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- ItemAirflow 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.
- ItemBEXIS2: 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, BirgittaObtaining 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.
- ItemFactors 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, BanoNitrous 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.
- ItemClimate 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, SofiaThe 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.
- ItemNear 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, ChristophImmediate 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.
- ItemIncorporating 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, GianniMulti-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.
- ItemA 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, SabrinaWith 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.
- ItemExtrusion of Different Plants into Fibre for Peat Replacement in Growing Media: Adjustment of Parameters to Achieve Satisfactory Physical Fibre-Properties(Basel : MDPI AG, 2021) Dittrich, Christian; Pecenka, Ralf; Loes, Anne-Kristin; Caceres, Rafaela; Conroy, Judith; Rayns, Francis; Schmutz, Ulrich; Kir, Alev; Kruggel-Emden, HaraldPeat is a highly contentious input in agriculture. Replacing or reducing peat by substitution with lignocellulosic biomass processed into fibre by twin-screw-extrusion could contribute to more sustainable agriculture with regard to horticultural production. Therefore, plant wastes including pruning from Olea europaea L. and Vitis spp. L., residues from perennial herbs like Salvia spp. L., Populus spp. L. and forest biomass were processed to fibre for peat replacement with a biomass extruder. The water-holding-capacity (WHC), particle-size-distribution and other physical fibre characteristics were determined and compared to peat. The specific energy demand during extrusion was measured for aperture settings from 6–40 mm. No fibre reached the 82% WHC of peat. At the setting of 20 mm of all materials investigated, Salvia performed best with a WHC of 53% and moderate specific energy demand (167 kWh tDM−1) followed by Olea europaea with a WHC of 43% and a low energy demand (93 kWh tDM−1). For Populus, opening the aperture from 20–40 mm decreased energy demand by 41% and WHC by 27%. The drying of biomass for storage and remoistening during extrusion increased the specific energy demand. Despite a lower WHC than peat, all investigated materials are suitable to replace peat in growing media regarding their physical properties.
- ItemSimultaneous Calibration of Grapevine Phenology and Yield with a Soil–Plant–Atmosphere System Model Using the Frequentist Method(Basel : MDPI, 2021-8-20) Yang, Chenyao; Menz, Christoph; Fraga, Helder; Reis, Samuel; Machado, Nelson; Malheiro, Aureliano C.; Santos, João A.Reliable estimations of parameter values and associated uncertainties are crucial for crop model applications in agro-environmental research. However, estimating many parameters simultaneously for different types of response variables is difficult. This becomes more complicated for grapevines with different phenotypes between varieties and training systems. Our study aims to evaluate how a standard least square approach can be used to calibrate a complex grapevine model for simulating both the phenology (flowering and harvest date) and yield of four different variety–training systems in the Douro Demarcated Region, northern Portugal. An objective function is defined to search for the best-fit parameters that result in the minimum value of the unweighted sum of the normalized Root Mean Squared Error (nRMSE) of the studied variables. Parameter uncertainties are estimated as how a given parameter value can determine the total prediction variability caused by variations in the other parameter combinations. The results indicate that the best-estimated parameters show a satisfactory predictive performance, with a mean bias of −2 to 4 days for phenology and −232 to 159 kg/ha for yield. The corresponding variance in the observed data was generally well reproduced, except for one occasion. These parameters are a good trade-off to achieve results close to the best possible fit of each response variable. No parameter combinations can achieve minimum errors simultaneously for phenology and yield, where the best fit to one variable can lead to a poor fit to another. The proposed parameter uncertainty analysis is particularly useful to select the best-fit parameter values when several choices with equal performance occur. A global sensitivity analysis is applied where the fruit-setting parameters are identified as key determinants for yield simulations. Overall, the approach (including uncertainty analysis) is relatively simple and straightforward without specific pre-conditions (e.g., model continuity), which can be easily applied for other models and crops. However, a challenge has been identified, which is associated with the appropriate assumption of the model errors, where a combination of various calibration approaches might be essential to have a more robust parameter estimation.
- ItemPerspectives from CO+RE: How COVID-19 changed our food systems and food security paradigms(Amsterdam : Elsevier, 2020) Bakalis, Serafim; Valdramidis, Vasilis P.; Argyropoulos, Dimitrios; Ahrne, Lilia; Chen, Jianshe; Cullen, P.J.; Cummins, Enda; Datta, Ashim K.; Emmanouilidis, Christos; Foster, Tim; Fryer, Peter J.; Gouseti, Ourania; Hospido, Almudena; Knoerzer, Kai; LeBail, Alain; Marangoni, Alejandro G.; Rao, Pingfan; Schlüter, Oliver K.; Taoukis, Petros; Xanthakis, Epameinondas; Van Impe, Jan F.M.[no abstract available]