Dr. Santosha Rathod, Senior Scientist(Agricultural Statistics)

Name:- Dr. Santosha Rathod

Designation: Senior Scientist (Agricultural Statistics)

Email ID: This email address is being protected from spambots. You need JavaScript enabled to view it.

Official phone number:- 040-24591319

Google scholar link:- https://scholar.google.co.in/citations?user=jpO-NcoAAAAJ&hl=en

Research gate link:- https://www.researchgate.net/profile/Santosha-Rathod

ORCID link:- https://orcid.org/0000-0001-9820-149X

Educational details

Sc. (Ag.) – 2009 – Agriculture and Allied Subjects, University of Agricultural Sciences Dharwad, Karnataka, India.
Sc. (Ag.) – 2011 – Agricultural Statistics, University of Agricultural Sciences Bangalore, Karnataka, India.
G. Diploma – 2014 – Software based statistical Analysis, Annamalai university, Tamil Nadu, India.
D. – 2017 – Agricultural Statistics, Banaras Hindu University, India.

Employment Record/Work Experience

Senior Scientist (Agricultural Statistics), ICAR-Indian Institute of Rice Research, Hyderabad, India (Level 12 – From 01/07/2023 to Present)
Scientist (Agricultural Statistics), ICAR-Indian Institute of Rice Research, Hyderabad, India (Level 11 – From 01/07/2018 to 30/06/2023)
Scientist (Agricultural Statistics), ICAR-Indian Institute of Rice Research, Hyderabad, India (Level 10 – From 15/06/2018 to 30/06/2018)
Scientist (Agricultural Statistics), ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India (Level 10 – From 01/07/2014 to 14/06/2018)

Area of Specialization

Agricultural Statistics
Statistical Modelling
Machine Learning
Time Series Analysis
Spatiotemporal Modelling
Genomic Selection

Important projects under taken

Institute projects as Principal Investigator

Development of statistical and machine learning models for genomic prediction, disease and insect pest surveillance in Rice crop under climate change scenarios (2023-2027)
Statistical modelling and soft computing approaches for genomic selection in Rice (2019-2023)
Forecasting of spatiotemporal TS data using Space Time Autoregressive Moving Average (STARMA) model (2015-2018)

Institute projects as Co-investigator

Smart precision models and Mobile Apps for real time advisories on Rice Crop Management (2021-Present).
Smart village(s) strategy for accelerated rice technology transfer (2019-Present)
On-Farm Adoption of IPM Technologies and impact analysis (2019-Present)
Study of rice vegetation in terms of crop stress to model the yield using NDVI (2019-Present).
Deciphering multiple (heat and drought) abiotic stress tolerance in rice (2022 – present)
Novel Genetic approaches for development of Climate Smart Rice Varieties (2020 – present)
Development of Hybrid Time Series Models using Machine Learning Techniques for Forecasting Crop Yield with Covariates (2015-2017)
Nonparametric bootstrap approach for constructing prediction intervals for non-linear and bivariate Time Series models (2015-2017)
Parameter estimation of Time Series models using Bayesian technique (2017-2018)
Future perspective of Bt technology in Indian agriculture. (2016-2028)

Externally funded projects as Co-investigator

DBT Funded Network Project on Crop Bioinformatics: Plant Genomics, Gene Regulatory Network and Novel RNA Molecules. NNP project: Decoding Agronomically Important Metabolic Pathways in Rice, Chickpea, Black Pepper and Ginger (2023-2028)
IRRI Philippines funded Insect-Pest and Disease Forecasting and Decision Support Systems in rice (2020-2023).
Evaluating IoT enabled AWD system for reducing GHG emissions and enhancing sustainability of rice production (2022 to Present)

Award and Honors

Recipient of Associate Fellow of the Telangana Academy of Sciences for the year 2022.
Recipient of Best Research Paper 2023- Crop Improvement Category for the paper entitled “Characterization of heterogeneity in popular rice landrace through field and molecular evaluation” published in Field Crop Research awarded by ICAR-IIRR, Hyderabad for the year 2020.
Recipient of Best Young Scientist Awards – 2023 under Social Sciences Category, awarded by ICAR-IIRR, Hyderabad.
Recipient of Best Young Scientist Awards – 2022 under Social Sciences Category, awarded by ICAR-IIRR, Hyderabad.
Recipient of Best Young Scientist Awards – 2021 under Social Sciences Category, awarded by ICAR-IIRR, Hyderabad.
Recipient of Outstanding Achievement Award in the field of Agricultural statistics awarded during 3rd International Conference (Hybrid Mode) on Food, Agriculture and Innovations during 24-26 December, 2021.
Recipient of Best Research Paper – 2021 Social Science Category for the paper entitled “Two-Stage Spatiotemporal Time Series Modelling Approach for Rice Yield Prediction & Advanced Agroecosystem Management” awarded by ICAR-IIRR, Hyderabad for the year 2021
Recipient of Best Research Paper – Social Science Category for the paper entitled “A hybrid spatiotemporal modelling: an application to space-time rainfall forecasting” published in theoretical and applied climatology awarded by ICAR-IIRR, Hyderabad for the year 2020.
Recipient of Dr. G R Seth memorial young scientist award of Indian society of agricultural statistics awarded by the Indian society of agricultural statistics in the year 2017.
Recipient of UGC Fellowship for Ph.D. Program awarded by the UGC-Banaras Hindu University, India for the period 2012-2014.

Methodologies developed

Developed Two Stage Spatiotemporal Time Series models to predict Rice yield of Andhra Pradesh.
Developed prediction model for forecasting rice gall midge populations using count time series and machine learning approaches.
Developed Machine Learning-Based Time-Series Intervention Models to Assess the Impact of COVID-19 Lockdown on Rice Price in India.
Developed AI based genomic prediction models for genomic selection in SNP RDP Rice population.
Developed Bayesian multi-trait multi environment genomic prediction models for genomic selection in Rice.
Statistical modelling of AICRIP data for genetic gain in rice yield.
Fuzzy inference system (FIS) based improved STARMA model.
Developed Hybrid spatiotemporal models to forecast spatiotemporal time series.
Developed Artificial Intelligence (AI) based time series models to predict the water stress (Drought) in Hyderabad region of India.
AI based intervention models for assessing the impact of interventions in time series data.
Developed difference in difference regression model to assess the impact of rice production technologies.
Developed CERES-Rice Model for Rice Yield Gap Analysis.
Developed technology forecasting methodology for envisioning Bt technology scenario in Indian agriculture
Developed tuned-support vector regression model to forecast the cotton production.
Developed zero inflated count regression models to model the relationship between yellow stem borer population and weather variables
Development of new approach for spatiotemporal modelling using fuzzy techniques in conjunction with K-means clustering
Development of methodology for Robust Estimation of Single Exponential Smoothing model using Kalman Filter.
Construction of multi-stress responsive gene co-expression networks in chickpea using systems biology approaches.
Developed hybrids models with the combination of different classical statistical models and artificial intelligence models to capture the linear and nonlinear pattern present in the data sets.
Time series and AI based methodologies for modelling and forecasting various agricultural data sets.

Students Guided

Major Guide: M.Sc. (Agricultural Statistics): 4

Co-Guide/Member: Ph.D. – 10: M.Sc. – 15

Editors of the Journals

As Editor: Associate editor (Agricultural Statistics) Journal of Rice Research

Member of Scientific Society

Life Member - Indian Society of Agricultural Statistics, India.
Life Member - Society of Statistics, Computer and Applications, India.
Life Member - Society for Advancement of Rice Research.

Training Organized

SERB Sponsored High-end workshop on “Statistical and machine learning techniques for agricultural systems modelling and forecasting using R” (under the KARYASHAALA scheme –a SERB initiative) during 18-30 July 2022 as Course Director.
SERB Sponsored High-end workshop on “Multivariate Statistical Machine Learning Methods for Modelling Agricultural Data” (under the KARYASHAALA scheme –a SERB initiative) during 24 July-4 August 2023 as Course Director.
Short Training Course on “Statistical Analysis of Agricultural Data Using R” during 30 Jan to 4 Feb, 2023.
Organized Online Training Program on “Virtual Users Training cum Workshop on AICRIP Intranet functionalities 15-17 February, 2022 in association with Society for Advancement of Rice Research and Indian Institute of Rice Research, Rajendranagar, Hyderabad as Course Director.
Organized Online Training Program on “Advanced Statistical Techniques for Data Analysis using R” 03rd to 15th January 2022 sponsored by Society for Advancement of Rice Research with Indian Institute of Rice Research, Rajendranagar, Hyderabad as Course Director.
Organized ICAR Sponsored 21 days’ winter school on “Advanced Statistical Tools and Techniques for Modelling and Forecasting Agricultural Data” during 08-28, November, 2017 at ICAR-IASRI, New Delhi as Course Director.
Six days Hindi Training programme on “Statistical Modelling and Forecasting Techniques for Agricultural Data” to technical/Scientist of ICAR-IASRI, New Delhi, from 09-14, February, 2017 as Co-Course Coordinator.
Two days Training to RA/SRF’of ATFC project on Technology Forecasting Methods at ICAR-IASRI, New Delhi from 20-21 July 2016 as Co-Course Coordinator.

Training Undergone

CAFT training program on "Development of AI based Android Applications in Agriculture (Online) under the aegis of Centre for Advanced Faculty Training (CAFT) during March 05-25, 2024 organized at ICAR-Indian Agricultural Statistics Research Institute, New Delhi.
Training Programme on “Statistical analysis and interpretation of agricultural data" organized by ICAR-IASRI during March 01 - 10, 2023.
Ten days National FDP (Online) on “Understanding Research and Statistical Analysis using SPSS “from 07-16 March, 2022 organized by IIT, Tiruchirappalli.
Online training program on Analytical Techniques for Decision Making in Agriculture during 5-25 Feb 2022 organized by ICAR-NIAP, New Delhi
Online training program on Transcriptomic Data Analysis” organized by Centre for Agricultural Bioinformatics, ICAR-IASRI, New Delhi-12 during September 28-30, 2021.
Training program on “Analysis of Multi-Location Experiments” during 28-30 October, 2021 organized by ICAR-NAARM, Hyderabad
Online training program on “Transcriptomic Data Analysis” during 28-30 September, 2021 organized by ICAR-IASRI, New Delhi.
Training program on “Genomic Selection in Plant Breeding through Advanced R & Machine Learning” from 18-22 November, 2019 organized by ICRISAT, Hyderabad
National Workshop on Bioinformatics in Agriculture during 26-27 July, 2019 organized by ICAR-NAARM, Hyderabad.
Foundation Course for Agricultural Research Management (FOCARS) at ICAR-NAARM Hyderabad during 01 Jul, 2014 to 30 Sep, 2014 (3 Months).
Professional Attachment Training on "Application of machine learning techniques in time series analysis" at Indian Statistical Institute Bengaluru during 6 December, 2014 to 6 March 2015 (3 Months).

Publications (Top 30)

Shivakumar Maranna, Vennampally Nataraj, Giriraj Kumawat, S. P. Mehetre, Rajendra Reddy, Santosh Jaybhay, Suresh P. G., Santosha Rathod, Nisha Agrawal, Vangala Rajesh et al. (2024). Understanding of G× E interactions of yield attributes in soybean MAGIC population and characterization for charcoal rot resistance. Agronomy Journal. 1–12.
Vanama, S., Gopalan, N.R., Pesari, M., Baskar, M., Gali, U.D., Lakshmi, D.L., Koteshwar, P., Jesudasu, G., Rathod, S., Prasad, M.S. and Panuganti, R. (2024). Native bio-control agents from the rice fields of Telangana, India: characterization and unveiling the potential against stem rot and false smut diseases of rice. World Journal of Microbiology and Biotechnology, 40(1), p.2.
Suman, K., Madhubabu, P., Jaldhani, V., Rathod, S., Subbarao, L.V., Sundaram, R.M. and Neeraja, C.N. (2023). Characterization of heterogeneity in popular rice landrace through field and molecular evaluation. Field Crops Research, 304, p.109181.
Patil R, Polisgowdar BS, Rathod S, Bandumula N, Mustac I, Srinivasa Reddy GV, Wali V, Satishkumar U, Rao S, Kumar A, Ondrasek G. 2023. Spatiotemporal characterization of drought magnitude, severity, and return period at various time scales in the Hyderabad Karnataka Region of India. Water, 15(13), p.2483.
Dasari A, Balakrishnan D, Rathod S, Rao PV, Vemireddy LR, Neeraja CN, Vanisri S, Ranjith KN, Sundaram RM, Badri J. 2023. Multi-environment testing revealed the effect of yield genes on the grain yield stability in diverse rice germplasm. Cereal Research Communications, pp.1-18.
Chintalapati P, Rathod S, Repalle N, Varma NR, Karthikeyan K, Sharma S, Kumar RM, Katti G. 2023. Insect pest incidence with the system of rice intensification: results of a multi-location study and a meta-analysis. Agronomy, 13(4), p.1100.
Patil R, Polisgowdar BS, Rathod S, Kumar U, Wali V, Reddy G, Rao S. 2023. Comparison and evaluation of drought indices Using Analytical Hierarchy Process (AHP) over Raichur district, Karnataka. Mausam, 74(1), pp.43-56.
Saha A, Singh KN, Ray M, Rathod S, Dhyani M. 2022. Fuzzy rule–based weighted space–time autoregressive moving average models for temperature forecasting. Theoretical and Applied Climatology, 150(3), pp.1321-1335.
Rathod S, Chitikela G, Bandumula N, Ondrasek G, Ravichandran S, Sundaram RM. 2022. Modeling and forecasting of rice prices in India during the COVID-19 lockdown using machine learning approaches. Agronomy, 12(9), p.2133.
Patil R, Nagaraj DM, Polisgowdar BS, Rathod S. 2022. Forecasting potential evapotranspiration for Raichur district using seasonal ARIMA model. Mausam, 73(2), pp.433-440.
Bandumula N, Rathod S, Ondrasek G, Pillai MP, Sundaram RM. 2022. An economic evaluation of improved rice production technology in Telangana State, India. Agriculture, 12(9), p.1387.
Rathod S, Yerram S, Arya P, Katti G, Rani J, Padmakumari AP, Somasekhar N, Padmavathi C, Ondrasek G, Amudan S, Malathi S. 2021. Climate-based modeling and prediction of rice gall midge populations using count time series and machine learning approaches. Agronomy, 12(1), p.22.
Saha A, Singh KN, Ray M, Santhosha Rathod, Choudhury S. 2021. Modelling and forecasting cotton production using tuned-support vector regression. Current Science. 121(8):1090-1098.
Rathod S, Saha A, Patil R, Ondrasek G, Gireesh C, Anantha MS, Rao DV, Bandumula N, Senguttuvel P, Swarnaraj AK, Meera SN. 2021. Two-stage spatiotemporal time series modelling approach for rice yield prediction & advanced agroecosystem management. Agronomy, 11(12), p.2502.
Chitikela G, Admala M, Ramalingareddy VK, Bandumula N, Ondrasek G, Sundaram RM, Rathod S. 2021. Artificial-intelligence-based time-series intervention models to assess the impact of the COVID-19 pandemic on tomato supply and prices in Hyderabad, India. Agronomy, 11(9), p.1878.
Deepika K, Lavuri K, Rathod S, Yeshala CM, Jukanti AK, Reddy SN, Lv SR, Badri J. 2021. Multivariate analysis of geographically diverse rice germplasm for genetic improvement of yield, dormancy and shattering-related traits. Plant Genetic Resources, 19(2), pp.144-152.
Suman K, Neeraja CN, Madhubabu P, Santosha Rathod, Sonali B, Jadhav KP, Kumar JA, Chaitanya U, Smita CP, Surekha HR, Subbarao LV, Voleti SR. 2021. Identification of promising RILs for high grain zinc through genotype× environment analysis and stable grain zinc QTL using SSRs and SNPs in rice (Oryza sativa L.). Frontiers in plant science, 12: Article No.587482.
Saha A, Singh KN, Ray M, Rathod S. 2020. A hybrid spatio-temporal modelling: an application to space-time rainfall forecasting. Theoretical and Applied Climatology, 142, pp.1271-1282.
Ray M, Singh KN, Ramasubramanian V, Paul RK, Mukherjee A, Rathod S. 2020. Integration of wavelet transform with ann and wnn for time series forecasting: an application to indian monsoon rainfall. National Academy Science Letters, 43(6), pp.509-513.
Babu PM, Neeraja CN, Rathod S, Suman K, Uttam GA, Chakravartty N, Lachagari VR, Chaitanya U, Rao LV, Voleti SR. 2020. Stable SNP allele associations with high grain zinc content in polished rice (Oryza sativa L.) identified based on ddRAD sequencing. Frontiers in Genetics, 11, p.763.
Aravind K. Konda, Parasappa R. Sabale , Khela R. Soren , Shanmugavadivel P. Subramaniam, Pallavi Singh, Santosha Rathod, SushilK.Chaturvedi and Narendra P. Singh. 2019. Systems biology approaches reveal a multi-stress responsive WRKY transcription factor and stress associated gene co-expression networks in chickpea. Current Bioinformatics. 14(7):591-601.
Saha Amit, Singh KN, Ray Mrinmoy, kumar Sanjay, Santosh Rathod. 2019. A New Approach for Spatio-temporal Modelling and forecasting based on fuzzy techniques in conjunction with k-means clustering. Journal of the Indian Society of agricultural Statistics. 73(2):111-120.
Alam W, Ray MR, Kumar RR, Sinha KA, Rathod SA, Singh KN. 2018. Improved ARIMAX modal based on ANN and SVM approaches for forecasting rice yield using weather variables. Indian Journal of Agricultural Sciences. 88(12).1909-1913.
Rathod S, Gurung B, Singh KN, Ray M. 2018. An improved space-time autoregressive moving average (STARMA) model for modelling and forecasting of spatio-temporal time-series data. Journal of the Indian Society of Agricultural Statistics, 72(3), pp.239-253.
Rathod S, Singh KN, Patil SG, Naik RH, Ray MR, Meena VS. 2018. Modeling and forecasting of oilseed production of India through artificial intelligence techniques. Indian Journal of Agricultural Sciences. 88(1), pp.22-27.
Rathod S, Mishra GC. 2018. Statistical models for forecasting mango and banana yield of Karnataka, India. Journal of Agricultural Science and Technology, 20(4), pp.803-816.
Alam W, Sinha K, Kumar RR, Ray M, Santosha Rathod, Singh KN, Arya P. 2018. Hybrid linear time series approach for long term forecasting of crop yield. The Indian Journal of Agricultural Sciences. 88(8):1275-1279.
Rathod S, Singh KN, Arya P, Ray M, Mukherjee A, Sinha K, Kumar P, Shekhawat RS. 2017. Forecasting maize yield using ARIMA-Genetic Algorithm approach. Outlook on Agriculture, 46(4), pp.265-271.
Rathod S, Mishra GC, Singh KN. 2017. Hybrid time series models for forecasting banana production in Karnataka State, India. Journal of the Indian Society of Agricultural Statistics, 71(3), pp.193-200.
Rathod, S., Singh, K., Paul, R., Meher, S., Mishra, G., 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. 2017-103.