Institut für Kulturpflanzenwissenschaften

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Correction to: Assessing the efficiency and heritability of blocked tree breeding trials
(2024) Piepho, Hans-Peter; Williams, Emlyn; Prus, Maryna
Assessing the efficiency and heritability of blocked tree breeding trials
(2024) Piepho, Hans-Peter; Williams, Emlyn; Prus, Maryna
Progeny trials in tree breeding are often laid out using blocked experimental designs, in which families are randomly assigned to plots and several trees are planted per plot. Such designs are optimized for the assessment of family effects. However, tree breeders are primarily interested in assessing breeding values of individual trees. This paper considers the assessment of heritability at both the family and tree levels. We assess heritability based on pairwise comparisons among individual trees. The approach shows that there is considerable heterogeneity in pairwise heritabilities, primarily due to the differences in both genetic as well as error variances among within- and between-family comparisons. Our results further show that efficient blocking positively affects all types of comparison except those among trees within the same plot.
To move or not to move—factors influencing small-scale herder and livestock movements in the Dzungarian Gobi, Mongolia
(2023) Michler, Lena M.; Kaczensky, Petra; Oyunsaikhan, Ganbaatar; Bartzke, Gundula S.; Devineau, Olivier; Treydte, Anna C.
In Mongolia, where nomadic pastoralism is still practiced by around one-third of the population, increasing livestock numbers, socio-economic constraints and climate change raise concerns over rangeland health. Little empirical evidence explains what triggers camp moves of pastoralists in the Dzungarian Gobi in Mongolia, which factors influence grazing mobility around camps, and how altitudinal migration benefits small livestock. We combined GPS tracking data of 19 small livestock herds monitored from September 2018 to April 2020 with remotely sensed climate and environmental data. We used general linear-mixed models to analyse variables influencing camp use duration and daily mobility patterns. To understand the importance of the altitudinal migration, we compared climatic conditions along the elevation gradient and looked at seasonal body weight changes of small livestock. We found that available plant biomass and season best explained camp use duration. Daily walking distance and maximum distance from camp increased with camp use duration. Pasture time increased with increasing biomass and rising temperatures. We conclude that herders in the Dzungarian Gobi have optimized pasture use by reacting to changes in biomass availability at landscape and local scale, and by embracing altitudinal migration. Flexibility in grazing mobility seems to have enabled local herder communities to practise sustainable pasture use. Maintaining this mobility will most likely be the best strategy to deal with environmental change under the current climate change scenarios.
Effect of phosphorus fertilizer placement depth, amount, and soil water content on early maize growth
(2025) Ning, Fangfang; Nkebiwe, Peteh Mehdi; Munz, Sebastian; Hartung, Jens; Zhang, Ping; Huang, Shoubing; Graeff‐Hönninger, Simone; Ning, Fangfang; Department of Agronomy (340a), Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Nkebiwe, Peteh Mehdi; Department of Fertilization and Soil Matter Dynamics (340i), Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Munz, Sebastian; Department of Agronomy (340a), Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Hartung, Jens; Biostatistics Unit (340c), Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Zhang, Ping; Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang, China; Huang, Shoubing; College of Agronomy and Biotechnology, China Agricultural University, Beijing, China; Graeff‐Hönninger, Simone; Department of Agronomy (340a), Institute of Crop Science, University of Hohenheim, Stuttgart, Germany
Background: Drought stress (DS) reduces soil phosphorus (P) availability by limiting P diffusion and uptake, while global P resource scarcity exacerbates nutrient limitations for crops. Aim: This study investigated whether deep subsurface P placement could alleviate the combined effects of P deficiency and DS on maize growth. Methods: A greenhouse trial with maize (cv. Ricardinio) was conducted involving three factors: three P fertilizer amounts (0 mg P pot −1 [NP], 109 mg P pot −1 [LP], and 655 mg P pot −1 [HP]), three placement depths (0–9 cm [U, upper layer], 9–18 cm [L, lower layer], and uniformly mixed throughout 0–18 cm [M]), and two soil water contents (45% of soil water holding capacity [WHC] [DS] and 75% WHC [WW]). Root and shoot traits were assessed at the fourth‐ and tenth‐leaf stages. Results: LP significantly reduced shoot biomass and P content compared to HP treatment. At the fourth‐leaf stage, DS increased root biomass by 69.3% and 27.1% in the 9–18 cm and 0–18 cm layers compared to WW treatment. At the tenth‐leaf stage, DS reduced root biomass by at least 41% across layers and decreased shoot growth and P uptake. Under DS, L‐DS increased root growth and root length in the 9–18 cm layer compared to M‐DS and U‐DS treatments but did not improve shoot traits. Conclusion: Deep subsurface P placement promoted deeper root development under drought and P deficiency. However, its benefits on shoot growth were not evident in early stages, indicating the need for longer term field validation.
Optimizing mung bean productivity and root morphology with biofertilizers for sustainable farming
(2025) Nabati, Jaafar; Mirzaeetalarposhti, Reza; Yousefi, Afsaneh; Kurdestani, Ali Malakshahi; Nabati, Jaafar; Department of Agrotechnology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran; Mirzaeetalarposhti, Reza; Institute of Crop Science, University of Hohenheim, 70599, Stuttgart, Germany
The excessive use of chemical fertilizers has raised major environmental and economic concerns in legume cultivation. This study assessed the effects of various fertilizers, including biofertilizers and chemical nitrogen, on yield, root characteristics, and nutrient dynamics in two mung bean genotypes (Partow, IC418452). Field trials were conducted over a two-year period in Mashhad, Iran, using a factorial randomized block design. Treatments included two genotypes and six fertilizer levels: control, N-fixing bacteria (FLNF), P-solubilizing bacteria (PSB), K-solubilizing bacteria (KSB), a consortium (FLNF + PSB + KSB), and Urea. Yield components, biomass, root morphology, nodulation, and plant/soil NPK concentrations were measured and analyzed. Fertilizers significantly affected yield, biomass, root structure, and nutrient uptake. Urea yielded the highest biomass, grain yield, and root area, especially in Partow. However, the microbial consortium significantly improved yield components compared to the control and uniquely maximized root nodulation and inoculation percentage, indicating an enhanced biological nitrogen fixation potential. On average across the two seasons, urea increased grain yield by 46% and biomass by 41% relative to the control, whereas the microbial consortium enhanced root nodulation by 62% and yield by 32%. Significant genotype×fertilizer interactions highlighted genotype-specific responses. Nodulation correlated positively with yield. Both urea and the PGPR consortium significantly increased mung bean productivity. While urea maximized yield, the consortium provided considerable yield gains and enhanced biological nitrogen fixation potential, presenting a viable and sustainable alternative to reduce reliance on chemical nitrogen. The goal was to understand the relationships between root morphology, nutrient utilization, and yield to promote sustainable, high-yield mung bean cultivation. These findings highlight the potential of multi-strain biofertilizers to maintain mung-bean productivity while reducing dependence on synthetic N inputs.
Miscanthus‐derived products for material applications: can they contribute to greenhouse gas emission mitigation?
(2025) Lask, Jan; Weik, Jan; Kiesel, Andreas; Lewandowski, Iris; Wagner, Moritz; Lask, Jan; Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Weik, Jan; Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Kiesel, Andreas; Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Lewandowski, Iris; Institute of Crop Science, University of Hohenheim, Stuttgart, Germany; Wagner, Moritz; Institute of Applied Ecology, Geisenheim University, Geisenheim, Germany
Miscanthus is a particularly promising lignocellulosic biomass as it can also grow under marginal conditions and can be used for a wide range of products including energy and material applications. The latter, including applications in the construction, textile, chemical, or agricultural sector, is becoming increasingly relevant today. In general, it is hypothesised that biobased products are advantageous in terms of their greenhouse gas (GHG) performance when compared to conventional—in particular fossil—alternatives. To investigate this, the life cycle assessment methodology is typically applied. However, assessments are subject to uncertainty and variability due to assumptions and methodological choices. Given the increasing interest in miscanthus‐derived material applications, this study aims to draw more general conclusions about their GHG performance and relative mitigation potential. This should support a better understanding of their contribution to climate change mitigation objectives and guide the selection of promising products or product groups. A systematic review of peer‐reviewed literature was conducted. In total, 20 studies reporting on 188 comparisons of the GHG performance of miscanthus‐derived and alternative products were assessed. Most comparisons indicated potential GHG mitigation through miscanthus‐derived products, with the majority ranging between 20% and 100% savings. Key parameters defining the relative performance include the selection of the reference product, consideration of soil carbon changes, changes in product and process design, as well as the incorporation of indirect Land Use Change (iLUC) impacts. Overall, we conclude that miscanthus‐derived material applications have the potential to contribute to GHG emission mitigation if iLUC effects are minimised. Given the limited availability of agricultural land, miscanthus‐derived products with high absolute GHG mitigation potential per unit of biomass used and long product lifetime are preferable. For future development, potential environmental trade‐offs need to be monitored.
Viroid ecology in hops (Humulus lupulus L.): high prevalence in commercial systems but low presence in wild populations
(2026) Jagani, Swati; Krönauer, Christina; Born, Ute; Hagemann, Michael Helmut; Jagani, Swati; Department of Production Systems of Horticultural Crops, University of Hohenheim, Stuttgart, Germany; Krönauer, Christina; Bavarian State Research Center for Agriculture, Institute for Crop Science and Plant Breeding, Wolnzach, Germany; Born, Ute; Department of Production Systems of Horticultural Crops, University of Hohenheim, Stuttgart, Germany; Hagemann, Michael Helmut; Department of Production Systems of Horticultural Crops, University of Hohenheim, Stuttgart, Germany
Introduction: Hop (Humulus lupulus L.), a vital crop in the brewing industry, is increasingly threatened by infections caused by viroids and viruses. The extensive use of vegetative propagation in hop cultivation facilitates the accumulation and dissemination of these pathogens. However, little is known about their prevalence and ecological behavior in non-commercial settings. This study provides a comprehensive overview of viroid and virus infections across Germany, with particular attention to their occurrence and potential transmission across commercial, settlement, and wild hop populations. Methods: Between 2020 and 2023, 418 hop leaf samples from commercial (n = 345), settlement (n = 29), and wild (n = 44) populations were collected. Viroid and virus detection was performed using RT-PCR and PCR. To investigate possible cross-species transmission and sequence variation, HSVd-positive samples from hops and nearby grapevines were further analyzed via Sanger sequencing. Results: Viroid screening revealed that the citrus bark cracking viroid (CBCVd; Cocadviroid rimocitri) was confined to commercial hop cultivation. This study also marks the first confirmed detection of hop stunt viroid (HSVd; Hostuviroid impedihumuli) in commercial hop fields in Germany. Virus screening showed that hop latent virus (HpLV; Carlavirus latenshumuli) and american hop latent virus (AHpLV; Carlavirus americanense) were exclusively found in commercial hops. Hop mosaic virus (HpMV; Carlavirus humuli) was detected across all three groups—commercial, settlement, and wild populations. Arabis mosaic virus (ArMV; Nepovirus arabis) and apple mosaic virus (ApMV; Ilarvirus ApMV) were identified in both commercial and wild hops but were absent from settlement samples. Overall, commercial hop populations exhibited the highest pathogen burden, frequently harboring multiple viroid and virus infections. These findings underscore the importance of using certified, pathogen-free planting material, implementing early detection strategies, and updating plant passport regulations to include high-risk pathogens. While prevalence estimates reflect risk-based sampling from key production regions, the study provides a solid basis for enhancing pathogen surveillance and improving preventive measures in hop cultivation.
Operational principles for fostering transformative qualities and capacities in higher education sustainability science and practice
(2026) Fagerholm, Nora; Coles, Neil; Beery, Thomas; Torralba, Mario; Hakkarainen, Viola; Albert, Christian; Andersson, Erik; Bergström, Ryan; Bieling, Claudia; Gentin, Sandra; Klonner, Carolin; Olafsson, Anton Stahl; Raymond, Christopher; Rouhiainen, Henna; Wamsler, Christine; Fagerholm, Nora; Department of Geography and Geology, University of Turku, 20114, Turku, Finland; Coles, Neil; Institute of Agriculture, The University of Western Australia, Crawley, 6009, Perth, WA, Australia; Beery, Thomas; Sustainable Multifunctional Landscapes Research Group, Kristianstad University, Kristianstad, Sweden; Torralba, Mario; Environmental Geography Group, IVM Institute for Environmental Studies, VU University Amsterdam, Amsterdam, The Netherlands; Hakkarainen, Viola; Faculty of Sustainability, Leuphana University Lüneburg, Lüneburg, Germany; Albert, Christian; Institute of Environmental Planning, Leibniz University Hannover, Herrenhaeuser Str. 2, 30419, Hannover, Germany; Andersson, Erik; Ecosystems and Environment Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, 00014, Helsinki, Finland; Bergström, Ryan; Sustainable Multifunctional Landscapes Research Group, Kristianstad University, Kristianstad, Sweden; Bieling, Claudia; Division Societal Transition and Agriculture (430B), Institute of Social Sciences in Agriculture, University of Hohenheim, Stuttgart, Germany; Gentin, Sandra; Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark; Klonner, Carolin; Department of Geography and Geology, University of Turku, 20114, Turku, Finland; Stahl Olafsson, Anton; Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark; Raymond, Christopher; Ecosystems and Environment Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, 00014, Helsinki, Finland; Rouhiainen, Henna; Biodiversity Unit, University of Turku, Turku, Finland; Wamsler, Christine; Lund University Centre for Sustainability Studies (LUCSUS), Lund, Sweden
Education for sustainability is widely recognised as a critical pathway for driving the transformations needed to address today’s polycrisis. Despite growing theoretical and conceptual advancements in sustainability education, current approaches have not achieved the deep systemic changes required. While university networks and individual institutions increasingly integrate sustainability into their education, concerns persist that transformative learning agendas often remain superficial. In particular, they frequently fail to equip learners with the emotional resilience and skills necessary to engage effectively with complex global challenges, as well as educators with the pedagogical framework to facilitate such learning. This article emphasises the need to advance transformative learning in sustainability science and practice in higher education by addressing the inner dimensions of sustainability: our individual and collective values, beliefs, worldviews, and associated transformative qualities and capacities. This means targeting deep leverage points and meaningful change by supporting more relational approaches, including an integrated inner–outer change in being, thinking, and acting. We provide seven operational principles for supporting the inner–outer transformation towards sustainability in learning and teaching sustainability science and practice, especially in geography and related fields. These principles highlight the importance of nurturing five clusters of transformative qualities and capacities—awareness, connection, insight, purpose, and agency—guided by relational approaches required to support profound and integrative learning experiences. We provide concrete examples of how to implement these principles. The proposed principles aim to inspire educators and learners to deeply engage with sustainability challenges to contribute to transformative change across individual, collective, and system levels.
Impact of different growing substrates on growth, yield and cannabinoid content of two Cannabis sativa L. genotypes in a pot culture
(2020) Burgel, Lisa; Hartung, Jens; Graeff-Hönninger, Simone
The impacts of different growing substrate compositions, consisting of peat (PM), peat substituted with 30% green fibre (G30) and coco coir fibre (CC) growth media, were investigated in regard to the plant height, biomass and floral yield, biomass nitrogen (N) content, root growth, and cannabidiol content (CBD/A) of two phytocannabinoid-rich cannabis genotypes in an indoor pot cultivation system. Genotypes and substrate treatment combinations were randomly allocated to 36 plants according to a Latin square design. The results showed a higher total plant height for PM (39.96 cm), followed by G30 (35.28 cm), and the lowest in CC (31.54 cm). The N content of leaves indicated the highest values for plants grown in G30 (52.24 g kg DW−1), followed by PM (46.75 g kg DW−1) and a significantly lower content for CC (37.00 g kg DW−1). Root length density (RLD) increased by 40% (PM) and 50% (G30), compared to CC treatments, with no significant differences in root dry weight. Both genotypes, Kanada (KAN) and 0.2x, reacted in a genotype-specific manner. KAN indicated a reduced floral yield of plants grown in G30 (4.94 g plant−1) and CC (3.84 g plant−1) compared to PM (8.56 g plant−1). 0.2x indicated stable high floral yields of 9.19 g plant−1 (G30) to 7.90 g plant−1 (CC). Leaf DW increased in PM (5.78 g plant−1) and G30 (5.66 g plant−1) compared to CC (3.30 g plant−1), while CBD/A content remained constant. Due to a higher biomass yield, the CBD/A yield of flowers (549.66 mg plant−1) and leaves (224.16 mg plant−1) revealed 0.2x as an interesting genotype for indoor pot cultivation in a peat-based substrate substituted with 30% green fibres. Overall, the demand for organic green fibres to partly replace fractionated peat showed a genotype-specific option for a homogeneous plant development, with comparable high biomass yields and stable cannabinoid contents compared to a peat containing standard substrate.
Towards more nuanced narratives in bioeconomy strategies and policy documents to support knowledge-driven sustainability transitions
(2025) Stoye, Juliane; Schlaile, Michael P.; von Cossel, Moritz; Bertacchi, Stefano; Escórcio, Rita; Winkler, Bastian; Curran, Thomas P.; Ní Chléirigh, Laoise; Nic an Bhaird, Máire; Klakla, Jan Bazyli; Nachtergaele, Pieter; Ciantar, Hailey; Scheurich, Philipp; Lewandowski, Iris; Reinmuth, Evelyn; Hopmans, Jan
The bioeconomy has been discussed as a key strategy for addressing sustainability challenges, particularly regarding the transition from fossil-based to bio-based systems, in numerous national and supranational strategies and policy documents related to the bioeconomy. However, public understanding of and engagement with the bioeconomy remains limited. This is partly due to the bias of many bioeconomy strategies and policy documents towards technological solutions that tend to overlook the social, normative, and transformative dimensions of systemic change as well as the necessary knowledge. This opinion paper explores the potential of narratives as a means of communicating bioeconomy research in public policy, with the aim of addressing the communication gap between science, policy, and society. When applied in responsible and nuanced ways that acknowledge their embeddedness and context, bioeconomy (policy) narratives can support sensemaking for science communication, improve public understanding, facilitate stakeholder engagement and behavioural change. We argue that such narrative approaches can help to create narrative ‘boundary objects’ that can support more inclusive and participatory processes, enabling the co-creation of transformative knowledge for bioeconomy transitions with stakeholders as active participants. In summary, we highlight several opportunities, as well as limitations and implications, that could inform future work on bioeconomy narratives.
Deviation from the regression of yield on nitrogen fertiliser rate as a tool for detecting fraud in organic banana production
(2025) Benzing, Albrecht; Piepho, Hans‐Peter; Orr, Ryan; Ullauri, Juan‐Carlos
Background and aims: Bananas are demanding in nitrogen (N) input; therefore, there is a temptation for organic farmers for using synthetic N fertilisers, which are not allowed under organic standards. The aim of our study was to develop a tool that identifies high banana yields obtained with suspiciously low organic N input. Methods: We systematically reviewed literature from experimental studies on N fertilisation in bananas from all over the world. We also developed a simplified N balance model for organic bananas. Furthermore, N fertilisation and banana yield data from organic and conventional farmers in different countries were collected. From these, a subset of trustworthy organic farms was identified, as a reference concerning plausible ratios of yield versus fertilisation. A model was developed to estimate the deviation from the regression of trustworthy farms and thus identify suspicious cases. Results: Neither literature nor the N balance led to a meaningful benchmark for differentiating plausible from non‐plausible yields. The regression of yield on N fertiliser rate from the trustworthy organic farmers, however, turned out to be a helpful reference, and the deviation from this regression helps to achieve our aim. Depending on the alert limit, that is, the probability of obtaining false positive results, 4, 6, or 9 out of 157 data‐pairs from organic farmers turned out to be suspicious. Conclusion: Measuring deviation from the regression of the trustworthy farms is a useful tool for identifying organic banana farmers suspected to be using synthetic N fertilisers but is not in itself a proof of fraud. The model will improve as more data becomes available.
How equal space seeding in maize (Zea mays L.) influences weed competition, crop growth, and grain yield
(2025) Naruhn, Georg‐Peter; Hartung, Jens; Schulz, Vanessa; Möller, Kurt; Gerhards, Roland
The increase in herbicide‐resistant weeds and new political guidelines force farmers to change their weed management strategies while reducing herbicides. Current study aimed to explore the potential of equal space seeding (ESS) in maize ( Zea mays L.) compared to conventional row seeding (CRS) regarding weed suppression and crop development. A multisite experiment was carried out in 2022 in southwestern Germany comparing ESS and CRS by pooling the data of three treatments (untreated, herbicide, and hoeing) of each system. The parameters leaf area index (LAI), photosynthetic active radiation (PAR), maize and weed biomass, and grain yield were measured. The ESS was neither statistically different in terms of LAI and PAR absorption nor did it show a higher weed suppression due to a reduced weed biomass compared to CRS. Although two of three trials also showed no differences between both systems in grain yield, the experiment with the lowest rainfall and irrigation amount as well as the evaluation across all three sites showed a significant increase in yield from ESS (5.72 Mg ha −1 ) compared to CRS (3.77 Mg ha −1 ). It was assumed that a reduced intraspecific competition, a slightly higher PAR absorption during maize flowering, and an improved root growth contributed to the higher yields in the ESS system. For more evidence as well as for a reliable recommendation for a specific cropping system, further studies in different environments are needed.
Bird species richness and diversity responses to land use change in the Lake Victoria Basin, Kenya
(2024) Mugatha, Simon M.; Ogutu, Joseph O.; Piepho, Hans-Peter; Maitima, Joseph M.
The increasing demand for cultivated lands driven by human population growth, escalating consumption and activities, combined with the vast area of uncultivated land, highlight the pressing need to better understand the biodiversity conservation implications of land use change in Sub-Saharan Africa. Land use change alters natural wildlife habitats with fundamental consequences for biodiversity. Consequently, species richness and diversity typically decline as land use changes from natural to disturbed. We assess how richness and diversity of avian species, grouped into feeding guilds, responded to land use changes, primarily expansion of settlements and cultivation at three sites in the Lake Victoria Basin in western Kenya, following tsetse control interventions. Each site consisted of a matched pair of spatially adjacent natural/semi-natural and settled/cultivated landscapes. Significant changes occurred in bird species richness and diversity in the disturbed relative to the natural landscape. Disturbed areas had fewer guilds and all guilds in disturbed areas also occurred in natural areas. Guilds had significantly more species in natural than in disturbed areas. The insectivore/granivore and insectivore/wax feeder guilds occurred only in natural areas. Whilst species diversity was far lower, a few species of estrildid finches were more common in the disturbed landscapes and were often observed on the scrubby edges of modified habitats. In contrast, the natural and less disturbed wooded areas had relatively fewer estrildid species and were completely devoid of several other species. In aggregate, land use changes significantly reduced bird species richness and diversity on the disturbed landscapes regardless of their breeding range size or foraging style (migratory or non-migratory) and posed greater risks to non-migratory species. Accordingly, land use planning should integrate conservation principles that preserve salient habitat qualities required by different bird species, such as adequate patch size and habitat connectivity, conserve viable bird populations and restore degraded habitats to alleviate adverse impacts of land use change on avian species richness and diversity.
Hierarchical modelling of variance components makes analysis of resolvable incomplete block designs more efficient
(2024) Studnicki, Marcin; Piepho, Hans Peter
The standard approach to variance component estimation in linear mixed models for alpha designs is the residual maximum likelihood (REML) method. One drawback of the REML method in the context of incomplete block designs is that the block variance may be estimated as zero, which can compromise the recovery of inter-block information and hence reduce the accuracy of treatment effects estimation. Due to the development of statistical and computational methods, there is an increasing interest in adopting hierarchical approaches to analysis. In order to increase the precision of the analysis of individual trials laid out as alpha designs, we here make a proposal to create an objectively informed prior distribution for variance components for replicates, blocks and plots, based on the results of previous (historical) trials. We propose different modelling approaches for the prior distributions and evaluate the effectiveness of the hierarchical approach compared to the REML method, which is classically used for analysing individual trials in two-stage approaches for multi-environment trials.
Mapping knowledge domains of regenerative agriculture with a focus on on-farm nitrogen fertilization experimentation and response surface regression
(2025) Abdipourchenarestansofla, Morteza; Piepho, Hans-Peter
In the face of growing environmental concerns and the global demand for sustainable agriculture, achieving balanced nitrogen (N) management is critical for both maximizing crop productivity and maintaining environmental health. This dissertation proposes an innovative framework to address this challenge within the scope of regenerative agriculture, which emphasizes sustainable farming practices. Regenerative agriculture aims to reduce chemical inputs while maintaining yield levels yet implementing these practices at scale is complex due to the intricate interactions between biological, environmental, and technological factors on farms. This research tackles these challenges by introducing a Knowledge Domain Mapping (KDM)-based framework, integrating advanced technologies—including remote sensing, Internet of Things (IoT) telemetry, geospatial sciences, statistical modeling, machine learning, and cloud computing—to create a holistic and scalable system for optimizing nitrogen applications. Central to this research is the accurate estimation and spatial allocation of the Economic Optimum Nitrogen Rate (EONR), a crucial element for reducing nitrogen use and enhancing yield. A key contribution of this study is the development of a robust Response Surface Model (RSM) that leverages multispectral indices (MSIs) from Sentinel-2 imagery, historical IoT telemetry data, and on-machine nitrogen sensors. This RSM approach allows for precise EONR predictions tailored to field-specific conditions, reducing the need for traditional plot-based trials and achieving an average prediction error of just 14.5%. Applied to a 7-hectare winter wheat field, the model successfully predicted EONR values ranging from 43 kg/ha to 75 kg/ha across zones, showcasing the adaptability and accuracy of RSM for field-specific nitrogen recommendations. This precisionfocused approach exemplifies the study’s goal of minimizing environmental impacts while ensuring sustainable yield improvements. Beyond the initial field-level implementation, this research examines the generalizability of the RSM framework using two modeling strategies: a single RSM across fields and a weighted average model that aggregates individual field-specific RSMs. The weighted model demonstrated superior adaptability and high prediction accuracy, with a root mean square error (RMSE) of 11 kg N/ha for the EONR, highlighting the framework’s potential for broader application across different agricultural settings. Such generalizability supports the framework’s adoption in diverse farming environments, enabling precise and informed nitrogen management at scale. To facilitate widespread adoption and practical application, the dissertation also introduces a cloud-based infrastructure that integrates the KDM framework with real-time IoT data and satellite imagery. Leveraging cloud services like Amazon Web Services (AWS) Batch for job orchestration, Amazon S3 for scalable data storage, and RDS Postgres for structured data management, this8 infrastructure allows for seamless handling of both real-time and historical data. Spatial interpolation techniques, such as Kriging, enhance the model’s capability to generate real-time nitrogen prescription maps, enabling precise nutrient management for large-scale agricultural operations. Automated data quality control and data harmonization embedded within this cloud architecture provide a strong foundation for managing increasing data volumes and diverse field conditions, making the system cost-effective, adaptable, and efficient for modern agriculture. In summary, this dissertation maps regenerative agriculture via a comprehensive roadmap for translating regenerative agriculture principles into practical, operational nitrogen management practices. Through KDM an interdisciplinary approach is mapped by the integration of advanced modeling, data processing, and cloud technologies. This framework enables sustainable crop management and aligns with global goals for environmentally responsible food production. The innovations introduced here support a scalable, data-driven approach to agricultural sustainability, bridging scientific research with real-world applications to meet the evolving demands of modern agriculture.
Metabolic profiling of ‘Elstar’ and ‘Nicoter’ apples: impact of storage time, dynamic controlled atmosphere and 1-MCP treatment
(2024) Thewes, Fabio Rodrigo; Büchele, Felix; Uhlmann, Lilian Osmari; Lugaresi, Adriana; de Oliveria Neuwald, Daiane Quadros; Brackmann, Auri; Both, Vanderlei; Wagner, Roger; Neuwald, Daniel Alexandre; Yao, Jia-Long
The aim of this work was to evaluate the effect of CA and DCA on sugars, tricarboxylic acid cycle (TCA), anaerobic metabolism and some volatile compounds of ‘Elstar’ and ‘Nicoter’ apples. This study also aimed to evaluate the effect of ethylene action blocking by 1-MCP (0.650 ppm). The storage conditions tested for both cultivars were (1) CA; (2) DCA-CF; (3) DCA-RQ 1.3; (4) DCA-RQ 1.5; (5) DCA-CD 1.1; and (6) DCA-CD 1.3. The lowest oxygen limit (LOL) was higher for the ‘Nicoter’ apples, and the three DCA methods were able to detect this difference between the cultivars. Sorbitol had a trend of accumulation when the fruit was stored under DCA-RQ and DCA-CD, especially in higher RQ and CD, showing a negative Pearson correlation with the oxygen partial pressure over the storage period. The 1-MCP treatment induced sorbitol accumulation even when the fruit was stored under CA. The TCA intermediaries, such as citrate, 2-oxoglutarate, succinate, fumarate and oxaloacetate, were the most affected by the atmosphere conditions and the 1-MCP treatment for both cultivars. Malic acid was more affected by the storage time than the atmosphere conditions. Succinate and fumarate had an accumulation trend when the fruit was stored under DCA-RQ.
The role of digital technologies to support sustainability management in agriculture
(2025) Weber, Rolf; Lewandowski, Iris
Agriculture causes many environmental problems in the production of food. In addition to the emissions that the agricultural sector emits in the upstream and downstream value chains, the use of plant protection products to increase yields also contributes to the decline in biodiversity. Consumer demands for more sustainable food production are increasing and stricter regulations are also being implemented politically to increase sustainability in European and German agriculture. To achieve this goal, many different assessment tools have been developed to measure and evaluate sustainability in agriculture. In addition to its role in the respective tools, digitization is also becoming increasingly important in food production. The possibilities of digital technologies in agriculture are multifaceted and can help to support farmers in managing their farms. Furthermore, digitization will also have an important impact on sustainability management. Digitization can help to increase the output:input ratio of farm inputs. Improving the efficiency of resource use has an impact on sustainability. However, tools for assessing sustainability in agriculture cannot show whether the use of digital technologies creates synergies or trade-offs. The sustainability tools also have limitations when it comes to assessing biodiversity, as the assessment takes place retrospectively on the one hand and across farms on the other. An algorithm that supports farmers in the field-specific biodiversity assessment before the cultivation season is still missing. Whether farmers are willing to accept the use of digital technologies to support decision-making has not yet been researched. Without the willingness of farmers to invest in digital technologies, the associated efficiency gains will remain unused and thus slow down the development towards a more sustainable agriculture. The aim of this work is to show how sustainability management in agriculture can be improved in food production with the support of digital technologies. In the study, field trials on site-specific fertilization were carried out over a period of four years on three different farms in a case study. Using the example of site-specific fertilization as a digital technology, the on-farm-research trials show which trade-offs and synergies occur between ecological and economic sustainability indicators in the digitization of agriculture in arable farming. Site-specific fertilization has led to an increase in yields, regardless of the size of the farm. This results in lower emissions per unit of product produced. In terms of economic benefits, the results show that farm size is crucial for the profitability of site-specific fertilization. The smaller the size of the farm, the higher the costs per unit associated with the technology. Whether synergies or trade-offs occur between ecological and economic sustainability indicators in site-specific fertilization has to be calculated manually so far, as the sustainability assessment tools do not provide this information. In the second study, an algorithm was developed that assesses the biodiversity potential in an indicator-based and prospective manner. To this end, agricultural management parameters (on-crop) and landscape parameters (off-crop) were first derived from the literature and then discussed in expert interviews. In these interviews, points were awarded for the on-crop and off-crop parameters and parameters influencing biodiversity in particular were weighted twice. The algorithm developed enables the biodiversity potential to be assessed on a field-specific basis. This allows farmers to determine which biodiversity potential is achieved at the cultivation planning stage. In addition, the algorithm can show farmers scenarios on how to optimize biodiversity performance. The third study addresses the social acceptance of digital technologies among farmers. The first and second study showed how the use of digital technologies can support farmers in their management. Therefore, the third research question investigated whether farmers use them at all. A qualitative Delphi study with experts was conducted to find out whether farmers accept and use digital technologies and how they affect the social dimension of sustainability. In most questions, the experts were unsure about farmers' acceptance of digital technologies and the general impact of digitization on farm life. The experts were concerned about data security, dependence on individual providers and the risk of smaller farmers not digitizing and thus being left behind in the digitization process because the costs of the technology are too high. Digital technologies can support the farmer's management on the one hand and contribute to a standardized sustainability assessment by automatically evaluating existing data on the other. However, this requires better interoperability of different software programs so that all data generated on the farm can be collected and evaluated centrally. This can enable the automation of the sustainability assessment and the transparency of sustainability performance for the downstream value chain. However, dealing with trade-offs within the sustainability dimensions when using digital technologies on the one hand, and the risk that farmers will not digitize due to a lack of economic viability on the other, hinder the digitization process.
Current prospects of social–ecologically more sustainable agriculture and urban agriculture
(2025) von Cossel, Moritz; Díaz-Chavez, Rocío; Winkler, Bastian
Combined bioenergy and food potential of Opuntia ficus-indica grown on marginal land in rural Mexico
(2024) Varela Pérez, Paola; Winkler, Bastian; Röcker, Philip; von Cossel, Moritz; Rubiera González, Fernando
Opuntia ficus-indica (cactus pear) emerged as a promising crop for sustainable bioenergy production on marginal agricultural land, mitigating competition with food crops and lowering the risk of other indirect land use changes. In this study, the bioenergy potential is investigated of cactus pear residues within a smallholder farming context of Nopaltepec, a rural municipality in Central Mexico. Nopaltepec is a native environment of cactus pear and shows an annual production volume of 30 Gg of fresh matter. A bottom-up approach employing semi-structured interviews ( n = 16) was utilized to assess the feasibility of transforming the pruning residues of cactus pear into a viable bioenergy source. The results indicate a substantial bioenergy potential, with 27 Mg of fresh matter biomass (equivalent to 9720 m 3 biogas) per hectare obtainable annually without compromising fruit yields. Moreover, the digestate produced through anaerobic digestion can be recycled as biofertilizer, offering economic and ecological advantages to smallholders. Notably, farmers expressed keen interest in integrating this technology into their agricultural systems. This research underscores the potential of cactus pear residues for developing a decentralized bioenergy sector and provides valuable ideas for future bottom-up assessments in rural communities like Nopaltepec.
Computational aspects of experimental designs in multiple-group mixed models
(2023) Prus, Maryna; Filová, Lenka
We extend the equivariance and invariance conditions for construction of optimal designs to multiple-group mixed models and, hence, derive the support of optimal designs for first- and second-order models on a symmetric square. Moreover, we provide a tool for computation of D - and L -efficient exact designs in multiple-group mixed models by adapting the algorithm of Harman et al. (Appl Stoch Models Bus Ind, 32:3–17, 2016). We show that this algorithm can be used both for size-constrained problems and also in settings that require multiple resource constraints on the design, such as cost constraints or marginal constraints.

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