Industry Expertise (4)
Areas of Expertise (3)
University of Paris VI: Ph.D., Laser and Matter interactions 1996
University of Paris XII: M.S., Laser Engineering and Application 1992
Selected Articles (3)
Cucumber is a source of essential minerals to the diet. However, it is attacked by Cucumber mosaic virus that can reduce its yields. We propose in this study a strategy for early detection of this virus by artificial neural networks using the fingerprint of the cucumber leaves in the transmission, reflection and diffusion modes. We demonstrates in this work that the use of the optical spectral fingerprints of plants leaves contents, such as cucumber, is a powerful technique to resolve their contents and for earlier detection of some related diseases. We have built and used a cost-effective light emitting diodes multispectral and multimodal imaging which enabled the acquisition of the spectral and spatial information, used for an earlier detection of Cucumber mosaic virus.
Most commercially available ground coffees are processed from Robusta or Arabica coffee beans. In this work, we report on the potential of Structured Laser Illumination Planar Imaging (SLIPI) technique for the classification of five types of Robusta and Arabica commercial ground coffee samples (Familial, Belier, Brazil, Colombia and Malaga). This classification is made, here, from the measurement of the extinction coefficient µe and of the optical depth OD by means of SLIPI. The proposed technique offers the advantage of eliminating the light intensity from photons which have been multiply scattered in the coffee solution, leading to an accurate and reliable measurement of µe. Data analysis uses the chemometric techniques of Principal Component Anaysis (PCA) for variable selection and Hierarchical Cluster Analysis (HCA) for classification. The chemometric model demonstrates the potential of this approach for practical assessment of coffee grades by correctly classifying the coffee samples according to their species.
Sustainable agriculture with use of Arbuscular Mycorrhizal Fungi (AMF) is an emerging farm management that improves crops nutrient and water use efficiency. Decision making on the effect of AMF is still dependent on agronomic diagnosis which is long, tedious, expensive and destructive. This study demonstrates the applicability of proximal fluorescence and reflectance spectroscopy for evaluating and detecting at early stage distinct types of mycorrhized plantain from two cultivars (Musa paradisiaca).
Visible-near infrared (400-1000 nm) reflectance and fluorescence data were collected from control and three levels mycorrhized plants designed in randomized and complete block under greenhouse conditions. Two spectral measurements at a week interval were performed on plant leaves by using an USB spectrometer mounted with an Arduino-based LED driver clip.
A new normalized reflectance water NWI5 index shows with Datt5 alone highly significant differences at P