Plant Health in the Wake of AI
Objectives
The environmental awareness is increasing, to some extent because of the increasing number of reports on global climate change. This has and will continue to have a large impact on management of future cropping systems, especially concerning plant protection. The overall objective of this course is to give early-stage PhD students and MSc students from different subject areas (e.g. ecology, entomology, nematology, plant breeding, molecular biology etc.) a deeper understanding of challenges and constraints in relation to modern plant protection in different systems. A special focus will be given to applications of Artificial Intelligence (AI) through the machine and deep learning that are emerging in plant health strategies. The course is intended to give the students a broad scientific basis for current and future work in relation to development of environmentally sustainable plant protection methods, in addition to their own specialization. Furthermore, influences and inputs from related fields in general and AI applications in particular may create new ideas and inspire new approaches in ongoing projects. Whether the students stay in science or move on to other careers (e.g., at private companies or national boards for agriculture or similar institutions) after finishing, a broad knowledge of plant protection will be valuable.
Content
The aim of the course is to bring together PhD students from different backgrounds (biology, agronomy, horticulture, agroecology etc.) working on plant heakth related areas and set them in relation to aspects of policy governing their field of study. To account for the expected diversity of student backgrounds and to make sure that they are on a comparable scientific level in the management strategy discussions, some lectures in the beginning will be devoted to introducing the fundamental aspects of plant health. The lecturers will be asked to give a brief basic introduction to the subject area and then to move on and end with the latest results (which will also be discussed during the literature seminars).
The following topics will be dealt with during the course: Plant defense, resistance biology and breeding. Pests and pathogens. Ecology/population dynamics, life cycle etc. - some typical examples from each group. Crop loss assessment and presentation of different management methods, e.g. biological and chemical control, resistance breeding, molecular tools, disease prediction, etc. Development of management strategies based on the different methods that are at hand - examples from different cropping systems - agriculture, horticulture and forestry. How the threats from pathogens and pests can be expected to be affected by climate change. How different protection strategies is affected by and can be adapted to climate change. How techniques emerging based on Artificial Intelligence (AI) research can be used for crop health and disease monitoring, weeding and pesticide application can be integrated into pest protection strategies to increase sustainability.
And generally, how AI is influencing and will be iinfluencing the research area of plant health. Applications of (AI) through machine and deep learning emerging in plant health strategies will be presented and students will have to consider how AI will have a positive or negative impact on their case studies.
Syllabus and other information
Syllabus
P000076 Plant Health in the Wake of AI, 5.0 Credits
Subjects
BiologyEducation cycle
Postgraduate levelGrading scale
Language
EnglishPrior knowledge
PhD students as well as MSc students interested in e.g. (agro)ecology, entomology, plant breeding, plant molecular biology, nematology, mycology, plant protection, plant pathology, IPP/IPM, pest/pathogen and plant interactions, climate change, biotic and abiotic stress.Objectives
After completing the course, the student is expected to be able to:
• Enumerate at least three biological aspects of plant defense
• Compare and contrast the natural system with the cultivated system with regards to plant defense
• Describe the ecology and biology of common pests and/or pathogens
• Relate molecular mechanisms of host and pest/pathogen interactions to pest/pathogen management methods and strategies
• Apply knowledge of pest/pathogen management methods and strategies to evaluate research result from case studies and the scientific literature
• Formulate plant protection strategies for different plant-pathogen/pest interaction systems based on the latest results and trends within plant protection as part of the project-based learning case scenarios, and use them to evaluate their own research in a broader perspective
• Give an overview of use of robotics in plant protection
• Identify sectors within plant health where Artificial Intelligence through machine and deep learning can be applied.
Content
Objectives
The environmental awareness is increasing, to some extent because of the increasing number of reports on global climate change. This has and will continue to have a large impact on management of future cropping systems, especially concerning plant protection. The overall objective of this course is to give early-stage PhD students and MSc students from different subject areas (e.g. ecology, entomology, nematology, plant breeding, molecular biology etc.) a deeper understanding of challenges and constraints in relation to modern plant protection in different systems. A special focus will be given to applications of Artificial Intelligence (AI) through the machine and deep learning that are emerging in plant health strategies. The course is intended to give the students a broad scientific basis for current and future work in relation to development of environmentally sustainable plant protection methods, in addition to their own specialization. Furthermore, influences and inputs from related fields in general and AI applications in particular may create new ideas and inspire new approaches in ongoing projects. Whether the students stay in science or move on to other careers (e.g., at private companies or national boards for agriculture or similar institutions) after finishing, a broad knowledge of plant protection will be valuable.
Content
The aim of the course is to bring together PhD students from different backgrounds (biology, agronomy, horticulture, agroecology etc.) working on plant heakth related areas and set them in relation to aspects of policy governing their field of study. To account for the expected diversity of student backgrounds and to make sure that they are on a comparable scientific level in the management strategy discussions, some lectures in the beginning will be devoted to introducing the fundamental aspects of plant health. The lecturers will be asked to give a brief basic introduction to the subject area and then to move on and end with the latest results (which will also be discussed during the literature seminars).
The following topics will be dealt with during the course: Plant defense, resistance biology and breeding. Pests and pathogens. Ecology/population dynamics, life cycle etc. - some typical examples from each group. Crop loss assessment and presentation of different management methods, e.g. biological and chemical control, resistance breeding, molecular tools, disease prediction, etc. Development of management strategies based on the different methods that are at hand - examples from different cropping systems - agriculture, horticulture and forestry. How the threats from pathogens and pests can be expected to be affected by climate change. How different protection strategies is affected by and can be adapted to climate change. How techniques emerging based on Artificial Intelligence (AI) research can be used for crop health and disease monitoring, weeding and pesticide application can be integrated into pest protection strategies to increase sustainability.
And generally, how AI is influencing and will be iinfluencing the research area of plant health. Applications of (AI) through machine and deep learning emerging in plant health strategies will be presented and students will have to consider how AI will have a positive or negative impact on their case studies.
Additional information
Pedagogical formIt is important that the students take active part in their own learning. AI through machine or deep learning is an emerging field where many of the students possess larger skills than teachers in plant health. We hope that will be reflected in the course through student-teacher dialogues and student discussion. Part of the active learning is that the students will do a ”case study” that will be presented both orally - where all students should participate actively in the discussions - and as a written report. The work should be done in groups to profit from the different expertise of the students in the discussions and development of management strategies. In addition, they will get a chance to practice oral presentation when they present their own research. The literature seminars will give them an opportunity to read recent and relevant literature (papers selected by the lecturers and handed out before the course) and to discuss - in smaller groups - with each other and experienced scientists (the lecturers) within the subject area.
Contact for application and further information:
Svante Resjö, svante.resjo@slu.se, registration of course will be done via PlantLink’s homepage
Responsible department
Department of Plant Protection Biology