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    Effects of Drought and Heat on Photosynthetic Performance, Water Use and Yield of Two Selected Fiber Hemp Cultivars at a Poor-Soil Site in Brandenburg (Germany)
    (Basel : MDPI, 2020) Herppich, Werner B.; Gusovius, Hans-Jörg; Flemming, Inken; Drastig, Katrin
    Hemp currently regains certain importance as fiber, oil and medical crop not least because of its modest requirements of biocides, fertilizer and water. During recent years, crops were exposed to a combination of drought and heat, even in northern Central-Europe. Dynamic responses of photosynthesis and stomatal conductance to these stresses and their persistent effects had been studied, if at all, in controlled environment experiments. Comprehensive field studies on diurnal and long-term net photosynthesis and gas exchange, and yield properties of hemp during a drought prone, high-temperature season in northern Central-Europe are obviously missing. Thus, in whole season field trails, the essential actual physiological (rates of net photosynthesis and transpiration, stomatal conductance, water use efficiencies, ambient and internal CO2 concentrations) and the yield performance of modern high-yielding multi-purpose hemp cultivars, ‘Ivory’ and ‘Santhica 27’, were evaluated under extreme environmental conditions and highly limited soil water supply. This provides comprehensive information on the usability of these cultivars under potential future harsh production conditions. Plants of both cultivars differentially cope with the prevailing climatic and soil water conditions. While ‘Ivory’ plants developed high rates of CO2 gain and established large leaf area per plant in the mid-season, those of ‘Santhica 27’ utilized lower CO2 uptake rates at lower leaf area per plant most time. This and the higher germination success of ‘Santhica 27’ resulted in nearly twice the yield compared to ‘Ivory’. Although stomatal control of CO2 gain was pronounced in both cultivars, higher stomatal limitations in ‘Ivory’ plants resulted in higher overall intrinsic water use efficiency. Cultivation of both hemp cultivars with only basic irrigation during seed germination was successful and without large effects on yield and quality. This was valid even under extremely hot and dry climatic conditions in northern Central Europe.
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    Airflow resistance of two hop varieties
    (Tartu : Estonian Agricultural University, Faculty of Agronomy, 2021) Ziegler, T.; Teodorov, T.
    The quality of hops used in brewing is substantially reliant upon the processing step of drying. To ensure effective drying in kiln as well conveyor-belt dryers, homogeneous distribution of air is of particular importance. Uneven air distribution often results in inefficient drying and nonuniform moisture content of the hop cones. The air distribution naturally is governed by the airflow resistances in the individual floors or belts of a dryer. Hence, in order to quantify the airflow resistance of hop cones at different air velocities and bed heights, systematic measurements were carried out. In addition to determining the bulk densities of hops, the investigations included trials with fresh and dried hop samples. Clear differences were observed between hop varieties both in measured pressure drops and in bulk densities. Moreover, in the case of fresh hops, a non-linear increase in pressure drop with bed height was ascertained. Semiempirical equations were developed to describe pressure drop as a function of air velocity. This work will contribute to the design of dryers with optimum airflow distribution and thus enhance the efficiency of drying as well as the product quality.
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    Ammonia and greenhouse gas emissions from slurry storage : A review
    (Amsterdam [u.a.] : Elsevier, 2020) Kupper, Thomas; Häni, Christoph; Neftel, Albrecht; Kincaid, Chris; Bühler, Marcel; Amon, Barbara; VanderZaag, Andrew
    Storage of slurry is an important emission source for ammonia (NH3), nitrous oxide (N2O), methane (CH4), carbon dioxide (CO2) and hydrogen sulfide (H2S) from livestock production. Therefore, this study collected published emission data from stored cattle and pig slurry to determine baseline emission values and emission changes due to slurry treatment and coverage of stores. Emission data were collected from 120 papers yielding 711 records of measurements conducted at farm-, pilot- and laboratory-scale. The emission data reported in a multitude of units were standardized and compiled in a database. Descriptive statistics of the data from untreated slurry stored uncovered revealed a large variability in emissions for all gases. To determine baseline emissions, average values based on a weighting of the emission data according to the season and the duration of the emission measurements were constructed using the data from farm-scale and pilot-scale studies. Baseline emissions for cattle and pig slurry stored uncovered were calculated. When possible, it was further distinguished between storage in tanks without slurry treatment and storage in lagoons which implies solid-liquid separation and biological treatment. The baseline emissions on an area or volume basis are: for NH3: 0.12 g m−2 h-1 and 0.15 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 0.08 g m−2 h-1 and 0.24 g m−2 h-1 for cattle and pig slurry stored in tanks; for N2O: 0.0003 g m−2 h-1 for cattle slurry stored in lagoons, and 0.002 g m−2 h-1 for both slurry types stored in tanks; for CH4: 0.95 g m-3 h-1 and 3.5 g m-3 h-1 for cattle and pig slurry stored in lagoons, and 0.58 g m-3 h-1 and 0.68 g m-3 h-1 for cattle and pig slurry stored in tanks; for CO2: 6.6 g m−2 h-1 and 0.3 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 8.0 g m−2 h-1 for both slurry types stored in tanks; for H2S: 0.04 g m−2 h-1 and 0.01 g m−2 h-1 for cattle and pig slurry stored in lagoons. Related to total ammoniacal nitrogen (TAN), baseline emissions for tanks are 16% and 15% of TAN for cattle and pig slurry, respectively. Emissions of N2O and CH4 relative to nitrogen (N) and volatile solids (VS) are 0.13% of N and 0.10% of N and 2.9% of VS and 4.7% of VS for cattle and pig slurry, respectively. Total greenhouse gas emissions from slurry stores are dominated by CH4. The records on slurry treatment using acidification show a reduction of NH3 and CH4 emissions during storage while an increase occurs for N2O and a minor change for CO2 as compared to untreated slurry. Solid-liquid separation causes higher losses for NH3 and a reduction in CH4, N2O and CO2 emissions. Anaerobically digested slurry shows higher emissions during storage for NH3 while losses tend to be lower for CH4 and little changes occur for N2O and CO2 compared to untreated slurry. All cover types are found to be efficient for emission mitigation of NH3 from stores. The N2O emissions increase in many cases due to coverage. Lower CH4 emissions occur for impermeable covers as compared to uncovered slurry storage while for permeable covers the effect is unclear or emissions tend to increase. Limited and inconsistent data regarding emission changes with covering stores are available for CO2 and H2S. The compiled data provide a basis for improving emission inventories and highlight the need for further research to reduce uncertainty and fill data gaps regarding emissions from slurry storage.
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    BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data
    (Sofia : Pensoft Publishers, 2021) Chamanara, Javad; Gaikwad, Jitendra; Gerlach, Roman; Algergawy, Alsayed; Ostrowski, Andreas; König-Ries, Birgitta
    Obtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research.
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    Factors That Influence Nitrous Oxide Emissions from Agricultural Soils as Well as Their Representation in Simulation Models: A Review
    (Basel : MDPI, 2021-4-14) Wang, Cong; Amon, Barbara; Schulz, Karsten; Mehdi, Bano
    Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model.
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    Climate change and potential distribution of potato (Solanum tuberosum) crop cultivation in Pakistan using Maxent
    (Springfield, MO : AIMS Press, 2021) Khalil, Tayyaba; Asad, Saeed A.; Khubaib, Nusaiba; Baig, Ayesha; Atif, Salman; Umar, Muhammad; Kropp, Jürgen P.; Pradhan, Prajal; Baig, Sofia
    The impacts of climate change are projected to become more intense and frequent. One of the indirect impacts of climate change is food insecurity. Agriculture in Pakistan, measured fourth best in the world, is already experiencing visible adverse impacts of climate change. Among many other food sources, potato crop remains one of the food security crops for developing nations. Potatoes are widely cultivated in Pakistan. To assess the impact of climate change on potato crop in Pakistan, it is imperative to analyze its distribution under future climate change scenarios using Species Distribution Models (SDMs). Maximum Entropy Model is used in this study to predict the spatial distribution of Potato in 2070 using two CMIP5 models for two climate change scenarios (RCP 4.5 and RCP 8.5). 19 Bioclimatic variables are incorporated along with other contributing variables like soil type, elevation and irrigation. The results indicate slight decrease in the suitable area for potato growth in RCP 4.5 and drastic decrease in suitable area in RCP 8.5 for both models. The performance evaluation of the model is based on AUC. AUC value of 0.85 suggests the fitness of the model and thus, it is applicable to predict the suitable climate for potato production in Pakistan. Sustainable potato cultivation is needed to increase productivity in developing countries while promoting better resource management and optimization.
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    Near Real-Time Biophysical Rice (Oryza sativa L.) Yield Estimation to Support Crop Insurance Implementation in India
    (Basel : MDPI, 2020) Arumugam, Ponraj; Chemura, Abel; Schauberger, Bernhard; Gornott, Christoph
    Immediate yield loss information is required to trigger crop insurance payouts, which are important to secure agricultural income stability for millions of smallholder farmers. Techniques for monitoring crop growth in real-time and at 5 km spatial resolution may also aid in designing price interventions or storage strategies for domestic production. In India, the current government-backed PMFBY (Pradhan Mantri Fasal Bima Yojana) insurance scheme is seeking such technologies to enable cost-efficient insurance premiums for Indian farmers. In this study, we used the Decision Support System for Agrotechnology Transfer (DSSAT) to estimate yield and yield anomalies at 5 km spatial resolution for Kharif rice (Oryza sativa L.) over India between 2001 and 2017. We calibrated the model using publicly available data: namely, gridded weather data, nutrient applications, sowing dates, crop mask, irrigation information, and genetic coefficients of staple varieties. The model performance over the model calibration years (2001–2015) was exceptionally good, with 13 of 15 years achieving more than 0.7 correlation coefficient (r), and more than half of the years with above 0.75 correlation with observed yields. Around 52% (67%) of the districts obtained a relative Root Mean Square Error (rRMSE) of less than 20% (25%) after calibration in the major rice-growing districts (>25% area under cultivation). An out-of-sample validation of the calibrated model in Kharif seasons 2016 and 2017 resulted in differences between state-wise observed and simulated yield anomalies from –16% to 20%. Overall, the good ability of the model in the simulations of rice yield indicates that the model is applicable in selected states of India, and its outputs are useful as a yield loss assessment index for the crop insurance scheme PMFBY.
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    Incorporating Biodiversity into Biogeochemistry Models to Improve Prediction of Ecosystem Services in Temperate Grasslands: Review and Roadmap
    (Basel : MDPI, 2020) Van Oijen, Marcel; Barcza, Zoltán; Confalonieri, Roberto; Korhonen, Panu; Kröel-Dulay, György; Lellei-Kovács, Eszter; Louarn, Gaëtan; Louault, Frédérique; Martin, Raphaël; Moulin, Thibault; Movedi, Ermes; Picon-Cochard, Catherine; Rolinski, Susanne; Viovy, Nicolas; Wirth, Stephen Björn; Bellocchi, Gianni
    Multi-species grasslands are reservoirs of biodiversity and provide multiple ecosystem services, including fodder production and carbon sequestration. The provision of these services depends on the control exerted on the biogeochemistry and plant diversity of the system by the interplay of biotic and abiotic factors, e.g., grazing or mowing intensity. Biogeochemical models incorporate a mechanistic view of the functioning of grasslands and provide a sound basis for studying the underlying processes. However, in these models, the simulation of biogeochemical cycles is generally not coupled to simulation of plant species dynamics, which leads to considerable uncertainty about the quality of predictions. Ecological models, on the other hand, do account for biodiversity with approaches adopted from plant demography, but without linking the dynamics of plant species to the biogeochemical processes occurring at the community level, and this hampers the models’ capacity to assess resilience against abiotic stresses such as drought and nutrient limitation. While setting out the state-of-the-art developments of biogeochemical and ecological modelling, we explore and highlight the role of plant diversity in the regulation of the ecosystem processes underlying the ecosystems services provided by multi-species grasslands. An extensive literature and model survey was carried out with an emphasis on technically advanced models reconciling biogeochemistry and biodiversity, which are readily applicable to managed grasslands in temperate latitudes. We propose a roadmap of promising developments in modelling.
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    A Parametric Model for Local Air Exchange Rate of Naturally Ventilated Barns
    (Basel : MDPI AG, 2021) Doumbia, E. Moustapha; Janke, David; Yi, Qianying; Prinz, Alexander; Amon, Thomas; Kriegel, Martin; Hempel, Sabrina
    With an increasing number of naturally ventilated dairy barns (NVDBs), the emission of ammonia and greenhouse gases into the surrounding environment is expected to increase as well. It is very challenging to accurately determine the amount of gases released from a NVDB on-farm. Moreover, control options for the micro-climate to increase animal welfare are limited in an NVDB at present. Both issues are due to the complexity of the NVDB micro-environment, which is subject to temporal (such as wind direction and temperature) and spatial (such as openings and animals acting as airflow obstacles) fluctuations. The air exchange rate (AER) is one of the most valuable evaluation entities, since it is directly related to the gas emission rate and animal welfare. In this context, our study determined the general and local AERs of NVDBs of different shapes under diverse airflow conditions. Previous works identified main influencing parameters for the general AER and mathematically linked them together to predict the AER of the barn as a whole. The present research study is a continuation and extension of previous studies about the determination of AER. It provides new insights into the influence of convection flow regimes. In addition, it goes further in precision by determining the local AERs, depending on the position of the considered volume inside the barn. After running several computational fluid dynamics (CFD) simulations, we used the statistical tool of general linear modeling in order to identify quantitative relationships between the AER and the following five influencing parameters, the length/width ratio of the barn, the side opening configuration, the airflow temperature, magnitude and incoming direction. The work succeeded in taking the temperature into account as a further influencing parameter in the model and, thus, for the first time, in analysing the effect of the different types of flow convection in this context. The resulting equations predict the barn AER with an R2 equals 0.98 and the local AER with a mean R2 equals around 0.87. The results go a step further in the precise determination of the AER of NVDB and, therefore, are of fundamental importance for a better and deeper understanding of the interaction between the driving forces of AER in NVDB.
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    Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver
    (Basel : MDPI, 2021) Janke, David; Swaminathan, Senthilathiban; Hempel, Sabrina; Kasper, Robert; Amon, Thomas
    Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources.