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- ItemAssessment of continuous vaginal logger-based temperature monitoring in fever-induced gilts(Dubai : Science Publications, 2013) Schmidt, Mariana; Ammon, Christian; Schon, Peter; Manteuffel, Christian; Hoffmann, GundulaThe aim of this study was to identify a low risk method to induce fever in gilts and to evaluate vaginal sensors for temperature monitoring. Therefore, a rhinitis atrophicans vaccine was used to induce fever to evaluate sensors and behavioral patterns. During 11 trials, two of four animals were injected with 2 mL of the vaccine Porcilis AR-T DF (Intervet) and the other two animals were treated with 2 mL of 0.9% NaCl as controls. A temperature logger (TRIX-8, LogTag Recorders, Auckland, New Zealand) was used to continuously monitor the vaginal temperature. Additionally, rectal temperatures were measured four times daily. The water consumption, food intake and locomotion behaviors of the animals were analysed one day before treatment and during the day of the treatment. The vaccine induced fever in all gilts, which occurred approximately 5.87 h after vaccination. The vaginal logger temperatures and the rectal temperatures showed a linear correlation in 21 vaccinated gilts (r = 0.86; p<0.0001) and 22 non-vaccinated gilts (r = 0.65; P<0.0001). The vaginal logger can be continuously used to measure the core temperature. Water intake decreased (p<0.0001) in the gilts with fever, whereas food intake did not change (p = 0.9411). The vaccinated gilts spent 79±16 more minutes per day lying after the vaccination (p<0.001) in comparison to the day before the vaccination. Treatment with this vaccine provides the opportunity to induce fever over a short time period (5.13 h) and mild sickness behavior in gilts to investigate disease indicators.
- ItemNitrous oxide emissions from winter oilseed rape cultivation(Amsterdam [u.a.] : Elsevier, 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, HeinzWinter 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
- ItemDNA and RNA extraction and quantitative real-time PCR-based assays for biogas biocenoses in an interlaboratory comparison(Basel : MDPI, 2016) Lebuhn, Michael; Derenkó, Jaqueline; Rademacher, Antje; Helbig, Susanne; Munk, Bernhard; Pechtl, Alexander; Stolze, Yvonne; Prowe, Steffen; Schwarz, Wolfgang H.; Schlüter, Andreas; Liebl, Wolfgang; Klocke, MichaelFive institutional partners participated in an interlaboratory comparison of nucleic acid extraction, RNA preservation and quantitative Real-Time PCR (qPCR) based assays for biogas biocenoses derived from different grass silage digesting laboratory and pilot scale fermenters. A kit format DNA extraction system based on physical and chemical lysis with excellent extraction efficiency yielded highly reproducible results among the partners and clearly outperformed a traditional CTAB/chloroform/isoamylalcohol based method. Analytical purpose, sample texture, consistency and upstream pretreatment steps determine the modifications that should be applied to achieve maximum efficiency in the trade-off between extract purity and nucleic acid recovery rate. RNA extraction was much more variable, and the destination of the extract determines the method to be used. RNA stabilization with quaternary ammonium salts was an as satisfactory approach as flash freezing in liquid N2. Due to co-eluted impurities, spectrophotometry proved to be of limited value for nucleic acid qualification and quantification in extracts obtained with the kit, and picoGreen® based quantification was more trustworthy. Absorbance at 230 nm can be extremely high in the presence of certain chaotropic guanidine salts, but guanidinium isothiocyanate does not affect (q)PCR. Absolute quantification by qPCR requires application of a reliable internal standard for which correct PCR efficiency and Y-intercept values are important and must be reported.
- ItemUncertainty in the measurement of indoor temperature and humidity in naturally ventilated dairy buildings as influenced by measurement technique and data variability(Amsterdam : Elsevier, 2017) Hempel, Sabrina; König, Marcel; Menz, Christoph; Janke, David; Amon, Barbara; Banhazi, Thomas M.; Estellés, Fernando; Amon, ThomasThe microclimatic conditions in dairy buildings affect animal welfare and gaseous emissions. Measurements are highly variable due to the inhomogeneous distribution of heat and humidity sources (related to farm management) and the turbulent inflow (associated with meteorologic boundary conditions). The selection of the measurement strategy (number and position of the sensors) and the analysis methodology adds to the uncertainty of the applied measurement technique. To assess the suitability of different sensor positions, in situations where monitoring in the direct vicinity of the animals is not possible, we collected long-term data in two naturally ventilated dairy barns in Germany between March 2015 and April 2016 (horizontal and vertical profiles with 10 to 5 min temporal resolution). Uncertainties related to the measurement setup were assessed by comparing the device outputs under lab conditions after the on-farm experiments. We found out that the uncertainty in measurements of relative humidity is of particular importance when assessing heat stress risk and resulting economic losses in terms of temperature-humidity index. Measurements at a height of approximately 3 m–3.5 m turned out to be a good approximation for the microclimatic conditions in the animal occupied zone (including the air volume close to the emission active zone). However, further investigation along this cross-section is required to reduce uncertainties related to the inhomogeneous distribution of humidity. In addition, a regular sound cleaning (and if possible recalibration after few months) of the measurement devices is crucial to reduce the instrumentation uncertainty in long-term monitoring of relative humidity in dairy barns. © 2017 The Authors
- ItemHydrothermal carbonization (HTC): Near infrared spectroscopy and partial least-squares regression for determination of selective components in HTC solid and liquid products derived from maize silage(Amsterdam : Elsevier, 2014) Reza, M. Toufiq; Becker, Wolfgang; Sachsenheimer, Kerstin; Mumme, JanNear-infrared (NIR) spectroscopy was evaluated as a rapid method of predicting fiber components (hemicellulose, cellulose, lignin, and ash) and selective compounds of hydrochar and corresponding process liquor produced by hydrothermal carbonization (HTC) of maize silage. Several HTC reaction times and temperatures were applied and NIR spectra of both HTC solids and liquids were obtained and correlated with concentration determined from van-Soest fiber analysis, IC, and UHPLC. Partial least-squares regression was applied to calculate models for the prediction of selective substances. The model developed with the spectra had the best performance in 3–7 factors with a correlation coefficient, which varied between 0.9275–0.9880 and 0.9364–0.9957 for compounds in solid and liquid, respectively. Calculated root mean square errors of prediction (RMSEP) were 0.42–5.06 mg/kg. The preliminary results indicate that NIR, a widely applied technique, might be applied to determine chemical compounds in HTC solid and liquid.
- ItemEstimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR(Basel : MDPI AG, 2019) Tsoulias, Nikos; Paraforos, Dimitrios S.; Fountas, Spyros; Zude-Sasse, ManuelaData 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.
- ItemExpressing stemflow commensurate with its ecohydrological importance(Amsterdam [u.a.] : Elsevier Science, 2018) Carlyle-Moses, Darryl E.; Iida, Shin'ichi; Germer, Sonja; Llorens, Pilar; Michalzik, Beate; Nanko, Kazuki; Tischer, Alexander; Levia, Delphis F.Despite some progress, the importance of stemflow remains obscured partly due to computations emphasizing canopy interception loss. We advocate for two metrics—the stand-scale funneling ratio and the stand-scale infiltration funneling ratio—to more accurately portray stemflow inputs and increase comparability across ecosystems. These metrics yield per unit area stemflow inputs orders of magnitude greater than what would have been delivered by throughfall or precipitation alone. We recommend that future studies employ these stand-scale funnelling metrics to express stemflow commensurate with its ecohydrological importance and better conceptualize the role of stemflow in plant-soil interactions, permitting advances in critical zone science. © 2018 The Authors
- ItemThe MiLA tool: Modeling greenhouse gas emissions and cumulative energy demand of energy crop cultivation in rotation(Amsterdam : Elsevier, 2016) Peter, Christiane; Specka, Xenia; Aurbacher, Joachim; Peter Kornatz, Peter Kornatz; Herrmann, Christiane; Heiermann, Monika; Müller, Janine; Nendel, ClaasCrop rotations are part of current agricultural practice, since they and their effects can contribute to a sustainable agricultural cropping system. However, in current Life Cycle Assessment (LCA) studies, crop rotation effects are insufficiently considered, since these effects are difficult to measure. LCA studies from crop production typically take only one vegetation period into account. As a result, the consideration of how the assessed crop is influenced by the previous crop (crop rotation effects) including: (1) nutrient carryover, (2) reduction in operational requirements and (3) different intensity and timing of farming activities, is outside of the system boundary. However, ignoring these effects may lead to incorrect interpretation of LCA results and consequently to poor agricultural management as well as poor policy decisions. A new LCA tool called the “Model for integrative Life Cycle Assessment in Agriculture (MiLA)” is presented in this work. MiLA has been developed to assess GHG emissions and cumulative energy demands (CED) of cropping systems by taking the characteristics of crop cultivation in rotation into account. This tool enables the user to analyze cropping systems at farm level in order to identify GHG mitigation options and energy-efficient cropping systems. The tool was applied to a case study, including two crop rotations in two different regions in Germany with the goal of demonstrating the effectiveness of this tool on LCA results. Results show that including crop rotation effects can influence the GHG emission result of the individual crop by − 34% up to + 99% and the CED by − 16 up to + 89%. Expanding the system boundary by taking the whole crop rotation into account as well as providing the results based on different functional units improves LCA of energy crop production and helps those making the assessment to draw a more realistic picture of the interactions between crops while increasing the reliability of the LCA results.
- ItemAn alternative to field retting: Fibrous materials based on wet preserved hemp for the manufacture of composites(Basel : MDPI AG, 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.
- ItemMilk fatty acids estimated by mid-infrared spectroscopy and milk yield can predict methane emissions in dairy cows(Berlin ; Heidelberg : Springer, 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).