linear and nonlinear time series modeling and forecasting in agriculture.
  • Machine learning techniques in agriculture.
  • Spatio-temporal modeling of time series and Bayesian time series modeling.
  • Climatic modeling relevant to agricultural systems.
  • Technology foresight in agriculture.
  • Impact assessment methodologies and econometric modeling in agriculture.

Ongoing Projects:

Institute Funded

S. No.PROJECT NAMEProject Team
1Future perspective of Bt technology in Indian agriculture.Mrinmoy Ray,  Santosha Rathod, Bishal Gurung, K.N. Singh, Ravindra Singh Shekhawat (from 15.12.2016),  and Ramasubramanian V (from 18.07.2017)
2Development of count time-series models for predicting pest dynamics using weather variables.Prawin Arya and                                 Bishal Gurung
3Tractorization in Semi-Arid Tropic India: Determinants and Implications.Ravindra Singh Shekhawat      and Rajeev Ranjan Kumar
4Modelling and forecasting of drought index using machine learning techniques.Rajeev Ranjan Kumar,  Ravindra Singh Shekhawat and  Sanjeev Panwar
5Parameter estimation of time series models using Bayesian techniqueAchal Lama, Bishal Gurung and Santosha Rathod

External Funded

S. No.PROJECT NAMEFunding AgencyProject Team
1Crop yield forecasting under Forecasting Agricultural output using Space Agro meteorology and Land based observation (FASAL) scheme.IMD, IndiaK.N. Singh and Bishal Gurung
2Efficiency of Micro Irrigation in Economizing Water Use in India- Learning from Potential and Unexplored States NITI AyogDr Subhash Chand, Prabhat Kishore, Dr S K Shrivastva, Dr R S Pundir and Dr. R S Shekhawat (From ICAR-IASRI)

Collaborative (inter-institute project)

S. No.PROJECT NAMEProject Team
1Enhancing smallholder’s productivity and agricultural growth through technology, sustainable intensification and ecosystem services.

(In collaboration with IARI, New Delhi)
Amit Kar (ICAR-IARI, New Delhi)

Prawin Arya (ICAR-IASRI, New Delhi)

Completed Projects:

Instituted Funded

S. No.PROJECT NAMEProject Team
1Forecasting of spatio-temporal time series data using Space Time Autoregressive Moving Average (STARMA) modelSantosha Rathod, Mrinmoy Ray, Ajit, K.N. Singh and Bishal Gurung (from 20.9-2015),
2Development of Hybrid Time Series Models using Machine Learning Techniques for Forecasting Crop Yield with CovariatesMd. Wasi Alam, *Kanchan Sinha (Upto 22.08.2016), Mrinmoy Ray, Santosha Rathod, KN Singh, and Rajeev Ranjan Kumar (from 23.08.2016).
3Nonparametric bootstrap approach for constructing prediction intervals for non-linear and bivariate time series models.Mrinmoy Ray, Santosha Rathod, Wasi Alam, KN Singh
4A study on Price Efficiency in Agricultural Commodity Market.SP Bhardwaj, Kanchan Sinha, Bishal Gurung
5Study on Volatility spillover of Agricultural commodity prices.Kanchan Sinha, Wasi Alam, Sanjeev Panwar, Bishal Gurung
6Study of Commodity Price Forecast based on time series dataSP Bhardwaj, KN Singh, Sanjeev Panwar, Ranjit Kumar Paul
7A study on STAR and SV families of nonlinear time-series models for describing cyclicity and volatility in AgricultureBishal Gurung, Himadri Ghosh, Ranjit Kumar Paul
8Study of Asymmetry in Retail –Wholesale Price Transmission for selected essential CommoditiesS P Bhardwaj, Ashok Kumar, Sanjeev Panwar
9Weather based yield forecast for rice and wheat using non-linear regression techniquesSanjeev Panwar, N Okendro Singh
10Weather based forewarning of Mango pestsRanjana Agarwal
11An Econometric Study of Water Markets in Canal Command Area of North-Western RajasthanD R Singh, Prawin Arya, S P Bhardwaj
12Study on robustness of sequential testing procedures on some distributions used in agricultural pest controlWasi Alam
13Weather based forewarning models for Onion ThripsAmrender Kumar, Ranjana Agrawal, yanti Mala BR
14Use of discriminant function and principal component techniques for weather  based crop yield forecastChandrahas, Ranjana Agrawal, S S Walia
15An Econometric analysis of groundwater markets in Indo-Energetic plains of IndiaD R Singh, A K Vasisht, Prawin Arya, Ashok Kumar
16Econometric study of long–run effect of public investment in irrigation on food grains productivityAshok Kuma, S P Bhardwaj
17Weather based models for forecasting potato yieldS C Mehta, Satya Pal
18Neural network based forecast modeling in cropsAmrender Kumar, Ramasubramanian V, Ranjana Agrawal
19Crop forecasting using state space modelsRamasubramanian V, Chandrahas
20A study on editing and imputation using neural networkRamasubramanian V, S B Lal
21Study of non-linear time series modeling in agricultureHimadri Ghosh, Prajneshu, A K Paul
22Pilot study for developing Bayesian probability forecast model based on farmers’ appraisal data on wheat cropChandrahas, Tribhuwan Rai
23Use of dis-criminant function of weather parameters for developing forecast model of rice cropTribhuwan Rai, Chandrahas
24Study to develop model for assessing the effect of flood on yield of cropsJagmohan Singh, B H Singh, Ranjana Agrawal
25Yield forecast based on weather variables and agricultural inputs on agro-climatic zone basisRanjana Agrawal, R C Jain, S C Mehta
26Integrated yield forecast model using biometrical characters, agricultural inputs, weather and remotely sensed dataRanjana Agrawal, Gurcharan Singh, B C Panda, R C Jain, R N Garg
27Composite forecast of sugarcane yieldS C Mehta, Chandrahas
28Statistical modeling for forecasting of marine fish catchS S Walia, Balbir Singh
29A statistical model for assessing the effect of weeds on crop yieldG N Bahuguna, B H Singh, Madan Mohan
30Models for forecasting aphid-pest of mustard cropG N Bahuguna, Chandrahas
31Pre-harvest forecasting of apple yield on the basis of data on biometrical characters, weather factors and crop inputs in Shimla District of Himachal Pradesh during 1984-86Chandrahas, Prem Narain
32Yield forecast model based on biometrical characters and inputs for jowar cropR C Jain, Ranjana Agrawal, K G Aneja
33A within-year growth model for pre-harvest forecasting of crop yieldsR C Jain, Ranjana Agrawal, K N Singh
34Probability model for crop yield forecastingR C Jain, Ranjana Agrawal
35Studies to develop models for obtaining pre-harvest forecast of wheat yield on the basis of weather parametersRanjana Agrawal, R C Jain
36Tobacco yield forecast model based on principal components of biometrical characters and crop inputsChandrahas, K G Aneja, B H Singh
37Pilot studies on pre-harvest forecasting of yield of Sugarcane in Kohlapur District, MaharashtraS R Bapat, B H Singh, Chandrahas
38Studies on forecasting of rice yield based on weather parameters – Puri DistrictRanjana Agrawal, R C Jain, M P Jha
39Pilot studies on pre-harvest forecasting of yield of (Kharif) jowar in Sangli District (Maharashtra)R C Jain, M P Jha, Ranjana Agrawal
40Incidence of pests and diseases, and consequent crop loss in wheat cropG N Bahuguna, K G Aneja, V K Mahajan
41Pre-harvest forecasting of yield of TobaccoChandrahas, B H Singh, M P Jha
42Effects of weather and agricultural inputs on rice crop and its forecast – Raipur DistrictRanjana Agrawal, R C Jain, M P Jha
43Incidence of pests and diseases, and consequent crop loss in paddy cropK G Aneja, M P Jha, G N Bahuguna, V K Mahajan
44Forecasting rice yield based on weather parameters (Raipur District)Ranjana Agrawal, R C Jain, M P Jha
45Pre-harvest forecasting of yield of PaddyM P Jha, Padam Singh, V N Iyer, Chandrahas
46Pilot studies on pre-harvest forecasting of yield of wheat in Ludhiana (Punjab) and Aligarh (Uttar Pradesh) DistrictsM P Jha, P Singh, V N Iyer, Chandrahas
47Pre-harvest forecasting of yield of cottonD Singh, M P Jha, Padam Singh, H P Singh
48Pre-harvest forecasting of yield of JuteH P Singh, Padam Singh,M P Jha

External funded projects

S. No.PROJECT NAMEFunding AgencyProject Team
1Mapping the Cultural Authority of Science across Europe and India (MACAS-EU & India 2012-14)ICAR, DARE, Min. of Agriculture, GOIKN Singh, Rajesh Shukla  (From IHD)
2National Information System for Pest Management (NISPM) (Bt Cotton)DOAC, Min. of Agriculture, GOIPrawin Arya
3Market IntelligenceICAR, DARE, Min. of Agriculture, GOIS P Bhardwaj, K N Singh, Sanjeev Panwar, Ranjit Kumar Paul
4Visioning Policy Analysis and Gender (V.Page) sub programme on Technology ForecastingNational Agricultural Innovation Project [V.K. Bhatia from 13 August, 2008], [S.D. Sharma till 12 August, 2008], Ramasubramanian V., Amrender Kumar, [Anil Rai till 31 March, 2011], [Satya Pal till 31 December, 2010], [K.K.Chaturvedi till 01 September, 2010], [Ranjana Agrawal till 19 November, 2008]
5Visioning Policy Analysis and Gender (V.Page) sub prog. III : Policy analysis and market intelligenceNational Agricultural Innovation ProjectD R Singh, Ashok Kumar, S P Bhardwaj, Prawin Arya, Sushila Kaul, Pratap Singh (NCAP), N P Singh (IARI), Anil Rai, K K Chaturvedi, N Sivaramane
6Development of weather based forewarning system for crop pests and diseasesNational Agricultural Technology ProjectY S Ramakrishna (CRIDA, Hyderabad), R Agarwal, S C Mehta, L M Bhar, Amrender Kumar

Collaborative (Inter institutinonal projects)

S. No.PROJECT NAMEProject Team
1Development of Forecasting module for  podfly,Melanagromyzaobtusa Malloch in late pigeonpea  (in collaboration with IIPR, Kanpur)Ranjana Agrawal, Amrender Kumar, S K Singh (IIPR, Kanpur)
2Studies on bioecology and population dynamics of major pests of mango (hoppers, fruit–flywebber & inflorescance midge) and guava (fruit–borer), (In collaboration with CISH, Lucknow)R P Shukla, Shashi Sharma (CISH, Lucknow), S C Mehta
3Modelling for Forecasting of crop yield using weather parameters and agricultural inputs. (In collaboration with CISH, Lucknow)Ranjana Agrawal, Asha Saksena, L M Bhar, Amrender Kumar, Madam Mohan, Y S Ramakrishna, AV R Kesva Rao (CRIDA, Hyderabad)
4Forecasting the loss in yield due to weeds (In collaboration with IARI)Madan Mohan, Rajvir Sharma (IARI), T Rai, Ranjana Agrawal
5Pilot study on forecasting of brood-lac yield from Butea monosperma (Palas) (In collaboration with ILRI, Ranchi & funded through A.P. Cess Fund)A K Jaiswal, K K Sharma (ILRI, Ranchi), Chandrahas
5To develop model of forewarning about infestation of insects of Paddy crop (In collaboration with NDUAT, Faizabad)M K Sharma, V Pandey, R S Singh (NDUAT, Faizabad), Ramasubramanian V, S S Walia
6Epidemiology and forecasting of powdery mildew & Anthracnose.(for Mango) (In collaboration with CISH, Lucknow)A K Misra, Om Prakash (CISH, Lucknow) Ramasubramanian V
7Development of early warning and yield assessment models for rainfed crops based on agro-meteorological indice. (In collaboration with PDCSR)Asha Saksena, R C Jain, R L Yadav (PDCSR)
8Forecasting fish production from ponds (In collaboration with CIFA)L M Bhar, S S Walia, A K Roy, Radhey Shyam (CIFA)

2018

  • Mahalingaraya, Rathod S, Sinha K, Shekhawat R R S, and Chavan S. (2018). Statistical Modeling and Forecasting of Total Fish Production of India: A Time Series Perspective. Int.J.Curr.Microbiol.App.Sci. 7(3): 1698-1707.
  • Rathod, S. and Mishra, G.C. (2018). Statistical Models for Forecasting Mango and Banana Yield of Karnataka, India. Journal of Agricultural Science and Technology. 20(4): July 2018 (Accepted on 24 October 2017).
  • Rathod S, Singh K N, Patil S G, Naik R H, Ray M and Meena V S. (2018). Modeling and forecasting of oilseed production of India through artificial intelligence techniques. The Indian Journal of Agricultural Sciences. 88(1): 22-27.
  • Vinay, A., Ramasubramanian, V., Krishnan, M. and Ananthan, P.S. (2018). Total factor productivity of Tuna fisheries in Lakshadweep, Indian Journal of Geomarine Sciences47(2), 319-32.

2017

  • Rathod, S., Singh, K,N., Paul, R.K., Meher, R.K., Mishra, G.C., Gurung, B., Ray, M. and Sinha, K. (2017). An Improved ARFIMA Model using Maximum Overlap Discrete Wavelet Transform (MODWT) and ANN for Forecasting Agricultural Commodity Price.  Journal of the Indian Society of agricultural Statistics. 71(2): 103–111.
  • Gurung, Bishal, Panwar, Sanjeev, Singh, K.N., Banerjee, Rahul, Gurung, Sisir Raj, and Rathod, Abhisek (2017). Wheat Yield Forecast Using Detrended Yield over a Sub-Humid Climatic Environment In Five Districts of Uttar Pradesh, India. Indian Journal of Agricultural Sciences. 87(1), 87-91.
  • Ray, M., Rai, A., Singh, K.N., Ramasubramanian,  V. and Kumar, A.(2017). Technology forecasting using time series intervention based trend impact analysis for wheat yield scenario in India, Technological Forecasting and Social Change, 118: 128–133.
  • Arun, V.V., Saharan, N., Ramasubramanian, V., Rani, A.M.B., Salin, K.R., Sontakke, R., Haridas, H. and Pazhayamadom, D.G. (2017). Multi-response optimization of Artemia hatching process using split-split-plot design based response surface methodology, Scientific Reports, doi: 10.1038/srep40394, 7: 1-16.
  • Kanchan Sinha, Bishal Gurung, Ranjit Kumar Paul, Anil Kumar, Sanjeev Panwar,  Alam, W., Mrinmoy Ray and Santosha Rathod (2017). Volatility Spillover using Multivariate GARCH Model: An Application in Futures and Spot Market Price of Black Pepper. Journal of the Indian Society of Agricultural Statistics, 71(1):21-28.
  • Gurung, Bishal, Singh, K.N., Shekhawat, Ravinder, and Yeasin, Md (2017). An insight into technology diffusion of tractor through Weibull growth model. Journal of Applied Statistics. http://dx.doi.org/10.1080/02664763.2017.1289504
  • Gurung, Bishal, Singh, K.N., Paul, Ranjit Kumar, Panwar, Sanjeev, Gurung, Biwash, and Lepcha, Lawrence (2017). An alternative method for forecasting price volatility by combining models. Communications in Statistics: Simulation and Computation. 46(6), 4627-4636. http://dx.doi.org/10.1080/03610918.2015.1124115
  • Ibandalin, M., Kumar, S., Gurung, Bishal, Singh, K.H., and Singh, D.(2017).A Simple Spectrophotometric Method for Estimating Total Glucosinolates in Mustard de-oiled cake. International Journal of Food Properties.  http://dx.doi.org/10.1080/10942912.2017.1286353
  • Panwar, S, Singh, KN, Kumar, A, Gurung, Bishal, Sarkar, S., Sivaramane and Rathore, A (2017). Pre harvest forecasting of crop yield using non-linear regression modelling: A concept. Indian Journal of Agricultural Sciences, 87(5), 685-689.
  • Sanjeev Panwar, Anil Kumar, Priya Sharma and Gurung, Bishal (2017). Analysis of Volatile Export Data of Fruits and Vegetables Seeds: An Application of Stochastic Volatility Model using the Particle Filter. Ind. Jour. Agril. Mark. 31(1), 32-41.
  • Hemlata Bharti , P. Manivel, Gurung, Bishal, and Jitendra Kumar. (2017) Multivariate analysis of yield associated traits in Safed musli (Chlorophytum borivilianum) genotypes under semi-arid conditions. Indian Journal of Horticulture, 74(2), 264-270.
  • Angami, T., Assumi, S.R., Baruah, S., Sen, A., Bam, B., Khatoon, A., Gurung, Bishal and H. Kalita. (2017) A Study on the Quality Changes of Taktir Fruits (Garcinia lancifolia. Roxb) in Different Packages during Storage. International Journal of Current Microbiology and Applied Sciences, 6(8), 928-936.
  • Panwar, S, Singh, KN, Kumar, A, Paul, RK, Sarkar, SK, Gurung, Bishal and Rathore, A (2017). Performance evaluation of yield crop forecasting models using weather index regression analysis. The Ind. Jour. Agril. Sci., 87 (2), 270-272.
  • Anjoy, P., Paul, R. K., Sinha, K., Paul, A. K. and Ray, M. (2017). A hybrid wavelet based neural networks model for predicting monthly WPI of pulses in India. Indian Journal of Agricultural Sciences. 87 (6), 834-839.
  • Amit Saha, A., Bhardwaj, S.P., Singh, K.N., Sinha, K., Grover, A. and Gurung, B. (2017) Hedge Ratio based on Ordinary Least Squares (OLS) Vs State Space Methodologies, Journal of the Indian Society of Agricultural Statistics, 71(1), 15–20.
  • Singh, Sh. H., Narasimiah, L., De, S., Sinha, K., Sathish, G. and Sahu, P.K. (2017) Discriminant analysis: a tool for identifying significant socio-economic correlates in farming system – a case study, Journal of Crop and Weed, 13(1), 42-45.
  • Rathod, S., Singh, K,N., Paul, R.K., Meher, R.K., Mishra, G.C., Gurung, B., Ray, M. and Sinha, K. (2017). An Improved ARFIMA Model using Maximum Overlap Discrete Wavelet Transform (MODWT) and ANN for Forecasting Agricultural Commodity Price.  Journal of the Indian Society of agricultural Statistics. 71(2): 103–111.
  • Naveena, K., Subedar Singh, Santosha Rathod and Abhishek Singh. (2017). Hybrid ARIMA-ANN Modelling for Forecasting the Price of Robusta Coffee in India.  International Journal of Current Microbiology and Applied Sciences, 6(7): 1721-1726.
  • Naveena, K., Subedar Singh, Santosha Rathod and Abhishek Singh (2017) Hybrid Time Series Modelling for Forecasting the Price of Washed Coffee (Arabica Plantation Coffee) in India. International Journal of Agriculture Sciences, 9(10): 4004-4007.
  • Meena, V.S., Mittal, R. K., Choudhury, P. R., Rathod, S., Mahadevaswamy, H. K. and Choudhary, R. (2017). Utilization of molecular and morphometric tools for assessment of genetic diversity of Rice bean [Vigna umbellata (Thunb.) Ohwi and Ohashi]. International Journal of Current Microbiology and Applied Sciences. 6(5): 2882-2892.
  • Shekhawat, R. S., Singh, K. N., Burark, S. S., Meena, G. L. and Shekhawat, N. (2017). Agribusiness and Food Processing Industries in Uttar Pradesh State of India. Asian Journal of Agricultural Extension, Economics & Sociology, 15(4): 1-7.
  • Prakash, A., Singh, H. N. and Shekhawat, R. S. (2017). Resource Use Efficiency in Hybrid and Inbred Rice Production in Uttarakhand. Asian Journal of Agricultural Extension, Economics & Sociology, 18(1): 1-7.
  • Prakash, A., Singh, H. N., Shekhawat, R. S. and Sandu, S. (2017). Comparative Analysis on Economic Efficiency of Hybrid and Inbred Rice Production in Udham Singh Nagar District of Uttarakhand. Journal of Economics, Management and Trade, 18(4): 1-7.

2016

  • Ray, M., Rai, A., Ramasubramanian, V. and Singh K. N. (2016). ARIMA-WNN hybrid model for forecasting wheat yield time series data. Journal of the Indian Society of the Agricultural Statistics. 70(1), 63-70.
  • Bhowmik,A., Ramasubramanian, V., Rai, A., Kumar, A. and Kundu, M.G. (2016). Improved Estimation in Logistic Regression through Quadratic Bootstrap Approach: An Application in Agricultural  Ergonomics, Journal of the Indian Society of Agricultural Statistics, 70(3): 227–235.
  • H. S. Roy, R. K. Paul, L. M. Bhar and P. Arya (2016). Application of INAR model on the pest population dynamics in Agriculture. Journal of Crop and Weed, 12(2):96-101
  • Alam, W., Ajit Chaturvedi, Anil Kumar, K.N. Singh and Kanchan Sinha (2016). Sequential testing for decision making in the management of mustard aphid using size-biased negative binomial distribution. International Journal of Agricultural and Statistical Sciences. 12(2): 531-535 [NAAS Score=5.13, 2017]
  • Bansal, Ruchi, Pradheep, K., Kumari, Jyoti, Kumar, S., Yadav, MC, Gurung, Bishal, Kumari, NKP, Rana, JC. (2016). Physiological and biochemical evaluation for drought tolerance in wheat germplasm collected from arid western plains of India. Indian Journal of Biochemistry and Biophysics, 53, 212-217.
  • Gurung, Bishal, Singh, K.N., Prajneshu, and Avnish Grover. (2016). Analysis of cyclical fish landings through ESTAR nonlinear time-series approach. Indian Journal of Fisheries. 63(2), 110-113.
  • Panwar, S, Kumar, A, Singh, KN, Gurung, Bishal and Rathore, A (2016). Use of Weather Indices approach in wheat yield crop forecast. Int.  J. Tropical Agril., ISSN: 0254-8755, 1-4.
  • Bhardwaj S.P, Gurung, Bishal, Kanchan Sinha and K.N. Singh (2016) Study on Market Efficiency and Price Risk Management in Future Trading. Ind. Jr. of Agril. Marketing. 30 (3), 48-58.
  • Panwar, S, Kumar, A, Sarkar, SK, Paul, RK, Gurung, Bishal and Rathore, A (2016) Forecasting of common carp fish production from ponds using non-linear growth models: A modelling approach. Journal of the Indian Society of Agricultural Statistics, 70 (2), 139–144.
  • Paul, AK, Kundu, MG, Paul, RK and Gurung, Bishal (2016). Usefulness of Growth Curve Parameters in early selection of pigs. Journal of the Society for Application of Statistics in Agriculture and Allied Sciences (SASAA), 1(2), 27-34.
  • Paul, RK, Gurung, Bishal, Paul, AK and Samanta, S (2016). Long memory in conditional variance. Journal of the Indian Society of Agricultural Statistics, 70(3), 243-254.
  • Amit Saha, SP Bhardwaj, KN Singh, Kanchan Sinha, Avnish Grover and Gurung, Bishal (2016). Hedge ratio based on Ordinary Least Square (OLS) vs. State space methodologies. Journal of Indian Society of Agricultural Statistics. 71(1), 15-20.
  • Namita Das Saha, Anita Chaudhary, Shiv Dhar Singh, Suresh Walia, Tapas Kumar Das, Dinesh Singh, Bhawana Pant, Arpan Bhowmik, Bishal Gurung and Himanshu Pathak. (2016) Climate change variables induced soft rot causing plant pathogen to produce new quorum sensing (cell to cell communication) signal for enhanced pathogenesis. Indian Phytopatholog, 69(4s),260-265
  • Achal Lama, Girish K Jha, Gurung, Bishal, Ranjit Kumar Paul and Kanchan Sinha (2016).  VAR-MGARCH models for volatility modelling pulses prices: An application. Journal of Indian Society of Agricultural Statistics. 70(2),145-151.
  • Achal Lama, Girish K Jha, Gurung, Bishal, Ranjit Kumar Paul, Anshu Bharadwaj and Rajender Parsad. (2016) A comparative study on time-delay neural network and GARCH models for forecasting agricultural commodity price volatility. Journal of Indian Society of Agricultural Statistics 70(1), 7-18.
  • Bhardwaj, S. P., Gurung, B. and Sinha, K. (2016) Commodity Futures a New Form of Marketing Based on Market Fundamentals, Indian Journal of Agricultural Economics, 71 (3), 314.
  • Sinha, K, Paul, R.K. and Bhar, L. M. (2016) Price Transmission and Causality in major onion markets of India. Journal of the Society for Application of Statistics in Agriculture and Allied Sciences (SASAA), 1(2), 35-40.
  • Paul, R. K. and Sinha, K. (2016) Forecasting crop yield: ARIMAX and NARX model, RASHI, 1(1), 77-85
  • Pardhi, R., Singh, R., Rathod, S. and Singh, P.K. 2016. Effect ofPrice of Other Seasonal Fruits on Mango Price in Uttar Pradesh. Economic Affairs, 61(4):1-5.

2015

  • Gurung, Bishal, Singh, K.N., Paul, Ranjit Kumar, Arya, Prawin, Panwar, Sanjeev, Paul, Amrit, Gurung, Sisir Raj and Lama, Achal (2015). Fitting Stochastic Volatility model through Genetic Algorithm. International Journal of Agricultural and Statistical Sciences. 11, Supplement 1,257-264.
  • Prawin Arya, Ranjit Kumar Paul, Anil Kumar, K. N. Singh, N. Sivaramne and Pradeep Chaudhary (2015). Predicting pest population using weather variables : An ARIMAX time series framework. Int. J. Agricult. Stat. Sci. 11 (2), pp. 381-386.
  • Ranjit Kumar Paul, S. P. Bhardwaj, D. R. Singh , Anil Kumar, Prawin Arya and K. N. Singh (2015). Price volatility in food commodities in India – an empirical investigation. Int. J. Agricult. Stat. Sci. II (2), pp. 395-401.
  • Joshi, M.A., Aggarwal, D., Pandey, A., Bind, D. and Alam, W. (2015). Generation of Distinct Profiles of rice varieties based on agro-morphological characters and assessment of genetic divergence. Research on Crops. 16(2): 311-319
  • Surendra Singh, A.K. Paul, Ranjit Kumar Paul, L.M. Bhar, Ashok Kumar and Wasi Alam (2015).  Study of Growth Pattern of Cattle under Different Error Structures. Model Assisted Statistics and Applications. 10:109-115
  • Gurung, Bishal, Paul, Ranjit Kumar, Singh, K.N., Panwar, Sanjeev, Lama, Achal and Lepcha, Lawrence (2015). An alternative approach to capture cyclical and volatile phenomena in time-series data. Model Assisted Statistics and Applications. 11(3), 221-230.
  • Paul, Ranjit Kumar, Gurung, Bishal, Samanta, Sandipan, and Amrit Kumar Paul (2015). Modeling Long Memory in Volatility for Spot Price of Lentil with Multi-step Ahead Out-of-sample Forecast Using AR-FIGARCH Model. Economic Affairs, 60(3), 457-466.
  • Paul, Ranjit Kumar, Samanta, Sandipan, and Gurung, Bishal (2015). Monte Carlo simulation for comparison of different estimators of long memory parameter: An application of ARFIMA model for forecasting commodity price. Model Assisted Statistics and Applications. 10 (2), 117-128.
  • Joshi, Deepika, Singh, H.P., and Gurung, Bishal (2015). Stability Analysis of Indian Spices Export – A Markov Chain Approach. Economic Affairs. 60 (2), 257-262.
  • Ranjit Kumar Paul, P. S. Birthal, Amrit Kumar Paul and Gurung, Bishal (2015). Temperature trend in different agro-climatic zones in India. MAUSAM. 66(4), 841-846.
  • Lama, Achal, Jha, GK, Paul, Ranjit Kumar, Gurung, Bishal (2015). Modelling and forecasting of price volatility: An application of GARCH and EGARCH models. Agricultural Economics Research Review. 28 (1), 73-82.
  • Gurung, Bishal (2015). An Exponential Autoregressive (EXPAR) model for the forecasting of All India annual rainfall. MAUSAM. 66(4), 847-849.
  • Devi, C.P., Munshi, A.D., Behera, T.K., Choudhary, H., Vinod, Gurung, Bishal, Saha, P. (2015). Cross compatibility study in interspecific hybridization of Solanum melongena and its wild relatives. Scientia Horticulturae. 193, 353–358.
  • Paul, Ranjit Kumar, Gurung, Bishal, and Samanta, Sandipan (2015). Analyzing the Effect of Dual Long Memory Process in Forecasting Agricultural Prices in Different Markets of India. International Journal of Empirical Finance. 4(4), 235-249.
  • Paul, R. K. and Sinha, K. (2015) Spatial market integration among major coffee markets in India, Journal of the Indian Society of Agricultural Statistics, 69 (3), 281-287
  • Boyal, V. K., Pant, D. C., Burark, S. S., Shekhawat, R. S. and Mehra, J. (2015). Growth and Instability in Production of Cumin in Rajasthan. Journal of Agricultural Research and Technology, 40(2): 309-314.

2014

  • Panwar, S, Singh, KN, Kumar, A, Sarkar, SK, Paul, RK, Rathore, A and Sivaramane, N. (2014). Forecasting of growth rates of wheat yield of Uttar Pradesh through non-linear growth models. Ind. J. Agric. Sci., 84(7), 68-71.
  • Amerender Kumar, C. Chattopadhyay, K. N. Singh, S. Vennila and Vum Rao. (2014). Trend analysis of climatic variables in Pigeonpea growing regions in India. Mausam, 65, 2 (April 2014), 161-170.
  • Ramasubramanian, V., Kumar, A., Prabhu, K.V., Bhatia, V.K. and Ramasundaram, P. (2014). Forecasting technological needs and prioritizing factors in agriculture from plant breeding and genetics domain perspective: A review, Indian Journal of Agricultural Sciences, 84 (3), 311-316.
  • Ramasubramanian, V. and Bhar, L. (2014). Crop yield forecasting by multiple Markov chain models and simulation, Statistics and Applications, 12(1&2), 1-13.
  • Sadhu, S.K., Ramasubramanian, V., Rai, A. and Kumar, A. (2014). Decision tree based models for classification in agricultural ergonomics, Statistics and Applications, 12(1&2), 21-33.
  • Ray, M., Ramasubramanian V., Kumar, A. and Rai, A. (2014). Application of time series intervention model for forecasting cotton yield, Statistics and Applications, 12(1&2), 61-70.
  • KV Praveen, S Kumar, DR Singh, A Kumar, P Arya, K Chaudhary (2014). An Analysis of Price Levels of Selected Food Commodities under Modern and Traditional Retailing Formats in Kochi, Global Journal of Finance and Management :5 (4): 96-101.
  • Alam, W.,  Ajit Chaturvedi, K.N. Singh, Anil Kumar, Amrit K. Paul, Ranjit K. Paul and Kanchan Sinha (2014). Maximum Likelihood and Uniformly Minimum Variance Unbiased Esimation of P(Y<X) for Gompertz Distribution. International journal of Agricultural and Statistical Sciences. 10(2):267-274
  • Alam W., Chaturvedi, A. and Kumar, A. (2014). Estimation of survival function under type II censoring using a generalized family approach.International Journal of Agricultural and Statistical Sciences.  10(1): 17-19
  • Paul, R.K., Alam, W. and A.K. Paul (2014). Prospects of livestock and dairy production in India under time series framework. The Indian Journal of Animal Sciences. 84(4):462-466.
  • Behera, S.K., Paul,A.K, Wahi, S.D., Iquebal, M.A., Das, S., Paul, R., Alam, W. and Kumar, A. (2014). Estimation of heritability of mastitis disease using moment estimators. Int. J. Agricult. Stat. Sci.Vol. 10, Supplement 1: 243-247.
  • Ghosh, Himadri, Gurung, Bishal, and Prajneshu (2014). Kalman filter based modelling and forecasting of stochastic volatility with threshold. Journal of Applied Statistics. 42(3), 492-507.
  • Ghosh, Himadri, Gurung, Bishal, and Prajneshu (2014). Fitting EXPAR models through the extended Kalman filter. Sankhya B. 77(B 1), 27-44.
  • Gurung, Bishal, Paul, Ranjit Kumar and Ghosh, Himadri. (2014) Fitting Smooth Transition Autoregressive nonlinear time-series model using Particle Swarm Optimization technique. Journal of Indian Society of Agricultural Statistics.  68(3), 327-332.
  • Lawrence Lepcha, Gurung, Bishal, Paul, Ranjit Kumar, and Kanchan Sinha (2014). Stochastic model for sticklac forecasting in India. Economic Affairs. 59(3),479-483.
  • Gurung, Bishal, Paul, Ranjit Kumar, and Lawrence Lepcha (2014). Volatility and cointegration in export of livestock and marine products of India. Indian Journal of Animal Sciences. 84(11),1244-1247.
  • Gurung, Bishal, Prajneshu, and Ghosh, Himadri (2014). Stochastic Volatility Model Fitting using Particle Filter: An Application. Journal of Indian Society of Agricultural Statistics. 68(3), 343-350.
  • Paul, Ranjit Kumar, Gurung, Bishal, and Paul, Amrit Kumar (2014). Modelling and forecasting of retail price of Arhar Dal in Karnal, Haryana. Indian Journal of Agricultural Sciences. 85(1), 69-52.
  • Assumi, R., Pal, R.K., Gurung, Bishal, and Kaur, C. (2014). Physico-chemical characteristics and sensory quality of pineapple vermouth. Indian Journal of Horticulture. 71(3), 402-407.
  • Gurung, Bishal (2014). Fitting nonlinear time-series model using Swarm Optimization technique. Advance in Electronic and Electric Engineering, 4(6), 537-540.
  • Jha, G. K. and Sinha, K. (2014) Time-delay neural networks for time series prediction: an application to the monthly wholesale price of oilseeds in India, Neural Computing and Applications, 24 (3-4), 563-571
  • Lepcha, L., Gurung, B., Paul, R. K. and Sinha, K. (2014) Stochastic model for sticklac forecasting in India, Economic Affairs 59 (3), 479.
  • Naganagoudar, Y.B, Kenchanagoudar, P.V., Rathod, S., Keerthi, C.M., Nadaf, H.L. and Channappagoudar, B.B. (2016). Inheritance of fresh seed dormancy in recombinant inbred lines (RIL) developed for mapping population TAG 24 x GPBD 4 in groundnut (Arachis hypogeal L.), Legume Research, 39 (5): 844-846.
  • Naveena, K., Rathod, S., Shukla, G. and Yogish, K.J.  (2014). Forecasting of coconut production in India: A suitable time series model, International Journal of Agricultural Engineering, 7(1):190-193.
  • Shekhawat, R. S. and Singh, S. P. (2014). Impact of Futures Trading on Wholesale Price Indices (WPI) of Agricultural Commodities in India. Annals of Agri-Bio Research, 19 (2): 335-339.
  • Shekhawat, R. S. and Singh, S. P. (2014). Impact of Futures Trading on Volatility in Spot and Futures Prices of Agricultural Commodities in India. Journal of Plant Development Science, 6 (2): 255-259.
  • Shekhawat, N. Jadeja, G. C., Singh, J. and Shekhawat, R. S. (2014). Character Association Studies among Yield and its Component Characters in Indian Mustard (Brassica Juncea L. Czern & Coss). The Bioscan, 9(2): 685-688.

2013

  • Singh, N. Okendro, Paul, A.K., Kumar, Surinder, Alam,Wasi, Singh, N. Gopimohon, Singh, K.N. and Singh, Pal.(2013). Fitting of Partial Reparameterized Logistic Growth Model to Oil Palm Yield Data. Int. J. Agricult. Stat. Sci., Vol. 9, Supplement 1, pp. 55-62, 2013.
  • M.C. Manna, P. Bhattacharya, T.K. Adhya, M. Singh, R.H. Wanjari, S. Ramana, A.K.Tripathi, K.N. Singh, K.S. Reddy, A. Subba Rao, R.S. Sisodia, M. Dongre, P. Jha, S. Neogi, K. Roy, K.S. Rao, S. D. Sawarkar, and V.R. Rao.(2013). Carbon fractions and productivity under changed  climate scenario in soybean-wheat system. Field Crops Research -145 (2013): 10-12.
  • N. Okendro Singh, Surinder Kumar, N. Gopimohon Singh, A.K. Paul, K.N. Singh and Pal Singh. (2013). Fitting of Fox Model with Autoregressive of Order One Using Expected Value Parameters. Indian Journal of Agricultural Sciences, 83(2), 83(2), 201-203.
  • Patel, R.M., Goyal, R.C., Ramasubramanian, V. and Marwaha, S. (2013).  Markov chain based crop forecast modelling software, Indian Journal of Agricultural Statistics, 67(3), 371-379.
  • Jeeva, C.,  Ramasubramanian V., Kumar, A., Bhatia, V.K., Geethalakshmi, V. and Premi, S.K. (2013). Forecasting technological needs and prioritizing factors for the post harvest sector of Indian Fisheries, Fishery Technology, 50 (1), 87-91
  • Paul, A.K., Paul, R.K., Alam, W. (2013).Effect of Non-normality and inadmissible estimates on estimation of heritability. The Indian Journal of Animal Sciences. 83(12): 114–116.
  • Chaturvedi, A., Alam, W. and Chauhan, K. (2013): Robustness of the Sequential Testing Procedures for the Parameters of Zero-Truncated Negative Binomial, Binomial and Poisson distributions. Journal of Indian Statistical Association:51(2):313-328
  • Gurung, Bishal, Ghosh, Himadri and Prajneshu (2013). Forecasting volatile time-series data through Stochastic volatility model, Indian Journal of Agricultural Sciences, 83(12), 1368-71.
  • Gurung, Bishal (2013).  Modelling and forecasting of volatile time-series data: An application of Genetic Algorithm. International Journal of Agricultural and Statistical Sciences. 9, 87-94.
  • Gurung, Bishal (2013). An application of Exponential Autoregressive (EXPAR) nonlinear time-series model. International Journal of Information and Computation Technology. 3(4), 261-266.
  • Jha, G. K. and Sinha, K. (2013) Agricultural Price Forecasting Using Neural Network Model: An Innovative Information Delivery System, Agricultural Economics Research Review 26 (2)
  • C. P. Bhavana, C.P., Munirajappa, R., Surendra, H.S. and Rathod, S.  (2013). Effect of Rainfall Patterns on Crop Yield in Southern Dry Zone of Karnataka.  Environment & Ecology. 31 (2): 888-891.
  • Chnnappagoudar. B.B., Naganagoudar, Y.B., Rathod, S., Channappagoudar, S. B. and Babu. V.  (2013). Influence of herbicides on physiological characters of Brinjal (Solanum melongena L.). Bioinfolet, 10 (3 B): 1014 – 1018.
  • Chnnappagoudar, B.B., Naganagoudar, Y.B., Rathod, S.  Channappagoudar, S.B and Mane, S.S.  (2013). Influence of herbicides on physiological characters of Turmeric. Bioinfolet. 10 (3 B): 1019-1022.
  • Chnnappagoudar, B.B., Mane, S.S.  Naganagoudar, Y.B., Channappagoudar, S.B and Rathod, S.  (2013). Crop Weed Competition and Chemical Control of Weeds in Turmeric, Environment & Ecology. 31 (2): 532-536.
  • Chnnappagoudar, B.B., Babu, V., Naganagoudar, Y.B., Channappagoudar, S.B and Rathod, S.  (2013). Crop Weed Competition and Chemical Control of Weeds in Brinjal (Solanum melongena L.), Environment & Ecology. 31 (2): 532-536.
  • Chnnappagoudar, B.B., Babu, V., Naganagoudar, Y.B. and Rathod, S.  (2013). Influence of herbicides on morpho-physiological Growth parameters in turmeric (curcuma longa L.), The Bioscan, 8(3): 1019-1023.
  • Chnnappagoudar, B.B., Mane, S.S. Naganagoudar, Y.B. and Rathod, S.  (2013). Influence of herbicides on morpho-physiological Growth parameters in brinjal (solanum melongena L.), The Bioscan, 8(3): 1049-1052.
  • Kumar, Shiv, Rakesh Kumar, D. R. Singh, Anil Kumar, Prawin Arya and K. R. Chaudhary (2013). Equity, Efficiency and Profitability of migratory sheep production system in Rajasthan, Indian Journal of Animal Sciences, 83(9):976-982.

2012

  • S.P.Bhardwaj, Ashok Kumar and K. N. Singh (2012). Market Intelligence – An empirical Study of market behavior of agricultural commodity.  International Journal of Research in Commerce & Management, 3(5): 107.
  • Surendra Singh, A K Paul, K.N. Singh and Ashok Kumar (2012). Study of growth pattern of cattle under different climatic condition. The IUP Journal of Genetic & Evolution, 5(1): 41-46. 
  • D.R. Singh, Anil Kumar, N. Sivaramane, K.N. Singh and Prawin Arya . (2012). Application of Data Envelopment Analysis for Estimation of Farm Level Efficiencies in Rice Cultivation in Indo-Gangetic Plains of India. Int. J. Agricult. Stat. Sci. Vol. 8, No. 2, pp. 729-735.
  • Sanjeev Panwar, Anil Kumar, K. N. Singh, Md. Samir Farooqi and Abhishek Rathore.(2012). Using nonlinear regression techniques for analysis of           onion (Allium cepa) production in India. Indian Journal of Agricultural Sciences. 82 (12); 1051-4, 43-46.
  • Amrit Kumar Paul, Surendra Singh, Ashok Kumar, K.N. Singh and N. Okendro Singh.(2012). Modeling the Growth of Crossbred Piglets. Indian Journal of Animal Science 82 (9): 1098-1099.
  • Shweta Nagpal, Charanjit Kaur, Harshwardhan Chaudhary, Jagbir Singh, Braj Bhusan Singh and K.N. Singh. (2012). Lycopene content, antioxidant capacity and colour attributes of selected watermelon (Citrullus lanatus (Thunb.) Mansfeld ) cultivarsgrown in India. International Journal of Food Sciences and Nutrition; Early Online: 1–5.
  • Singh, N. Okendro, A.K. Paul, Surinder Kumar, Wasi Alam, N. Gopimohon Singh, K.N. Singh and Pal Singh (2013). Fitting of Partial Reparameterized Logistic Growth Model to Oil Palm Yield Data. International Journal of Agricultural and Statistical Sciences. 9(1):55-62.
  • C. Naveen, Dinesh Kumar,Wasi Alam, Rahul Chaubey, S. Subramanian and Rajagopal Raman (2012). A Model Study Integrating Time Dependent Mortality in Evaluating Insecticides Against Bemisia Tabaci (Hemiptera: Aleyrodidae). Indian Journal of Entomology,74(4):384-388.
  • Narayanaswamy, T., Surendra, H. S and Rathod, S.  (2012). Multiple stepwise regression analysis to estimate root length, seed yield per plant and number of capsules per plant in Sesame (Seasamum indicum L.). Mysore journal of agricultural sciences. Vol: 46 (3): 581-587.
  •  Narayanaswamy, T., Surendra, H. S and Rathod, S. (2012).  Fitting of statistical models for growth patterens of root and shoot morphological traits in Sesame (Seasamum indicum L.). Environment & Ecology. Vol: 30 (4): 1362-1365.
  • C. P. Bhavana, C.P., Munirajappa, R., Surendra, H.S. and Rathod, S. (2012). Modeling of Daily Rainfall using Gamma Probability Distribution. Environment & Ecology. Vol: 30 (3B): 884-888.
  • Praveen, K.V., Shiv Kumar, D. R. Singh, Prawin Arya, K. R. Chaudhary and Anil Kumar (2012). A study on economic behaviour, perception and attitude of households towards traditional and modern food retailing formats in Kochi, Indian Journal of Agricultural Marketing, 27(2), 142-151.
  • Singh, D. R., A. Kumar, Sivaramane N., K. N. Singh and Prawin Arya (2012). Application of Data Envelopment Analysis for Estimation of Farm Level Efficiencies in Rice Cultivation in Indo-Gangetic Plains of India, International Journal of Agricultural and Statistical Sciences, 8(2): 729-735.

Training Programmes Organized

Completed

S. No.Name of the trainingType of trainingVenueDuration
1Advanced Statistical Tools and Techniques for Modeling and Forecasting Agricultural Data Co-ordinator: Santosha Rathod
Co-Course Coordinator: Ravindra Singh Shekhawat
Winter School,
Education Division ICAR
ICAR-IASRI, New Delhi08-28, November, 2017
2Recent Developments in Statistical Modeling and Forecasting in Agriculture
Co-ordinator: K. N. Singh
Co-Course Coordinator: Rajeev Ranjan Kumar
CAFT, Education Division ICARICAR-IASRI, New Delhi28 December 2017 - 17 January 2018
3Statistical Modelling and Forecasting Techniques for Agricultural Data
Co-ordinator: Rajeev Ranjan Kumar
Co-Course Coordinator: Santosha Rathod and Ravindra Singh Shekhawat
Hindi Training programme to technical/Scientist of ICAR-IASRI, New Delhi.ICAR-IASRI, New Delhi09-14, February, 2017
4Advances in Statistical Modeling and Forecasting in Agriculture
Co-ordinator: Bishal Gurung
Co-Course Coordinator: Mrinmoy Ray
CAFT, Education Division ICARICAR-IASRI, New Delhi23 December 2016 - 12 January 2017
5Technology Forecasting Methods
Co-ordinator: K. N. Singh,
Co-Course Coordinator: Mrinmoy Ray and Santosha Rathod
Training to RA/SRF’s of ATFC projectICAR-IASRI, New Delhi20-21 July 2016
6Application of Forecasting Techniques in Agriculture Using Advanced Software Packages
Co-ordinator: Wasi Alam
Co-Course Coordinator: Kanchan Sinha
Hindi Training programme to technical/Scientist of ICAR-IASRI, New Delhi.ICAR-IASRI, New Delhi26-31, march, 2016
7Forecast Modelling Analytics in Crops
Co-ordinator: Prawin Arya
Co-Course Coordinator: Sanjeev Panwar
CAFT, Education Division ICARICAR-IASRI, New Delhi30 May- 19th June, 2014
8Forecast Modelling in Crops
Co-ordinator: K.N. Singh
Co-Course Coordinator:
Wasi Alam, Prawin Arya and Sanjeev Panwar
Summer school,
Education Division ICAR
ICAR-IASRI, New Delhi03- 23 September, 2013
9Advances in Statistical Genetics
Co-ordinator: Wasi Alam
Co-course Coordinator:
R. K. Paul and A.K. Paul
CAFT, Education Division ICARICAR-IASRI, New Delhi02-22 July 2013
10Recent Advances in Statistical Modelling Techniques
Co-ordinator: R.K. Paul
Co-Course Coordinator:
Bishal Gurung and A.K. Paul
CAFT, Education Division ICARICAR-IASRI, New Delhi31 May- 20 June 2013
11Advances in Quantitative Techniques for Policy Analysis in Agricultural Economics
Co-ordinator: Ashok Kumar
Co-Course Coordinator: DR Singh, Prawin Arya
CAFT, Education Division ICARICAR-IASRI, New Delhi06-26 December, 2007

Scientific Staff

Technical Staff

ASHWANI KUMAR

Ashwani Kumar

C.T.O.

ashwani.kumar@icar.gov.in

(011)-25847121-24

Extn: 4288

Personel Staff

SURAT RAM

Surat Ram

Private Secretary

surat.ram@icar.gov.in

(011)25847121-24   Extn: 4110

RAJ KARAN

Raj Karan

Skilled Sporting Staff

(011)-25847121-24   Extn: 4110

D.C. RABIDAS

D.C. RABIDAS

Bearer

(011)-25847121-24   Extn: 4110

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