Institut für Agrartechnik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/19

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How fluid pseudoplasticity and elasticity affect propeller flows in biogas fermenters
(2024) Kolano, Markus; Ohnmacht, Benjamin; Lemmer, Andreas; Kraume, Matthias
Mixing in biogas fermenters is complex due to the non‐Newtonian rheology of biogenic substrates, which exhibit both pseudoplasticity and elasticity. It is yet unclear how these non‐Newtonian properties affect propeller flows and the mixing behavior in fermenters. Therefore, propeller flows in Newtonian as well as shear‐thinning inelastic and elastic fluids are compared numerically and validated against particle image velocity (PIV) data. Elastic normal stresses lead to an increase of pumping rates in the laminar regime and a suppression of the formation of a propeller jet in the transitional regime. Thus, flow rates are severely overestimated by the inelastic, shear‐thinning model in this regime. The results indicate that elasticity is critical for an accurate modeling of flows of biogenic substrates.
Herstellung von HMF aus Kartoffelschalen
(2025) Limbach, Nadine; Konnerth, Philipp; Kruse, Andrea
Die stoffliche Nutzung von Biomasse zur Herstellung von Plattformchemikalien gewinnt zunehmend an Bedeutung für eine nachhaltigere Chemie. Eine wichtige Verbindung in diesem Bereich ist 5-Hydroxymethylfurfural (HMF), das aus einfachen Zuckern gebildet werden kann. Ziel dieser Arbeit war es, HMF aus dem stärkehaltigen Nebenprodukt der Kartoffelschale zu synthetisieren. Dazu wurden die Einflüsse zweier Mineralsäuren – Schwefelsäure und Salpetersäure – in unterschiedlichen Konzentrationen (1 M, 1,5 M und 2 M) untersucht. Die experimentelle Arbeit bestand aus zwei aufeinanderfolgenden Schritten. Zunächst wurde die Stärke der Kartoffelschalen hydrolytisch aufgeschlossen, um eine möglichst hohe Glucoseausbeute zu erzielen. Im anschließenden Versuch wurde diese Glucose über Isomerisierungs- und Dehydratisierungsschritte zu HMF umgesetzt. Hierfür wurden die Reaktionslösungen auf verschiedene pH-Startwerte (pH 2, pH 2,5 und pH 3) eingestellt. Die Ergebnisse zeigen, dass beide Säuren die Stärkehydrolyse in ähnlicher Weise katalysieren und vergleichbare Ausbeuten an Glucose, Fructose und Zucker-Dimeren bei gleicher Verweilzeit liefern. In der nachfolgenden HMF-Synthese traten jedoch deutliche Unterschiede zwischen den Säuren auf: Schwefelsäure führte zu einer schnelleren Zuckerumwandlung und zu höheren HMF-Ausbeuten bei kürzerer Reaktionszeit. Mit sinkendem pH-Wert stiegen die HMF-Ausbeuten bei beiden Säuren an. Neben HMF entstanden weitere Neben- und Abbauprodukte wie Levulinsäure, Ameisensäure und Huminstoffe. Dabei bildete sich bei Verwendung von Schwefelsäure eine höhere Menge an Huminstoffen als bei Salpetersäure. Insgesamt zeigt sich, dass Schwefelsäure die beteiligten Reaktionen bei gleichem pH-Startwert stärker katalysiert.
Effects of pretreatment with a ball mill on methane yield of horse manure
(2023) Heller, René; Roth, Peter; Hülsemann, Benedikt; Böttinger, Stefan; Lemmer, Andreas; Oechsner, Hans
Lignocellulosic biomass is an abundant organic material, which can be utilised in biogas plants for sustainable production of biogas. Since these substrates usually have high lignin contents and consist of rather elongated particles, a special pretreatment is required for an economical and process-stable utilisation in the biogas plant. The mechanical pretreatment of horse manure was carried out with the prototype of a ball mill at different speeds. The aim of ball milling is to comminute the substrate and disintegrate the lignocellulosic bond. Mechanical pretreatment in the ball mill resulted in a significant increase in specific methane yield of more than 37% in anaerobic batch digestion (up to 243 LCH4 kgVS−1) of horse manure. The kinetics of the methane gas formation process was analysed by a modified Gompertz model fitting and showed a higher methane production potential and maximum daily methane production rate as well as a lower duration of the lag phase after pretreatment at 6 rpm. This was further confirmed by sieve analyses, which showed a significant reduction of particle size compared to the untreated variant. Thus, the use of the ball mill increases the specific methane yield and improves the fermentation of lignocellulosic substrates such as horse manure.
Risk analysis of the biogas project
(2023) Nurgaliev, Timur; Koshelev, Valery; Müller, Joachim
The dynamic model of the biogas project was created with changing parameter values over time and compared to the static model of the same project based on constant values of the same parameters. For the dynamic model, the same methods were used to evaluate the biogas project as for the static model to calculate substrate mix volumes, costs, farm production volumes, number of biogas plant equipment, driers, and other numerical characteristics of the farm. Project risks were evaluated by the sensitivity analysis and Monte Carlo simulation. The study was conducted for four scenarios regarding the substrate mix structure and the possibility of selling electricity on the market. In the scenarios, the scale of the project was determined by the size and structure of agricultural and biogas production. The results have shown that when only wastes are used as substrates, net present values (NPVs) of the project are equal to 29.45 and 56.50 M RUB in dependence on the possibility to sell electricity on the market. At the same time, when the substrate mix is diversified, the project NPVs are equal to 89.17 and 186.68 M RUB depending on the ability to sell all the produced electricity to the common power grid. The results of the sensitivity analysis defined that the values of elasticity coefficients are less than 3.14%. Results of the Monte Carlo simulation have shown a probability distribution of positive NPVs for each scenario. This study was conducted to make recommendations for business and municipalities.
Assessing the capability of YOLO- and transformer-based object detectors for real-time weed detection
(2025) Allmendinger, Alicia; Saltık, Ahmet Oğuz; Peteinatos, Gerassimos G.; Stein, Anthony; Gerhards, Roland
Impact of high-pressure processing on the bioactive compounds of milk - a comprehensive review
(2024) Siddiqui, Shahida Anusha; Khan, Sipper; Bahmid, Nur Alim; Nagdalian, Andrey Ashotovich; Jafari, Seid Mahdi; Castro-Muñoz, Roberto
High-pressure processing (HPP) is a promising alternative to thermal pasteurization. Recent studies highlighted the effectivity of HPP (400–600 MPa and exposure times of 1–5 min) in reducing pathogenic microflora for up to 5 logs. Analysis of modern scientific sources has shown that pressure affects the main components of milk including fat globules, lactose, casein micelles. The behavior of whey proteins under HPP is very important for milk and dairy products. HPP can cause significant changes in the quaternary (> 150 MPa) and tertiary (> 200 MPa) protein structures. At pressures > 400 MPa, they dissolve in the following order: αs2-casein, αs1-casein, k-casein, and β-casein. A similar trend is observed in the processing of whey proteins. HPP can affect the rate of milk fat adhering as cream with increased results at 100–250 MPa with time dependency while decreasing up to 70% at 400–600 MPa. Some studies indicated the lactose influencing casein on HP, with 10% lactose addition in case in suspension before exposing it to 400 MPa for 40 min prevents the formation of large casein micelles. Number of researches has shown that moderate pressures (up to 400 MPa) and mild heating can activate or stabilize milk enzymes. Pressures of 350–400 MPa for 100 min can boost the activity of milk enzymes by up to 140%. This comprehensive and critical review will benefit scientific researchers and industrial experts in the field of HPP treatment of milk and its effect on milk components.
AI-assisted tractor control for secondary tillage
(2025) Boysen, Jonas; Bökle, Sebastian; Stein, Anthony
Modern agricultural machinery requires skilled operators to optimally configure their complex machines, while autonomous machines without operators must already optimize their configuration themselves to achieve optimal performance. During secondary tillage multiple performance measures need to be monitored and maximized: Seedbed quality, area output and fuel consumption. The seedbed quality can be measured with the soil surface roughness coefficient which can be computed with 3D-cameras attached to the machine. For our work, such cameras are mounted in the front and back of a Claas Arion 660 tractor with an attached power harrow seeding combination. The soil-machine response model of our prior work is utilized to model the soil-machine interaction for the training of a reinforcement learning agent and the application of a decision-time planning agent to assist in controlling the working speed of the machine. The control agents are tested in real-world field trials and compared to good professional practice. The decision-time planning agent achieves comparable results to a gold-standard while reaching significantly higher performance in terms of area output (29.1%) and more efficient fuel consumption (8.4%) than a baseline while the reinforcement learning agent performed worse during the field trials. The seedbed quality and field emergence are not showing significant differences between the variants. Further analysis shows that model training and selection for the reinforcement agent could have led to performance loss and models that are performing better in simulation have been trained after the field trials. Furthermore, we analyze the models when tested under the field conditions in the field trials (out-of-distribution) that are different from the field conditions during training data collection. The out-of-distribution testing leads to a reduced performance in terms of rRMSE of the decision-time planning agent and to some extend reward of the reinforcement learning agent compared to in-distribution testing.
Assessing the capability of YOLO- and transformer-based object detectors for real-time weed detection
(2025) Allmendinger, Alicia; Saltık, Ahmet Oğuz; Peteinatos, Gerassimos G.; Stein, Anthony; Gerhards, Roland
Spot spraying represents an efficient and sustainable method for reducing herbicide use in agriculture. Reliable differentiation between crops and weeds, including species-level classification, is essential for real-time application. This study compares state-of-the-art object detection models-YOLOv8, YOLOv9, YOLOv10, and RT-DETR-using 5611 images from 16 plant species. Two datasets were created, dataset 1 with training all 16 species individually and dataset 2 with grouping weeds into monocotyledonous weeds, dicotyledonous weeds, and three chosen crops. Results indicate that all models perform similarly, but YOLOv9s and YOLOv9e, exhibit strong recall (66.58 % and 72.36 %) and mAP50 (73.52 % and 79.86 %), and mAP50-95 (43.82 % and 47.00 %) in dataset 2. RT-DETR-l, excels in precision reaching 82.44 % (dataset 1) and 81.46 % (dataset 2) making it ideal for minimizing false positives. In dataset 2, YOLOv9c attains a precision of 84.76% for dicots and 78.22% recall for Zea mays L.. Inference times highlight smaller YOLO models (YOLOv8n, YOLOv9t, and YOLOv10n) as the fastest, reaching 7.64 ms (dataset 1) on an NVIDIA GeForce RTX 4090 GPU, with CPU inference times increasing significantly. These findings emphasize the trade-off between model size, accuracy, and hardware suitability for real-time agricultural applications.
Development and evaluation of a self-adaptable planting unit for an autonomous planting process of field vegetables
(2024) Lüling, Nils; Straub, Jonas; Stana, Alexander; Brodbeck, Matthias; Reiser, David; Berner, Pirmin; Griepentrog, Hans W.
Today, the number of solutions for automated processes in agriculture is growing rapidly. This is primarily driven by the lack of available and affordable labour, pricing pressures, and regulatory requirements. Vegetable production in particular has a lot of potential for automation, as many process steps, such as planting, are performed partly manually. Fully automated systems for the planting process are characterized by their big size, which is only suitable for large farms. At the same time, these planters typically have a low level of intelligence, which is essential for a fully autonomous planting process performed by autonomous vehicles or robots. The following work therefore deals with the development and construction of a prototype for vegetable planting via a robotic platform. This prototype is designed to meet the requirements of a conventional planter and carry out the planting process automatically using a robotic platform. To ensure a robust robotic planting process, an AI-based control system has been integrated that can detect and adjust the planting quality. For this reason, the planting unit was designed to allow dynamic changes in working depth and furrow width. By dynamically controlling these planting parameters, there is potential for a more sustainable planting process with lower energy requirements. A number of evaluations have been carried out to validate the described characteristics of the prototype planting unit.
Water hyacinth conversion to biochar for soil nutrient enhancement in improving agricultural product
(2025) Kassa, Yezbie; Amare, Agmas; Nega, Tayachew; Alem, Teferi; Gedefaw, Mohammed; Chala, Bilhate; Freyer, Bernhard; Waldmann, Beatriz; Fentie, Tarekegn; Mulu, Tewodros; Adgo, Taddesse; Ayalew, Gizachew; Adugna, Marelign; Tibebe, Dessie
The conversion of water hyacinth into biochar offers a sustainable solution to mitigate its proliferation and enhances its potential as a soil amendment for agriculture. This study examined the physicochemical properties of water hyacinth biochar (WHBC) and its impact on soil fertility. Water hyacinth ( Eichhornia crassipes ) was pyrolyzed at 300 °C for 40 minute with restricted airflow (2–3 m/s), producing biochar with desirable properties and a yield of 44.6%. WHBC exhibited a pH of 8.11 ± 0.91, electrical conductivity of 18.70 ± 1.15 mS/cm, and nutrient contents including TN (0.69 ± 0.10%), TP (8.80 ± 0.01%), OC (13.95 ± 0.65%), C/N ratio (20.22 ± 0.95), S (0.34 ± 0.03%), and metallic nutrients (Ca, Mg, K). Heavy metals (Fe, Mn, Cu, Ni, Cd, Pb, Cr, Zn) were within permissible limits for biochar. Soil amended with 2500 kg/ha WHBC (BC2) produced comparable Teff crop yields (fresh mass: 1191.67 ± 428.44 g, dry mass: 700.00 ± 248.34 g, grain yield: 95.00 ± 39.69 g) to those with mineral fertilizers and mixed amendments. Fourier Transform Infrared (FTIR) and Scanning Electron Microscopy (SEM) revealed significant structural changes in WHBC, enhancing its pore structure and surface morphology. These results demonstrate the potential of WHBC as an effective soil amendment to improve agricultural sustainability and soil fertility.
Drying behavior and effect of drying temperatures on cyanide, bioactive compounds, and quality of dried cassava leaves
(2025) Chaiareekitwat, Sawittree; Nagle, Marcus; Mahayothee, Busarakorn; Khuwijitjaru, Pramote; Rungpichayapichet, Parika; Latif, Sajid; Müller, Joachim; Medana, Claudio
In this study, the drying behavior and quality of the dried leaves of cassava ( Manihot esculenta Crantz) of the ‘Rayong 5’ cultivar from Thailand were investigated. An increase in the drying temperature resulted in an increased drying rate and a reduction in drying time. The Page model provided the best fit for describing the drying characteristics of cassava leaves, with the entire drying process occurring in the falling rate period. The results showed that cyanide content was sensitive to high temperatures, with drying at 80 °C being the most effective method for toxin elimination. Prolonged drying periods lead to the degradation of vitamin C. Drying cassava leaves at 50–80 °C did not significantly affect β–carotene levels. However, lutein, chlorophyll– a , and chlorophyll– b were reduced after drying. The drying processes did not change the crude proteins content but increased the levels of histidine, alanine, and aspartic acid. In this study, high-temperature, short-time drying was identified as the optimal condition for detoxification, maintaining nutrients, and preserving the color of dried cassava leaves.
An evaluation of biogas potential of cassava, yam and plantain peel mixtures using theoretical models and Hohenheim Biogas Yield Test-Based experiments
(2025) Kusi, Joseph Yankyera; Empl, Florian; Müller, Ralf; Pelz, Stefan; Poetsch, Jens; Sailer, Gregor; Kirchhof, Rainer; Derkyi, Nana Sarfo Agyemang; Attiogbe, Francis; Zelić, Bruno
This research aimed to evaluate the comparative biogas yields of waste (peels) of selected fibrous materials from the West African region: cassava, plantain, a mixture of cassava, plantain and yam. Three models: The Boyle model, the Modified Boyle’s model, and the Buswell and Müller’s model were used to determine the theoretical maximum biomethane potentials (TMBP), while the Hohenheim Biogas Yield test (D-HBT) was used to undertake a batch test of anaerobic digestion. The samples were co-digested with digested sewage sludge (DSS) for 39 days, with an operating temperature of 37 ± 0.5 °C. The study draws comparisons between the TBMPs and the experimental results, the experimental results of the different substrates, and the experimental results and figures reported in the literature. From the experimental results, plantain peels had the highest biogas yield (468 ± 72 mL/g oTS), followed by a mixture of yam, cassava and plantain peels (362 ± 31 mL/g oTS) and cassava peels obtained the least biogas yield (218 ± 19 mL/g oTS). TMBPS of 204.04, 209.03 and 217.45 CH4 mL/g oTS were obtained for plantain peels, a mixture of yam, cassava and plantain peels and cassava peels, respectively, evaluated using Boyle’s model. For all the samples, the TMBPS (205.56, 209.03 and 218.45 CH4 mL/g oTS, respectively) obtained using the Buswell and Mueller model were slightly higher than those obtained by both the Boyle and the modified Boyle’s model (163.23, 167.22 and 174.76 CH4 mL/g oTS, respectively). While the study result is sufficient to imply that generating biogas from fibrous waste materials in its mixture form is a valuable approach, it is not sufficient to conclude that the use of these waste materials in its naturally occurring mixture form has a technical added advantage in co-digestion over their individual potential. However, future studies could explore this possibility with different fractions of the mixture with a view to optimising generation. The study finds that theoretically modelling the biogas potential of fibrous materials is a good method for biogas evaluation despite having overestimation tendencies, as this challenge could be corrected by applying factors that result in these tendencies, biodegradability indices. The data can, therefore, find use in fibrous waste treatment and waste-to-energy technologies, especially in Africa. This application will not be negatively affected by whether single water streams are used or their mixture.
Measurement of the reaction enthalpy of CO₂ in aqueous solutions with thermographic and gravimetric methods
(2024) Jung-Fittkau, Jessica; Diebold, Josef; Kruse, Andrea; Deigner, Hans-Peter; Schmidt, Magnus S.
In this work, a new concept for the approximate determination of the reaction enthalpy of the reaction between CO2 and monoethanolamine (MEA) in aqueous solution was developed. For this purpose, a CO2 gas stream was flowed into aqueous MEA solutions with different concentrations of 1 wt%, 2.5 wt% and 7.5 wt%. The weight difference ∆T, which is based on the increase in CO2 bound by the MEA over time, was documented using a thermographic camera. The mass difference ∆m, which is also based on the increase in CO2 bound by the MEA over time, was determined using a balance. By determining ∆T and ∆m, an approximate calculation of the reaction enthalpy is possible. The deviation from the values from the data known from the literature was less than 5% in all experiments.
Use of real-time load profile measurement to optimize photovoltaicsystems dimensioning in shea butter production
(2024) Bonzi, Joévin Wiomou; Nounagnon, Bignon Stephanie; Romuli, Sebastian; Soro, Yrébégnan Moussa; Müller, Joachim
Productive use of renewable energy, particularly solar power, is essential for sustainable energy provision, especially in resource-constrained regions like sub-Saharan Africa. Accurate data on energy consumption patterns is crucial for properly sizing photovoltaic systems. However, conventional sizing methods, particularly for commercial and industrial needs often overestimate requirements, leading to economically onerous systems. Intuitive methods rely on simplified computations based on worstcase scenarios, such as lowest monthly average irradiation and daily load demand. They fail to consider solar irradiation fluctuations. Numerical methods, involve simulations at regular intervals. However, their practical application relies on interviews or electrical bills, which lacks accuracy in evaluating dynamic electrical consumption. This study tackles this challenge by developing a remote measurement system to monitor power consumption in a shea butter production facility (SOTOKACC, Toussiana, Burkina Faso). Shea, a popular product in the cosmetic, pharmaceutic, and food industries globally, originates solely from sub-Saharan Africa, where it sustains livelihoods for over 16 million rural women. While traditional methods still dominate shea butter production, initiatives aimed at adopting mechanical presses for extraction are on the rise. The system developed comprises two Arduino devices: a weather station and a power sensor. The weather station, powered by solar energy, recorded solar irradiation, ambient temperature and relative humidity. The power sensor, equipped with current clamp and voltage sensors, monitors various electrical parameters across three phases. The data were transmitted to an online platform via a Wi-Fi network. Over a two-month period, constant measurements were conducted to delineate the facility’s load profile. Sizing was performed using the HOMER Pro software to determine the characteristics of the most cost-effective photovoltaic system for the facility. A comparison was made between the conventional sizing procedure based on monthly electrical consumption and that based on remote measurements. Results indicate that load profile evaluation yields more cost-effective solutions with reduced storage requirements compared to traditional methods. This research highlights the potential of affordable measurement tools in developing sustainable energy solutions for small and medium-sized enterprises (SMEs).
DIY insect flushing bar 2.0
design and implementation in the InsectMow project
(2025) Frank, Jonas
Quick guide to building the insect flushing bar from the InsectMow project. Second, updated and extended version
DIY Insektenscheuche 2.0
Konzept und Umsetzung im Projekt InsectMow
(2025) Frank, Jonas
Kurzanleitung zum Bau der Insektenscheuche aus dem Projekt InsectMow. Zweite, aktualisierte und ergänzte Version
Technical evaluation of a solar-biomass flatbed dryer for maize cobs drying in Rwanda
(2023) Ntwali, Janvier; Romuli, Sebastian; Bonzi, Joévin Wiomou; Müller, Joachim
The persistent problem of postharvest losses in the maize value chain poses an arduous challenge for smallholder farmers in Rwanda, ultimately reducing their market bargaining power. As a consequence, there is an exacerbated disparity in revenues that makes farmers, predominantly female farmers, more vulnerable. The existing drying facilities are based on ambient air drying with a long drying time and the alternative mechanical dryers use mostly fossil fuels which is not a sustainable solution. A solar-biomass hybrid flatbed dryer for maize cobs drying was designed and constructed in the high-altitude volcanic zone of Rwanda. The objective was to provide farmers with an affordable and sustainable drying system with a high drying rate compared to the existing method. In this study, we present the results of the technical evaluation of the dryer to rate its capacity to dry maize cobs to the recommended moisture content. Energy balance was assessed by temperature sensors, airflow distribution was measured with a vane anemometer and the solar radiation from weather station were compared to the solar system data recorded through a datalogging charge controller. Maize was dried in three batches and the moisture content was measure with oven method. Results showed a uniform distribution of airflow on the dryer perforated flow. The burner consumed on average 6 kg of empty cobs per hour and the burner efficiency was 59.4 %. The solar system provided a maximum daily yield of 2.6 kWh, and the battery was able to maintain the system during days of low solar energy availability. Maize cobs were dried from an average moisture content of 23.0 % to 13.7 % in an average period of 90.6 hours. This drying time was significantly lower compared to the already existing system which uses more than 6 weeks. The results prove that the solar-Biomass hybrid flatbed dryer was appropriate for drying maize cobs to the recommended moisture content and thus reduce the risk of postharvest losses in maize value chain in Rwanda. The dryer might be further improved by combining the burner with a solar heating system to further reduce the biomass mass consumption.
Classifying early-stage soybean fungal diseases on hyperspectral images using convolutional neural networks
(2025) Hsiao, Chieh Fu; Feyrer, Georg; Stein, Anthony
Using convolutional neural networks (CNNs) to detect plant diseases has proven to reach high accuracy in the classification of infected and non-infected plant images. However, most of the existing researches are based on RGB images due to the availability and the comparably low cost of image collection. The limited spectral information restricts the detectability of plant diseases, especially in the early stage where often symptoms of pathogen infection have not yet become visible. To this end, in this study, hyperspectral imaging (HSI) data are combined with deep learning models to test the classification ability of two soybean fungal diseases: Asian soybean rust (Phakopsora pachyhizi) and soybean stem rust (Sclerotinia scleroriorum). Different CNNs employing 2D, 3D convolution, and hybrid approaches are compared. The influences of the depth of the convolutional layer and the regularization techniques are also discussed. Besides, image augmentation methods are investigated to overcome the problem of data scarcity. The results indicate the 6-convolutional-layer depth hybrid model to have the best capacity in classifying Asian soybean rust in the early-mid to mid-late stage when there are over 2 % visible symptoms but a limited detectability in the early stages when there are below 2 % visible symptoms on leaves. On the other hand, the optimized CNN model shows a limited capability to detect both diseases when there are no visible symptoms observable. Overall, this study suggests a hybrid 2D-3D convolutional model with augmentation and regularization methods has a high potential in the early detection of fungal diseases. This research is expected to contribute to a new cropping system that vastly reduces the chemical-synthesis plant protection products, where a continuous pathogen disease monitoring plays a key to manage the crop stands.
Effects of harvest date and ensiling additives on the optimized ensiling of Silphium perfoliatum to prevent faulty fermentation
(2024) Baumgart, Marian; Hülsemann, Benedikt; Sailer, Gregor; Oechsner, Hans; Müller, Joachim; Hu, Wei; Zhou, Zhiguo; Zhao, Wenqing
Silphium perfoliatum , an energy crop with a high fiber content but low concentrations of fermentable carbohydrates, presents challenges for complete fermentation in biogas production. To overcome this, a bioeconomic approach proposes the use of the fibers for paper and board production, which requires high-quality silage with minimal butyric acid, which affects the marketability of the fibers. This study aims to optimize the silaging process of Silphium perfoliatum by investigating the effects of harvest date, bacterial cultures and additives on fermentation results. Laboratory experiments were conducted to evaluate the effect of three harvest dates on fermentation acid composition, with a focus on increasing lactic acid production to inhibit butyric acid formation. Results indicate that an early harvest date (early September) is critical for achieving stable fermentation and minimizing ensiling losses. The addition of sugar-rich additives, such as syrup, was found to be essential, especially for later harvest dates. Despite these interventions, a late harvest (early November) consistently resulted in suboptimal fermentation. The results suggest that optimizing harvest timing and incorporating appropriate additives are key strategies for producing high quality silage and ensuring the suitability of Silphium perfoliatum fibers for industrial applications.
Technical evaluation of a modular dryer for medicinal and aromatic plants in practical German conditions
(2025) Ntwali, Janvier; Barati, Ziba; Bonzi, Joévin Wiomou; Esper, Albert; Müller, Joachim
A modular batch dryer with partial recirculation of outlet air to save thermal energy was developed for small-scale medicinal plants producers in Germany. Different operational modes were tested for energy consumption and the quality of the dried product using lemon balm leaves. Fresh air mode, partial recirculation-controlled flap mode and full recirculation-controlled flap mode alternated depending on the progress of drying and the set relative humidity at the inlet. Experiments consisted of comparing two modes of controlled flap modes with relative humidity varying from 80 to 30 % for one mode and fixed at 40 % for the other mode. A total mass of 500 kg of lemon balm leaves were dried in an average of 23 hours to reduce moisture content from 72 % to 7 %. The throughput ranged from 19.7 to 23.7 kg∙h-1 for lemon balm drying. Air recirculation significantly reduced the thermal energy consumption where a specific thermal energy consumption of 3540 kJ·kg-1 H₂O was achieved by controlling the inlet air humidity to 40 % when drying lemon balm compared to the 4075 kJ·kg-1 H₂O achieved under the 80-30 % mode. No significant difference in essential oils content was observed between the two humidity control modes. This research confirmed the energy-efficient attributes of the dryer and recommends the implementation of air recirculation as one of the methods to reduce energy consumption in medicinal plants drying.

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