Does international cereal trade save water?: the impact of virtual water trade on global water use

Cereals / Trade policy / Water use / Irrigation water / Productivity / Evapotranspiration / Water scarcity / Water conservation

Linear regression for numeric symbolic variables: an ordinary least squares approach based on Wasserstein Distance

In this paper we present a linear regression model for modal symbolic data. The observed variables are histogram variables according to the definition given in the framework of Symbolic Data Analysis and the parameters of the model are estimated using the classic Least Squares method. An appropriate metric is introduced in order to measure the error between the observed and the predicted distributions. In particular, the Wasserstein distance is proposed. Some properties of such metric are exploited to predict the response variable as direct linear combination of other independent histogram variables. Measures of goodness of fit are discussed. An application on real data corroborates the proposed method

Can global precipitation datasets benefit the estimation of the area to be cropped in irrigated agriculture?

The area to be cropped in irrigation districts needs to be planned according to the available water resources to avoid agricultural production loss. However, the period of record of local hydro-meteorological data may be short, leading to an incomplete understanding of climate variability and consequent uncertainty in estimating surface water availability for irrigation area planning. In this study we assess the benefit of using global precipitation datasets to improve surface water availability estimates. A reference area that can be irrigated is established using a complete record of 30 years of observed river discharge data. Areas are then determined using simulated river discharges from six local hydrological models forced with in situ and global precipitation datasets (CHIRPS and MSWEP), each calibrated independently with a sample of 5 years extracted from the full 30-year record. The utility of establishing the irrigated area based on simulated river discharge simulations is compared against the reference area through a pooled relative utility value (PRUV). Results show that for all river discharge simulations the benefit of choosing the irrigated area based on the 30 years of simulated data is higher compared to using only 5 years of observed discharge data, as the statistical spread of PRUV using 30 years is smaller. Hence, it is more beneficial to calibrate a hydrological model using 5 years of observed river discharge and then to extend it with global precipitation data of 30 years as this weighs up against the model uncertainty of the model calibration.</p

Multiplex quantitative PCR for single-reaction genetically modified (GM) plant detection and identification of false-positive GM plants linked to Cauliflower mosaic virus (CaMV) infection.

BACKGROUND:Most genetically modified (GM) plants contain a promoter, P35S, from the plant virus, Cauliflower mosaic virus (CaMV), and many have a terminator, TNOS, derived from the bacterium, Agrobacterium tumefaciens. Assays designed to detect GM plants often target the P35S and/or TNOS DNA sequences. However, because the P35S promoter is derived from CaMV, these detection assays can yield false-positives from non-GM plants infected by this naturally-occurring virus. RESULTS:Here we report the development of an assay designed to distinguish CaMV-infected plants from GM plants in a single multiplexed quantitative PCR (qPCR) reaction. Following initial testing and optimization via PCR and singleplex-to-multiplex qPCR on both plasmid and plant DNA, TaqMan qPCR probes with different fluorescence wavelengths were designed to target actin (a positive-control plant gene), P35S, P3 (a CaMV-specific gene), and TNOS. We tested the specificity of our quadruplex qPCR assay using different DNA extracts from organic watercress and both organic and GM canola, all with and without CaMV infection, and by using commercial and industrial samples. The limit of detection (LOD) of each target was determined to be 1% for actin, 0.001% for P35S, and 0.01% for both P3 and TNOS. CONCLUSIONS:This assay was able to distinguish CaMV-infected plants from GM plants in a single multiplexed qPCR reaction for all samples tested in this study, suggesting that this protocol is broadly applicable and readily transferrable to any interested parties with a qPCR platform

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

Revitalizing Asia's irrigation: to sustainably meet tomorrow's food needs

Irrigated farming / Food security / Irrigation management / Participatory management / Water users associations / Public sector / Private sector / Farmer managed irrigation systems / Surface irrigation / Pumps / Groundwater irrigation / Water productivity / Models / Reservoirs / Canals / Tanks / Irrigation programs / Climate change / Water conservation / Asia

Polyclonal antibody production anti Pc_312-324 peptide: Its potential use in electrochemical immunosensors for transgenic soybean detection

A new polyclonal antibody that recognizes the CP4 5-enolpyruvylshikimate-3-phosphate synthase (CP4-EPSPS), which provides resistance to glyphosate in soybean (Roundup Ready®, RR soybean), was produced. New Zealand rabbits were injected with a synthetic peptide (Pc_312-324, (PEP)) present in the soybean CP4-EPSPS protein. The anti-PEP antibodies production was evaluated by electrophoresis (SDS-PAGE) and an enzyme-linked immunosorbent assay (ELISA) was developed in order to study their specificity. The ELISA showed that the polyclonal antibody was specific to PEP. In addition, the anti- PEP was immobilized onto a gold disk electrode and the antigen-antibody interaction was evaluated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Moreover, the EIS showed that the electron transfer resistance of the modified electrode increased after incubation with solutions containing CP4-EPSPS protein from RR transgenic soybean, while no changes were detected after incubation with no-RR soybean proteins. These results suggest that the CP4-EPSPS was immobilized onto the electrode, due to the specific interaction with the anti-PEP. These results show that this antigen-antibody interaction can be detected by electrochemical techniques, suggesting that the anti-PEP produced can be used in electrochemical immunosensors development to quantify transgenic soybean.Fil: Farias, Marcos Ezequiel. Universidad Nacional de Río Cuarto. Instituto para el Desarrollo Agroindustrial y de la Salud. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto para el Desarrollo Agroindustrial y de la Salud; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Biología Molecular; ArgentinaFil: Marani, Mariela Mirta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico para el Estudio de los Ecosistemas Continentales; ArgentinaFil: Ramirez, Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Niebylski, Ana Maria. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Biotecnología Ambiental y Salud - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Biotecnología Ambiental y Salud; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Biología Molecular; ArgentinaFil: Correa, Nestor Mariano. Universidad Nacional de Río Cuarto. Instituto para el Desarrollo Agroindustrial y de la Salud. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto para el Desarrollo Agroindustrial y de la Salud; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Química; ArgentinaFil: Molina, Patricia Gabriela. Universidad Nacional de Río Cuarto. Instituto para el Desarrollo Agroindustrial y de la Salud. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto para el Desarrollo Agroindustrial y de la Salud; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Departamento de Química; Argentin

Managing uncertainty: a review of food system scenario analysis and modelling

Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address