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- ItemDirect nitrous oxide emissions from oilseed rape cropping – a meta-analysis(Milton Park : Taylor & Francis, 2014) Walter, Katja; Don, Axel; Fuß, Roland; Kern, Jürgen; Drewer, Julia; Flessa, HeinzOilseed rape is one of the leading feedstocks for biofuel production in Europe. The climate change mitigation effect of rape methyl ester (RME) is particularly challenged by the greenhouse gas (GHG) emissions during crop production, mainly as nitrous oxide (N2O) from soils. Oilseed rape requires high nitrogen fertilization and crop residues are rich in nitrogen, both potentially causing enhanced N2O emissions. However, GHG emissions of oilseed rape production are often estimated using emission factors that account for crop-type specifics only with respect to crop residues. This meta-analysis therefore aimed to assess annual N2O emissions from winter oilseed rape, to compare them to those of cereals and to explore the underlying reasons for differences. For the identification of the most important factors, linear mixed effects models were fitted with 43 N2O emission data points deriving from 12 different field sites. N2O emissions increased exponentially with N-fertilization rates, but interyear and site-specific variability were high and climate variables or soil parameters did not improve the prediction model. Annual N2O emissions from winter oilseed rape were 22% higher than those from winter cereals fertilized at the same rate. At a common fertilization rate of 200 kg N ha−1 yr−1, the mean fraction of fertilizer N that was lost as N2O-N was 1.27% for oilseed rape compared to 1.04% for cereals. The risk of high yield-scaled N2O emissions increased after a critical N surplus of about 80 kg N ha−1 yr−1. The difference in N2O emissions between oilseed rape and cereal cultivation was especially high after harvest due to the high N contents in oilseed rape's crop residues. However, annual N2O emissions of winter oilseed rape were still lower than predicted by the Stehfest and Bouwman model. Hence, the assignment of oilseed rape to the crop-type classes of cereals or other crops should be reconsidered.
- ItemNeues Prinzip eines Mähhackers für Kurzumtriebsplantagen(Darmstadt : KTBL, 2012) Ehlert, Detlef; Pecenka, Ralf; Wiehe, JensGegenwärtig auf dem Markt verfügbare Mähhacker für Kurzumtriebsplantagen (KUPs) auf Basis von Feldhäckslern haben Nachteile hinsichtlich der Maschinenmasse und der hohen Investitionskosten. Traktorgebundene Geräte sind bisher nur begrenzt leistungsfähig. Um einen Beitrag zur Erweiterung des Angebots kostengünstiger Erntetechnik zu leisten, wurde ein neuartiges Prinzip eines traktorbasierten Mähhackers für einreihige KUPs entwickelt, der sich durch einen einfachen Aufbau und ein breites Einsatzspektrum auszeichnet.
- ItemStrategy for the development of a smart NDVI camera system for outdoor plant detection and agricultural embedded systems(Basel : MDPI, 2013) Dworak, Volker; Selbeck, Joern; Dammer, Karl-Heinz; Hoffmann, Matthias; Zarezadeh, Ali Akbar; Bobda, ChristopheThe application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI) for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR) and the red channel optical frequency band. Two aligned charge coupled device (CCD) chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed.
- ItemRecovery and techno-functionality of flours and proteins from two edible insect species: Meal worm (Tenebrio molitor) and black soldier fly (Hermetia illucens) larvae(Amsterdam : Elsevier, 2016) Bußler, Sara; Rumpold, Birgit A.; Jander, Elisabeth; Rawel, Harshadrai M.; Schlüter, Oliver K.Depending on the species, edible insects are highly nutritious and thus represent a noteworthy alternative food and feed source. The current work investigates the protein extractability and techno-functionality of insect flour fractions recovered from Tenebrio molitor and Hermetia illucens. T. molitor and H. illucens flours contained about 20% crude fat and 60% and 36 % crude protein, respectively. Defatting reduced the crude fat content to 2.8% (T. molitor) and 8.8% (H. illucens) and increased the crude protein content to 68% and 47%, respectively. To isolate proteins from the flours, protein solubility was optimized by varying the pH, the ionic strength, and the extraction temperature of the solvent. All products and by-products accumulated in the protein production process were characterized by composition, selected techno-functional properties, protein solubility, composition and structure as well as their microbial load.
- ItemImpact of different water activities (aw) adjusted by solutes on high pressure high temperature inactivation of Bacillus amyloliquefaciens spores(Lausanne : Frontiers Media, 2015) Sevenich, Robert; Reineke, Kai; Hecht, Philipp; Fröhling, Antje; Rauh, Cornelia; Schlüter, Oliver; Knorr, DietrichMuch research has been conducted to comprehend the mechanisms of high pressure (HP) inactivation of spores in aqueous systems but for food model systems these information are scarce. In these systems spores can interact with ingredients which then could possibly lead to retarded or reduced inactivation, which can cause a problem for the sterilization process. The protective mechanism of a reduced aw-value is still unclear. HP processing might prove valuable to overcome protective effects of solutes and achieve shorter process times for sterilization under HP. To gain insight into the underlying mechanisms five aw-values (0.9, 0.92, 0.94, 0.96, 1) were adjusted with two different solutes (NaCl, sucrose). Solutions were inoculated with spores of Bacillus amyloliquefaciens and treated at 105, 110, and 115°C at 600 MPa. Further a thermal inactivation was conducted at the same temperatures for a comparison with the HP data. Afterward, the influence of HP high temperature treatment on the inactivation, the dipicolinic acid (DPA)-release and membrane constitution was assessed by plate count, HPLC and flow cytometry (FCM). The results show that during HP treatments sucrose and salt both have a protective effect, in which the influence of sucrose on the retarded inactivation is higher. The threshold water activities (aw), which is 0.94, here salt and sucrose have a significant influence on the inactivation. The comparison of thermal (105–115°C) and HP and high temperature (600 MPa, 105–115°C) treated samples showed that the time needed to achieve a 4–5 log10 inactivation is reduced from 45 (aw = 1) to 75 (aw = 0.9) min at 105°C to 3 (aw = 1) to 15 (aw = 0.9) minutes at 600 MPa and 105°C. The release of DPA is the rate limiting step of the inactivation and therefore monitoring the release is of great interest. The DPA-release is slowed down in high concentrated solutions (e.g., sucrose, salt) in comparison to aw 1. Since there is a difference in the way the solutes protect the spore it could be seen as an inner spore membrane effect. Maybe as shown for vegetative microorganism the solutes can interact with membranes, e.g., the inner spore membrane. Flow cytometry (FCM) measurement data show a similar trend.
- ItemPrediction of the biogas production using GA and ACO input features selection method for ANN model(Amsterdam [u.a.] : Elsevier, 2019) Beltramo, Tanja; Klocke, Michael; Hitzmann, BerndThis paper presents a fast and reliable approach to analyze the biogas production process with respect to the biogas production rate. The experimental data used for the developed models included 15 process variables measured at an agricultural biogas plant in Germany. In this context, the concentration of volatile fatty acids, total solids, volatile solids acid detergent fibre, acid detergent lignin, neutral detergent fibre, ammonium nitrogen, hydraulic retention time, and organic loading rate were used. Artificial neural networks (ANN) were established to predict the biogas production rate. An ant colony optimization and genetic algorithms were implemented to perform the variable selection. They identified the significant process variables, reduced the model dimension and improved the prediction capacity of the ANN models. The best prediction of the biogas production rate was obtained with an error of prediction of 6.24% and a coefficient of determination of R2 = 0.9.
- ItemA computational model for path loss in wireless sensor networks in orchard environments(Basel : MDPI, 2014) Anastassiu, Hristos T.; Vougioukas, Stavros; Fronimos, Theodoros; Regen, Christian; Petrou, Loukas; Zude, Manuela; Käthner, JanaA computational model for radio wave propagation through tree orchards is presented. Trees are modeled as collections of branches, geometrically approximated by cylinders, whose dimensions are determined on the basis of measurements in a cherry orchard. Tree canopies are modeled as dielectric spheres of appropriate size. A single row of trees was modeled by creating copies of a representative tree model positioned on top of a rectangular, lossy dielectric slab that simulated the ground. The complete scattering model, including soil and trees, enhanced by periodicity conditions corresponding to the array, was characterized via a commercial computational software tool for simulating the wave propagation by means of the Finite Element Method. The attenuation of the simulated signal was compared to measurements taken in the cherry orchard, using two ZigBee receiver-transmitter modules. Near the top of the tree canopies (at 3 m), the predicted attenuation was close to the measured one—just slightly underestimated. However, at 1.5 m the solver underestimated the measured attenuation significantly, especially when leaves were present and, as distances grew longer. This suggests that the effects of scattering from neighboring tree rows need to be incorporated into the model. However, complex geometries result in ill conditioned linear systems that affect the solver’s convergence.
- ItemApplication of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury(Basel : MDPI AG, 2021) Yang, Zhuo; Li, Mo; East, Andrew R.; Zude-Sasse, ManuelaKiwifruit chilling injury (CI) damage occurs after long-term exposure to low temperature. A non-destructive approach to detect CI injury was tested in the present study, using a laser backscattering image (LBI) technique calibrated with 56 liquid phantoms for providing absorption coefficient (µa) and reduced scattering coefficient (µs’). Calibration of LBI resulted in a true-positive (TP) classification of 91.5% and 65.6% of predicted µs’ and µa, respectively. The optical properties of ‘SunGold™’and ‘Hayward’ kiwifruit were analysed at 520 nm with a two-step protocol capturing pre-classification according to the LBI parameters used in the calibration and estimation with the Farrell equation. Severely injured kiwifruit showed white corky tissue and water soaking, reduced soluble solids content and firmness measured destructively. Non-destructive classification results for ‘SunGold™’ showed a high percentage of TP for severe CI of 92% and 75% using LBI parameters directly and predicted µa and µs’ after pre-classification, respectively. The classification accuracy for severe CI ‘Hayward’ kiwifruit with LBI parameter was low (58%) and with µa and µs’ decreased further (35%), which was assumed to be due to interference caused by the long trichomes on the fruit surface.
- ItemAwassi sheep keeping in the Arabic steppe in relation to nitrous oxide emission from soil(Amsterdam : Elsevier, 2013) Hijazi, Omar; Berg, Werner; Moussa, Samouil; Ammon, Christian; von Bobrutzki, Kristina; Brunsch, ReinerSheep husbandry is the main source of income for farmers in arid zones. Increasing sheep production on steppes may increase the greenhouse gas production. The objective of this study was to investigate the nitrous oxide (N2O) emissions from the steppes for Awassi sheep keeping and feed cropping in arid zones such as Syria. The methodology developed by the Intergovernmental Panel on Climate Change (IPCC) was used to estimate N2O emissions. A survey was conducted on 64 farms in Syria to gather data for analysis. Precipitation and crop yield data from 2001 to 2009 were also used for calculation and modelling. Sheep-keeping systems, precipitation, year and the region have significant effects on N2O emissions (p<0.05). Emissions of N2O from lands with extensive, semi-intensive and intensive systems were 0.30 ± 0.093, 0.598± 0.113 and 2.243± 0.187 kg sheep1year1, respectively. Crop production was higher in regions with high precipitation levels, which helped to reduce N2O emissions. Using more residuals of wheat, cotton and soya as feed for sheep in the keeping systems evaluated may decrease the overuse of steppe regions and N2O emissions. Nitrous oxide emissions of N2O from sheep-keeping areas can be reduced by changing sheep-keeping systems and increasing the crop production in arid zones through artificial irrigation.
- ItemMethane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed(New York, NY [u.a.] : Elsevier, 2019) Engelke, Stefanie W.; Daş, Gürbüz; Derno, Michael; Tuchscherer, Armin; Wimmers, Klaus; Rychlik, Michael; Kienberger, Hermine; Berg, Werner; Kuhla, Björn; Metges, Cornelia C.Milk fatty acids (MFA) are a proxy for the prediction of CH4 emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH4 production, (2) to predict CH4 production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH4 production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH4 prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH4 production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH4 production (L/d), the cross-validation coefficient of determination (R2 CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R2 CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R2 CV = 0.31 to 0.71) compared with data from CS diets (R2 CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R2 CV = 0.62 to 0.68) compared with L0 diets (R2 CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH4 prediction, and CH4 prediction equations based on diets containing linseed resulted in lower prediction accuracy. © 2019 American Dairy Science Association