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Venugopalan R

Venugopalan R
Designation: 
Principal Scientist (Agril. Statistics)
Division/Section: 
Division of Social Sciences and Training
Specialisation: 
Statistical modeling and Biometrics
Qualification: 
Ph.D (Agril.Stat) IASRI (1996)
Experience (No. of Years): 
19 years
Research Accomplishments: 

•Developed stability models in Watermelon, Chilli and Onion and identified lines/hybrids which are stable for commercial exploitation, and for release as a variety.

•Developed a statistical package for performing stability analysis research in vegetable crops.

•Developed ANN models to arrive at the crop logging parameters (significant yield contributing biometric factors) across different crop growth stages along with their optimum values for Banana (cv Ney poovan & Robusta) and Papaya (cv Surya).

•Developed statistical models for optimizing the role of weather factors on disease incidence of Anthracnose & Downy mildew in Grapes (cv Anab-E-Shahi), Powdery mildew in Mango (cv Alphonso) and Blossom blight in Mango (cv Totapuri).

•ANN models for population dynamics of Thrips in chilli and capsicum (across different rating) in relation to weather factors were developed.

•A menu driven statistical package for horticultural research (SPHR 1.0) was developed on windows platform facilitating day-to-day IIHR research projects statistical data analysis.

•Statistical models were developed for describing ideo-type canopy architecture of Thompson Seedless vine & Alphonso

•Suggested statistical procedures to solve the problems of multi-collinearity/outliers in entomological experiments, before proceeding for carrying out classical regression analysis

•Constructed advanced statistical experimental designs for varietals/germplasm evaluated under resource constraint scenario(Crop: Okra) •Developed a nonparametric index for assessing the relative performance of IIHR technologies

•Developed statistical models to ascertain reasons for aril browning in Pomegranate

•Developed a statistical model for identifying factors increasing Jasmine crop productivity *RS Models for optimising input-use (nutrient/water) efficiency in Acid lime and Mango

Lead for carrying our basic research in precision farming techniques in Banana/Papaya had been emanated by evolving crop-logging statistical models to identify significant yield indicating biometrical traits along with their desired optimum values across different crucial phenological crop growth stages.

a)Design of experiments: Optimum sample size for conducting field experiments in vegetables, fruits and ornamental were standardized by conducting several uniformity trails. Response surface models were developed to work out the optimum values of Evaporation Replenishment & Recommended dose of fertilizer with their corresponding yield so as to increase the input use efficiency in Mango. Response surface models were developed to Optimize the role of N, K and Ca on the influence of leaf hopper in brinjal Developed a balanced incomplete block design structure for evaluating breeding germplasm lines as a measure of improving input use efficiency in crop research b)Statistical modeling: Crop-logging models: Statistical models were developed using ANN theory to suggest the best indicators of crop-yield across its various growth-stages and the optimum estimates of crop-logging parameters required at each stages were worked out in Papaya and Banana. Substrate dynamics models in Tomato were constructed to optimize the role of various soil, biochemical and microbial parameters. Developed statistical models to identify the factors influencing pruning time on enhancing the yield and quality of Jasminum sambac flowers during off-season. Nonlinear stochastic models for disease forecasting in Grapes: Logistic and Gompertz nonlinear stochastic statistical models were developed to express the downy mildew disease progression. Method for revalidation of canopy architecture model in Mango based on resampling procedure. A quick model for estimation of leaf area in Fig (Cv Deanna) using non-destructive sampling approach Bootstrap method to evaluate the sampling efficiency and arrive at optimum sample size for leaf area estimations in Fig(Poona) by non-destructive sampling. Partial least square (PLS) regression models were developed, based on secondary metabolites (56 isolates) profiling by TLC for 7 different alternaria species and to predict the specific chemical diversity among 7 alternaria species. Diversity studies on Brinjal accessions for identifying resistance traits for Gallmidge. Non-linear statistical models were developed to study the population dynamics of thrips across different ratings in Capsicum Developed ideo-type canopy architecture model in Alphonso mango for higher productivity Climate change models: 1.Developed statistical models for optimizing the role of weather factors on disease incidence of Anthracnose & Downy mildew in Grapes (cv Anab-E-Shahi), Powdery mildew in Mango (cv Alphonso) and Blossom blight in Mango (cv Totapuri). 2.ANN models to express the nonlinear relation among climatic factors vis-à-vis thrips incidence in Capsicum 3.Development of population dynamics models for thrips in Chilli (to assess the time lag of climatic factors with thrips inoculum severity) 4.To study the effect of climatic change on trap catches of cucurbit fruit fly and fruit infestation on bitter gourd c)Biometrics: Stability models were developed to identify proper pool of superior lines/genotypes/hybrids suitable for ideal/poor and good environments useful in hybridization programme in vegetable crops (Watermelon, Onion, and Chilli) based on 4 years data on yield and attributing traits Identified factors attributing to aril browning in pomegranate by developing a selection index based model Developed a statistical package for performing stability analysis research in vegetable crops. A menu driven statistical package for horticultural research (SPHR 1.0) was developed on windows platform facilitating day-to-day IIHR research projects statistical data analysis. d)Nonparametric methods: Nonparametric index for assessing the relative performance of IIHR technologies were developed. e)Variety released and genetic stock registered: As a multi-disciplinary research team member of Ornamental breeding program, released a Gladiolus variety Arka Naveen (for flower quality having 9 days of vase life as a prominent character with yield 1-1.5 marketable spikes/corm). As a multi-disciplinary research team member of Ornamental breeding program, Registered (IC0584125; INGR:10067;) a gladiolus germplasm at PGRC/NBPGR, New Delhi, (for Floret colour), under plant germplasm registration system of ICAR 2010. f)Software/database developed Developed Window based (GUI) Statistical Package for Horticultural Research (SHPH V 1.0). Developed Bio-stat Package for Horticultural Crops Research (Biostat IIHR V 1.0) Developed a database Horticultural database system (HDS V 1.0) Organized an in-house (six batch of a week duration) Statistical training program on Horticultural Data Analysis Recognized as faculty with UAS, Bangalore, UHS, Bagalkot, APHU, A.P and Jain University, Bangalore for guiding students and course leader for offering statistics courses. Guided four M.Sc (Agricultural Statistics) student as a Chairman, UAS, Bangalore and served/serving as a statistician for 80 Ph.D/M.Sc students (Horticulture/ Soil Science, Entomology, Agril. Statistics) at UAS, UHS(B) & IARI. Identified as expert (Statistics) to serve as a Faculty member of Central silk Board (CSB) to conduct statistical training along with IIM(B)/IISc professors to Directors, Asst. Directors and Scientists of CSB during 2002,2003,2004. Offered as course leader AST 601: Applied Regression Analysis (2+1) for the Ph.D students of UHS (B) during 2010,2011,2012,2013,2014,2015,2016 sessions. Offered as course leader PGS 504: Basic Statistical methods for Agricultural Research (2+1) for the Ph.D students of IARI-IIHR during 2014-15. Offered as course leader AST 602: Advanced Statistical Genetics (1+1) for the Ph.D students of IARI-IIHR during 2014-15 and 2015-16. List of crops covered under multi-disciplinary research projects of stat lab, IIHR (since 2000) Fruit crops: Banana/Papaya (Crop logging models) Mango/Grapes/Fig (Canopy architecture models) Mango/Grapes (disease forecasting models) Pomegranate (Selection index) Mango, Acid lime, Passion fruit (Response surface models) Vegetable crops: Chilli, Cucumber, Watermelon, Brinjal and Onion: Biometrical/stability models Okra: Advanced designs for evaluating germplsam lines Tomato: Substrate dynamics models Chill, Capsicum, Brinjal, Onion, melons: Pest population dynamics models Ornamentals Jasmine, Rose, Gerbera (crop production models) Under consultancy services extended Statistics lab ,IIHR extends statistical consultancy on planning, designing, analyzing and interpretation of scientific project data and provide training for the same. Editor, JHS since 2009 for assessing statistical adequacy of the article submitted for publication.

Important Publications: 

R. Venugopalan and K.S.Shamasundaran. (2003). Nonlinear regressions: A realistic modeling approach in horticultural crop research. J. of Indian Society of Agrl. Statistics.56:1-6. M.Mani, A.Krishnamoorthy, and R.Venugopalan (2004). Role of the Aphelinid Parasitoid Encarsia guadeloupae in the Suppression of the Exotic Spiralling Whitefly on Banana in India. Biocontrol Science and Technology, Canada (September 2004). Vol. 14. No.6. 619-622. N.K.Krishnakumar, R.Venugopalan and P.N.Krishnamoorthy, (2004). A statistical modeling approach to study the influence of weather parameters on the leafminer in South India. Pest Management in Horticultural Ecosystems. Vol.10. No.1. pp 55-59. R.Venugopalan and R.Veere Gowda (2005). Stability Analysis In Onion: A Statistical Look. J. Indian Soc. Coastal agric. Res., 23(2), 123-29. R.Venugopalan and K.S.Shamasundaran (2005). Statistical model for evolving crop-logging technique in banana. Trop. Agric. (Trinidad), 82(1):25-29. Shikhamany, S.D., Somkuwar, R.G. and Venugopalan, R. (2008). Evaluation of canopy efficiency using leaf area index in thompson seedless vines. Acta Hort. 785:389-392. Rawal, R.D., Venugopalan, R. and Saxena, A.K. (2008). A statistical model for describing the epidemiology of incidence of downy mildew in grapes. Acta Hort. (ISHS) 785:279-284. Sujatha A. Nair, Sujatha, K. and Venugopalan, R. 2009. Influence of pruning time on enhancing the yield and quality of Jasminum sambac flowers during off-season. Indian J. Agric. Sci., 79 (11): 857-60. S. H. Jalikop, R. Venugopalan and R. Kumar (2010). Association of fruit traits and aril browning in pomegranate (Punica granatum L.). Euphytica (2010) 174:137–141. K.Srinivas,V.V., Sulladmath,R. Palaniappan and R. Venugopalan (2010). Plant Water Relations, Yield and Nutrient Content of Passion Fruit in Relation to Evaporation Replenishment and Fertigation. Indian Journal of Horticulture (2010). Vol. 67, No. 3. PP 1;6. R.Venugopalan and R.D.Rawal (2011). Effect of outliers in statistical modelling for predicting the outbreak of anthracnose in grapes. Indian J. Agric. Sci., 81 (10): 61-63. R.Venugopalan (2010). Application of statistical principles for evolving crop-logging models in banana (cv Ney Poovan). Tropical Agriculture, 87(1), pp. 29-32. H. P. Sumangala, K. Manivannan, A. S. Sidhu and R. Venugoplan (2011). Molecular characterization of senecio species using RAPD markers. Plant Archives. 11 (2): 657-660. R Venugopalan and K Madhavi Raddy (2010). Stability analysis for fruit yield and attributing traits in chilli. Veg.Sci. 37 (2): 141-145. Rajiv Kumar, Deka, B.C, and R.Venugopalan (2012). Genetic variability and trait association studies in gerbera (Gerbera jamesonii) for quantitative traits. Indian Journal of Agricultural Sciences 82 (7): 615. George, S., Venugopalan, R., Balakrishna, B., & Hegde, M. R. (2012). Training Variables Influencing Training Outcome. Journal of Extension systems.12(2):35-43. N Vijay, R Venugopalan, A Srinivasaraghavan (2013). The influence and reliability of weather parameters on incidence of downy mildew in grapes. BIOINFOLET – A Quarterly Journal of Life Sciences,10(3a): 848- 850. Pratheepa,M., Meena,K., Subramaniam,K.R., Venugopalan,R., Bheemanna,H (2011). A decision tree analysis for predicting the occurrence of the pest, Helicoverpa armigera and its natural enemies on cotton based on economic threshold level. Current Science, VOL. 100, NO. 2, 25 pp 238-46. Devi, B. Nightingale, M. Krishnan, R. Venugopalan and B.K. Mahapatra, 2013. Artificial Neural Network Model for Synergy Analysis of Input Markets in Ornamental Fish Trade in Mumbai, Agricultural Economics Research Review, 26(1):83-90. G.S. Ravi, R.Venugopalan, K. Padmini and D.M. Gowda (2013). Nonparametric measures for assessing yield stability in cucumber. International Journal of Agricultural and Statistical Sciences. 9(1):365-371. S.D. Shikhamany, Sanjay K. Jeughale, Kailas N. Khapre and R. Venugopalan (2015). Variation in relation between yield and yield attributes in ‘Thompson Seedless’ grape and its clones.J. Hortl. Sci. 10(1):8-12. Venugopalan, R. (2015). Yield prediction in banana (Musa × paradisiaca) (cv Grand Naine) by ANN models. The Indian Journal of Agricultural Sciences. 85(6): 859-60. R.Venugopalan and N. Vijay (2015). Nonlinear Logistic Model for Describing Downy Mildew Incidence in Grapes. J. of Indian Soc., of Agri., Stat.,69(1):19-25. V. Srilatha, Y.T.N. Reddy, K.K. Upreti, R. Venugopalan, and H.L. Jayaram (2016). Responses of pruning and paclobutrazol in mango (Mangiferaindica L.): changes in tree vigour, flowering and phenols. J. Applied Hort. 11(2). 871-878. R. Venugopalan, M.R. Dinesh and T. Janakiram (2016). PG Education at IIHR: Present Status and Future Prospects. Indian Horticulture. 61(3):23-24. V. Sridhar, L. S. Vinesh, M. Jaya Shankar and R. Venugopalan (2016). Climex Based Spatio-Temporal Analysis For Predicting The Number of Generations of Spodoptera Litura (Fabricius) (Lepidoptera: Noctuidae) Under Climate Change Scenario. The Bioscon., An International Quarterly Journal of Life Sciences. 11(2): 871-878. Sujatha A. Nair and R. Venugopalan (2016). Stability analysis of nutrient scheduling for lean season flowering in Arabian jasmine (Jasminum sambac). Indian Journal of Agricultural Sciences. 86(3): 321–325. AN Ganeshamurthy, V Ravindra, R Venugopalan, Malarvizhi Mathiazhagan, RM Bhat (2016). Biomass Distribution and Development of Allometric Equations for Non-Destructive Estimation of Carbon Sequestration in Grafted Mango Trees. Journal of Agricultural Science, 8(8): 201-211.

Awards & Recognitions, Patents, Inventions, etc: 

• Multi-disciplinary group member for releasing a gladiolus variety Arka Naveen: Released (for flower quality) and germplasm IIHR-5 of gladiolus (INGR 10067) as collaborator with breeder. • Gold medalist during B.Sc Statistics (Hons) at St. Joseph’s college, Trichy • ICAR research fellowship for pursuing M.Sc (Agril. Stat) and Ph.D (Agril. Stat) at IASRI, New Delhi during 1991-93 and 1993-96, respectively. • Recognized scientific personal for student guidance/evaluation at UAS, UHS, APHU, NIMHANS, Jain University and CSB • Guided as Chairman 4 M.Sc (Stat) students at UAS (B) and member for 80 students in the division of Horticulture, Soil Science, and Statistics. • Editor for Journal of Horticultural Sciences, Bangalore • Nodal person for SAS and PIMS, ICAR Chairman PG Education for Monitoring & Implementation of IARI-IIHR Ph.D (Hort. & PHT) program

Contact Details
Address for Communication: 
Principal Scientist (Agril. Stat), Division of Social Sciences and Training, IIHR, Bangalore-89
Email Address: 
venur@icar.org.in, gopalantry@yahoo.com
Telephone #: 
93416 35491
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