A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

O arroz no varejo e os fatores que influenciam o dispêndio das famílias consumidoras

Apesar da idéia consagrada de que arroz é uma commodity e, portanto, pouco passível de diferenciação, há um grande número de produtos, com variação de tipo, classe, padrão, embalagem, marca etc. Observa-se significativa variabilidade nos preços, tanto entre diferentes marcas, fabricantes, lojas, como também para um mesmo produto, em um curto intervalo de tempo. Diante dessas constatações, questiona-se qual o efeito da estratégia de compra de arroz por parte dos consumidores sobre seus dispêndios. Este trabalho utiliza modelos matemáticos para simular o processo de decisão de compra dos consumidores com diferentes perfis de preferência, diante dos produtos nas gôndolas dos supermercados em uma cidade no estado do Rio Grande do Sul e outra em São Paulo.

Response of oriental fruit moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae), eggs to gamma radiation

As insects increase in radiotolerance as they develop and usually several developmental stages of the pest may be present in the fresh shipped commodity, it is important to know the radiation susceptibility of the stages of the target insect before the establishment of ionizing radiation quarantine treatments. This study was performed to determine the radiotolerance of eggs of the oriental fruit moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae), to gamma radiation. This species is considered as one of the most serious worldwide pests for temperate fruits, especially peaches. Eggs (12 h old) were exposed to 0 (control), 25, 35, 50, 75, 100, 125 and 150 Gy of gamma radiation. Surviving larvae were allowed to feed on an artificial diet. Three days after irradiation, it was verified that larvae`s cephalic capsules were significantly affected by gamma radiation, and the estimated mean LD(90) and LD(99) were 66.3 Gy and 125.8 Gy, respectively. Oriental fruit moth eggs revealed to be quite radiosensitive and very low doses as 50 Gy were sufficient to disrupt G. molesta embryogenesis. At 25 Gy, only male adults originated from the surviving larvae and, after mating with untreated fertile females, shown to be sterile. (C) 2010 Elsevier Ltd. All rights reserved.

Changes in isoflavone profiles of soybean treated with gamma irradiation

Soybean is an important Brazilian agricultural commodity that contains a high concentration of isoflavones. Many studies showed that isoflavones are active in the prevention of many human diseases. However, the correct processing techniques used to prepare the soy foodstuffs are important to maintain the active forms. The objective of this study was to evaluate the effect of gamma irradiation on the isoflavone contents of the defatted soybean flour when compared with soybean molasses, a derivative from the soybean food production. After extracting phenolic compounds with methanol aqueous solution (80%), isoflavones were detected by reverse-phase high-performance liquid chromatography/diode-array detector. The radiation doses of 2 and 5 kGy presented a small effect on the isoflavones content of defatted soy flour. Samples irradiated at 50 kGy showed lower isoflavone contents. The observed reduction in the concentration of isoflavones-daidzein, glycitein and genistein-induced by gamma radiation in soy molasses was not significant in defatted soy flour, thus suggesting that isoflavones in defatted soy flour were not eliminated by gamma radiation at rates up to 50 kGy.

The food business environment and the role of China and Brazil building a ""food bridge""

Purpose - The purpose of this paper is to discuss the economic crisis of 2008/2009 and the major impacts on developing nations and food-producing countries Within this macro-environment of food chains, there is concern that food inflation might come back sooner than expected The role of China as one of the major food consumers in the future, and Brazil, as the major food producer, is described as the food bridge, and an agenda of common development of these countries suggested. Design/methodology/approach - This paper reviews literature on muses of food inflation, production shortages, and investigation of programs to solve the problem in the future, it is also based on author`s personal insights and experience of working on this field in the last 15 years, and recent discussions in forums and interviews Findings - The major factors that jointly caused food prices increase in 2007/2008 were population growth, Income distribution, urbanization, dollar devaluations, commodity funds, social programs, production shortages, and bionic`s A list of ten policies is suggested. horizontal expansion of food production, vertical expansion, reduction in transaction costs, in protectionism and other taxes, investment in logistics, technology and better coordination, contracts, new generation of fertilizers and to use the best sources of biofuels. Originality/value - Two major outputs from this paper are the ""food demand model"" that inserts in one model the trends and muses of food inflation and the solutions, and the ""food bridge concept"" that also aligns in one box the imminent major food chain cooperation between China and Brazil

Molecular characterization and fumonisin production by Fusarium verticillioides isolated from corn grains of different geographic origins in Brazil

Gibberella moniliformis is most commonly associated with maize worldwide and produces high levels of fumonisins, some of the most agriculturally important mycotoxins. Studies demonstrate that molecular methods can be helpful for a rapid identification of Fusarium species and their levels of toxin production. The purpose of this research was to apply molecular methods (AFLP, TEF-1 alpha partial gene sequencing and PCR based on MAT alleles) for the identification of Fusarium species isolated from Brazilian corn and to verify if real time RT-PCR technique based on FUM1 and FUM19 genes is appropriated to estimate fumonisins B(1) and B(2) production levels. Among the isolated strains, 96 were identified as Fusarium verricillioides, and four as other Fusarium species. Concordant phylogenies were obtained by AFLP and TEF-1 alpha sequencing, permitting the classification of the different species into distinct clades. Concerning MAT alleles, 70% of the F. verricillioides isolates carried the MAT-1 and 30% MAT-2. A significant correlation was observed between the expression of the genes and toxin production r=0.95 and r=0.79 (correlation of FUM1 with FB(1) and FB(2), respectively, P < 0.0001): r=0.93 and r =0.78 (correlation of FUM19 with FB(1) and FB(2). respectively, P < 0.0001). Molecular methods used in this study were found to be useful for the rapid identification of Fusarium species. The high and significant correlation between FUM1 and FUM19 expression and fumonisins production suggests that real time RT-PCR is suitable for studies considering the influence of abiotic and biotic factors on expression of these genes. This is the first report concerning the expression of fumonisin biosynthetic genes in Fusarium strains isolated from Brazilian agricultural commodity. (c) 2010 Elsevier B.V. All rights reserved.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

A multi-GPU algorithm for large-scale neuronal networks

Large-scale simulations of parts of the brain using detailed neuronal models to improve our understanding of brain functions are becoming a reality with the usage of supercomputers and large clusters. However, the high acquisition and maintenance cost of these computers, including the physical space, air conditioning, and electrical power, limits the number of simulations of this kind that scientists can perform. Modern commodity graphical cards, based on the CUDA platform, contain graphical processing units (GPUs) composed of hundreds of processors that can simultaneously execute thousands of threads and thus constitute a low-cost solution for many high-performance computing applications. In this work, we present a CUDA algorithm that enables the execution, on multiple GPUs, of simulations of large-scale networks composed of biologically realistic Hodgkin-Huxley neurons. The algorithm represents each neuron as a CUDA thread, which solves the set of coupled differential equations that model each neuron. Communication among neurons located in different GPUs is coordinated by the CPU. We obtained speedups of 40 for the simulation of 200k neurons that received random external input and speedups of 9 for a network with 200k neurons and 20M neuronal connections, in a single computer with two graphic boards with two GPUs each, when compared with a modern quad-core CPU. Copyright (C) 2010 John Wiley & Sons, Ltd.