Wageningen University and Research Centre

About: Wageningen University and Research Centre is a education organization based out in Wageningen, Netherlands. It is known for research contribution in the topics: Population & Sustainability. The organization has 23474 authors who have published 54833 publications receiving 2608897 citations.

What Has Natural Variation Taught Us about Plant Development, Physiology, and Adaptation?

Abstract: Nearly 100 genes and functional polymorphisms underlying natural variation in plant development and physiology have been identified. In crop plants, these include genes involved in domestication traits, such as those related to plant architecture, fruit and seed structure and morphology, as well as yield and quality traits improved by subsequent crop breeding. In wild plants, comparable traits have been dissected mainly in Arabidopsis thaliana. In this review, we discuss the major contributions of the analysis of natural variation to our understanding of plant development and physiology, focusing in particular on the timing of germination and flowering, plant growth and morphology, primary metabolism, and mineral accumulation. Overall, functional polymorphisms appear in all types of genes and gene regions, and they may have multiple mutational causes. However, understanding this diversity in relation to adaptation and environmental variation is a challenge for which tools are now available.

A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda

Abstract: While there is a lot of literature from a natural or technical sciences perspective on different forms of digitalization in agriculture (big data, internet of things, augmented reality, robotics, sensors, 3D printing, system integration, ubiquitous connectivity, artificial intelligence, digital twins, and blockchain among others), social science researchers have recently started investigating different aspects of digital agriculture in relation to farm production systems, value chains and food systems. This has led to a burgeoning but scattered social science body of literature. There is hence lack of overview of how this field of study is developing, and what are established, emerging, and new themes and topics. This is where this article aims to make a contribution, beyond introducing this special issue which presents seventeen articles dealing with social, economic and institutional dynamics of precision farming, digital agriculture, smart farming or agriculture 4.0. An exploratory literature review shows that five thematic clusters of extant social science literature on digitalization in agriculture can be identified: 1) Adoption, uses and adaptation of digital technologies on farm; 2) Effects of digitalization on farmer identity, farmer skills, and farm work; 3) Power, ownership, privacy and ethics in digitalizing agricultural production systems and value chains; 4) Digitalization and agricultural knowledge and innovation systems (AKIS); and 5) Economics and management of digitalized agricultural production systems and value chains. The main contributions of the special issue articles are mapped against these thematic clusters, revealing new insights on the link between digital agriculture and farm diversity, new economic, business and institutional arrangements both on-farm, in the value chain and food system, and in the innovation system, and emerging ways to ethically govern digital agriculture. Emerging lines of social science enquiry within these thematic clusters are identified and new lines are suggested to create a future research agenda on digital agriculture, smart farming and agriculture 4.0. Also, four potential new thematic social science clusters are also identified, which so far seem weakly developed: 1) Digital agriculture socio-cyber-physical-ecological systems conceptualizations; 2) Digital agriculture policy processes; 3) Digitally enabled agricultural transition pathways; and 4) Global geography of digital agriculture development. This future research agenda provides ample scope for future interdisciplinary and transdisciplinary science on precision farming, digital agriculture, smart farming and agriculture 4.0.

Energy consumption and constant current operation in membrane capacitive deionization

Abstract: Membrane capacitive deionization (MCDI) is a water desalination technology based on applying a cell voltage between two oppositely placed porous electrodes sandwiching a spacer channel that transports the water to be desalinated. In the salt removal step, ions are adsorbed at the carbon–water interface within the micropores inside the porous electrodes. After the electrodes reach a certain adsorption capacity, the cell voltage is reduced or even reversed, which leads to ion release from the electrodes and a concentrated salt solution in the spacer channel, which is flushed out, after which the cycle can start over again. Ion-exchange membranes are positioned in front of each porous electrode, which has the advantage of preventing the co-ions from leaving the electrode region during ion adsorption, while also allowing for ion desorption at reversed voltage. Both effects significantly increase the salt removal capacity of the system per cycle. The classical operational mode of MCDI at a constant cell voltage results in an effluent stream of desalinated water of which the salt concentration varies with time. In this paper, we propose a different operational mode for MCDI, whereby desalination is driven by a constant electrical current, which leads to a constant salt concentration in the desalinated stream over long periods of time. Furthermore, we show how the salt concentration of the desalinated stream can be accurately adjusted to a certain setpoint, by either varying the electrical current level and/or the water flow rate. Finally, we present an extensive dataset for the energy requirements of MCDI, both for operation at constant voltage and at constant current, and in both cases also for the related technology in which membranes are not included (CDI). We find consistently that in MCDI the energy consumption per mole of salt removed is lower than that in CDI. Within the range 10–200 mM ionic strength of the water to be treated, we find for MCDI a constant energy consumption of ∼22 kT per ion removed. Results in this work are an essential tool to evaluate the economic viability of MCDI for the treatment of saltwater.