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Keywords = Phenoliner

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26 pages, 2643 KiB  
Article
Detection of Grapevine Leafroll-Associated Virus 1 and 3 in White and Red Grapevine Cultivars Using Hyperspectral Imaging
by Nele Bendel, Anna Kicherer, Andreas Backhaus, Janine Köckerling, Michael Maixner, Elvira Bleser, Hans-Christian Klück, Udo Seiffert, Ralf T. Voegele and Reinhard Töpfer
Remote Sens. 2020, 12(10), 1693; https://doi.org/10.3390/rs12101693 - 25 May 2020
Cited by 40 | Viewed by 6949
Abstract
Grapevine leafroll disease (GLD) is considered one of the most widespread grapevine virus diseases, causing severe economic losses worldwide. To date, six grapevine leafroll-associated viruses (GLRaVs) are known as causal agents of the disease, of which GLRaV-1 and -3 induce the strongest symptoms. [...] Read more.
Grapevine leafroll disease (GLD) is considered one of the most widespread grapevine virus diseases, causing severe economic losses worldwide. To date, six grapevine leafroll-associated viruses (GLRaVs) are known as causal agents of the disease, of which GLRaV-1 and -3 induce the strongest symptoms. Due to the lack of efficient curative treatments in the vineyard, identification of infected plants and subsequent uprooting is crucial to reduce the spread of this disease. Ground-based hyperspectral imaging (400–2500 nm) was used in this study in order to identify white and red grapevine plants infected with GLRaV-1 or -3. Disease detection models have been successfully developed for greenhouse plants discriminating symptomatic, asymptomatic, and healthy plants. Furthermore, field tests conducted over three consecutive years showed high detection rates for symptomatic white and red cultivars, respectively. The most important detection wavelengths were used to simulate a multispectral system that achieved classification accuracies comparable to the hyperspectral approach. Although differentiation of asymptomatic and healthy field-grown grapevines showed promising results further investigations are needed to improve classification accuracy. Symptoms caused by GLRaV-1 and -3 could be differentiated. Full article
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18 pages, 11519 KiB  
Article
Phenoliner: A New Field Phenotyping Platform for Grapevine Research
by Anna Kicherer, Katja Herzog, Nele Bendel, Hans-Christian Klück, Andreas Backhaus, Markus Wieland, Johann Christian Rose, Lasse Klingbeil, Thomas Läbe, Christian Hohl, Willi Petry, Heiner Kuhlmann, Udo Seiffert and Reinhard Töpfer
Sensors 2017, 17(7), 1625; https://doi.org/10.3390/s17071625 - 14 Jul 2017
Cited by 46 | Viewed by 9529
Abstract
In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, [...] Read more.
In grapevine research the acquisition of phenotypic data is largely restricted to the field due to its perennial nature and size. The methodologies used to assess morphological traits and phenology are mainly limited to visual scoring. Some measurements for biotic and abiotic stress, as well as for quality assessments, are done by invasive measures. The new evolving sensor technologies provide the opportunity to perform non-destructive evaluations of phenotypic traits using different field phenotyping platforms. One of the biggest technical challenges for field phenotyping of grapevines are the varying light conditions and the background. In the present study the Phenoliner is presented, which represents a novel type of a robust field phenotyping platform. The vehicle is based on a grape harvester following the concept of a moveable tunnel. The tunnel it is equipped with different sensor systems (RGB and NIR camera system, hyperspectral camera, RTK-GPS, orientation sensor) and an artificial broadband light source. It is independent from external light conditions and in combination with artificial background, the Phenoliner enables standardised acquisition of high-quality, geo-referenced sensor data. Full article
(This article belongs to the Special Issue Sensors in Agriculture)
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4 pages, 137 KiB  
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Synthesis, Physical Characterization, Antibacterial and Antifungal Activities of 2-((E)-1-(2-((E)-1-(2-Hydroxyphenyl)ethylideneamino) phenylamino) ethyl) phenol
by A. A. Jarrahpour, A. F. Jalbout, J. M. Brunel, C. Loncle, S. Rezaei and B. Trzaskowski Trzaskowski
Molbank 2006, 2006(5), M489; https://doi.org/10.3390/M489 - 1 Sep 2006
Viewed by 4446
Abstract
In this paper we report the synthesis of 2-((E)-1-(2-((E)-1-(2-hydroxyphenyethylideneamino) phenylamino) ethyl) phenol.In addition to its synthesis we present AM1 and B3LYP/6-31G* calculations to characterize the physical properties of this molecule. Finally, the antifungal and antibacterial activities of this derivative have been evaluated. Full article
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