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Open AccessArticle

Coupling Waveguide-Based Micro-Sensors and Spectral Multivariate Analysis to Improve Spray Deposit Characterization in Agriculture

1
ITAP, Irstea, Montpellier SupAgro, Université de Montpellier, 361 rue Jean-François Breton, 34000 Montpellier, France
2
ICGM, UMR 5253, cc1503, Université de Montpellier, Place Eugène Bataillon, CEDEX 5, 34095 Montpellier, France
3
IES, UMR 5214, cc05005, Université de Montpellier, Bâtiment 5, 860 rue Saint-Priest, 34090 Montpellier, France
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(19), 4168; https://doi.org/10.3390/s19194168
Received: 7 August 2019 / Revised: 9 September 2019 / Accepted: 24 September 2019 / Published: 26 September 2019
(This article belongs to the Special Issue Smart Sensing Technologies for Agriculture)
The leaf coverage surface is a key measurement of the spraying process to maximize spray efficiency. To determine leaf coverage surface, the development of optical micro-sensors that, coupled with a multivariate spectral analysis, will be able to measure the volume of the droplets deposited on their surface is proposed. Rib optical waveguides based on Ge-Se-Te chalcogenide films were manufactured and their light transmission was studied as a response to the deposition of demineralized water droplets on their surface. The measurements were performed using a dedicated spectrophotometric bench to record the transmission spectra at the output of the waveguides, before (reference) and after drop deposition, in the wavelength range between 1200 and 2000 nm. The presence of a hollow at 1450 nm in the relative transmission spectra has been recorded. This corresponds to the first overtone of the O–H stretching vibration in water. This result tends to show that the optical intensity decrease observed after droplet deposition is partly due to absorption by water of the light energy carried by the guided mode evanescent field. The probe based on Ge-Se-Te rib optical waveguides is thus sensitive throughout the whole range of volumes studied, i.e., from 0.1 to 2.5 μL. Principal Component Analysis and Partial Least Square as multivariate techniques then allowed the analysis of the statistics of the measurements and the predictive character of the transmission spectra. It confirmed the sensitivity of the measurement system to the water absorption, and the predictive model allowed the prediction of droplet volumes on an independent set of measurements, with a correlation of 66.5% and a precision of 0.39 μL. View Full-Text
Keywords: optical micro-sensors; crop protection; precision agriculture; infrared spectroscopy; principal component analysis (PCA); partial least squares (PLS); droplet characterization optical micro-sensors; crop protection; precision agriculture; infrared spectroscopy; principal component analysis (PCA); partial least squares (PLS); droplet characterization
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MDPI and ACS Style

Taleb Bendiab, A.; Ryckewaert, M.; Heran, D.; Escalier, R.; Kribich, R.K.; Vigreux, C.; Bendoula, R. Coupling Waveguide-Based Micro-Sensors and Spectral Multivariate Analysis to Improve Spray Deposit Characterization in Agriculture. Sensors 2019, 19, 4168.

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