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Fees
₹8,00,000
Placement
92.0%
Avg Package
₹7,50,000
Highest Package
₹15,00,000
Fees
₹8,00,000
Placement
92.0%
Avg Package
₹7,50,000
Highest Package
₹15,00,000
Seats
100
Students
250
Seats
100
Students
250
The curriculum of the B.Tech in Agriculture program at Sigma University Vadodara is designed to provide students with a comprehensive understanding of modern agricultural practices, integrating traditional knowledge with cutting-edge science and technology. The program spans four years, divided into eight semesters, with a carefully structured sequence of core courses, departmental electives, science electives, and laboratory sessions.
The curriculum is structured to build foundational knowledge in the first two years, followed by specialized courses in the third and fourth years. Students are encouraged to engage in project-based learning and research, which are integral components of the program.
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|---|
| 1 | 1 | AGRI101 | Introduction to Agriculture | 3-0-0-3 | - |
| 1 | 1 | AGRI102 | Plant Physiology | 3-0-0-3 | - |
| 1 | 1 | AGRI103 | Soil Science | 3-0-0-3 | - |
| 1 | 1 | AGRI104 | Environmental Science | 3-0-0-3 | - |
| 1 | 1 | AGRI105 | Basic Mathematics | 3-0-0-3 | - |
| 1 | 1 | AGRI106 | Basic Physics | 3-0-0-3 | - |
| 1 | 2 | AGRI107 | Crop Science | 3-0-0-3 | AGRI101, AGRI102, AGRI103 |
| 1 | 2 | AGRI108 | Plant Pathology | 3-0-0-3 | AGRI101, AGRI102 |
| 1 | 2 | AGRI109 | Agricultural Entomology | 3-0-0-3 | AGRI101, AGRI102 |
| 1 | 2 | AGRI110 | Farm Machinery | 3-0-0-3 | AGRI101 |
| 1 | 2 | AGRI111 | Basic Chemistry | 3-0-0-3 | - |
| 1 | 2 | AGRI112 | Statistics for Agriculture | 3-0-0-3 | - |
| 2 | 3 | AGRI201 | Agricultural Biotechnology | 3-0-0-3 | AGRI107, AGRI108 |
| 2 | 3 | AGRI202 | Farm Management | 3-0-0-3 | AGRI107, AGRI109 |
| 2 | 3 | AGRI203 | Climate Change and Agriculture | 3-0-0-3 | AGRI101, AGRI104 |
| 2 | 3 | AGRI204 | Sustainable Farming Systems | 3-0-0-3 | AGRI107, AGRI108 |
| 2 | 3 | AGRI205 | Research Methodology | 3-0-0-3 | AGRI112 |
| 2 | 3 | AGRI206 | Project Planning | 3-0-0-3 | AGRI205 |
| 2 | 4 | AGRI207 | Agri-Economics | 3-0-0-3 | AGRI107, AGRI112 |
| 2 | 4 | AGRI208 | Agro-Environmental Science | 3-0-0-3 | AGRI104, AGRI107 |
| 2 | 4 | AGRI209 | Soil and Water Conservation | 3-0-0-3 | AGRI103, AGRI104 |
| 2 | 4 | AGRI210 | Plant Breeding and Genetics | 3-0-0-3 | AGRI102, AGRI108 |
| 2 | 4 | AGRI211 | Food Processing | 3-0-0-3 | AGRI101, AGRI107 |
| 2 | 4 | AGRI212 | Agricultural Policy and Planning | 3-0-0-3 | AGRI207, AGRI208 |
| 3 | 5 | AGRI301 | Precision Farming | 3-0-0-3 | AGRI201, AGRI202 |
| 3 | 5 | AGRI302 | Agricultural Robotics | 3-0-0-3 | AGRI201, AGRI202 |
| 3 | 5 | AGRI303 | GIS and Remote Sensing | 3-0-0-3 | AGRI203, AGRI204 |
| 3 | 5 | AGRI304 | Smart Irrigation Systems | 3-0-0-3 | AGRI209, AGRI210 |
| 3 | 5 | AGRI305 | Agri-Data Science | 3-0-0-3 | AGRI205, AGRI206 |
| 3 | 5 | AGRI306 | Machine Learning in Agriculture | 3-0-0-3 | AGRI305 |
| 3 | 6 | AGRI307 | Agri-Entrepreneurship | 3-0-0-3 | AGRI207, AGRI212 |
| 3 | 6 | AGRI308 | Agri-Startups | 3-0-0-3 | AGRI307 |
| 3 | 6 | AGRI309 | Agri-Consulting | 3-0-0-3 | AGRI307 |
| 3 | 6 | AGRI310 | Agri-Finance | 3-0-0-3 | AGRI207 |
| 3 | 6 | AGRI311 | Agri-Marketing | 3-0-0-3 | AGRI207 |
| 3 | 6 | AGRI312 | Agri-Research | 3-0-0-3 | AGRI205 |
| 4 | 7 | AGRI401 | Final Year Project | 3-0-0-3 | AGRI305, AGRI306 |
| 4 | 7 | AGRI402 | Advanced Agri-Tech | 3-0-0-3 | AGRI301, AGRI302 |
| 4 | 7 | AGRI403 | Climate Resilient Agriculture | 3-0-0-3 | AGRI203, AGRI204 |
| 4 | 7 | AGRI404 | Agri-Business Strategy | 3-0-0-3 | AGRI307, AGRI308 |
| 4 | 7 | AGRI405 | Agri-Policy Analysis | 3-0-0-3 | AGRI212 |
| 4 | 7 | AGRI406 | Agri-Research Thesis | 3-0-0-3 | AGRI312 |
| 4 | 8 | AGRI407 | Agri-Internship | 3-0-0-3 | AGRI401, AGRI406 |
| 4 | 8 | AGRI408 | Agri-Consulting Project | 3-0-0-3 | AGRI309, AGRI310 |
| 4 | 8 | AGRI409 | Agri-Startups | 3-0-0-3 | AGRI308 |
| 4 | 8 | AGRI410 | Agri-Data Analytics | 3-0-0-3 | AGRI305, AGRI306 |
| 4 | 8 | AGRI411 | Agri-Finance | 3-0-0-3 | AGRI310 |
| 4 | 8 | AGRI412 | Agri-Research | 3-0-0-3 | AGRI312 |
Advanced departmental electives in the Agriculture program at Sigma University Vadodara are designed to provide students with specialized knowledge and skills in emerging areas of agriculture. These courses are taught by faculty members with expertise in their respective fields and are aligned with industry trends and research needs.
This course focuses on the application of technology in agriculture, including GPS mapping, drone-based monitoring, and sensor networks. Students learn to use precision farming tools to optimize crop yields and reduce resource waste. The course includes hands-on lab sessions and field projects.
Agricultural robotics is an emerging field that combines mechanical engineering, artificial intelligence, and agricultural science. This course introduces students to the design and application of robots in farming, including automated planting, harvesting, and pest control systems.
Geographic Information Systems (GIS) and remote sensing are powerful tools for analyzing agricultural data. This course covers the principles of GIS and remote sensing, including satellite imagery analysis, spatial data processing, and mapping techniques for agricultural applications.
This course explores the design and implementation of smart irrigation systems that optimize water usage and improve crop productivity. Students learn about drip irrigation, sprinkler systems, and automated control mechanisms.
Data science is increasingly important in agriculture. This course teaches students how to collect, analyze, and interpret agricultural data using statistical and machine learning techniques. Students work on real-world datasets to solve agricultural problems.
This course introduces students to machine learning algorithms and their applications in agriculture, including crop disease detection, yield prediction, and resource optimization. Students learn to use tools like Python and TensorFlow for agricultural data analysis.
Entrepreneurship in agriculture is crucial for driving innovation and economic growth. This course covers business planning, market analysis, and funding strategies for agri-startups. Students develop business plans for agricultural ventures.
This course provides students with insights into the startup ecosystem in agriculture. Students learn about venture capital, incubation, and scaling strategies for agri-businesses. The course includes guest lectures from successful agri-entrepreneurs.
Agri-consulting involves providing expert advice to farmers and agri-businesses. This course teaches students how to conduct agronomic assessments, develop management plans, and deliver consulting services.
Financial management is essential for agricultural businesses. This course covers financial planning, risk assessment, and investment strategies for agri-businesses. Students learn about agricultural loans, subsidies, and funding opportunities.
Marketing plays a key role in the success of agricultural products. This course covers marketing strategies, branding, and distribution channels for agricultural products. Students learn to develop marketing plans for agri-products.
Research is the foundation of innovation in agriculture. This course teaches students how to design research projects, collect data, and analyze results. Students work on research projects under faculty supervision.
The department's philosophy on project-based learning is rooted in the belief that students learn best when they engage in real-world problem-solving. Projects are designed to be interdisciplinary, allowing students to apply knowledge from multiple courses and fields.
The mandatory mini-projects in the second and third years provide students with hands-on experience in applying theoretical concepts to practical agricultural challenges. These projects are typically completed in teams and are evaluated based on research quality, presentation, and impact.
The final-year thesis/capstone project is a significant component of the program. Students select a topic related to their specialization and work under the guidance of a faculty mentor. The project involves extensive research, data analysis, and a written thesis. Students also present their findings in a public forum.
Project selection is based on student interests, faculty availability, and research needs. Students are encouraged to propose their own projects, but they must be approved by faculty mentors. The department also provides a list of suggested projects that align with current research trends and industry needs.
The evaluation criteria for projects include research quality, methodology, presentation, and impact. Students are evaluated by a panel of faculty members and industry experts. The final project grade is based on the quality of the research, the clarity of the presentation, and the potential for real-world application.
