Document Type
Thesis - Open Access
Award Date
2022
Degree Name
Master of Science (MS)
Department / School
Mechanical Engineering
First Advisor
Anamika Prasad
Keywords
chemical polymerization, dip coating, plant strain sensor, Polyaniline, soybean, sunflower
Abstract
The need for precision agriculture in today and future farming cannot be overstressed. Recent agriculture is characterized by numerous challenges such as environmental stressors and resource constraints resulting in low crop yield and unsustainable agriculture practices. Understanding plant growth mechanism and growth rate under the external influence is a bedrock towards precision agriculture practices ensuring optimum yield and sustainable utilization of resources. The current study addresses this need by developing and applying an affordable and stable sensor for monitoring plant growth. The sensor was fabricated by in-situ chemical polymerization of aniline on an elastic band substrate by dip coating. The sensor was characterized using optical imaging and Fourier-transformed infrared spectroscopy (FTIR), calibrated for strain sensing, and its stability was analyzed under cycling loading and temperature variations. When applied to sunflower and soybean stems, the sensor detected a rhythmic growth pattern with higher growth during the dark cycle in sunflower plants but a continuous growth for both the light and dark cycle for soybean. The similarities between growth rate and growth pattern observed on these plants with available information on plant growth indicate the fitness of the sensor for such precision measurement for plant health and suggest a step towards the development of precision sensing capability for agriculture.
Library of Congress Subject Headings
Growth (Plants)
Sunflowers -- Growth.
Sunflowers -- Monitoring.
Soybean -- Growth.
Soybean -- Monitoring.
Wearable technology.
Detectors.
Precision farming.
Number of Pages
50
Publisher
South Dakota State University
Recommended Citation
Borode, Temitope, "Design of Affordable Polyaniline - Based Wearable Sensor for Real Time Plant Growth Monitoring" (2022). Electronic Theses and Dissertations. 437.
https://openprairie.sdstate.edu/etd2/437