NC State University’s Jing Zhang describes her entry into the field of plant phenomics as accidental, but the twists she encountered early on launched a career pioneering the future of agricultural science.

Zhang joined the university’s horticultural science faculty and its N.C. Plant Sciences Initiative three years ago, establishing the Translational Plant Phenomics Lab in the Plant Sciences Building on Centennial Campus.

Plant phenomics involves using high-tech automated tools to measure and analyze a plant’s observable traits — things like height, color, root structure, and response to stress.

Such information, Zhang says, holds the key to accelerating crop breeding and developing better crop management practices. With more data — coupled with faster, better tools to analyze it  —scientists can gain greater insights into the complex interplay that occurs when plants with different genetics respond in different ways to similar environmental conditions.

“We are bridging the barriers between engineering and crop production and plant breeding.”

Zhang was one of the first, if not the first, to employ plant phenomics in turfgrass science. That was back in the mid-2010s, when plant phenomics was emerging as a distinct field of study and she was a graduate student and postdoctoral researcher.

Today, Zhang uses a wide range of tools  — cameras and other sensors, drones, robots and satellites — to help researchers and farmers get the data they need to address key challenges related to producing fruits, vegetables and other specialty crops.

She sees herself as an applied scientist, bringing together experts that develop remote sensing, robotics and artificial intelligence technologies with those focused on plant breeding, plant protection and crop production.

“We are bridging the barriers between engineering and crop production and plant breeding,” she says. “I can speak both languages.” 

While Zhang has made a name for herself in the field of plant phenomics, her journey has been anything but direct.

The First ‘Accident’: An Aspiring Med Student Sent to Ag School

Zhang grew up in a Chinese suburb, and when it came time for college in the early 2000s, she’d been thinking about studying medicine, English or finance.

She had never considered agriculture, but the country’s complicated system of matching upper-grade students with universities and fields of studies landed her at the South China Agricultural University in Guangzhou, in a new undergraduate program focused on turfgrass agronomy.

Fortunately for agriculture, Zhang thrived in her classes and came to admire her adviser.

The Next ‘Accident’: She Gets Stuck Doing Tedious Field Work, for Days

After earning a master’s degree in China in 2010, she decided to leave her home country for the United States, drawn by the country’s strong turfgrass research programs and well-developed industry. She entered the University of Florida as a Ph.D. student in 2010, then moved on to the University of Georgia for postdoctoral work from there.

“Breeders sometimes know when one plant is going good in the field, but they may not know why — they may not know the mechanism that underlies that performance,” Zhang explains.

It was her job to help figure that out by taking measurements related to photosynthesis and transpiration in plants when the soil was drying, trying to figure out what made some of the plant populations she was studying last longer than others.

“Human scouting is subjective and slow, and you can’t do acres in a short time. I used to have to spend two days taking pictures.”

“I was trying to screen a bunch of differences in many different genotypes, putting them in the field and looking at the canopy and the roots,” she recalls.

Sometimes, she found herself pushing a cart over research plots that spanned several acres, taking photographs and measurements along the way.

“Human scouting is subjective and slow, and you can’t do acres in a short time,” she explains. “I used to have to spend two days taking pictures.”

Zhang knew there had to be better ways to getting accurate data from field studies.

“It was back in 2013, when people started buying drones to take pictures, but we didn’t know how to get data from those pictures,” she says. “We were just using drones to take pretty pictures for presentations.

“But drones can take pictures much faster – five minutes – and they don’t get tired,” she notes.

Zhang had to start from scratch, but she figured out how to get useful images from the drones and then how to get the data the scientists needed from the photos.

Her success opened the door to opportunities to apply new tools and technologies to other crops, like sorghum and peanuts, and other challenges, including disease detection.

“I’m proud of what I was able to accomplish,” Zhang says. “There were limited resources back then, and now the field has exploded.”

Applying Hard-Won Knowledge to Big N.C. Farm Challenges

NC State took notice of the promise of plant phenomics, and its Department of Horticultural Sciences created a faculty position for translational plant phenomics. Zhang was hired to fill that slot in 2024.

As an assistant professor, Zhang has continued her work to advance turfgrass breeding, she’s also ventured into problem-solving on other key N.C. commodities.

Her work spans fruit, vegetable and other specialty crops, from cut flowers to sweetpotatoes.

One of her latest projects involves exploring ways to use cellphones to better measure blueberry ripeness – a key consideration for timing harvest.

“The agents really play a pivotal role in this, connecting us to the grower’s needs and identifying ways we could help them.”

Zhang began the work with NC State plant breeders who needed a practical, field-ready method to estimate blueberry maturity, and she worked with agents in the N.C. PSI Extension Agent Network to beta test and refine the tool so that growers could use it to decide when to harvest.

“This project started as a collaboration with plant breeders, but it turns out the growers can also benefit from it. That’s the exciting part,” Zhang said. “The agents really play a pivotal role in this, connecting us to the grower’s needs and identifying ways we could help them.”

More recently, Zhang has developing an artificial intelligence model to detect Neopestalotiopsis, or Neo-P, an emerging fungal disease that poses a significant threat to strawberry production. Using drone images, the computer vision-based model is designed to support the development of field stress maps that help growers identify disease hotspots and target management efforts more efficiently.

What’s Ahead for Zhang and the Field of Plant Phenomics

While she’s taking on new challenges, Zhang is also pondering ways she can continue to shape her field.

“We came a long way. The phenotyping world has exploded, and nowadays there are so many tools available that make the work easier. The development of AI also has made it much faster,” Zhang says.

“We can take data every day, every week, every month repeatedly. But what would we do with all that data? How do you sort it and make sense of it?”

“But there are challenges. Plant phenomics started with developing tools and workflows and increasing breeding efficiency, but now it’s starting to get fuzzy,” she adds. “One huge challenge is that we have so much data.”

To explain why too much data is problematic, Zhang harkens back to her early work with drones.

“Before it took two days just to take one data point for my trial – now, five minutes and it’s done,” she says. “That means we can take data every day, every week, every month repeatedly. But what would we do with all that data? How do you sort it and make sense of it?”

And then, how do you pay for all the things that go along with gathering, storing and analyzing data — things like labor, software, hardware and infrastructure costs?

“One of the big, big areas we are trying to address is, ‘How do we drive scientific discovery most efficiently,’” she says. “That could be pinpointing time points when data collection is most critical, or it could be by focusing on those traits that are most associated with a breeder’s interests — their objectives — and coming up with better ways to measure them. That falls under my umbrella.”

“There’s a traditional mindset in China: Your education is a priority. Finish it, no matter what, and then be prepared to embrace opportunities when they come — and then keep learning.”

While suggesting that there are more questions than answers right now about the challenges surrounding big data, Zhang remains optimistic about her field.

“There’s a traditional mindset in China: Your education is a priority,” Zhang says. “Finish it, no matter what, and then be prepared to embrace opportunities when they come — and then keep learning.

“I started from scratch in this field, and I’m happy where I am right now,” she adds. “I’m looking forward to what comes next.”

This post was originally published in Plant Sciences Initiative.