Assessing genotypic variation for cold tolerance in soybean

Increasing world demand for soybean has resulted in the expansion of soybean cropping acreage through the development of varieties suitable for a wide range of latitudes. Chilling stress is one of the major constrains for crop establishment and yield in high latitudes. This project aims to assess genotypic variation for cold tolerance in European soybean varieties. Germination, emergence and physiological traits related to seedling growth under cold conditions will be tested in controlled environments. The results obtained will be used as inputs in simulation models to assess the environmental and economic impact of growing soybean in new regions, and ultimately, may also help to detect target traits for breeding improvement. Based on the probabilities of achieving certain yields in specific regions, agri-businesses will be better informed to make decisions on whether to include soybean in their crop rotations.

A framework to analyse the vulnerability of farming systems to water stress

Water availability is a critical determinant of crop productivity for rain-fed agriculture. Inter-annual variability in crop yields is largely explained by annual rainfall. However, crop management and soil properties/condition ultimately determine whether water supply is adequate, insufficient or excessive to meet crop requirements. The aim of this project is to design an ecohydrological framework to analyse the vulnerability of farming systems to drought/flooding events that affect episodically agricultural production. The focus is to identify climatic factors (whose frequency can be estimated with probabilistic analyses) that determine the inherent risk of drought/floods for each particular system; measurable soil factors that can increase/reduce the system vulnerability to climate; and crop/land cover factors that can be managed to regulate water-use in a given season. The analysis of these factors and their integration into robust crop-soil-water models will help to identify effective mechanisms to increase agricultural system productivity and resilience.

Earth monitoring tools to improve the understanding and management of flooding

Historically, floods have been perceived as consequences of climatic events, however in the last two decades a more reciprocal image has emerged, in which terrestrial ecosystems and the people who manage them can leave a deep imprint on the hydrological system (for example, discharge in rivers and water tables). The general objective of this project is to improve the characterization and understanding of floods and their regional impacts, articulating very diverse sources of earth data. This is of particular interest in the Chaco-Pampean plains of Argentina, Paraguay and Bolivia, the core of grain production of the region, and where the replacement of natural vegetation (dry forest in Chaco and grasslands in Pampas) by crops is producing strong hydrological shifts.

This project will benefit from links with UK-based companies working in the field of geospatial technology, particularly businesses that are concerned with the use of remotely-sensed data and spatial analysis in land use management and agronomy. It will also interface with consultancies that are working in environmental management and catchment hydrology.

Low-cost multi-sensor stations for ammonia monitoring to increase agricultural productivity and to reduce environmental impact.

Tropospheric ammonia (NH3) is mainly emitted by agricultural activities causing great environmental impacts such as atmospheric pollution, reduction of biodiversity. Ammonia can be dangerous for human health even at very low concentration. Ammonia losses also have great agronomic and economic impacts for farmers, as they reduce nitrogen use efficiency. Thus, it is necessary to monitor ammonia emissions with sensitive and precise devices. Moreover, these devices must be simple, small, with the possibility of mass and low-cost production. Using cheap commercial electronic components, multi-sensor stations will be designed to manufacture prototypes. These stations will have remote-control by wireless networks in order to achieve real-time sensing. The station designed for ammonia monitoring/control will be deployed in different agricultural zones where the soils were treated with organic or synthetic fertilizers in order to measure the differences in nitrogen losses. Some of the physically recorded variables will be temperature, humidity, conductivity and atmospheric pressure. The purpose of manufactured low-cost stations is to create the opportunity of monitoring large agricultural areas by placing a large number of stations along the study zones.

Understanding hydrological processes to improve rainwater harvesting in natural and human-dominated livestock systems

Sustainable food production is one of the greatest challenges for arid and semi-arid regions of the planet. The livestock production of these regions is based on consuming the small fraction of forage that native dry forests and, in some cases planted pastures offer. The main limitation of these production systems is the lack of surface freshwater or groundwater sources for drinking supply. This limitation is partially solved by rainwater harvesting in human-made impoundments (or small dykes). The main objective of this project is to understand the rainwater harvesting process in the southern edge of Dry Chaco, one of the largest and flattest semiarid rangelands globally where dykes are widely disseminated throughout the region. To address this objective, I will combine field measurements with hydrological modelling tools (e.g. ‘CAPTAIN’ simulation model developed at Lancaster University). The expected results will help understand the relation between rainfall and landscape runoff process (water inputs to dykes) and between atmospheric demand and water storage (water outputs from dykes). At the end of this project, I will be able to propose different technological alternatives that might enhance rainwater harvesting efficiency, to mitigate water shortages that constrain livestock production.