Institut für Agrartechnik

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

Browse

Now showing 1 - 20 of 153

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; Baumgart, Marian; State Institute of Agricultural Engineering and Bioenergy, University of Hohenheim, Garbenstraße 9, 70599 Stuttgart, Germany; (B.H.); (G.S.); (H.O.); Hülsemann, Benedikt; State Institute of Agricultural Engineering and Bioenergy, University of Hohenheim, Garbenstraße 9, 70599 Stuttgart, Germany; (B.H.); (G.S.); (H.O.); Sailer, Gregor; State Institute of Agricultural Engineering and Bioenergy, University of Hohenheim, Garbenstraße 9, 70599 Stuttgart, Germany; (B.H.); (G.S.); (H.O.); Oechsner, Hans; State Institute of Agricultural Engineering and Bioenergy, University of Hohenheim, Garbenstraße 9, 70599 Stuttgart, Germany; (B.H.); (G.S.); (H.O.); Müller, Joachim; Institute of Agricultural Engineering, Tropics and Subtropics Group, University of Hohenheim, Garbenstraße 9, 70599 Stuttgart, Germany;; 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, Wiomou Joévin; 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.
Computational sizing of solar powered peanut oil extraction in Senegal using a synthetic load profile
(2024) Bonzi, Wiomou Joévin; Romuli, Sebastian; Diouf, Djicknoum; Piriou, Bruno; Meissner, Klaus; Müller, Joachim
This paper presents an approach for sizing a hybrid photovoltaic system for a small-scale peanut oil processing company (Yaye Aissatou, Passy) in rural Senegal using a synthetic load profile. In this study, a predictive model of the electrical load of a service-based plant oil processing company was developed through a diagnosis, to evaluate the extraction process. The mass and energy balance were measured, and the process was implemented into MATLAB Simulink. The simulated load profile was implemented in HOMER Pro and the characteristics of the most profitable hybrid systems were identified. The results showed that the lowest net present cost over 25 years was found with a PV/battery/grid-system with 18.6 kWp solar panels, 16 kWh of storage, and an initial investment of 20,019 €. Compared to a grid-only scenario, this solution reduces the net present cost from an initial 72,163 € to 31,603 €, the operating cost from 3675 € per year to 590 € per year, and the cost of energy from 0.29 to 0.13 €/kWh. The renewable fraction of the proposed system is 90.0 % while the expected payback period is 6.2 years. The study demonstrates the economic feasibility of using solar energy for plant oil processing.
Disc mower versus bar mower: Evaluation of the direct effects of two common mowing techniques on the grassland arthropod fauna
(2025) von Berg, Lea; Frank, Jonas; Betz, Oliver; Steidle, Johannes L. M.; Böttinger, Stefan; Sann, Manuela; von Berg, Lea; Evolutionary Biology of Invertebrates, Institute for Evolution and Ecology, University of Tübingen, Tübingen, Germany; Frank, Jonas; Fundamentals of Agricultural Engineering, Institute for Agricultural Engineering, University of Hohenheim, Stuttgart, Germany; Betz, Oliver; Evolutionary Biology of Invertebrates, Institute for Evolution and Ecology, University of Tübingen, Tübingen, Germany; Steidle, Johannes L. M.; Chemical Ecology, Institute for Biology, University of Hohenheim, Stuttgart, Germany; Böttinger, Stefan; Fundamentals of Agricultural Engineering, Institute for Agricultural Engineering, University of Hohenheim, Stuttgart, Germany; Sann, Manuela; Chemical Ecology, Institute for Biology, University of Hohenheim, Stuttgart, Germany
1. In Central Europe, species‐rich grasslands are threatened by intensive agriculture with frequent mowing, contributing to the reduction of arthropods such as insects and spiders. However, comprehensive and standardised studies on the direct effects of the two most agriculturally relevant mowing techniques, e.g., double‐blade bar mower versus disc mower, are lacking. 2. In a 2‐year experiment, we have investigated the direct effect of mowing on eight abundant arthropod groups in grassland, covering two seasonal mowing events in both years, using a randomised block design. We compared (a) an unmown control, (b) a double‐blade bar mower and (c) a disc mower. 3. For most of the taxonomic groups studied, a significantly lower number of individuals was found in the experimental plots immediately after mowing, regardless of the mowing technique, compared to an unmown control. This was not the case for Orthoptera and Coleoptera, which did not show a significant reduction in the number of individuals for both mowing techniques (Orthoptera) or only for the double‐blade bar mower (Coleoptera). 4. Between both mowing techniques, no significant differences were found for all taxonomic groups investigated. 5. Synthesis and applications: Our findings suggest that mowing in general has a negative impact on abundant arthropod groups in grassland, regardless of the method used. Tractor‐driven double‐blade bar mowers do not seem to be a truly insect‐friendly alternative to a conventional disc mower. Other factors such as cutting height and mowing regimes should be seriously considered to protect spiders and insects from the negative effects of mowing. In addition, we strongly recommend the maintenance of unmown refugia. Insects and spiders that are spared by mowing can take refuge in these unmown areas to avoid subsequent harvesting and thermally unfavourable conditions that arise on mown areas. Further, unmown refugia are basic habitat structures for a subsequent recolonisation of mown areas once the flora has recovered.
A concept of a decentral server infrastructure to connect farms, secure data, and increase the resilience of digital farming
(2025) Bökle, Sebastian; Gscheidle, Michael; Weis, Martin; Paraforos, Dimitrios S.; Griepentrog, Hans W.
With the intensified use and integration of digital technologies in agriculture, dependencies and constraints occurred which weakened the adoption and reduced effectiveness of innovative technology due to lacking interoperability and resilience. As awareness of these problems increased concepts have been developed to meet this issue with decentralized IT- infrastructures. With the proposed concept the authors aim to refine these existing infrastructures with concrete suggestions for server infrastructures. Off-the-shelf hardware and open-source software, enable cheap access to digital technologies yet provide sufficient support by choosing open-source tools with big or active communities. With the involvement of the machinery rings the economic advantages scale up because of the interfarm use of expensive technology. The farmservers on the farmside are the edge nodes of a regional network. The local machinery ring is the next node which is supposed to offer remote services for the farmers, who have a trustful partner in the machinery rings. The concept orients on revised requirements enriched by the results of a survey, conducted by the authors, adding the focus on interfarm cooperations. The concept meets the main constraints farmers face in digitalization: Data sovereignty, resilience, interoperability, high costs, and trust.
Fed-batch bioreactor cultivation of Bacillus subtilis using vegetable juice as an alternative carbon source for lipopeptides production: a shift towards a circular bioeconomy
(2024) Gugel, Irene; Vahidinasab, Maliheh; Benatto Perino, Elvio Henrique; Hiller, Eric; Marchetti, Filippo; Costa, Stefania; Pfannstiel, Jens; Konnerth, Philipp; Vertuani, Silvia; Manfredini, Stefano; Hausmann, Rudolf; Gugel, Irene; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Vahidinasab, Maliheh; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Benatto Perino, Elvio Henrique; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Hiller, Eric; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Marchetti, Filippo; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Costa, Stefania; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Pfannstiel, Jens; Core Facility Hohenheim, Mass Spectrometry Unit, University of Hohenheim, Ottlie-Zeller-Weg 2, 70599 Stuttgart, Germany; Konnerth, Philipp; Department of Conversion Technology of Biobased Resources, University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany;; Vertuani, Silvia; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Manfredini, Stefano; Department of Life Sciences and Biotechnology, University of Ferrara, 44121 Ferrara, Italy, (S.V.);; Hausmann, Rudolf; Department of Bioprocess Engineering (150k), Institute of Food Science and Biotechnology, University of Hohenheim, Fruwirthstrasse 12, 70599 Stuttgart, Germany; (E.H.B.P.);; Gudiña, Eduardo
In a scenario of increasing alarm about food waste due to rapid urbanization, population growth and lifestyle changes, this study aims to explore the valorization of waste from the retail sector as potential substrates for the biotechnological production of biosurfactants. With a perspective of increasingly contributing to the realization of the circular bioeconomy, a vegetable juice, derived from unsold fruits and vegetables, as a carbon source was used to produce lipopeptides such as surfactin and fengycin. The results from the shake flask cultivations revealed that different concentrations of vegetable juice could effectively serve as carbon sources and that the fed-batch bioreactor cultivation strategy allowed the yields of lipopeptides to be significantly increased. In particular, the product/substrate yield of 0.09 g/g for surfactin and 0.85 mg/g for fengycin was obtained with maximum concentrations of 2.77 g/L and 27.53 mg/L after 16 h, respectively. To conclude, this study provides the successful fed-batch cultivation of B. subtilis using waste product as the carbon source to produce secondary metabolites. Therefore, the consumption of agricultural product wastes might be a promising source for producing valuable metabolites which have promising application potential to be used in several fields of biological controls of fungal diseases.
AI-based planting and monitoring of cabbage with a robotic platform
(2024) Lüling, Nils; Griepentrog, Hans W.
Labour shortages, price pressure and changes in legislation are just a few of the drivers of automation and digitalization in field vegetable cultivation. Due to its high-value crops and its high demands on crop maintenance, field vegetable cultivation is the ideal working area for agricultural robotics. However, the versatile and rapid establishment of agricultural robotics systems has so far failed due to the limited adaptivity to the complex working environment under outdoor conditions, the process chain and the applications that an agricultural robot has to carry out in a field. Only through the developing possibilities of using cameras and artificial intelligence can complex automated applications be implemented. The overall aim of this cumulative dissertation was the development and analysis of systems for AI-based crop establishment and crop maintenance of white cabbage with a robotic platform. Three aspects were analysed: (1) Design, prototyping and evaluation of a planting unit for an autonomous planting process of cabbage with a robotic platform. By using AI-based image classification, a camera at the end of the planting unit was used to evaluate the planting quality and dynamically adjust individual planting parameters. (2) Development of a camera-based vegetation monitoring system for determining the fruit volume and leaf area of white cabbage across several growth stages. (3) Analysis of a method for unsupervised image translation for automated exposure adjustment. By reducing the exposure variation, a lower implementation effort and a higher robustness of the detection and segmentation of white cabbage are aimed for. As part of the autonomous crop establishment, a planting unit was developed and constructed that can carry out an automated crop stand establishment process using a robot platform. The analysis of the quality of the planting process showed a comparable planting performance and planting accuracy to conventional systems of automated field vegetable planting. During the development of the planting unit, the focus was placed on an adaptive design of the unit so that machine parameters can be dynamically adjusted during the planting process. It was possible to reduce the energy requirement of the overall system by dynamically opening and closing the planting furrow during the planting process in order to minimize the draft force. It also creates the basis for an autonomous planting process. Using an attached camera and an AI for image classification, the planting quality can also be recorded and planting parameters such as the planting depth and furrow width can then be adjusted in order to influence the plant placement. At the same time, the AI-based image classification can also be used to control the planting process itself. If the planting tape tears or the separation is blocked, no seedlings are planted. The AI recognizes this and can instruct the robot to suspend the planting process. For automated crop monitoring, the camera, in cooperation with a neural network for instance segmentation, offers the possibility of a contact-free and high-resolution recording of plant parameters. Using instance segmentation of the cabbage head, the cabbage plant and the individual cabbage leaves, as well as a depth image generation using structure-from-motion, it was possible to determine plant parameters such as the absolute leaf area, the number of leaves or the fruit volume of the cabbage head across several growth stages. This offers farmers new opportunities in crop management, which can be tailored even more specifically to individual plants using the information collected. As many possibilities as the use of cameras in combination with neural network-based image analysis offers, there are still some challenges. One of the fundamental challenges lies in the provision and annotation of image data to ensure robust image analysis. The more complex the use case, the more varying images the data set must contain in order to provide the neural network with a basis of information with which it can learn the necessary features. To reduce the complexity of the use case of detecting and segmenting cabbage plants, an AI-based image translation was used to standardize the exposure variations. No annotation is required to train the AI-based image translation, which is trained unsupervised. By standardizing the exposure, the complexity of the images can be reduced, which means that fewer images need to be annotated for a robust use of instance segmentation. This method was also tested for varying growth stages and varieties.
Stimulating awareness of precision farming through gamification: The farming simulator case
(2024) Pavlenko, Tetiana; Argyropoulos, Dimitrios; Arnoult, Matthieu; Engel, Thomas; Gadanakis, Yiorgos; Griepentrog, Hans W.; Kambuta, Jacob; Latherow, Tamisan; Murdoch, Alistair J.; Tranter, Richard; Paraforos, Dimitrios S.
Precision Farming (PF) provides different solutions to assist the decision-making process on farms. Current PF technologies such as variable rate site-specific applications can bring financial benefits to farmers as well as environmental advantages. Increasing scientific research and an expanding number of PF products are supporting a growing interest in PF applications. However, the actual implementation of these technologies on farms in many cases remains low. Therefore, there is a need to disseminate and transfer knowledge about the positive aspects of PF. One of the ways to facilitate the adoption process of PF technologies is education and training among farmers and other interested stakeholders. This paper presents a case study using the computer game Farming Simulator as an educational tool for raising awareness about the topic in an engaging and enjoyable way. Two distinct downloadable content (DLC) versions were developed and implemented in the versions 2019 and 2022 of the game, respectively, each with a range of PF functionalities (automatic steering, variable rate applications, yield mapping among others). The PF DLCs have received positive feedback from students and scientists but also the general public. The growing number of downloads (3,661,069 in total for both DLC versions as of 15th November 2023) demonstrates the effectiveness of computer games as an educational tool to educate and inform stakeholders (farmers, scientists, students, and the general public) about agricultural challenges and the potential of PF as a solution.
Effects of different ground segmentation methods on the accuracy of UAV-based canopy volume measurements
(2024) Han, Leng; Wang, Zhichong; He, Miao; He, Xiongkui; Han, Leng; College of Science, China Agricultural University, Beijing, China; Wang, Zhichong; Tropics and Subtropics Group, Institute of Agricultural Engineering, University of Hohenheim, Stuttgart, Germany; He, Miao; College of Science, China Agricultural University, Beijing, China; He, Xiongkui; College of Science, China Agricultural University, Beijing, China
The nonuniform distribution of fruit tree canopies in space poses a challenge for precision management. In recent years, with the development of Structure from Motion (SFM) technology, unmanned aerial vehicle (UAV) remote sensing has been widely used to measure canopy features in orchards to balance efficiency and accuracy. A pipeline of canopy volume measurement based on UAV remote sensing was developed, in which RGB and digital surface model (DSM) orthophotos were constructed from captured RGB images, and then the canopy was segmented using U-Net, OTSU, and RANSAC methods, and the volume was calculated. The accuracy of the segmentation and the canopy volume measurement were compared. The results show that the U-Net trained with RGB and DSM achieves the best accuracy in the segmentation task, with mean intersection of concatenation (MIoU) of 84.75% and mean pixel accuracy (MPA) of 92.58%. However, in the canopy volume estimation task, the U-Net trained with DSM only achieved the best accuracy with Root mean square error (RMSE) of 0.410 m 3 , relative root mean square error (rRMSE) of 6.40%, and mean absolute percentage error (MAPE) of 4.74%. The deep learning-based segmentation method achieved higher accuracy in both the segmentation task and the canopy volume measurement task. For canopy volumes up to 7.50 m 3 , OTSU and RANSAC achieve an RMSE of 0.521 m 3 and 0.580 m 3 , respectively. Therefore, in the case of manually labeled datasets, the use of U-Net to segment the canopy region can achieve higher accuracy of canopy volume measurement. If it is difficult to cover the cost of data labeling, ground segmentation using partitioned OTSU can yield more accurate canopy volumes than RANSAC.
Effect of packaging and storage conditions on the pasting and functional properties of pretreated yellow-fleshed cassava flour
(2024) Ekeledo, Esther; Abass, Adebayo; Müller, Joachim
Cassava is highly susceptible to post harvest physiological deterioration which makes it necessary to initiate processing so as to extend the shelf life. In order to improve and enhance the nutritional characteristics of the processed cassava flour, this research was carried out so as to evaluate the adequate packaging materials and storage conditions necessary for safe storage and good flour quality. Pasting properties of food/flour is an indication of the different applicability of starch-based food ingredients in product development. The effect of packaging materials (cylindric polyvinyl containers and aluminum ziplock pouch bags) on quality attributes of pretreated yellow-fleshed cassava flour (YFCF) samples stored in two storage conditions a (cooling chamber at 5 ◦ C and 30 % relative humidity and; in a climate chamber at 30 ◦C and 50 % relative humidity) was investigated for 8 weeks. Flour samples from each package type were evaluated for water absorption capacity, pasting and oil absorption capacity fortnightly. The treated initial flour sample before storage-sulfured (BSS) had the highest peak viscosity (891 RVU). The low peak time at the end of storage in non-sulfured flours packed in aluminum pouch bags and stored at 5 ◦C is an evidence of time and energy saving capacity. The water absorption capacity of non-sulfured flour samples packed in cylindric polyvinyl containers and the sulfured flour sample packed in an aluminum pouch bag at 30 ◦C increased with storage duration. The aluminum ziplock pouch bags showed excellent storage quality and retained better pasting property. The climatic storage condition revealed better keeping quality. The use of sodium metabisulphite revealed its suitability as a pretreatment tool.
Is heat stress a growing problem for dairy cattle husbandry in the temperate regions? A case study of Baden-Württemberg in Germany
(2024) Leandro, Miguel António; Stock, Joana; Bennewitz, Jörn; Chagunda, Mizeck G. G.
Heat stress with measurable effects in dairy cattle is a growing concern in temperate regions. Heat stress in temperate regions differs between environments with different geophysical characteristics. Microclimates specific to each environment were found to greatly impact at what level heat stress occurs and will occur in the future. The landlocked state of Baden-Württemberg, Germany, provides several different environments, hence, a good case-study. Temperature–Humidity Index (THI) from 17 weather stations for the years 2003 to 2022 was calculated and milking yields from 22 farms for the years 2017 to 2022 were collected. The occurrences and evolving patterns of heat stress were analyzed with the use of a THI, and the effect of heat stress on milk yield was analyzed based on milking records from Automated Milking Systems. Daily average THI was calculated using hourly readings of relative humidity and ambient temperature, disregarding solar radiation and wind, as all animals were permanently stabled. Based on studies conducted in Baden-Württemberg and neighboring regions, cited ahead in the section of THI, THI = 60 was the threshold for heat stress occurrence. Findings show that the heat stress period varied between stations from 64 to 120 d with THI ≥ 60 in a year. This aligns with yearly and summer averages, also steadily increasing from May to September. The length of the heat stress period was found to increase 1 extra day every year. Extreme weather events such as heat waves did not increase the heat stress period of that year in length but increased the average THI. Milk yield was found to be significantly (α = 0.05) different between counties grouped into different zones according to heat stress severity and rate of increase in daily average THI. Future attempts at managing heat stress on dairy cattle farms in the temperate regions should account for microclimate, as geographical proximity does not mean that the increase in heat stress severity will be the same in the 2 neighboring areas.
Modeling and spatiotemporal mapping of water quality through remote sensing techniques: A case study of the Hassan Addakhil dam
(2021) El Ouali, Anas; El Hafyani, Mohammed; Roubil, Allal; Lahrach, Abderrahim; Essahlaoui, Ali; Hamid, Fatima Ezzahra; Muzirafuti, Anselme; Paraforos, Dimitrios S.; Lanza, Stefania; Randazzo, Giovanni
With its high water potential, the Ziz basin is one of the most important basins in Morocco. This paper aims to develop a methodology for spatiotemporal monitoring of the water quality of the Hassan Addakhil dam using remote sensing techniques combined with a modeling approach. Firstly, several models were established for the different water quality parameters (nitrate, dissolved oxygen and chlorophyll a) by combining field and satellite data. In a second step, the calibration and validation of the selected models were performed based on the following statistical parameters: compliance index R2, the root mean square error and p-value. Finally, the satellite data were used to carry out spatiotemporal monitoring of the water quality. The field results show excellent quality for most of the samples. In terms of the modeling approach, the selected models for the three parameters (nitrate, dissolved oxygen and chlorophyll a) have shown a good correlation between the measured and estimated values with compliance index values of 0.62, 0.56 and 0.58 and root mean square error values of 0.16 mg/L, 0.65 mg/L and 0.07 µg/L for nitrate, dissolved oxygen and chlorophyll a, respectively. After the calibration, the validation and the selection of the models, the spatiotemporal variation of water quality was determined thanks to the multitemporal satellite data. The results show that this approach is an effective and valid methodology for the modeling and spatiotemporal mapping of water quality in the reservoir of the Hassan Addakhil dam. It can also provide valuable support for decision-makers in water quality monitoring as it can be applied to other regions with similar conditions.
Food informatics - Review of the current state-of-the-art, revised definition, and classification into the research landscape
(2021) Krupitzer, Christian; Stein, Anthony
Background: The increasing population of humans, changing food consumption behavior, as well as the recent developments in the awareness for food sustainability, lead to new challenges for the production of food. Advances in the Internet of Things (IoT) and Artificial Intelligence (AI) technology, including Machine Learning and data analytics, might help to account for these challenges. Scope and Approach: Several research perspectives, among them Precision Agriculture, Industrial IoT, Internet of Food, or Smart Health, already provide new opportunities through digitalization. In this paper, we review the current state-of-the-art of the mentioned concepts. An additional concept is Food Informatics, which so far is mostly recognized as a mainly data-driven approach to support the production of food. In this review paper, we propose and discuss a new perspective for the concept of Food Informatics as a supportive discipline that subsumes the incorporation of information technology, mainly IoT and AI, in order to support the variety of aspects tangent to the food production process and delineate it from other, existing research streams in the domain. Key Findings and Conclusions: Many different concepts related to the digitalization in food science overlap. Further, Food Informatics is vaguely defined. In this paper, we provide a clear definition of Food Informatics and delineate it from related concepts. We corroborate our new perspective on Food Informatics by presenting several case studies about how it can support the food production as well as the intermediate steps until its consumption, and further describe its integration with related concepts.
Lab-scale carbonation of wood ash for CO2-sequestration
(2021) Koch, Robin; Sailer, Gregor; Paczkowski, Sebastian; Pelz, Stefan; Poetsch, Jens; Müller, Joachim
This study evaluated the CO2 sequestration potential with combustion ashes in the aqueous phase. The aim was to provide a cost-effective carbon sequestration method for combustion unit operators (flue gas cleaning) or biogas producers (biogas upgrading). Therefore, two separate test series were executed to identify the carbonation efficiency (CE) of bottom wood ash (1) at different mixing ratios with water in batch experiments and (2) under dynamic flow conditions. It was furthermore evaluated whether subsequent use of the carbonated wood ash for soil amendment could be possible and whether the process water could be passed into the sewage. The batch test series showed that different mixing ratios of wood ash and water had an influence on the CE. The flow series showed that the mean CE varied between approximately 14% and 17%. Thus, the ash proved to be suitable for carbonation processes. The process water was dischargeable, and the carbonated wood ash has potential for chalking, as no legal thresholds were exceeded. Therefore, wood ash carbonation could be used as a low-tech CO2 sequestration technology. Compared to existing energy consuming and cost intensive carbon capture and storage technologies, sequestration with ash could be beneficial, as it represents a low-tech approach.
Characteristics and anaerobic co-digestion of press water from wood fuel preparation and digested sewage sludge
(2022) Sailer, Gregor; Empl, Florian; Kuptz, Daniel; Silberhorn, Martin; Ludewig, Darwin; Lesche, Simon; Pelz, Stefan; Müller, Joachim
Technical drying of harvested wood fuels is heat and energy consuming, while natural pre-drying in the forest, e.g., in stacks or storage piles, is accompanied by energy losses through natural degradation processes. Dewatering of energy wood by mechanical pressing is an innovative method to reduce the moisture content prior to thermal drying while producing press waters (PW, also referred to as wood juice) as a by-product. To date, the characteristics and utilization potentials of PW are largely unknown. In this study, three different spruce- and poplar-based PW were analyzed for their characteristics such as dry matter (DM), organic dry matter (oDM) concentration, pH-value, element concentration or chemical compounds. Additionally, they were used for anaerobic digestion (AD) experiments with digested sewage sludge (DSS) serving as inoculum. The fresh matter-based DM concentrations of the PW were between 0.4 and 3.2%, while oDM concentrations were between 87 and 89%DM. The spruce-based PW were characterized by lower pH-values of approx. 4.4, while the poplar-based PW was measured at pH 8. In the AD experiments, DSS alone (blank variant) achieved a specific methane yield of 95 ± 26 mL/goDM, while the mixture of spruce-based PW and DSS achieved up to 160 ± 12 mL/goDM, respectively. With further research, PW from wood fuel preparation offer the potential to be a suitable co-substrate or supplement for AD processes.
Catalase activity in hot-air dried mango as an indicator of heat exposure for rapid detection of heat stress
(2022) Mukhtar, Adnan; Latif, Sajid; Salvatierra-Rojas, Ana; Müller, Joachim
The growing market for dried fruits requires more attention to quality parameters. Mango and other tropical fruits are commonly dried at temperatures ranging from 40 °C to 80 °C. Convincing evidence suggests that the nutritional quality of dried fruits is best preserved when dried at low temperatures ≤50 °C, whereas increasing drying temperatures lead to the degradation of the most valuable nutrients inside the fruit. Currently, there is no system or direct measurement method that can assist in identifying the quality deterioration of dried fruits caused by excessive heat exposure during drying. From this perspective, the activity of the heat-sensitive enzyme ‘catalase’ was used for the first time to evaluate and compare mango slices dried at 40 °C, 60 °C and 80 °C. Various methods, including direct and indirect flotation tests and spectrophotometric measurements, were explored to measure the residual catalase activity in the dried samples. Results showed that the spectrophotometry and indirect flotation test produced the best results, revealing a significant difference (p < 0.05) in the catalase activity of mango slices dried at 40 °C, 60 °C and 80 °C, which the direct-dried mango flotation test failed to predict. Furthermore, this study demonstrates the potential applicability of catalase activity to indicate heat stress in dried mango slices processed at different temperatures.
Maize characteristics estimation and classification by spectral data under two soil phosphorus levels
(2022) Qiao, Baiyu; He, Xiongkui; Liu, Yajia; Zhang, Hao; Zhang, Lanting; Liu, Limin; Reineke, Alice-Jacqueline; Liu, Wenxin; Müller, Joachim
As an essential element, the effect of Phosphorus (P) on plant growth is very significant. In the early growth stage of maize, it has a high sensitivity to the deficiency of phosphorus. The main purpose of this paper is to monitor the maize status under two phosphorus levels in soil by a nondestructive testing method and identify different phosphorus treatments by spectral data. Here, the Analytical Spectral Devices (ASD) spectrometer was used to obtain canopy spectral data of 30 maize inbred lines in two P-level fields, whose reflectance differences were compared and the sensitive bands of P were discovered. Leaf Area Index (LAI) and yield under two P levels were quantitatively analyzed, and the responses of different varieties to P content in soil were observed. In addition, the correlations between 13 vegetation indexes and eight phenotypic parameters were compared under two P levels so as to find out the best vegetation index for maize characteristics estimation. A Back Propagation (BP) neural network was used to evaluate leaf area index and yield, and the corresponding prediction model was established. In order to classify different P levels of soil, the method of support vector machine (SVM) was applied. The results showed that the sensitive bands of P for maize canopy included 763 nm, 815 nm, and 900–1000 nm. P-stress had a significant effect on LAI and yield of most varieties, whose reduction rate reached 41% as a whole. In addition, it was found that the correlations between vegetation indexes and phenotypic parameters were weakened under low-P level. The regression coefficients of 0.75 and 0.5 for the prediction models of LAI and yield were found by combining the spectral data under two P levels. For the P-level identification in soil, the classification accuracy could reach above 86%. These abilities potentially allow for phenotypic parameters prediction of maize plants by spectral data and different phosphorus contents identification with unknown phosphorus fertilizer status.
Drying behavior and curcuminoids changes in turmeric slices during drying under simulated solar radiation as influenced by different transparent cover materials
(2022) Komonsing, Nilobon; Reyer, Sebastian; Khuwijitjaru, Pramote; Mahayothee, Busarakorn; Müller, Joachim
Dried turmeric is used as a spice and traditional medicine. The common drying methods for turmeric (Curcuma longa L.) are sun drying and solar drying. In this study, turmeric slices with a thickness of 2 mm were dried at 40, 50, 60, and 70 °C in a laboratory hot-air dryer with a simulated solar radiation applied through transparent polycarbonate cover (UV impermeable) and PMMA cover (UV permeable). Air velocity and relative humidity of drying air were fixed at 1.0 M·s−1 and 25 g H2O kg−1 dry air, respectively. Light significantly increased the sample temperature under both covers. Page was the best model to predict the drying characteristics of turmeric slices. Drying rate correlated with the effective moisture diffusivity, which increased at higher temperature. The hue angle (h°) of turmeric was distinctly lower at 70 °C under both covers. The dried products were of intensive orange color. Curcumin, demethoxycurcumin, and total curcuminoids were affected by the cumulated thermal load (CTL). The lowest curcumin content was found at 40 °C under PMMA (highest CTL). The optimum drying condition was 70 °C under polycarbonate cover due to shorter drying time and better preservation of color and curcuminoids in the dried product.
Application of infrared imaging for early detection of downy mildew (Plasmopara viticola) in grapevine
(2022) Zia-Khan, Shamaila; Kleb, Melissa; Merkt, Nikolaus; Schock, Steffen; Müller, Joachim
Late detection of fungal infection is the main cause of inadequate disease control, affecting fruit quality and reducing yield of grapevine. Therefore, infrared imagery as a remote sensing technique was investigated in this study as a potential tool for early disease detection. Experiments were conducted under field conditions, and the effects of temporal and spatial variability in the leaf temperature of grapevine infected by Plasmopara viticola were studied. Evidence of the grapevine’s thermal response is a 3.2 °C increase in leaf temperature that occurred long before visible symptoms appeared. In our study, a correlation of R2 = 0.76 at high significance level (p ≤ 0.001) was found between disease severity and MTD. Since the pathogen attack alters plant metabolic activities and stomatal conductance, the sensitivity of leaf temperature to leaf transpiration is high and can be used to monitor irregularities in temperature at an early stage of pathogen development.

Browse

Recent Submissions