Variability of apparently homogeneous soilscapes in São Paulo state, Brazil: II. quality of soil maps

The quality of semi-detailed (scale 1:100.000) soil maps and the utility of a taxonomically based legend were assessed by studying 33 apparently homogeneous fields with strongly weathered soils in two regions in São Paulo State: Araras and Assis. An independent data set of 395 auger sites was used to determine purity of soil mapping units and analysis of variance within and between mapping units and soil classification units. Twenty three soil profiles were studied in detail. The studied soil maps have a high purity for some legend criteria, such as B horizon type (> 90%) and soil texture class (> 80%). The purity for the "trophic character" (eutrophic, dystrophic, allic) was only 55% in Assis. It was 88% in Araras, where many soil units had been mapped as associations. In both regions, the base status of clay-textured soils was generally better than suggested by the maps. Analysis of variance showed that mapping was successful for "durable" soil characteristics such as clay content (> 80% of variance explained) and cation exchange capacity (≥ 50% of variance explained) of 0-20 and 60-80 cm layers. For soil characteristics that are easily modified by management, such as base saturation of the 0-20 cm layer, the maps had explained very little (< 15%) of the total variance in the study areas. Intermediate results were obtained for base saturation of the 60-80 cm layer (56% in Assis; 42% in Araras). Variance explained by taxonomic groupings that formed the basis for the legend of the soil maps was similar to, often even smaller than, variance explained by mapping units. The conclusion is that map boundaries have been very carefully located, but descriptions of mapping units could be improved. In future mappings, this could possibly be done at low cost by (a) bulk sampling to remove short range variation and enhance visualization of spatial patterns at distances > 100 m; (b) taking advantage of correlations between easily measured soil characteristics and chemical soil properties and, (c) unbending the link between legend criteria and a taxonomic system. The maps are well suited to obtain an impression of land suitability for high-input farming. Additional field work and data on former land use/management are necessary for the evaluation of chemical properties of surface horizons.

Variability of apparently homogeneous soilscapes in São Paulo state, Brazil: I. spatial analysis

The spatial variability of strongly weathered soils under sugarcane and soybean/wheat rotation was quantitatively assessed on 33 fields in two regions in São Paulo State, Brazil: Araras (15 fields with sugarcane) and Assis (11 fields with sugarcane and seven fields with soybean/wheat rotation). Statistical methods used were: nested analysis of variance (for 11 fields), semivariance analysis and analysis of variance within and between fields. Spatial levels from 50 m to several km were analyzed. Results are discussed with reference to a previously published study carried out in the surroundings of Passo Fundo (RS). Similar variability patterns were found for clay content, organic C content and cation exchange capacity. The fields studied are quite homogeneous with respect to these relatively stable soil characteristics. Spatial variability of other characteristics (resin extractable P, pH, base- and Al-saturation and also soil colour), varies with region and, or land use management. Soil management for sugarcane seems to have induced modifications to greater depths than for soybean/wheat rotation. Surface layers of soils under soybean/wheat present relatively little variation, apparently as a result of very intensive soil management. The major part of within-field variation occurs at short distances (< 50 m) in all study areas. Hence, little extra information would be gained by increasing sampling density from, say, 1/km² to 1/50 m². For many purposes, the soils in the study regions can be mapped with the same observation density, but residual variance will not be the same in all areas. Bulk sampling may help to reveal spatial patterns between 50 and 1.000 m.

Comparison of estimation methods of soil strength in five soils

In agriculture, the soil strength is used to describe the susceptibility to deformation by pressure caused by agricultural machine. The purpose of this study was to compare different methods for estimating the inherent soil strength and to identify their suitability for the evaluation of load support capacity, compaction susceptibility and root growth. The physical, chemical, mineralogical and intrinsic strength properties of seven soil samples, collected from five sampling pits at different locations in Brazil, were measured. Four clay (CS) and three sandy clay loam (SCL) soils were used. The clay soils were collected on a farm in Santo Ângelo, RS (28 º 16 ' 16 '' S; 54 º 13 ' 11 '' W 290 m); A and B horizons at the Universidade Federal de Lavras, Lavras, MG (21 º 13 ' 47 '' S; 44 º 58 ' 6'' W; 918 m) and on the farm Sygenta, in Uberlandia, MG (18 º 58 ' 37 '' S; 48 º 12 ' 05 '' W 866 m). The sandy clay loam soils were collected in Aracruz, ES (19 º 47 ' 10 '' S; 40 º 16 ' 29 '' W 81 m), and on the farm Xavier, Lavras, MG (21 º 13 ' 24 '' S; 45 º 05 ' 00 '' W; 844 m). Soil strength was estimated based on measurements of: (a) a pneumatic consolidometer, (b) manual pocket (non-rotating) penetrometer; and (c) automatic (rotating) penetrometer. The results of soil strength properties were similar by the three methods. The soil structure had a significant influence on soil strength. Results of measurements with both the manual pocket and the electric penetrometer were similar, emphasizing the influence of soil texture. The data showed that, to enhance the reliability of predictions of preconsolidation pressure by penetrometers, it is better to separate the soils into the different classes, rather than analyze them jointly. It can be concluded that the consolidometer method, although expensive, is the best when evaluations of load support capacity and compaction susceptibility of soil samples are desired.

Strategy of specification of management areas: rice grain yield as related to soil fertility

It is well-known nowadays that soil variability can influence crop yields. Therefore, to determine specific areas of soil management, we studied the Pearson and spatial correlations of rice grain yield with organic matter content and pH of an Oxisol (Typic Acrustox) under no- tillage, in the 2009/10 growing season, in Selvíria, State of Mato Grosso do Sul, in the Brazilian Cerrado (longitude 51º24' 21'' W, latitude 20º20' 56'' S). The upland rice cultivar IAC 202 was used as test plant. A geostatistical grid was installed for soil and plant data collection, with 120 sampling points in an area of 3.0 ha with a homogeneous slope of 0.055 m m-1. The properties rice grain yield and organic matter content, pH and potential acidity and aluminum content were analyzed in the 0-0.10 and 0.10-0.20 m soil layers. Spatially, two specific areas of agricultural land management were discriminated, differing in the value of organic matter and rice grain yield, respectively with fertilization at variable rates in the second zone, a substantial increase in agricultural productivity can be obtained. The organic matter content was confirmed as a good indicator of soil quality, when spatially correlated with rice grain yield.

Management zones in agriculture acording to the soil and landscape variables

The study of spatial variability of soil and plants attributes, or precision agriculture, a technique that aims the rational use of natural resources, is expanding commercially in Brazil. Nevertheless, there is a lack of mathematical analysis that supports the correlation of these independent variables and their interactions with the productivity, identifying scientific standards technologically applicable. The aim of this study was to identify patterns of soil variability according to the eleven physical and seven chemical indicators in an agricultural area. It was used two multivariate techniques: the hierarchical cluster analysis (HCA) and the principal component analysis (PCA). According to the HCA, the area was divided into five management zones: zone 1 with 2.87ha, zone 2 with 0.8ha, zone 3 with 1.84ha, zone 4 with 1.33ha and zone 5 with 2.76ha. By the PCA, it was identified the most important variables within each zone: V% for the zone 1, CTC in the zone 2, levels of H+Al in the zone 4 and sand content and altitude in the zone 5. The zone 3 was classified as an intermediate zone with characteristics of all others. According to the results it is concluded that it is possible to separate into groups (management zones) samples with the same patterns of variability by the multivariate statistical techniques.

Strategy of specification of management areas: rice grain yield as related to soil fertility

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Cross-hole and seismic CPT tests in a tropical soil site

A large portion of Brazil is covered with tropical soils but literature about dynamic parameters of these soils is very limited. SCPT and cross-hole tests were carried out at an experimental research site inland in the state of São Paulo, Brazil. Shear wave velocities (VS) determined based on both tests are presented and compared. A good agreement was observed between both test results and the differences can be associated with soil variability, which was very sensitive to CPT tests. It was also observed that Go/q c ratio determined based on SCPT appears to be an interesting technique to help identify tropical soils. Copyright ASCE 2006.

Digital soil mapping: evaluation of sampling systems for soil surveys and refinement of soil maps at lower cost using legacy data

In soil surveys, several sampling systems can be used to define the most representative sites for sample collection and description of soil profiles. In recent years, the conditioned Latin hypercube sampling system has gained prominence for soil surveys. In Brazil, most of the soil maps are at small scales and in paper format, which hinders their refinement. The objectives of this work include: (i) to compare two sampling systems by conditioned Latin hypercube to map soil classes and soil properties; (II) to retrieve information from a detailed scale soil map of a pilot watershed for its refinement, comparing two data mining tools, and validation of the new soil map; and (III) to create and validate a soil map of a much larger and similar area from the extrapolation of information extracted from the existing soil map. Two sampling systems were created by conditioned Latin hypercube and by the cost-constrained conditioned Latin hypercube. At each prospection place, soil classification and measurement of the A horizon thickness were performed. Maps were generated and validated for each sampling system, comparing the efficiency of these methods. The conditioned Latin hypercube captured greater variability of soils and properties than the cost-constrained conditioned Latin hypercube, despite the former provided greater difficulty in field work. The conditioned Latin hypercube can capture greater soil variability and the cost-constrained conditioned Latin hypercube presents great potential for use in soil surveys, especially in areas of difficult access. From an existing detailed scale soil map of a pilot watershed, topographical information for each soil class was extracted from a Digital Elevation Model and its derivatives, by two data mining tools. Maps were generated using each tool. The more accurate of these tools was used for extrapolation of soil information for a much larger and similar area and the generated map was validated. It was possible to retrieve the existing soil map information and apply it on a larger area containing similar soil forming factors, at much low financial cost. The KnowledgeMiner tool for data mining, and ArcSIE, used to create the soil map, presented better results and enabled the use of existing soil map to extract soil information and its application in similar larger areas at reduced costs, which is especially important in development countries with limited financial resources for such activities, such as Brazil.

Fertilization Management: Assessing New Techniques and Key Interactions to Increase Crop Yields With Less N2O Emissions

El óxido nitroso (N2O) es un potente gas de efecto invernadero (GHG) proveniente mayoritariamente de la fertilización nitrogenada de los suelos agrícolas. Identificar estrategias de manejo de la fertilización que reduzcan estas emisiones sin suponer un descenso de los rendimientos es vital tanto a nivel económico como medioambiental. Con ese propósito, en esta Tesis se han evaluado: (i) estrategias de manejo directo de la fertilización (inhibidores de la nitrificación/ureasa); y (ii) interacciones de los fertilizantes con (1) el manejo del agua, (2) residuos de cosecha y (3) diferentes especies de plantas. Para conseguirlo se llevaron a cabo meta-análisis, incubaciones de laboratorio, ensayos en invernadero y experimentos de campo. Los inhibidores de la nitrificación y de la actividad ureasa se proponen habitualmente como medidas para reducir las pérdidas de nitrógeno (N), por lo que su aplicación estaría asociada al uso eficiente del N por parte de los cultivos (NUE). Sin embargo, su efecto sobre los rendimientos es variable. Con el objetivo de evaluar en una primera fase su efectividad para incrementar el NUE y la productividad de los cultivos, se llevó a cabo un meta-análisis. Los inhibidores de la nitrificación dicyandiamide (DCD) y 3,4-dimetilepyrazol phosphate (DMPP) y el inhibidor de la ureasa N-(n-butyl) thiophosphoric triamide (NBPT) fueron seleccionados para el análisis ya que generalmente son considerados las mejores opciones disponibles comercialmente. Nuestros resultados mostraron que su uso puede ser recomendado con el fin de incrementar tanto el rendimiento del cultivo como el NUE (incremento medio del 7.5% y 12.9%, respectivamente). Sin embargo, se observó que su efectividad depende en gran medida de los factores medioambientales y de manejo de los estudios evaluados. Una mayor respuesta fue encontrada en suelos de textura gruesa, sistemas irrigados y/o en cultivos que reciben altas tasas de fertilizante nitrogenado. En suelos alcalinos (pH ≥ 8), el inhibidor de la ureasa NBPT produjo el mayor efecto. Dado que su uso representa un coste adicional para los agricultores, entender las mejores prácticas que permitan maximizar su efectividad es necesario para posteriormente realizar comparaciones efectivas con otras prácticas que incrementen la productividad de los cultivos y el NUE. En base a los resultados del meta-análisis, se seleccionó el NBPT como un inhibidor con gran potencial. Inicialmente desarrollado para reducir la volatilización de amoniaco (NH3), en los últimos años algunos investigadores han demostrado en estudios de campo un efecto mitigador de este inhibidor sobre las pérdidas de N2O provenientes de suelos fertilizados bajo condiciones de baja humedad del suelo. Dada la alta variabilidad de los experimentos de campo, donde la humedad del suelo cambia rápidamente, ha sido imposible entender mecanísticamente el potencial de los inhibidores de la ureasa (UIs) para reducir emisiones de N2O y su dependencia con respecto al porcentaje de poros llenos de agua del suelo (WFPS). Por lo tanto se realizó una incubación en laboratorio con el propósito de evaluar cuál es el principal mecanismo biótico tras las emisiones de N2O cuando se aplican UIs bajo diferentes condiciones de humedad del suelo (40, 60 y 80% WFPS), y para analizar hasta qué punto el WFPS regula el efecto del inhibidor sobre las emisiones de N2O. Un segundo UI (i.e. PPDA) fue utilizado para comparar el efecto del NBPT con el de otro inhibidor de la ureasa disponible comercialmente; esto nos permitió comprobar si el efecto de NBPT es específico de ese inhibidor o no. Las emisiones de N2O al 40% WFPS fueron despreciables, siendo significativamente más bajas que las de todos los tratamientos fertilizantes al 60 y 80% WFPS. Comparado con la urea sin inhibidor, NBPT+U redujo las emisiones de N2O al 60% WFPS pero no tuvo efecto al 80% WFPS. La aplicación de PPDA incrementó significativamente las emisiones con respecto a la urea al 80% WFPS mientras que no se encontró un efecto significativo al 60% WFPS. Al 80% WFPS la desnitrificación fue la principal fuente de las emisiones de N2O en todos los tratamientos mientras que al 60% tanto la nitrificación como la desnitrificación tuvieron un papel relevante. Estos resultados muestran que un correcto manejo del NBPT puede suponer una estrategia efectiva para mitigar las emisiones de N2O. Con el objetivo de trasladar nuestros resultados de los estudios previos a condiciones de campo reales, se desarrolló un experimento en el que se evaluó la efectividad del NBPT para reducir pérdidas de N y aumentar la productividad durante un cultivo de cebada (Hordeum vulgare L.) en secano Mediterráneo. Se determinó el rendimiento del cultivo, las concentraciones de N mineral del suelo, el carbono orgánico disuelto (DOC), el potencial de desnitrificación, y los flujos de NH3, N2O y óxido nítrico (NO). La adición del inhibidor redujo las emisiones de NH3 durante los 30 días posteriores a la aplicación de urea en un 58% y las emisiones netas de N2O y NO durante los 95 días posteriores a la aplicación de urea en un 86 y 88%, respectivamente. El uso de NBPT también incrementó el rendimiento en grano en un 5% y el consumo de N en un 6%, aunque ninguno de estos incrementos fue estadísticamente significativo. Bajo las condiciones experimentales dadas, estos resultados demuestran el potencial del inhibidor de la ureasa NBPT para mitigar las emisiones de NH3, N2O y NO provenientes de suelos arables fertilizados con urea, mediante la ralentización de la hidrólisis de la urea y posterior liberación de menores concentraciones de NH4 + a la capa superior del suelo. El riego por goteo combinado con la aplicación dividida de fertilizante nitrogenado disuelto en el agua de riego (i.e. fertirriego por goteo) se considera normalmente una práctica eficiente para el uso del agua y de los nutrientes. Algunos de los principales factores (WFPS, NH4 + y NO3 -) que regulan las emisiones de GHGs (i.e. N2O, CO2 y CH4) y NO pueden ser fácilmente manipulados por medio del fertirriego por goteo sin que se generen disminuciones del rendimiento. Con ese propósito se evaluaron opciones de manejo para reducir estas emisiones en un experimento de campo durante un cultivo de melón (Cucumis melo L.). Los tratamientos incluyeron distintas frecuencias de riego (semanal/diario) y tipos de fertilizantes nitrogenados (urea/nitrato cálcico) aplicados por fertirriego. Fertirrigar con urea en lugar de nitrato cálcico aumentó las emisiones de N2O y NO por un factor de 2.4 y 2.9, respectivamente (P < 0.005). El riego diario redujo las emisiones de NO un 42% (P < 0.005) pero aumentó las emisiones de CO2 un 21% (P < 0.05) comparado con el riego semanal. Analizando el Poder de Calentamiento global en base al rendimiento así como los factores de emisión del NO, concluimos que el fertirriego semanal con un fertilizante de tipo nítrico es la mejor opción para combinar productividad agronómica con sostenibilidad medioambiental en este tipo de agroecosistemas. Los suelos agrícolas en las áreas semiáridas Mediterráneas se caracterizan por su bajo contenido en materia orgánica y bajos niveles de fertilidad. La aplicación de residuos de cosecha y/o abonos es una alternativa sostenible y eficiente desde el punto de vista económico para superar este problema. Sin embargo, estas prácticas podrían inducir cambios importantes en las emisiones de N2O de estos agroecosistemas, con impactos adicionales en las emisiones de CO2. En este contexto se llevó a cabo un experimento de campo durante un cultivo de cebada (Hordeum vulgare L.) bajo condiciones Mediterráneas para evaluar el efecto de combinar residuos de cosecha de maíz con distintos inputs de fertilizantes nitrogenados (purín de cerdo y/o urea) en estas emisiones. La incorporación de rastrojo de maíz incrementó las emisiones de N2O durante el periodo experimental un 105%. Sin embargo, las emisiones de NO se redujeron significativamente en las parcelas enmendadas con rastrojo. La sustitución parcial de urea por purín de cerdo redujo las emisiones netas de N2O un 46 y 39%, con y sin incorporación de residuo de cosecha respectivamente. Las emisiones netas de NO se redujeron un 38 y un 17% para estos mismos tratamientos. El ratio molar DOC:NO3 - demostró predecir consistentemente las emisiones de N2O y NO. El efecto principal de la interacción entre el fertilizante nitrogenado y el rastrojo de maíz se dio a los 4-6 meses de su aplicación, generando un aumento del N2O y una disminución del NO. La sustitución de urea por purín de cerdo puede considerarse una buena estrategia de manejo dado que el uso de este residuo orgánico redujo las emisiones de óxidos de N. Los pastos de todo el mundo proveen numerosos servicios ecosistémicos pero también suponen una importante fuente de emisión de N2O, especialmente en respuesta a la deposición de N proveniente del ganado mientras pasta. Para explorar el papel de las plantas como mediadoras de estas emisiones, se analizó si las emisiones de N2O dependen de la riqueza en especies herbáceas y/o de la composición específica de especies, en ausencia y presencia de una deposición de orina. Las hipótesis fueron: 1) las emisiones de N2O tienen una relación negativa con la productividad de las plantas; 2) mezclas de cuatro especies generan menores emisiones que monocultivos (dado que su productividad será mayor); 3) las emisiones son menores en combinaciones de especies con distinta morfología radicular y alta biomasa de raíz; y 4) la identidad de las especies clave para reducir el N2O depende de si hay orina o no. Se establecieron monocultivos y mezclas de dos y cuatro especies comunes en pastos con rasgos funcionales divergentes: Lolium perenne L. (Lp), Festuca arundinacea Schreb. (Fa), Phleum pratense L. (Php) y Poa trivialis L. (Pt), y se cuantificaron las emisiones de N2O durante 42 días. No se encontró relación entre la riqueza en especies y las emisiones de N2O. Sin embargo, estas emisiones fueron significativamente menores en ciertas combinaciones de especies. En ausencia de orina, las comunidades de plantas Fa+Php actuaron como un sumidero de N2O, mientras que los monocultivos de estas especies constituyeron una fuente de N2O. Con aplicación de orina la comunidad Lp+Pt redujo (P < 0.001) las emisiones de N2O un 44% comparado con los monocultivos de Lp. Las reducciones de N2O encontradas en ciertas combinaciones de especies pudieron explicarse por una productividad total mayor y por una complementariedad en la morfología radicular. Este estudio muestra que la composición de especies herbáceas es un componente clave que define las emisiones de N2O de los ecosistemas de pasto. La selección de combinaciones de plantas específicas en base a la deposición de N esperada puede, por lo tanto, ser clave para la mitigación de las emisiones de N2O. ABSTRACT Nitrous oxide (N2O) is a potent greenhouse gas (GHG) directly linked to applications of nitrogen (N) fertilizers to agricultural soils. Identifying mitigation strategies for these emissions based on fertilizer management without incurring in yield penalties is of economic and environmental concern. With that aim, this Thesis evaluated: (i) the use of nitrification and urease inhibitors; and (ii) interactions of N fertilizers with (1) water management, (2) crop residues and (3) plant species richness/identity. Meta-analysis, laboratory incubations, greenhouse mesocosm and field experiments were carried out in order to understand and develop effective mitigation strategies. Nitrification and urease inhibitors are proposed as means to reduce N losses, thereby increasing crop nitrogen use efficiency (NUE). However, their effect on crop yield is variable. A meta-analysis was initially conducted to evaluate their effectiveness at increasing NUE and crop productivity. Commonly used nitrification inhibitors (dicyandiamide (DCD) and 3,4-dimethylepyrazole phosphate (DMPP)) and the urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) were selected for analysis as they are generally considered the best available options. Our results show that their use can be recommended in order to increase both crop yields and NUE (grand mean increase of 7.5% and 12.9%, respectively). However, their effectiveness was dependent on the environmental and management factors of the studies evaluated. Larger responses were found in coarse-textured soils, irrigated systems and/or crops receiving high nitrogen fertilizer rates. In alkaline soils (pH ≥ 8), the urease inhibitor NBPT produced the largest effect size. Given that their use represents an additional cost for farmers, understanding the best management practices to maximize their effectiveness is paramount to allow effective comparison with other practices that increase crop productivity and NUE. Based on the meta-analysis results, NBPT was identified as a mitigation option with large potential. Urease inhibitors (UIs) have shown to promote high N use efficiency by reducing ammonia (NH3) volatilization. In the last few years, however, some field researches have shown an effective mitigation of UIs over N2O losses from fertilized soils under conditions of low soil moisture. Given the inherent high variability of field experiments where soil moisture content changes rapidly, it has been impossible to mechanistically understand the potential of UIs to reduce N2O emissions and its dependency on the soil water-filled pore space (WFPS). An incubation experiment was carried out aiming to assess what is the main biotic mechanism behind N2O emission when UIs are applied under different soil moisture conditions (40, 60 and 80% WFPS), and to analyze to what extent the soil WFPS regulates the effect of the inhibitor over N2O emissions. A second UI (i.e. PPDA) was also used aiming to compare the effect of NBPT with that of another commercially available urease inhibitor; this allowed us to see if the effect of NBPT was inhibitor-specific or not. The N2O emissions at 40% WFPS were almost negligible, being significantly lower from all fertilized treatments than that produced at 60 and 80% WFPS. Compared to urea alone, NBPT+U reduced the N2O emissions at 60% WFPS but had no effect at 80% WFPS. The application of PPDA significantly increased the emissions with respect to U at 80% WFPS whereas no significant effect was found at 60% WFPS. At 80% WFPS denitrification was the main source of N2O emissions for all treatments. Both nitrification and denitrification had a determinant role on these emissions at 60% WFPS. These results suggest that adequate management of the UI NBPT can provide, under certain soil conditions, an opportunity for N2O mitigation. We translated our previous results to realistic field conditions by means of a field experiment with a barley crop (Hordeum vulgare L.) under rainfed Mediterranean conditions in which we evaluated the effectiveness of NBPT to reduce N losses and increase crop yields. Crop yield, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification potential, NH3, N2O and nitric oxide (NO) fluxes were measured during the growing season. The inclusion of the inhibitor reduced NH3 emissions in the 30 d following urea application by 58% and net N2O and NO emissions in the 95 d following urea application by 86 and 88%, respectively. NBPT addition also increased grain yield by 5% and N uptake by 6%, although neither increase was statistically significant. Under the experimental conditions presented here, these results demonstrate the potential of the urease inhibitor NBPT in abating NH3, N2O and NO emissions from arable soils fertilized with urea, slowing urea hydrolysis and releasing lower concentrations of NH4 + to the upper soil layer. Drip irrigation combined with split application of N fertilizer dissolved in the irrigation water (i.e. drip fertigation) is commonly considered best management practice for water and nutrient efficiency. Some of the main factors (WFPS, NH4 + and NO3 -) regulating the emissions of GHGs (i.e. N2O, carbon dioxide (CO2) and methane (CH4)) and NO can easily be manipulated by drip fertigation without yield penalties. In this study, we tested management options to reduce these emissions in a field experiment with a melon (Cucumis melo L.) crop. Treatments included drip irrigation frequency (weekly/daily) and type of N fertilizer (urea/calcium nitrate) applied by fertigation. Crop yield, environmental parameters, soil mineral N concentrations, N2O, NO, CH4, and CO2 fluxes were measured during the growing season. Fertigation with urea instead of calcium nitrate increased N2O and NO emissions by a factor of 2.4 and 2.9, respectively (P < 0.005). Daily irrigation reduced NO emissions by 42% (P < 0.005) but increased CO2 emissions by 21% (P < 0.05) compared with weekly irrigation. Based on yield-scaled Global Warming Potential as well as NO emission factors, we conclude that weekly fertigation with a NO3 --based fertilizer is the best option to combine agronomic productivity with environmental sustainability. Agricultural soils in semiarid Mediterranean areas are characterized by low organic matter contents and low fertility levels. Application of crop residues and/or manures as amendments is a cost-effective and sustainable alternative to overcome this problem. However, these management practices may induce important changes in the nitrogen oxide emissions from these agroecosystems, with additional impacts on CO2 emissions. In this context, a field experiment was carried out with a barley (Hordeum vulgare L.) crop under Mediterranean conditions to evaluate the effect of combining maize (Zea mays L.) residues and N fertilizer inputs (organic and/or mineral) on these emissions. Crop yield and N uptake, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification capacity, N2O, NO and CO2 fluxes were measured during the growing season. The incorporation of maize stover increased N2O emissions during the experimental period by c. 105 %. Conversely, NO emissions were significantly reduced in the plots amended with crop residues. The partial substitution of urea by pig slurry reduced net N2O emissions by 46 and 39 %, with and without the incorporation of crop residues respectively. Net emissions of NO were reduced 38 and 17 % for the same treatments. Molar DOC:NO3 - ratio was found to be a robust predictor of N2O and NO fluxes. The main effect of the interaction between crop residue and N fertilizer application occurred in the medium term (4-6 month after application), enhancing N2O emissions and decreasing NO emissions as consequence of residue incorporation. The substitution of urea by pig slurry can be considered a good management strategy since N2O and NO emissions were reduced by the use of the organic residue. Grassland ecosystems worldwide provide many important ecosystem services but they also function as a major source of N2O, especially in response to N deposition by grazing animals. In order to explore the role of plants as mediators of these emissions, we tested whether and how N2O emissions are dependent on grass species richness and/or specific grass species composition in the absence and presence of urine deposition. We hypothesized that: 1) N2O emissions relate negatively to plant productivity; 2) four-species mixtures have lower emissions than monocultures (as they are expected to be more productive); 3) emissions are lowest in combinations of species with diverging root morphology and high root biomass; and 4) the identity of the key species that reduce N2O emissions is dependent on urine deposition. We established monocultures and two- and four-species mixtures of common grass species with diverging functional traits: Lolium perenne L. (Lp), Festuca arundinacea Schreb. (Fa), Phleum pratense L. (Php) and Poa trivialis L. (Pt), and quantified N2O emissions for 42 days. We found no relation between plant species richness and N2O emissions. However, N2O emissions were significantly reduced in specific plant species combinations. In the absence of urine, plant communities of Fa+Php acted as a sink for N2O, whereas the monocultures of these species constituted a N2O source. With urine application Lp+Pt plant communities reduced (P < 0.001) N2O emissions by 44% compared to monocultures of Lp. Reductions in N2O emissions by species mixtures could be explained by total biomass productivity and by complementarity in root morphology. Our study shows that plant species composition is a key component underlying N2O emissions from grassland ecosystems. Selection of specific grass species combinations in the context of the expected nitrogen deposition regimes may therefore provide a key management practice for mitigation of N2O emissions.

Soil organic carbon storage and soil properties for 50 soil profiles in the Lena River Delta including land form description and map

To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58±10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2±2.0 kg C/m**2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m**2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.

In Situ Near-Infrared (NIR) Versus High-Throughput Mid- Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Production

The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coil cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R-2) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).

Large-eddy simulation of wind flows over complex terrains for wind energy applications

Wind energy has obtained outstanding expectations due to risks of global warming and nuclear energy production plant accidents. Nowadays, wind farms are often constructed in areas of complex terrain. A potential wind farm location must have the site thoroughly surveyed and the wind climatology analyzed before installing any hardware. Therefore, modeling of Atmospheric Boundary Layer (ABL) flows over complex terrains containing, e.g. hills, forest, and lakes is of great interest in wind energy applications, as it can help in locating and optimizing the wind farms. Numerical modeling of wind flows using Computational Fluid Dynamics (CFD) has become a popular technique during the last few decades. Due to the inherent flow variability and large-scale unsteadiness typical in ABL flows in general and especially over complex terrains, the flow can be difficult to be predicted accurately enough by using the Reynolds-Averaged Navier-Stokes equations (RANS). Large- Eddy Simulation (LES) resolves the largest and thus most important turbulent eddies and models only the small-scale motions which are more universal than the large eddies and thus easier to model. Therefore, LES is expected to be more suitable for this kind of simulations although it is computationally more expensive than the RANS approach. With the fast development of computers and open-source CFD software during the recent years, the application of LES toward atmospheric flow is becoming increasingly common nowadays. The aim of the work is to simulate atmospheric flows over realistic and complex terrains by means of LES. Evaluation of potential in-land wind park locations will be the main application for these simulations. Development of the LES methodology to simulate the atmospheric flows over realistic terrains is reported in the thesis. The work also aims at validating the LES methodology at a real scale. In the thesis, LES are carried out for flow problems ranging from basic channel flows to real atmospheric flows over one of the most recent real-life complex terrain problems, the Bolund hill. All the simulations reported in the thesis are carried out using a new OpenFOAM® -based LES solver. The solver uses the 4th order time-accurate Runge-Kutta scheme and a fractional step method. Moreover, development of the LES methodology includes special attention to two boundary conditions: the upstream (inflow) and wall boundary conditions. The upstream boundary condition is generated by using the so-called recycling technique, in which the instantaneous flow properties are sampled on aplane downstream of the inlet and mapped back to the inlet at each time step. This technique develops the upstream boundary-layer flow together with the inflow turbulence without using any precursor simulation and thus within a single computational domain. The roughness of the terrain surface is modeled by implementing a new wall function into OpenFOAM® during the thesis work. Both, the recycling method and the newly implemented wall function, are validated for the channel flows at relatively high Reynolds number before applying them to the atmospheric flow applications. After validating the LES model over simple flows, the simulations are carried out for atmospheric boundary-layer flows over two types of hills: first, two-dimensional wind-tunnel hill profiles and second, the Bolund hill located in Roskilde Fjord, Denmark. For the twodimensional wind-tunnel hills, the study focuses on the overall flow behavior as a function of the hill slope. Moreover, the simulations are repeated using another wall function suitable for smooth surfaces, which already existed in OpenFOAM® , in order to study the sensitivity of the flow to the surface roughness in ABL flows. The simulated results obtained using the two wall functions are compared against the wind-tunnel measurements. It is shown that LES using the implemented wall function produces overall satisfactory results on the turbulent flow over the two-dimensional hills. The prediction of the flow separation and reattachment-length for the steeper hill is closer to the measurements than the other numerical studies reported in the past for the same hill geometry. The field measurement campaign performed over the Bolund hill provides the most recent field-experiment dataset for the mean flow and the turbulence properties. A number of research groups have simulated the wind flows over the Bolund hill. Due to the challenging features of the hill such as the almost vertical hill slope, it is considered as an ideal experimental test case for validating micro-scale CFD models for wind energy applications. In this work, the simulated results obtained for two wind directions are compared against the field measurements. It is shown that the present LES can reproduce the complex turbulent wind flow structures over a complicated terrain such as the Bolund hill. Especially, the present LES results show the best prediction of the turbulent kinetic energy with an average error of 24.1%, which is a 43% smaller than any other model results reported in the past for the Bolund case. Finally, the validated LES methodology is demonstrated to simulate the wind flow over the existing Muukko wind farm located in South-Eastern Finland. The simulation is carried out only for one wind direction and the results on the instantaneous and time-averaged wind speeds are briefly reported. The demonstration case is followed by discussions on the practical aspects of LES for the wind resource assessment over a realistic inland wind farm.

Mapeamento das formas do relevo para estimativa de custos de fertilização em cana-de-açúcar

A modelagem matemática associada ao conhecimento da variabilidade dos atributos do solo e mapeamento das formas do relevo pode auxiliar no manejo da fertilidade do solo em usinas sucroalcooleiras. O presente trabalho teve como objetivo avaliar o uso da geoestatística e da modelagem matemática na estimativa de custos de fertilização, em diferentes formas do relevo. em uma área de 200 ha, foram identificadas duas formas de relevo, uma côncava e outra convexa, sendo os solos coletados nos pontos de cruzamento de uma malha, com intervalos regulares de 50 m, perfazendo um total de 623 pontos. As amostras foram submetidas a análises químicas, e, posteriormente, os dados foram avaliados por meio da estatística descritiva, geoestatística e modelagem matemática. Os resultados mostraram que, quando as formas do relevo são incorporadas às análises geoestatística e de modelagem matemática, ocorre aumento na eficiência de aplicação do calcário, fósforo e potássio no solo.