Search Results
Nitrous oxide emissions from winter oilseed rape cultivation
2017, Ruser, Reiner, Fuß, Roland, Andres, Monique, Hegewald, Hannes, Kesenheimer, Katharina, Köbke, Sarah, Räbiger, Thomas, Quinones, Teresa Suarez, Augustin, Jürgen, Christen, Olaf, Dittert, Klaus, Kage, Henning, Lewandowski, Iris, Prochnow, Annette, Stichnothe, Heinz, Flessa, Heinz
Winter oilseed rape (Brassica napus L., WOSR) is the major oil crop cultivated in Europe. Rapeseed oil is predominantly used for production of biodiesel. The framework of the European Renewable Energy Directive requires that use of biofuels achieves GHG savings of at least 50% compared to use of fossil fuel starting in 2018. However, N2O field emissions are estimated using emission factors that are not specific for the crop and associated with strong uncertainty. N2O field emissions are controlled by N fertilization and dominate the GHG balance of WOSR cropping due to the high global warming potential of N2O. Thus, field experiments were conducted to increase the data basis and subsequently derive a new WOSR-specific emission factor. N2O emissions and crop yields were monitored for three years over a range of N fertilization intensities at five study sites representative of German WOSR production. N2O fluxes exhibited the typical high spatial and temporal variability in dependence on soil texture, weather and nitrogen availability. The annual N2O emissions ranged between 0.24 kg and 5.48 kg N2O-N ha−1 a−1. N fertilization increased N2O emissions, particularly with the highest N treatment (240 kg N ha−1). Oil yield increased up to a fertilizer amount of 120 kg N ha−1, higher N-doses increased grain yield but decreased oil concentrations in the seeds. Consequently oil yield remained constant at higher N fertilization. Since, yield-related emission also increased exponentially with N surpluses, there is potential for reduction of the N fertilizer rate, which offers perspectives for the mitigation of GHG emissions. Our measurements double the published data basis of annual N2O flux measurements in WOSR. Based on this extended dataset we modeled the relationship between N2O emissions and fertilizer N input using an exponential model. The corresponding new N2O emission factor was 0.6% of applied fertilizer N for a common N fertilizer amount under best management practice in WOSR production (200 kg N ha−1 a−1). This factor is substantially lower than the linear IPCC Tier 1 factor (EF1) of 1.0% and other models that have been proposed. © 2017
Livelihood and climate trade-offs in Kenyan peri-urban vegetable production
2017, Kurgat, Barnabas K., Stöber, Silke, Mwonga, Samuel, Lotze-Campen, Hermann, Rosenstock, Todd S.
Trade-offs between livelihood and environmental outcomes due to agricultural intensification in sub-Saharan Africa are uncertain. The present study measured yield, economic performance and nitrous oxide (N2O) emissions in African indigenous vegetable (AIV) production to investigate the optimal nutrient management strategies. In order to achieve this, an on-farm experiment with four treatments – (1) 40 kg N/ha diammonium phosphate (DAP), (2) 10 t/ha cattle manure, (3) 20 kg N/ha DAP and 5 t/ha cattle manure and (4) a no-N input control – was performed for two seasons. Yields and N2O emissions were directly measured with subsampling and static chambers/gas chromatography, respectively. Economic outcomes were estimated from semi-structured interviews (N = 12). Trade-offs were quantified by calculating N2O emissions intensity (N2OI) and N2O emissions economic intensity (N2OEI). The results indicate that, DAP alone resulted at least 14% greater yields, gross margin and returns to labour in absolute terms but had the highest emissions (p = 0.003). Productivity-climate trade-offs, expressed as N2OI, were statistically similar for DAP and mixed treatments. However, N2OEI was minimized under mixed management (p = 0.0004) while maintaining productivity and gross margins. We therefore conclude that soil fertility management strategies that mix inorganic and organic source present a pathway to sustainable intensification in AIV production. Future studies of GHG emissions in crop production need to consider not only productivity but economic performance when considering trade-offs.
Biochar research activities and their relation to development and environmental quality. A meta-analysis
2017-6-6, Mehmood, Khalid, Chávez Garcia, Elizabeth, Schirrmann, Michael, Ladd, Brenton, Kammann, Claudia, Wrage-Mönnig, Nicole, Siebe, Christina, Estavillo, Jose M., Fuertes-Mendizabal, Teresa, Cayuela, Mariluz, Sigua, Gilbert, Spokas, Kurt, Cowie, Annette L., Novak, Jeff, Ippolito, James A., Borchard, Nils
Biochar is the solid product that results from pyrolysis of organic materials. Its addition to highly weathered soils changes physico-chemical soil properties, improves soil functions and enhances crop yields. Highly weathered soils are typical of humid tropics where agricultural productivity is low and needs to be raised to reduce human hunger and poverty. However, impact of biochar research on scientists, politicians and end-users in poor tropical countries remains unknown; assessing needs and interests on biochar is essential to develop reliable knowledge transfer/translation mechanisms. The aim of this publication is to present results of a meta-analysis conducted to (1) survey global biochar research published between 2010 and 2014 to assess its relation to human development and environmental quality, and (2) deduce, based on the results of this analysis, priorities required to assess and promote the role of biochar in the development of adapted and sustainable agronomic methods. Our main findings reveal for the very first time that: (1) biochar research associated with less developed countries focused on biochar production technologies (26.5 ± 0.7%), then on biochars’ impact on chemical soil properties (18.7 ± 1.2%), and on plant productivity (17.1 ± 2.6%); (2) China dominated biochar research activities among the medium developed countries focusing on biochar production technologies (26.8 ± 0.5%) and on use of biochar as sorbent for organic and inorganic compounds (29.1 ± 0.4%); and (3) the majority of biochar research (69.0±2.9%) was associated with highly developed countries that are able to address a higher diversity of questions. Evidently, less developed countries are eager to improve soil fertility and agricultural productivity, which requires transfer and/or translation of biochar knowledge acquired in highly developed countries. Yet, improving local research capacities and encouraging synergies across scientific disciplines and countries are crucial to foster development of sustainable agronomy in less developed countries. © 2017, The Author(s).
Comparing methane emissions from different sheep-keeping systems in semiarid regions: A case study of Syria
2014, Hijazi, O., Berg, W., Moussa, S., Ammon, C., von Bobrutzki, K., Brunsch, R.
Sheep husbandry represents a significant source of methane (CH4) in semiarid grassland regions such as Syria. However, the contribution of sheep to CH4 emissions in Syria is still unknown. This study was designed to quantify CH4 emissions and identify possible mitigation strategies for their reduction. Methodology developed by the Intergovernmental Panel on Climate Change (IPCC) was used to estimate CH4 emissions. A survey was conducted on 64 farms from different locations in Syria in 2009. Data were collected concerning sheep-keeping systems (SKSs), body mass, milk and wool yield, farm locations, feed rations, periods of grazing on the Steppe, the duration of pasturing on agricultural residuals and time periods when sheep were kept in stables. Using a linear statistical model, the influence of SKS, geographical region and sheep body mass on emitted CH4 were analysed. The results showed that the geographical region, SKS and sheep body mass had significant effects (P < 0.05) on CH4 emissions. According to the model, the mean values of estimated CH4 emissions from extensive, semi-intensive and intensive SKSs were 26 ± 0.9, 22.5 ± 1.3 and 13.5 ± 1.7 kg/sheep year, respectively. In comparing differences between the least square means of CH4 emissions, the extensive and semi-intensive SKSs produced 92% and 66% higher CH4 emissions compared to intensive SKS. The differences in CH4 emissions within the distinct SKSs were attributed to dietary composition. Extensive SKS used a less concentrated feeding regime (98 ± 17 day/year) than semi-intensive SKS (114 ± 47 day/year), and intensive SKS employed concentrated feeding year round. Furthermore, it was observed that sheep with the same body mass produced higher CH4 emissions in extensive SKS than in semi-intensive and intensive SKSs. Moreover, the semi-intensive SKS occupied more natural pastures than extensive SKS, which caused an overuse of the Steppe. Therefore, an effective mitigation strategy involves the use of more digestible feed, which would be accomplished by increasing the quantity of concentrated feed. Owing to unfavourable farming conditions, low-cost nonconventional feeds such as the residuals of wheat and cotton should be used to improve sheep management practices to reduce Steppe overgrazing in the extensive and semi-intensive SKSs of Syria and other semiarid areas.
Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR
2019, Tsoulias, Nikos, Paraforos, Dimitrios S., Fountas, Spyros, Zude-Sasse, Manuela
Data of canopy morphology are crucial for cultivation tasks within orchards. In this study, a 2D light detection and range (LiDAR) laser scanner system was mounted on a tractor, tested on a box with known dimensions (1.81 m × 0.6 m × 0.6 m), and applied in an apple orchard to obtain the 3D structural parameters of the trees (n = 224). The analysis of a metal box which considered the height of four sides resulted in a mean absolute error (MAE) of 8.18 mm with a bias (MBE) of 2.75 mm, representing a root mean square error (RMSE) of 1.63% due to gaps in the point cloud and increased incident angle with enhanced distance between laser aperture and the object. A methodology based on a bivariate point density histogram is proposed to estimate the stem position of each tree. The cylindrical boundary was projected around the estimated stem positions to segment each individual tree. Subsequently, height, stem diameter, and volume of the segmented tree point clouds were estimated and compared with manual measurements. The estimated stem position of each tree was defined using a real time kinematic global navigation satellite system, (RTK-GNSS) resulting in an MAE and MBE of 33.7 mm and 36.5 mm, respectively. The coefficient of determination (R2) considering manual measurements and estimated data from the segmented point clouds appeared high with, respectively, R2 and RMSE of 0.87 and 5.71% for height, 0.88 and 2.23% for stem diameter, as well as 0.77 and 4.64% for canopy volume. Since a certain error for the height and volume measured manually can be assumed, the LiDAR approach provides an alternative to manual readings with the advantage of getting tree individual data of the entire orchard.
An alternative to field retting: Fibrous materials based on wet preserved hemp for the manufacture of composites
2019, Gusovius, H.-J., Lühr, C., Hoffmann, T., Pecenka, R., Idler, C.
A process developed at the Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) for the supply and processing of wet-preserved fiber plants opens up new potential uses for such resources. The processing of industrial hemp into fiber materials and products thereof is undergoing experimental research along the value-added chain from the growing process through to the manufacturing of product samples. The process comprises the direct harvesting of the field-fresh hemp and the subsequent anaerobic storage of the entire plant material. Thus, process risk due to unfavorable weather conditions is prevented in contrast to common dew retting procedures. The effects of the anaerobic storage processes on the properties of the bast part of the plant material are comparable to the results of common retting procedures. Harvest storage, as well as further mechanical processing, leads to different geometrical properties compared to the bast fibers resulting from traditional post harvesting treatment and decortication. The fiber raw material obtained in this way is well suited to the production of fiberboards and the reinforcement of polymer or mineral bonded composites. The objective of this paper is to present recent research results on final products extended by a comprehensive overview of the whole supply chain in order to enable further understanding of the result influencing aspects of prior process steps.
Effect of densification variables on water resistance of corn cob briquettes
2019, Orisaleye, J.I., Jekayinfa, S.O., Pecenka, R., Onifade, T.B.
Solid biofuels can be used in heat and power generation applications. The utilization of agricultural residues for this purpose would be of immense benefit to rural communities of developing countries where the resource is being produced. Water resistance is a crucial property for transport and storage of biomass briquettes under moist climate conditions. In this study, the effect of process and material variables on the water resistance property of corn cob briquettes was investigated. The water resistance of briquettes produced ranged between 32.6 and 94.8% for die temperature between 90 °C and 120 °C, hold time from 7.5 to 15 minutes and die pressures between 9 and 15 MPa. A higher die temperature resulted in an increase in the water resistance of the biomass briquettes. Also, increasing the hold time improved the water resistance of the briquettes. Using a particle size less than 2.5 mm resulted in higher briquette water resistance property compared to briquettes produced from particle sizes greater than 2.5 mm. It was also shown that the effect of the interaction of the temperature with particle size on the water resistance of corn cob briquettes was statistically significant (p < 0.05). © 2019, Eesti Pollumajandusulikool. All rights reserved.
Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
2017, Fronzek, Stefan, Pirttioja, Nina, Carter, Timothy R., Bindi, Marco, Hoffmann, Holger, Palosuo, Taru, Ruiz-Ramos, Margarita, Tao, Fulu, Trnka, Miroslav, Acutis, Marco, Asseng, Senthold, Baranowski, Piotr, Basso, Bruno, Bodin, Per, Buis, Samuel, Cammarano, Davide, Deligios, Paola, Destain, Marie-France, Dumont, Benjamin, Ewert, Frank, Ferrise, Roberto, François, Louis, Gaiser, Thomas, Hlavinka, Petr, Jacquemin, Ingrid, Kersebaum, Kurt Christian, Kollas, Chris, Krzyszczak, Jaromir, Lorite, Ignacio J., Minet, Julien, Minguez, M. Ines, Montesino, Manuel, Moriondo, Marco, Müller, Christoph, Nendel, Claas, Öztürk, Isik, Perego, Alessia, Rodríguez, Alfredo, Ruane, Alex C., Ruget, Françoise, Sanna, Mattia, Semenov, Mikhail A., Slawinski, Cezary, Stratonovitch, Pierre, Supit, Iwan, Waha, Katharina, Wang, Enli, Wu, Lianhai, Zhao, Zhigan, Rötter, Reimund P.
Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
Milk fatty acids estimated by mid-infrared spectroscopy and milk yield can predict methane emissions in dairy cows
2018-5-2, Engelke, Stefanie W., Daş, Gürbüz, Derno, Michael, Tuchscherer, Armin, Berg, Werner, Kuhla, Björn, Metges, Cornelia C.
Ruminant enteric methane emission contributes to global warming. Although breeding low methane-emitting cows appears to be possible through genetic selection, doing so requires methane emission quantification by using elaborate instrumentation (respiration chambers, SF6 technique, GreenFeed) not feasible on a large scale. It has been suggested that milk fatty acids are promising markers of methane production. We hypothesized that methane emission can be predicted from the milk fatty acid concentrations determined by mid-infrared spectroscopy, and the integration of energy-corrected milk yield would improve the prediction. Therefore, we examined relationships between methane emission of cows measured in respiration chambers and milk fatty acids, predicted by mid-infrared spectroscopy, to derive diet-specific and general prediction equations based on milk fatty acid concentrations alone and with the additional consideration of energy-corrected milk yield. Cows were fed diets differing in forage type and linseed supplementation to generate a large variation in both CH4 emission and milk fatty acids. Depending on the diet, equations derived from regression analysis explained 61 to 96% of variation of methane emission, implying the potential of milk fatty acid data predicted by mid-infrared spectroscopy as novel proxy for direct methane emission measurements. When data from all diets were analyzed collectively, the equation with energy-corrected milk yield (CH4 (L/day) = − 1364 + 9.58 × energy-corrected milk yield + 18.5 × saturated fatty acids + 32.4 × C18:0) showed an improved coefficient of determination of cross-validation R2 CV = 0.72 compared to an equation without energy-corrected milk yield (R2 CV = 0.61). Equations developed for diets supplemented by linseed showed a lower R2 CV as compared to diets without linseed (0.39 to 0.58 vs. 0.50 to 0.91). We demonstrate for the first time that milk fatty acid concentrations predicted by mid-infrared spectroscopy together with energy-corrected milk yield can be used to estimate enteric methane emission in dairy cows. © 2018, The Author(s).
Hydrothermal Carbonization and Pyrolysis of Sewage Sludge: Effects on Lolium perenne Germination and Growth
2019, Paneque, Marina, Knicker, Heike, Kern, Jürgen, De la Rosa, José María
The pyrolysis and hydrothermal carbonization (HTC) of sewage sludge (SS) resulted in products free of pathogens, with the potential for being used as soil amendment. With this work, we evaluated the impact of dry pyrolysis-treated (600 °C, 1 h) and HTC-treated (200 °C, 260 °C; 0.5 h, 3 h) SS on the germination, survival, and growth of Lolium perenne during an 80 day greenhouse experiment. Therefore, the hydrochars and pyrochars were amended to a Calcic Cambisol at doses of 5 and 25 t ha−1. The addition of sludge pyrochars to the Cambisol did not affect Lolium germination, survival rates or plant yields. However, the use 25 t ha−1 of wood biochar reduced germination and survival rates, which may be related to the low N availability of this sample. In comparison to the control, higher or equal plant biomass was produced in the hydrochar-amended pots, even though some hydrochars decreased plant germination and survival rates. Among all the evaluated char properties, only the organic and inorganic N contents of the chars, along with their organic C values, positively correlated with total and shoot biomass production. Our work demonstrates the N fertilization potential of the hydrochar produced at low temperature, whereas the hydrochar produced at 260 °C and the pyrochars were less efficient with respect to plant yields.