Stage of detection and number of sprays for controlling soybean rust

During winter extension meetings, three of the most common questions asked about Asian soybean rust were: when will soybean rust show up in the northern United States; how early should a spray application be made; and how many sprays would be needed. It is incorrect that once soybean rust outbreaks occur in coastal regions of the Gulf of Mexico, the disease can be airborne to Iowa within 2 to 3 days and defoliate soybeans in a week or two if no chemical is applied immediately after the spores arrive. Another recent question is whether spraying at the vegetative growth stage is needed. To address all these questions, we need to know the most likely stage of soybean rust when it appears in the United States

Update: Outbreak prediction for Asian soybean rust in Iowa

Last year, Asian soybean rust moved slowly and did not show up in Iowa. Because of the dry weather conditions that prevailed during the 2005 growing season, one cannot draw a meaningful conclusion. Therefore, soybean rust remains a major concern for soybean producers in the northern regions. A common question asked this winter has been: what is the risk of a soybean rust outbreak in the upcoming season

Path Integral Approach to Strongly Nonlinear Composite

We study strongly nonlinear disordered media using a functional method. We solve exactly the problem of a nonlinear impurity in a linear host and we obtain a Bruggeman-like formula for the effective nonlinear susceptibility. This formula reduces to the usual Bruggeman effective medium approximation in the linear case and has the following features: (i) It reproduces the weak contrast expansion to the second order and (ii) the effective medium exponent near the percolation threshold are $s=1$, $t=1+\kappa$, where $\kappa$ is the nonlinearity exponent. Finally, we give analytical expressions for previously numerically calculated quantities.Comment: 4 pages, 1 figure, to appear in Phys. Rev.

On the stationary stochastic response of an order-constrained inventory system

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordWe investigate the stochastic response of a base stock inventory system where the order quantity is either upper- or lower-constrained. This system can represent many real-world settings: forbidden returns, minimum order quantities, and capacity constraints, for example. We show that this problem can be translated into a stopping time problem where the distributions of orders and inventory can be represented by a countably infinite mixture of truncated and convoluted demand distributions. This result can be extended to the cases of arbitrary lead time and auto-correlated demand. A state space algorithm is developed to approximate the first-and second-order moments of the order quantity and inventory level. Via a numerical analysis, we investigate the performance of the approximation, as well as the operational and economic impact of the order constraint. In particular, the constraint impacts order and inventory variances via different combinations of the mixture and truncation effects. We show how tuning the constraint can improve the operational and financial performance of the inventory system by acting as a smoothing mechanism.Spanish State Research Agency (Agencia Estatal de Investigación

Exploring the nonlinear dynamics of the lost-sales order-up-to policy

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this recordWith most inventory theory investigating linear models, the dynamics of nonlinear inventory systems is not well understood. We explore the dynamics of the order-up- to policy under lost-sales for the case of i.i.d. normally distributed demand and unit lead times. We consider the ideal minimum mean squared error forecast and two alternative scenarios: partial demand observation and dynamic demand forecasting, providing a broad understanding of the operational performance of lost-sales sys- tems. In each scenario, we obtain analytical expressions for the order, inventory, and satis ed demand distributions. This allows us to quantify the Bullwhip and inven- tory variance ampli cation ratios as well as the ll rate and the inventory cover. We show the lost sales nonlinearity induces complex behaviors in inventory systems. Interestingly, lost sales smooth supply chain dynamics, signi cantly a ecting the trade-o between service level and average inventory holding. We also reveal the inventory downsides of demand censoring and the production damages induced by dynamic forecasts. We identify a key parameter, the relative safety margin, that characterizes the performance of lost-sales systems. We nish by o ering some pre- scriptive results for the optimal safety stock and capacity level in both a retail and a manufacturing lost-sales setting

Models and applications for risk assessment and prediction of Asian soybean rust epidemics.

Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed

Models and applications for risk assessment and prediction of Asian soybean rust epidemics

Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhiziSyd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed

Soybean rust update - May 2, 2005

Based on our experience with corn rusts, we suspected that disease outbreaks occurring in Florida and southern Texas in March and April would be an indication that rust spores would likely be available to move to Gulf Coast states. The earlier an outbreak occurs in the South, the higher the risk for northern soybean production regions. Since the first detection in kudzu in central Florida in late February, no outbreak was observed in the last two months. The first detection outside Florida on volunteer soybeans was confirmed in southern Georgia

Iniciativas de manejo comunitário e valoração dos recursos naturais em assentamentos rurais no Sudeste Paraense.

Analisa os conflitos sociais pelo acesso aos recursos em áreas remanescentes de mangabeira no Nordeste e Norte do Brasil A pesquisa foi realizada em sete estados do Nordeste (BA, SE, AL, PE, PB, RN) e do Norte (PA). Outros temas como acesso aos recursos e gestão coletiva de recursos naturais também foram abordados

StarHorse: A Bayesian tool for determining stellar masses, ages, distances, and extinctions for field stars

Understanding the formation and evolution of our Galaxy requires accurate distances, ages and chemistry for large populations of field stars. Here we present several updates to our spectro-photometric distance code, that can now also be used to estimate ages, masses, and extinctions for individual stars. Given a set of measured spectro-photometric parameters, we calculate the posterior probability distribution over a given grid of stellar evolutionary models, using flexible Galactic stellar-population priors. The code (called {\tt StarHorse}) can acommodate different observational datasets, prior options, partially missing data, and the inclusion of parallax information into the estimated probabilities. We validate the code using a variety of simulated stars as well as real stars with parameters determined from asteroseismology, eclipsing binaries, and isochrone fits to star clusters. Our main goal in this validation process is to test the applicability of the code to field stars with known {\it Gaia}-like parallaxes. The typical internal precision (obtained from realistic simulations of an APOGEE+Gaia-like sample) are $\simeq 8\%$ in distance, $\simeq 20\%$ in age,$\simeq 6\$ in mass, and $\simeq 0.04$ mag in $A_V$. The median external precision (derived from comparisons with earlier work for real stars) varies with the sample used, but lies in the range of $\simeq [0,2]\%$ for distances, $\simeq [12,31]\%$ for ages, $\simeq [4,12]\%$ for masses, and $\simeq 0.07$ mag for $A_V$. We provide StarHorse distances and extinctions for the APOGEE DR14, RAVE DR5, GES DR3 and GALAH DR1 catalogues.Comment: 21 pages, 12 figures, accepte