Caracterización morfoagronómica de seis cultivares de ayote (Cucurbita moschata Duch.) e incidencia de artrópodos y enfermedades

ResumenCon el objetivo de llevar a cabo la caracterización morfoagronómica en seis cultivares de ayote  Cucurbita moschata Duch) se realizó la presente investigación durante los meses de Julio del 2016 hasta Abril del 2017, en la Estación Experimental y Prácticas de la Facultad de Ciencias agronómicas, Universidad de El Salvador, ubicado en el municipio de San Luis Talpa, departamento de La Paz. El Salvador, C.A.  Para los seis tratamientos representados como cultivares e identificados por la forma del fruto, se registraron características cuantitativas y cualitativas de 10 plantas por cultivar bajo la técnica del microtunel durante las primeras dos semanas. Los datos de las variables se obtuvieron por medio de la guía de descriptores según las normas Internacionales del IBPGR, interpretando los datos con el programa InfoStat 20.0 aplicando estadística descriptiva: promedios, desviación estándar, coeficiente de variación y análisis multivariado que comprende: Correlación, Componentes Principales y Conglomerados.  El análisis de conglomerados generado dividió en tres grupos o clúster los cultivares, cuyas características reflejan homogeneidad dentro de cada uno. Se concluye que al realizar la caracterización mostró relevantes diferencias en cuanto al rendimiento y el desarrollo de la planta, observando el potencial de cada cultivar para diferentes propósitos de acuerdo a sus características. En el registro de artrópodos asociados al ayote los organismos que ocasionaron mayores daños son: Coleóptera: Crhysomelidae, incluyendo los géneros Diabrótica sp. y Acalymma sp; Lepidoptera: Pyralidae: Diaphania sp., y Sesiidae: Melittia sp. Asimismo, se identificaron los organismos de rol benéfico: Apidae (Apis sp., y Melipona sp.); Vespidae: Polybia sp.; Hemíptero: Anthocoridae: Orius sp., y Neuróptera: Chrysopidae. La manifestación de síntomas por virus y hongos se identificó en laboratorio por parte del CENTA, determinando la presencia de Cercospora sp., Curvularia sp., Alternaria sp., Sclerotium sp., y en mayor cantidad de daño el patógeno Pseudoperonospora sp.AbstractIn order to carry out the morphoagronomic characterization in six cultivars of cucumber (Cucurbita moschata Duch), this research was carried out during the months of July 2016 to April 2017, at the Experimental Station and Practices of the Faculty of Agronomic Sciences, University Of El Salvador, located in the municipality of San Luis Talpa, Department of La Paz. El Salvador, C.A. For the six treatments represented as cultivars and identified by the fruit shape, quantitative and qualitative characteristics of 10 plants per cultivar were recorded, and under the microtunel technique during the first two weeks. The data of the variables were obtained through the descriptive guide according to IBPGR International standards, interpreting the data with the program InfoStat 20.0 applying descriptive statistics: averages, standard deviation, coefficient of variation and multivariate analysis that includes: Correlation, Components Main and Conglomerates. The conglomerates generated by the multivariate analysis were divided into three groups whose characteristics reflect homogeneity within each one. It is concluded that the characterization showed significant differences in the yield and development of the plant, observing the potential of each cultivar for different purposes according to their characteristics. In the register of arthropods associated with the crop, the organisms that caused the most damage are: Coleoptera: Crhysomelidae, including the genus Diabrótica sp. and Acalymma sp, Lepidoptera: Pyralidae: Diaphania sp., And Sesiidae: Melittia sp. Likewise, organisms with a beneficial role were identified: Apidae (Apis sp., and Melipona sp.), Vespidae: Polybia sp., Hemiptera: Anthocoridae: Orius sp., and Neuróptera: Chrysopidae. The manifestation of symptoms by viruses and fungi was identified in the laboratory by CENTA, determining the presence of Cercospora sp., Curvularia sp., Alternaria sp., Sclerotium sp., and in greater amount of damage the pathogen Pseudoperonospora sp

Production and secretion of collagen-binding proteins from Aeromonas veronii

Collagen-binding protein (CNBP) synthesized by Aeromonas veronii is located conserved within the subcellular fraction. The results of this study show that 98% of the total CNBP produced by Aer. veronii is present in the extracellular medium, and that the remaining CNBP is distributed either on the cell surface, within the periplasm or anchored on the outer membrane. CNBP is specifically secreted from Aer. veronii into the culture medium, because all the -lactamase activity was located in the cells and could be released by polymixin B extraction of periplasmic proteins. CNBP was produced at growth temperatures from 12 °C to 42 °C, but not at 4 °C. The findings indicate that the level of CNBP in the medium increases during the exponential growth phase and reaches a maximum during the early stationary phase. There was less CNBP production in poor nutrient MMB medium than in the rich LB nutrient medium. CNBP secretion, in contrast to aerolysin secretion, was unaffected by the exeA mutation of Aer. hydrophila. It is concluded that CNBP secretion from Aer. veronii must be achieved by a mechanism different from that reported for aerolysin secretion

Genetic change following fire in populations of a seed-banking perennial plant

Disturbances such as fire have the potential to remove genetic variation, but seed banks may counter this loss by restoring alleles through a reservoir effect. We used allozyme analysis to characterize genetic change in two populations of the perennial Hypericum cumulicola, an endemic of the fire-prone Florida scrub. We assessed genetic variation before and 1, 2, and 3 years after fire that killed nearly all aboveground plants. Populations increased in size following fire, with most seedlings likely recruited from a persistent seed bank. Four of five loci were variable. Most alleles were present in low frequencies, but our large sample sizes allowed detection of significant trends. Expected heterozygosity increased, and allele presence and allele frequencies showed marked shifts following fire. The post-fire seedling cohort contained new alleles to the study and one new allele to the species. Population differentiation between the two study sites did not change. Our study is the first to directly documents genetic changes following fire, a dominant ecological disturbance worldwide, and is also one of the few to consider shifts in a naturally recruiting post-disturbance seedling cohort. We demonstrate the potential of seed banks to restore genetic variation lost between disturbances. Our study demonstrates that rapid genetic change can occur with disturbance and that fire can have positive effects on the genetics of rare species

Exploring population responses to environmental change when there is never enough data: a factor analytic approach

© 2018 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society Temporal variability in the environment drives variation in vital rates, with consequences for population dynamics and life-history evolution. Integral projection models (IPMs) are data-driven structured population models widely used to study population dynamics and life-history evolution in temporally variable environments. However, many datasets have insufficient temporal replication for the environmental drivers of vital rates to be identified with confidence, limiting their use for evaluating population level responses to environmental change. Parameter selection, where the kernel is constructed at each time step by randomly selecting the time-varying parameters from their joint probability distribution, is one approach to including stochasticity in IPMs. We consider a factor analytic (FA) approach for modelling the covariance matrix of time-varying parameters, whereby latent variable(s) describe the covariance among vital rate parameters. This decreases the number of parameters to estimate and, where the covariance is positive, the latent variable can be interpreted as a measure of environmental quality. We demonstrate this using simulation studies and two case studies. The simulation studies suggest the FA approach provides similarly accurate estimates of stochastic population growth rate to estimating an unstructured covariance matrix. We demonstrate how the latent parameter can be perturbed to show how selection on reproductive delays in the monocarp Carduus nutans changes under different environmental conditions. We develop a demographic model of the fire dependent herb Eryngium cuneifolium to show how a putative driver of the variation in environmental quality can be incorporated with the addition of a single parameter. Using perturbation analyses we determine optimal management strategies for this species. This approach estimates fewer parameters than previous approaches and allows novel eco-evolutionary insights. Predictions on population dynamics and life-history evolution under different environmental conditions can be made without necessarily identifying causal factors. Putative environmental drivers can be incorporated with relatively few parameters, allowing for predictions on how populations will respond to changes in the environment

Encapsulación de lacasa en alginato: comparación entre extrusión asistida y no asistida para producción a gran escala

ResumenSe estudió el efecto de la extrusión asistida y no asistida para la producción a gran escala sobre el tamaño, forma y desempeño bioquímico de capsulas de lacasa-alginato. Las capsulas se formularon usando una concentración de alginato al 1.0% y 3.0% (m/v) y se prepararon por un método de extrusión-goteo. Los resultados mostraron que la técnica de extrusión afecta el tamaño de las capsulas y su distribución de tamaño, pero no afecta su forma. La caracterización bioquímica mostro un comportamiento similar entre ambos métodos de extrusión. Sin embargo, las capsulas no asistidas presentaron mayor variabilidad en su actividad enzimática y menor estabilidad en el tiempo. Los resultados muestran que con el método de extrusión, material particulado altamente homogéneo mejora bioprocesos facilitando el control de etapas de temperatura y pH, por lo tanto, un método asistido presenta varias ventajas para la producción de material particulado de lacasa en grandes cantidades. AbstractThe effect of assisted and not-assisted extrusion for large scale production on size, shape and biochemical performance of the laccase-alginate beads was studied. The alginate beads were formulated using 1.0% and 3.0% (w/v) alginate concentrations and were prepared by an extrusion-dripping method. Results showed that the extruding technique affects the beads size and size distribution but not the beads shape. The biochemical characterization showed a similar performance for both extruding methods. However, not-assisted beads presented higher enzymatic activity variability and lower stability in time. Results shown that in extrusion method, bioprocesses are improved by highly homogeneous particulate material easing temperature or pH controlled steps, then, an assisted method presents several benefits for producing laccase particulate material at large quantities

Caracterización morfoagronómica de cacao criollo (Theobroma cacao L.) y su incidencia en la selección de germoplasma promisorio en áreas de presencia natural en El Salvador

En El Salvador el cultivo de cacao, se proyecta como un rubro nuevo de producción agrícola tanto en el ámbito nacional como internacional, constituyendo una oportunidad para el desarrollo económico de productores interesados en este cultivo; por tal motivo se realizó un proceso de prospección de esta especie entre el período de octubre 2013 a junio 2014, iniciando colectas de frutos y material vegetativo de cacao en áreas de presencia natural de la especie. El objetivo fue identificar in situ árboles de cacao para la caracterización morfoagronómica, utilizando descriptores adaptados al catálogo de cultivares de cacao del Perú, CATIE y FEDECACAO, se identificaron zonas donde había presencia de la especie, en los municipios de Caluco, en Sonsonate; el Salitre, Ciudad Delgado y Planes de Renderos, San Salvador; Tenancingo, Cuscatlán; San Pedro Nonualco y Santa María Ostuma, La Paz; Ciudad Victoria, Cabañas y Jucuapa, Usulután. Se caracterizaron 21 árboles; cada uno con sus respectivos atributos cualitativos y cuantitativos como: altura del árbol, forma y tamaño de hojas, frutos, semillas y flores. Cada árbol muestreado, fue georeferenciado, con el fin de ubicarlo y generar el mapa de distribución de los mismos a nivel nacional. Asimismo, en el laboratorio de Química Agrícola de la Facultad de Ciencias Agronómicas, se realizó análisis bromatológicos a muestras de frutos, determinando: grasa, proteína, ceniza, hierro, zinc, humedad total, humedad parcial y materia seca. Como resultados de esta investigación, se inició una colección de cacao con atributos sobresalientes, los mayores porcentajes de grasa lo obtuvieron los árboles codificados como: UES-PDP-19, con 56.4%; UES-SPN-7 con 50.67% y UES-SPN-8 con 50.29%; y los mayores porcentajes de proteína se identificaron para las accesiones, UES-SLT-16, con 27.38%; UES-TNG-18, con 23.36%; y UES-SAL-3 con 21.31%; parámetros que son importantes al momento de hacer programas de producción, mejoramiento genético y en la preservación de este germoplasma

Caracterización morfoagronómica in situ de cacao criollo (Theobroma cacao L.) en lugares de prevalencia natural y su incidencia en la selección de germoplasma promisorio

Con el objetivo de identificar árboles de cacao criollo con alto potencial genético, se inició una búsqueda sistemática de germoplasma de cacao in situ entre los meses de abril de 2017 y julio de 2018, para tal fin se efectuaron giras de prospección y colecta en lugares de prevalencia natural de la especie, en diversas localidades de El Salvador, realizando caracterización morfoagronómica de 47 árboles de cacao localizados en los municipios de San Luis Talpa y San Pedro Nonualco, La Paz; Arcatao, Chalatenango; Tenancingo, Cuscatlán y Ciudad Delgado, San Salvador. Se analizaron atributos cualitativos y cuantitativos de cada árbol y de sus segmentos: hojas, flores, frutos, y semillas. Para la caracterización se utilizaron descriptores morfoagronómicos propuestos por la Cocoa Research Centre at the University of West Indies (Trinidad y Tobago), el Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP) y el Instituto Nacional de Investigaciones Agrícolas (INIA). La interpretación de datos se hizo a través de estadística simple y análisis multivariado utilizando el programa IBM SPSS® Statistics Software V.23. El análisis de componentes principales generó 11 conglomerados que reunieron características de 27 árboles. Se encontraron 10 árboles de cacao con características del tipo “criollo de aroma fino”, con frutos con formas angoleta y cundeamor, el 100% de semillas de color blanco y contenidos de grasa menores al 50%. También sobresalieron cuatro árboles con contenidos mayores al 50% de grasa en las semillas, estas características encontradas demuestran que dichos árboles deberían incluirse en programas de producción, alimentación humana y mejoramiento genético. Finalmente se elaboró un catálogo de los árboles caracterizados con semillas de almendra blanca y los clones denominados Santa Clara

Fine-scale spatial variation in fitness is comparable to disturbance-induced fluctuations in a fire-adapted species

The spatial scale at which demographic performance (e.g., net reproductive output) varies can profoundly influence landscape-level population growth and persistence, and many demographically pertinent processes such as species interactions and resource acquisition vary at fine scales. We compared the magnitude of demographic variation associated with fine-scale heterogeneity (1 ha) fluctuations associated with fire disturbance. We used a spatially explicit model within an IPM modeling framework to evaluate the demographic importance of fine-scale variation. We used a measure of expected lifetime fruit production, EF, that is assumed to be proportional to lifetime fitness. Demographic differences and their effects on EF were assessed in a population of the herbaceous perennial Hypericum cumulicola (~2,600 individuals), within a patch of Florida rosemary scrub (400 × 80 m). We compared demographic variation over fine spatial scales to demographic variation between years across 6 yr after a fire. Values of EF changed by orders of magnitude over <10 m. This variation in fitness over fine spatial scales (<10 m) is commensurate to postfire changes in fitness for this fire-adapted perennial. A life table response experiment indicated that fine-scale spatial variation in vital rates, especially survival, explains as much change in EF as demographic changes caused by time-since-fire, a key driver in this system. Our findings show that environmental changes over a few tens of meters can have ecologically meaningful implications for population growth and extinction

The implications of seasonal climatic effects for managing disturbance dependent populations under a changing climate

The frequency of ecological disturbances, such as fires, is changing due to changing land use and climatic conditions. Disturbance-adapted species may thus require the manipulation of disturbance regimes to persist. However, the effects of changes in other abiotic factors, such as climatic conditions, are frequently disregarded in studies of such systems. Where climatic effects are included, relatively simple approaches that disregard seasonal variation in the effects are typically used. We compare predictions of population persistence using different fire return intervals (FRIs) under recent and predicted future climatic conditions for the rare fire-dependent herb Eryngium cuneifolium. We used functional linear models (FLMs) to estimate the cumulative effect of climatic variables across the annual cycle, allowing the strength and direction of the climatic impacts to differ over the year. We then estimated extinction probabilities and minimum population sizes under past and forecasted future climatic conditions and a range of FRIs. Under forecasted climate change, E. cuneifolium is predicted to persist under a much broader range of FRIs, because increasing temperatures are associated with faster individual growth. Climatic impacts on fecundity do not result in a temporal trend in this vital rate due to antagonistic seasonal effects operating through winter and summer temperatures. These antagonistic seasonal climatic effects highlight the importance of capturing the seasonal dependence of climatic effects when forecasting their future fate. Synthesis. Awareness of the potential effects of climate change on disturbance-adapted species is necessary for developing suitable management strategies for future environmental conditions. However, our results suggest that widely used simple methods for modelling climate impacts, that disregard seasonality in such effects, may produce misleading inferences

Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment

We present a simulation-based study using deep convolutional neural networks (DCNNs) to identify neutrino interaction vertices in the MINERvA passive targets region, and illustrate the application of domain adversarial neural networks (DANNs) in this context. DANNs are designed to be trained in one domain (simulated data) but tested in a second domain (physics data) and utilize unlabeled data from the second domain so that during training only features which are unable to discriminate between the domains are promoted. MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at Fermilab. $A$-dependent cross sections are an important part of the physics program, and these measurements require vertex finding in complicated events. To illustrate the impact of the DANN we used a modified set of simulation in place of physics data during the training of the DANN and then used the label of the modified simulation during the evaluation of the DANN. We find that deep learning based methods offer significant advantages over our prior track-based reconstruction for the task of vertex finding, and that DANNs are able to improve the performance of deep networks by leveraging available unlabeled data and by mitigating network performance degradation rooted in biases in the physics models used for training.Comment: 41 page