LCA-GIS Integrated approach for a Sustainable Land Use Under Energy Crops

In genere, negli studi di vocazionalità delle colture, vengono presi in considerazione solo variabili ambientali pedo-climatiche. La coltivazione di una coltura comporta anche un impatto ambientale derivante dalle pratiche agronomiche ed il territorio può essere più o meno sensibile a questi impatti in base alla sua vulnerabilità. In questo studio si vuole sviluppare una metodologia per relazionare spazialmente l’impatto delle colture con le caratteristiche sito specifiche del territorio in modo da considerare anche questo aspetto nell’allocazione negli studi di vocazionalità. LCA è stato utilizzato per quantificare diversi impatti di alcune colture erbacee alimentari e da energia, relazionati a mappe di vulnerabilità costruite con l’utilizzo di GIS, attraverso il calcolo di coefficienti di rischio di allocazione per ogni combinazione coltura-area vulnerabile. Le colture energetiche sono state considerate come un uso alternativo del suolo per diminuire l’impatto ambientale. Il caso studio ha mostrato che l’allocazione delle colture può essere diversa in base al tipo e al numero di impatti considerati. Il risultato sono delle mappe in cui sono riportate le distribuzioni ottimali delle colture al fine di minimizzare gli impatti, rispetto a mais e grano, due colture alimentari importanti nell’area di studio. Le colture con l’impatto più alto dovrebbero essere coltivate nelle aree a vulnerabilità bassa, e viceversa. Se il rischio ambientale è la priorità, mais, colza, grano, girasole, e sorgo da fibra dovrebbero essere coltivate solo nelle aree a vulnerabilità bassa o moderata, mentre, le colture energetiche erbacee perenni, come il panico, potrebbero essere coltivate anche nelle aree a vulnerabilità alta, rappresentando cosi una opportunità per aumentare la sostenibilità di uso del suolo rurale. Lo strumento LCA-GIS inoltre, integrato con mappe di uso attuale del suolo, può aiutare a valutarne il suo grado di sostenibilità ambientale.

A multiparental cross population for mapping QTL for relevant agronomic traits in durum wheat (Triticum durum Desf.)

Multiparental cross designs for mapping quantitative trait loci (QTL) in crops are efficient alternatives to conventional biparental experimental populations because they exploit a broader genetic basis and higher mapping resolution. We describe the development and deployment of a multiparental recombinant inbred line (RIL) population in durum wheat (Triticum durum Desf.) obtained by crossing four elite cultivars characterized by different traits of agronomic value. A linkage map spanning 2,663 cM and including 7,594 single nucleotide polymorphisms (SNPs) was produced by genotyping 338 RILs with a wheat-dedicated 90k SNP chip. A cluster file was developed for correct allele calling in the framework of the tetraploid durum wheat genome. Based on phenotypic data collected over four field experiments, a multi-trait quantitative trait loci (QTL) analysis was carried out for 18 traits of agronomic relevance (including yield, yield-components, morpho-physiological and seed quality traits). Across environments, a total of 63 QTL were identified and characterized in terms of the four founder haplotypes. We mapped two QTL for grain yield across environments and 23 QTL for grain yield components. A novel major QTL for number of grain per spikelet/ear was mapped on chr 2A and shown to control up to 39% of phenotypic variance in this cross. Functionally different QTL alleles, in terms of direction and size of genetic effect, were distributed among the four parents. Based on the occurrence of QTL-clusters, we characterized the breeding values (in terms of effects on yield) of most of QTL for heading and maturity as well as yield component and quality QTL. This multiparental RIL population provides the wheat community with a highly informative QTL mapping resource enabling the dissection of the genetic architecture of multiple agronomic relevant traits in durum wheat.

Diversity and Genetic structure of the Spanish collection of durum wheat (Triticum turgidum L) landraces

The objectives of this study were to assess diversity and genetic structure of a collection of Spanish durum wheat (Triticum turgidum L) landraces, using SSRs, DArTs and gliadin-markers, and to correlate the distribution of diversity with geographic and climatic features, as well as agro-morphological traits. A high level of diversity was detected in the genotypes analyzed, which were separated into nine populations with a moderate to great genetic divergence among them. The three subspecies taxa, dicoccon, turgidum and durum, present in the collection, largely determined the clustering of the populations. Genotype variation was lower in dicoccon (one major population) and turgidum (two major populations) than in durum (five major populations). Genetic differentiation by the agro-ecological zone of origin was greater in dicoccon and turgidum than in durum. DArT markers revealed two geographic substructures, east-west for dicoccon and northeast-southwest for turgidum. The ssp. durum had a more complex structure, consisting of seven populations with high intra-population variation. DArT markers allowed the detection of subgroups within some populations, with agro-morphological and gliadin differences, and distinct agro-ecological zones of origin. Two different phylogenetic groups were detected; revealing that some durum populations were more related to ssp. turgidum from northern Spain, while others seem to be more related to durum wheats from North Africa

Creation and Validation of the Spanish Durum Wheat Core Collection.

Spanish wheat (Triticum spp.) landraces have a considerable polymorphism, containing many unique alleles, relative to other collections. The existence of a core collection is a favored approach for breeders to efficiently explore novel variation and enhance the use of germplasm. In this study, the Spanish durum wheat (Triticum turgidum L.) core collection (CC) was created using a population structure–based method, grouping accessions by subspecies and allocating the number of genotypes among populations according to the diversity of simple sequence repeat (SSR) markers. The CC of 94 genotypes was established, which accounted for 17% of the accessions in the entire collection. An alternative core collection (CH), with the same number of genotypes per subspecies and maximizing the coverage of SSR alleles, was assembled with the Core Hunter software. The quality of both core collections was compared with a random core collection and evaluated using geographic, agromorphological, and molecular marker data not previously used in the selection of genotypes. Both core collections had a high genetic representativeness, which validated their sampling strategies. Geographic and agromorphological variation, phenotypic correlations, and gliadin alleles of the original collection were more accurately depicted by the CC. Diversity arrays technology (DArT) markers revealed that the CC included genotypes less similar than the CH. Although more SSR alleles were retained by the CH (94%) than by the CC (91%), the results showed that the CC was better than CH for breeding purposes.

Growth rate and TRI5 gene expression profiles of Fusarium equiseti strains isolated from Spanish cereals cultivated on wheat and barley media at different environmental conditions

Fusarium equiseti is a toxigenic species that often contaminates ce real crops from diverse climatic regions such as Northern and Southern Europe. Previous results suggested the existence of two distinct populations within this species with differences in toxin pro file which largely corresponded to North and South Europe (Spain). In this work, growth rate profiles of 4 F. equiseti strains isolated from different cereals and distinct Spanish regions were determined on wheat and barley based media at a range of temperatures (15, 20, 25, 30, 35 and 40 °C) and water potentialregimens(−0.7,−2.8,−7.0,and −9.8MPa,correspondingto 0.99,0.98,0.95 and 0.93aw values).Growth was observed at all temperatures except at 40 °C, and at all the solute potential values except at−9.8 MPa when combined with 15 °C. Optimal growth was observed at 20– 30 °C and −0.7/−2.8 MPa. The effect of these factors on trichothecene biosynthesis was examined on a F. equiseti strain using a newly developed real time RT-PCR protocol to quantify TRI5 gene expression at 15, 25 and 35 °C and −0.7, −2.8, − 7.0 and −9.8 MPa on wheat and barley based media. Induction of TRI5 expression was detected between 25 and 35 °C and −0.7 and − 2.8 MPa, with maximum values at 35 °C and −2.8 MPa being higher in barley than in wheat medium. These results appeared to be consistent with a population well adapted to the present climatic conditions and predicted scenarios for Southern Europe and suggested some differences depending on the cereal considered. These are also discussed in relation to other Fusarium species co-occurring in cereals grown in this region and to their significance for prediction and control strategies of toxigenic risk in future scenarios of climate change for this region.

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.

Review of the effects of disaster conditions on wheat, soybeans, and feed grains production : hearings before the Subcommittee on Wheat, Soybeans, and Feed Grains of the Committee on Agriculture, House of Representatives, One Hundred First Congress, first session, March 23 and April 6, 1989; May 19, 1989, Amarillo, TX, and May 20, 1989, Great Bend, KS.

"Serial no. 101-7."

Hard red spring and durum wheat quality /

Mode of access: Internet.

Stem sawflies of economic importance in grain crops in the United States,

"Literature cited": p. 37-50.

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Piggery pond sludge as a nitrogen source for crops - 2. Assay of wet and stockpiled piggery pond sludge by successive cereal crops or direct measurement of soil available N

The appropriate use of wastes is a significant issue for the pig industry due to increasing pressure from regulatory authorities to protect the environment from pollution. Nitrogen contained in piggery pond sludge ( PPS) is a potential source of supplementary nutrient for crop production. Nitrogen contribution following the application of PPS to soil was obtained from 2 field experiments on the Darling Downs in southern Queensland on contrasting soil types, a cracking clay ( Vertosol) and a hardsetting sandy loam (Sodosol), and related to potentially mineralisable N from laboratory incubations conducted under controlled conditions and NO3- accumulation in the field. Piggery pond sludge was applied as-collected ( wet PPS) and following stockpiling to dry ( stockpiled PPS). Soil NO3- levels increased with increased application rates of wet and stockpiled PPS. Supplementary N supply from PPS estimated by fertiliser equivalence was generally unsatisfactory due to poor precision with this method, and also due to a high level of NO3- in the clay soil before the first assay crop. Also low recoveries of N by subsequent sorghum ( Sorghum bicolor) and wheat ( Triticum aestivum) assay crops at the 2 sites due to low in-crop rainfall in 1999 resulted in low apparent N availability. Over all, 29% ( range 12 - 47%) of total N from the wet PPS and 19% ( range 0 - 50%) from the stockpiled PPS were estimated to be plant-available N during the assay period. The high concentration of NO3- for the wet PPS application on sandy soil after the first assay crop ( 1998 barley, Hordeum vulgare) suggests that leaching of NO3- could be of concern when high rates of wet PPS are applied before infrequent periods of high precipitation, due primarily to the mineral N contained in wet PPS. Low yields, grain protein concentrations, and crop N uptake of the sorghum crop following the barley crop grown on the clay soil demonstrated a low residual value of N applied in PPS. NO3- in the sandy soil before sowing accounted for 79% of the variation in plant N uptake and was a better index than anaerobically mineralisable N ( 19% of variation explained). In clay soil, better prediction of crop N uptake was obtained when both anaerobically mineralisable N (39% of variation explained) and soil pro. le NO3- were used in combination (R-2 = 0.49).

Changes in the properties of a Vertisol and responses of wheat after compaction with harvester traffic

Soil compaction has been recognised as the greatest problem in terms of damage to Australia's soil resource. Compaction by tractor and harvester tyres, related to trafficking of wet soil, is one source of the problem. In this paper an array of soil properties was measured before and immediately after the application of a known compaction force to a wet Vertisol, A local grain harvester was used on soil that was just trafficable; a common scenario at harvest. The primary aim was to determine the changes in various soil properties in order to provide a benchmark against which the effectiveness of future remedial treatments could be evaluated. A secondary aim was a comparison of the measurements' efficiency to assess a soil's structural degradation status. Also assessed was the subsequent effect of the applied compaction on wheat growth and yield in the following cropping season. Nine of the soil properties measured gave statistically significant differences as a result of the soil compaction. Differences were mostly restricted to the top 0.2 m of the soil. The greatest measured depth of effect was decreased soil porosity to 0.4 m measured from intact soil clods. There was 72% emergence of the wheat crop planted into the compact soil and 93% in the uncompact soil. Wheat yield, however, was not affected by the compaction. This may demonstrate that wheat, growing on a full profile of stored soil water as did the current crop, may be little affected by compaction, Also, wheat may have potential to facilitate rapid repair of the damage in a Vertisol such as the current soil by drying the topsoil between rainfall events so increasing shrinking and swelling cycles. If this is true, then sowing a suitable crop species in a Vertisol may be a better option than tillage for repairing compaction damage by agricultural traffic. (C) 2000 Elsevier Science B.V. All rights reserved.

Structure repair of a compacted vertisol with wet-dry cycles and crops

We hypothesized that the four rotation crops: wheat (Triticum aestivum L.), sorghum [Sorghum bicolor (L.) Merr.], lablab [Lablab purpureus (L.) Sweet] and mung bean [ Vigna radiata (L.) R. Wilczek] differ in their ability to repair soil structure. The study was conducted on a Typic Haplustert, Queensland, Australia, locally termed a Black Earth and considered a prime cropping soil. Large (0.5-m depth by 0.3-m diam.) soil cores, collected from compacted wheel furrows in an irrigated cotton (Gossypium hirsutum L.) field, were subjected to three, six, or nine wet-dry cycles that simulated local flood irrigation practices. After each cycle, soil profiles were sampled for clod bulk density, image analysis of soil structure, and evapotranspiration. Generally, all crops improved soil structure over the initial field condition but lablab and mung bean gave improvements to greater depths and more rapidly than wheat and sorghum. Mung bean and lablab caused up to a threefold increase in clod porosity in the 0.1- to 0.4-m soil layer after only three wet-dry cycles, whereas sorghum required nine wet-dry cycles to increase clod porosity in only the 0.2- to 0.3-m layer, and wheat gave no improvement even after nine wet-dry cycles. Image analysis of soil structure showed that lablab and mung bean rapidly (by three wet-dry cycles) produced smaller peds with more interconnected pore space than wheat and sorghum. By nine wet-dry cycles, sorghum achieved deep cracking of the soil but the material between the cracks remained large and dense. Evapotranspiration was double under lablab and mung bean compared with wheat and sorghum. Our results indicate greater cycles of wetting and drying under lablab and mung bean than wheat and sorghum that have led to rapid repair of soil compaction.

Isolation, characterization and discovery of new alleles of sHsp genes in durum wheat (Triticum durum Desf.)

Gli organismi vegetali mostrano una notevole capacità di adattamento alle condizioni di stress e lo studio delle componenti molecolari alla base dell'adattamento in colture cerealicole di interesse alimentare, come il frumento, è di particolare interesse per lo studio di varietà che consentano una buona produzione con basso input anche in condizioni ambientali non ottimali. L'esposizione delle colture cerealicole a stress termico durante determinate fasi del ciclo vitale influisce negativamente sulla resa e sulla qualità, a questo fine è necessario chiarire le basi genetiche e molecolari della termotolleranza per identificare geni e alleli vantaggiosi da impiegare in programmi di incrocio volti al miglioramento genetico. Numerosi studi dimostrano il coinvolgimento delle sHSP a localizzazione cloroplastica (in frumento sHSP26) nel meccanismo di acquisizione della termotolleranza e la loro interazione con diverse componenti del fotosistema II (PSII) che determinerebbe un’azione protettiva in condizioni di stress termico e altri tipi di stress. Lo scopo del progetto è quello di caratterizzare in frumento duro nuove varianti alleliche correlate alla tolleranza a stress termico mediate l'utilizzo del TILLING (Target Induced Local Lesion In Genome), un approccio di genetica inversa che prevede la mutagenesi e l'identificazione delle mutazioni indotte in siti di interesse. Durante la tesi sono state isolate e caratterizzate 3 sequenze geniche complete per smallHsp26 denominate TdHsp26-A1; TdHsp26-A2; TdHsp26-B1 e un putativo pseudogene denominato TdHsp26-A3. I geni isolati sono stati usati come target in analisi di TILLING in due popolazioni di frumento duro mutagenizzate con EMS (EtilMetanoSulfonato). Nel nostro studio sono stati impiegati due differenti approcci di TILLING: un approccio di TILLING classico mediante screening con High Resolution Melting (HRM) e un approccio innovativo che sfrutta un database di TILLING recentemente sviluppato. La popolazione di mutanti cv. Kronos è stata analizzata per la presenza di mutazioni in tutti e tre i geni individuati mediante ricerca online nel database di TILLING, il quale sfrutta la tecnica dell’exome capture sulla popolazione di TILLING seguito da sequenziamento ad alta processività. Attraverso questa tecnica sono state individuate, nella popolazione mutagenizzata di frumento duro cv. Kronos, 36 linee recanti mutazioni missenso. Contemporaneamente lo screening con HRM, effettuato su 960 genotipi della libreria di TILLING di frumento duro cv. Cham1 ha consentito di individuare mutazioni in una regione di 211bp di interesse funzionale del gene TdHsp26-B1, tra le quali 3 linee mutanti recanti mutazioni missenso in omozigosi. Alcune mutazioni missenso individuate sui due geni TdHsp26-A1 e TdHsp26-B1 sono state confermate in vivo nelle piante delle rispettive linee mutanti generando marcatori codominanti KASP (Kompetitive Allele Specific PCR) con cui è stato possibile verificare anche il grado di zigosità di tali mutazioni. Al fine di ridurre il numero di mutazioni non desiderate nelle linee risultate più interessanti, è stato eseguito il re-incrocio dei mutanti con i relativi parentali wild type ed inoltre sono stati generati alcuni doppi mutanti che consentiranno di comprendere meglio i meccanismi molecolari presieduti da questa classe genica. Gli individui F1 degli incroci sono stati poi genotipizzati con i medesimi marcatori KASP specifici per la mutazione di interesse per verificare la buona riuscita dell’incrocio. Questo approccio ha permesso di individuare ed implementare risorse genetiche utili ad intraprendere studi funzionali relativi al ruolo di smallHSP plastidiche implicate nella acquisizione di termotolleranza in frumento duro e di generare marcatori potenzialmente utili in futuri programmi di breeding.