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Remote sensing has gained much attention for agronomic applications such as crop management or yield estimation. Crop phenotyping under field conditions has recently become another important application that requires specific needs: the considered remote-sensing method must be (1) as accurate as possible so that slight differences in phenotype can be detected and related to genotype, and (2) robust so that thousands of cultivars potentially quite different in terms of plant architecture can be characterized with a similar accuracy over different years and soil and weather conditions. In this study, the potential of nadir and off-nadir ground-based spectro-radiometric measurements to remotely sense five plant traits relevant for field phenotyping, namely, the leaf area index (LAI), leaf chlorophyll and nitrogen contents, and canopy chlorophyll and nitrogen contents, was evaluated over fourteen sugar beet (Beta vulgaris L.) cultivars, two years and three study sites. Among the diversity of existing remote-sensing methods, two popular approaches based on various selected Vegetation Indices (VI) and PROSAIL inversion were compared, especially in the perspective of using them for phenotyping applications.Overall, both approaches are promising to remotely estimate LAI and canopy chlorophyll content ( ≤ 10 %). In addition, VIs show a great potential to retrieve canopy nitrogen content ( = 10 %). On the other hand, the estimation of leaf-level quantities is less accurate, the best accuracy being obtained for leaf chlorophyll content estimation based on VIs ( = 17 %). As expectedAuthor-produced version of the article published in Field Crops Research, 2017, N°210, p.33-46. The original publication is available at http://www.sciencedirect.com Doi: 10.1016Doi: 10. /j.fcr.2017 when observing the relationship between leaf chlorophyll and nitrogen contents, poor correlations are found between VIs and mass-based or area-based leaf nitrogen content. Importantly, the estimation accuracy is strongly dependent on sun-sensor geometry, the structural and biochemical plant traits being generally better estimated based on nadir and off-nadir observations, respectively.Ultimately, a preliminary comparison tends to indicate that, providing that enough samples are included in the calibration set, (1) VIs provide slightly more accurate performances than PROSAIL inversion, (2) VIs and PROSAIL inversion do not show significant differences in robustness across the different cultivars and years. Even if more data are still necessary to draw definitive conclusions, the results obtained with VIs are promising in the perspective of high-throughput phenotyping using UAVembedded multispectral cameras, with which only a few wavebands are available.

Accurate estimation of leaf chlorophyll content (Cab) from remote sensing is of tremendous significance to monitor the physiological status of vegetation or to estimate primary production. Many vegetation indices (VIs) have been developed to retrieve Cab at the canopy level from meter-to decameter-scale reflectance observations. However, most of these VIs may be affected by the possible confounding influence of canopy structure. The objective of this study is to develop methods for Cab estimation using millimeter to centimeter spatial resolution reflectance imagery acquired at the field level. Hyperspectral images were acquired over sugar beet canopies from a ground-based platform in the 400-1000 nm range, concurrently to Cab, green fraction (GF), green area index (GAI) ground measurements. The original image spatial resolution was successively degraded from 1 mm to 35 cm, resulting in eleven sets of hyperspectral images. Vegetation and soil pixels were discriminated, and for each spatial resolution, measured Cab values were related to various VIs computed over four sets of reflectance spectra extracted from the images (soil and vegetation pixels, only vegetation pixels, 50% darkest and brightest vegetation pixels). The selected VIs included some classical VIs from the literature as well as optimal combinations of spectral bands, including simple ratio (), modified

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In order to better understand physical and biological clogging in drip-irrigation, a study was conducted on the impacts of hydrodynamic conditions on clay particle deposition and biofilm development in drippers using an optical method. A transparent milli-fluidic system composed of labyrinth channels was used to identify areas most susceptible to particle clogging using two different types of clay suspensions: sodium bentonite and kaolin. The impact of salt addition ([NaCl] =200 mg.L-1) on the clay deposition was also analyzed. Biofilm development was studied using the same methodology using a nutritive solution (chemical oxygen demand, COD = 200 mg.L-1). In addition, fluid dynamics simulations were performed along the labyrinth channel to understand the effect of flow behaviour on the fouling. Computational Fluid Dynamics results show two types of flow topology: high velocity in the main flow (around 1m.s-1) and low velocity in the vortex zones (less than 0.2 m.s-1) found in the channel corners. Using an optical method, kaolin deposition and biofilm growth in the dripper were observed to occur mainly in the inlet channel and initial vortex zones, which are characterized by lower mean velocity and turbulent kinetic energy values. This part of the dripper can be considered as a bottleneck that amplifies the fouling phenomena and which should be optimized. With the addition of NaCl, kaolin particles tend to form bigger flocs. Therefore, more significant particle deposition is observed, but this is not the case of bentonite for which no fouling is observed along the dripper.

We introduce a time-domain model to study the dynamics of optoelectronic oscillators. We show that, due to the interaction between nonlinearity and time delay, the envelope amplitude of ultrapure microwaves generated by optoelectronic oscillators can turn unstable when the gain is increased beyond a given critical value. Our analytical predictions are confirmed by numerical simulations and experiments.