A new classification of foods based on the extent and purpose of their processing

This paper describes a new food classification which assigns foodstuffs according to the extent and purpose of the industrial processing applied to them. Three main groups are defined: unprocessed or minimally processed foods (group 1), processed culinary and food industry ingredients (group 2), and ultra-processed food products (group 3). The use of this classification is illustrated by applying it to data collected in the Brazilian Household Budget Survey which was conducted in 2002/2003 through a probabilistic sample of 48,470 Brazilian households. The average daily food availability was 1,792 kcal/person being 42.5% from group 1 (mostly rice and beans and meat and milk), 37.5% from group 2 (mostly vegetable oils, sugar, and flours), and 20% from group 3 (mostly breads, biscuits, sweets, soft drinks, and sausages). The share of group 3 foods increased with income, and represented almost one third of all calories in higher income households. The impact of the replacement of group 1 foods and group 2 ingredients by group 3 products on the overall quality of the diet, eating patterns and health is discussed.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Eucalyptus sp seedling response to potassium fertilization and soil water

A considerable portion of Brazil's commercial eucalypt plantations is located in areas Subjected to periods of water deficit and grown in soils with low natural fertility, particularly poor In potassium. Potassium is influential in controlling water relations of plants. The objective of this study was to verify the influence of potassium fertilization and soil water potential (psi(w)) oil the dry matter production and oil water relations Of eucalypt seedlings grown under greenhouse conditions. the experimental units were arranged in 4x4x2 randomized blocks factorial design, as follow: four species of Eucalyptus (Eucalyptus grandis, Eucalyptus urophylla, Eucalyptus camaldulensis and hybrid Eucalyptus grandis x Eucalyptus urophylla), four dosages of K (0, 50, 100 and 200 mg dm(-3)) and two soil water potentials (-0.01 M Pa and -0.1 M Pa). Plastic containers with 15 cm diameter and 18 cm height, with Styrofoam base, containing 3.0 dm(3) of soil and two plants per container were used. Soil water potential was kept at -0.01 MPa for 40 days after seeding. Afterward, the experimental units were divided into two groups: in one group the potential was kept at 0.01 MPa, and in the other one, at -0.10 MPa. Sol I water potential was control led gravimetrically twice a day with water replacement until the desired potential was reestablished. A week before harvesting, the leaf water potential (psi), the photosynthetic rate (A), the stomatal conductance (gs) and the transpiration rate were evaluated. The last week before harvesting, the mass of the containers was recorded daily before watering to determine the consumption of water by the plants. After harvesting, total dry matter and leaf area were evaluated. the data were Submitted to analysis of variance, to Tukey's tests and regression analyses. The application of K influenced A, gs and the transpiration rate. Plants deficient in K showed lower A and higher Us and transpiration rates. There were no statistical differences in A, gs and transpiration rates ill plants with and Without water deficit. The addition of K reduced the consumption of water per unit of leaf area and, in general, plants submitted to water deficit presented a lower consumption of water.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

LIPSCHITZ CLASSIFICATION OF FUNCTIONS ON A HOLDER TRIANGLE

The problem of semialgebraic Lipschitz classification of quasihomogeneous polynomials on a Holder triangle is studied. For this problem, the ""moduli"" are described completely in certain combinatorial terms.

Effect of sugarcane harvesting systems on soil carbon stocks in Brazil: an examination of existing data

Agricultural management practices that promote net carbon (C) accumulation in the soil have been considered as an important potential mitigation option to combat global warming. The change in the sugarcane harvesting system, to one which incorporates C into the soil from crop residues, is the focus of this work. The main objective was to assess and discuss the changes in soil organic C stocks caused by the conversion of burnt to unburnt sugarcane harvesting systems in Brazil, when considering the main soils and climates associated with this crop. For this purpose, a dataset was obtained from a literature review of soils under sugarcane in Brazil. Although not necessarily from experimental studies, only paired comparisons were examined, and for each site the dominant soil type, topography and climate were similar. The results show a mean annual C accumulation rate of 1.5 Mg ha-1 year-1 for the surface to 30-cm depth (0.73 and 2.04 Mg ha-1 year-1 for sandy and clay soils, respectively) caused by the conversion from a burnt to an unburnt sugarcane harvesting system. The findings suggest that soil should be included in future studies related to life cycle assessment and C footprint of Brazilian sugarcane ethanol.

Soil carbon stocks under no-tillage mulch-based cropping systems in the Brazilian Cerrado: An on-farm synchronic assessment

No-tillage mulch-based (NTM) cropping systems have been widely adopted by farmers in the Brazilian savanna region (Cerrado biome). We hypothesized that this new type of management should have a profound impact on soil organic carbon (SOC) at regional scale and consequently on climate change mitigation. The objective of this study was thus to quantify the SOC storage potential of NTM in the oxisols of the Cerrado using a synchronic approach that is based on a chronosequence of fields of different years under NTM. The study consisted of three phases: (1) a farm/cropping system survey to identify the main types of NTM systems to be chosen for the chronosequence; (2) a field survey to identify a homogeneous set of situations for the chronosequence and (3) the characterization of the chronosequence to assess the SOC storage potential. The main NTM system practiced by farmers is an annual succession of soybean (Glycine max)or maize (Zea mays) with another cereal crop. This cropping system covers 54% of the total cultivated area in the region. At the regional level, soil organic C concentrations from NTM fields were closely correlated with clay + silt content of the soil (r(2) = 0.64). No significant correlation was observed (r(2) = 0.07), however, between these two variables when we only considered the fields with a clay + silt content in the 500-700 g kg(-1) range. The final chronosequence of NTM fields was therefore based on a subsample of eight fields, within this textural range. The SOC stocks in the 0-30 cm topsoil layer of these selected fields varied between 4.2 and 6.7 kg C m(-2) and increased on average (r(2) = 0.97) with 0.19 kg C m(-2) year(-1). After 12 years of NTM management, SOC stocks were no longer significantly different from the stocks under natural Cerrado vegetation (p < 0.05), whereas a 23-year-old conventionally tilled and cropped field showed SOC stocks that were about 30% below this level. Confirming our hypotheses, this study clearly illustrated the high potential of NTM systems in increasing SOC storage under tropical conditions, and how a synchronic approach may be used to assess efficiently such modification on farmers` fields, identifying and excluding non desirable sources of heterogeneity (management, soils and climate). (C) 2010 Elsevier B.V. All rights reserved.

Do plant species influence soil CO(2) and N(2)O fluxes in a diverse tropical forest?

To test whether plant species influence greenhouse gas production in diverse ecosystems, we measured wet season soil CO(2) and N(2)O fluxes close to similar to 300 large (>35 cm in diameter at breast height (DBH)) trees of 15 species at three clay-rich forest sites in central Amazonia. We found that soil CO(2) fluxes were 38% higher near large trees than at control sites >10 m away from any tree (P < 0.0001). After adjusting for large tree presence, a multiple linear regression of soil temperature, bulk density, and liana DBH explained 19% of remaining CO(2) flux variability. Soil N(2)O fluxes adjacent to Caryocar villosum, Lecythis lurida, Schefflera morototoni, and Manilkara huberi were 84%-196% greater than Erisma uncinatum and Vochysia maxima, both Vochysiaceae. Tree species identity was the most important explanatory factor for N(2)O fluxes, accounting for more than twice the N(2)O flux variability as all other factors combined. Two observations suggest a mechanism for this finding: (1) sugar addition increased N(2)O fluxes near C. villosum twice as much (P < 0.05) as near Vochysiaceae and (2) species mean N(2)O fluxes were strongly negatively correlated with tree growth rate (P = 0.002). These observations imply that through enhanced belowground carbon allocation liana and tree species can stimulate soil CO(2) and N(2)O fluxes (by enhancing denitrification when carbon limits microbial metabolism). Alternatively, low N(2)O fluxes potentially result from strong competition of tree species with microbes for nutrients. Species-specific patterns in CO(2) and N(2)O fluxes demonstrate that plant species can influence soil biogeochemical processes in a diverse tropical forest.

Changes in soil organic carbon storage under different agricultural management systems in the Southwest Amazon Region of Brazil

The Cerrado and Amazon regions of Brazil are probably the largest agricultural frontier of the world, and Could be a sink or source for C depending on the net effect of land use change and subsequent management on soil organic C pools. We evaluated the effects of agricultural management systems on soil organic C (SOC) stocks in the Brazilian states of Rondonia and Mato Grosso, and derived regional specific factors for soil C stock change associated with different management systems. We used 50 observations (data points) in this study, including 42 dealing with annual cropping practices and 8 dealing with perennial cropping, and analyzed the data in linear mixed-effect models. No tillage (NT) systems in Cerrado areas increased SOC Storage by 1.08 +/- 0.06 relative to SOC stocks under native conditions, while SOC storage increased by a modest factor of 1.01 +/- 0.17 in Cerradao and Amazon Forest conditions. Full tillage (FT) had negative effect on SOC storage relative to NT, decreasing SOC stocks by a factor of 0.94 +/- 0.04. but did not significantly reduce SOC stocks relative to native levels when adopted in the Cerrado region. Perennial cropping had a minimal impact on SOC stocks, estimated at a factor Value of 0.98 +/- 0.14, suggesting these systems maintain about 98% of the SOC stock found under native vegetation. The results Suggest that NT adoption may be increasing SOC with land use change from native vegetation to cropland management in the Cerrado region of Brazil. (C) 2009 Elsevier B.V. All rights reserved.

Soil Carbon Turnover Measurement by Physical Fractionation at a Forest-to-Pasture Chronosequence in the Brazilian Amazon

The effect of conversion from forest-to-pasture upon soil carbon stocks has been intensively discussed, but few studies focus on how this land-use change affects carbon (C) distribution across soil fractions in the Amazon basin. We investigated this in the 20 cm depth along a chronosequence of sites from native forest to three successively older pastures. We performed a physicochemical fractionation of bulk soil samples to better understand the mechanisms by which soil C is stabilized and evaluate the contribution of each C fraction to total soil C. Additionally, we used a two-pool model to estimate the mean residence time (MRT) for the slow and active pool C in each fraction. Soil C increased with conversion from forest-to-pasture in the particulate organic matter (> 250 mu m), microaggregate (53-250 mu m), and d-clay (< 2 mu m) fractions. The microaggregate comprised the highest soil C content after the conversion from forest-to-pasture. The C content of the d-silt fraction decreased with time since conversion to pasture. Forest-derived C remained in all fractions with the highest concentration in the finest fractions, with the largest proportion of forest-derived soil C associated with clay minerals. Results from this work indicate that microaggregate formation is sensitive to changes in management and might serve as an indicator for management-induced soil carbon changes, and the soil C changes in the fractions are dependent on soil texture.

Near infrared spectroscopy for soil bulk density assessment

P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

Total soil carbon and chemical attributes under different land uses in the Brazilian savanna

Total soil carbon and chemical attributes under different land uses in the Brazilian savanna. The Brazilian savanna region (Cerrado) is one of the largest cultivated areas of the world. The different land uses in the region can effectively change the quantities of soil organic matter and the cycling of nutrients. I-lie objective of this study was to evaluate the effect of different land use management systems on the relationship between soil organic carbon and the soil chemical attributes of a Red Latosol (Oxisol) under Cerrado in Rio Verde (Goias state). The treatments studied were native vegetation (cerrado), low-productivity pasture, conventional tillage with soybean, and no-tillage with soybean and maize. The smallest values for pH, available P, K, Ca and Mg were observed for the Cerradao treatment, even if the relatively high C levels increased the potential soil cation exchange capacity. The pasture, conventional tillage and no-tillage treatments showed higher K, Ca, Mg, available 13, and S concentrations in the soil. In the areas where soil tillage did not take place and lime and fertilizers were applied superficially, the stratification of the soil organic carbon provides the retention of the elements near to the surface, with significance correlations with the soil chemicals attributes.

Soil organic carbon and fertility interactions affected by a tillage chronosequence in a Brazilian Oxisol

No-till (NT) adoption is an essential tool for development of sustainable agricultural systems, and how NT affects the soil organic C (SOC) dynamics is a key component of these systems. The effect of a plow tillage (PT) and NT age chronosequence on SOC concentration and interactions with soil fertility were assessed in a variable charge Oxisol, located in the South Center quadrant of Parana State, Brazil (50 degrees 23`W and 24 degrees 36`S). The chronosequence consisted of the following six sites: (i) native field (NF); (ii) PT of the native field (PNF-1) involving conversion of natural vegetation to cropland; (iii) NT for 10 years (NT-10); (iv) NT for 20 years (NT-20); (v) NT for 22 years (NT-22); and (vi) conventional tillage for 22 years (CT-22) involving PT with one disking after summer harvest and one after winter harvest to 20 cm depth plus two harrow disking. Soil samples were collected from five depths (0-2.5; 2.5-5; 5-10; 10-20; and 20-40 cm) and SOC, pH (in H(2)O and KCl), Delta pH, potential acidity, exchangeable bases, and cation exchangeable capacity (CEC) were measured. An increase in SOC concentration positively affected the pH, the negative charge and the CEC and negatively impacted potential acidity. Regression analyses indicated a close relationship between the SOC concentration and other parameters measured in this study. The regression fitted between SOC concentration and CEC showed a close relationship. There was an increase in negative charge and CEC with increase in SOC concentration: CEC increased by 0.37 cmol(c) kg(-1) for every g of C kg(-1) soil. The ratio of ECEC:SOC was 0.23 cmol(c) kg(-1) for NF and increased to 0.49 cmol(c) kg(-1) for NT-22. The rates of P and K for 0-10 cm depth increased by 9.66 kg ha(-1) yr(-1) and 17.93 kg ha(-1) yr(-1), respectively, with NF as a base line. The data presented support the conclusion that long-term NT is a useful strategy for improving fertility of soils with variable charge. (C) 2008 Elsevier B.V. All rights reserved.

Simulation of Soil Carbon Dynamics under Sugarcane with the CENTURY Model

Currently there is a trend for the expansion of the area cropped with sugarcane (Saccharum officinarum L.), driven by an increase in the world demand for biofuels, due to economical, environmental, and geopolitical issues. Although sugarcane is traditionally harvested by burning dried leaves and tops, the unburned, mechanized harvest has been progressively adopted. The use of process based models is useful in understanding the effects of plant litter in soil C dynamics. The objective of this work was to use the CENTURY model in evaluating the effect of sugarcane residue management in the temporal dynamics of soil C. The approach taken in this work was to parameterize the CENTURY model for the sugarcane crop, to simulate the temporal dynamics of soil C, validating the model through field experiment data, and finally to make predictions in the long term regarding soil C. The main focus of this work was the comparison of soil C stocks between the burned and unburned litter management systems, but the effect of mineral fertilizer and organic residue applications were also evaluated. The simulations were performed with data from experiments with different durations, from 1 to 60 yr, in Goiana and Timbauba, Pernambuco, and Pradopolis, Sao Paulo, all in Brazil; and Mount Edgecombe, Kwazulu-Natal, South Africa. It was possible to simulate the temporal dynamics of soil C (R(2) = 0.89). The predictions made with the model revealed that there is, in the long term, a trend for higher soil C stocks with the unburned management. This increase is conditioned by factors such as climate, soil texture, time of adoption of the unburned system, and N fertilizer management.