226 research outputs found

    Automatically controlled deficit irrigation of lettuce in “organic potponics”

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    Concerns with water crisis involve all sectors of society and irrigated agriculture remains the main water consumer. This study evaluated an agricultural production system for lettuce cultivation in greenhouse, “organic potponics”, to economize water and manure use, using a Simplified Irrigation Controller (SIC), based on soil matric potential monitoring. Five irrigation volumes were evaluated in pots with 4.8 L, fertilized with 200 g of vermicompost. One of the volumes was controlled with the SIC. The other volumes represented 130, 80, 60 and 33 % of that controlled by the SIC and all treatments received water at the same time. Shoot fresh weight, head diameter and stomatal conductance (gs) increased linearly with irrigation volumes. For shoot dry weight, number of leaves and water use efficiency (WUE), the regression was quadratic with maximum values at 126, 114 and 83 %, respectively. Leaf relative water content did not show variation among treatments and changes in some fluorescence parameters (Reo/RC, Sm, N and φR0) were much more remarkable to drought compared with the FV/ FM ratio, one of the most commonly used stress indicators. The data indicated a tradeoff between WUE and plant growth thus the economic values of water and lettuce should be taken into account to indicate the best SIC irrigation volume. Organic potponics is promising and should be further improved to save on water, labor and fertilizer use

    A PESQUISA DE CLIMA ORGANIZACIONAL COMO INSTRUMENTO PARA CONDUÇÃO DA ORGANIZAÇÃO: O CASO DE UMA INSTITUIÇÃO FINANCEIRA

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    O presente trabalho tem por objetivo demonstrar a importância da pesquisa de clima organizacional como ferramenta para melhorar os resultados de uma organização. Como método de pesquisa foi utilizado o bibliográfico e documental, além da análise de um caso específico desta aplicação em uma instituição financeira. Esta ação permitiu analisar e discutir com base no referencial teórico apropriado a aplicação empírica da pesquisa de clima e sua contribuição para gestão de uma organização. Para tanto, se fez necessário diferenciar a gestão centrada nos processos da gestão centrada nas pessoas, esta última uma fonte importante de vantagem competitiva para a organização. Deste modo, ficou evidente a importância da pesquisa de clima organizacional como um instrumento de leitura da situação atual da organização como um todo, além de suas áreas específicas, o que pode fornecer informações importantes e necessárias para desenvolver e melhorar a organização. Este estudo demonstra como os gestores utilizam a pesquisa de clima para auxiliar em suas tomadas de decisões com relação às melhorias e mudanças para os empregados

    Informative prior distribution applied to linseed for the estimation of genetic parameters using a small sample size

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    O objetivo deste trabalho foi avaliar um procedimento para elicitação de distribuição a priori informativa, comparada à distribuição a priori não informativa, em tamanho amostral reduzido, com uso de 14 caracteres de três genótipos de linhaça (Linum usitatissimum), em sete épocas de semeadura. Os valores dos hiperparâmetros regulam a informatividade da distribuição a priori; portanto, para cada época, foram calculados os hiperparâmetros a serem utilizados na próxima época. As duas distribuições a priori, não informativa e informativa, foram comparadas pelo comprimento dos intervalos de credibilidade e pela variância da distribuição a posteriori. Em geral, quando a distribuição a priori informativa é adotada, os parâmetros genéticos apresentam menor comprimento do intervalo de credibilidade e estimativas mais precisas. O mecanismo de elicitação a priori informativa com uso de informações prévias de programas de melhoramento é eficiente para estimativa de parâmetros genéticos, incluindo herdabilidade e variância genética, mesmo quando o tamanho da amostra é pequeno. Na avaliação genética, o uso da distribuição a priori informativa é melhor do que o da distribuição não informativa para tamanho amostral pequeno. Em geral, os resultados das distribuições a priori informativas indicam que os valores genéticos da primeira época de semeadura são maiores para os seguintes caracteres: comprimento do ciclo, altura da planta, e número de cápsulas não granuladas e de ramos produtivos.The objective of this work was to evaluate a procedure for the elicitation of informative prior distribution, compared with non-informative prior distribution, in a small sample size, using 14 traits of three linseed (Linum usitatissimum) genotypes in seven sowing seasons. The values of the hyperparameters regulate the informativeness of the prior distribution; therefore, for each season, the hyperparameters to be used in the next season were calculated. The two prior distributions, non-informative and informative, were compared by the length of the credible interval and variance of the posterior distribution. In general, when the informative prior distribution is adopted, the genetic parameters present a shorter length of the credible interval and more precise estimates. The mechanism for informative prior elicitation using previous information from breeding programs is efficient for the estimation of genetic parameters, including heritability and genetic variance, even when the sample size is small. In genetic evaluation, the use of informative prior distribution is better than that of non-informative distribution for a small sample size. In general, the results of the informative prior distributions are indicative that the genetic values of the first sowing season are greater for the following traits: cycle length, plant height, and number of non-grained capsules and of productive branches

    Predição genômica com o modelo aditivo-dominante por métodos de redução de dimensionalidade

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    The objective of this work was to evaluate the application of different dimensionality reduction methods in the additive-dominant model and to compare them with the genomic best linear unbiased prediction (G-BLUP) method. The dimensionality reduction methods evaluated were: principal components regression (PCR), partial least squares (PLS), and independent components regression (ICR). A simulated data set composed of 1,000 individuals and 2,000 single-nucleotide polymorphisms was used, being analyzed in four scenarios: two heritability levels x two genetic architectures. To help choose the number of components, the results were evaluated as to additive, dominant, and total genomic information. In general, PCR showed higher accuracy values than the other methods. However, none of the methodologies are able to recover true genomic heritabilities and all of them present biased estimates, under- or overestimating the genomic genetic values. For the simultaneous estimation of the additive and dominance marker effects, the best alternative is to choose the number of components that leads the dominance genomic value to a higher accuracy.O objetivo deste trabalho foi avaliar a aplicação de diferentes métodos de redução de dimensionalidade no modelo aditivo-dominante e compará-los ao método genômico da melhor predição linear não viesada (G-BLUP). Os métodos de redução avaliados foram: regressão via componentes principais (PCR), quadrados mínimos parciais (PLS) e regressão via componentes independentes (ICR). Utilizou-se um conjunto de dados simulados composto por 1.000 indivíduos e 2.000 polimorfismos de nucleotídeo único, analisados em quatro cenários: dois níveis de herdabilidade x duas heranças genéticas. Para auxiliar na escolha do número de componentes, os resultados foram avaliados quanto às informações genômicas aditiva, dominante e total. De modo geral, a PCR apresentou maiores valores de acurácia em comparação aos demais métodos. No entanto, nenhuma das metodologias consegue capturar as herdabilidades genômicas reais e todas apresentam estimativas viesadas, tendo subestimado ou superestimado os valores genéticos genômicos. Para a estimação simultânea dos efeitos de marcadores aditivos e devidos à dominância, a melhor alternativa é a escolha do número de componentes que conduz o valor genômico devido à dominância à maior acurácia

    Triple categorical regression for genomic selection: application to cassava breeding

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    Genome-wide selection (GWS) is currently a technique of great importance in plant breeding, since it improves efficiency of genetic evaluations by increasing genetic gains. The process is based on genomic estimated breeding values (GEBVs) obtained through phenotypic and dense marker genomic information. In this context, GEBVs of N individuals are calculated through appropriate models, which estimate the effect of each marker on phenotypes, allowing the early identification of genetically superior individuals. However, GWS leads to statistical challenges, due to high dimensionality and multicollinearity problems. These challenges require the use of statistical methods to approach the regularization of the estimation process. Therefore, we aimed to propose a method denominated as triple categorical regression (TCR) and compare it with the genomic best linear unbiased predictor (G-BLUP) and Bayesian least absolute shrinkage and selection operator (BLASSO) methods that have been widely applied to GWS. The methods were evaluated in simulated populations considering four different scenarios. Additionally, a modification of the G-BLUP method was proposed based on the TCR-estimated (TCR/G-BLUP) results. All methods were applied to real data of cassava (Manihot esculenta) with to increase efficiency of a current breeding program. The methods were compared through independent validation and efficiency measures, such as prediction accuracy, bias, and recovered genomic heritability. The TCR method was suitable to estimate variance components and heritability, and the TCR/G-BLUP method provided efficient GEBV predictions. Thus, the proposed methods provide new insights for GWS

    New insights into genomic selection through population-based non-parametric prediction methods

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    Genome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS are based on random regression or dimensionality reduction methods. In this study a new non-parametric method, called Delta-p was proposed, which was then compared to the Genomic Best Linear Unbiased Predictor (G-BLUP) method. Furthermore, a new selection index combining the genetic values obtained by the G-BLUP and Delta-p, named Delta-p/G-BLUP methods, was proposed. The efficiency of the proposed methods was evaluated through both simulation and real studies. The simulated data consisted of eight scenarios comprising a combination of two levels of heritability, two genetic architectures and two dominance status (absence and complete dominance). Each scenario was simulated ten times. All methods were applied to a real dataset of Asian rice (Oryza sativa) aiming to increase the efficiency of a current breeding program. The methods were compared as regards accuracy of prediction (simulation data) or predictive ability (real dataset), bias and recovery of the true genomic heritability. The results indicated that the proposed Delta-p/G-BLUP index outperformed the other methods in both prediction accuracy and predictive ability

    Administration Hosts Regional Economic Summit to Accelerate Recovery and Create Jobs in Northeast MA

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    <p><b>Posterior density for the multi-trait multi-environment model above (left: NUpE and right: NUtE) and for each of the single-trait multi-environment models below (left: NUpE and right: NUtE)</b>. The solid line represents the posterior density for the HN level, while the dotted line represents the posterior density for the LN level.</p

    Health Complexity Assessment in Primary Care : a validity and feasibility study of the INTERMED tool

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    Acknowledgments We would like to thank Professor Craig Ramsay for his comments on this work during an international meeting held at the Health Services Research Unit of the University of Aberdeen in July 2019.Peer reviewedPublisher PD

    Cytotoxicity, inflammation, biomineralization, and immunoexpression of IL-1β and TNF-α promoted by a new bioceramic cement

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    Aim: To evaluate the cytotoxicity, biocompatibility and mineralization capacity of BIO-C PULPO, and MTA. Methodology: L929 fibroblasts were cultured and MTT assay was used to determine the material cytotoxicity on 6, 24, and 48 h. A total of 30 male rats (Wistar) aged between 4 and 6 months, weighing between 250 and 300 g were used. Polyethylene tubes containing BIO-C PULPO, MTA, and empty tubes were implanted into dorsal connective tissue. After the experimental periods (7, 15, 30, 60, and 90 days) the tubes were histologically analyzed using hematoxylin-eosin (H&amp;E), immunolabeling of IL-1β and TNF-α, and von Kossa staining, or without staining for polarized light analysis. The average number of inflammatory cells was quantified; the mineralization assessment was determined by the area marked in μm2 and semiquantitative immunolabeling analyses of IL-1β and TNF-α were performed. Then, data underwent statistical analysis with a 5% significance level. Results: It was observed that BIO-C PULPO and MTA presented cytocompatibility at 6, 24, and 48 similar or higher than control for all evaluated period. On periods 7 and 15 days, BIO-C PULPO was the material with the highest number of inflammatory cells (p&lt;0.05). On periods 30, 60, and 90 days, BIO-C PULPO and MTA presented similar inflammatory reactions (p&gt;0.05). No statistical differences were found between Control, BIO-C PULPO, and MTA for immunolabeling of IL-1β and TNF-α in the different periods of analysis (p&lt;0.05). Positive von Kossa staining and birefringent structures under polarized light were observed in all analyzed periods in contact with both materials, but larger mineralization area was found with BIO-C PULPO on day 90 (p&lt;0.05). Conclusion: BIO-C PULPO was biocompatible and induced mineralization similar to MTA
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