The top 100 questions of importance to the future of global agriculture

Despite a significant growth in food production over the past half-century, one of the most important challenges facing society today is how to feed an expected population of some nine billion by the middle of the 20th century. To meet the expected demand for food without significant increases in prices, it has been estimated that we need to produce 70-100 per cent more food, in light of the growing impacts of climate change, concerns over energy security, regional dietary shifts and the Millennium Development target of halving world poverty and hunger by 2015. The goal for the agricultural sector is no longer simply to maximize productivity, but to optimize across a far more complex landscape of production, rural development, environmental, social justice and food consumption outcomes. However, there remain significant challenges to developing national and international policies that support the wide emergence of more sustainable forms of land use and efficient agricultural production. The lack of information flow between scientists, practitioners and policy makers is known to exacerbate the difficulties, despite increased emphasis upon evidence-based policy. In this paper, we seek to improve dialogue and understanding between agricultural research and policy by identifying the 100 most important questions for global agriculture. These have been compiled using a horizon-scanning approach with leading experts and representatives of major agricultural organizations worldwide. The aim is to use sound scientific evidence to inform decision making and guide policy makers in the future direction of agricultural research priorities and policy support. If addressed, we anticipate that these questions will have a significant impact on global agricultural practices worldwide, while improving the synergy between agricultural policy, practice and research. This research forms part of the UK Government's Foresight Global Food and Farming Futures project.

Modeling Indian Ocean circulation: Bay of Bengal fresh water plume and the Arabian Sea Mini Warm Pool

The Indian subcontinent divides the north Indian Ocean into two tropical basins, namely the Arabian Sea and the Bay of Bengal. The Arabian Sea has high salinity whereas the salinity of the Bay of Bengal is much lower due to the contrast in freshwater forcing of the two basins. The freshwater received by the Bay in large amounts during the summer monsoon through river discharge is flushed out annually by ocean circulation. After the withdrawal of the summer monsoon, the Ganga – Brahmaputra river plume flows first along the Indian coast and then around Sri Lanka into the Arabian Sea creating a low salinity pool in the southeastern Arabian Sea (SEAS). In the same region, during the pre-monsoon months of February – April, a warm pool, known as the Arabian Sea Mini Warm Pool (ASMWP), which is distinctly warmer than the rest of the Indian Ocean, takes shape. In fact, this is the warmest region in the world oceans during this period. Simulation of the river plume and its movement as well as its implications to thermodynamics has been a challenging problem for models of Indian Ocean. Here we address these issues using an ocean general circulation model – first we show that the model is capable of reproducing fresh plumes in the Bay of Bengal as well as its movement and then we use the model to determine the processes that lead to formation of the ASMWP. Hydrographic observations from the western Bay of Bengal have shown the presence of a fresh plume along the northern part of the Indian coast during summer monsoon. The Indian Ocean model when forced by realistic winds and climatological river discharge reproduces the fresh plume with reasonable accuracy. The fresh plume does not advect along the Indian coast until the end of summer monsoon. The North Bay Monsoon Current, which flows eastward in the northern Bay, separates the low salinity water from the more saline southern parts of the bay and thus plays an important role in the fresh water budget of the Bay of Bengal. The model also reproduces the surge of the fresh-plume along the Indian coast, into the Arabian Sea during northeast monsoon. Mechanisms that lead to the formation of the Arabian Sea Mini Warm Pool are investigated using several numerical experiments. Contrary to the existing theories, we find that salinity effects are not necessary for the formation of the ASMWP. The orographic effects of the Sahyadris (Western Ghats) and resulting reduction in wind speed leads to the formation of the ASMWP. During November – April, the SEAS behave as a low-wind heatdominated regime where the evolution of sea surface temperature is solely determined by atmospheric forcing. In such regions the evolution of surface layer temperature is not dependent on the characteristics of the subsurface ocean such as the barrier layer and temperature inversion.

Biosorption of heavy metal ions from aqueous and cyanide solutions using fungal biomass

A waste fungal biomass containing killed cells of Aspergillus niger was efficiently used in the removal of toxic metal ions such as nickel, calcium, iron and chromium from aqueous solutions. The role of different parameters such as initial metal ion concentration, solution pH and biomass concentration on biosorption capacity was established. The maximum metal uptake was found to be dependent on solution pH and increased with biomass loading upto 10g/L. The adsorption densities for various metal ions could be arranged as Ca>Cr (III)>Ni>Fe>Cr (VI). The effect of the presence of various metal ions in binary, ternary and quaternary combinations on biosorption was also assessed. Ni uptake was significantly affected, while that of Cr (VI) the least, in the presence of other metal ions. Uptake of base metals from an industrial cyanide effluent was studied using different species of fungi such as Aspergillus niger, Aspergillus terreus and Penicillium funiculosum and yeast such as Saccharomyces cerevisiae which were isolated from a gold mine. Traces of gold present in the cyanide effluent could be efficiently recovered. Among the four base metal contaminants present in the cyanide effluent, zinc was found to be most efficiently biosorbed, followed by iron, copper and lead. The role of both living and dead biomass on biosorption was distinguished and probable mechanisms illustrated.

Biodegradation of some organic reagents from mineral process effluents

The utility of a soil microbe, namely Bacillus polymyxa, in the removal of organic reagents such as dodecylamine, ether diamine, isopropyl xanthate and sodium oleate from aqueous solutions is demonstrated. Time-bound removal of the above organic reagents from an alkaline solution was investigated under different experimental conditions during bacterial growth and in the presence of metabolites by frequent monitoring of residual concentrations as a function of time, reagent concentration and cell density. The stages and mechanisms in the biodegradation process were monitored through UV-visible and FTIR spectroscopy. Surface chemistry of the bacterial cells as well as the biosorption tendency for various organics were also established through electrokinetic and adsorption density measurements. Both the cationic amines were found to be biosorbed followed by their degradation through bacterial metabolism. The presence of the organic reagents promoted bacterial growth through effective bacterial utilization of nitrogen and carbon from the organics. Under optimal conditions, complete degradation and bioremoval of all the organics could be achieved.

Selective biodissolution of calcium and iron from bauxite in the presence of Bacillus polymyxa

A bacterium Bacillus polymyxa was found to be capable of selective removal of calcium and iron from bauxite. The bioleached residue was found to be enriched in its alumina content with insignificant amounts of iron and calcium as impurities. The developed bio- process was found to be capable of producing a bauxite product which meets the specifica- tions as a raw material for the manufacture of alumina based ceramics and refractories. The role of bacterial cells and metabolic products in the selective dissolution of calcium (present as calcite) and iron (present as hematite and goethite) from bauxite was assessed and possi- ble mechanisms illustrated. The effect of different parameters such as sucrose concentra- tion, pH, pulp density and time on selective biodissolution was studied. It was observed that periodic decantation and replenishment of the leach medium was beneficial in improving the dissolution kinetics. Calcium removal involves chelation with bacterial exopolysaccha- tides and acidolysis by organic acid generation. Hematite could be solubilized through a reductive dissolution mechanism.

On the basin-scale detection and attribution of human-induced climate change in monsoon precipitation and streamflow

Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

A constant factor approximation algorithm for boxicity of circular arc graphs

Boxicity of a graph G(V, E) is the minimum integer k such that G can be represented as the intersection graph of k-dimensional axis parallel boxes in Rk. Equivalently, it is the minimum number of interval graphs on the vertex set V such that the intersection of their edge sets is E. It is known that boxicity cannot be approximated even for graph classes like bipartite, co-bipartite and split graphs below O(n0.5-ε)-factor, for any ε > 0 in polynomial time unless NP = ZPP. Till date, there is no well known graph class of unbounded boxicity for which even an nε-factor approximation algorithm for computing boxicity is known, for any ε < 1. In this paper, we study the boxicity problem on Circular Arc graphs - intersection graphs of arcs of a circle. We give a (2+ 1/k)-factor polynomial time approximation algorithm for computing the boxicity of any circular arc graph along with a corresponding box representation, where k ≥ 1 is its boxicity. For Normal Circular Arc(NCA) graphs, with an NCA model given, this can be improved to an additive 2-factor approximation algorithm. The time complexity of the algorithms to approximately compute the boxicity is O(mn+n2) in both these cases and in O(mn+kn2) which is at most O(n3) time we also get their corresponding box representations, where n is the number of vertices of the graph and m is its number of edges. The additive 2-factor algorithm directly works for any Proper Circular Arc graph, since computing an NCA model for it can be done in polynomial time.