EVALUATION OF FIVE SUGAR CANE PLANTERS

Brazil is the world biggest producer of sugar cane with an area of 7x10(6) hectares. Mainly the system used for planting is the semi-mechanized one, which consists in opening the furrows with a machine, manually allocating the fractioned stalks and then covering the furrows done by the machines. The great amount of human labor used in the semi-mechanized system is becoming harder to find and also more expensive, indicating the need of a fully mechanized operation. Currently in Brazil these agriculture machines industries offers six different types of fully mechanized sugar cane planters (two types of whole stalks for planting and four using mechanized harvested stalks known as billets). All of them plant in two furrows simultaneously in 1.5 m row spacing. This study analyzed five different machines and the following variables: Working Speed (km h(-1)); Effective Capacity (ha h(-1)), Drawbar Force (kgf), Draw Bar Power (in HP), Fuel Consumption (L h(-1)) and Costs (US$ ha(-1)) comparing them with the semi-mechanized system. This research also characterized the stalks for planting as viable gems number (%), non viable gems number (%) and billet length (m). And lastly the mechanized planting system is cheaper than the conventional one and none of the machines has an adequate mechanism for placing the right amount of sugar cane seed.

PROPOSAL OF A PERFORMANCE MEASURING SYSTEM APPLIED TO AGRICULTURAL MECHANIZATION

The leaders` organizations of several different sectors have as characteristic to measure their own performance in a systematic way. However, this concept is still unusual in agricultural enterprises, including the mechanization sector. Mechanization has an important role on the production costs and to know its performance is a key factor for the agricultural enterprise success. This work was generated by the importance that measurement of performance has for the management and the mechanization impact on the production costs. Its aim is to propose an integrated performance measurement system to give support to agricultural management. The methodology was divided in two steps: adjustment of a conceptual model based on Balanced Score Card - BSC; application of the model in a study case at sugar cane mill. The adjustment and the application of the conceptual model allowed to obtain the performance index in a systematic way, that are associated to: costs and deadline ( traditionally used); control and improvement on the quality of operations and support process; environmental preservation; safety; health; employees satisfaction; development of information systems. The adjusted model helped the development of the performance measurement system for the mechanized management systems and the index allows an integrated view of the enterprise, related to its strategic objectives.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Changes in the genetic structure of Bacteria and microbial activity in an agricultural soil amended with tannery sludge

The application of tannery sludge to soils is a form of recycling; however, few studies have examined the impacts of this practice on soil microbial properties. We studied effects of two applications (2006 and 2007) of tannery sludge (with a low chromium content) on the structure of the bacterial community and on the microbial activity of soils. We fertilized an agricultural area in Rolandia, Parana state, Brazil with different doses of sludge based on total N content, which ranged from 0 to 1200 kg N ha(-1). Sludge remained on the soil surface for three months before being plowed. Soils were sampled seven times during the experiment. Bacterial community structure, assessed by denaturing gradient gel electrophoresis (DGGE), was modified by the application of tannery sludge. Soon after the first application, there was clear separation between the bacterial communities in different treatments, such that each dose of sludge was associated with a specific community. These differences remained until 300 days after application and also after the second sludge application, but 666 days after the beginning of the experiment no differences were found in the bacterial communities of the lowest doses and the control. The principal response curve (PRC) analysis showed that the first sludge application strongly stimulated biological activity even 300 days after application. The second application also stimulated activity, but at a lower magnitude and for a shorter time, given that 260 days after the second application there was no difference in biological activity among treatments. PRC also showed that the properties most influenced by the application of tannery sludge were enzymatic activities related to N cycling (asparaginase and urease). The redundancy analysis (RDA) showed that tannery sludge`s influence on microbial activity is mainly related to increases in inorganic N and soil pH. Results showed that changes in the structure of the bacterial community in the studied soils were directly related to changes of their biological activity. (C) 2010 Elsevier Ltd. All rights reserved.

Production and characteristics comparison of crude beta-glucosidases produced by microorganisms Thermoascus aurantiacus e Aureobasidium pullulans in agricultural wastes

The purified beta-glucosidase of Aureobasidium pullulans ER-16 is one of more thermostable enzyme reported to date. Considering the unfeasibility of using purified enzyme for industrial application, it was interesting to analyze this property for the crude enzyme. Thermophilic fungus Thermoascus aurantiacus CBMAI-756 and mesophilic A. pullulans ER-16 were cultivated in different hemicellulosic materials on solid-state cultivation for beta-glucosidase production. Wheat bran was most appropriate for beta-glucosidase production by both microorganisms. T. aurantiacus exhibited maximum enzyme production (7.0 U/ml or 70 U/g) at 48-72 h and A. pullulans a maximum (1.3 U/ml or 13 U/g) at 120 h. Maximum activities were at 75 degrees C with optimum pH at 4.5 and 4.0, for T aurantiacus and A. pullulans, respectively. A. pullulans`s beta-glucosidase was more pH stable (4.5-10.0 against 4.5-8.0) and more thermostable (90% after 1 h at 75 degrees C against 85% after 1 h at 70 degrees C) than the enzyme from the thermophilic T. aurantiacus. The t((1/2)) at 80 degrees C were 50 and 12.5 min for A. pullulans and T. aurantiascus, respectively. These data confirm the high thermostability of crude beta-glucosidase from A. pullulans. Both beta-glucosidases were strongly inhibited by glucose, but ethanol significantly increased the activity of the enzyme from T. aurantiacus. (C) 2008 Elsevier Inc. All rights reserved.

Reshaping the global agricultural landscape: perspectives from Brazil

This article highlights the main changes observed in Brazilian agriculture and analyzes the connections of the observed changes in global agriculture. My approach to the analysis focuses the main drivers of changes, where institutions play a central role. Three driving forces are are considered: first, the effects of global demand for food, fiber, and energy; second, the sustainability debate; and third, the bio-energy paradigm. Each driver presents both local as well as global effects. The article does not emphasize the impact changes in Brazil had on the global agricultural landscape but argues that the impacts run from local and global changes, which cannot be discussed separately.

Customer Perception about Loyalty Programs in Agricultural Market: a case study

This study discusses the use of loyalty programs and Customer perception in, agricultural market. The theoretical review includes relationship marketing, its objectives, dimensions and instruments, and loyalty programs. The method for the empirical part consisted on qualitative research, through a case study conducted at one of the largest crop protection chemical companies in Brazil. The case is representative once this company was pioneer in its segment in adopting the customer relationship management. (CRM) approach to-their clients: It has been a consensus that customer relationship is a tool to amplify the Customer share. This.,is so, due the. increasing competition generated by the entrance of generic products and the retaliation actions adopted by the multinational groups. The case study includes a market overview, a description of the company, its loyalty program, the image of the program from the customer`s perspective, and the main results acquired with the CRM program. The Study also presents some recommendations for-companies that are pursuing strategies to. increase their customer share through loyalty programs.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Chronic Diseases: Chronic Diseases and Development 2 Health, agricultural, and economic effects of adoption of healthy diet recommendations

Transition to diets that are high in saturated fat and sugar has caused a global public health concern as the pattern of food consumption is a mayor modifiable risk factor for chronic non-communicable diseases Although agri food systems are intimately associated with this transition, agriculture and health sectors are largely disconnected in their priorities policy, and analysis with neither side considering the complex inter relation between agri trade patterns of food consumption health, and development We show the importance of connection of these perspectives through estimation of the effect of adopting a healthy diet on population health, agricultural production trade the economy and livelihoods, with a computable general equilibrium approach On the basis of case studies from the UK and Brazil we suggest that benefits of a healthy diet policy will vary substantially between different populations, not only because of population dietary intake but also because of agricultural production trade and other economic factors

Sanitation assessment of wastewater treated by stabilization ponds for potential reuse in agricultural irrigation sanitation assessment

Wastewater reuse has become an important alternative to agricultural irrigation; on the other hand, it poses concern with regard to public health. Total coliform and Escherichia coli concentration, presence of helminth eggs and Salmonella, and physical-chemical parameters were evaluated in raw and treated wastewater. Chemical and biochemical oxygen demand removal efficiency was 74.6 and 77.9%, respectively. As for organic nitrogen, total phosphorus, and total suspended solids, total efficiency removal was 17.4, 12.5, and 32.9%, respectively. The average density of total coliforms and E. coli was 3.5 x 10(9) and 1.8 x 10(8) MPN/100 mL and 1.1 x 10(7) MPN/100 mL and 3.9 x 10(5) MPN/100 mL for raw and treated wastewater, respectively. Ascaris eggs were observed in 80.8% of the samples collected, and viable eggs in 42.3% of the samples. Salmonella was detected in 36.4% of the samples. The values observed in treated wastewater did not show the adequate bacteriological quality, as recommended by World Health Organization (Geneva, Switzerland). Therefore, additional measures should be taken to achieve an improved microbiological and parasitological quality.

Extended time weather forecasts contributes to agricultural productivity estimates

Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.