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- 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.
- 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
- ItemCharacteristics of methicillin-resistant Staphylococcus aureus from broiler farms in Germany are rather lineage- than source-specific(Oxford ; Cary, NC : Oxford University Press, 2019) Kittler, Sophie; Seinige, Diana; Meemken, Diana; Müller, Anja; Wendlandt, Sarah; Ehricht, Ralf; Monecke, Stefan; Kehrenberg, CorinnaMethicillin-resistant Staphylococcus aureus (MRSA) are a major concern for public health, and broiler farms are a potential source of MRSA isolates. In this study, a total of 56 MRSA isolates from 15 broiler farms from 4 different counties in Germany were characterised phenotypically and genotypically. Spa types, dru types, SCCmec types, and virulence genes as well as resistance genes were determined by using a DNA microarray or specific PCR assays. In addition, PFGE profiles of isolates were used for analysis of their epidemiological relatedness. While half of the isolates belonged to spa type t011, the other half was of spa types t1430 and t034. On 3 farms, more than 1 spa type was found. The most common dru type was dt10a (n = 19), followed by dt11a (n = 17). Susceptibility testing of all isolates by broth microdilution revealed 21 different resistance phenotypes and a wide range of resistance genes was present among the isolates. Up to 10 different resistance phenotypes were found on individual farms. Resistance to tetracyclines (n = 53), MLSB antibiotics (n = 49), trimethoprim (n = 38), and elevated MICs of tiamulin (n = 29) were most commonly observed. Microarray analysis detected genes for leucocidin (lukF/S), haemolysin gamma (hlgA), and other haemolysines in all isolates. In all t1430 isolates, the egc cluster comprising of genes encoding enterotoxin G, I, M, N, O, U, and/or Y was found. The splitstree analysis based on microarray and PCR gene profiles revealed that all CC9/SCCmec IV/t1430/dt10a isolates clustered apart from the other isolates. These findings confirm that genotypic patterns were specific for clonal lineages rather than for the origin of isolates from individual farms.
- ItemRapid determination of lime requirement by mid-infrared spectroscopy: A promising approach for precision agriculture(Weinheim : Wiley-VCH, 2019) Leenen, Matthias; Welp, Gerhard; Gebbers, Robin; Pätzold, StefanMid-infrared spectroscopy (MIRS) has proven to be a cost-effective, high throughput measurement technique for soil analysis. After multivariate calibration mid-infrared spectra can be used to predict various soil properties, some of which are related to lime requirement (LR). The objective of this study was to test the performance of MIRS for recommending variable rate liming on typical Central European soils in view of precision agriculture applications. In Germany, LR of arable topsoils is commonly derived from the parameters organic matter content (SOM), clay content, and soil pH (CaCl2) as recommended by the Association of German Agricultural Analytical and Research Institutes (VDLUFA). We analysed a total of 458 samples from six locations across Germany, which all revealed large within-field soil heterogeneity. Calcareous topsoils were observed at some positions of three locations (79 samples). To exclude such samples from LR determination, peak height at 2513 cm−1 of the MIR spectrum was used for identification. Spectra-based identification was accurate for carbonate contents > 0.5%. Subsequent LR derivation (LRSPP) from MIRS-PLSR predictions of SOM, clay, and pH (CaCl2) for non-calcareous soil samples using the VDLUFA look-up tables was successful for all locations (R2 = 0.54–0.82; RMSE = 857–1414 kg CaO ha−1). Alternatively, we tested direct LR prediction (LRDP) by MIRS-PLSR and also achieved satisfactory performance (R2 = 0.52–0.77; RMSE = 811–1420 kg CaO ha−1; RPD = 1.44–2.08). Further improvement was achieved by refining the VDLUFA tables towards a stepless algorithm. It can be concluded that MIRS provides a promising approach for precise LR estimation on heterogeneous arable fields. Large sample numbers can be processed with low effort which is an essential prerequisite for variable rate liming in precision agriculture. © 2019 The Authors. Journal of Plant Nutrition and Soil Science published by WILEY-VCH Verlag GmbH & Co. KGaA
- ItemAerial river management by smart cross-border reforestation(Amsterdam [u.a.] : Elsevier Science, 2019) Weng, Wei; Costa, Luís; Lüdeke, Matthias K.B.; Zemp, Delphine C.In the face of increasing socio-economic and climatic pressures in growing cities, it is rational for managers to consider multiple approaches for securing water availability. One often disregarded option is the promotion of reforestation in source regions supplying important quantities of atmospheric moisture transported over long distances through aerial rivers, affecting water resources of a city via precipitation and runoff (‘smart reforestation’). Here we present a case demonstrating smart reforestation's potential as a water management option. Using numerical moisture back-tracking models, we identify important upwind regions contributing to the aerial river of Santa Cruz de la Sierra (Bolivia). Simulating the effect of reforestation in the identified regions, annual precipitation and runoff reception in the city was found to increase by 1.25% and 2.30% respectively, while runoff gain during the dry season reached 26.93%. Given the city's population growth scenarios, the increase of the renewable water resource by smart reforestation could cover 22–59% of the additional demand by 2030. Building on the findings, we argue for a more systematic consideration of aerial river connections between regions in reforestation and land planning for future challenges. © 2019 The Authors
- ItemEffects of Pre-Processing Short-Term Hot-Water Treatments on Quality and Shelf Life of Fresh-Cut Apple Slices(Basel : MDPI AG, 2019) Rux, Guido; Efe, Efecan; Ulrichs, Christian; Huyskens-Keil, Susanne; Hassenberg, Karin; Herppich, Werner B.Processing, especially cutting, reduces the shelf life of fruits. In practice, fresh-cut fruit salads are, therefore, often sold immersed in sugar syrups to increase shelf life. Pre-processing short-term hot-water treatments (sHWT) may further extend the shelf life of fresh-cuts by effectively reducing microbial contaminations before cutting. In this study, fresh-cut ‘Braeburn’ apples, a major component of fruit salads, were short-term (30 s) hot water-treated (55 °C or 65 °C), partially treated with a commercial anti-browning solution (ascorbic/citric acid) after cutting and, thereafter, stored immersed in sugar syrup. To, for the first time, comprehensively and comparatively evaluate the currently unexplored positive or negative effects of these treatments on fruit quality and shelf life, relevant parameters were analyzed at defined intervals during storage at 4 °C for up to 13 days. Compared to acid pre-treated controls, sHWT significantly reduced the microbial loads of apple slices but did not affect their quality during the 5 day-standard shelf life period of fresh-cuts. Yeasts were most critical for shelf life of fresh-cut apples immersed in sugar syrup. The combination of sHWT and post-processing acid treatment did not further improve quality or extend shelf life. Although sHWT could not extend potential maximum shelf life beyond 10 d, results highlighted the potentials of this technique to replace pre-processing chemical treatments and, thus, to save valuable resources.
- ItemForest carbon allocation modelling under climate change(Victoria, BC : Heron, 2019) Merganičová, Katarína; Merganič, Ján; Lehtonen, Aleksi; Vacchiano, Giorgio; Ostrogović Sever, Maša Zorana; Augustynczik, Andrey L. D.; Grote, Rüdiger; Kyselová, Ina; Mäkelä, Annikki; Yousefpour, Rasoul; Krejza, Jan; Collalti, Alessio; Reyer, Christopher P. O.Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions. © The Author(s) 2019. Published by Oxford University Press.
- ItemRecent advances in d-lactic acid production from renewable resources: Case studies on agro-industrial waste streams(Zagreb : Faculty of Food Technology and Biotechnology, University of Zagreb, 2019) Alexandri, Maria; Schneider, Roland; Mehlmann, Kerstin; Venus, JoachimThe production of biodegradable polymers as alternatives to petroleum-based plastics has gained significant attention in the past years. To this end, polylactic acid (PLA) constitutes a promising alternative, finding various applications from food packaging to pharmaceuticals. Recent studies have shown that d-lactic acid plays a vital role in the production of heat-resistant PLA. At the same time, the utilization of renewable resources is imperative in order to decrease the production cost. This review aims to provide a synopsis of the current state of the art regarding d-lactic acid production via fermentation, focusing on the exploitation of waste and byproduct streams. An overview of potential downstream separation schemes is also given. Additionally, three case studies are presented and discussed, reporting the obtained results utilizing acid whey, coffee mucilage and hydrolysate from rice husks as alternative feedstocks for d-lactic acid production. © 2019, University of Zagreb.
- ItemValidation study for measuring absorption and reduced scattering coefficients by means of laser-induced backscattering imaging(Amsterdam [u.a.] : Elsevier Science, 2019) Zude-Sasse, Manuela; Hashim, Norhashila; Hass, Roland; Polley, Nabarun; Regen, ChristianDecoupling of optical properties appears challenging, but vital to get better insight of the relationship between light and fruit attributes. In this study, nine solid phantoms capturing the ranges of absorption (μa) and reduced scattering (μs’) coefficients in fruit were analysed non-destructively using laser-induced backscattering imaging (LLBI) at 1060 nm. Data analysis of LLBI was carried out on the diffuse reflectance, attenuation profile obtained by means of Farrell's diffusion theory either calculating μa [cm−1] and μs’ [cm−1] in one fitting step or fitting only one optical variable and providing the other one from a destructive analysis. The nondestructive approach was approved when calculating one unknown coefficient non-destructively, while no ability of the method was found to analysis both, μa and μs’, non-destructively. Setting μs’ according to destructive photon density wave (PDW) spectroscopy and fitting μa resulted in root mean square error (rmse) of 18.7% in comparison to fitting μs’ resulting in rmse of 2.6%, pointing to decreased measuring uncertainty, when the highly variable μa was known. The approach was tested on European pear, utilizing destructive PDW spectroscopy for setting one variable, while LLBI was applied for calculating the remaining coefficient. Results indicated that the optical properties of pear obtained from PDW spectroscopy as well as LLBI changed concurrently in correspondence to water content mainly. A destructive batch-wise analysis of μs’ and online analysis of μa may be considered in future developments for improved fruit sorting results, when considering fruit with high variability of μs’. © 2019 The Authors
- ItemExtraction of phenolic compounds from palm oil processing residues and their application as antioxidants(Zagreb : Faculty of Food Technology and Biotechnology, University of Zagreb, 2019) Tsouko, Erminda; Alexandri, Maria; Fernandes, Keysson Vieira; Freire, Denise Maria Guimarães; Mallouchos, Athanasios; Koutinas, Apostolis A.The side streams derived from the palm oil production process, namely palm kernel cake, palm pressed fibre, palm kernel shells and empty fruit bunches, were evaluated as sources of phenolic compounds. Among these streams, kernel cake had the highest total phenolic content (in mg of gallic acid equivalents (GAE) per g of dry sample) with a value of 5.19, whereas the empty fruit bunches had the lowest value (1.79). The extraction time and liquid-to-solid ratio were investigated to optimize the phenolic extraction. Kernel cake exhibited the highest total phenolic content (5.35 mg/g) with a liquid-to-solid ratio of 40:1 during 20 min of extraction. The main phenolic compounds of the extracts deriving from all byproduct streams were also identified and quantified with HPLC-DAD. Pyrogallol, 4-hydroxybenzoic acid, gallic acid and ferulic acid were the main compounds found in kernel cake extracts. Empty fruit bunch and pressed fibre extracts were also rich in 4-hydroxybenzoic acid, while pyrogallol was the predominant compound in kernel shell extracts. All extracts showed antioxidant activity as it was indicated from the results of DPPH analysis and subsequently tested in sunflower oil aiming to prolong its shelf life. The addition of 0.8 % kernel cake extract increased the induction time of sunflower oil more than 50 %. According to the results obtained in this study, kernel cake extracts could be considered as a value-added co-product with a potential application as antioxidants in the food industry. © 2018 University of Zagreb.