FEBRUARY 2021 |
Our research spotlight for February is Jian Jin, assistant professor of agricultural and biological engineering.
What is your educational background?
I received my Ph.D. in agricultural engineering from Iowa State University in 2009. I earned my M.S. degree in computer engineering from Denmark Technical University in 2005 and my B.S. degree in computer science from Zhejiang University in 2003.
What kind of research do you do?
I’m a plant sensor developer. My major research interest at Purdue is to build the next generation plant sensors and automatic plant phenotyping systems, along with machine vision, machine learning and robotics.
How long have you been doing this research?
Around 11 years in both industry and academia. Before joining Purdue, I was a research scientist at DuPont Pioneer (now Corteva) from 2010-2015, where I was responsible for the company’s greenhouse phenotyping projects. I was the major designer of the high-throughput imaging systems in DuPont Pioneer’s modern phenotyping greenhouse deployed in 2013, which is currently still one of the nation’s largest indoor phenotyping facilities.
What is the big-picture view of your work – for instance, how could your findings help improve the quality of life around the world?
Producing enough food and energy for a world population likely exceeding 9.7 billion in 2050 is the biggest challenge facing agriculture. To meet this demand, the yield of all major food and energy crops will have to double. Genomic tools are already commonly used in crop breeding programs. A major bottleneck is the lack of high-quality and easy-to-use phenotyping methods, which makes breeding and plant science research efforts slower and more expensive.
Many plant sensing technologies have been developed in the last decades. Although the current systems have shown effectiveness in phenotyping, the measurement results suffer from various sources of noise such as the changing environment, status of the plant and significant variance across the canopy. Besides, most current systems are too big and expensive to be widely applied.
My goal of research at Purdue is to address the bottleneck issues and introduce new plant sensor technologies with improved sensitivity to plant’s nutrient level, diseases stresses, chemical responses, and so on. One example of my recent innovations is the award winning LeafSpec, the world’s first handheld hyperspectral leaf imager. It integrated hardware and software technologies from the modern phenotyping facilities into a small mobile device, so much more people can benefit from the advanced hyperspectral imaging technology in various scenarios. LeafSpec also resolved many bottleneck sensing quality issues with most current plant imaging sensors, thus it can provide unprecedented imaging signal from the leaves.
More information about LeafSpec can be found at:
What do you find most rewarding about the work you do?
While we keep making progresses in publications and patent applications, the most rewarding moments were when our sensor innovations showed their values in practical plant science activities. We were very proud in the past when our nutrient sensors were adopted in major ag company’s breeding activities, when we helped botanist and state agents to detect herbicide drift earlier, and when our technology was adopted by industry to detect wheat diseases.
In the future, I hope the next high-yield, disease resistant and nutrient-usage-efficient crop seeds can be introduced earlier with our sensor’s contribution in it.
Did you intend, when you were working on your degree(s), to do this kind of work? If not, how did you arrive at this place in your career?
I never imagined working on agricultural crop sensing when I studied for my earlier degrees in computer science or computer engineering. The graduate school and job opportunities somehow transferred me to my current area. However, when I look back, I really think this was such a wise transition which enabled me to apply my skills in computer science and engineering into the huge agricultural market where I’ll spend my whole career life to make my greatest contribution to the people.
How has the Purdue Life Sciences Initiative positively impacted your research?
In order to introduce the best plant sensor technologies, multidisciplinary collaboration is the key. It really takes the plant scientists, engineers, data scientists and many other people to work together to resolve the current plant sensing issues. Since my 1st year at Purdue, I have been collaborating with researchers under Life Sciences Initiative and Plant Science Initiative for every single innovation project.
What are some fun facts we should know about you?
I’m an amateur singer and I have been playing Badminton regularly before the pandemic. I still claim to be Purdue faculty #1 in badminton men’s singles and I accept challenges from any faculty friends.