Doctor of Philosophy (Agronomy) — Ph.D. (Agronomy)
The programme produces graduates who are academic leaders and innovation researchers in agronomy, able to integrate knowledge across disciplines to manage, solve problems, and guide society with integrity and professional ethics, towards international excellence.
The Doctor of Philosophy Program in Agronomy has been offered since academic year 2525 (1982) and was most recently revised in B.E. 2569 (2026) to raise research competence, the creation of new knowledge, and the application of advanced technology to real production problems.
Three plans are offered: Plan 1.1 — thesis only, not fewer than 48 credits; Plan 2.1 — coursework and thesis, not fewer than 48 credits in total; and Plan 2.2 for holders of a bachelor's degree, not fewer than 72 credits in total.
The 2026 revision opens four new courses — Agricultural Climate Data Analysis, Advanced Artificial Intelligence for Crop Science Research and Communication, Metabolomics in Field Crops, and Industrial Grain Science and Technology — alongside co-curricular activities that build soft skills. Effective from the first semester of academic year 2569 (2026).
| Plan 1.1 (after a master's degree) | ไม่น้อยกว่า 48 |
| Major (non-credit) | ไม่น้อยกว่า 7 |
| — Seminar | 4 |
| — Required major | 3 |
| Thesis | ไม่น้อยกว่า 48 |
| Plan 2.1 (after a master's degree) | ไม่น้อยกว่า 48 |
| Major | ไม่น้อยกว่า 12 |
| — Seminar | 4 |
| — Required major | 3 |
| — Elective major | ไม่น้อยกว่า 5 |
| Thesis | ไม่น้อยกว่า 36 |
| Plan 2.2 (after a bachelor's degree) | ไม่น้อยกว่า 72 |
| Major | ไม่น้อยกว่า 24 |
| — Seminar | 6 |
| — Required major | 6 |
| — Elective major | ไม่น้อยกว่า 12 |
| Thesis | ไม่น้อยกว่า 48 |
For holders of a master's degree — thesis only, not fewer than 48 credits; required major courses and seminars are taken without credit.
| Code | Course | credits | |
|---|---|---|---|
| Year 1 First semester | 8 credits | ||
| 01003691 | Advanced Research Methods in Agronomy | Non-credit | 3(3-0-6) |
| 01003699 | Thesis | 8 | |
| Year 1 Second semester | 8 credits | ||
| 01003697 | Seminar | Non-credit | 1 |
| 01003699 | Thesis | 8 | |
| Year 2 First semester | 8 credits | ||
| 01003697 | Seminar | Non-credit | 1 |
| 01003699 | Thesis | 8 | |
| Year 2 Second semester | 8 credits | ||
| 01003697 | Seminar | Non-credit | 1 |
| 01003699 | Thesis | 8 | |
| Year 3 First semester | 8 credits | ||
| 01003697 | Seminar | Non-credit | 1 |
| 01003699 | Thesis | 8 | |
| Year 3 Second semester | 8 credits | ||
| 01003699 | Thesis | 8 | |
For holders of a master's degree — at least 12 credits of coursework plus a thesis of at least 36 credits.
| Code | Course | credits | |
|---|---|---|---|
| Year 1 First semester | 9 credits | ||
| 01003691 | Advanced Research Methods in Agronomy | 3(3-0-6) | |
| X9999991 | วิชาเอกเลือก | 5 | |
| 01003699 | Thesis | 1 | |
| Year 1 Second semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 2 First semester | 8 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 7 | |
| Year 2 Second semester | 8 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 7 | |
| Year 3 First semester | 8 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 7 | |
| Year 3 Second semester | 8 credits | ||
| 01003699 | Thesis | 8 | |
For holders of a bachelor's degree — at least 24 credits of coursework plus a thesis of at least 48 credits.
| Code | Course | credits | |
|---|---|---|---|
| Year 1 First semester | 9 credits | ||
| 01003691 | Advanced Research Methods in Agronomy | 3(3-0-6) | |
| X9999991 | วิชาเอกเลือก | 6 | |
| Year 1 Second semester | 9 credits | ||
| 01003542 | Statistics and Coding for Agricultural Research | 3(3-0-6) | |
| X9999991 | วิชาเอกเลือก | 6 | |
| Year 2 First semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 2 Second semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 3 First semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 3 Second semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 4 First semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 4 Second semester | 7 credits | ||
| 01003697 | Seminar | 1 | |
| 01003699 | Thesis | 6 | |
| Year 5 First semester | 6 credits | ||
| 01003699 | Thesis | 6 | |
| Year 5 Second semester | 6 credits | ||
| 01003699 | Thesis | 6 | |
Role of statistics in agricultural research. Concepts and theories of experimental design. Analysis and interpretation. Regression and correlation analysis. Coding for statistical analysis and data visualization. R language and packages.
More detailsTypes of meteorological elements and sources for data access. Paleoclimate data. Reanalysis data. Satellite and weather radar data. Climate Model Intercomparison Project (CMIP). Preparation of climate datasets. Analysis of climate time series data. Use of platform and software for processing and visualizing climate datasets. Interpretation from climate data analysis. Application of climate data analysis results in agricultural research and production.
More detailsIntegration of interdisciplinary knowledge. Systems analysis. Big data analytics. Entrepreneurship. Artificial intelligence for strategic planning from drivers of climate change, emerging technologies, and economic factors. Regional and international study cases to design and implement research programs. Human resource management for sustainable plant breeding and global food security.
More detailsExperimental design and analysis. Application of linear mixed models. Generation mean analysis. Analysis of experiments in North Carolina, diallel crosses, and line x tester mating designs. Cultivar stability analysis. Regression and path coefficient analysis. Multivariate analysis. Principal component analysis. Cluster analysis. Quantitative trait analysis and gene mapping.
More detailsAcademic report preparation. Use of modern AI tools. Ethics and responsibility. Research analysis and synthesis. Experimental design. Statistical analysis. Research article writing. Image and graphic creation. Original manuscript quality check. Crop and production system management. Agricultural image analysis. Case studies and project presentations on AI applications in research.
More detailsLimitation of crop yield, physiological processes related to crop yield. Applications of physiological knowledge for yield improvement under normal and adverse conditions.
More detailsPhysiological, biochemical, and molecular basis of plants to major herbicides, bio-herbicides, herbicide resistance mechanisms in weed and crop plants, environmental and food safety risks, problem analysis, issues applicable to crop production.
More detailsPrinciples and applications of metabolomics technology in field crop studies. Sample collection and preparation methods. Advanced metabolite analysis techniques using sophisticated instruments. Data processing and applications of metabolomics in plant breeding, production management, nutritional value improvement, stress response studies, and agricultural product quality control. Integration with other omics technologies. Development of metabolomics research projects in field crops.
More detailsGenetic markers and plant genetic analysis using molecular and bioinformatics approaches. Marker-assisted selection. Genome-wide association study. Genomic selection. Multi-omics analysis in plant breeding for quantitative and qualitative traits.
More detailsPhysiological and biochemical aspect of seed development, maturation, germination, dormancy, deterioration and storability. Artificial seed and varietal identification.
More detailsGrain formation and development. Advanced grain chemistry. Functional and nutritional properties of grains. Industrial grain production technology, harvest, post-harvest management and storage. Grain processing technologies. Grain quality analysis. Microbiology and grain safety. Agricultural commodity and food standards.
More detailsAdvanced research in agronomy. Research ethics. Research proposal development. Writing the research framework. Project analysis. Budget planning. Pathways to research impact. Research project management. Use of information technology and computer systems for data processing and information retrieval. Result analysis. Academic writing and manuscript preparation. Research presentation. Research discussion. Preparation of reports for conference presentation and publication in academic journals.
More detailsSelected topics in agronomy at the doctoral degree level. Topics are subject to change for each semester.
More detailsPresentation and discussion on current interesting topics in agronomy at the doctoral degree level.
More detailsResearch at the doctoral degree level and compile into a thesis.
More detailsวิชาเอกเลือก
More details
Assoc. Prof. Dr. Chalermpol Phumichai
Lecturer
Assoc. Prof. Dr. Damrongvudhi ONWIMOL
Lecturer
Asst. Prof. Dr. Songyos CHOTCHUTIMA
Lecturer
Assoc. Prof. Dr. Tanapon Chaisan
Lecturer
Assoc. Prof. Dr. Tanee Sreewongchai
Lecturer
Asst. Prof. Dr. Parichart Promchote
Lecturer
Assoc. Prof. Dr. Pitipong Thobunluepop
Lecturer
Asst. Prof. Dr. Piya Kittipadakul
Lecturer
Assoc. Prof. Dr. Pasajee KONGSILA
Lecturer
Asst. Prof. Dr. Wannasiri Wannarat
Lecturer
Asst. Prof. Dr. Weerachai MATTHAYATTHAWORN
Lecturer
Asst. Prof. Dr. Sarawut Rungmekarat
Lecturer
Asst. Prof. Dr. Sujin Jenweerawat
Lecturer
Assoc. Prof. Dr. Sutkhet Nakasathien
Lecturer
Asst. Prof. Dr. Arunee WONGKAEW
Lecturer
Admission follows the graduate study regulations of the Graduate School, Kasetsart University. Plans 1.1 and 2.1 admit holders of a master's degree; Plan 2.2 admits holders of a bachelor's degree. The programme admits both Thai and international students and is taught in Thai and English.
Contact the department for more information about admissions and applicant qualifications.
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