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Hyperspectral Imaging (HSI) techniques have demonstrated potential to provide useful information in a broad set of applications in different domains, from precision agriculture to environmental science. A first step in the preparation of the algorithms to be employed outdoors starts at a laboratory level, capturing a high amount of samples to be analysed and processed in order to extract the necessary information about the spectral characteristics of the studied samples in the most precise way. In this article, a custom-made scanning system for hyperspectral image acquisition is described. Commercially available components have been carefully selected in order to be integrated into a flexible infrastructure able to obtain data from any Generic Interface for Cameras (GenICam) compliant devices using the gigabyte Ethernet interface. The entire setup has been tested using the Specim FX hyperspectral series (FX10 and FX17) and a Graphical User Interface (GUI) has been developed in order to control the individual components and visualise data. Morphological analysis, spectral response and optical aberration of these pushbroom-type hyperspectral cameras have been evaluated prior to the validation of the whole system with different plastic samples for which spectral signatures are extracted and compared with well-known spectral libraries.

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Multispectral imaging (MI) techniques are being used very often to identify different properties of nature in several domains, going from precision agriculture to environmental studies, not to mention quality inspection of pharmaceutical production, art restoration, biochemistry, forensic sciences or geology, just to name some. Different implementations are commercially available from the industry and yet there is quite an interest from the scientific community to spread its use to the majority of society by means of cost effectiveness and ease of use for solutions. These devices make the most sense when combined with unmanned aerial vehicles (UAVs), going a step further and alleviating repetitive routines which could be strenuous if traditional methods were adopted. In this work, a low cost and modular solution for a multispectral camera is presented, based on the use of a single panchromatic complementary metal oxide semiconductor (CMOS) sensor combined with a rotating wheel of interchangeable band pass optic filters. The system is compatible with open source hardware permitting one to capture, process, store and/or transmit data if needed. In addition, a calibration and characterization methodology has been developed for the camera, allowing not only for quantifying its performance, but also able to characterize other CMOS sensors in the market in order to select the one that best suits the budget and application. The process was experimentally validated by mounting the camera in a Dji Matrice 600 UAV to uncover vegetation indices in a reduced area of palm trees plantation. Results are presented for the normalized difference vegetation index (NDVI) showing a generated colored map with the captured information.

Canarias es uno de los destinos turísticos principales de Europa. El Archipiélago recibió en 2015 más de 13 millones de turistas y todo ello en un territorio muy limitado (7.4 mil km2 y una población de 2.1 millones). Las dimensiones de estas cifras adquieren relevancia en un contexto donde el 63 % de la superficie de las Islas ha sido declarada Reserva Mundial de la Biosfera. Se estudia aquí pues, el impacto del turismo –así como algunas alternativas en aras de paliar dicho impacto–, en las cinco islas que han sido declaradas en su integridad como tales, partiendo de sus particularidades.

In the course of a study conducted to isolate genes upregulated by plant cell wall sugars, we identified an arabinose-inducible locus from a transcriptional fusion library of Rhizobium leguminosarum VF39, carrying random insertions of the lacZ transposon Tn5B22. Sequence analysis of the locus disrupted by the transposon revealed a high similarity to uncharacterized malate synthase G genes from Sinorhizobium meliloti, Agrobacterium tumefaciens, and Mesorhizobium loti. This enzyme catalyzes the condensation of glyoxylate and acetyl-CoA to yield malate and CoA and is thought to be a component of the glyoxylate cycle, which allows microorganisms to grow on two carbon compounds. Enzyme assays showed that a functional malate synthase is encoded in the glcB gene of R. leguminosarum and that its expression is induced by arabinose, glycolate, and glyoxylate. An Escherichia coli aceB glcB mutant, complemented with the R. leguminosarum PCR-amplified gene, recovered malate synthase activity. A very similar genome organization of the loci containing malate synthase and flanking genes was observed in R. leguminosarum, S. meliloti, and A. tumefaciens. Pea plants inoculated with the glcB mutant or the wild-type strain showed no significant differences in nitrogen fixation. This is the first report regarding the characterization of a mutant in one of the glyoxylate cycle enzymes in the rhizobia.

Plant responses to abiotic stresses are complex and dynamic, and involve changes in different traits, either as the direct consequence of the stress, or as an active acclimatory response. Abiotic stresses frequently occur simultaneously or in succession, rather than in isolation. Despite this, most studies have focused on a single stress and single or few plant traits. To address this gap, our study comprehensively and categorically quantified the individual and combined effects of three major abiotic stresses associated with climate change (flooding, progressive drought and high temperature) on 12 phenotypic traits related to morphology, development, growth and fitness, at different developmental stages in four Arabidopsis thaliana accessions. Combined sublethal stresses were applied either simultaneously (high temperature and drought) or sequentially (flooding followed by drought). In total, we analysed the phenotypic responses of 1782 individuals across these stresses and different developmental stages. Overall, abiotic stresses and their combinations resulted in distinct patterns of effects across the traits analysed, with both quantitative and qualitative differences across accessions. Stress combinations had additive effects on some traits, whereas clear positive and negative interactions were observed for other traits: 9 out of 12 traits for high temperature and drought, 6 out of 12 traits for post-submergence and drought showed significant interactions. In many cases where the stresses interacted, the strength of interactions varied across accessions. Hence, our results indicated a general pattern of response in most phenotypic traits to the different stresses and stress combinations, but it also indicated a natural genetic variation in the strength of these responses. This includes novel results regarding the lack of a response to drought after submergence and a decoupling between leaf number and flowering time after submergence. Overall, our study provides a rich characterization of trait responses of Arabidopsis plants to sublethal abiotic stresses at the phenotypic level and can serve as starting point for further in-depth physiological research and plant modelling efforts.