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About LeafSpec

Innovated in the ABE Plant Sensor Lab at the Department of Agricultural and Biological Engineering of Purdue University, LeafSpec is the first portable hyperspectral crop leaf imager of its kind in the world which can be easily deployed at any location and generates hyperspectral leaf images. 

A device designed to be compact in size

Many advanced hyperspectral imaging stations have been built in industry and academia for
plant phenotyping in the last 10 years, but this is the first time the hardware and software technologies
from the big hyperspectral imaging stations are implemented into a small handheld device.


Reliable results

Compared with the various crop remote sensing platforms, LeafSpec provides the new option of
“proximal” hyperspectral imaging of the crops with unprecedented higher imaging resolution, up to 0.5mm,  and
measurement quality. What does this mean? All the secondary veins on the leaf can be captured clearly with this handheld device.

Furthermore, Imaging in a closed chamber with a stable artificial lighting source
removes impact from the changing ambient light. The leaf is gently grasped inside the imaging chamber
with a fixed distance and surface angle to the camera and lighting source. Combining the hardware
design of the proximal hyperspectral imager with advanced image processing software, LeafSpec can
achieve higher signal-over-noise for leaf measurement, detecting plant nutrient and chemical stress
several days before experienced farmers or researchers can visually see the signs.


Convenience is our mission

Grab the leave, start scanning,  and wait. It takes only 10 seconds for LeafSpec to scan a leaf non-destructively and provide the measurement results of the plant’s physiological features. LeafSpec’s data technology provides automatic data transfer and results viewing functions: The image is immediately processed with an onboard microprocessor, and the measured plant features can be viewed in real-time with a smartphone app. Each measurement is geo-referenced and automatically saved to a digital ag cyberinfrastructure.

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