isical.ac.in ISI Admission Test JRF Agricultural Chemistry & Soil Science Syllabus : Indian Statistical Institute
Organisation : Indian Statistical Institute
Announcement : Syllabus
Name of Examination : ISI Admission Test
Degree : JRF Junior Research Fellowship
Subject : Agricultural Chemistry and Soil Science
Home Page : http://www.isical.ac.in/
Download Syllabus : http://www.syllabus.gen.in/uploads/1273-JRF-Agriculture.pdf
Agricultural Chemistry & Soil Science Syllabus :
Standard : M.Sc. (Agriculture) in Agricultural Chemistry and Soil Science of Indian University.
1. Agrometeorology :
Related : ISI Admission Test Psychology Syllabus Indian Statistical Institute : www.syllabus.gen.in/1269.html
What is agrometeorology; weather forecasting; water balance model; available moisture index model; factors limiting growth, development and yield of crop as affected by light, temperature, humidity and precipitation.
Growth and development in adverse environmental conditions like drought, flood.
2. Soil Genesis :
Classification of rocks, parent materials for soil formation, weathering, types of weathering, factors affecting weathering, soil formation, factors affecting soil formation, soil profile
3. Soil physical properties :
Soil texture, structure, particle density, bulk density, pore space, soil aeration, soil water holding capacity, soil temperature, soil moisture,
4. Soil chemical properties :
Soil clay minerals, soil colloids, cation exchange capacity, soil acidity, soil alkinity, soil salinity, soil organic matter, soil nutrients,
5. Soil fertility and water management :
Soil fertility problems; role of organic matter, important manures and fertilizers including biofertilizers, their application and behaviour in different soils; soil testing methods and fertilizer recommendation; role of water in plant development and crop production; systems of irrigation and drainage; irrigation requirement of different field crops.
6. Field experimentation :
Objects and trends in agronomic experiments; application, layout and analysis of data of principal experimental designs viz. Randomized block, Latin squares, factorial experiments, split-plot and confounding; computation of linear and curvilinear regressions and their uses.