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Model projections show that production of high-value products from microalgae could be profitable nowadays and commodities will become profitable within 10 years.

Despite the great number of models developed in research projects, only a small percentage have been successfully transferred to the productive sector. The PRIMA programme supported by Horizon 2020, the European Union Framework Programme for Research and Innovation, aims to reverse this situation. The SUPROMED project funded by PRIMA sought to develop an online platform composed of several models adapted to the requirements of end users for increasing the economic and environmental sustainability of Mediterranean agricultural systems. MOPECO, in its research version, was designed to maximize the profitability of irrigated farms in water-scarce regions. A simplified version of this model (MOPECO irrigation scheduling) was included in the SUPROMED platform for improving irrigation efficiency, providing farmers with a useful irrigation scheduling software. This paper shows the approach to adapt and transfer MOPECO to the productive sector. The tool was validated in three different demosite areas across the Mediterranean, involving local stakeholders in the design, validation, and dissemination of the software. The simplified tool reached similar or higher yields than farmers using less water. Thus, the average water saved was around 16%, while the average yield increased around 10% in the plots located in the three demosites of the project (Eastern Mancha in Spain, Bekaa valley in Lebanon, and Sidi Bouzid in Tunisia). This fact decreased the water footprint and increased the profitability of farms. The high applicability of the tool has generated interest among many technicians, farmers, and advisory enterprises. Furthermore, regional and national governmental extension services have shown interest in spreading the use of the tool across their territories, validating the methodology used for adapting and transferring a scientific model to the productive sector.

The aim of this study was to quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land-cover types. Location: Europe Time period: 2018 Major taxa studied: Microbial community (fungi and bacteria) We collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20ºC and microbial biomass (substrate-induced respiration) using an O2-microcompensation apparatus. Climate and soil data were obtained from previous LUCAS surveys and online databases. Structural equation modeling (SEM) was used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass. Soil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands. Soil microbial communities in grasslands and croplands are likely carbon-limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already-degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in coming management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change. [Methods] Soil samples were collected during the 2018 LUCAS soil sampling campaign. Soil chemical and physical properties were measured at the Joint Research Centre in Ispra, Italy (Orgiazzi et al., 2018). Soil microbial respiration and biomass, as well as water content and water holding capacity, were measured in the Eisenhauer lab of the German Centre for Integrative Biodiversity Research. Fungi/Bacteria was measured by fatty acid analysis by Felipe Bastida at CEBAS CSIC. Climate and geographical data were harvested from various databases, which are listed in Appendix 1 (data sources) of the associated paper. For more details on the soil sampling and physical and chemical properties, see: Orgiazzi, A., Ballabio, C., Panagos, P., Jones, A., & Fernández-Ugalde, O. (2018). LUCAS Soil, the largest expandable soil dataset for Europe: a review. European Journal of Soil Science, 69(1), 140-153. https://doi.org/10.1111/ejss.12499 For more details on the measurements of soil microbial respiration and biomass, fatty acids, and water holding capacity, see the supplementary methods of the associated paper (Appendix 2). [Usage Notes] Fatty acid analysis was performed for a subset of 267 samples. Water holding capacity and associated measurements of basal respiration was analyzed in a subset of 100 samples. The samples that were not in these subsets have NA values for the columns associated with these measurements. In order to protect the precise locations of the LUCAS sampling sites, latitude and longitude values could not be given. The approximate location of each sampling site is instead described by the NUTS3 region. If you wish to replicate the structural equation modeling described in the paper, for which latitude is required, please get in touch. A description of each column is available in the associated metadata file. Deutsche Forschungsgemeinschaft, Award: FZT 118-202548816. European Research Council, Award: 694368. European Commission. Directorate-General for the Environment. Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement du Service Public de Wallonie. Eurostat. Peer reviewed

We evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing season. We find that overall, the BEPS-simulated crop gross primary production (GPP), net primary production (NPP), and LAI time-series can explain 82%, 83%, and 85%, respectively, of the variation in the above-ground biomass (AGB) for six selected annual crops, while an application of individual crop LAI explains only 50% of the variation in AGB. The linear relationships between the AGB and these three indicators (GPP, NPP and LAI time-series) are rather high for the six crops, while the slopes of the regression models vary for individual crop type, indicating the need for calibration of key photosynthetic parameters and carbon allocation coefficients. This study demonstrates that accumulated GPP and NPP derived from an ecosystem model, driven by Sentinel-2 LAI data and abiotic data, can be effectively used for crop AGB mapping; the temporal information from LAI is also effective in AGB mapping for some crop types.

ABSTRACTThe aquifer system of Doñana (SW Spain) represents the most important freshwater source in the Doñana Natural Area. Its spatiotemporal dynamics favours the hydrological connection between surface and subsurface ecosystems, and promotes matter fluxes among the different terrestrial and aquatic systems present here. This aquifer has been intensively studied from a hydrogeological point of view but little is known from an ecological perspective. In order to understand the ecological roles played by microbial communities in this system, we conducted a long‐term seasonal study of bacterial abundance, cell biomass, bacterial biomass and functional activities over a 2‐year period. Bacterial abundance ranged between 2.11 ± 1.79 × 105 and 8.58 ± 6.99 × 107 bacteria mL−1 groundwater, average cell biomass was estimated to be 77.01 ± 31.56 fgC and bacterial biomass varied between 8.99 ± 4.10 × 10−2 and 5.65 ± 0.70 µgC mL−1. Iron‐related bacteria showed the highest activities among the functional groups studied. Moreover, among the variables that usually control spatial distributions of microbial communities in aquifer systems, depth did not have a relevant effect on this aquifer, at least in the range of depths studied, but grain size, probably due to its direct effects on hydrogeological parameters, such as permeability or porosity, appeared to exert moderate control, principally in terms of bacterial abundance. Finally, significant seasonal differences in the means of these microbiological variables were also observed; temperature seems to be the main factor controlling the temporal distribution of microbial communities in this aquifer system.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

AbstractMicroalgal biotechnology could generate substantial amounts of biofuels with minimal environmental impact if the economics can be improved by increasing the rate of biomass production. Chlorella kessleri was grown in a small‐scale raceway pond and in flask cultures with the entire volume, 1% (v/v) at any instant, periodically exposed to static magnetic fields to demonstrate increased biomass production and investigate physiological changes, respectively. The growth rate in flasks was maximal at a field strength of 10 mT, increasing from 0.39 ± 0.06 per day for the control to 0.88 ± 0.06 per day. In the raceway pond the 10 mT field increased the growth rate from 0.24 ± 0.03 to 0.45 ± 0.05 per day, final biomass from 0.88 ± 0.11 to 1.56 ± 0.18 g/L per day, and maximum biomass production from 0.11 ± 0.02 to 0.38 ± 0.04 g/L per day. Increased pigment, protein, Ca, and Zn content made the biomass produced with magnetic stimulation nutritionally superior. An increase in oxidative stress was measured indirectly as a decrease in antioxidant capacity from 26 ± 2 to 17 ± 1 µmol antioxidant/g biomass. Net photosynthetic capacity (NPC) and respiratory rate were increased by factors of 2.1 and 3.1, respectively. Loss of NPC enhancement after the removal of magnetic field fit a first‐order model well (R2 = 0.99) with a half‐life of 3.3 days. Transmission electron microscopy showed enlarged chloroplasts and decreased thylakoid order with 10 mT treatment. By increasing daily biomass production about fourfold, 10 mT magnetic field exposure could make algal oil cost competitive with other biodiesel feedstocks. Bioelectromagnetics 33:298–308, 2012. © 2011 Wiley Periodicals, Inc.