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- ItemIn-Situ Measurement of Fresh Produce Respiration Using a Modular Sensor-Based System(Basel : MDPI, 2020) Keshri, Nandita; Truppel, Ingo; Herppich, Werner B.; Geyer, Martin; Weltzien, Cornelia; Mahajan, Pramod VIn situ, continuous and real-time monitoring of respiration (R) and respiratory quotient (RQ) are crucial for identifying the optimal conditions for the long-term storage of fresh produce. This study reports the application of a gas sensor (RMS88) and a modular respirometer for in situ real-time monitoring of gas concentrations and respiration rates of strawberries during storage in a lab-scale controlled atmosphere chamber (190 L) and of Pinova apples in a commercial storage facility (170 t). The RMS88 consisted of wireless O2 (0% to 25%) and CO2 sensors (0% to 0.5% and 0% to 5%). The modular respirometer (3.3 L for strawberries and 7.4 L for apples) consisted of a leak-proof arrangement with a water-containing base plate and a glass jar on top. Gas concentrations were continuously recorded by the RMS88 at regular intervals of 1 min for strawberries and 5 min for apples and, in real-time, transferred to a terminal program to calculate respiration rates ( RO2 and RCO2 ) and RQ. Respiration measurement was done in cycles of flushing and measurement period. A respiration measurement cycle with a measurement period of 2 h up to 3 h was shown to be useful for strawberries under air at 10 °C. The start of anaerobic respiration of strawberries due to low O2 concentration (1%) could be recorded in real-time. RO2 and RCO2 of Pinova apples were recorded every 5 min during storage and mean values of 1.6 and 2.7 mL kg−1 h−1, respectively, were obtained when controlled atmosphere (CA) conditions (2% O2, 1.3% CO2 and 2 °C) were established. The modular respirometer was found to be useful for in situ real-time monitoring of respiration rate during storage of fresh produce and offers great potential to be incorporated into RQ-based dynamic CA storage system.
- ItemCold atmospheric pressure plasma and low energy electron beam as alternative nonthermal decontamination technologies for dry food surfaces: A review(Amsterdam [u.a.] : Elsevier Science, 2018) Hertwig, Christian; Meneses, Nicolas; Mathys, AlexanderBackground: Dry food products are often highly contaminated, and dry stress-resistant microorganisms, such as certain types of Salmonella and bacterial spores, can be still viable and multiply if the product is incorporated into high moisture food products or rehydrated. Traditional technologies for the decontamination of these products have certain limitations and drawbacks, such as alterations of product quality, environmental impacts, carcinogenic potential and/or lower consumer acceptance. Cold atmospheric pressure plasma (CAPP) and low energy electron beam (LEEB) are two promising innovative technologies for microbial inactivation on dry food surfaces, which have shown potential to solve these certain limitations. Scope and approach: This review critically summarizes recent studies on the decontamination of dry food surfaces by CAPP and LEEB. Furthermore, proposed inactivation mechanisms, product-process interactions, current limitations and upscaling potential, as well as future trends and research needs for both emerging technologies, are discussed. Key findings and conclusions: CAPP and LEEB are nonthermal technologies with a high potential for the gentle decontamination of dry food surfaces. Both technologies have similarities in their inactivation mechanisms. Due to the limited penetration depth of both technologies, product-process interactions can be minimized by maintaining product quality. A first demonstrator with Technology Readiness Level (TRL) 7 for LEEB has already been introduced into the food industry for the decontamination of herbs and spices. Compared with LEEB, CAPP is at the advanced development stage with TRL 5, for which further work is essential to design systems that are scalable to industrial requirements. © 2018 The Authors
- ItemModelling the effect of feeding management on greenhouse gas and nitrogen emissions in cattle farming systems(Amsterdam [u.a.] : Elsevier Science, 2021) Ouatahar, Latifa; Bannink, André; Lanigan, Gary; Amon, BarbaraFeed management decisions are an important element of managing greenhouse gas (GHG) and nitrogen (N) emissions in livestock farming systems. This review aims to a) discuss the impact of feed management practices on emissions in beef and dairy production systems and b) assess different modelling approaches used for quantifying the impact of these abatement measures at different stages of the feed and manure management chain. Statistical and empirical models are well-suited for practical applications when evaluating mitigation strategies, such as GHG calculator tools for farmers and for inventory purposes. Process-based simulation models are more likely to provide insights into the impact of biotic and abiotic drivers on GHG and N emissions. These models are based on equations which mathematically describe processes such as fermentation, aerobic and anaerobic respiration, denitrification, etc. and require a greater number of input parameters. Ultimately, the modelling approach used will be determined by a) the activity input data available, b) the temporal and spatial resolution required and c) the suite of emissions being studied. Simulation models are likely candidates to be able to better explain variation in on-farm GHG and N emissions, and predict with a higher accuracy for a specific mitigation measure under defined farming conditions, due to the fact that they better represent the underlying mechanisms causal for emissions. Integrated farm system models often make use of rather generic values or empirical models to quantify individual emissions sources, whereas combining a whole set of process-based models (or their results) that simulates the variation in GHG and N emissions and the associated whole farm budget has not been used. The latter represents a valuable approach to delineate underlying processes and their drivers within the system and to evaluate the integral effect on GHG emissions with different mitigation options.
- ItemSoil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)(Basel : MDPI, 2020) Erler, Alexander; Riebe, Daniel; Beitz, Toralf; Löhmannsröben, Hans-Gerd; Gebbers, RobinPrecision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.
- ItemEvaluating Three-Pillar Sustainability Modelling Approaches for Dairy Cattle Production Systems(Basel : MDPI, 2021) DÃaz de Otálora, Xabier; del Prado, AgustÃn; Dragoni, Federico; Estellés, Fernando; Amon, BarbaraMilk production in Europe is facing major challenges to ensure its economic, environmental, and social sustainability. It is essential that holistic concepts are developed to ensure the future sustainability of the sector and to assist farmers and stakeholders in making knowledge-based decisions. In this study, integrated sustainability assessment by means of whole-farm modelling is presented as a valuable approach for identifying factors and mechanisms that could be used to improve the three pillars (3Ps) of sustainability in the context of an increasing awareness of economic profitability, social well-being, and environmental impacts of dairy production systems (DPS). This work aims (i) to create an evaluation framework that enables quantitative analysis of the level of integration of 3P sustainability indicators in whole-farm models and (ii) to test this method. Therefore, an evaluation framework consisting of 35 indicators distributed across the 3Ps of sustainability was used to evaluate three whole-farm models. Overall, the models integrated at least 40% of the proposed indicators. Different results were obtained for each sustainability pillar by each evaluated model. Higher scores were obtained for the environmental pillar, followed by the economic and the social pillars. In conclusion, this evaluation framework was found to be an effective tool that allows potential users to choose among whole-farm models depending on their needs. Pathways for further model development that may be used to integrate the 3P sustainability assessment of DPS in a more complete and detailed way were identified.
- ItemQuantity- and Quality-Based Farm Water Productivity in Wine Production: Case Studies in Germany(Basel : MDPI, 2017-2-1) Peth, Denise; Drastig, Katrin; Prochnow, AnnetteThe German wine sector has encountered new challenges in water management recently. To manage water resources responsibly, it is necessary to understand the relationship between the input of water and the output of wine, in terms of quantity and quality. The objectives of this study are to examine water use at the farm scale at three German wineries in Rhenish Hesse, and to develop and apply, for the first time, a quality-based indicator. Water use is analyzed in terms of wine production and wine-making over three years. After the spatial and temporal boundaries of the wineries and the water flows are defined, the farm water productivity indicator is calculated to assess water use at the winery scale. Farm water productivity is calculated using the AgroHyd Farmmodel modeling software. Average productivity on a quantity basis is 3.91 L wine per m3 of water. Productivity on a quality basis is 329.24 Oechsle per m3 of water. Water input from transpiration for wine production accounts for 99.4%-99.7% of total water input in the wineries, and, because irrigation is not used, precipitation is the sole source of transpired water. Future studies should use both quality-based and mass-based indicators of productivity. © 2017 by the authors.
- ItemDirect Measurements of the Volume Flow Rate and Emissions in a Large Naturally Ventilated Building(Basel : MDPI, 2020) Janke, David; Yi, Qianying; Thormann, Lars; Hempel, Sabrina; Amon, Barbara; Nosek, Štepán; van Overbeke, Philippe; Amon, ThomasThe direct measurement of emissions from naturally ventilated dairy barns is challenging due to their large openings and the turbulent and unsteady airflow at the inlets and outlets. The aim of this study was to quantify the impacts of the number and positions of sensors on the estimation of volume flow rate and emissions. High resolution measurements of a naturally ventilated scaled building model in an atmospheric boundary layer wind tunnel were done. Tracer gas was released inside the model and measured at the outlet area, using a fast flame ionization detector (FFID). Additionally, the normal velocity on the area was measured using laser Doppler anemometry (LDA). In total, for a matrix of 65 × 4 sensor positions, the mean normal velocities and the mean concentrations were measured and used to calculate the volume flow rate and the emissions. This dataset was used as a reference to assess the accuracy while systematically reducing the number of sensors and varying the positions of them. The results showed systematic errors in the emission estimation up to +97%, when measurements of concentration and velocity were done at one constant height. This error could be lowered under 5%, when the concentrations were measured as a vertical composite sample.
- ItemChemical insights into the base-tuned hydrothermal treatment of side stream biomasses(Cambridge : Royal Society of Chemistry, 2022) Tkachenko, Vitalii; Marzban, Nader; Vogl, Sarah; Filonenko, Svitlana; Antonietti, MarkusHerein, we analyzed the hydrothermal processes applied to four very different side stream biomasses (chestnut foliage, sugar beet pressing chips, pine bark and branches from park cleaning, bamboo cuts) and identified diverse soluble products depending on the starting pH of the reaction, covering mild to strong basic pH conditions. Despite the biological diversity of the starting products, hydrothermal disintegration of biomass results in a remarkable reduction of chemical diversity towards a controllable number of molecular products, and the well-resolved and rather simple NMR-spectra allow the assignment of the products to only a few families of compounds. It has been revealed that in comparison with the classical hydrothermal treatment, where mostly hydrochar is produced, molar excess of base shifts the hydrothermal treatment towards a humification process. A further increase of the base content causes destruction of the biomass into the more oxygenated homogeneous colloid and thus, for the first time, it can be assigned to the hydrothermal fulvication process. We discuss diverse valorization schemes depending on the biomass and conditions applied.
- ItemDetermination of Nutrients in Liquid Manures and Biogas Digestates by Portable Energy-Dispersive X-ray Fluorescence Spectrometry(Basel : MDPI AG, 2021) Horf, Michael; Gebbers, Robin; Vogel, Sebastian; Ostermann, Markus; Piepel, Max-Frederik; Olfs, Hans-WernerKnowing the exact nutrient composition of organic fertilizers is a prerequisite for their appropriate application to improve yield and to avoid environmental pollution by over-fertilization. Traditional standard chemical analysis is cost and time-consuming and thus it is unsuitable for a rapid analysis before manure application. As a possible alternative, a handheld X-ray fluorescence (XRF) spectrometer was tested to enable a fast, simultaneous, and on-site analysis of several elements. A set of 62 liquid pig and cattle manures as well as biogas digestates were collected, intensively homogenized and analysed for the macro plant nutrients phosphorus, potassium, magnesium, calcium, and sulphur as well as the micro nutrients manganese, iron, copper, and zinc using the standard lab procedure. The effect of four different sample preparation steps (original, dried, filtered, and dried filter residues) on XRF measurement accuracy was examined. Therefore, XRF results were correlated with values of the reference analysis. The best R2s for each element ranged from 0.64 to 0.92. Comparing the four preparation steps, XRF results for dried samples showed good correlations (0.64 and 0.86) for all elements. XRF measurements using dried filter residues showed also good correlations with R2s between 0.65 and 0.91 except for P, Mg, and Ca. In contrast, correlation analysis for liquid samples (original and filtered) resulted in lower R2s from 0.02 to 0.68, except for K (0.83 and 0.87, respectively). Based on these results, it can be concluded that handheld XRF is a promising measuring system for element analysis in manures and digestates.
- ItemHyperspectral Imaging Tera Hertz System for Soil Analysis : Initial Results(Basel : MDPI, 2020) Dworak, Volker; Mahns, Benjamin; Selbeck, Jörn; Gebbers, Robin; Weltzien, CorneliaAnalyzing soils using conventional methods is often time consuming and costly due to their complexity. These methods require soil sampling (e.g., by augering), pretreatment of samples (e.g., sieving, extraction), and wet chemical analysis in the laboratory. Researchers are seeking alternative sensor-based methods that can provide immediate results with little or no excavation and pretreatment of samples. Currently, visible and infrared spectroscopy, electrical resistivity, gamma ray spectroscopy, and X-ray spectroscopy have been investigated extensively for their potential utility in soil sensing. Little research has been conducted on the application of THz (Tera Hertz) spectroscopy in soil science. The Tera Hertz band covers the frequency range between 100 GHz and 10 THz of the electromagnetic spectrum. One important feature of THz radiation is its correspondence with the particle size of the fine fraction of soil minerals (clay < 2 µm to sand < 2 mm). The particle size distribution is a fundamental soil property that governs soil water and nutrient content, among other characteristics. The interaction of THz radiation with soil particles creates detectable Mie scattering, which is the elastic scattering of electromagnetic waves by particles whose diameter corresponds approximately to the wavelength of the radiation. However, single-spot Mie scattering spectra are difficult to analyze and the understanding of interaction between THz radiation and soil material requires basic research. To improve the interpretation of THz spectra, a hyperspectral imaging system was developed. The addition of the spatial dimension to THz spectra helps to detect relevant features. Additionally, multiple samples can be scanned in parallel and measured under identical conditions, and the high number of data points within an image can improve the statistical accuracy. Technical details of the newly designed hyperspectral imaging THz system working from 250 to 370 GHz are provided. Results from measurements of different soil samples and buried objects in soil demonstrated its performance. The system achieved an optical resolution of about 2 mm. The sensitivity of signal damping to the changes in particle size of 100 µm is about 10 dB. Therefore, particle size variations in the µm range should be detectable. In conclusion, automated hyperspectral imaging reduced experimental effort and time consumption, and provided reliable results because of the measurement of hundreds of sample positions in one run. At this stage, the proposed setup cannot replace the current standard laboratory methods, but the present study represents the initial step to develop a new automated method for soil analysis and imaging.