Enroll online course in “Plant and Crop Modeling for Smart Farming” by KMUTT

We would like to invite you to join our special Friday lecture series in “Plant and Crop Modeling for Smart Farming”

OPEN REGISTRATION until March 26th, 2021 (10 seats available)
Enroll free online course: https://bml.kmutt.ac.th/register

DATE: April 2nd – May 10th, 2021 (Every Friday)
TIME: 2:00 PM – 5:00 PM
VENUE: Online class in Zoom or Microsoft Teams

Course coordinators:
– Asst.Prof.Dr.Saowalak Kalapanulak (SK)
– Assoc.Prof.Dr.Treenut Saithong (TS)

Online class designed into 2 modules:
– Module A: Plant genotyping & phenotyping technology (Dr. Tobias Wojciechowski)
– Module B: Functional structural model (Dr. Johannes A. Postma)

For further information please contact course coordinators:
saowalak.kal[at]kmutt.ac.th
treenut.sai[at]kmutt.ac.th

Descriptions of Courses

To pursue food security and energy sustainability under climate change crisis, advanced sciences and technology are demanded to build up the intelligent agriculture which help finding the optimal resource management for crop cultivation. The best practice for agricultural management, 80 nowadays, lies not only on the maximal yield of a crop but also on the minimal environmental destruction. Therefore, the modeling capability to understand the intracellular regulation of a crop and ability to predict its response to environment is crucial. Through a project-based learning method, the plant and crop modeling for smart farming course will provide the essential knowledge for simulating the interrelationship between genotype-phenotype of a plant. Modern genomics, traditional physiology, biochemistry and advanced modeling are combined for systematically exploring the relationship between genotype-phenotype under a particular environmental condition. Crop systems biology, as a course principle, is comprised of plant modeling, including basic concept of modeling, unicellular modeling till whole plant modeling; plant physiology; and agricultural sciences, including advances in agricultural technology for monitoring soil, atmosphere, and plants. The content of the course can be exploited in diverse applications relevant to intelligent agriculture, i.e. crop yield forecasting, climatically-determined yield prediction, breeding and introduction of a new crop variety, scoping best farming practices etc.