Jinliang is an Assistant Professor of the Department of Agronomy and Horticulture.
How long have you been a part of plant phenomics? Since I started here in 2017. My job is in quantitative genetics and genomics. Our regular work involves a lot of phenotyping and genotyping. For the phenotyping part, first, we do the traditional work of manually observing. It’s labor-intensive and very tedious work. It’s pretty conventional. People have been doing that since the start of genetics. People walk in the field, observe this and that, collect data. It’s tough work, the growing season has a lot of hot and humid days.
Here at UNL I collaborate with several folks working in this area, especially (AgroHort Associate Professor) James Schnable and (Director of Plant Phenomics) Yufeng Ge. Sometimes with (Biological Systems Engineering Associate Professor) Yeyin Shi. We kind of form a phenomics team. In addition, (lab assistant and AgroHort Ph. D candidate) Eric Rodene is from the computer science program; he got a master’s in computer science. He became very interested in analyzing the imagery data. He published a paper already and there’s another in preparation. This area is progressing very rapidly. Now he’s working on using a machine learning approach to identify the tassel. We’re very interested in the flowering time because it is an important trait for the yield.
What is your background? This position is actually a perfect fit for me because I have been working on quantitative genetics, specifically on maize or corn. I have been working with corn for more than 15 years now, I got my PhD degree from Iowa State and then went to the University of California-Davis to work with maize evolution. I worked to study the domestication history of maize. My skill set is a combination of quantitative genetics and evolutionary genomics. In 2017 the department at UNL was looking for someone specifically focusing on maize quantitative genetics and statistical genomics. The resources at UNL allow me to explore all the different areas of genomics and genetics. Over the years, I have established a lot of great collaborations here.
Why did you choose to study maize? Probably maize chose me, not me choosing maize. I’m originally from China, my bachelor and master’s degrees were both obtained from the China Agricultural University in Beijing. A very famous professor provided me with an opportunity to work in his lab. Maize is among one of the first batch of species that the whole genome has been sequenced. Right after the first human reference genome was released. Back then, the professor needed someone to annotate the transposon elements in the newly assembled maize genome. Through a literature study, I realized the one who discovered transposon was a Nobel Prize Laureate — Barbara McClintock. It is a fascinating and encouraging story. That had me step into the area of maize genomics and motivated me to learn more fundamental knowledge about plant genetics and genomics. I applied for a PhD position at Iowa and got in.
What plant phenomics research or projects are you currently working on? I currently work on several different phenomics related projects. My position is to support plant breeding by developing novel statistical approaches and dissecting the genetic architecture in controlling the complex agronomy traits. From the plant phenomics perspective, my personal interest is the unmanned aerial vehicle (UAV)-based phenotyping, as it can get large-scale in-field data in a time-series manner.
The first project we finished is extracting vegetation indices from the UAV images and relates these indices with agronomy traits, including in-field plant nitrogen levels. We then applied the data collected from a population to conduct genome-wide association analysis — a method to connect the UAV information with the genotypic information to identify genes controlling for the trait of interest, for example, in-field plant nitrogen responses.
This year we’re going to collect new data. Eric is not only extracting information from pixel analysis but also using machine learning algorithm to detect the tassel. Eventually, we’re going to characterize which genotypes flowering early or late, or last longer in pollen shelling and then associate the traits with genes. These genes can be incorporated into the breeding program in the future. In fact, we have already identified a number of promising genes in affecting the plant performance yet need to be further validated. These identified advantageous genes can also be added to the breeding pipeline through gene-editing approaches.
What is one thing you wish people knew about plant phenomics? From my perspective it’s a plant breeding enabling tool. Given years of further development, I believe plant phenomics will have real impacts for plant breeding. This can be a next generation plant breeding innovation technology in combination with other technical advancements, such as artificial intelligence. Phenomics only becomes more important if you can bring real-world impacts through plant breeding.
What do you like to do in your free time? I like reading and playing with my two kids. Right now my second one is one year old, and I read for my daughter who’s eight years old. During the pandemic everything stopped, all we did was play inside. Before the pandemic I liked to travel around the country and around the world.
Where do you want to travel to next? I want to travel to Europe to learn different things and explore different parts of the world. For example, go to Germany, France, Belgium. I have some friends in Germany who invited me to visit, and I hope I can visit them very soon.
