A new device for instant leaf analysis

A handheld, hyperspectral leaf imager will enable farmers to measure leaf moisture, chlorophyll content, nutrient level and diseases instantly.

LeafSpec, an accurate, affordable and portable hyperspectral leaf imager developed by assistant professor of agricultural and biological engineering Jian Jin at Purdue University in the US, was recently selected as an AE50 winner. The award, sponsored by the American Society of Agricultural and Biological Engineers’ Resource magazine, recognises top agricultural technology.

In an article published by Purdue University, Jian explains that plant phenotyping can be divided into remote sensing and proximal sensing. Remote sensing gathers data on plants from afar, using tools such as drones, and does so rapidly.

Proximal sensing, which is the technology built into LeafSpec, requires users to deal with plants individually. Although slower, it provides more information. “With proximal sensing, you can see details like disease spots, nutrient and stress distributions, and veins on the plant leaves,” explains Jian.

With just a five-second, nondestructive leaf scan, LeafSpec can measure a plant’s physiological features such as leaf moisture, chlorophyll content, nutrient level and diseases.

The handheld tool can be used at any location and generates hyperspectral leaf images with 0,5mm resolution. Measured plant features can be viewed in real time with a smartphone app.

SUPERIOR PERFORMANCE

Comparing his invention with other sensors, Jian says LeafSpec provides more detail and reliability, yet needs less work.

SPAD meters (chlorophyll meters) and spectrometers are the current standards. These devices read the greenness/ spectrum of a single point on a leaf.

“If you measure a maize leaf from collar to tip, you will see a significant increase in NDVI/ chlorophyll content,” said Jian.

“If you move the sensor just one inch to the left or right, you might have a 30% change, so measuring a single point opens the door to inconsistency. LeafSpec gives you a real hyperspectral image of the entire leaf.

“Combining LeafSpec’s hardware with our software and Geographic Information System, our device has unique advantages on the market.”

He adds that, on its own, the hardware provides a beautiful hyperspectral leaf image of unprecedented quality. But this alone is not useful to breeders and farmers, who need to be able to analyse the images and gain knowledge from them.

This is done with hyperspectral imageprocessing software. Working with other researchers, a system was developed to automatically receive data from LeafSpec and provide data-viewing functions in real time with a user-friendly interface.

When a leaf is scanned, the nitrogen predictions, water and disease information appear on the user’s smartphone within seconds. If the smartphone is connected to the Internet, it will automatically upload predictions with the GPS location, time, weather and additional data.

Early versions of LeafSpec have already been sold to university laboratories and agricultural companies such as Farm2U, a company in India that has used the device to scan apple tree leaves.

According to Jian, although the current device and software meet the needs of researchers, it is not completely ready for the much larger market of crop farmers. However, the device should be ready for commercial sale by 2022.

For more information on the equipment in this report, email Denene Erasmus at denene@caxton.co.za.

Subject line: Equipment.

THE DEVICE PROVIDES MORE DETAIL THAN OTHER SENSORS, YET REQUIRES LESS WORK

PURDUE UNIVERSITY Jian Jin, a research engineer at Purdue University in the US, with the LeafSpec hyperspectral leaf imager, which he designed. The device will make it possible for farmers to conduct detailed leaf analysis within seconds in their fields.