Data from: In situ foliar augmentation of multiple species for optical phenotyping and bioengineering using soft robotics
Data files
Dec 11, 2025 version files 222.79 MB
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Actuator_Blocking_Force_Pictures.zip
6.72 MB
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Actuator_Elongation_Pictures.zip
8.35 MB
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Actuator_Optimization_Dataset.zip
26.41 KB
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Actuator_Profile_Movie.zip
112.79 MB
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Agroinfiltration_Pictures.zip
18.50 MB
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Confocal_Microscopy_Pictures.zip
2.95 MB
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Cotton_Injection-Injury_Pictures.zip
29.75 MB
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Injection_area_and_porometer_Dataset.zip
5.36 KB
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README.md
3.06 KB
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Spectrometer_Dataset.zip
206.01 KB
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Spectrophotometer_Dataset.zip
318.50 KB
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Sunflower_Injection-Injury_Pictures.zip
43.16 MB
Abstract
Precision agriculture aims to increase crop yield while reducing the use of harmful chemicals (e.g., pesticides, excess fertilizer) by employing minimal, tailored interventions. These strategies, however, are limited by (i) sensor quality, which typically relies on visual plant expressions, and (ii) the manual, destructive nature of many non-visual measurement methods, such as the Scholander pressure bomb. By automating more intimate interactions with foliage, in vivo, it would be possible to inject chemical and biological probes that reveal more phenotypes, such as water stress in response to varying environmental conditions, and visible gene expression to measure the success of gene engineering applications. To address this, we developed a soft robotic leaf gripper and stamping-injection method to improve foliar delivery of nanoscale synthetic and biological probes. This allows for non-destructive, in situ, multi-species applications. We used two probes: (i) Agrobacterium tumefaciens carrying the RUBY gene as a reporter system for plant transformation, and (ii) nanoparticle hydrogels for measuring leaf water potential (ψ). Our hourglass-shaped design enabled the gripper to achieve higher forces with reduced radial expansion, resulting in an injection success rate above 91%. Studies on sunflower (Helianthus annuus L.) and cotton (Gossypium hirsutum L.) showed our method achieved an average 12-fold increase in infiltration areas, with significantly less leaf damage—3.6% in sunflower and none in cotton—compared to the needle-free syringe method. Enabling long periods of successful in vivo phenotyping on both species following precise and safe foliar delivery underscores the potential of the leaf gripper for robotic plant bioengineering.
Dataset DOI: 10.5061/dryad.9kd51c5vm
Description of the data and file structure
Includes:
- PICTURES/MOVIES:
- Actuator Blocking Force Pictures
- Actuator Elongation Pictures
- Actuator Profile Movie
- Agroinfiltration Pictures
- Confocal Microscopy Pictures
- Cotton Injection-Injury Pictures
- Sunflower Injection-Injury Pictures
- DATASET & MATLAB Scripts:
- Actuator Optimization Dataset
- Injection area and porometer Dataset
- Spectrometer Dataset
- Spectrophotometer Dataset
Files and variables
Note: All the folders have respective README file which describes the respective files.
File: Actuator_Optimization_Dataset.zip
Description: ANSYS simulation results for 800 cases, along with a MATLAB script for generating the surface optimization plot.
File: Actuator_Blocking_Force_Pictures.zip
Description: Pictures of the soft actuator blocking force test for a pressure range of 0 to 13 psi.
File: Actuator_Elongation_Pictures.zip
Description: Images from the soft actuator elongation test for a pressure range of 0 to 8 psi.
File: Confocal_Microscopy_Pictures.zip
Description: Confocal microscopy images of a leaf injected with AquaDust.
File: Agroinfiltration_Pictures.zip
Description: Photos of 0DPI taken after agroinfiltration, along with images of 3DPI displaying betalain pigmentation.
File: Actuator_Profile_Movie.zip
Description: The movie demonstrates the stamping profile of the soft actuator.
File: Injection_area_and_porometer_Dataset.zip
Description: Dataset of injection areas and promoter measurements, along with a MATLAB script for plant characterization plots.
File: Spectrophotometer_Dataset.zip
Description: Dataset of spectrophotometer measurements and MATLAB script displaying the plot of changes in leaf reflectance and absorbtion.
File: Cotton_Injection-Injury_Pictures.zip
Description: Injection photos taken immediately after the injection and subsequent leaf injury images for the cotton plant.
File: Sunflower_Injection-Injury_Pictures.zip
Description: Injection photos taken immediately after the injection and subsequent leaf injury images for the sunflower plant.
File: Spectrometer_Dataset.zip
Description: Dataset of spectrometer measurements and MATLAB script for the plot illustrating the change in FRET levels.
Code/software
The provided scripts were originally written in MATLAB, which requires a commercial license. However, the code can be adapted for use with open-source programming languages such as Python, by converting MATLAB functions and library calls to their Python equivalents and ensuring the syntax is appropriately adjusted.
Access information
Other publicly accessible locations of the data:
- None
Data was derived from the following sources:
- None
