Dr. L. M. Bhar


Dr. L. M. Bhar


Sr No.Title of the projectProject teamDurationFunding agency
1.Development of Rank Based Stability Measures for Selecting GenotypesPrakash Kumar, A K Paul, Samarendra Das, L M Bhar10.09.2015 to 31.08.2017ICAR-IASRI, New Delhi
2.Stochastic differential equation models and their applications to agriculture.Prajneshu, Himadri Ghosh, L M Bhar6.11.2015 to 05.11.2018DST
3.Study of Long Memory and Periodicities in Climate Variables in Different Agro-Climatic Zones of IndiaRanjit Paul, L M Bhar, A K Paul19.04.2017 to 18.05.2020ICAR-IASRI, New Delhi


Sr No.Title of the projectProject teamDurationFunding agency
1.Designs for Mixture Experiments in AgricultureKrishan Lal, VK Gupta, PK Batra, Lalmohan Bhar 2.5 years ICAR-IASRI, New Delhi
2.A Study on Multiple Bio-assaysL M Bhar and V K Gupta1.5 yearsNational Professor Fund
3.Analysis of Experimental Designs with t-Family of Error DistributionKrishan Lal, Rajender Parsad , VK Gupta and Lalmohan Bhar2 yearsICAR-IASRI, New Delhi
4.Designs for Single Factor and Multifactor Experiments and Their Application in Agricultural System Research (A scheme under National Professor (ICAR))V K Gupta and L M Bhar 9 yearsNational Professor Fund
5.Strengthening Statistical Computing in NARS (Under NAIP) Rajender Parsad, PK Malhotra , VK Mahajan, Seema Jaggi, Samir Farooqui, Ramasubramanian V, LM Bhar, AK Paul and N Sivaramane3 yearsNAIP
6.Planning, designing and analysis of data relating to experiments for AICRP on long-term fertilizer experimentsL M Bhar From IASRI1 year 1 monthICAR-IASRI, New Delhi
7.Development of forecasting methodology for fish production from ponds of uplandN Okendro Singh, Sanjeev Panwar , LM Bhar and Ranjana Agrawal2 years 6 monthsICAR-IASRI, New Delhi
8.Outliers in designed experiments. LM Bhar, Rajender Parsad, VK Gupta3 yearsAP Cess Fund, ICAR
9.Development of weather based forewarning system for crop pests and diseases. Ranjana Agrawal, SC Mehta, LM Bhar, Amrender Kumar3 yearsNATP
10.Modeling of forecasting of crop yield using weather parameters and agricultural inputs (Funded through AP Cess Fund, ICAR).Ranjana Agrawal, Asha Saksena, LM Bhar, Amrender Kumar, Madan Mohan,YS Kesava Rao2 yearsAP Cess Fund, ICAR
11.Forecasting fish production from pondsL M Bhar, S S Walia and A K Roy2 yearsICAR-IASRI, New Delhi
12.Development of Forewarning System of Potato AphidsT P Trivedi, R C Jain, L M Bhar and S C Mehta2 yearsNCIPM




Head (A) Statistical Genetics

  1. Bhar, L. M. and Sankalpa Ojha (2017): Influence Measures in Blocked Designs of Experiments with Correlated Errors, Communications in Statistics – Theory and Methods, 46 (5), 2411-2434.
  2. Bhar, L. M. (2016). Efficient block designs for symmetric parallel line assays, Cogent Mathematics, 3(1), 1 – 11.
  3. Bhar, L. M. (2013). A diagnostic tool for detecting outliers in experimental data, Model Assisted Statistics and Applications, 8(1),61-68.
  4. Bhar, L. M. (2013). Robustness of Variance Balanced Block Designs. Sankhya B. DOI: 1007/s13571-013-0073-4.
  5. Bhar, L. M. and Dey, A. (2003). Robustness of nested balanced incomplete block designs against missing data. Journal of Indian Society of Agricultural Statistics, 56(1), 25 – 38.
  6. Bhar, L. M. and Gupta, V. K. (2003). Study of outliers under variance – inflation model in experimental designs. Journal of Indian Society of Agricultural Statistics, 56(2), 142 – 154.
  7. Bhar, L. M. and Amitava Dey(2003). Robustness of Block Designs for Diallel Crosses Against Missing Data. Communications in Statistics – Theory and Methods, 32(1), 193 –213.
  8. Bhar, L. M. and Amitava Dey (2002). Triallel-Cross Block Designs That Are Robust Against Missing observations. Utilitas Mathematica, 65, 231-242.
  9. Bhar, L. M. and V. K. Gupta (2002). Robust Row-Column Designs for Complete Diallel Cross Experiments. Metrika, 56, 83 – 90.
  10. Bhar, L. M. and Gupta, V. K. (2001). A useful statistic for studying outliers in experimental designs. Sankhya, B63, 338-350.
  1. Gupta, V. K., Prasad, R., Bhar, L. M. and Mandal, B. N. (2016). Statistical Analysis of Agricultural Experiments (Part-I; Single Factor Experiments). ICAR-Indian Agricultural Statistics Research Institute, New Delhi. ISBN Number: 987-93- 5265-859-6
  2. Sud, U. C., Hukum Chandra, Bhar, L. M. and Sarkar, S. K. (2015). Statistics and Informatics in Agricultural Research. Published by Indian Society of Agricultural Statistics.
  3. Bhar, L. M. (2015). Regression analysis diagnostics and remedial measures. pp. 245-270 In: Rajni Jain and S S Raju Edition. Decision support system in agriculture using quantitative analysis, Agrotech Publishing Academy, ISBN: 978-81-8321-395-0
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