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Acrocomia spp.: Neglected crop, ballyhooed multipurpose palm or fit for the bioeconomy? A review
(2021) Vargas-Carpintero, Ricardo; Hilger, Thomas; Mössinger, Johannes; Souza, Roney Fraga; Barroso Armas, Juan Carlos; Tiede, Karen; Lewandowski, Iris
Acrocomia spp., a genus of wild-growing palms in the neotropics, is rapidly gaining interest as a promising multipurpose crop. Diverse products can be derived from various components of the palm, the oils being of highest interest. Acrocomia shows similar oil yield and fatty acid composition to the African oil palm (Elaeis guineensis). It is, however, able to cope with a wider range of environmental conditions, including temporary water scarcity and lower temperatures, thus potentially a more sustainable alternative to its tropical counterpart. Acrocomia’s research history is recent compared to other traditional crops and thus knowledge gaps, uncertainty, and challenges need to be addressed. This review attempts to assess the acrocomia’s preparedness for cultivation by highlighting the state-of-the-art in research and identifying research gaps. Based on a systematic literature search following a value web approach, it (a) provides a comprehensive overview of research topics, (b) shows the development of publication activities over time and the drivers of this development, and (c) compiles main findings to assess the acrocomia’s preparedness for commercial cultivation. Our results confirm its multipurpose characteristic as a potential feedstock for manifold sectors. Research has continued to increase over the last decade, especially on A. aculeata and is driven by the interest in bioenergy. Increasing knowledge on botany has contributed to understanding the genetic diversity and genus-specific biology. This has enabled applied research on seed germination and propagation toward domestication and initial plantation activities, mostly in Brazil. Main research gaps are associated with genotype–environment interaction, planting material, crop management, and sustainable cropping systems. Overall, we conclude that acrocomia is at an early phase of development as an alternative and multipurpose crop and its up-scaling requires the integration of sustainability strategies tailored to location-based social-ecological conditions.
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 functional properties of diet protein hydrolysate and oil from fish waste on canine immune parameters, cardiac biomarkers, and fecal microbiota
(2024) Cabrita, Ana R. J.; Barroso, Carolina; Fontes-Sousa, Ana Patrícia; Correia, Alexandra; Teixeira, Luzia; Maia, Margarida R. G.; Vilanova, Manuel; Yergaliyev, Timur; Camarinha-Silva, Amélia; Fonseca, António J. M.
Locally produced fish hydrolysate and oil from the agrifood sector comprises a sustainable solution both to the problem of fish waste disposal and to the petfood sector with potential benefits for the animal’s health. This study evaluated the effects of the dietary replacement of mainly imported shrimp hydrolysate (5%) and salmon oil (3%; control diet) with locally produced fish hydrolysate (5%) and oil (3.2%) obtained from fish waste (experimental diet) on systemic inflammation markers, adipokines levels, cardiac function and fecal microbiota of adult dogs. Samples and measurements were taken from a feeding trial conducted according to a crossover design with two diets (control and experimental diets), six adult Beagle dogs per diet and two periods of 6 weeks each. The experimental diet, with higher docosahexaenoic (DHA) and eicosapentaenoic (EPA) acids contents, decreased plasmatic triglycerides and the activity of angiotensin converting enzyme, also tending to decrease total cholesterol. No effects of diet were observed on serum levels of the pro-inflammatory cytokines interleukin (IL)-1β, IL-8, and IL-12/IL-23 p40, and of the serum levels of the anti-inflammatory adipokine adiponectin. Blood pressure, heart rate and echocardiographic measurements were similar between diets with the only exception of left atrial to aorta diameter ratio that was higher in dogs fed the experimental diet, but without clinical relevance. Diet did not significantly affect fecal immunoglobulin A concentration. Regarding fecal microbiome, Megasphaera was the most abundant genus, followed by Bifidobacterium , Fusobacterium , and Prevotella , being the relative abundances of Fusobacterium and Ileibacterium genera positively affected by the experimental diet. Overall, results from the performed short term trial suggest that shrimp hydrolysate and salmon oil can be replaced by protein hydrolysate and oil from fish by-products without affecting systemic inflammatory markers, cardiac structure and function, but potentially benefiting bacterial genera associated with healthy microbiome. Considering the high DHA and EPA contents and the antioxidant properties of fish oil and hydrolysate, it would be worthwhile in the future to assess their long-term effects on inflammatory markers and their role in spontaneous canine cardiac diseases and to perform metabolomic and metagenomics analysis to elucidate the relevance of microbiota changes in the gut.
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.
A collaborative, systems approach for the development of biomass-based value webs: The case of the acrocomia palm
(2022) Vargas-Carpintero, Ricardo; Hilger, Thomas; Tiede, Karen; Callenius, Carolin; Mössinger, Johannes; Souza, Roney Fraga; Barroso Armas, Juan Carlos; Rasche, Frank; Lewandowski, Iris
The diversification of biomass resources is key to the transition towards a bioeconomy. Acrocomia spp., a neotropical genus of palms, is an example of plants’ diversity potential for a sustainable bioeconomy. Acrocomia’s adaptability to environments outside rainforests, its specific fruit properties and high yields has generated the interest of researchers and entrepreneurs, triggering its introduction as a multipurpose oil crop. Developing sustainability-oriented and knowledge-based acrocomia value webs requires a collaborative, systems approach from the outset. Fostering an inter- and transdisciplinary dialogue on acrocomia through a participatory workshop with both academic and non-academic actors contributed to this endeavor. This allowed the identification of priorities, knowledge gaps, and stakeholder roles, and served as the basis for the co-creation of a research and development roadmap. Key steps for the introduction of acrocomia include intertwined technical aspects relating to the development of planting material, cultivation systems, processing technologies and applications, market entry, and value web governance aspects. A broad collaboration among scientists, the public and private sectors, farmers, and civil society, is required for the development of acrocomia value webs. The incorporation of sustainability and a consideration of context in the design and development phases are fundamental to fostering the sustainable performance of acrocomia value webs.
Coping and social cohesion mechanisms in addressing climate change and land degradation in Ghana
(2025) Amankwah, Harry Quaye; Ndah, Hycenth Tim; Schuler, Johannes; Abdulai, Alhassan Lansah; Knierim, Andrea
The West Africa sub-region is faced with major interlinked challenges in ensuring sustainable livelihoods in the context of climate change and land degradation. To ensure sustainable food production and resource use, agriculture needs to be resilient through the application of responsive adaptation and coping strategies. While many studies have explored coping and adaptation strategies employed by farmers, little attention has been paid to the farmers’ indigenous practices and the role of social cohesion mechanisms. Using the sustainable livelihood framework, this study addressed this gap by exploring coping strategies and social cohesion mechanisms used by smallholder farmers in northern Ghana. It made use of a mixed-method approach, including a household survey, focus group discussions, expert interviews, field observations, and key informant interviews. Data was collected from 60 households in 6 communities across 3 districts in the study region. The results showed that social assets such as membership of self-help groups were the most important source of coping, particularly for the most vulnerable households. Such membership enabled farmers to secure micro-loans and receive aid from fellow members during extreme climate events such as floods. Farmers’ tacit knowledge emerged as pivotal in coping with climate change and enhancing soil fertility, encompassing traditional weather forecasting, the making of bio-pesticides, and sustainable land management (SLM) practices such as ridge and bund creation as well as intercropping. Key coping practices reported by the study participants included reduction of food consumption, off-farm jobs, selling livestock, charcoal making and reliance on remittances. The results further revealed that social cohesion mechanisms or collective action play a key role in helping farmers cope and adapt to climate change while improving soil fertility. Social cohesion is mainly reflected in two different structures depending on gender. While diverse challenges of innovation adoption exist, socio-cultural barriers differ by gender. The study recommends the integration of farmers throughout the innovation development process and proposes the need for a concerted effort to strengthen land tenure security policies, ensuring equitable access to farmlands for all genders.
CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning
(2022) Krupitzer, Christian; Naber, Jens; Stauffert, Jan-Philipp; Mayer, Jan; Spielmann, Jan; Ehmann, Paul; Boci, Noel; Bürkle, Maurice; Ho, André; Komorek, Clemens; Heinickel, Felix; Kounev, Samuel; Becker, Christian; Latoschik, Marc Erich
Goal: This paper presents an immersive Virtual Reality (VR) system to analyze and train Executive Functions (EFs) of soccer players. EFs are important cognitive functions for athletes. They are a relevant quality that distinguishes amateurs from professionals. Method: The system is based on immersive technology, hence, the user interacts naturally and experiences a training session in a virtual world. The proposed system has a modular design supporting the extension of various so-called game modes. Game modes combine selected game mechanics with specific simulation content to target particular training aspects. The system architecture decouples selection/parameterization and analysis of training sessions via a coaching app from an Unity3D-based VR simulation core. Monitoring of user performance and progress is recorded by a database that sends the necessary feedback to the coaching app for analysis. Results: The system is tested for VR-critical performance criteria to reveal the usefulness of a new interaction paradigm in the cognitive training and analysis of EFs. Subjective ratings for overall usability show that the design as VR application enhances the user experience compared to a traditional desktop app; whereas the new, unfamiliar interaction paradigm does not negatively impact the effort for using the application. Conclusion: The system can provide immersive training of EF in a fully virtual environment, eliminating potential distraction. It further provides an easy-to-use analyzes tool to compare user but also an automatic, adaptive training mode.
Cow’s microbiome from antepartum to postpartum: a long-term study covering two physiological challenges
(2022) Tröscher-Mußotter, Johanna; Deusch, Simon; Borda-Molina, Daniel; Frahm, Jana; Dänicke, Sven; Camarinha-Silva, Amélia; Huber, Korinna; Seifert, Jana
Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.
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.
Determination of optimal phage load and administration time for antibacterial treatment
(2024) Plunder, Steffen; Burkard, Markus; Helling, Thomas; Lauer, Ulrich M.; Hoelzle, Ludwig E.; Marongiu, Luigi
Using phages as antibacterials is becoming a customary practice in Western countries. Nonetheless, successful treatments must consider the growth rate of the bacterial host and the degradation of the virions. Therefore, successful treatments require administering the right amount of phage (viral load, Vφ) at the right moment (administration time, Tφ). The present protocols implement a machine learning approach to determine the best combination of Vφ and Tφ to obtain the elimination of the target bacterium from a system. Basic Protocol 1: One bacterium, one phage. Alternate Protocol 1: One bacterium, one phage (wrapping function). Alternate Protocol 2: One bacterium, one phage (wrapping function, alternative growing model). Basic Protocol 2: Two bacteria, one phage. Alternate Protocol 3: Two bacteria, one phage (launch from terminal).
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.
Functionality of the Na+-translocating NADH:quinone oxidoreductase and quinol:fumarate reductase from Prevotella bryantii inferred from homology modeling
(2024) Hau, Jann-Louis; Schleicher, Lena; Herdan, Sebastian; Simon, Jörg; Seifert, Jana; Fritz, Günter; Steuber, Julia
Members of the family Prevotellaceae are Gram-negative, obligate anaerobic bacteria found in animal and human microbiota. In Prevotella bryantii , the Na + -translocating NADH:quinone oxidoreductase (NQR) and quinol:fumarate reductase (QFR) interact using menaquinone as electron carrier, catalyzing NADH:fumarate oxidoreduction. P. bryantii NQR establishes a sodium-motive force, whereas P. bryantii QFR does not contribute to membrane energization. To elucidate the possible mode of function, we present 3D structural models of NQR and QFR from P. bryantii to predict cofactor-binding sites, electron transfer routes and interaction with substrates. Molecular docking reveals the proposed mode of menaquinone binding to the quinone site of subunit NqrB of P. bryantii NQR. A comparison of the 3D model of P. bryantii QFR with experimentally determined structures suggests alternative pathways for transmembrane proton transport in this type of QFR . Our findings are relevant for NADH-dependent succinate formation in anaerobic bacteria which operate both NQR and QFR.
Host metabolome and faecal microbiome shows potential interactions impacted by age and weaning times in calves
(2023) Amin, Nida; Schwarzkopf, Sarah; Tröscher-Mußotter, Johanna; Camarinha-Silva, Amélia; Dänicke, Sven; Huber, Korinna; Frahm, Jana; Seifert, Jana
Background: Calves undergo nutritional, metabolic, and behavioural changes from birth to the entire weaning period. An appropriate selection of weaning age is essential to reduce the negative effects caused by weaning-related dietary transitions. This study monitored the faecal microbiome and plasma metabolome of 59 female Holstein calves during different developmental stages and weaning times (early vs. late) and identified the potential associations of the measured parameters over an experimental period of 140 days. Results: A progressive development of the microbiome and metabolome was observed with significant differences according to the weaning groups (weaned at 7 or 17 weeks of age). Faecal samples of young calves were dominated by bifidobacterial and lactobacilli species, while their respective plasma samples showed high concentrations of amino acids (AAs) and biogenic amines (BAs). However, as the calves matured, the abundances of potential fiber-degrading bacteria and the plasma concentrations of sphingomyelins (SMs), few BAs and acylcarnitines (ACs) were increased. Early-weaning at 7 weeks significantly restructured the microbiome towards potential fiber-degrading bacteria and decreased plasma concentrations of most of the AAs and SMs, few BAs and ACs compared to the late-weaning event. Strong associations between faecal microbes, plasma metabolites and calf growth parameters were observed during days 42–98, where the abundances of Bacteroides, Parabacteroides , and Blautia were positively correlated with the plasma concentrations of AAs, BAs and SMs as well as the live weight gain or average daily gain in calves. Conclusion: The present study reported that weaning at 17 weeks of age was beneficial due to higher growth rate of late-weaned calves during days 42–98 and a quick adaptability of microbiota to weaning-related dietary changes during day 112, suggesting an age-dependent maturation of the gastrointestinal tract. However, the respective plasma samples of late-weaned calves contained several metabolites with differential concentrations to the early-weaned group, suggesting a less abrupt but more-persistent effect of dietary changes on host metabolome compared to the microbiome.
Impact of added phytase and different dietary InsP6 levels on the structure and core microbiota of the digestive tract in broiler chickens
(2025) Rubio-Cervantes, Ismael; Wolfrum, Stephanie; Rodehutscord, Markus; Camarinha-Silva, Amélia
The main objective of this research was to investigate the composition and shifts of the gut microbiota of broiler chickens in response to varying exogenous phytase combined with increasing levels of myo-inositol (1,2,3,4,5,6) hexakis (dihydrogen phosphate) (InsP6) in the feed. The InsP6 level was adjusted with the addition of oilseed meals (OSM) at the expense of maize starch. A secondary objective was to assess the existence of a core microbiota across the feed, litter and gastrointestinal tract (GIT). A total of 840 Ross 308 broiler chickens were raised in 84 elevated pens in groups of 10. The treatments consisted of four feed mixtures (FM) designed to achieve 1.4 (FM1.4), 1.9 (FM1.9), 2.4 (FM2.4), and, 3.0 (FM3.0) g InsP6-P/kg, each combined with 500, 1500 or 3000 FTU phytase/kg. In the crop and the ileum, Lactobacillus relative abundance decreased when OSM and phytase increased (p < 0.05), while FM2.4 and FM3.0 were associated with increased Ligilactobacillus abundance across the GIT (p < 0.05). No interaction effects were found across the studied sections (p = 0.22). Four amplicon sequence variants (ASV), identified within the genera Lactobacillus, Ligilactobacillus, and Limosilactobacillus were consistently found across the intestine sections. These four ASVs represented 58.9 % of the relative abundance in the crop, 72.9 % in the ileum and 29.7 % in the ceca. The results demonstrated that higher levels of OSM in the feed and exogenous phytase significantly affected these bacterial populations, decreasing Lactobacillus while increasing Ligilactobacillus, indicating independent effects of FM and phytase supplementation.
Integrating sensor data, laboratory analysis, and computer vision in machine learning-driven E-Nose systems for predicting tomato shelf life
(2025) Senge, Julia Marie; Kaltenecker, Florian; Krupitzer, Christian
Assessing the quality of fresh produce is essential to ensure a safe and satisfactory product. Methods to monitor the quality of fresh produce exist; however, they are often expensive, time-consuming, and sometimes require the destruction of the sample. Electronic Nose (E-Nose) technology has been established to track the ripeness, spoilage, and quality of fresh produce. Our study developed a freshness monitoring system for tomatoes, combining E-Nose technology with storage condition monitoring, color analysis, and weight-loss tracking. Different post-purchase scenarios were investigated, focusing on the influence of temperature and mechanical damage on shelf life. Support Vector Classifier (SVC) and k-Nearest Neighbor (kNN) were applied to classify storage scenarios and storage days, while Support Vector Regression (SVR) and kNN regression were used for predicting storage days. By using a data fusion approach with Linear Discriminant Analysis (LDA), the SVC achieved an accuracy of 72.91% in predicting storage days and an accuracy of 86.73% in distinguishing between storage scenarios. The kNN yielded the best regression results, with a Mean Absolute Error (MAE) of 0.841 days and a coefficient of determination of 0.867. The results highlight the method’s potential to predict storage scenarios and storage days, providing insight into the product’s remaining shelf life.
Methane reduction potential of brown seaweeds and their influence on nutrient degradation and microbiota composition in a rumen simulation technique
(2022) Künzel, Susanne; Yergaliyev, Timur; Wild, Katharina J.; Philippi, Hanna; Petursdottir, Asta H.; Gunnlaugsdottir, Helga; Reynolds, Chris K.; Humphries, David J.; Camarinha-Silva, Amélia; Rodehutscord, Markus
This study aimed to investigate the effects of two brown Icelandic seaweed samples (Ascophyllum nodosum and Fucus vesiculosus) on in vitro methane production, nutrient degradation, and microbiota composition. A total mixed ration (TMR) was incubated alone as control or together with each seaweed at two inclusion levels (2.5 and 5.0% on a dry matter basis) in a long-term rumen simulation technique (Rusitec) experiment. The incubation period lasted 14 days, with 7 days of adaptation and sampling. The methane concentration of total gas produced was decreased at the 5% inclusion level of A. nodosum and F. vesiculosus by 8.9 and 3.6%, respectively (P < 0.001). The total gas production was reduced by all seaweeds, with a greater reduction for the 5% seaweed inclusion level (P < 0.001). Feed nutrient degradation and the production of volatile fatty acids and ammonia in the effluent were also reduced, mostly with a bigger effect for the 5% inclusion level of both seaweeds, indicating a reduced overall fermentation (all P ≤ 0.001). Microbiota composition was analyzed by sequencing 16S rRNA amplicons from the rumen content of the donor cows, fermenter liquid and effluent at days 7 and 13, and feed residues at day 13. Relative abundances of the most abundant methanogens varied between the rumen fluid used for the start of incubation and the samples taken at day 7, as well as between days 7 and 13 in both fermenter liquid and effluent (P < 0.05). According to the differential abundance analysis with q2-ALDEx2, in effluent and fermenter liquid samples, archaeal and bacterial amplicon sequence variants were separated into two groups (P < 0.05). One was more abundant in samples taken from the treatment without seaweed supplementation, while the other one prevailed in seaweed supplemented treatments. This group also showed a dose-dependent response to seaweed inclusion, with a greater number of differentially abundant members between a 5% inclusion level and unsupplemented samples than between a 2.5% inclusion level and TMR. Although supplementation of both seaweeds at a 5% inclusion level decreased methane concentration in the total gas due to the high iodine content in the seaweeds tested, the application of practical feeding should be done with caution.
Microbiota and nutrient portraits of European roe deer (Capreolus capreolus) rumen contents in characteristic Southern German habitats
(2023) Dahl, Sarah-Alica; Seifert, Jana; Camarinha-Silva, Amélia; Cheng, Yu-Chieh; Hernández-Arriaga, Angélica; Hudler, Martina; Windisch, Wilhelm; König, Andreas
Roe deer ( Capreolus capreolus ) are found in various habitats, from pure forest cultures to agricultural areas and mountains. In adapting to the geographically and seasonally differentiating food supply, they depend, above all, on an adapted microbiome. However, knowledge about the microbiome of wild ruminants still needs to be improved. There are only a few publications for individual species with a low number of samples. This study aims to identify a core microbiota for Bavarian roe deer and present nutrient and microbiota portraits of the individual habitat types. This study investigated the roe deer’s rumen (reticulorumen) content from seven different characteristic Bavarian habitat types. The focus was on the composition of nutrients, fermentation products, and the rumen bacterial community. A total of 311 roe deer samples were analysed, with the most even possible distribution per habitat, season, age class, and gender. Significant differences in nutrient concentrations and microbial composition were identified for the factors habitat, season, and age class. The highest crude protein content (plant protein and microbial) in the rumen was determined in the purely agricultural habitat (AG), the highest value of non-fibre carbohydrates in the alpine mountain forest, and the highest fibre content (neutral detergent fibre, NDF) in the pine forest habitat. Maximum values for fibre content go up to 70% NDF. The proportion of metabolites (ammonia, lactate, total volatile fatty acids) was highest in the Agriculture-Beech-Forest habitat (ABF). Correlations can be identified between adaptations in the microbiota and specific nutrient concentrations, as well as in strong fluctuations in ingested forage. In addition, a core bacterial community comprising five genera could be identified across all habitats, up to 44% of total relative abundance. As with all wild ruminants, many microbial genera remain largely unclassified at various taxonomic levels. This study provides a more in-depth insight into the diversity and complexity of the roe deer rumen microbiota. It highlights the key microorganisms responsible for converting naturally available nutrients of different botanical origins.
Network impact analysis on the performance of Secure Group Communication schemes with focus on IoT
(2024) Prantl, Thomas; Amann, Patrick; Krupitzer, Christian; Engel, Simon; Bauer, André; Kounev, Samuel
Secure and scalable group communication environments are essential for many IoT applications as they are the cornerstone for different IoT devices to work together securely to realize smart applications such as smart cities or smart health. Such applications are often implemented in Wireless Sensor Networks, posing additional challenges. Sensors usually have low capacity and limited network connectivity bandwidth. Over time, a variety of Secure Group Communication (SGC) schemes have emerged, all with their advantages and disadvantages. This variety makes it difficult for users to determine the best protocol for their specific application purpose. When selecting a Secure Group Communication scheme, it is crucial to know the model’s performance under varying network conditions. Research focused so far only on performance in terms of server and client runtimes. To the best of our knowledge, we are the first to perform a network-based performance analysis of SGC schemes. Specifically, we analyze the network impact on the two centralized SGC schemes SKDC and LKH and one decentralized/contributory SGC scheme G-DH. To this end, we used the ComBench tool to simulate different network situations and then measured the times required for the following group operations: group creation, adding and removing members. The evaluation of our simulation results indicates that packet loss and delay influence the respective SGC schemes differently and that the execution time of the group operations depends more on the network situations than on the group sizes.
Seasonal variation in the activity pattern of red squirrels and their mammalian predators
(2024) Kalb, Nadine; Schlindwein, Xenia; Gottschalk, Thomas K.; Dvorak, Jan; Randler, Christoph; Kalb, Nadine; Department of Biology, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 24, D-72076, Tübingen, Germany; Schlindwein, Xenia; Department of Biology, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 24, D-72076, Tübingen, Germany; Gottschalk, Thomas K.; Department of Regional Management, University of Applied Forest Sciences Rottenburg, Schadenweilerhof, D-72108, Rottenburg am Neckar, Germany; Dvorak, Jan; Department of Food Informatics / Computational Science Hub (CSH), University of Hohenheim, D-70599, Stuttgart, Germany; Randler, Christoph; Department of Biology, Eberhard Karls Universität Tübingen, Auf der Morgenstelle 24, D-72076, Tübingen, Germany
Camera traps are a powerful tool to monitor the activity pattern of species over long time periods. Camera data can be used to analyze activity patterns of or temporal niche partitioning among species. Temporal niche partitioning plays an important role for species coexistence and is under constant evolutionary pressure from predator-prey relationships. Our study aimed to investigate temporal shifts in activity patterns of red squirrels and two mammalian predators, red fox and marten ( Martes spec .). Previous studies yielded different activity patterns for these species depending on location, season, predator-prey interactions, and food- availability. We used camera traps to monitor the activity of squirrels, red fox and martens throughout a whole year in a mountainous forest in southwestern Germany. We also investigated a possible difference in activity among different color morphs as coloration in mammals is often associated with concealment, for squirrels, however, such an effect could not be demonstrated so far. We found a diurnal activity for squirrels in all seasons with a bimodal activity pattern during spring, trimodal in summer and unimodal in fall and winter. Activity patterns did not differ between black and red color morphs. The activity of the squirrels showed only low to moderate overlaps with fox and marten, but there was still slight variation among seasons. Activity overlaps were higher in spring and summer, which coincides with breeding season. Our results suggest that predators might adjust their activity during squirrel breeding season to increase the chance of preying on their offspring. Squirrels in turn could benefit by minimizing the activity overlap during wintertime when they are highly visible to predators as trees are leaf-free or even snow might enhance the contrast between them and their background. Lastly, our results indicate that temporal niche portioning among red squirrel, red fox and martens might be rather fine scaled.
Skill needs for sustainable agri-food and forestry sectors (I): Assessment through European and National Focus Groups
(2022) Mayor, Luis; Lindner, Line F.; Knöbl, Christoph F.; Ramalho, Ana; Berruto, Remigio; Sanna, Francesca; Rossi, Daniele; Tomao, Camilla; Goodburn, Billy; Avila, Concha; Leijdens, Marg; Stollewerk, Katharina; Bregler, Michael; Koidis, Christos; Morin, Alexandre; Miličić, Vesna; Fadini, Giulia; Lazaro-Mojica, Jonas; Busato, Patrizia
The agri-food and forestry sectors are under increasing pressure to adapt to climate change, consumer concern, technological and economic change, and complex global value chains. In turn, such challenges require that the necessary skills and competences are identified at various levels and within specific areas of the sectors. For that purpose, eleven focus groups in nine different EU-countries and two at EU-level were organized within the ERASMUS+ project “FIELDS” with the participation of farmers, cooperatives, agri-food companies, foresters, forest industries, advisors, and education providers to identify the skills needed in the agri-food and forestry sectors. The focus group participants identified business and strategic management skills, communication skills, and other skills related to sustainability, entrepreneurship, digital and soft skills to be most important for the agri-food and forestry sectors as a whole.

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