M.Sc Agronomy
The M.Sc. (Ag.) Agronomy programme at the Doon School of Modern Agriculture & Forestry is a research-intensive, technology-forward postgraduate degree designed for graduates
who wish to deepen their expertise in crop science, soil-plant relationships, and sustainable intensification.
Agronomy sits at the heart of India's food security mission. This programme prepares students not only in classical agronomic principles but in the digital tools transforming the discipline: Crop Simulation Models (DSSAT, AquaCrop, FAO CROPWAT), GIS-based precision agriculture, AI-driven diagnostics, and advanced statistical computing (R-Studio, Python, SPSS).
Graduates are equipped for research positions at ICAR institutes, faculty roles at agricultural universities, leadership in agri-tech companies, or Ag-tech entrepreneurship through the innovative IDEA (Internship for Development of Entrepreneurship in Agriculture) track. The M.Sc. in Agronomy is a specialised postgraduate program that delves into advanced studies of crop production and management.
The comprehensive curriculum encompasses soil science, crop physiology, pest management, and sustainable agriculture practices. It provides expertise in optimising crop yields, employing precision farming techniques, and addressing challenges in modern agriculture. With a strong focus on research, the program prepares individuals for careers as agronomists, researchers, and consultants, fostering a deep understanding of sustainable and innovative approaches to enhance global food production and meet the evolving demands of the agricultural industry.
USPs of the Program
AI-Powered Delivery & Digital Excellence
Programme Educational Objectives (PEOs)
Professional Excellence in Digital Agronomy
Graduates will apply advanced agronomic principles integrated with AI, GIS, and Remote Sensing to solve real-world agricultural challenges in research, academia, or industry.
Innovation and Ag-Tech Entrepreneurship
Graduates will develop or manage Agri-business startups and consultancy services leveraging decision-support systems and precision farming tools.
Leadership in Sustainable Intensification
Graduates will design resource-efficient cropping systems balancing food security with environmental conservation using predictive modeling and carbon-smart practices.
Research Ethics and Global Competence
Graduates will conduct ethical, high-impact research supported by advanced statistical modeling (R-Studio/Python) and international IPR standards.
Lifelong Learning and Digital Adaptation
Graduates will remain at the forefront of emerging Ag-Tech trends including robotics, automation, and biotechnology.
Advantage @DGU
350+
Campus Recruiters Every Year
23
States Represented on Campus
20+
Countries for Global Exposure
5
Countries — International Students
Career Opportunities
Research & Academia
Government Sector
Private Sector & Agri-Tech
International Opportunities
Course Structure
| SEMESTER I | SEMESTER II | ||||||
| Code | Course Title | Credits | Category | Code | Course Title | Credits | Category |
| AGR-501 | Modern Concepts in Crop Production | 3 (2+1) | Major | AGR-504 | Principles & Practices of Soil Fertility & Nutrient Management | 3 (2+1) | Major |
| AGR-502 | Principles and Practices of Weed Management | 3 (2+1) | Major | AGR-505 | Agronomy of Major Cereals and Pulses | 3 (2+1) | Major |
| AGR-503 | Agronomy of Oilseed, Fiber, and Sugar Crops | 3 (2+1) | Major | AGR-506 | Agrostology and Agroforestry | 2 (1+1) | Major |
| — | Elective Paper | 3 (2+1) | Minor | — | Elective Paper | 3 (2+1) | Minor |
| STAT-511 | Experimental Design | 3 (2+1) | Supporting | STAT-512 | Data Analysis Using Statistical Packages | 3 (2+1) | Supporting |
| PGS-501 | Basic Concepts in Laboratory Technique | 1 (0+1) | Common | PGS-503 | Agricultural Research, Ethics & Rural Dev. Programmes | 1 (1+0) | Common |
| PGS-502 | Intellectual Property & Its Management in Agriculture | 1 (1+0) | Common | PGS-504 | Library and Information Services | 1 (0+1) | Common |
| TOTAL | 17 | TOTAL | 16 | ||||
| SEMESTER III | SEMESTER IV | ||||||
| Code | Course Title | Credits | Category | Code | Course Title | Credits | Category |
| AGR-507 | Principles and Practices of Water Management | 3 (2+1) | Major | AGR-591 | Master Seminar | 1 (0+1) | Seminar |
| AGR-508 | Dryland Farming and Watershed Management | 3 (2+1) | Major | AGR-599 | Master Research (Thesis) OR IDEA Internship | 30 | Research / Entrepreneurship |
| AGR-509 | Agronomy of Fodder and Forage Crops | 2 (2+0) | Major | ||||
| — | Elective Paper | 2 (1+1) | Minor | ||||
| PGS-505 | Technical Writing and Communications Skills | 1 (0+1) | Common | ||||
| TOTAL | 11 | TOTAL | 31 | ||||
Credit Summary
| Category | Credits |
| Major Courses | 25 |
| Minor Courses (from other departments) | 08 |
| Supporting Courses (Statistics etc.) | 06 |
| Common Courses (PGS series) | 05 |
| Seminar | 01 |
| Course Work Sub-Total | 45 |
| Thesis Research / IDEA Internship | 30 |
| Grand Total | 75 |
Grading System
| Percentage of Marks | Grade Points | Division |
| 100 | 10 | — |
| 90 to <100 | 9 to <10 | — |
| 80 to <90 | 8 to <9 | I Division with Distinction |
| 70 to <80 | 7 to <8 | I Division |
| 60 to <70 | 6 to <7 | II Division |
| 50 to <60 | 5 to <6 | Pass |
| <50 | <5 (Fail) | — |
| Passing Criteria: CGPA ≥ 5.000 | Minimum 50% marks separately in Theory and Practical of every subject. | ||
AI Integration — M.Sc. Agronomy
| AI Tool / Platform | Application |
| Google Earth Engine | NDVI/REIP-based soil fertility mapping, crop monitoring, geo-ecological zoning |
| FAO AquaCrop / CROPWAT | Simulate crop yield and water stress under varied climate scenarios |
| DSSAT (Decision Support System) | Crop simulation for weed management, cereal/pulse production, dryland scenarios |
| QGIS | GIS-based field mapping, variable rate technology, watershed delineation |
| R-Studio / Python | ANOVA, PCA, regression, neural networks, experimental design analysis |
| Power BI / Excel AI (Copilot) | Crop productivity dashboards, cost-benefit analysis, irrigation efficiency visualization |
| Plantix / Agrio | AI-driven nutrient deficiency and disease diagnostics in the field |
| Wolfram Alpha | Mitscherlich equations, nitrogen response functions, Michaelis-Menten kinetics |
| Mendeley / Grammarly | Reference management, citation formatting, scientific writing quality control |
Fee Structure
M.Sc. Agronomy 2026-28
| Fees | I Semester | II Semester | III Semester | IV Semester |
|---|---|---|---|---|
| Admission Fee | 15,000 | - | - | - |
| Tution Fee | 46,000 | 46,000 | 48,000 | 48,000 |
| University Examinations Fees | 5,500 | 5,500 | 5,500 | 5,500 |
| Total | 66,500 | 51,500 | 53,500 | 53,500 |
| Security (Refundable) | - | 10,000 | - | - |
| Other Incidental Compulsory Charges | ||||
| Charges for Uniform (Dress Camp) | 9,500 | - | - | - |
| Book Bank (EET Library) | 4,500 | - | - | - |
| Alumni Registration + 1 Year Enrollment | - | - | - | 5,000 |
| Online ERP Fee | 1,000 | 1,000 | 1,000 | 1,000 |
Fee is subject to change. For updated fee structure kindly visit www.doonbusinessschool.com / www.dgu.ac
Scholarship
Scholarships for Postgraduate Students (2026 Intake)
M.Sc. Agronomy National Entrance Examination-Based Scholarship
| Exam / Score | 10% | 20% | 30% | 40% | 50% Waiver |
| ICAR AIEEA-PG (Rank) | 3001–5000 | 2001–3000 | 1001–2000 | 501–1000 | 1–500 |
| CUET-PG (%tile) | 55–59.9 | 60–69.9 | 70–79.9 | 80–89.9 | 90.00+ |
| Graduation Score-Based Scholarship | |||||
| Graduation % | 10% | 20% | 30% | 40% | 50% Waiver |
| Graduation Score | 60–64.9 | 65–69.9 | 70–74.9 | 75–79.9 | 80.00+ |
Uttarakhand Domicile Scholarship
25% Scholarship on tuition fees
Note
No two scholarships can be clubbed together. Renewal each semester subject to 70% marks and 75% attendance. For detailed scholarship terms, refer to the Program Prospectus
Eligibility Criteria
Level
Graduate
Duration
2 Years (4 Semesters)
75 Credits Total
To pursue this program
Admission Process
Selection is based on a cumulative merit score comprisingPlacements
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