Institut für Agrartechnik

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

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Predicting herbage biomass on small‐scale farms by combining sward height with different aggregations of weather data
(2024) Scheurer, Luca; Leukel, Joerg; Zimpel, Tobias; Werner, Jessica; Perdana‐Decker, Sari; Dickhoefer, Uta
Accurate predictions of herbage biomass are important for efficient grazing management. Small‐scale farms face challenges using remote sensing technologies due to insufficient resources. This limitation hinders their ability to develop machine learning‐based prediction models. An alternative is to adopt less expensive measurement methods and readily available data such as weather data. This study aimed to examine how different temporal aggregations of weather data combined with compressed sward height (CSH) affect the prediction performance. We considered weather features based on different numbers of weather variables, statistical functions, weather events, and periods. Between 2019 and 2021, data were collected from 11 organic dairy farms in Germany. Herbage biomass exhibited high variability (coefficient of variation [CV] = 0.65). Weather data were obtained from on‐farm and nearby public stations. Prediction models were learned on a training set ( n = 291) and evaluated on a test set ( n = 125). Random forest models performed better than models based on artificial neural networks and support vector regression. Representing weather data by a single feature for leaf wetness reduced the root mean square error (RMSE) by 12.1% (from 536 to 471 kg DM ha −1 , where DM is dry matter) and increased the R 2 by 0.109 (from 0.518 to 0.627). Adding features based on multiple variables, functions, events, and periods resulted in a further reduction in RMSE by 15.9% ( R 2 = 0.737). Overall, different aggregations of weather data enhanced the accuracy of CSH‐based models. These aggregations do not cause additional effort for data collection and, therefore, should be integrated into CSH‐based models for small‐scale farms.
Evaluation of energetic potential of slaughterhouse waste and its press water obtained by pressure-induced separation via anaerobic digestion
(2024) Yankyera Kusi, Joseph; Empl, Florian; Müller, Ralf; Pelz, Stefan; Poetsch, Jens; Sailer, Gregor; Kirchhof, Rainer; Agyemang Derkyi, Nana Sarfo; Attiogbe, Francis; Siabi, Sarah Elikplim; Jeon, Byong-Hun
Anaerobic digestion has the potential to convert organic waste materials into valuable energy. At the same time, using press water from biomass materials for energy generation while taking advantage of the resulting cake for other purposes is an emerging approach. Therefore, this study aimed to investigate the residual potential expected from a typical biogas feedstock after it has been mechanically separated into liquid and solid phases. Hence, in this study, the rumen contents of ruminants (cow, goat, and sheep) and their proportionate ratios were obtained from an abattoir in Ghana. Resource characterization of the waste samples was carried out in the central laboratory of the HFR, Germany. Anaerobic batch tests for biogas (biomethane) yield determination were set up using the Hohenheim Biogas Yield Test (HBT). The inoculum used was obtained from an inoculum production unit at the Hohenheim University biogas laboratory. The trial involved two different forms of the sample: mixture of rumen contents, press water, and inoculum, each in four (4) replicates. The trial was carried out at a mesophilic temperature of 37 °C. Results obtained over a seventy (70) day period were transformed into biogas yields. Overall, the results show that the current contents are suitable for biogas generation as an option as opposed to the current form of disposal at a refuse dump. However, using these mixtures in their original forms is more technically viable than using press water without further treatment.
From coffee waste to wastewater treatment: optimization of hydrothermal carbonization and H₃PO₄ activation for Cr(VI) adsorption
(2026) Piccoli Miranda de Freitas, Caroline; De Freitas Batista, Gabriel; Dalmolin da Silva, Mariele; Checa Gomez, Manuel; Arauzo, Pablo J.; França da Cunha, Fernando; Kruse, Andrea
Spent coffee grounds (SCG) are an abundant agro-industrial waste, and their valorization as activated carbon (AC) offers a sustainable approach for wastewater treatment and heavy-metal remediation. However, the high energy demand of SCG activation limits large-scale application. Hydrothermal carbonization (HTC) reduces energy consumption and enhances material properties. This study evaluated the performance of activated carbon (AC) derived from SCG via HTC, followed by H₃PO₄ activation for Cr(VI) removal, and compared it with non-activated carbon obtained by HTC and pyrolysis. The results highlight the effect of chemical activation on enhancing surface area, porosity, and adsorption efficiency. The predicted optimal IN was 1624.7 mg·g⁻¹, closely matching the experimental value of 1640.1 ± 15.5 mg·g⁻¹, achieved at 426 °C, 92 min, and a hydrochar-to-H₃PO₄ ratio of 1:1.6. The optimized AC exhibited a maximum adsorption capacity (Qₑ) of 33 ± 1.1 mg·g⁻¹ and 99.4 ± 0.1 % Cr(VI) removal under pH 2, 25 mg·L⁻¹ initial concentration, and 2 g·L⁻¹ adsorbent dose. In contrast, the non-activated carbon presented a lower iodine number (1411 ± 70 mg·g⁻¹) and inferior adsorption performance, confirming the key role of H₃PO₄ activation in improving surface reactivity and adsorption sites. Chemical activation proved essential for improving Cr(VI) adsorption, with the H₃PO₄-AC exhibiting the highest capacity. These results demonstrate the potential of SCG-derived AC as a low-cost adsorbent for heavy-metal-rich industrial effluents, supporting circular economy strategies.
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.

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