Spectral unmixing approach in hyperspectral remote sensing: a tool for oil palm mapping

Las plantaciones de palma de aceite típicamente abarcan grandes áreas, por esto, la teledetección remota se ha convertido en una herramienta útil para el monitoreo avanzado de este cultivo. Este trabajo revisa y evalúa dos enfoques para analizar las plantaciones de palma de aceite a partir de datos de teledetección remota hiperespectral: desmezclado espectral lineal y variabilidad espectral. Además, se propone un marco computacional basado en el desmezclado espectral para la estimación de las fracciones de abundancias de cultivos de palma de aceite. Este enfoque también considera la variabilidad espectral de las firmas en las imágenes hiperespectrales. El marco computacional propuesto modifica el modelo de mezcla lineal mediante la introducción de un vector de pesos, de manera que se puedan identificar las bandas espectrales que menos contribuyen a la estimación de fracciones de abundancias erróneas. Este enfoque aprovecha la detección de los árboles de palma de aceite, ya que permite diferenciarlos de otros materiales en términos de fracciones de abundancia. Los resultados experimentales obtenidos a partir de datos de teledetección remota hiperespectral en el rango de 410-990 nm, muestran mejoras de un 8.18 % en la métrica de Precisión del Usuario (Uacc) en la identificación de palmas de aceite por el marco propuesto con respecto a los métodos tradicionales de desmezclado espectral; el método propuesto logró un 95 % de Uacc. Esto confirma las capacidades del marco computacional formulado y facilita la gestión y el monitoreo de grandes áreas de plantaciones de palma de aceite.Oil palm plantations typically span large areas; therefore, remote sensing has become a useful tool for advanced oil palm monitoring. This work reviews and evaluates two approaches to analyze oil palm plantations based on hyperspectral remote sensing data: linear spectral unmixing and spectral variability. Moreover, a computational framework based on spectral unmixing for the estimation of fractional abundances of oil palm plantations is proposed in this study. Such approach also considers the spectral variability of hyperspectral image signatures. More specifically, the proposed computational framework modifies the linear mixing model by introducing a weighting vector, so that the spectral bands that contribute the least to the estimation of erroneous fractional abundances can be identified. This approach improves palm detection as it allows to differentiate them from other materials in terms of fractional abundances. Experimental results obtained from hyperspectral remote sensing data in the range 410-990 nm show improvements of 8.18 % in User Accuracy (Uacc) in the identification of oil palms by the proposed framework with respect to traditional unmixing methods. Thus, the proposed method achieved a 95% Uacc. This confirms the capabilities of the proposed computational framework and facilitates the management and monitoring of large areas of oil palm plantations

Genetic Basis and Clonal Population Structure of Antibiotic Resistance in Campylobacter jejuni Isolated From Broiler Carcasses in Belgium

&lt;p&gt;Human campylobacteriosis is the leading food-borne zoonosis in industrialized countries. This study characterized the clonal population structure, antimicrobial resistance profiles and occurrence of antimicrobial resistance determinants of a set of strains isolated from broiler carcasses in Belgium. Minimum inhibitory concentrations (MICs) against five commonly-used antibiotics (ciprofloxacin, nalidixic acid, tetracycline, gentamicin, and erythromycin) were determined for 204 isolates. More than half of the isolates were resistant to ciprofloxacin or nalidixic acid. In contrast, a lower percentage of screened isolates were resistant to gentamicin or erythromycin. isolates resistant to ciprofloxacin and/or nalidixic acid were screened for the substitution T86I in the quinolone resistance determining region (QRDR) of the gene, while isolates resistant to tetracycline were screened for the presence of the gene. These resistance determinants were observed in most but not all resistant isolates. Regarding resistance to erythromycin, different mutations occurred in diverse genetic loci, including mutations in the 23S rRNA gene, the and ribosomal genes, and the intergenic region between and . Interestingly, and contrary to previous reports, the A2075G transition mutation in the 23S rRNA gene was only found in one strain displaying a high level of resistance to erythromycin. Ultimately, molecular typing by multilocus sequence typing revealed that two sequence types (ST-824 and ST-2274) were associated to quinolones resistance by the presence of mutations in the gene ( = 0.01). In addition, ST-2274 was linked to the CIP-NAL-TET-AMR multidrug resistant phenotype. In contrast, clonal complex CC-45 was linked to increased susceptibility to the tested antibiotics. The results obtained in this study provide better understanding of the phenotypic and the molecular basis of antibiotic resistance in , unraveling some the mechanisms which confer antimicrobial resistance and particular clones associated to the carriage and spread of resistance genes.&lt;/p&gt;</p

Orthogonal typing methods identify genetic diversity among Belgian Campylobacter jejuni strains isolated over a decade from poultry and cases of sporadic human illness

Campylobacter jejuni is a zoonotic pathogen commonly associated with human gastroenteritis. Retail poultry meat is a major food-related transmission source of C. jejuni to humans. The present study investigated the genetic diversity, clonal relationship, and strain risk-analysis of 403 representative C. jejuni isolates from chicken broilers (n = 204) and sporadic cases of human diarrhea (n = 199) over a decade (2006–2015) in Belgium, using multilocus sequence typing (MLST), PCR binary typing (P-BIT), and identification of lipooligosaccharide (LOS) biosynthesis locus classes. A total of 123 distinct sequence types (STs), clustered in 28 clonal complexes (CCs) were assigned, including ten novel sequence types that were not previously documented in the international database. Sequence types ST-48, ST-21, ST-50, ST-45, ST-464, ST-2274, ST-572, ST-19, ST-257 and ST-42 were the most prevalent. Clonal complex 21 was the main clonal complex in isolates from humans and chickens. Among observed STs, a total of 35 STs that represent 72.2% (291/403) of the isolates were identified in both chicken and human isolates confirming considerable epidemiological relatedness; these 35 STs also clustered together in the most prevalent CCs. A majority of the isolates harbored sialylated LOS loci associated with potential neuropathic outcomes in humans. Although the concordance between MLST and P-BIT, determined by the adjusted Rand and Wallace coefficients, showed low congruence between both typing methods. The discriminatory power of P-BIT and MLST was similar, with Simpson's diversity indexes of 0.978 and 0.975, respectively. Furthermore, P-BIT could provide additional epidemiological information that would provide further insights regarding the potential association to human health from each strain. In addition, certain clones could be linked to specific clinical symptoms. Indeed, LOS class E was associated with less severe infections. Moreover, ST-572 was significantly associated with clinical infections occurring after travelling abroad. Ultimately, the data generated from this study will help to better understand the molecular epidemiology of C. jejuni infection.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Microbiota of human precolostrum and its potential role as a source of bacteria to the infant mouth

Human milk represents a source of bacteria for the initial establishment of the oral (and gut) microbiomes in the breastfed infant, however, the origin of bacteria in human milk remains largely unknown. While some evidence points towards a possible endogenous enteromammary route, other authors have suggested that bacteria in human milk are contaminants from the skin or the breastfed infant mouth. In this work 16S rRNA sequencing and bacterial culturing and isolation was performed to analyze the microbiota on maternal precolostrum samples, collected from pregnant women before delivery, and on oral samples collected from the corresponding infants. The structure of both ecosystems demonstrated a high proportion of taxa consistently shared among ecosystems, Streptococcus spp. and Staphylococcus spp. being the most abundant. Whole genome sequencing on those isolates that, belonging to the same species, were isolated from both the maternal and infant samples in the same mother-infant pair, evidenced that in 8 out of 10 pairs both isolates were >99.9% identical at nucleotide level. The presence of typical oral bacteria in precolostrum before contact with the newborn indicates that they are not a contamination from the infant, and suggests that at least some oral bacteria reach the infant's mouth through breastfeeding.status: publishe

Mimicking a rainfall gradient to test the role of soil microbiota for mediating plant responses to drier conditions

Plant interactions with soil microbiota are important drivers of biodiversity and ecosystem function, but climate change can modify these interactions by directly altering the soil community, which can affect the direction and magnitude of such interactions. We manipulated water quantity and soil microbiota of two populations of three plant species that differ in their interactions with soil microbiota and assessed germination and biomass production under conditions that mimicked a rainfall gradient in southeastern Spain. We assessed the importance of soil microbiota from home and away (drier) sites for alleviating or exacerbating the effects of drier conditions. Our results suggest that home soil microbiota enhanced germination of the legume Trifolium stellatum. Conversely, we found that the grass, Lagurus ovatus, and the forb, Sisymbrium erysimoides, produced more biomass under moderate drying with soil microbiota from a drier site than with home soil microbiota, suggesting that dry-adapted soil microbiota alleviated the negative effects of drier conditions for these species. This maintenance of productivity with dry-adapted soil microbiota under drier conditions was found despite simultaneous reductions in leaf dry matter content and root-to-shoot ratio that would typically be less optimal traits changes under reduced water availability. Severe water limitation resulted in decreased plant biomass regardless of the plant species and soil inoculum, indicating a threshold effect whereby severe water limitation on growth supersedes the beneficial effects of soil microbiota. Overall, our results show that species identity, the severity of water limitation, and soil microbiota interact to determine the response of plants to drier conditions