Knowledge and perception of Ghanaian cocoa farmers on mirid control and their willingness to use forecasting systems

Annual losses of cocoa in Ghana to mirids are significant. Therefore, accurate timing of insecticide application is critical to enhance yields. However, cocoa farmers often lack information on the expected mirid population for each season to enable them to optimise pesticide use. This study assessed farmers’ knowledge and perceptions of mirid control and their willingness to use forecasting systems informing them of expected mirid peaks and time of application of pesticides. A total of 280 farmers were interviewed in the Eastern and Ashanti regions of Ghana with a structured open and closed ended questionnaire. Most farmers (87%) considered mirids as the most important insect pest on cocoa with 47% of them attributing 30-40% annual crop loss to mirid damage. There was wide variation in the timing of insecticide application as a result of farmers using different sources of information to guide the start of application. The majority of farmers (56%) do not have access to information on the type, frequency and timing of insecticides to use. However, respondents who are members of farmer groups had better access to such information. Extension officers were the preferred channel for information transfer to farmers with 72% of farmers preferring them to other available methods of communication. Almost all the respondents (99%) saw the need for a comprehensive forecasting system to help farmers manage cocoa mirids. The importance of accurate timing for mirid control based on forecasted information to farmer groups and extension officers was discussed.

A coupling cutting stock-lot sizing problem in the paper industry

An important production programming problem arises in paper industries coupling multiple machine scheduling with cutting stocks. Concerning machine scheduling: how can the production of the quantity of large rolls of paper of different types be determined. These rolls are cut to meet demand of items. Scheduling that minimizes setups and production costs may produce rolls which may increase waste in the cutting process. On the other hand, the best number of rolls in the point of view of minimizing waste may lead to high setup costs. In this paper, coupled modeling and heuristic methods are proposed. Computational experiments are presented.

System size dependence of associated yields in hadron-triggered jets STAR Collaboration

We present results on the system size dependence of high transverse momentum di-hadron correlations at root s(NN) = 200 GeV as measured by STAR at RHIC. Measurements in d + Au, Cu + Cu and Au + Au collisions reveal similar jet-like near-side correlation yields (correlations at small angular separation Delta phi similar to 0, Delta eta similar to 0) for all systems and centralities. Previous measurements have shown Chat the away-side (Delta phi similar to pi) yield is suppressed in heavy-ion collisions. We present measurements of the away-side Suppression as a function of transverse momentum and centrality in Cu + Cu and Au + Au collisions. The suppression is found to be similar in Cu + Cu and An + An collisions at a similar number of participants. The results are compared to theoretical calculations based on the patron quenching model and the modified fragmentation model. The observed differences between data and theory indicate that the correlated yields presented here will further constrain dynamic energy loss models and provide information about the dynamic density profile in heavy-ion collisions. (C) 2009 Elsevier B.V. All rights reserved.

Distribution Of Hydrological Losses For Varying Rainfall And Antecedent Wetness Conditions

Hydrological loss is a vital component in many hydrological models, which are usedin forecasting floods and evaluating water resources for both surface and subsurface flows. Due to the complex and random nature of the rainfall runoff process, hydrological losses are not yet fully understood. Consequently, practitioners often use representative values of the losses for design applications such as rainfall-runoff modelling which has led to inaccurate quantification of water quantities in the resulting applications. The existing hydrological loss models must be revisited and modellers should be encouraged to utilise other available data sets. This study is based on three unregulated catchments situated in Mt. Lofty Ranges of South Australia (SA). The paper focuses on conceptual models for: initial loss (IL), continuing loss (CL) and proportional loss (PL) with rainfall characteristics (total rainfall (TR) and storm duration (D)), and antecedent wetness (AW) conditions. The paper introduces two methods that can be implemented to estimate IL as a function of TR, D and AW. The IL distribution patterns and parameters for the study catchments are determined using multivariate analysis and descriptive statistics. The possibility of generalising the methods and the limitations of this are also discussed. This study will yield improvements to existing loss models and will encourage practitioners to utilise multiple data sets to estimate losses, instead of using hypothetical or representative values to generalise real situations.

An assessment of the economic impact of climate change on the Agriculture Sector in Jamaica

The agricultural sector‟s contribution to GDP and to exports in Jamaica has been declining with the post-war development process that has led to the differentiation of the economy. In 2010, the sector contributed 5.8% of GDP, and 3% to the exports (of goods), but with 36% of employment, it continues to be a major employer. With a little less than half of the population living in rural communities, agricultural activities, and their linkages with other economic activities, continue to play an important role as a source of livelihoods, and by extension, the economic development of the country. Sugar cane cultivation has, with the exception of a couple of decades in the twentieth century when it was superseded by bananas, dominated the agricultural export sector for centuries as the source of the raw materials for the manufacture of sugar for export. In 2005, sugar cane itself accounted for 6.4% of the sector‟s contribution to GDP, and 52% of the contribution of agricultural exports to GDP. Production for the domestic market has long been the larger subsector, organized around the production of root crops, especially yams, vegetables and condiments. To analyse the potential impact of climate change on the agricultural sector, this study selected three important crops for detailed examination. In particular, the study selected sugar cane because of its overwhelming importance to the export subsector of agriculture, and yam and escallion for both their contribution to the domestic subsector as well as the preeminent role yams and escallion play in the economic activities of the communities in the hills of central Jamaica, and the plains of the southwest respectively. As with other studies in this project, the methodology adopted was to compare the estimated values of output on the SRES A2 and B2 Scenarios with the value of output on a “baseline” Business As Usual (BAU), and then estimate the net benefits of investment in the relevant to climate change for the selected crops. The A2 and B2 Scenarios were constructed by applying forecasts of changes in temperature and precipitation generated by INSMET from ECHAM inspired climate models. The BAU “baseline” was a linear projection of the historical trends of yields for each crop. Linear models of yields were estimated for each crop with particular attention to the influence of the two climate variables – temperature and precipitation. These models were then used to forecast yields up to 2050 (table1). These yields were then used to estimate the value of output of the selected crop, as well as the contribution to overall GDP, on each Scenario. The analysis suggested replanting sugar cane with heat resistant varieties, rehabilitating irrigation systems where they existed, and establishing technologically appropriate irrigation systems where they were not for the three selected crops.

Modelos agrometeorológicos estatísticos de previsão de produtividade e qualidade para cana-de-açúcar

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Nuclear-modification factor for open-heavy-flavor production at forward rapidity in Cu plus Cu collisions at root s(NN)=200 GeV

Background: Heavy-flavor production in p + p collisions is a good test of perturbative-quantum-chromodynamics (pQCD) calculations. Modification of heavy-flavor production in heavy-ion collisions relative to binary-collision scaling from p + p results, quantified with the nuclear-modification factor (R-AA), provides information on both cold-and hot-nuclear-matter effects. Midrapidity heavy-flavor R-AA measurements at the Relativistic Heavy Ion Collider have challenged parton-energy-loss models and resulted in upper limits on the viscosity-entropy ratio that are near the quantum lower bound. Such measurements have not been made in the forward-rapidity region. Purpose: Determine transverse-momentum (p(T)) spectra and the corresponding R-AA for muons from heavy-flavor meson decay in p + p and Cu + Cu collisions at root s(NN) = 200 GeV and y = 1.65. Method: Results are obtained using the semileptonic decay of heavy-flavor mesons into negative muons. The PHENIX muon-arm spectrometers measure the p(T) spectra of inclusive muon candidates. Backgrounds, primarily due to light hadrons, are determined with a Monte Carlo calculation using a set of input hadron distributions tuned to match measured-hadron distributions in the same detector and statistically subtracted. Results: The charm-production cross section in p + p collisions at root s = 200 GeV, integrated over p(T) and in the rapidity range 1.4 < y < 1.9, is found to be d(sigma e (e) over bar)/dy = 0.139 +/- 0.029 (stat)(-0.058)(+0.051) (syst) mb. This result is consistent with a perturbative fixed-order-plus-next-to-leading-log calculation within scale uncertainties and is also consistent with expectations based on the corresponding midrapidity charm-production cross section measured by PHENIX. The R-AA for heavy-flavor muons in Cu + Cu collisions is measured in three centrality bins for 1 < p(T) < 4 GeV/c. Suppression relative to binary-collision scaling (R-AA < 1) increases with centrality. Conclusions: Within experimental and theoretical uncertainties, the measured charm yield in p + p collisions is consistent with state-of-the-art pQCD calculations. Suppression in central Cu + Cu collisions suggests the presence of significant cold-nuclear-matter effects and final-state energy loss.

Rainwater Catchment from a High Tunnel for Irrigation Use

High tunnels are simple, plastic-covered, passive solar-heated structures in which crops are grown in the ground. They are used by fruit and vegetable growers to extend the growing season and intensify production in cold climates. The covered growing area creates a desert-like environment requiring carefully monitored irrigation practices. In contrast, the exterior expanse of a high tunnel generates a large volume of water with every measurable rainfall. Each 1,000 ft of high tunnel roof will generate approximately 300 gallons from a half inch of rain. Unless the high tunnel site is elevated from the surrounding area or drainage tiles installed, or other drainage accommodations are made around the perimeter, the soil along the inside edge of the high tunnel is nearly continuously saturated. High volumes of water can also create an erosion problem. The objective of this project was to design and construct a system that enables growers using high tunnels in their production operation to reduce drainage problems, erosion, and crop loss due to excess moisture in and around their high tunnel(s) without permanent environmental and soil mediations.

Simulating improved combinations tillage-rotation under dryland conditions.

The adequate combination of reduced tillage and crop rotation could increase the viability of dry land agriculture in Mediterrenean zones. Crop simulation models can support to examine various tillage-rotation combinations and explore management scenarios. The decision support system for agrotechnology transfer (DSSAT) (Hoogenboom et al., 2010) provides a suite of crop models suitable for this task. The objective of this work was to simulate the effects of two tillage systems, conventional tillage (ConvT) and no tillage (NoT), and three crop rotations, continuous cereal (CC), fallow-cereal (FallowC) and legume-cereal (LegumeC), under dry conditions, on the cereal yield, soil organic carbon (SOC) and nitrogen (SON) in a 15-year experiment, comparing these simulations with field observations.

Simulating improved combinations tillage-rotation under dryland conditions.

Crop simulation models allow analyzing various tillage-rotation combinations and exploring management scenarios. This study was conducted to test the DSSAT (Decision Support System for Agrotechnology Transfer) modelling system in rainfed semiarid central Spain. The focus is on the combined effect of tillage system and winter cereal-based rotations (cereal/legume/fallow) on the crop yield and soil quality. The observed data come from a 16-year field experiment. The CERES and CROPGRO models, included in DSSAT v4.5, were used to simulate crop growth and yield, and DSSAT- CENTURY was used in the soil organic carbon (SOC) and soil nitrogen (SN) simulations. Genetic coefficients were calibrated using part of the observed data. Field observations showed that barley grain yield was lower for continuous cereal (BB) than for vetch (VB) and fallow (FB) rotations for both tillage systems. The CERES-Barley model also reflected this trend. The model predicted higher yield in the conventional tillage (CT) than in the no tillage (NT) probably due to the higher nitrogen availability in the CT, shown in the simulations. The SOC and SN in the top layer only, were higher in NT than in CT, and decreased with depth in both simulated and observed values. These results suggest that CT-VB and CT-FB were the best combinations for the dry land conditions studied. However, CT presented lower SN and SOC content than NT. This study shows how models can be a useful tool for assessing and predicting crop growth and yield, under different management systems and under specific edapho-climatic conditions. Additional key words: CENTURY model; CERES-Barley; crop simulation models; DSSAT; sequential simula- tion; soil organic carbon.

Climate variability effects on field crops in Iberian Peninsula. Predictability

La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

Analysis and Design Considerations of an Electric Vehicle Powertrain regarding Energy Efficiency and Magnetic Field Exposure

En esta tesis se analiza el sistema de tracción de un vehículo eléctrico de batería desde el punto de vista de la eficiencia energética y de la exposición a campos magnéticos por parte de los pasajeros (radiación electromagnética). Este estudio incluye tanto el sistema de almacenamiento de energía como la máquina eléctrica, junto con la electrónica de potencia y los sistemas de control asociados a ambos. Los análisis y los resultados presentados en este texto están basados en modelos matemáticos, simulaciones por ordenador y ensayos experimentales a escala de laboratorio. La investigación llevada a cabo durante esta tesis tuvo siempre un marcado enfoque industrial, a pesar de estar desarrollada en un entorno de considerable carácter universitario. Las líneas de investigación acometidas tuvieron como destinatario final al diseñador y al fabricante del vehículo, a pesar de lo cual algunos de los resultados obtenidos son preliminares y/o excesivamente académicos para resultar de interés industrial. En el ámbito de la eficiencia energética, esta tesis estudia sistemas híbridos de almacenamiento de energía basados en una combinación de baterías de litio y supercondensadores. Este tipo de sistemas son analizados desde el punto de vista de la eficiencia mediante modelos matemáticos y simulaciones, cuantificando el impacto de ésta en otros parámetros tales como el envejecimiento de las baterías. Respecto a la máquina eléctrica, el estudio se ha centrado en máquinas síncronas de imanes permanentes. El análisis de la eficiencia considera tanto el diseño de la máquina como la estrategia de control, dejando parcialmente de lado el inversor y la técnica de modulación (que son incluidos en el estudio como fuentes adicionales de pérdidas, pero no como potenciales fuentes de optimización de la eficiencia). En este sentido, tanto la topología del inversor (trifásico, basado en IGBTs) como la técnica de modulación (control de corriente en banda de histéresis) se establecen desde el principio. El segundo aspecto estudiado en esta tesis es la exposición a campos magnéticos por parte de los pasajeros. Este tema se enfoca desde un punto de vista predictivo, y no desde un punto de vista de diagnóstico, puesto que se ha desarrollado una metodología para estimar el campo magnético generado por los dispositivos de potencia de un vehículo eléctrico. Esta metodología ha sido validada mediante ensayos de laboratorio. Otros aspectos importantes de esta contribución, además de la metodología en sí misma, son las consecuencias que se derivan de ella (por ejemplo, recomendaciones de diseño) y la comprensión del problema proporcionada por esta. Las principales contribuciones de esta tesis se listan a continuación: una recopilación de modelos de pérdidas correspondientes a la mayoría de dispositivos de potencia presentes en un vehículo eléctrico de batería, una metodología para analizar el funcionamiento de un sistema híbrido de almacenamiento de energía para aplicaciones de tracción, una explicación de cómo ponderar energéticamente los puntos de operación par-velocidad de un vehículo eléctrico (de utilidad para evaluar el rendimiento de una máquina eléctrica, por ejemplo), una propuesta de incluir un convertidor DC-DC en el sistema de tracción para minimizar las pérdidas globales del accionamiento (a pesar de las nuevas pérdidas introducidas por el propio DC-DC), una breve comparación entre dos tipos distintos de algoritmos de minimización de pérdidas para máquinas síncronas de imanes permanentes, una metodología predictiva para estimar la exposición a campos magnéticos por parte de los pasajeros de un vehículo eléctrico (debida a los equipos de potencia), y finalmente algunas conclusiones y recomendaciones de diseño respecto a dicha exposición a campos magnéticos. ABSTRACT This dissertation analyzes the powertrain of a battery electric vehicle, focusing on energy efficiency and passenger exposure to electromagnetic fields (electromagnetic radiation). This study comprises the energy storage system as well as the electric machine, along with their associated power electronics and control systems. The analysis and conclusions presented in this dissertation are based on mathematical models, computer simulations and laboratory scale tests. The research performed during this thesis was intended to be of industrial nature, despite being developed in a university. In this sense, the work described in this document was carried out thinking of both the designer and the manufacturer of the vehicle. However, some of the results obtained lack industrial readiness, and therefore they remain utterly academic. Regarding energy efficiency, hybrid energy storage systems consisting in lithium batteries, supercapacitors and up to two DC-DC power converters are considered. These kind of systems are analyzed by means of mathematical models and simulations from the energy efficiency point of view, quantifying its impact on other relevant aspects such as battery aging. Concerning the electric machine, permanent magnet synchronous machines are studied in this work. The energy efficiency analysis comprises the machine design and the control strategy, while the inverter and its modulation technique are taken into account but only as sources of further power losses, and not as potential sources for further efficiency optimization. In this sense, both the inverter topology (3-phase IGBT-based inverter) and the switching technique (hysteresis current control) are fixed from the beginning. The second aspect studied in this work is passenger exposure to magnetic fields. This topic is approached from the prediction point of view, rather than from the diagnosis point of view. In other words, a methodology to estimate the magnetic field generated by the power devices of an electric vehicle is proposed and analyzed in this dissertation. This methodology has been validated by laboratory tests. The most important aspects of this contribution, apart from the methodology itself, are the consequences (for instance, design guidelines) and the understanding of the magnetic radiation issue provided by it. The main contributions of this dissertation are listed next: a compilation of loss models for most of the power devices found in a battery electric vehicle powertrain, a simulation-based methodology to analyze hybrid energy storage performance in traction applications, an explanation of how to assign energy-based weights to different operating points in traction drives (useful when assessing electrical machine performance, for instance), a proposal to include one DC-DC converter in electric powertrains to minimize overall power losses in the system (despite the new losses added by the DC-DC), a brief comparison between two kinds of loss-minimization algorithms for permanent magnet synchronous machines in terms of adaptability and energy efficiency, a predictive methodology to estimate passenger magnetic field exposure due to power devices in an electric vehicle, and finally some useful conclusions and design guidelines concerning magnetic field exposure.

Minimising cold damage during reproductive development among temperate rice genotypes. I. Avoiding low temperature with the use of appropriate sowing time and photoperiod-sensitive varieties

Multiple-sown field trials in 4 consecutive years in the Riverina region of south-eastern Australia provided 24 different combinations of temperature and day length, which enabled the development of crop phenology models. A crop model was developed for 7 cultivars from diverse origins to identify if photoperiod sensitivity is involved in determining phenological development, and if that is advantageous in avoiding low-temperature damage. Cultivars that were mildly photoperiod-sensitive were identified from sowing to flowering and from panicle initiation to flowering. The crop models were run for 47 years of temperature data to quantify the risk of encountering low temperature during the critical young microspore stage for 5 different sowing dates. Cultivars that were mildly photoperiod-sensitive, such as Amaroo, had a reduced likelihood of encountering low temperature for a wider range of sowing dates compared with photoperiod-insensitive cultivars. The benefits of increased photoperiod sensitivity include greater sowing flexibility and reduced water use as growth duration is shortened when sowing is delayed. Determining the optimal sowing date also requires other considerations, e. g. the risk of cold damage at other sensitive stages such as flowering and the response of yield to a delay in flowering under non-limiting conditions. It was concluded that appropriate sowing time and the use of photoperiod-sensitive cultivars can be advantageous in the Riverina region in avoiding low temperature damage during reproductive development.

Physical Design Methodologies for Low Power and Reliable 3D ICs

As the semiconductor industry struggles to maintain its momentum down the path following the Moore's Law, three dimensional integrated circuit (3D IC) technology has emerged as a promising solution to achieve higher integration density, better performance, and lower power consumption. However, despite its significant improvement in electrical performance, 3D IC presents several serious physical design challenges. In this dissertation, we investigate physical design methodologies for 3D ICs with primary focus on two areas: low power 3D clock tree design, and reliability degradation modeling and management. Clock trees are essential parts for digital system which dissipate a large amount of power due to high capacitive loads. The majority of existing 3D clock tree designs focus on minimizing the total wire length, which produces sub-optimal results for power optimization. In this dissertation, we formulate a 3D clock tree design flow which directly optimizes for clock power. Besides, we also investigate the design methodology for clock gating a 3D clock tree, which uses shutdown gates to selectively turn off unnecessary clock activities. Different from the common assumption in 2D ICs that shutdown gates are cheap thus can be applied at every clock node, shutdown gates in 3D ICs introduce additional control TSVs, which compete with clock TSVs for placement resources. We explore the design methodologies to produce the optimal allocation and placement for clock and control TSVs so that the clock power is minimized. We show that the proposed synthesis flow saves significant clock power while accounting for available TSV placement area. Vertical integration also brings new reliability challenges including TSV's electromigration (EM) and several other reliability loss mechanisms caused by TSV-induced stress. These reliability loss models involve complex inter-dependencies between electrical and thermal conditions, which have not been investigated in the past. In this dissertation we set up an electrical/thermal/reliability co-simulation framework to capture the transient of reliability loss in 3D ICs. We further derive and validate an analytical reliability objective function that can be integrated into the 3D placement design flow. The reliability aware placement scheme enables co-design and co-optimization of both the electrical and reliability property, thus improves both the circuit's performance and its lifetime. Our electrical/reliability co-design scheme avoids unnecessary design cycles or application of ad-hoc fixes that lead to sub-optimal performance. Vertical integration also enables stacking DRAM on top of CPU, providing high bandwidth and short latency. However, non-uniform voltage fluctuation and local thermal hotspot in CPU layers are coupled into DRAM layers, causing a non-uniform bit-cell leakage (thereby bit flip) distribution. We propose a performance-power-resilience simulation framework to capture DRAM soft error in 3D multi-core CPU systems. In addition, a dynamic resilience management (DRM) scheme is investigated, which adaptively tunes CPU's operating points to adjust DRAM's voltage noise and thermal condition during runtime. The DRM uses dynamic frequency scaling to achieve a resilience borrow-in strategy, which effectively enhances DRAM's resilience without sacrificing performance. The proposed physical design methodologies should act as important building blocks for 3D ICs and push 3D ICs toward mainstream acceptance in the near future.