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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3D-surface MALDI mass spectrometry imaging for visualising plant defensive cardiac glycosides in Asclepias curassavica
(2021) Dreisbach, Domenic; Petschenka, Georg; Spengler, Bernhard; Bhandari, Dhaka R.
Mass spectrometry–based imaging (MSI) has emerged as a promising method for spatial metabolomics in plant science. Several ionisation techniques have shown great potential for the spatially resolved analysis of metabolites in plant tissue. However, limitations in technology and methodology limited the molecular information for irregular 3D surfaces with resolutions on the micrometre scale. Here, we used atmospheric-pressure 3D-surface matrix-assisted laser desorption/ionisation mass spectrometry imaging (3D-surface MALDI MSI) to investigate plant chemical defence at the topographic molecular level for the model system Asclepias curassavica. Upon mechanical damage (simulating herbivore attacks) of native A. curassavica leaves, the surface of the leaves varies up to 700 μm, and cardiac glycosides (cardenolides) and other defence metabolites were exclusively detected in damaged leaf tissue but not in different regions of the same leaf. Our results indicated an increased latex flow rate towards the point of damage leading to an accumulation of defence substances in the affected area. While the concentration of cardiac glycosides showed no differences between 10 and 300 min after wounding, cardiac glycosides decreased after 24 h. The employed autofocusing AP-SMALDI MSI system provides a significant technological advancement for the visualisation of individual molecule species on irregular 3D surfaces such as native plant leaves. Our study demonstrates the enormous potential of this method in the field of plant science including primary metabolism and molecular mechanisms of plant responses to abiotic and biotic stress and symbiotic relationships.
A low-tech approach to mobilize nutrients from organic residues to produce bioponic stock solutions
(2024) Heintze, Sebastian; Beckett, Marc; Kriem, Lukas Simon; Germer, Jörn; Asch, Folkard; Liu, Guodong
Organic residues, as a nutrient source suitable of producing solutions for hydroponic crop production, have the potential to reduce the dependence on mineral fertilizers. Especially in remote and resource-constrained regions, organic residues might be the only option to produce hydroponic nutrient solutions. However, nutrient solutions made from organic residues, called bioponic solutions, are usually unbalanced in their nutrient composition, which leads to deficiencies and poor plant growth. This study aimed to experimentally develop a low-tech approach to produce bioponic stock solutions rich in NO3−, P, and K, to create a balanced bioponic solution. The mixed bioponic solution contained 58 mg L−1 NH4+-N, 43 mg L−1 NO3−-N, 50 mg L−1 PO43−-P, and 246 mg L−1 K+. This approach resulted in satisfactory levels of P, K and micronutrients. The solution was tested pure and spiked with Ca(NO3)2 on lettuce in comparison with a mineral Hoagland nutrient solution. Neither the bioponic nor the spiked bioponic solution achieved comparable lettuce yields to the Hoagland solution. The poor growth of the plants in the bioponic solution was attributed to an unfavorable NH4+:NO3− ratio, high microorganism load, and elevated pH levels. However, the approach of preparing bioponic stock solutions could be promising for future research into the production of balanced bioponic nutrient solutions from organic residues.
The 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.
Analysis of the species spectrum of the Diaporthe/Phomopsis complex in European soybean seeds
(2020) Hosseini, Behnoush; El-Hasan, Abbas; Link, Tobias; Vögele, Ralf
Phytopathogenic fungal species of the Diaporthe/Phomopsis complex (DPC) are associated with three highly destructive diseases on soybean: seed decay, pod and stem blight, and stem canker. They are responsible for poor seed quality and significant yield reduction in most soybean-producing areas. Precise identification and classification of DPC species are important in understanding the epidemiology of disease and to develop effective control measures. Although cultural and morphological characteristics of DPC-associated pathogens have been described, establishing a more accurate taxonomic framework seems necessary for a revaluation of the taxonomy and phylogeny of DPC species. In this study, we focused on morphological and molecular analyses of species from DPC-damaged European soybean seeds obtained from several locations throughout Europe. Colony characteristics, conidia dimensions, existence of α- and β-conidia, and formation of perithecia were evaluated in order to assign the isolates to a species morphologically. Phylogenetic relationships were determined based on sequences from beta-tubulin (TUB), translation elongation factor 1-alpha (TEF1), and nuclear ribosomal DNA internal transcribed spacers (ITS). All isolates were tested for pathogenicity on soybean with positive results. In this study, we present updated taxonomic data by combining morphological observations and molecular tools which placed 32 Diaporthe isolates into four DPC species: D. longicolla, D. caulivora, D. eres, and D. novem, which are well-known soybean pathogens.
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 impacts of crop area expansion and crop-livestock integration on ecosystem functions in African savannas using the coupled LUCIA and LIVSIM models
(2025) Gutai, Benjamin; Marohn, Carsten; Bateki, Christian Adjogo; Asch, Folkard
Large-scale land use change (LUC) of African Guinea savannas to crop fields is expected to cause negative impacts on ecosystem functions (ESF) and long term land productivity. The complex interactions of key processes in savannas evoked by LUC calls for a process-based modelling approach. We employed the dynamically coupled Land Use Change Impact Assessment (LUCIA) model and the Livestock Simulator (LIVSIM) which represent LUC impacts on soil processes, landscape-scale matter fluxes, seasonal grass and crop growth, and livestock nutrition, production and reproduction, depending on seasonal feed availability and quality on accessible pastures. For a rangeland in Borana, Ethiopia, two different LUC scenarios were evaluated in comparison to the baseline of traditional pasture-based land use. In the intensive LUC scenario 52% of grassland was converted into unfertilized maize fields, inaccessible for livestock. The integrated LUC scenario of the same grassland conversion rate allowed feeding maize straw and provided high-quality feed reserves from seasonally managed pastures. LUC in the intensive LUC scenario led to declining yields in the second year after conversion. Feed production on the remaining rangeland patches was insufficient for livestock nutrition, causing drops of herd body weight and herd size particularly in drought years. Resilience of herd performance to LUC was enhanced in the integrated LUC scenario when feeding maize straw and high-quality feed reserves. In both LUC scenarios, topsoil organic carbon storage decreased after ploughing shrub grassland for cultivation, and so did soil water storage capacity due to soil pore destruction. Soil erosion of less than one cm after 10 years occurred under cultivation. The simulation results indicated that the well validated model framework could predict impacts of LUC and simple crop-livestock integration on savanna ESFs, grass growth dynamics and livestock production during seasonal and inter-annual rainfall variation. This study lays the foundation for further land use scenario simulations to improve the understanding of benefits and risks caused by savanna grassland conversion.
Assessing the capability of YOLO- and transformer-based object detectors for real-time weed detection
(2025) Allmendinger, Alicia; Saltık, Ahmet Oğuz; Peteinatos, Gerassimos G.; Stein, Anthony; Gerhards, Roland
Assessing the capability of YOLO- and transformer-based object detectors for real-time weed detection
(2025) Allmendinger, Alicia; Saltık, Ahmet Oğuz; Peteinatos, Gerassimos G.; Stein, Anthony; Gerhards, Roland
Spot spraying represents an efficient and sustainable method for reducing herbicide use in agriculture. Reliable differentiation between crops and weeds, including species-level classification, is essential for real-time application. This study compares state-of-the-art object detection models-YOLOv8, YOLOv9, YOLOv10, and RT-DETR-using 5611 images from 16 plant species. Two datasets were created, dataset 1 with training all 16 species individually and dataset 2 with grouping weeds into monocotyledonous weeds, dicotyledonous weeds, and three chosen crops. Results indicate that all models perform similarly, but YOLOv9s and YOLOv9e, exhibit strong recall (66.58 % and 72.36 %) and mAP50 (73.52 % and 79.86 %), and mAP50-95 (43.82 % and 47.00 %) in dataset 2. RT-DETR-l, excels in precision reaching 82.44 % (dataset 1) and 81.46 % (dataset 2) making it ideal for minimizing false positives. In dataset 2, YOLOv9c attains a precision of 84.76% for dicots and 78.22% recall for Zea mays L.. Inference times highlight smaller YOLO models (YOLOv8n, YOLOv9t, and YOLOv10n) as the fastest, reaching 7.64 ms (dataset 1) on an NVIDIA GeForce RTX 4090 GPU, with CPU inference times increasing significantly. These findings emphasize the trade-off between model size, accuracy, and hardware suitability for real-time agricultural applications.
Assessing the combination efficiency of some unconventional feed resources with concentrates and Chloris gayana grass in mitigating ruminal methane production in vitro
(2024) Melesse, Aberra; Steingass, Herbert; Holstein, Julia; Titze, Natascha; Rodehutscord, Markus
In a preliminary in vitro study, leaves of Acacia nilotica, Prosopis juliflora, Cajanus cajan, Leucaena leucocephala and seed kernel of Mangifera indica were identified as potential candidates in mitigating ruminal methane (CH4) production. The objective of the current study was to investigate the combination efficiency of these unconventional feeds with concentrate mix (CM) or Chloris gayana grass in CH4 reduction. Two feed combinations in different proportions were incubated in vitro with buffered rumen fluid at Hohenheim Gas test. In combination 1, C. gayana and CM were included as basal substrates, while in combination 2, A. nilotica, P. juliflora, C. cajan, L. leucocephala or M. indica seed kernel were included as CH4 reducing supplements at different proportions. The CH4 reducing potentials of feed combinations were presented as the ratio of CH4 to net gas production and expressed as percentage (pCH4). The pCH4 for CM and C. gayana was 16.7% and 16.9%, respectively, while it ranged from 3.18% in A. nilotica to 13.1% in C. cajan. The pCH4 was reduced (p < 0.05) from 14.6% to 9.39% when A. nilotica was combined with CM. In combination of L. leucocephala or C. cajan with CM, the pCH4 (p < 0.05) was reduced from 16.5% and 16.6% with the lowest proportion to 15.1% and 15.2% with the highest inclusion rate respectively. The combination of C. gayana with L. leucocephala or C. cajan reduced (p < 0.05) the pCH4 from 16.3% and 16.4% to 15.1% and 14.9% respectively. The pCH4 was reduced (p < 0.05) from 13.4% to 7.60% when A. nilotica was combined with C. gayana. Estimated digestible organic matter (dOM) and metabolizable energy (ME) increased (p < 0.05) with increasing proportions of M. indica seed kernel with CM or C. gayana. In conclusion, the combination of the basal substrates with unconventional supplements resulted in CH4 reduction without affecting the dOM and ME at lower inclusion rates. Animal‐based experiments await to validate in vitro findings.
Assessment of different methods to determine NH₃ emissions from small field plots after fertilization
(2025) Götze, Hannah; Brokötter, Julian; Frößl, Jonas; Kelsch, Alexander; Kukowski, Sina; Pacholski, Andreas Siegfried; Anderson, William A.
Ammonia (NH₃) emissions affect the environment, climate and human health and originate mainly from agricultural sources like synthetic nitrogen fertilizers. Accurate and replicable measurements of NH₃ emissions are crucial for research, inventories and evaluation of mitigation measures. There exist specific application limitations of NH₃ emission measurement techniques and a high variability in method performance between studies, in particular from small plots. Therefore, the aim of this study was the assessment of measurement methods for ammonia emissions from replicated small plots. Methods were evaluated in 18 trials on six sites in Germany (2021–2022). Urea was applied to winter wheat as an emission source. Two small-plot methods were employed: inverse dispersion modelling (IDM) with atmospheric concentrations obtained from Alpha samplers and the dynamic chamber Dräger tube method (DTM). Cumulative NH₃ losses assessed by each method were compared to the results of the integrated horizontal flux (IHF) method using Alpha samplers (Alpha IHF) as a micrometeorological reference method applied in parallel large-plot trials. For validation, Alpha IHF was also compared to IHF/ZINST with Leuning passive samplers. Cumulative NH₃ emissions assessed using Alpha IHF and DTM showed good agreement, with a relative root mean square error (rRMSE) of 11%. Cumulative emissions assessed by Leuning IHF/ZINST deviated from Alpha IHF, with an rRMSE of 21%. For low-wind-speed and high-temperature conditions, NH3 losses detected with Alpha IDM had to be corrected to give acceptable agreement (rRMSE 20%, MBE +2 kg N ha−1). The study shows that quantification of NH₃ emissions from small plots is feasible. Since DTM is constrained to specific conditions, we recommend Alpha IDM, but the approach needs further development.
Back to the roots: understanding banana below‐ground interactions is crucial for effective management of Fusarium wilt
(2022) Were, Evans; Viljoen, Altus; Rasche, Frank
Global banana production is affected by Fusarium wilt, a devastating disease caused by the soilborne root‐infecting fungus, Fusarium oxysporum f. sp. cubense (Foc). Fusarium wilt is notoriously difficult to manage because infection arises through complex below‐ground interactions between Foc, the plant, and the soil microbiome in the root–soil interface, defined as the rhizosphere. Interactions in the rhizosphere play a pivotal role in processes associated with pathogen development and plant health. Modulation of these processes through manipulation and management of the banana rhizosphere provides an auspicious prospect for management of Fusarium wilt. Yet, a fundamental understanding of interactions in the banana rhizosphere is still lacking. The objective of this review is to discuss the state‐of‐the‐art of the relatively scant data available on banana below‐ground interactions in relation to Fusarium wilt and, as a result, to highlight key research gaps. Specifically, we seek to understand (a) the biology of Foc and its interaction with banana; (b) the ecology of Foc, including the role of root‐exuded metabolites in rhizosphere interactions; and (c) soil management practices and how they modulate Fusarium wilt. A better understanding of molecular and ecological factors influencing banana below‐ground interactions has implications for the development of targeted interventions in the management of Fusarium wilt through manipulation of the banana rhizosphere.
The baobab (Adansonia digitata L.) in Southern Kenya–a study on status, distribution, use and importance in Taita–Taveta County
(2020) Fischer, Sahrah; Jäckering, Lisa; Kehlenbeck, Katja
Baobab (Adansonia digitata L.) is a multipurpose, drought resistant, wild fruit tree, endemic to arid and semi-arid lands of Sub-Saharan Africa. Baobab populations have been showing a lack of regeneration, and therefore causes concern for the species survival. This study investigated the state, distribution and use of baobabs in an under-researched population in Kenya, to identify the potential for further use and development of baobab resources. A baobab population was chosen in Taita–Taveta County, covering a sample area of 2015 km2. A systematic stratified transect survey was done to map baobab distribution using 49 transects (0.5 × 3 km each). The diameter at breast height and other indicators were measured on all baobabs in the transects to assess population status and health. A household survey (n = 46) and focus group discussions (n = 12) were done following the transect survey to gain an idea on the uses and distribution of baobab. In total, 432 baobab trees were measured and recorded in the research area of 2015 km2. The baobabs grew in two clusters (i.e., areas with a baobab density of ≥0.08 baobabs/ha). Both clusters showed rejuvenating populations. The main factors identified by the respondents, positively and negatively influencing baobab distribution were environmental factors, wildlife, human impact and commercial value. The study area shows a great potential for baobab to become an important part of the diet, due to its current use as an emergency food during food scarce times, and the relatively healthy and stable rejuvenating populations.
Bayesian inference of root architectural model parameters from synthetic field data
(2021) Morandage, Shehan; Laloy, Eric; Schnepf, Andrea; Vereecken, Harry; Vanderborght, Jan
Background and aims: Characterizing root system architectures of field-grown crops is challenging as root systems are hidden in the soil. We investigate the possibility of estimating root architecture model parameters from soil core data in a Bayesian framework. Methods: In a synthetic experiment, we simulated wheat root systems in a virtual field plot with the stochastic CRootBox model. We virtually sampled soil cores from this plot to create synthetic measurement data. We used the Markov chain Monte Carlo (MCMC) DREAM(ZS) sampler to estimate the most sensitive root system architecture parameters. To deal with the CRootBox model stochasticity and limited computational resources, we essentially added a stochastic component to the likelihood function, thereby turning the MCMC sampling into a form of approximate Bayesian computation (ABC). Results: A few zero-order root parameters: maximum length, elongation rate, insertion angles, and numbers of zero-order roots, with narrow posterior distributions centered around true parameter values were identifiable from soil core data. Yet other zero-order and higher-order root parameters were not identifiable showing a sizeable posterior uncertainty. Conclusions: Bayesian inference of root architecture parameters from root density profiles is an effective method to extract information about sensitive parameters hidden in these profiles. Equally important, this method also identifies which information about root architecture is lost when root architecture is aggregated in root density profiles.
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.
Breeding progress of nitrogen use efficiency of cereal crops, winter oilseed rape and peas in long-term variety trials
(2024) Laidig, Friedrich; Feike, T.; Lichthardt, C.; Schierholt, A.; Piepho, Hans-Peter
Breeding and registration of improved varieties with high yield, processing quality, disease resistance and nitrogen use efficiency (NUE) are of utmost importance for sustainable crop production to minimize adverse environmental impact and contribute to food security. Based on long-term variety trials of cereals, winter oilseed rape and grain peas tested across a wide range of environmental conditions in Germany, we quantified long-term breeding progress for NUE and related traits. We estimated the genotypic, environmental and genotype-by-environment interaction variation and correlation between traits and derived heritability coefficients. Nitrogen fertilizer application was considerably reduced between 1995 and 2021 in the range of 5.4% for winter wheat and 28.9% for spring wheat while for spring barley it was increased by 20.9%. Despite the apparent nitrogen reduction for most crops, grain yield (GYLD) and nitrogen accumulation in grain (NYLD) was increased or did not significantly decrease. NUE for GYLD increased significantly for all crops between 12.8% and 35.2% and for NYLD between 8% and 20.7%. We further showed that the genotypic rank of varieties for GYLD and NYLD was about equivalent to the genotypic rank of the corresponding traits of NUE, if all varieties in a trial were treated with the same nitrogen rate. Heritability of nitrogen yield was about the same as that of grain yield, suggesting that nitrogen yield should be considered as an additional criterion for variety testing to increase NUE and reduce negative environmental impact.
Can market fragmentation explain the limited success of political attempts to promote grain legume cultivation in Germany?
(2025) Mittag, Franziska; Hess, Sebastian
Grain legumes, such as field peas, field beans, sweet lupins and soybeans, are known to increase biodiversity within the appropriate crop rotation and are an important source of import-substituting feed protein. National and regional policy schemes have long tried to support the cultivation of grain legumes. Although many regions in Germany offer favourable conditions for grain legumes, previous subsidy schemes have failed to increase the area under cultivation and farmers report a lack of market incentives. Indeed, the available price data exhibit a substantial share of non-random missing values in weeks when grain legumes were not traded. We analyse these non-price periods using cointegration tests and single-hurdle Tobit models. The results indicate that regional price formation for grain legumes in German regions depends not only on a minimum quantity of the respective legume crop in supply but also on a favourable supra-regional soybean price: Regional grain legume markets are not integrated and show evidence of a fragmented market structure. This may explain why local grain legume value chains have failed to emerge in Germany, despite decades of policy attempts to support these crops.
The chicken gut microbiome in conventional and alternative production systems
(2025) Cheng, Yu-Chieh; Krieger, Margret; Korves, Anna-Maria; Camarinha‑Silva, Amélia
The poultry gut microbiome plays a key role in nutrient digestion, immune function, and overall health. Differences among various farming systems, including conventional, antibiotic-free, free-range, and organic systems, influence microbial composition and function through variations in diet, genetic selection, environmental exposure, and antibiotic use. Conventional systems typically rely on formulated diets and controlled housing conditions, often with routine antimicrobial use. In contrast, organic systems emphasize natural feed ingredients, including roughage, outdoor access, and strict limitations on the use of antibiotics. These divergent practices shape the gut microbiota differently, with organic systems generally associated with greater exposure to environmental microbes and, consequently, greater microbial diversity. However, the implications of this increased diversity for poultry health and performance are complex, as organic systems may also carry a higher risk of pathogen exposure. This review summarizes current findings on the chicken gut microbiome across conventional and alternative production systems (antibiotic-free, free-range, and organic), focusing on microbial diversity, functional potential, and disease resilience. The need for standardized methodologies and consistent nomenclature in microbiome research is also discussed to improve comparability across studies. Understanding how production systems influence the gut microbiota is essential for improving poultry health and productivity while addressing challenges related to antimicrobial resistance and sustainable farming practices.

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