yield prediction

Angelos arrived at Iowa State University on March 19, 2019 for a five-month program. During his visit, Angelos has been working with Dr. Archontoulis to provide technical support on the FACTS project and design a web interface and data flow simulation model that will be used to show yield predictions. Angelos is also working to create a website that would provide project information and updates to site visitors. Dr. Archontoulis said, “I have really enjoy hosting Angelos because of his motivation and drive to learn and participate in the project.” Angelos has contributed a significant amount of technical support to the project, but has also valued all that he has learned from Dr. Archontoulis and his colleagues that have been working on the project. Angelos said, “When first arriving to Iowa State, I had little knowledge about agriculture as my studies are in computer science and engineering, but after spending time with Dr. Sotirios I have gained a wealth of knowledge on the industry as well as enhanced my computer science skills through hands on learning opportunities.”

Low-cost nitrate sensors to populate genotype-informed yield prediction models for next generation breeders

Our civilization depends on continuously increasing levels of agricultural productivity, which itself depends on (among other things) the interplay of crop varieties and the environments in which these varieties are grown. Hence, to increase agricultural productivity and yield stability, it is necessary to develop improved crop varieties that deliver ever more yield, even under the variable weather conditions induced by global climate change, all the while minimizing the use of inputs such as fertilizers that are limiting, expensive or have undesirable ecological impacts.

Subscribe to RSS - yield prediction