Résumé
New techniques for agriculture science are widely explored since several decades in order to improve production yield. Measurements of optical properties at different scales of the crop are investigated and exploited to assess different parameters of interest such as state of stress. For instance, nowadays, there exists acquisition systems embedded in drones, mobile machines and satellites that are able to collect huge amount of hyperspectral imaging data. Identification of optical signature extracted from these techniques can help agronomist with adapting irrigation or distinguishing different plant varieties. These techniques allow to improve greatly the agricultural management, however they do not provide information about the internal structure of the plant leaf and their interaction with electromagnetic fields. Knowing precisely the plant leaf structure can bring critical information that can lead to the development of new techniques for phenotyping and precocious stress detection. To do this it is necessary to probe the plant at the leaf scale using THz instead of optical frequencies because the scattering sensitive phenomenon for plants is more drastic at optical frequencies. To find out how the light interact with the leaf, in a deterministic way, we can model the vegetal tissue as a stack of different physical layers characterized by the thickness and the optical index. In this study, funded by ANR project OptiPAG, we use a well-known reverse engineering technique to retrieve leaf architecture from the reflection data. In time domain, a short Terahertz pulse illuminates a multilayer sample that reflects a part of the signal carrying information about the sample structure. Using a numerical fit in the frequency domain allows to identify each layer and deduce the respective optical index over the input frequency range. We use a few classical (inorganic) etalon samples and analyze the echoes to reveal their thicknesses under the assumption of negligible absorption. Then, we use reverse engineering technique to fit the data in the THz range by taking into account the absorption, making an excellent agreement with the previous results with more accuracy. The measured thickness of the samples correspond very well with the manufacturing specifications. And finally we use this technique with vegetal tissues (sunflower leaves), that poses a much more complex situation. Results emphasize a 8-layer stack including trichomes, cuticules, epidermis and mesophyll layers and for each layer we extract the thickness and the complex index. To our knowledge this is the first time that the leaf multilayer structure is extracted with accuracy using a non-contact techniques.