Climate Change Impacts on Maize and Dry Bean Yields of smallholder farmers in Honduras

The rotation maize and dry bean provides the main food supply of smallholder farmers in Honduras. Crop model assessment of climate change impacts (2070?2099 compared to a 1961?1990 baseline) on a maize?dry bean rotation for several sites across a range of climatic zones and elevations in Honduras. Low productivity systems, together with an uncertain future climate, pose a high level of risk for food security. The cropping systems simulation dynamic model CropSyst was calibrated and validated upon field trail site at Zamorano, then run with baseline and future climate scenarios based upon general circulation models (GCM) and the ClimGen synthetic daily weather generator. Results indicate large uncertainty in crop production from various GCM simulations and future emissions scenarios, but generally reduced yields at low elevations by 0 % to 22 % in suitable areas for crop production and increased yield at the cooler, on the hillsides, where farming needs to reduce soil erosion with conservation techniques. Further studies are needed to investigate strategies to reduce impacts and to explore adaptation tactics.

Cover crops effect on farm benefits and nitrate leaching: Linking economic and environmental analysis.

Introducing cover crops (CC) interspersed with intensively fertilized crops in rotation has the potential to reduce nitrate leaching. This paper evaluates various strategies involving CC between maize and compares the economic and environmental results with respect to a typical maize?fallow rotation. The comparison is performed through stochastic (Monte-Carlo) simulation models of farms? profits using probability distribution functions (pdfs) of yield and N fertilizer saving fitted with data collected from various field trials and pdfs of crop prices and the cost of fertilizer fitted from statistical sources. Stochastic dominance relationships are obtained to rank the most profitable strategies from a farm financial perspective. A two-criterion comparison scheme is proposed to rank alternative strategies based on farm profit and nitrate leaching levels, taking the baseline scenario as the maize?fallow rotation. The results show that when CC biomass is sold as forage instead of keeping it in the soil, greater profit and less leaching of nitrates are achieved than in the baseline scenario. While the fertilizer saving will be lower if CC is sold than if it is kept in the soil, the revenue obtained from the sale of the CC compensates for the reduced fertilizer savings. The results show that CC would perhaps provide a double dividend of greater profit and reduced nitrate leaching in intensive irrigated cropping systems in Mediterranean regions.

Improving simulation of soil water balance using lysimeter observations in a semiarid climate.

Water balance simulation in cropping systems is a very useful tool to study how water can be used efficiently. However this requires that models simulate an accurate water balance. Comparing model results with field observations will provide information on the performance of the models. The objective of this study was to test the performance of DSSAT model in simulating the water balance by comparing the simulations with observed measurements. The soil water balance in DSSAT uses a one dimensional ?tipping bucket? soil water balance approach where available soil water is determined by the drained upper limit (DUL), lower limit (LL) and saturated water content (SAT). A continuous weighing lysimeter was used to get the observed values of drainage and evapotranspiration (ET). An automated agrometeorological weather station close to the lisymeter was also used to record the climatic data. The model simulated accurately the soil water content after the optimization of the soil parameters. However it was found the inability of the model to capture small changes in daily drainage and ET. For that reason simulated cumulative values had larger errors as the time passed by. These results suggested the need to compare outputs of DSSAT and some hydrological model that simulates soil water movement with a more mechanistic approach. The comparison of the two models will allow us to find which mechanism can be modified or incorporated in DSSAT model to improve the simulations.

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.

Levantamento de ocorrência, alternativas de manejo, mecanismos de resistência e herança genética do capim-amargoso (Digitaria insularis) resistente ao herbicida glyphosate

O glyphosate é o principal herbicida utilizado no manejo de plantas daninhas na agricultura, aplicado em alguns sistemas de forma repetitiva ao longo de cada ano. Esta prática selecionou biótipos resistentes de espécies de plantas daninhas, sendo o capim-amargoso (Digitaria insularis) selecionado no Brasil. Portanto, se tornam necessários estudos para entender, manejar e reduzir a infestação do capim-amargoso resistente ao glyphosate. Dessa forma, esta pesquisa foi desenvolvida com os objetivos de: (i) mapear áreas do Brasil com possíveis infestações de capim-amargoso resistente ao glyphosate; (ii) avaliar alternativas químicas de seu manejo; (iii) elucidar os mecanismos de resistência ao glyphosate e; (iv) avaliar a herança genética dos genes que conferem resistência ao glyphosate. Para o desenvolvimento dos experimentos foram coletadas sementes de biótipos potencialmente resistentes de diversas regiões do Brasil onde ocorreram falhas de controle de D. insularis após a aplicação de glyphosate. Na primeira etapa da pesquisa foram realizados experimentos para determinação de uma dose discriminatória de triagementre as populações resistentes e suscetíveis ao glyphosate, através de curvas de dose-resposta, para identificar a resistência ao Glyphosate, sendo que estes dados foram utilizados para mapear a ocorrência de biótipos resistentes em algumas regiões do país. Na segunda etapa foi conduzido um experimento em casa-de-vegetação visando encontrar herbicidas alternativos ao Glyphosate para controle do capim-amargoso, utilizando herbicidas recomendados para as culturas do milho e algodão, tanto em condições de aplicação de pré como em pós-emergência da planta daninha. Na terceira etapa foram realizados ensaios para determinar a existência de absorção e translocação diferencial do glyphosate em biótipos suscetíveis e resistentes, juntamente com a análise molecular para comparar a região 106 do gene que codifica a EPSPs nestes biótipos. Por fim um estudo de polinização cruzada foi conduzido para avaliar se genes de resistência ao glyphosate são transferidos para a geração seguinte após inflorescências de biótipos suscetíveis serem acondicionadas com as de biótipos resistentes, submetendo a geração seguinte a experimentos de curva de dose-resposta com o glyphosate. Através do modelo de curva dose-resposta do programa estatístico R, determinou-se a dose de 960 g e.a ha-1, como a dose utilizada para triagem dos biótipos oriundos de diferentes regiões do Brasil. Com isto foram gerados mapas indicando a presença ou ausência de resistência ao herbicida, sendo que as região oeste do Paraná e sul do Mato Grosso do Sul apresentam maior número de localidades com a presença de biótipos resistentes. As alternativas de controle viáveis como pós-emergentes no estádio de um a dois perfilhos, foram os herbicidas Nicosulfuron, Imazapic + Imazapyr, Atrazine, Haloxifop-methyl e Tepraloxydim. Na pré-emergência do capim-amargoso os herbicidas Atrazine, Isoxaflutole, S-metolachlor, Clomazone, Diuron e Flumioxazin se apresentaram como eficazes para o controle desta espécie. Os resultados do experimento de absorção, translocação e comparação da região 106 não mostraram diferenças entre os biótipos resistente e suscetível. O experimento sobre cruzamento entre biótipos resistente e suscetível determinou a espécie D. insularis como autógama e sem transferência de genes que causam a resistência ao glyphosate.

Effects of cereal species, legume species, and nitrogen on no-till winter wheat and rye grown with perennial forage legume living mulches /

Thesis (Ph. D.)--Cornell University, May, 1988.

Tillage options for conservation farmers.

Shipping list no.: 89-80-P.

Sugarcane water use from shallow water tables: implications for improving irrigation water use efficiency

The resource potential of shallow water tables for cropping systems has been investigated using the Australian sugar industry as a case study. Literature concerning shallow water table contributions to sugarcane crops has been summarised, and an assessment of required irrigation for water tables to depths of 2 m investigated using the SWIMv2.1 soil water balance model for three different soils. The study was undertaken because water availability is a major limitation for sugarcane and other crop production systems in Australia and knowledge on how best to incorporate upflow from water tables in irrigation scheduling is limited. Our results showed that for the three soils studied (representing a range of permeabilities as defined by near-saturated hydraulic conductivities), no irrigation would be required for static water tables within 1 m of the soil surface. Irrigation requirements when static water tables exceeded 1 m depth were dependent on the soil type and rooting characteristics (root depth and density). Our results also show that the near-saturated hydraulic conductivities are a better indicator of the ability of water tables below 1 m to supply sufficient upflow as opposed to soil textural classifications. We conclude that there is potential for reductions in irrigation and hence improvements in irrigation water use efficiency in areas where shallow water tables are a low salinity risk: either fresh, or the local hydrology results in net recharge. (C) 2003 Elsevier B.V. All rights reserved.

Parthenium weed: a potential major weed for agro-ecosystems in Pakistan

Parthenium weed (Parthenium hysterophorus L.) is a new and potentially major weed in Pakistan. This weed, originating from central America, is now a major weed in many regions of the world including Eastern Africa, India, parts of South East Asia and Australia. Presumably its recent arrival in Pakistan has been due to its movement from India, but this has yet to be established. In Australia it has been present for about 50 years, in which time it has spread from isolated infestations to establish core populations in central Queensland with scattered and isolated plants occurring south into New South Wales and north-west into the Northern Territory. Its spread in Pakistan is likely to be much more rapid, but lessons learnt in Australia will be of great value for weed managers in Pakistan. This annual herb has the potential to spread to all medium rainfall rangeland, dairy and summer cropping areas in Pakistan. In Australia its main effect is upon livestock production, but it is also causing health concerns in regional communities. However, in India it has also had a significant impact in cropping systems. To help coordinate actions on its management in Australia, a National Weeds Program has created a Parthenium Weed Management Group (PWMG) and under this group a Parthenium Weed Research Group (PWRG) has been formed. Funding coming from this national program and other sources has supported the PWRG to undertake a collaborative and technology exchange research program in two main areas: 1) biology and ecology and 2) management; while the PWMG has focused on community awareness and the production of various extension and management packages. Research in the area of biology and ecology has included studies on the evaluation of competitive plants to displace parthenium weed, the use of process-based simulation models to monitor and predict future spread and abundance under present and future climate conditions, the effect of the weed on human health and the ecology of its seed bank. Management research has focussed on the development of biological control approaches using plant-feeding insects and pathogens. The effectiveness of biological control is also being monitored through long term studies on seed bank size and dynamics. The use of fire as another potential management tool is also being evaluated. In addition to this important research, an effort has also been made to spread the most important findings and management outcomes to the wider community through an extension and education program driven by the PWMG. These developments within Australia, in parthenium weed management, will be of great help to P

Peanut farmers experience with FARMSCAPE in peninsular India

Researchers and extension officers collaborated with farmers in addressing peanut cropping and sowing decisions using on-farm experiments and cropping systems simulation in the Pollachi region of Tamil Nadu, India. The most influential variable affecting the peanut productivity in this irrigated region regard sowing date. During the 1998-1999 rabi (post rainy) season, three farmers fields in villages in Pollachi region were selected and monitored. The APSIM model was used to simulate the effect of sowing date. The APSIM-Peanut module simulation demonstrated close correspondence with the field observation in predicting yield. The model predicted that December sowing resulted in higher yield than January sowing due to longer pod filling period, and this was confirmed by farmer experience. The farmers and extension officers became comfortable with their role as owners of the collaborative experiments and custodians of the learning environment.

Consórcio de cártamo e feijão caupi: alternativa para a produção de biodiesel na agricultura familiar

The new development strategies should operate mainly in the areas of energy efficiency and sustainable agriculture. Thus, the substitution of fossil fuels with biofuels, such as biodiesel, is increasingly on the agenda. The cultivation of oilseed plants for biodiesel production must take place in integrated systems that enable best environmental benefits and are more economically significant. The objectives of this study were to assess the morphological, anatomic, and physiological characteristics of safflower (Carthamus tinctorius L., promising oilseed for biodiesel production) grown in monoculture and intercropping with cowpea bean (Vigna unguiculata L. Walp.); and identify socioeconomic family farmers and verify their acceptance about safflower as an energy crop. The methodology used for the analysis of safflower growth in monoculture and intercropped with beans, were morphoanatomical and histochemical analyzes, made with samples of plants grown in the field in two cropping systems throughout the range of the life cycle of these plants. There were no changes in growth and anatomy of plants, even in the consortium, which is satisfactory to indicate the intercropping system for those crops and can be a good alternative for the family farmer, who may have safflower as a source of income without giving up planting their livelihood. To check the acceptance of safflower by farmers, interviews were made to family farmers by Canudos agrovila in Ceará-Mirim/RN. It was noticed that many of them accept the introduction of safflower as oil crop, although unaware of the species, and that, being more resistant to drought, safflower help in the stability of families who depend on the weather conditions for success their current crops. In general, it is concluded that safflower has features that allows it to be grown in consortium for biodiesel production combined with the production of food, such as cowpea, and can be used enabling better development for family farmers.

Biomass, quality traits and methane production of extensive grassland: biodiversity effects and sensor approaches

Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment

Rice-Infecting Pseudomonas Genomes Are Highly Accessorized and Harbor Multiple Putative Virulence Mechanisms to Cause Sheath Brown Rot

Sheath rot complex and seed discoloration in rice involve a number of pathogenic bacteria that cannot be associated with distinctive symptoms. These pathogens can easily travel on asymptomatic seeds and therefore represent a threat to rice cropping systems. Among the rice-infecting Pseudomonas, P. fuscovaginae has been associated with sheath brown rot disease in several rice growing areas around the world. The appearance of a similar Pseudomonas population, which here we named P. fuscovaginae-like, represents a perfect opportunity to understand common genomic features that can explain the infection mechanism in rice. We showed that the novel population is indeed closely related to P. fuscovaginae. A comparative genomics approach on eight rice-infecting Pseudomonas revealed heterogeneous genomes and a high number of strain-specific genes. The genomes of P. fuscovaginae-like harbor four secretion systems (Type I, II, III, and VI) and other important pathogenicity machinery that could probably facilitate rice colonization. We identified 123 core secreted proteins, most of which have strong signatures of positive selection suggesting functional adaptation. Transcript accumulation of putative pathogenicity-related genes during rice colonization revealed a concerted virulence mechanism. The study suggests that rice-infecting Pseudomonas causing sheath brown rot are intrinsically diverse and maintain a variable set of metabolic capabilities as a potential strategy to occupy a range of environments.

LATERAL BRANCHING OXIDOREDUCTASE acts in the final stages of strigolactone biosynthesis inArabidopsis

Strigolactones are a group of plant compounds of diverse but related chemical structures. They have similar bioactivity across a broad range of plant species, act to optimize plant growth and development, and promote soil microbe interactions. Carlactone, a common precursor to strigolactones, is produced by conserved enzymes found in a number of diverse species. Versions of the MORE AXILLARY GROWTH1 (MAX1) cytochrome P450 from rice and Arabidopsis thaliana make specific subsets of strigolactones from carlactone. However, the diversity of natural strigolactones suggests that additional enzymes are involved and remain to be discovered. Here, we use an innovative method that has revealed a missing enzyme involved in strigolactone metabolism. By using a transcriptomics approach involving a range of treatments that modify strigolactone biosynthesis gene expression coupled with reverse genetics, we identified LATERAL BRANCHING OXIDOREDUCTASE (LBO), a gene encoding an oxidoreductase-like enzyme of the 2-oxoglutarate and Fe(II)-dependent dioxygenase superfamily. Arabidopsis lbo mutants exhibited increased shoot branching, but the lbo mutation did not enhance the max mutant phenotype. Grafting indicated that LBO is required for a graft-transmissible signal that, in turn, requires a product of MAX1. Mutant lbo backgrounds showed reduced responses to carlactone, the substrate of MAX1, and methyl carlactonoate (MeCLA), a product downstream of MAX1. Furthermore, lbo mutants contained increased amounts of these compounds, and the LBO protein specifically converts MeCLA to an unidentified strigolactone-like compound. Thus, LBO function may be important in the later steps of strigolactone biosynthesis to inhibit shoot branching in Arabidopsis and other seed plants.