Skip to content

Semester IV

Agricultural Informatics and Artificial Intelligence

AST 221 · 3 (2+1) credit hours

Syllabus

Topic-wise syllabus

Theory

24 topics · 32 lectures

Theory topics
No.TopicLectures
Unit I
1Introduction to Computers, Anatomy of Computers, Memory Concepts and Units of Memory1
2Operating Systems: Definition and types1
3Application of MS Office for creating, editing and formatting a document, Data presentation, Tabulation and graph creation3
4Statistical Analysis: Mean, Standard Deviation, Correlation, Regression using mathematical and analysis tools in MS Excel2
5Database: Concepts and types, creating of database1
6Uses of DBMS in agriculture1
7Internet and World Wide Web: Concepts and Components1
8Computer Programming, General Concepts1
9Introduction to Visual Basics, Java, Fortran, C/C++ and Standard input output operations2
Unit II
10e-Agriculture, concepts, designs and development1
11Application of Innovative ways to use information and communication technologies in Agriculture1
12Computer models in Agriculture: Statistical, weather analysis and crop simulation methods2
13Concepts, structure, input-output files, limitation, advantages and application of models for understanding plant processes, sensitivity, verification, calibration and validation1
14IT applications for computation of water and nutrient requirement of crops1
15Computer controlled devices (automated systems) for agri-inputs management1
16Mobile Apps in agriculture for farm advice, market price and post-harvest management etc.1
17Geospatial technology: Concepts, techniques, components and uses for generating useful Agri-information1
18Decision support systems: Concepts, components and applications in Agriculture. Agriculture Expert System, Soil Information Systems etc., for supporting farm decisions1
19Preparation of contingent crop planning and crop calendar using IT tools1
20Digital India and schemes to promote digitalization of agriculture in India1
Unit III
21Introduction to artificial intelligence, background and applications in agriculture1
22Control Strategies, breadth first search, Depth first search, Heuristics search techniques, best first search, A* Algorithm, IoT and big data2
23Use of AI in agriculture for autonomous crop management and health, monitoring livestock health, intelligent pesticide application, yield mapping, predictive analysis, automatic weeding and harvesting, sorting of produce and other food processing applications3
24Concepts of smart agriculture, use of AI in food and nutrition science etc.1

Practical

14 topics

Practical topics
No.Topic
1Study of computer components accessories
2Practice of important DOS-commands
3Introduction of different operating systems such as Windows, Unix/Linux; Creating files and folders, file management
4To know about MS Word and its functions
5To know about MS-PowerPoint and its functions
6To know about MS-Excel and its functions
7Use of statistical tools in MS-Excel, creating graphs, analysis of scientific data
8MS-Access, creating database, prepare queries and reports
9Demonstration of Agri-information systems
10Introduction to World Wide Web (WWW) and its components, Introduction of programming languages such as Visual Basic, Java, Fortran, C, C++, Hands on practice on Crop Simulation Models (CSM)
11DSSAT/Crop-Info/CropSyst/Wofost, Preparation of inputs file for CSM and study of model outputs
12Computation of water and nutrient requirements of crop using CSM and IT tools
13Use of smartphones and other devices in agro-advisory and dissemination of market information
14Introduction of Geospatial technology, AR/VR demonstration, Preparation of contingent crop planning, India Digital Ecosystem of Agriculture (IDEA)

Study material

Notes

Hindi

Being added

English

Being added

E-books

Type to search.