Study of moisture content in leaves through regression analysis of terahertz images

Mayuri Kashyap; Aparajita Bandyopadhyay; Amartya Sengupta

doi:10.1117/12.2621425

17 May 2022 Study of moisture content in leaves through regression analysis of terahertz images

Mayuri Kashyap, Aparajita Bandyopadhyay, Amartya Sengupta

Proceedings Volume 12139, Optical Sensing and Detection VII; 121390J (2022) https://doi.org/10.1117/12.2621425
Event: SPIE Photonics Europe, 2022, Strasbourg, France

Abstract

Precision agriculture has evolved over the years to meet the growing demand for agricultural productivity with limited resources, and with it, the smart irrigation techniques are also gaining traction. Management of water is critical since it is one of the most significant components of the photosynthetic process and hence an indicator of crop health and yield. Due to the high sensitivity of Terahertz (THz) radiation towards the presence of water, in current work, the moisture content in leaves from a Capsicum annuum plant is approximated using THz time-domain imaging. To overcome the effect of approximations and limitations in theoretical models, this work aims to generalize the prediction of moisture content in plants by simulating drought stress in an un-watered plant through a detached leaf. This is achieved through analysis of time-lapsed THz imaging of several leaves by employing a machine learning approach. The THz images are processed to retrieve pixels corresponding only to the flat lamina without the veins because of their morphological differences. The process is repeated for all instances of images as the leaf dries up. For predicting the moisture content in the leaf, transmittance of the selected pixels at selected frequencies ranging from 0.4-2.1 THz are used to train supervised machine learning regression (SMLR) model. Standard error of estimate (SEE) used for performance analysis of Decision Tree, Random Forest and Support Vector regression models show that as the drought sets in and the leaves dry up, the prediction accuracy improves.

Conference Presentation

Citation Download Citation

Mayuri Kashyap, Aparajita Bandyopadhyay, and Amartya Sengupta "Study of moisture content in leaves through regression analysis of terahertz images", Proc. SPIE 12139, Optical Sensing and Detection VII, 121390J (17 May 2022); https://doi.org/10.1117/12.2621425

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