Institut für Kulturpflanzenwissenschaften

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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.
Iron partitioning and photosynthetic performance in Cannabis sativa L. reveal limitations of nanoscale zero-valent iron as a fertilizer
(2025) Büser, Christian; Hartung, Jens; Deurin, Lukas; Graeff-Hönninger, Simone
Iron (Fe) is the fourth most abundant element in the Earth’s crust but remains the third most limiting nutrient for crop productivity due to its low solubility in most soils. The emergence of nanotechnology has introduced nanoscale zero-valent iron (nZVI) as a potential Fe fertilizer with high surface reactivity and improved bioavailability. However, its comparative efficacy relative to conventional chelated Fe sources remains poorly understood. This study investigated Fe partitioning, photosynthetic efficiency, biomass accumulation, and cannabinoid synthesis in Cannabis sativa L. grown hydroponically under Fe-EDTA, nZVI, or Fe-deficient (-Fe) treatments. Total Fe concentrations were markedly reduced in -Fe plants compared with both Fe-EDTA and nZVI treatments. Despite similar root Fe contents between Fe-EDTA and nZVI, only Fe-EDTA facilitated efficient translocation to shoots, while nZVI-derived Fe predominantly accumulated in roots. Consequently, nZVI-treated plants exhibited intermediate photosynthetic performance and water-use efficiency—lower than Fe-EDTA but significantly higher than -Fe. Although Fe translocation differed substantially, inflorescence biomass and cannabinoid yield were comparable between nZVI and Fe-EDTA treatments, both exceeding those of -Fe plants. These results suggest that yield reductions under Fe deficiency arise not solely from Fe scarcity but also from the metabolic costs of Strategy I Fe acquisition, which are partially circumvented by root Fe availability from nZVI. Overall, Fe-EDTA demonstrated superior nutrient use efficiency, whereas nZVI partially alleviated Fe deficiency and revealed distinctive interactions between nanomaterials and plant Fe physiology. This study advances understanding of nZVI as an alternative Fe source in C. sativa and provides new insights into nanoparticle–plant nutrient dynamics.
Correction to: 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 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.
Impact of plastic rain shields and exclusion netting on pest dynamics and implications for pesticide use in apples
(2025) Bischoff, Robert; Piepho, Hans-Peter; Scheer, Christian; Petschenka, Georg
Apple production is among the most pesticide-intensive cultures. Recently, plastic rain shields and pest exclusion netting have emerged as potential measures to reduce the heavy reliance on chemical pesticides in apple, due to their inhibitory effect on pathogen and pest infestations. In a field trial, we compared yields, pest, and pathogen abundance in an orchard consisting of four plots, where two plots were covered with anti-hail net covers, one with plastic rain shields only, and one with plastic rain shields and exclusion netting. Pests and pathogens were assessed visually, and beating tray samples were collected to compare overall arthropod diversity between plots. We observed virtually no scab infections in both plastic rain shield plots, despite a more than 70% reduction of fungicides applied, when compared to anti-hail plots. Although no codling moth insecticides were sprayed in the plot with exclusion netting we found significantly reduced damage here, when compared to the anti-hail plots. However, likely due to microclimatic changes, we observed an increase of powdery mildew, woolly apple aphids, and spider mites under plastic rain shields. Modeling of metabolic rates of arthropod herbivores and predators revealed that there is an increased potential of herbivory under plastic rain shields. However, in terms of plant protection, the net effect of plastic rain shields and exclusion netting was a substantial reduction in chemical pesticide use, demonstrating that they represent a promising approach to minimize the use of chemical pesticides in apple production.
Sulfate enhances metabolic acclimation under drought stress - a comparative study of grapevine and maize
(2025) Lehr, Patrick Pascal; Erban, Alexander; Kopka, Joachim; Zörb, Christian
The importance of sulfate fertilization in plant production has becoming increasingly relevant due to the decline in atmospheric sulfur inputs. Moreover, high-intensity cropping systems are increasingly facing drought scenarios. The role of stomata is crucial during drought stress and is linked to sulfate metabolism. This study investigates the impact of sulfate application on the drought response of grapevine and maize guard cells. Both plant species may serve as crop model for analysing underlying physiological processes in a low fertilizer demanding crop such as grapevine and a high fertilizer demanding crop such as maize. Increased sulfate concentration in leaves was triggered by drought in maize and grapevine, but in grapevine only when additional sulfate was applied. Additional sulfate application improved sulfur availability under drought conditions, which enhanced drought stress response in grapevine and maize. This was characterized by enhanced metabolic acclimation under drought conditions. The effect of sulfate on the drought stress response was markedly diminished in guard cells, indicating enhanced metabolic stability of guard cells against external influences. These results underscore the significance of adequate sulfate supply to crops for optimal drought stress response and suggest that sulfate fertilisation may serve as a potential option to enhance drought acclimation
Historic insights and future potential in wheat elaborated using a diverse cultivars collection and extended phenotyping
(2025) El Hassouni, Khaoula; Afzal, Muhammad; Boeven, Philipp H. G.; Dornte, Jost; Koch, Michael; Pfeiffer, Nina; Pfleger, Franz; Rapp, Matthias; Schacht, Johannes; Spiller, Monika; Sielaff, Malte; Tenzer, Stefan; Thorwarth, Patrick; Longin, C. Friedrich H.
Wheat is one of the most important staple crops worldwide. Wheat breeding mainly focused on improving agronomy and techno-functionality for bread or pasta production, but nutrient content is becoming more important to fight malnutrition. We therefore investigated 282 bread wheat cultivars from seven decades of wheat breeding in Central Europe on 63 different traits related to agronomy, quality and nutrients in multiple field environments. Our results showed that wheat breeding has tremendously increased grain yield, resistance against diseases and lodging as well as baking quality across last decades. By contrast, mineral content slightly decreased without selection on it, probably due to its negative correlation with grain yield. The significant genetic variances determined for almost all traits show the potential for further improvement but significant negative correlations among grain yield and baking quality as well as grain yield and mineral content complicate their combined improvement. Thus, compromises in improvement of these traits are necessary to feed a growing global population.
Status quo of fertilization strategies and nutrient farm gate budgets on stockless organic vegetable farms in Germany
(2024) Stein, Sophie; Hartung, Jens; Zikeli, Sabine; Möller, Kurt; Reents, Hans Jürgen
Fertilizer management in stockless organic vegetable production is strongly affected by external nutrient purchases due to the high nitrogen (N) and potassium (K) requirements of vegetables. However, the database on nutrient flows and budgets in organic vegetable farming in Europe is very limited. Therefore, a survey based on semi-structured interviews was carried out comprising 12 organic horticultural farms in Germany. The results show that three different main fertilizer categories are used as inputs in different ratios by the inventoried farms: (1) base fertilizers (e.g., composts, solid farmyard manures), (2) commercial organic N fertilizers (e.g., keratins or plant products from food production or fermentation processes), and (3) commercial mineral fertilizers (e.g., potassium sulfate), all of which are approved for organic production. Ninety percent of the total nutrient inputs to the farms came from these fertilizers and biological N2 fixation, with the remaining 10% coming from other inputs, such as seeds or growing media. The estimated yearly average total farm budgets were nearly balanced across all farms with moderate surpluses (67.5 kg N ha−1, 2.06 kg P ha−1, and 0.26 kg K ha−1). However, large imbalances were found for most of the individual farms. These imbalances indicate the risk of nutrient accumulation or nutrient depletion in the soil, depending on the fertilization strategy and productivity of the farm. More specifically, increasing N share from base fertilizers led to increased P and K budgets, while strategies based on the use of large amounts of keratins led to the opposite—K and P depletion. We concluded that balanced nutrient management in organic vegetable production systems requires a thorough calculation and should combine the use of base fertilizers, commercial fertilizers with low P content, and increased N supply via BNF.
Spatiotemporal climatic signals in cereal yield variability and trends in Ethiopia
(2025) Abera, Kidist; Gayler, Sebastian; Piepho, Hans‑Peter; Streck, Thilo
Climatic variability and recurrent drought can strongly affect the variability of crop yield and are therefore frequently considered a risk to food security in Ethiopia. A better understanding of how crop yields vary in space and time, and their relationship to climatic and other driving factors, can assist in enhancing agricultural production and adapting to and mitigating the impacts of climate change. We applied a multiple linear regression model to examine the spatiotemporal climatic signal (air temperature, precipitation, and solar radiation) in the yields of the most important crops (maize, sorghum, tef, and wheat) over the period 1995–2018. An analysis of the climatic data indicated that growing season temperature increased significantly in most regions, but the trends in precipitation were not significant. The yields of maize, sorghum, tef, and wheat tended to increase across most crop-growing areas, particularly in the west, but was highly variable. The results highlight large spatial differences in the contribution of climatic trends to crop-yield variability across Ethiopian regions. The trends in climatic variability did not significantly affect crop yields in some areas, whereas in the main crop-growing areas, up to − 39.2% of yield variability could be attributed to the climatic trends. Specifically, the climatic trends negatively affected maize yields but positively affected sorghum, tef, and wheat yields. Nationally, the average impacts of climatic trends on crop yields was relatively small, ranging from a 3.2% decrease for maize to a 0.7% increase for wheat. In contrast, technological advancements contributed substantially more to yield gains, with annual increases ranging from 4.3% for wheat to 5.1% for sorghum. These findings highlight the dominant role of non-climatic drivers, particularly improved agricultural technology, in shaping crop yield trends. Our findings underscore the spatial heterogeneity of climate impacts on agriculture and highlight the critical importance of technological progress in enhancing crop productivity. They also provide actionable insights for designing crop- and location-specific adaptation strategies, and stress the need for integrated, climate-resilient development pathways in the region.

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