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.

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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 active core microbiota of two high-yielding laying hen breeds fed with different levels of calcium and phosphorus
(2022) Roth, Christoph; Sims, Tanja; Rodehutscord, Markus; Seifert, Jana; Camarinha-Silva, Amélia
The nutrient availability and supplementation of dietary phosphorus (P) and calcium (Ca) in avian feed, especially in laying hens, plays a vital role in phytase degradation and mineral utilization during the laying phase. The required concentration of P and Ca peaks during the laying phase, and the direct interaction between Ca and P concentration shrinks the availability of both supplements in the feed. Our goal was to characterize the active microbiota of the entire gastrointestinal tract (GIT) (crop, gizzard, duodenum, ileum, caeca), including digesta- and mucosa-associated communities of two contrasting high-yielding breeds of laying hens (Lohmann Brown Classic, LB; Lohmann LSL-Classic, LSL) under different P and Ca supplementation levels. Statistical significances were observed for breed, GIT section, Ca, and the interaction of GIT section x breed, P x Ca, Ca x breed and P x Ca x breed (p < 0.05). A core microbiota of five species was detected in more than 97% of all samples. They were represented by an uncl. Lactobacillus (average relative abundance (av. abu.) 12.1%), Lactobacillus helveticus (av. abu. 10.8%), Megamonas funiformis (av. abu. 6.8%), Ligilactobacillus salivarius (av. abu. 4.5%), and an uncl. Fusicatenibacter (av. abu. 1.1%). Our findings indicated that Ca and P supplementation levels 20% below the recommendation have a minor effect on the microbiota compared to the strong impact of the bird’s genetic background. Moreover, a core active microbiota across the GIT of two high-yielding laying hen breeds was revealed for the first time.
An evaluation of the lineage of Brucella isolates in turkey by a whole-genome single-nucleotide polymorphism analysis
(2024) Akar, Kadir; Holzer, Katharina; Hoelzle, Ludwig E.; Yıldız Öz, Gülseren; Abdelmegid, Shaimaa; Baklan, Emin Ayhan; Eroğlu, Buket; Atıl, Eray; Moustafa, Shawky A.; Wareth, Gamal; Elkhayat, Manar; Pedersen, Karl
Brucellosis is a disease caused by the Brucella ( B. ) species. It is a zoonotic disease that affects farm animals and causes economic losses in many countries worldwide. Brucella has the ability to persist in the environment and infect the host at low doses. Thus, it is more important to trace brucellosis outbreaks, identify their sources of infection, and interrupt their transmission. Some countries already have initial data, but most of these data are based on a Multiple-Locus Variable-Number Tandem-Repeat Analysis (MLVA), which is completely unsuitable for studying the Brucella genome. Since brucellosis is an endemic disease in Turkey, this study aimed to examine the genome of Turkish Brucella isolates collected between 2018 and 2020, except for one isolate, which was from 2012. A total of 28 strains of B. melitensis ( n = 15) and B. abortus ( n = 13) were analyzed using a core-genome single-nucleotide polymorphism (cgSNP) analysis. A potential connection between the Turkish isolates and entries from Sweden, Israel, Syria, Austria, and India for B. melitensis was detected. For B. abortus , there may be potential associations with entries from China. This explains the tight ties found between Brucella strains from neighboring countries and isolates from Turkey. Therefore, it is recommended that strict measures be taken and the possible effects of uncontrolled animal introduction are emphasized.
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.
Bayesian‐optimized experimental designs for estimating the economic optimum nitrogen rate: a model‐averaging approach
(2025) Matavel, Custódio Efraim; Meyer‐Aurich, Andreas; Piepho, Hans‐Peter
Field experiments play a crucial role in optimizing nutrient application strategies and determining the economic optimum nitrogen rate (EONR), aiding stakeholders in agricultural decision‐making. These experiments tailor agricultural input management to maximize efficiency and sustainability, ultimately improving farm economics. However, the optimal setup of field experiments remains an ongoing debate, particularly regarding economic considerations such as the selection of treatment levels (design points), their spatial arrangement, and the number of replications required for statistical validity and cost‐effectiveness. This study optimizes field experiments for estimating the EONR using a model‐averaging approach within a Bayesian framework. We employed Bayesian inference and the No‐U‐turn sampler to integrate model averaging across multiple yield response models, improving robustness in EONR estimation. Stochastic optimization, specifically simultaneous perturbation stochastic approximation, was used to optimize experimental designs, and their performance was evaluated through Monte Carlo simulations. Our results show that optimized experimental designs significantly improve the precision of EONR estimates. Designs incorporating higher number of nitrogen levels provided the best trade‐off between accuracy and efficiency, minimizing bias and mean squared error. Even with a fixed total number of plots (120), increasing the number of design points resulted in lower variance, demonstrating the efficiency of well‐structured experimental designs. This research lays the groundwork for future developments in experimental methodologies with wide‐ranging implications for agricultural economics and policymaking, ultimately supporting better‐informed decision‐making. Future work should integrate environmental constraints and account for real‐world variability in treatment replication to further refine experimental optimization strategies.
Biomonitoring via DNA metabarcoding and light microscopy of bee pollen in rainforest transformation landscapes of Sumatra
(2022) Carneiro de Melo Moura, Carina; Setyaningsih, Christina A.; Li, Kevin; Merk, Miryam Sarah; Schulze, Sonja; Raffiudin, Rika; Grass, Ingo; Behling, Hermann; Tscharntke, Teja; Westphal, Catrin; Gailing, Oliver
Background: Intense conversion of tropical forests into agricultural systems contributes to habitat loss and the decline of ecosystem functions. Plant-pollinator interactions buffer the process of forest fragmentation, ensuring gene flow across isolated patches of forests by pollen transfer. In this study, we identified the composition of pollen grains stored in pot-pollen of stingless bees, Tetragonula laeviceps , via dual-locus DNA metabarcoding (ITS2 and rbcL ) and light microscopy, and compared the taxonomic coverage of pollen sampled in distinct land-use systems categorized in four levels of management intensity (forest, shrub, rubber, and oil palm) for landscape characterization. Results: Plant composition differed significantly between DNA metabarcoding and light microscopy. The overlap in the plant families identified via light microscopy and DNA metabarcoding techniques was low and ranged from 22.6 to 27.8%. Taxonomic assignments showed a dominance of pollen from bee-pollinated plants, including oil-bearing crops such as the introduced species Elaeis guineensis (Arecaceae) as one of the predominant taxa in the pollen samples across all four land-use types. Native plant families Moraceae, Euphorbiaceae, and Cannabaceae appeared in high proportion in the analyzed pollen material. One-way ANOVA (p > 0.05), PERMANOVA (R² values range from 0.14003 to 0.17684, for all tests p-value > 0.5), and NMDS (stress values ranging from 0.1515 to 0.1859) indicated a lack of differentiation between the species composition and diversity of pollen type in the four distinct land-use types, supporting the influx of pollen from adjacent areas. Conclusions: Stingless bees collected pollen from a variety of agricultural crops, weeds, and wild plants. Plant composition detected at the family level from the pollen samples likely reflects the plant composition at the landscape level rather than the plot level. In our study, the plant diversity in pollen from colonies installed in land-use systems with distinct levels of forest transformation was highly homogeneous, reflecting a large influx of pollen transported by stingless bees through distinct land-use types. Dual-locus approach applied in metabarcoding studies and visual pollen identification showed great differences in the detection of the plant community, therefore a combination of both methods is recommended for performing biodiversity assessments via pollen identification.
Breeding progress of disease resistance and impact of disease severity under natural infections in winter wheat variety trials
(2021) Laidig, F.; Feike, T.; Hadasch, S.; Rentel, D.; Klocke, B.; Miedaner, T.; Piepho, H. P.
Key message: Breeding progress of resistance to fungal wheat diseases and impact of disease severity on yield reduction in long-term variety trials under natural infection were estimated by mixed linear regression models. Abstract: This study aimed at quantifying breeding progress achieved in resistance breeding towards varieties with higher yield and lower susceptibility for 6 major diseases, as well as estimating decreasing yields and increasing disease susceptibility of varieties due to ageing effects during the period 1983–2019. A further aim was the prediction of disease-related yield reductions during 2005–2019 by mixed linear regression models using disease severity scores as covariates. For yield and all diseases, overall progress of the fully treated intensity (I2) was considerably higher than for the intensity without fungicides and growth regulators (I1). The disease severity level was considerably reduced during the study period for mildew (MLD), tan spot (DTR) and Septoria nodorum blotch (ear) (SNB) and to a lesser extent for brown (leaf) rust (BNR) and Septoria tritici blotch (STB), however, not for yellow/stripe rust (YLR). Ageing effects increased susceptibility of varieties strongly for BNR and MLD, but were comparatively weak for SNB and DTR. Considerable yield reductions under high disease severity were predicted for STB (−6.6%), BNR (−6.5%) and yellow rust (YLR, −5.8%), but lower reductions for the other diseases. The reduction for resistant vs. highly susceptible varieties under high severity conditions was about halved for BNR and YLR, providing evidence of resistance breeding progress. The empirical evidence on the functional relations between disease severity, variety susceptibility and yield reductions based on a large-scale multiple-disease field trial data set in German winter wheat is an important contribution to the ongoing discussion on fungicide use and its environmental impact.
Climate on the edge: impacts and adaptation in Ethiopia’s agriculture
(2025) Feleke, Hirut Getachew; Amdie, Tesfaye Abebe; Rasche, Frank; Mersha, Sintayehu Yigrem; Brandt, Christian; Younos, Tamim; Lee, Juneseok; Parece, Tammy E.
Climate change poses a significant threat to Ethiopian agriculture, impacting both cereal and livestock production through rising temperatures, erratic rainfall, prolonged droughts, and increased pest and disease outbreaks. These challenges intensify food insecurity, particularly for smallholder farmers and pastoralists who rely on climate-sensitive agricultural systems. This systematic review aims to synthesize the impacts of climate change on Ethiopian agriculture, with a specific focus on cereal production and livestock feed quality, while exploring effective adaptation strategies that can support resilience in the sector. The review synthesizes 50 peer-reviewed publications (2020–2024) from the Climate Change Effects on Food Security project, which supports young African academics and Higher Education Institutions (HEIs) in addressing Sustainable Development Goals (SDGs). Using PRISMA guidelines, the review assesses climate change impacts on major cereal crops and livestock feed in Ethiopia and explores adaptation strategies. Over the past 30 years, Ethiopia has experienced rising temperatures (0.3–0.66 °C), with future projections indicating increases of 0.6–0.8 °C per decade resulting in more frequent and severe droughts, floods, and landslides. These shifts have led to declining yields of wheat, maize, and barley, shrinking arable land, and deteriorating feed quality and water availability, severely affecting livestock health and productivity. The study identifies key on-the-ground adaptation strategies, including adjusted planting dates, crop diversification, drought-tolerant varieties, soil and water conservation, agroforestry, supplemental irrigation, and integrated fertilizer use. Livestock adaptations include improved breeding practices, fodder enhancement using legumes and local browse species, and seasonal climate forecasting. These results have significant practical implications: they offer a robust evidence base for policymakers, extension agents, and development practitioners to design and implement targeted, context-specific adaptation strategies. Moreover, the findings support the integration of climate resilience into national agricultural policies and food security planning. The Climate Change Effects on Food Security project’s role in generating scientific knowledge and fostering interdisciplinary collaboration is vital for building institutional and human capacity to confront climate challenges. Ultimately, this review contributes actionable insights for promoting sustainable, climate-resilient agriculture across Ethiopia.
Combining improved mungbean cultivars with plant growth promoting rhizobacteria inoculation and regulated deficit irrigation to increase crop productivity
(2024) Pataczek, Lisa; Cadisch, Georg
The cultivation of legumes provides an approach to sustainably intensify agricultural production, since short-duration legumes can fit into existing cereal-based cropping systems, diversifying farm incomes and farmers diets, as well as providing environmental benefits through the fixation of atmospheric N2 and, thus, enhancing yields of following crops. Mungbean is a legume, which plays already an important role in the traditional nutrition of people in the Global South. Its nutritious seeds can improve food security and the short growing duration facilitates the diversification of mainly cereal-based crop rotations. However, yields are low and may even become lower in future in the face of climate change. Main constraints of mungbean cultivation include pest and diseases, as well as heat, drought and soil salinity due to inappropriate irrigation techniques or saline ground water. The main aim of this thesis was therefore to analyse the effects of more advanced cultivation techniques, i.e. the use of plant growth promoting rhizobacteria (PGPR) and regulated deficit irrigation (RDI), on the productivity and nitrogen (N) fixation capacity of improved mungbean (Vigna radiata L.) cultivars, resistant and/or tolerant to pests, diseases, heat and soil salinity. An extended literature review was conducted to summarize the current understanding of the use of PGPRs and the effect on crop productivity, especially on marginal land (Chapter 2). The use of PGPRs can on the one hand side increase plant growth through direct and indirect mechanisms, such as BNF, hormone production and nutrient solubilization or the production of antibiotics to suppress phytodiseases. Especially 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity plays a significant role to reduce the negative impact of stress environments. On the other side PGPRs can be used to remediate decontaminated sites, through metabolic capabilities, transforming for instance aromatic compounds into less toxic compounds, or the biodegradation of pesticides and organic pollutants. Since ACC deaminase-producing bacteria are also supposed to enhance root growth, it is assumed that they can potentially increase soil N uptake and/or infection sites for rhizobia to biologically fix atmospheric N2 (BNF). In order to test the effect of ACC deaminase-producing PGPRs on mungbean productivity and N accumulation, three strains were tested as single- or multistrain inoculation in the field: Rhizobium phaseoli, Bacillus subtilis and Pseudomonas fluorescens (Chapter 3). Their effect on one improved mungbean cultivar (NM11, resistant to the Mungbean Yellow Mosaic Disease) was assessed on two research sites in Faisalabad, Pakistan. The impact of the strains differed significantly, with no effect on productivity (total biomass, seed yield) or total N accumulation (BNF and soil-N uptake) with multi-strain inoculation of all strains and single-strain inoculation of P. fluorescens. Inoculation with B. subtilis did, however, result in significantly increased dry matter (roots: +211 kg ha-1, total dry matter: +1.7 t ha-1), and total plant-N (+36 kg ha-1), while R. phaseoli inoculation enhanced BNF (+24%). The results suggested that only the single strain inoculation of B. subtilis and R. phaseoli was promising in terms of productivity increase, however, the choice of the strain should be made according to the soil-N status: low soil-N favors R. phaseoli inoculation, while medium to high soil-N would rather point towards the use of B. subtilis. The improved mungbean cultivar NM11 was additionally tested together with three other improved cultivars (AVMU 1604, AVMU 1635 and KPS2, resistant/tolerant to powdery mildew, bruchids and heat and salt, respectively), in combination with RDI in a greenhouse trial at the University of Hohenheim (Chapter 4). The aim was to identify differences in drought adaptation strategies between the cultivars in terms of dry matter partitioning, yield, harvest index, pod harvest index, water use efficiency and carbon-13 isotope discrimination. Levels of water deficit as depletion fractions (%) of total available soil water were set to 0.45, 0.65 and 0.8, corresponding to recommended irrigation, moderate and severe water deficit, respectively. The cultivars differed in their drought resistance strategies, exhibiting either drought escape, avoidance, tolerance or a combination of several strategies. The cultivar KPS2 showed mainly a drought escape mechanism through faster development, stable yields and greatest harvest index/pod harvest index (36%/69%) across all RDI treatments and cultivars. The cultivar AVMU 1604 displayed mainly a mixture of drought avoidance and escape through increased remobilization of assimilates from vegetative plant parts to pods/seeds, resulting in greater yield under water deficit by 52%. The choice of a cultivar for the field should be based, thus, on the prevailing climatic conditions (season and region): KPS2 can grow in areas with terminate drought conditions, whereas AVMU 1604 can tolerate intermittent drought conditions. The results of this thesis showed that ACC deaminase-producing PGPRs can substantially affect N uptake, although this effect is barely discussed in literature. Moreover, improved mungbean cultivars, exhibiting already a range of tolerances and resistances to certain pests and diseases, showed a great potential in adapting to drought conditions, representing a viable option for cultivation under increasing abiotic and biotic stress factors in the face of climate change.
Composition of the ileum microbiota is a mediator between the host genome and phosphorus utilization and other efficiency traits in Japanese quail (Coturnix japonica)
(2022) Haas, Valentin; Vollmar, Solveig; Preuß, Siegfried; Rodehutscord, Markus; Camarinha-Silva, Amélia; Bennewitz, Jörn
Background: Phosphorus is an essential nutrient in all living organisms and, currently, it is the focus of much attention due to its global scarcity, the environmental impact of phosphorus from excreta, and its low digestibility due to its storage in the form of phytates in plants. In poultry, phosphorus utilization is influenced by composition of the ileum microbiota and host genetics. In our study, we analyzed the impact of host genetics on composition of the ileum microbiota and the relationship of the relative abundance of ileal bacterial genera with phosphorus utilization and related quantitative traits in Japanese quail. An F2 cross of 758 quails was genotyped with 4k genome-wide single nucleotide polymorphisms (SNPs) and composition of the ileum microbiota was characterized using target amplicon sequencing. Heritabilities of the relative abundance of bacterial genera were estimated and quantitative trait locus (QTL) linkage mapping for the host was conducted for the heritable genera. Phenotypic and genetic correlations and recursive relationships between bacterial genera and quantitative traits were estimated using structural equation models. A genomic best linear unbiased prediction (GBLUP) and microbial (M)BLUP hologenomic selection approach was applied to assess the feasibility of breeding for improved phosphorus utilization based on the host genome and the heritable part of composition of the ileum microbiota. Results: Among the 59 bacterial genera examined, 24 showed a significant heritability (nominal p ≤ 0.05), ranging from 0.04 to 0.17. For these genera, six genome-wide significant QTL were mapped. Significant recursive effects were found, which support the indirect host genetic effects on the host’s quantitative traits via microbiota composition in the ileum of quail. Cross-validated microbial and genomic prediction accuracies confirmed the strong impact of microbial composition and host genetics on the host’s quantitative traits, as the GBLUP accuracies based on the heritable microbiota-mediated components of the traits were similar to the accuracies of conventional GBLUP based on genome-wide SNPs. Conclusions: Our results revealed a significant effect of host genetics on composition of the ileal microbiota and confirmed that host genetics and composition of the ileum microbiota have an impact on the host’s quantitative traits. This offers the possibility to breed for improved phosphorus utilization based on the host genome and the heritable part of composition of the ileum microbiota.
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.
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.
Diacetoxyscirpenol, a Fusarium exometabolite, prevents efficiently the incidence of the parasitic weed Striga hermonthica
(2022) Anteyi, Williams Oyifioda; Klaiber, Iris; Rasche, Frank
Background: Certain Fusarium exometabolites have been reported to inhibit seed germination of the cereal-parasitizing witchweed, Striga hermonthica , in vitro . However, it is unknown if these exometabolites will consistently prevent S. hermonthica incidence in planta . The study screened a selection of known, highly phytotoxic Fusarium exometabolites, in identifying the most potent/efficient candidate (i.e., having the greatest effect at minimal concentration) to completely hinder S. hermonthica seed germination in vitro and incidence in planta , without affecting the host crop development and yield. Results: In vitro germination assays of the tested Fusarium exometabolites (i.e., 1,4-naphthoquinone, equisetin, fusaric acid, hymeglusin, neosolaniol (Neo), T-2 toxin (T-2) and diacetoxyscirpenol (DAS)) as pre- Striga seed conditioning treatments at 1, 5, 10, 20, 50 and 100 µM, revealed that only DAS, out of all tested exometabolites, completely inhibited S. hermonthica seed germination at each concentration. It was followed by T-2 and Neo, as from 10 to 20 µM respectively. The remaining exometabolites reduced S. hermonthica seed germination as from 20 µM ( P < 0. 0001). In planta assessment (in a S. hermonthica -sorghum parasitic system) of the exometabolites at 20 µM showed that, although, none of the tested exometabolites affected sorghum aboveground dry biomass ( P > 0.05), only DAS completely prevented S. hermonthica incidence. Following a 14-d incubation of DAS in the planting soil substrate, bacterial 16S ribosomal RNA (rRNA) and fungal 18S rRNA gene copy numbers of the soil microbial community were enhanced; which coincided with complete degradation of DAS in the substrate. Metabolic footprinting revealed that the S. hermonthica mycoherbicidal agent, Fusarium oxysporum f. sp. strigae (isolates Foxy-2, FK3), did not produce DAS; a discovery that corresponded with underexpression of key genes (Tri5, Tri4) necessary for Fusarium trichothecene biosynthesis ( P < 0.0001). Conclusions: Among the tested Fusarium exometabolites, DAS exhibited the most promising herbicidal potential against S. hermonthica . Thus, it could serve as a new biocontrol agent for efficient S. hermonthica management. Further examination of DAS specific mode of action against the target weed S. hermonthica at low concentrations (≤ 20 µM), as opposed to non-target soil organisms, is required.
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.
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
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.
Do lower nitrogen fertilization levels require breeding of different types of cultivars in triticale?
(2022) Neuweiler, Jan E.; Trini, Johannes; Maurer, Hans Peter; Würschum, Tobias
Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.
Do we need post-tree thinning management? Prescribed fire and goat browsing to control woody encroacher species in an Ethiopian savanna
(2024) Abate, Teshome; Abebe, Tesfaye; Treydte, Anna
Worldwide, bush encroachment threatens rangeland ecosystem services, including plant biodiversity and forage for livestock. Various control methods for encroaching woody species and restoring herbaceous vegetation exist but have rarely been explored experimentally. We assessed the impact of post-tree thinning management on tree mortality, the herbaceous community, and overall rangeland condition in Borana, an Ethiopian savanna ecosystem. At two 1.4 ha areas of encroached mono-specific Vachellia drepanolobium (whistling thorn) stands, we set up twenty-four 20 × 10 m experimental plots with four post-tree-thinning treatments (goat browsing only (1), prescribed fire (2), fire and goat browsing (3), and control (4) (i.e., no management after tree cutting), with three replications in a complete block design. Over two growing periods, we monitored resulting tree mortality, coppicing, seedling mortality and recruitment, as well as herbaceous layer attributes (diversity, biomass) and overall rangeland condition. All three post-tree thinning management scenarios significantly enhanced tree mortalities, reduced seedling recruitment and increased the abundance of the dominant desirable grass species. Prescribed fire and fire and goat-browsing treatments resulted in significantly greater grass and forb species richness, forb diversity, and biomass, as well as the overall rangeland condition compared to goat browsing only and the control treatment. However, grass species diversity did not respond to treatments. Post-tree management significantly increased tree mortality, reduced seedling recruitment, and increased the abundance of desirable grass species. Our findings strongly suggest that post-thinning management, particularly prescribed fire or a combination of fire and browsing, is highly effective in suppressing woody encroachment and improving biomass and overall rangeland condition.
Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material
(2021) Galán, Rodrigo José; Bernal-Vasquez, Angela-Maria; Jebsen, Christian; Piepho, Hans-Peter; Thorwarth, Patrick; Steffan, Philipp; Gordillo, Andres; Miedaner, Thomas
Key message: Hyperspectral data is a promising complement to genomic data to predict biomass under scenarios of low genetic relatedness. Sufficient environmental connectivity between data used for model training and validation is required. Abstract: The demand for sustainable sources of biomass is increasing worldwide. The early prediction of biomass via indirect selection of dry matter yield (DMY) based on hyperspectral and/or genomic prediction is crucial to affordably untap the potential of winter rye (Secale cereale L.) as a dual-purpose crop. However, this estimation involves multiple genetic backgrounds and genetic relatedness is a crucial factor in genomic selection (GS). To assess the prospect of prediction using reflectance data as a suitable complement to GS for biomass breeding, the influence of trait heritability ( ) and genetic relatedness were compared. Models were based on genomic (GBLUP) and hyperspectral reflectance-derived (HBLUP) relationship matrices to predict DMY and other biomass-related traits such as dry matter content (DMC) and fresh matter yield (FMY). For this, 270 elite rye lines from nine interconnected bi-parental families were genotyped using a 10 k-SNP array and phenotyped as testcrosses at four locations in two years (eight environments). From 400 discrete narrow bands (410 nm–993 nm) collected by an uncrewed aerial vehicle (UAV) on two dates in each environment, 32 hyperspectral bands previously selected by Lasso were incorporated into a prediction model. HBLUP showed higher prediction abilities (0.41 – 0.61) than GBLUP (0.14 – 0.28) under a decreased genetic relationship, especially for mid-heritable traits (FMY and DMY), suggesting that HBLUP is much less affected by relatedness and . However, the predictive power of both models was largely affected by environmental variances. Prediction abilities for DMY were further enhanced (up to 20%) by integrating both matrices and plant height into a bivariate model. Thus, data derived from high-throughput phenotyping emerges as a suitable strategy to efficiently leverage selection gains in biomass rye breeding; however, sufficient environmental connectivity is needed.

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