Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

Competição intra-específica entre Amaranthus hybridus L. e Amaranthus viridis L.

Ensaios de competição intra-específica foram conduzidos sobre Amaranthus viridis L. e A. hybridus L., a última espécie com dois biótipos distintos, tipo verde e tipo roxo. Os três ensaios, conduzidos separadamente, utilizaram cinco densidades de sementes por vaso. Em termos gerais, as sementes germinadas prontamente foram a razão do surgimento da próxima geração, visto que estabeleceram plântulas rapidamente e estas venceram em competição. A partir de certo número de sementes semeadas (20 por vaso), o número de plantas adultas obtidas revelou-se independente do número de sementes semeadas, o que indica que a capacidade de suporte do ambiente, ao invés do tamanho do banco de sementes no solo, é a razão da regulação do tamanho populacional; a mesma observação aplica-se à produção de matéria seca. Sob condições de competição, as espécies A. hybridus - tipo verde e A. viridis produziram maior quantidade de biomassa para reprodução (22% a 34%) do que A. hybridus - tipo roxo (15% a 18%). As primeiras, portanto, revelaram-se mais estrategistas-r que a última.

Variabilidade intra e intergenotípica em uma população de híbridos entre Leucaena leucocephala e L. diversifolia

O objetivo deste trabalho foi estimar a variabilidade de algumas características morfológicas em híbridos de Leucaena leucocephala e L. diversifolia (Leguminosae). Foram estabelecidos 20 genótipos, com 30 indivíduos cada, dispostos em seis blocos casualizados. As características morfológicas analisadas foram: comprimento de folha, número de pares de folíolos e foliólulos, número de nectários extraflorais; comprimento e largura de legumes e número de sementes por legume. O menor e o maior comprimento médio de folha foram, respectivamente, 8,6 cm e 30,6 cm. A população apresentou variação de 10,7 a 53,4 pares de foliólulos por folíolo. Em número de pares de folíolos por folha o menor valor médio foi 5,6 e o maior foi 20,3. A média de um nectário extrafloral por folha foi identificada na maioria dos indivíduos. O maior valor médio de número de sementes por legume foi 24,1 e o menor 5,0. Cinco genótipos se destacaram por sua uniformidade em relação às características analisadas.

Inter and intra-guild interactions in egg parasitoid species of the soybean stink bug complex

The objective of this research was to evaluate the parasitism behavior of Telenomus podisi Ashmead, Trissolcus basalis (Wollaston) e Trissolcus urichi Crawford (Hymenoptera: Scelionidae) on eggs of Nezara viridula L., Euschistus heros F., Piezodorus guildinii Westwood and Acrosternum aseadum Rolston (Heteroptera: Pentatomidae), in no choice and multiple choice experiments. For all parasitoid species, the results demonstrated the existence of a main host species that maximizes the reproductive success. The competitive interactions among the parasitoid species were investigated in experiments of sequential and simultaneous release of different combinations of parasitoid pairs on the hosts N. viridula, E. heros and A. aseadum. Exploitative competition was observed for egg batches at the genus level (Telenomus vs. Trissolcus) and interference competition at the species level (T. basalis vs. T. urichi). Trissolcus urichi was the most aggressive species, interfering with the parasitism of T. basalis. Generally, T. basalis showed an opportunistic behavior trying to parasitise eggs after T. urichi had abandoned the egg batch. The selection of parasitoid species for use in augmentative biological control programs should take into account the diversity of pentatomids present in soybean in addition to the interactions among the different species of parasitoids.

Desempenho reprodutivo de fêmeas suínas inseminadas pela técnica intra-uterina ou tradicional

O desempenho reprodutivo de fêmeas suínas foi avaliado com o objetivo de comparar duas técnicas de inseminação. Foram inseminadas, em delineamento inteiramente casualizado, 608 fêmeas com ordem de parto de dois a quatro, em dois tratamentos: inseminação intra-uterina com 1,5 bilhão de espermatozóides em 60 mL e inseminação tradicional, com 3 bilhões em 90 mL. Foi possível introduzir o cateter intra-uterino em 97,4% das fêmeas e houve sangramento em 9,5%, as quais apresentaram retorno ao estro superior (p<0,05). O porcentual de volume refluído até duas horas após a inseminação foi maior (p<0,05) na inseminação intra-uterina do que na tradicional, enquanto o porcentual de espermatozóides refluídos foi semelhante. Não houve influência do porcentual de espermatozóides refluídos sobre a taxa de parto e tamanho da leitegada. Não houve diferença nas taxas de retorno ao estro (3,6% e 4,3%), de prenhez aos 21 dias (99,5% e 97,2%), de parto ajustada (94,9% e 94,3%) e tamanho da leitegada (11,6 e 11,8 leitões) entre os dois tratamentos, respectivamente. A inseminação intra-uterina permite a obtenção de desempenho reprodutivo semelhante ao observado na tradicional, porém com uso de menor número de espermatozóides.

Prediction of cottonseed longevity

The objective of this work was to determine the viability equation constants for cottonseed and to detect the occurrence and depletion of hardseededness. Three seedlots of Brazilian cultivars IAC-19 and IAC-20 were tested, using 12 moisture content levels, ranging from 2.2 to 21.7% and three storage temperatures, 40, 50 and 65ºC. Seed moisture content level was reached from the initial value (around 8.8%) either by rehydration, in a closed container, or by drying in desiccators containing silica gel, both at 20ºC. Twelve seed subsamples for each moisture content/temperature treatment were sealed in laminated aluminium-foil packets and stored in incubators at those temperatures, until complete survival curves were obtained. Seed equilibrium relative humidity was recorded. Hardseededness was detected at moisture content levels below 6% and its releasing was achieved either naturally, during storage period, or artificially through seed coat removal. The viability equation quantified the response of seed longevity to storage environment well with K E = 9.240, C W = 5.190, C H = 0.03965 and C Q = 0.000426. The lower limit estimated for application of this equation at 65ºC was 3.6% moisture content.

Prediction of direct and indirect genetic gains and genotypic correlations in rubber tree progenies

The objective of this work was to estimate the genetic parameters, genotypic and phenotypic correlations, and direct and indirect genetic gains among and within rubber tree (Hevea brasiliensis) progenies. The experiment was set up at the Municipality of Jaú, SP, Brazil. A randomized complete block design was used, with 22 treatments (progenies), 6 replicates, and 10 plants per plot at a spacing of 3x3 m. Three‑year‑old progenies were assessed for girth, rubber yield, and bark thickness by direct and indirect gains and genotypic correlations. The number of latex vessel rings showed the best correlations, correlating positively and significantly with girth and bark thickness. Selection gains among progenies were greater than within progeny for all the variables analyzed. Total gains obtained were high, especially for girth increase and rubber yield, which were 93.38 and 105.95%, respectively. Young progeny selection can maximize the expected genetic gains, reducing the rubber tree selection cycle.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Field data and prediction models of pesticide spray drift on coffee crop

The objective of this work was to generate drift curves from pesticide applications on coffee plants and to compare them with two European drift-prediction models. The used methodology is based on the ISO 22866 standard. The experimental design was a randomized complete block with ten replicates in a 2x20 split-plot arrangement. The evaluated factors were: two types of nozzles (hollow cone with and without air induction) and 20 parallel distances to the crop line outside of the target area, spaced at 2.5 m. Blotting papers were used as a target and placed in each of the evaluated distances. The spray solution was composed of water+rhodamine B fluorescent tracer at a concentration of 100 mg L-1, for detection by fluorimetry. A spray volume of 400 L ha-1 was applied using a hydropneumatic sprayer. The air-induction nozzle reduces the drift up to 20 m from the treated area. The application with the hollow cone nozzle results in 6.68% maximum drift in the nearest collector of the treated area. The German and Dutch models overestimate the drift at distances closest to the crop, although the Dutch model more closely approximates the drift curves generated by both spray nozzles.

Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado

The objective of this work was to develop uni- and multivariate models to predict maximum soil shear strength (τmax) under different normal stresses (σn), water contents (U), and soil managements. The study was carried out in a Rhodic Haplustox under Cerrado (control area) and under no-tillage and conventional tillage systems. Undisturbed soil samples were taken in the 0.00-0.05 m layer and subjected to increasing U and σn, in shear strength tests. The uni- and multivariate models - respectively τmax=10(a+bU) and τmax=10(a+bU+cσn) - were significant in all three soil management systems evaluated and they satisfactorily explain the relationship between U, σn, and τmax. The soil under Cerrado has the highest shear strength (τ) estimated with the univariate model, regardless of the soil water content, whereas the soil under conventional tillage shows the highest values with the multivariate model, which were associated to the lowest water contents at the soil consistency limits in this management system.

Diversidade genética intra e interespecífica de pitaya com base nas características físico-químicas de frutos

Neste trabalho, objetivou-se avaliar a diversidade genética intra e interespecífica de 21 acessos de duas espécies de pitaya, Hylocereus undatus (Haw) Britton & Rose e Selenicereus setaceus Salm-Dyck. A. Bereger ex Werderm., com base nas características físico-químicas dos frutos. Foram avaliadas as características: comprimento, diâmetro, sólidos solúveis, massa total da casca e da polpa dos frutos. Com base na média das características físico-químicas de cada acesso, foram calculados índices de distância genética entre cada par de acessos com base na distância euclidiana média padronizada. A partir da matriz de distâncias genéticas, realizaram-se análises de agrupamento por meio de dendograma e dispersão gráfica baseada em escalas multidimensionais. As variáveis analisadas apresentaram diferentes contribuições relativas para a diversidade genética. O diâmetro do fruto foi a variável que teve maior contribuição no índice de diversidade genética (27,45 %), seguido pela massa total do fruto (25,43 %) e pela massa da polpa do fruto (24,67 %). As distâncias genéticas entre os 21 acessos de pitaya variaram entre 2,2 e 540,1. A análise de agrupamento permitiu subdividir os 21 acessos em dois grupos de similaridade genética, Hylocereus e Selenicereus, a uma distância genética relativa de 100. As características físico-químicas dos frutos evidenciaram alta diversidade genética entre os acessos das espécies H. undatus e S. setaceus.

Contribuição da ultra-sonografia intra-operatória (USIO) no estudo das características anátomo-sonográficas do leiomiossarcoma primário de pâncreas: nota prévia

Os autores apresentam um caso de leiomiossarcoma primário de pâncreas que teve seus aspectos ultra-sonográficos estudados pela ultra-sonografia intra-operatória. Embora os aspectos à ultra-sonografia abdominal, tomografia computadorizada e ressonância magnética já tenham sido descritos, as características à ultra-sonografia intra-operatória do leiomiossarcoma primário de pâncreas ainda não haviam sido relatadas na literatura. Os autores ressaltam, ainda, a importância deste método de imagem na determinação da invasão vascular pelo tumor.