Fakultät Agrarwissenschaften

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Die Fakultät entwickelt in Lehre und Forschung nachhaltige Produktionstechniken der Agrar- und Ernährungswirtschaft. Sie erarbeitet Beiträge für den ländlichen Raum und zum Verbraucher-, Tier- und Umweltschutz.

Homepage: https://agrar.uni-hohenheim.de/

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3D-surface MALDI mass spectrometry imaging for visualising plant defensive cardiac glycosides in Asclepias curassavica
(2021) Dreisbach, Domenic; Petschenka, Georg; Spengler, Bernhard; Bhandari, Dhaka R.
Mass spectrometry–based imaging (MSI) has emerged as a promising method for spatial metabolomics in plant science. Several ionisation techniques have shown great potential for the spatially resolved analysis of metabolites in plant tissue. However, limitations in technology and methodology limited the molecular information for irregular 3D surfaces with resolutions on the micrometre scale. Here, we used atmospheric-pressure 3D-surface matrix-assisted laser desorption/ionisation mass spectrometry imaging (3D-surface MALDI MSI) to investigate plant chemical defence at the topographic molecular level for the model system Asclepias curassavica. Upon mechanical damage (simulating herbivore attacks) of native A. curassavica leaves, the surface of the leaves varies up to 700 μm, and cardiac glycosides (cardenolides) and other defence metabolites were exclusively detected in damaged leaf tissue but not in different regions of the same leaf. Our results indicated an increased latex flow rate towards the point of damage leading to an accumulation of defence substances in the affected area. While the concentration of cardiac glycosides showed no differences between 10 and 300 min after wounding, cardiac glycosides decreased after 24 h. The employed autofocusing AP-SMALDI MSI system provides a significant technological advancement for the visualisation of individual molecule species on irregular 3D surfaces such as native plant leaves. Our study demonstrates the enormous potential of this method in the field of plant science including primary metabolism and molecular mechanisms of plant responses to abiotic and biotic stress and symbiotic relationships.
A low-tech approach to mobilize nutrients from organic residues to produce bioponic stock solutions
(2024) Heintze, Sebastian; Beckett, Marc; Kriem, Lukas Simon; Germer, Jörn; Asch, Folkard; Liu, Guodong
Organic residues, as a nutrient source suitable of producing solutions for hydroponic crop production, have the potential to reduce the dependence on mineral fertilizers. Especially in remote and resource-constrained regions, organic residues might be the only option to produce hydroponic nutrient solutions. However, nutrient solutions made from organic residues, called bioponic solutions, are usually unbalanced in their nutrient composition, which leads to deficiencies and poor plant growth. This study aimed to experimentally develop a low-tech approach to produce bioponic stock solutions rich in NO3−, P, and K, to create a balanced bioponic solution. The mixed bioponic solution contained 58 mg L−1 NH4+-N, 43 mg L−1 NO3−-N, 50 mg L−1 PO43−-P, and 246 mg L−1 K+. This approach resulted in satisfactory levels of P, K and micronutrients. The solution was tested pure and spiked with Ca(NO3)2 on lettuce in comparison with a mineral Hoagland nutrient solution. Neither the bioponic nor the spiked bioponic solution achieved comparable lettuce yields to the Hoagland solution. The poor growth of the plants in the bioponic solution was attributed to an unfavorable NH4+:NO3− ratio, high microorganism load, and elevated pH levels. However, the approach of preparing bioponic stock solutions could be promising for future research into the production of balanced bioponic nutrient solutions from organic residues.
The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes
(2023) Avila Santos, Anderson Paulo; Kabiru Nata’ala, Muhammad; Kasmanas, Jonas Coelho; Bartholomäus, Alexander; Keller-Costa, Tina; Jurburg, Stephanie D.; Tal, Tamara; Camarinha-Silva, Amélia; Saraiva, João Pedro; Ponce de Leon Ferreira de Carvalho, André Carlos; Stadler, Peter F.; Sipoli Sanches, Danilo; Rocha, Ulisses
Background: Metagenomic data can shed light on animal-microbiome relationships and the functional potential of these communities. Over the past years, the generation of metagenomics data has increased exponentially, and so has the availability and reusability of data present in public repositories. However, identifying which datasets and associated metadata are available is not straightforward. We created the Animal-Associated Metagenome Metadata Database (AnimalAssociatedMetagenomeDB - AAMDB) to facilitate the identification and reuse of publicly available non-human, animal-associated metagenomic data, and metadata. Further, we used the AAMDB to (i) annotate common and scientific names of the species; (ii) determine the fraction of vertebrates and invertebrates; (iii) study their biogeography; and (iv) specify whether the animals were wild, pets, livestock or used for medical research. Results: We manually selected metagenomes associated with non-human animals from SRA and MG-RAST. Next, we standardized and curated 51 metadata attributes (e.g., host, compartment, geographic coordinates, and country). The AAMDB version 1.0 contains 10,885 metagenomes associated with 165 different species from 65 different countries. From the collected metagenomes, 51.1% were recovered from animals associated with medical research or grown for human consumption (i.e., mice, rats, cattle, pigs, and poultry). Further, we observed an over-representation of animals collected in temperate regions (89.2%) and a lower representation of samples from the polar zones, with only 11 samples in total. The most common genus among invertebrate animals was Trichocerca (rotifers). Conclusion: Our work may guide host species selection in novel animal-associated metagenome research, especially in biodiversity and conservation studies. The data available in our database will allow scientists to perform meta-analyses and test new hypotheses (e.g., host-specificity, strain heterogeneity, and biogeography of animal-associated metagenomes), leveraging existing data. The AAMDB WebApp is a user-friendly interface that is publicly available at https://webapp.ufz.de/aamdb/ .
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
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.
Challenges of green production of 2,5‐furandicarboxylic acid from bio‐derived 5‐hydroxymethylfurfural: Overcoming deactivation by concomitant amino acids
(2022) Neukum, Dominik; Baumgarten, Lorena; Wüst, Dominik; Sarma, Bidyut Bikash; Saraçi, Erisa; Kruse, Andrea; Grunwaldt, Jan‐Dierk
The oxidation of 5‐hydroxymethylfurfural (HMF) to 2,5‐furandicarboxylic acid (FDCA) is highly attractive as FDCA is considered as substitute for the petrochemically derived terephthalic acid. There are only few reports on the direct use of unrefined HMF solutions from biomass resources and the influence of remaining constituents on the catalytic processes. In this work, the oxidation of HMF in a solution as obtained from hydrolysis and dehydration of saccharides in chicory roots was investigated without intermediate purification steps. The amount of base added to the solution was critical to increase the FDCA yield. Catalyst deactivation occurred and was attributed to poisoning by amino acids from the bio‐source. A strong influence of amino acids on the catalytic activity was found for all supported Au, Pt, Pd, and Ru catalysts. A supported AuPd(2 : 1)/C alloy catalyst exhibited both superior catalytic activity and higher stability against deactivation by the critical amino acids.
Comparing hops and malt price transmission in the beer value chain: evidence from Germany
(2025) Hess, Sebastian; Bublik, Nikolas
The German beer value chain has received limited attention so far, despite the country’s central role in global beer production. This study investigates the price dynamics of its two key inputs—hops and malt—using monthly price data from 2015 to 2024 based on a unique dataset from a German hops cooperative. While contract farming is common for both raw materials, malt is traded via private firms, whereas hops are marketed almost exclusively through farmer-owned cooperatives. A vector error correction model (VECM) is estimated, incorporating structural break dummies identified through Bai–Perron tests, followed by forecast error variance decomposition (FEVD) and impulse response function (IRF) analysis. The results show that hop prices are largely self-driven and adjust more quickly to deviations from equilibrium than malt or beer prices. While malt and beer exhibit stronger interdependencies, the hop sector displays greater price stability. The findings further reveal that the malting sector responded significantly to the recent energy price crisis in Germany, whereas the hop sector did not.
Computational aspects of experimental designs in multiple-group mixed models
(2023) Prus, Maryna; Filová, Lenka
We extend the equivariance and invariance conditions for construction of optimal designs to multiple-group mixed models and, hence, derive the support of optimal designs for first- and second-order models on a symmetric square. Moreover, we provide a tool for computation of D - and L -efficient exact designs in multiple-group mixed models by adapting the algorithm of Harman et al. (Appl Stoch Models Bus Ind, 32:3–17, 2016). We show that this algorithm can be used both for size-constrained problems and also in settings that require multiple resource constraints on the design, such as cost constraints or marginal constraints.
Computational sizing of solar powered peanut oil extraction in Senegal using a synthetic load profile
(2024) Bonzi, Joévin Wiomou; 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.
Computing optimal allocation of trials to subregions in crop‐variety testing in case of correlated genotype effects
(2025) Prus, Maryna
The subject of this work is the allocation of trials to subregions in crop variety testing in the case of correlated genotype effects. A solution for computation of optimal allocations using the OptimalDesign package in R is proposed. The obtained optimal designs minimize linear criteria based on the mean squared error matrix of the best linear unbiased prediction of the genotype effects. The proposed computational approach allows for any kind of additional linear constraint on the designs. The results are illustrated by a real data example.
DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics
(2021) Kienbaum, Lydia; Correa Abondano, Miguel; Blas, Raul; Schmid, Karl
Background: Maize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color in native landraces and modern varieties. Various phenotyping approaches were developed to measure maize cob parameters in a high throughput fashion. More recently, deep learning methods like convolutional neural networks (CNNs) became available and were shown to be highly useful for high-throughput plant phenotyping. We aimed at comparing classical image segmentation with deep learning methods for maize cob image segmentation and phenotyping using a large image dataset of native maize landrace diversity from Peru. Results: Comparison of three image analysis methods showed that a Mask R-CNN trained on a diverse set of maize cob images was highly superior to classical image analysis using the Felzenszwalb-Huttenlocher algorithm and a Window-based CNN due to its robustness to image quality and object segmentation accuracy (r = 0.99). We integrated Mask R-CNN into a high-throughput pipeline to segment both maize cobs and rulers in images and perform an automated quantitative analysis of eight phenotypic traits, including diameter, length, ellipticity, asymmetry, aspect ratio and average values of red, green and blue color channels for cob color. Statistical analysis identified key training parameters for efficient iterative model updating. We also show that a small number of 10–20 images is sufficient to update the initial Mask R-CNN model to process new types of cob images. To demonstrate an application of the pipeline we analyzed phenotypic variation in 19,867 maize cobs extracted from 3449 images of 2484 accessions from the maize genebank of Peru to identify phenotypically homogeneous and heterogeneous genebank accessions using multivariate clustering. Conclusions: Single Mask R-CNN model and associated analysis pipeline are widely applicable tools for maize cob phenotyping in contexts like genebank phenomics or plant breeding.
Degradation of hop latent viroid during anaerobic digestion of infected hop harvest residues
(2021) Hagemann, Michael Helmut; Born, Ute; Sprich, Elke; Seigner, Luitgardis; Oechsner, Hans; Hülsemann, Benedikt; Steinbrenner, Jörg; Winterhagen, Patrick; Lehmair, Erich
The citrus bark cracking viroid (CBCVd) was identified as causal agent for a severe stunting disease in hops. Viroids are highly stable parasitic RNAs, which can be easily transmitted by agricultural practices. Since CBCVd has recently been detected in two European countries a growing concern is that this pathogen will further spread and thereby threaten the European hop production. Biogas fermentation is used to sanitize hop harvest residues infected with pathogenic fungi. Consequently, the aim of this study was to test if biogas fermentation can contribute to viroid degradation at mesophilic (40 °C) and thermophilic (50 °C) conditions. Therefore, a duplex reverse transcription real-time PCR analysis was developed for CBCVd and HLVd detection in biogas fermentation residues. The non-pathogenic hop latent viroid (HLVd) was used as viroid model for the pathogenic CBCVd. The fermentation trials showed that HLVd was significantly degraded after 30 days at mesophilic or after 5 days at thermophilic conditions, respectively. However, sequencing revealed that HLVd was not fully degraded even after 90 days. The incubation of hop harvest residues at different temperatures between 20 and 70 °C showed that 70 °C led to a significant HLVd degradation after 1 day. In conclusion, we suggest combining 70 °C pretreatment and thermophilic fermentation for efficient viroid decontamination.
Design and development of an accessible open-source augmented reality learning authoring tool for applications in agroecological settings
(2024) Shidende, Deogratias; Treydte, Anna
Augmented Reality (AR) has emerged as a transformative educational technology, offering immersive, multisensory learning experiences that enhance engagement, conceptual understanding, and contextualization. In agroecology, where students must grasp complex ecological interactions and context-dependent knowledge, AR can bridge the gap between classroom instruction and field-based learning. However, the creation of AR content remains largely inaccessible to many educators in higher learning institutions (HLIs), particularly those without programming skills and individuals with disabilities such as the deaf and hard of hearing (DHH), and the blind and low vision (BLV). This dissertation addresses the central question: How can an accessible AR learning authoring tool enable non-technical educators and users with disabilities to create AR learning experiences for agroecology education in HLIs? To address this question, the study employed a design-based research (DBR) methodology, integrating Agile Scrum for iterative, inclusive tool development. Seven research questions (RQ1–RQ7) guided the investigation. First, a document-based analysis (RQ1) compared open-source software licenses (OSLs) to determine their suitability for academic–industry collaboration. Permissive licenses (e.g., MIT, BSD) were found to offer more flexibility in code reuse and integration, thereby promoting long-term project sustainability, although they require supplementary legal mechanisms to ensure reciprocity. Next, functional and non-functional software requirements (RQ2) were elicited through stakeholder workshops, interviews, surveys, and accessibility evaluations. These requirements informed the selection and redesign of MirageXR, an open-source AR platform. Key accessibility features were specified for DHH users, such as customizable captioning of audio augmentations, and for BLV users, such as voice navigation and spatial audio cues. These enhancements underscored the dual instructional and assistive roles of AR tools. In response to RQ3, a modular, component-based software architecture was designed using the C4 model. This enabled seamless integration of external services (e.g., 3D object repositories, learning management systems, and automatic speech recognition) and ensured that features could be added or updated without disrupting system stability. This modularity was essential given the evolving nature of AR technologies. The design and implementation phases (RQ4 & RQ5) employed participatory iterative prototyping with user feedback throughout the development process. Accessibility features were integrated into image, audio, and video augmentations, with functionalities such as caption editing, playback speed control, and 3D spatial positioning. These solutions directly addressed gaps in existing AR authoring tools, particularly for DHH and BLV users. The sixth research question (RQ6) investigated usability and applicability through an AR creation workshop involving 24 agroecology educators. Findings revealed that although participants initially encountered difficulties, they gained proficiency over time. UMUX scores showed a correlation between AR experience and perceived usefulness. Participants highlighted AR's potential to visualize complex concepts and engage students in experiential learning. However, limitations in 3D content availability and customization highlighted the need for integrated 3D content creation and editing tools specifically tailored to agroecology. To answer RQ7, the study conducted a systematic literature review of 60 studies to identify current accessibility evaluation methods in AR. Most evaluations employed task-based scenarios, utilizing metrics such as time on task, error rate, and user satisfaction. The study's own evaluation validated that DHH users could independently author AR content using the developed tool. In contrast, BLV users could navigate the authoring functionalities but were unable to fully author AR content, indicating that further design improvements and assistive functionalities are required for full inclusion. Methodologically, this study contributes a novel integration of DBR and Agile Scrum for inclusive educational technology design. This hybrid framework facilitated rapid prototyping, iterative refinement, and participatory co-design, and is recommended for broader application in accessibility-focused educational innovation. Future research should document and validate this methodological approach across additional contexts and user groups. The study makes the following contributions: (1) provision of an open-source, extensible AR authoring interfaces and codebase for public use; (2) improved AR accessibility for AR for DHH and BLV users; (3) development of modular architectural and algorithmic solutions to enable multimodal accessibility; (4) empirical validation of AR’s pedagogical value in agroecology education; and (5) identification of optimal open-source licensing models for collaborative educational software development. In sum, the findings demonstrate that an accessible, open-source AR authoring tool can empower diverse educators, including those with disabilities, to create inclusive and contextually relevant learning experiences. The research affirms the importance of universal design, participatory development, and modularity in educational technology design and concludes with strategic recommendations: integrating AI-assisted 3D content generation, expanding accessibility to additional user groups, and establishing communities of practice to support sustainable AR content development in agroecology.
Digital agriculture: socio-technical-physical interactions and the transformation of the rural world(s)
(2024) Hidalgo Jaramillo, Francisco Javier; Regina, Birner
The social and environmental challenges that humanity faces today to produce food, fuel, and fibers in a sustainable and fair way call for a transformation. Digital agriculture has been embraced with much enthusiasm by many as the contour of such transformation. Proponents of these technologies, including international organizations as well as numerous researchers focused on innovations, describe this innovation as a paradigm shift. Associated with increased efficiencies and enhanced communication, digital agriculture is commonly depicted by these groups as the advent of a more sustainable and ‘smart’ future. Other groups, including grassroots organizations, socio-environmental activists, and critical scholars, on the other hand, see digital agriculture with skepticism and concern. They refer to the entrenchment of digital agriculture in productivist, capitalist, and extractivist forms of production, and a linkage with the consolidation of corporate power and state surveillance. Using a critical and systems approach, this thesis scrutinizes these arguments, examining the socio-technical transitions that emerge from agricultural digitalization, and discerns their societal and environmental consequences. This examination is relevant given that despite digital agriculture can transform the face of agricultural systems, it is not yet clear in what way. The emergent condition of digitalization requires this analysis to inform responsible governance of this innovation. Critical studies have made important contributions to this understanding. However, the complexity of digital agriculture calls for additional conceptual frameworks to be incorporated. The coffee production system has been selected as a case study in this thesis. This selection responds to the global scope of this system and the relevance that it represents for rural development. To set the picture: coffee is one of the most traded agricultural products in the world. Yet, more than 70% of it is produced by smallholder farmers who receive less than 10% of its final value. Meanwhile, coffee farmers experience manifold social and environmental challenges that threaten their livelihoods and the sustainability of the whole system. Poverty, power and information asymmetries, and climate change are among them. Against this background, this thesis takes the perspective of coffee as a crop, a cultural system, and a value chain. Following a qualitative research approach, the analysis is informed by a theoretical literature review and data from semi-structured interviews with developers and users of digital technologies. The thesis is divided into three studies (chapters 2, 3, and 4) which together present a critical analysis applied at three scales: 1) global, 2) value chain, and 3) local. Across these studies, three main socio-technical aspects of digital agriculture are addressed. First, global governance of digital agriculture and its consequences for farmers’ rights and capabilities. Second, the consequences of different technical assemblages for the sustainability of agricultural systems. Third, local forms of interaction with digital technologies. After presenting and introduction in Chapter 1, Chapter 2 presents a literature review on the political dynamics of digital agriculture. Drawing upon an emancipatory conceptualization of agency and sovereignty, this chapter is focused on describing two main forms of governance: governance through and governance of digital technologies in the context of agriculture. This description is followed by an analysis of the multiple effects of these two forms of governance on farmer’s sovereignty and agency. The analysis revealed that the governance of digital agriculture is an assemblage of multiple agencies of human and cyber agents (smart devices, automated machines, algorithms). Socio-technical interactions in this assemblage result simultaneously in sovereignty and agency gains and losses for farmers - a complex set of power transactions in which farmers participate many times inadvertently. Together with oppressive forms of governance associated with corporate technological lock-in, data extractivism, and a surveilling state, there is evidence also of a democratic facet of digitalization. This facet is integrated by open-collaborative networks, data cooperatives, cyberactivism, and open-source software. With this analysis, the study aimed to understand how the political position of farmers is affected by digitalization, understanding that this process is occurring in a context of structural power imbalance. A socio-technical perspective is applied in Chapter 3 to explore 20 digital tools designed for the coffee value chain, examining the pathways toward sustainability (environmental, social, and economic) promoted by these tools. The socio-technical perspective mainly proposes that social and technical systems shape each other in reciprocal interactions. Building on this idea, the chapter examines the technical attributes of these tools (functionality, technologies included, operation rules, information flow). Subsequently, it analyzes the consequences of these attributes in terms of three broad social dynamics: 1) knowledge and value systems represented, 2) power structures, and 3) possibilities for using these tools effectively. The forms in which these social dynamics are shaped by these tools, in turn, yield specific sustainability outcomes. These include the kind of production systems that are endorsed - and not endorsed -, the access to these technologies and their benefits, and the way in which social inequalities and power asymmetries are addressed - or not addressed -. The data for this analysis comes from interviews with 15 developers of these tools and secondary information. The analysis shows that technical attributes play a fundamental role in directing the kinds of pathways toward sustainability that are made available for agricultural systems. Additionally, it shows that in some cases, rather than a revolution, digital agriculture can look like business as usual but tweaked. Chapter 4 presents a local perspective on digitalization. Using data from interviews with 73 households in two selected coffee growing communities in Colombia, this chapter explores how they engage with digital technologies. The study parts from the idea that important reality-design gaps in digital agriculture result from a lack of understanding and inclusion of local worldviews around digital technologies and farming. Amartya Sen’s capabilities approach was adopted as the conceptual framework for the analysis. This framework posits that resources only become assets when they can be used by individuals to accomplish the life they value. For that reason, the analysis in this chapter was focused on first, understanding the elements that configure a valuable life for these communities, and next, understanding how they use digital technologies to support the accomplishment of this life. The underlying values of this local process of technological appropriation were compared with the values represented by broader narratives of digital agriculture. This offered a picture of the negotiations and tensions that occur when contrasting visions of farming, digitalization, and a desirable future, interface. Drawing upon a relational perspective, the local appropriation process is characterized by multiple negotiations between farmers’ personal and collective goals, situated knowledge, institutional programs, and the agency of non-humans (e.g. land, plants, animals, machines). From these interactions emerge distinctive forms of digitalization and non-digitalization. This process of local appropriation revealed the critical view of farmers and agency, for example, by following a digitalization pathway that profoundly diverges from dominant imaginaries and discourses around digital agriculture. By applying a systems approach and by integrating three frameworks into critical scholarship - (1) emancipatory conceptualization of agency and sovereignty, (2) Sen´s capabilities approach, and (3) a relational approach - this thesis presents evidence of the complexity of socio-technical-physical interactions that lead to certain broad-mainstream and local-everyday digitalization pathways. These pathways, in turn, present particular societal consequences, such as the kind of agricultural worlds that are made possible, the interests that are represented in them, and the possibilities of participation for different social groups. More than a single trajectory, digital agriculture is a space of multiplicity and permanent emergence, also for reproducing current – not necessarily sustainable - models. For this reason, this thesis calls for abandoning notions of immutability, universality, and uniformity in development discourses, perspectives of rurality, and the generation of new technologies. Instead, it proposes to integrate a critical and systems-relational perspective into inclusionary innovation research and practice.
Effects of different ground segmentation methods on the accuracy of UAV-based canopy volume measurements
(2024) Han, Leng; Wang, Zhichong; He, Miao; He, Xiongkui
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.
Effects of using deep learning to predict the geographic origin of barley genebank accessions on genome–environment association studies
(2025) Chang, Che-Wei; Schmid, Karl
Genome–environment association (GEA) is an approach for identifying adaptive loci by combining genetic variation with environmental parameters, offering potential for improving crop resilience. However, its application to genebank accessions is limited by missing geographic origin data. To address this limitation, we explored the use of neural networks to predict the geographic origins of barley accessions and integrate imputed environmental data into GEA. Neural networks demonstrated high accuracy in cross-validation but occasionally produced ecologically implausible predictions as models solely considered geographical proximity. For example, some predicted origins were located within non-arable regions, such as the Mediterranean Sea. Using barley flowering time genes as benchmarks, GEA integrating imputed environmental data ( N=11,032) displayed partially concordant yet complementary detection of genomic regions near flowering time genes compared to regular GEA ( N=1,626), highlighting the potential of GEA with imputed data to complement regular GEA in uncovering novel adaptive loci. Also, contrary to our initial hypothesis anticipating a significant improvement in GEA performance by increasing sample size, our simulations yield unexpected insights. Our study suggests potential limitations in the sensitivity of GEA approaches to the considerable expansion in sample size achieved through predicting missing geographical data. Overall, our study provides insights into leveraging incomplete geographical origin data by integrating deep learning with GEA. Our findings indicate the need for further development of GEA approaches to optimize the use of imputed environmental data, such as incorporating regional GEA patterns instead of solely focusing on global associations between allele frequencies and environmental gradients across large-scale landscapes.
Etablierung und Vernetzung digital-gestützter Systeme auf Pferdebetrieben unter Berücksichtigung der betriebswirtschaftlichen Optimierung
(2024) Speidel, Linda Thurid; Dickhöfer, Uta
Das Management eines pferdehaltenden Betriebs umfasst eine Vielzahl arbeitswirtschaftlicher Herausforderungen. Dazu zählen unter anderem die zeitintensiven Arbeitsabläufe, das notwendige Kundenmanagement in Pensions- und Schulpferdebetrieben sowie die begrenzte Verfügbarkeit von Fachkräften. Auf Ackerbau- und Veredelungsbetrieben wird der Nutzen der Digitalisierung bereits wahrgenommen, da deren Einsatz unter anderem Potenzial zur Zeitersparnis und Arbeitserleichterung bietet. Obgleich des genannten Potenzials sind Pferdebetriebe bisher wenig digitalisiert und technisiert, die Grundversorgung erfolgt meist manuell. Im Rahmen dieser, im Projekt „Digitale Wertschöpfungsketten für eine nachhaltige kleinstrukturiert Landwirtschaft“ (DiWenkLa) angefertigten, Forschungsarbeit wurde daher untersucht, welche Möglichkeiten der Digitalisierung bisher genutzt werden und unter welchen Voraussetzungen die einzelnen Systeme in Pferdebetrieben etabliert werden können. Des Weiteren wurde analysiert, welche Auswirkungen der Einsatz dieser Systeme auf den Arbeitszeitbedarf im Pferdebetrieb hat und welche Informationen über Schnittstellen zwischen den Systemen ausgetauscht werden können. Dafür wurden von März 2020 bis Oktober 2023 Experteninterviews, (Arbeitszeit-)Beobachtungen und Online-Befragungen durchgeführt. Zunächst wurden die vorhandenen Möglichkeiten der digitalen Technisierung auf Pferdebetrieben in der Fütterung von Rau- und Krippenfutter, der Entmistung und Einstreu, der Gesundheits- und Sicherheitsüberwachung sowie der Kommunikation und dem Betriebsmanagement untersucht. Der Schwerpunkt lag auf den Voraussetzungen, die erfüllt sein müssen, um ausgewählte digital-technische Systeme auf den Betrieben zu etablieren. Zu diesem Zweck wurden Beobachtungen und Befragungen bei pferdehaltenden Betrieben (N=1235) und den Kooperationspartnern aus der Industrie des Projekts DiWenkLa durchgeführt. Die Ergebnisse zeigen, dass die Einbindung digital-technischer Systeme von der Investitionsbereitschaft der Betriebsleitenden, der stabilen Internetverbindung, einer verfügbaren Stromversorgung in den Stallgebäuden (Steckdosen) und dem vorhandenen Haltungssystem (z. B. Einzel- oder Gruppenhaltung sowie Gliederung der Haltung in Funktionsbereiche) abhängt. Auf den an einer Online-Befragung teilnehmenden Pferdebetrieben (N=451) wurden Kameras zur Sicherheits- (30,8 %) und Gesundheitsüberwachung (22,6 %) sowie Software für die Kundenkommunikation (24,8 %) und das Betriebsmanagement (13,7 %) eingesetzt. Die automatisierte Fütterung von Krippenfutter (9,3 %) und Raufutter (7,3 %) war selten vorhanden. Eine Gliederung der Haltung in Funktionsbereiche führte zu einem vermehrten Einsatz digital-technischer Systeme. Als Gründe gegen den Einsatz neuer digital-technischer Systeme wurden von den 207 teilnehmenden Betriebsleitenden die fehlenden Finanzmittel, der unbekannte wirtschaftliche Nutzen sowie der Kontaktverlust zu den Tieren genannt. In Anlehnung an die vorliegenden Ergebnisse erscheint eine erneute Erhebung der vorhandenen Systeme auf Pferdebetrieben sinnvoll, um etwaige Veränderungen im Verlauf der Zeit abzubilden und die Gründe für die Investition in neue digital-technische Systeme zu ermitteln. Des Weiteren sollte untersucht werden, ob Einsteller bei einem höheren Digitalisierungsgrad im Pferdebetrieb bereit sind, einen höheren Pensionspreis zu bezahlen. Zu diesem Zweck könnte die Zahlungsbereitschaft beim Einsatz von z. B. Futterautomation und intelligenten Kameras zur Gesundheitsüberwachung abgefragt werden. Des Weiteren wurde analysiert, welche betriebswirtschaftlichen Vorteile die auf den Pferdebetrieben etablierten, digital gesteuerten Systeme mit sich bringen können. Dazu wurden die möglichen Auswirkungen der Digitalisierung auf den Arbeitszeitbedarf für verschiedene Arbeitsabläufe wie die Fütterung, Entmistung und Hütesicherheit untersucht. Dies wurde durch Zeiterfassungen mit und ohne den Einsatz der Systeme sowie mit Hilfe von Online-Befragungen (N=1014) und Experteninterviews (N=16) realisiert. Die Ergebnisse der Untersuchungen zeigen bei der Einzelhaltung von Pferden eine potenzielle Arbeitszeitersparnis in der Fütterung und Entmistung von bis zu 65 % durch eine automatisierte Fütterung von Rau- und Krippenfutter und den Einsatz von mobiler Technik, wie beispielsweise einem Hoflader. Zudem kann der Einsatz dieser Systeme auch dazu führen, dass die benötigte Arbeitszeit in anderen Arbeitsabläufen sinkt. Ein Beispiel hierfür ist der Einsatz einer automatisierten Fütterung, welcher zu einer geringeren Arbeitszeit in der Kundenkommunikation führte. Dies wurde in den durchgeführten Datenerhebungen dadurch begründet, dass gewünschte Änderungen in der Rationsgestaltung automatisiert erfolgen und somit nicht persönlich kommuniziert werden müssen. Darüber hinaus lassen sich durch eine digitale Absprache und die Dokumentation wesentlicher Arbeitsschritte und Änderungen in den Abläufen sowie Kundenwünschen Fehler reduzieren und Missverständnisse vermeiden. Auf Basis der Ergebnisse sollten die Abfragen der Arbeitszeitbedarfe der Arbeitsabläufe mit exakten und vorgegebenen Werten wiederholt und teilweise ergänzt werden. Dies betrifft z. B. den Zeitbedarf für das Betriebsmanagement, die Tierkontrolle und den Weidegang. Dadurch können die vorhandenen Kalkulationsgrundlagen aktualisiert und das Bewusstsein der Betriebsleitenden für teils unbeachteten Arbeitszeitaufwand geschärft werden. Dieser kann wiederum durch den Einsatz von digital-technischen Systemen reduziert werden. Darüber hinaus wurde ein Konzept für eine Schnittstelle für digitale Systeme für Pferdebetriebe entwickelt, um den Datenaustausch zwischen Systemen zu vereinfachen und somit die Übersichtlichkeit der verschiedenen Informationen aus den eingesetzten Technologien zu optimieren sowie zusätzliche Zeitersparnis zu gewährleisten. Dazu wurden mittels Experteninterviews (N=20 Experten) die auszutauschenden Informationen zwischen Systemen für die Fütterung, die Entmistung und Einstreu, die Gesundheits- und Sicherheitsüberwachung sowie das Betriebsmanagement und die Kommunikation identifiziert, um eine verbesserte Übersicht für die Betriebsleitenden zu gewährleisten. In diesem Kontext wurde der Datenaustausch zwischen Futterautomationen und Kommunikationssoftware als besonders relevant hervorgehoben. Je nach Bedarf können die Informationen aus dem Datenaustausch transparent an die Kunden (z. B. Einsteller) weitergegeben werden. Eine Online-Befragung ergab, dass die Mehrheit (57,2 %) aller Teilnehmenden (N=451) Interesse an einer Vernetzung der Systeme zeigt. In zukünftigen Untersuchungen könnten zum einen die Gründe für das Interesse an einer Vernetzung analysiert werden, da bisher lediglich die Gegenposition untersucht wurde (d.h. Gründe gegen das Interesse an der Vernetzung). Zum anderen könnte die Einbindung weiterer Systeme neben den genannten geprüft werden, insbesondere die Anbindung der vorhandenen Hardware (z. B. Solarien, Aquatrainer) an das Internet und die (standardisierte) Programmierung der Schnittstelle, um z. B. eine unkomplizierte und transparente Abrechnung der Nutzung zu ermöglichen. Die Etablierung und Vernetzung digital-technischer Systeme in Pferdebetrieben ist bei erfüllbaren Voraussetzungen als sinnvoll anzusehen, da sie eine Arbeitszeiteinsparung generieren, eine Entlastung der Arbeitskräfte ermöglichen, die Kommunikation verbessern und das Betriebsmanagement sowie die Sicherheits- und Gesundheitskontrolle der Tiere vereinfachen. Diese Faktoren sind neben der Beachtung und Verbesserung des Tierwohls für eine nachhaltige, zukunftsfähige Pferdehaltung unabdingbar.
Exploring the impact of digitalization on sustainability challenges in German fruit production from the perspectives of stakeholders
(2025) Gaber, Kirsten; Rösch, Christine; Bieling, Claudia
Unique challenges exist in the fruit cultivation sector and, if not considered in the development and application of technologies, this sector is at risk of being left behind in the ongoing digital transformation of agriculture. While understanding perspectives of stakeholders is critical for technology acceptance, their knowledge and views are underrepresented in analyses on the impact of digitalization on fruit production. This research works to fill this knowledge gap by qualitatively analyzing semi-structured interviews on the impact of digitalization on sustainability challenges in fruit production with 34 stakeholders along the fruit value chain in the case study region of Lake Constance, Germany. Societal acceptance and understanding of fruit cultivation practices, restricted plant protection product use, labour availability, and biodiversity support were the main reported environmental and socio-economic challenges. Nearly all stakeholders (94%) were hopeful that digital technologies could effectively address environmental challenges in fruit production, particularly through increased efficiency, while greater uncertainties were reported for the socio-economic challenges. Perceptions of digitalization’s chances and challenges varied among individuals, fruit production systems, and farm sizes. Authors provide recommendations, including targeted support for small-scale fruit farmers and suggestions for future research activities, and emphasize the importance of factual knowledge dissemination on digitalization in fruit farming to support informed adoption choices for intended users. The results of this study offer critical viewpoints on the current challenges in fruit production and the potential for digitalization to increase sustainability in this sector.
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; 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.
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.

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