Coping with Water Scarcity: What Role for Biotechnologies?

At a conference of the FAO Biotechnology Forum in 2007, 78 participants from 24 countries offered their views on agricultural biotechnologies and water scarcity, addressing the pros and cons of various methods and their potential application. These viewpoints are represented in this discussion paper, along with an introductory section that defines the issues to be discussed. Funders in the WASH sector can use this document to educate themselves about the potential gains to be made in supporting different types of scientific research and agricultural technology development

AquaCrop: Manuel d'utilisation

Le logiciel AquaCrop est un modèle de bilan d’eau qui permet d’évaluer les efficiences en irrigation, l’élaboration des calendriers d’irrigation au niveau de la parcelle et l'estimation des rendements. AquaCrop a été sélectionné en raison de sa simplicité et de sa robustesse, et du nombre limité de variables à introduire. Il existe bien des modèles déterministes, mais pour fonctionner correctement, ils exigent des paramètres d’entrée très détaillés qui ne sont pas toujours disponibles quand il s’agit de recherche en milieu rural (‘on-farm’)

Sustainable Irrigation Management of Ornamental Cordyline Fruticosa “Red Edge” Plants with Saline Water

The aim of this work was to analyze the influence of the salinity of the nutrient solution on the transpiration and growth of Cordyline fruticosa var. “Red Edge” plants. A specific irrigation management model was calibrated with the experimental data. An experiment was performed with four treatments. These treatments consisted of the application of four nutrient solutions with different electrical conductivity (ECw) levels ranging from 1.5 dS m−1 (control treatment) to 4.5 dS m−1. The results showed that day-time transpiration decreases when salt concentration in the nutrient solution increases. The transpiration of the plant in the control treatment was modelled by applying a combination method while the effect of the salinity of the nutrient solution was modelled by deriving a saline stress coefficient from the experimental data. The results showed that significant reductions in plant transpiration were observed for increasing values of ECw. The crop development and yield were also affected by the increasing salinity of the nutrient solution. A relationship between the ECw and the relative crop yield was derived

AquaCrop-OS: An open source version of FAO's crop water productivity model

AbstractCrop simulation models are valuable tools for quantifying crop yield response to water, and for devising strategies to improve agricultural water management. However, applicability of the majority of crop models is limited greatly by a failure to provide open-access to model source code. In this study, we present an open-source version of the FAO AquaCrop model, which simulates efficiently water-limited crop production across diverse environmental and agronomic conditions. Our model, called AquaCrop-OpenSource (AquaCrop-OS), can be run in multiple programming languages and operating systems. Support for parallel execution reduces significantly simulation times when applying the model in large geospatial frameworks, for long-run policy analysis, or for uncertainty assessment. Furthermore, AquaCrop-OS is compliant with the Open Modelling Interface standard facilitating linkage to other disciplinary models, for example to guide integrated water resources planning

Yield gap analysis of field crops: Methods and case studies

The challenges of global agriculture have been analysed exhaustively and the need has been established for sustainable improvement in agricultural production aimed at food security in a context of increasing pressure on natural resources. Whereas the importance of R&D investment in agriculture is increasingly recognised, better allocation of limited funding is essential to improve food production. In this context, the common and often large gap between actual and attainable yield is a critical target. Realistic solutions are required to close yield gaps in both small and large scale cropping systems worldwide; to make progress in this direction, we need (1) definitions and techniques to measure and model yield at different levels (actual, attainable, potential) and different scales in space (field, farm, region, global) and time (short, long term); (2) identification of the causes of gaps between yield levels; (3) management options to reduce the gaps where feasible and (4) policies to favour adoption of gap-closing technologies. The aim of this publication is to review the methods for yield gap analysis, and to use case studies to illustrate different approaches, hence addressing the first of these four requirements. Theoretical, potential, water-limited, and actual yield are defined. Yield gap is the difference between two levels of yield in this series. Depending on the objectives of the study, different yield gaps are relevant. The exploitable yield gap accounts for both the unlikely alignment of all factors required for achievement of potential or water limited yield and the economic, management and environmental constraints that preclude, for example, the use of fertiliser rates that maximise yield, when growers’ aim is often a compromise between maximising profit and minimising risk at the whole-farm scale, rather than maximising yield of individual crops. The gap between potential and water limited yield is an indication of yield gap that can be removed with irrigation. Spatial and temporal scales for the determination of yield gaps are discussed. Spatially, yield gaps have been quantified at levels of field, region, national or mega-environment and globally. Remote sensing techniques describes the spatial variability of crop yield, even up to individual plots. Time scales can be defined in order to either remove or capture the dynamic components of the environment (soil, climate, biotic components of ecosystems) and technology. Criteria to define scales in both space and time need to be made explicit, and should be consistent with the objectives of the analysis. Satellite measurements can complement in situ measurements. The accuracy of estimating yield gaps is determined by the weakest link, which in many cases is good quality, sub-national scale data on actual yields that farmers achieve. In addition, calculation and interpretation of yield gaps requires reliable weather data, additional agronomic information and transparent assumptions. The main types of methods used in yield benchmarking and gap analysis are outlined using selected case studies. The diversity of benchmarking methods outlined in this publication reflects the diversity of spatial and temporal scales, the questions asked, and the resources available to answer them. We grouped methods in four broad approaches. Approach 1 compares actual yield with the best yield achieved in comparable environmental conditions, e.g. between neighbours with similar topography and soils. Comparisons of this type are spatially constrained by definition, and are an approximation to the gap between actual and attainable yield. With minimum input and greatest simplicity, this allows for limited but useful benchmarks; yield gaps can be primarily attributed to differences in management. This approach can be biased, however, where best management practices are not feasible; modelled yields provide more relevant benchmarks in these cases. Approach 2 is a variation of approach 1, i.e. it is based on comparisons of actual yield, but instead of a single yield benchmark, yield is expressed as a function of one or few environmental drivers in simple models. In common with Approach 1, these methods do not necessarily capture best management practices. The French and Schultz model is the archetype in this approach; this method plots actual yield against seasonal water use, fits a boundary function representing the best yield for a given water use, and calculates yield gaps as the departure between actual yields and the boundary function. A boundary model fitted to the data provides a scaled benchmark, thus partially accounting for seasonal conditions. Boundary functions can be estimated with different statistical methods but it is recommended that the shape and parameters of boundary functions are also assessed on the basis of their biophysical meaning. Variants of this approach use nitrogen uptake or soil properties instead of water. Approach 3 is based on modelling which may range from simple climatic indices to models of intermediate (e.g. AquaCrop) or high complexity (e.g. CERES-type models). More complex models are valuable agronomically because they capture some genetic features of the specific cultivar, and the critical interaction between water and nitrogen. On the other hand, more complex models have requirements of parameters and inputs that are not always available. “Best practice” approaches to model yield in gap analysis are outlined. Importantly, models to estimate potential yield require parameters that capture the physiology of unstressed crops. Approach 4 benchmarking involves a range of approaches combining actual data, remote sensing, GIS and models of varying complexity. This approach is important for benchmarking at and above the regional scale. At these large scales, particular attention needs to be paid to weather data used in modelling yield because significant bias can accrue from inappropriate data sources. Studies that have used gridded weather databases to simulate potential and water-limited yields for a grid are rarely validated against simulated yields based on actual weather station data from locations within the same grid. This should be standard practice, particularly where global scale yield gaps are used for policy decisions or investment in R&D. Alternatively, point-based simulations of potential and water-limited yields, complemented with an appropriate up-scaling method, may be more appropriate for large scale yield gap analysis. Remote sensing applied to yield gap analysis has improved over the last years, mainly through pixel-based biomass production models. Site-specific yield validation, disaggregated in biomass radiation-use-efficiency and harvest index, remains necessary and need to be carried out every 5 to 10 years

Developing a reliable strategy to infer the effective soil hydraulic properties from field evaporation experiments for agro-hydrological models

The Richards equation has been widely used for simulating soil water movement. However, the take-up of agro-hydrological models using the basic theory of soil water flow for optimizing irrigation, fertilizer and pesticide practices is still low. This is partly due to the difficulties in obtaining accurate values for soil hydraulic properties at a field scale. Here, we use an inverse technique to deduce the effective soil hydraulic properties, based on measuring the changes in the distribution of soil water with depth in a fallow field over a long period, subject to natural rainfall and evaporation using a robust micro Genetic Algorithm. A new optimized function was constructed from the soil water contents at different depths, and the soil water at field capacity. The deduced soil water retention curve was approximately parallel but higher than that derived from published pedo-tranfer functions for a given soil pressure head. The water contents calculated from the deduced soil hydraulic properties were in good agreement with the measured values. The reliability of the deduced soil hydraulic properties was tested in reproducing data measured from an independent experiment on the same soil cropped with leek. The calculation of root water uptake took account for both soil water potential and root density distribution. Results show that the predictions of soil water contents at various depths agree fairly well with the measurements, indicating that the inverse analysis is an effective and reliable approach to estimate soil hydraulic properties, and thus permits the simulation of soil water dynamics in both cropped and fallow soils in the field accurately

Tribological properties of plasma sprayed Cr2O3, Cr2O3–TiO2, Cr2O3–Al2O3 and Cr2O3–ZrO2 coatings

Plasma sprayed Cr2O3 is widely used to protect industrial components against wear. The present study seeks to clarify how its properties can be modified by alloying with other oxides. Therefore, pure Cr2O3 and Cr2O3–25%TiO2, Cr2O3–16%Al2O3, Cr2O3–35%Al2O3, Cr2O3–10%ZrO2 and Cr2O3–20%ZrO2 coatings were studied. All samples were obtained from pre-alloyed feedstock, resulting in rather homogeneous solid solutions. Compared with pure Cr2O3 and Cr2O3–Al2O3 coatings, the Cr2O3–25%TiO2 and Cr2O3–ZrO2 ones exhibit lower indentation hardness (HIT) but higher toughness, qualitatively assessed by scratch testing. Cr2O3 and Cr2O3–16%Al2O3 also exhibit higher hardness/elastic modulus ratios (HIT/E*, HIT3/E*2) than all other samples. The sliding wear resistance of the coatings against Al2O3 and ZrO2 balls is most closely correlated to indentation hardness and, secondarily, to the hardness/modulus ratios. Pure Cr2O3 is therefore the most sliding wear resistant of all samples, whilst Cr2O3–25%TiO2 suffers very severe wear. However, ZrO2 counterparts cause systematically more severe wear than do Al2O3 ones. Dry particles' abrasion, which proceeds through flake formation, is controlled by toughness. The resistance to abrasive wear is, therefore, predicted by scratch testing. The various coatings rank almost the opposite as they did in sliding wear tests, with comparatively lower wear losses for Cr2O3–25%TiO2 and (most of all) Cr2O3–ZrO2 samples.acceptedVersionPeer reviewe

Sustainable intensification of agriculture for human prosperity and global sustainability

There is an ongoing debate on what constitutes sustainable intensification of agriculture (SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined—at all scales—in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing. The criteria and approach we propose, for a paradigm shift towards sustainable intensification of agriculture, integrates the dual and interdependent goals of using sustainable practices to meet rising human needs while contributing to resilience and sustainability of landscapes, the biosphere, and the Earth system. Both of these, in turn, are required to sustain the future viability of agriculture. This paradigm shift aims at repositioning world agriculture from its current role as the world’s single largest driver of global environmental change, to becoming a key contributor of a global transition to a sustainable world within a safe operating space on Earth