Institut für Kulturpflanzenwissenschaften

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/12

Browse

Now showing 1 - 20 of 32

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.
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.
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.
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.
Comparative effects of individual and consortia plant growth promoting bacteria on physiological and enzymatic mechanisms to confer drought tolerance in maize (Zea mays L.)
(2021) Saleem, Muhammad; Nawaz, Fahim; Hussain, Muhammad Baqir; Ikram, Rao Muhammad
Mitigation strategies based on plant–microbe interactions to increase the performance of plants under water-deficit conditions are well documented. However, little is known about a suitable consortium of bacterial inoculants and underlying physiological and enzymatic events to improve drought tolerance in maize. We performed laboratory and pot experiments to understand the synergistic interactions among plant growth-promoting bacteria to alleviate the drought-induced damages in maize. Initially, ten bacterial strains were evaluated for their osmotic stress tolerance capacity by growing them in a media containing 0, 10, 20, and 30% polyethylene glycol (PEG-6000). Also, the seeds of a drought tolerant (NK-6654) and sensitive (SD-626) maize cultivar were inoculated with these bacterial strains in the first pot experiment to determine their effects on the growth and physiological processes. Later, in the second pot experiment, the best performing inoculants were selected to study the individual and synergistic effects of bacterial inoculation to confer drought tolerance in maize. Our findings showed that the inoculation with tolerant strains resulted in higher photosynthetic activity (25–39%), maintenance of leaf water status (14–18%) and pigments (27–32%), and stimulation of antioxidant machinery (28–38%) than no inoculation in water-stressed maize seedlings. Moreover, the treatment with bacteria consortia further stimulated the drought protective mechanisms and resulted in higher efficiency of photosynthetic (47–61%) and antioxidant systems (42–62%) than the individual inoculants under water-deficit conditions. We conclude that the inoculation with microbial consortia regulates water uptake, photosynthetic performance, and stress metabolites to minimize drought-induced damages in maize.
Comparative ungulate diversity and biomass change with human use and drought: implications for community stability and protected area prioritization in African savannas
(2025) Bartzke, Gundula S.; Ogutu, Joseph O.; Piepho, Hans‐Peter; Bedelian, Claire; Rainy, Michael E.; Kruska, Russel L.; Worden, Jeffrey S.; Kimani, Kamau; McCartney, Michael J.; Ng'ang'a, Leah; Kinoti, Jeniffer; Njuguna, Evanson C.; Wilson, Cathleen J.; Lamprey, Richard; Hobbs, Nicholas Thompson; Reid, Robin S.
Drought and human use may alter ungulate diversity and biomass in contrasting ways. In African savannas, resource‐dependent grazers such as wildebeest (Connochaetes taurinus) and zebra (Equus quagga) may decline or disperse as resources decline, opening space for more drought‐tolerant species such as gazelles (Eudorcas and Nanger) and impala (Aepyceros melampus). This shift can increase species richness, evenness, and overall ungulate diversity. Although higher diversity may stabilize ungulate communities, it may be associated with lower biomass (the total body mass of all individuals in a community), which in turn affects vegetation structure and composition, nutrient cycling, energy flows, and other organisms in savannas. While ungulate biomass often declines during drought or in areas of intense human use, the effects on diversity changes under low‐to‐moderate human use remain less clear. Our fine‐scale censuses in the Maasai Mara National Reserve and adjacent pastoral lands in Kenya showed that ungulate biomass declined more than diversity in the 1999 drought year. In the normal rainfall year of 2002, diversity peaked along the reserve boundary, but species richness leveled off in the drought year. Biomass peaked in the reserve in both census years, and migratory ungulates moved further into the reserve in the drought year, where diversity declined. These findings suggest that core protected areas are crucial for maintaining ungulate biomass, while transition zones from protected and pastoral lands support higher diversity unless drought reduces species richness.
Do lower nitrogen fertilization levels require breeding of different types of cultivars in triticale?
(2022) Neuweiler, Jan E.; Trini, Johannes; Maurer, Hans Peter; Würschum, Tobias
Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.
Drought impacts on plant–soil carbon allocation - integrating future mean climatic conditions
(2025) Leyrer, Vinzent; Blum, Juliette; Marhan, Sven; Kandeler, Ellen; Zimmermann, Telse; Berauer, Bernd J.; Schweiger, Andreas H.; Canarini, Alberto; Richter, Andreas; Poll, Christian
Droughts affect soil microbial abundance and functions—key parameters of plant–soil carbon (C) allocation dynamics. However, the impact of drought may be modified by the mean climatic conditions to which the soil microbiome has previously been exposed. In a future warmer and drier world, effects of drought may therefore differ from those observed in studies that simulate drought under current climatic conditions. To investigate this, we used the field experiment ‘Hohenheim Climate Change,’ an arable field where predicted drier and warmer mean climatic conditions had been simulated for 12 years. In April 2021, we exposed this agroecosystem to 8 weeks of drought with subsequent rewetting. Before drought, at peak drought, and after rewetting, we pulse‐labelled winter wheat in situ with 13CO2 to trace recently assimilated C from plants to soil microorganisms and back to the atmosphere. Severe drought decreased soil respiration (−35%) and abundance of gram‐positive bacteria (−15%) but had no effect on gram‐negative bacteria, fungi, and total microbial biomass C. This pattern was not affected by the mean precipitation regime to which the microbes had been pre‐exposed. Reduced mean precipitation had, however, a legacy effect by decreasing the proportion of recently assimilated C allocated to the microbial biomass C pool (−50%). Apart from that, continuous soil warming was an important driver of C fluxes throughout our experiment, increasing plant biomass, root sugar concentration, labile C, and respiration. Warming also shifted microorganisms toward utilizing soil organic matter as a C source instead of recently assimilated compounds. Our study found that moderate shifts in mean precipitation patterns can impose a legacy on how plant‐derived C is allocated in the microbial biomass of a temperate agroecosystem during drought. The overarching effect of soil warming, however, suggests that how temperate agroecosystems respond to drought will mainly be affected by future temperature increases.
Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material
(2021) Galán, Rodrigo José; Bernal-Vasquez, Angela-Maria; Jebsen, Christian; Piepho, Hans-Peter; Thorwarth, Patrick; Steffan, Philipp; Gordillo, Andres; Miedaner, Thomas
Key message: Hyperspectral data is a promising complement to genomic data to predict biomass under scenarios of low genetic relatedness. Sufficient environmental connectivity between data used for model training and validation is required. Abstract: The demand for sustainable sources of biomass is increasing worldwide. The early prediction of biomass via indirect selection of dry matter yield (DMY) based on hyperspectral and/or genomic prediction is crucial to affordably untap the potential of winter rye (Secale cereale L.) as a dual-purpose crop. However, this estimation involves multiple genetic backgrounds and genetic relatedness is a crucial factor in genomic selection (GS). To assess the prospect of prediction using reflectance data as a suitable complement to GS for biomass breeding, the influence of trait heritability ( ) and genetic relatedness were compared. Models were based on genomic (GBLUP) and hyperspectral reflectance-derived (HBLUP) relationship matrices to predict DMY and other biomass-related traits such as dry matter content (DMC) and fresh matter yield (FMY). For this, 270 elite rye lines from nine interconnected bi-parental families were genotyped using a 10 k-SNP array and phenotyped as testcrosses at four locations in two years (eight environments). From 400 discrete narrow bands (410 nm–993 nm) collected by an uncrewed aerial vehicle (UAV) on two dates in each environment, 32 hyperspectral bands previously selected by Lasso were incorporated into a prediction model. HBLUP showed higher prediction abilities (0.41 – 0.61) than GBLUP (0.14 – 0.28) under a decreased genetic relationship, especially for mid-heritable traits (FMY and DMY), suggesting that HBLUP is much less affected by relatedness and . However, the predictive power of both models was largely affected by environmental variances. Prediction abilities for DMY were further enhanced (up to 20%) by integrating both matrices and plant height into a bivariate model. Thus, data derived from high-throughput phenotyping emerges as a suitable strategy to efficiently leverage selection gains in biomass rye breeding; however, sufficient environmental connectivity is needed.
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.
Improving cover crop mixtures to increase soil carbon inputs and weed suppression as a tool to promote yield potential
(2024) Groß, Jonas; Müller, Torsten
Arable cropping systems are facing challenges imposed by climate change and are, at the same time, a tool to mitigate climate change. Soils are essential in securing yield potential and acting as a carbon sink. Recognizing small-scale site-specific differences in crop management and integrating cover crops, which provide ecosystem services such as carbon sequestration and weed suppression, are two approaches to climate-smart agriculture. To investigate site-specific soil heterogeneity, soil properties were analyzed in a field trial, measuring at three soil depths in 42 plots to determine their influence on yield measures. Soil organic carbon, silt, and clay contents in both topsoil and subsoil explained 45-46% of the variability in grain yield. Additionally, a positive correlation was found between increasing clay content in the topsoil and grain yield and tiller density. A higher clay content in the subsoil resulted in a decrease in grain yield. Soil organic carbon was identified as a soil property that positively influences yield and yield formation at any soil depth through multiple regressions and cluster analysis. Soil organic carbon is a critical soil measure that can significantly improve yield potential and can be manipulated by crop management practices like cover cropping. In a second field experiment, the impacts of increasing plant diversity of cover crop mixtures on rhizosphere carbon input and microbial utilization were investigated. A comparison was made between Mustard (Sinapis alba L.) planted as a sole crop and diversified cover crop mixtures of four (Mix4) or twelve (Mix12) species. A 13C-pulse labeling field experiment traced C transfer from shoots to roots to the soil microbial community. Mix 4 doubled the net CO2-C removal from the atmosphere, while Mix 12 more than tripled it, indicating that plant diversity positively impacts carbon cycling. This is reflected in higher atmospheric C uptake, higher transport rates to the rhizosphere, higher microbial incorporation, and longer residence time in the soil environment, improving the efficiency of C cycling in cropping systems. Root C-transfer could be identified as a fast pathway for C to reach soil C-compartments, but a substantial share of atmospheric C-catch comes from shoot biomass. In a third field experiment, the influence of species combination on shoot biomass formation was systematically assessed by investigating species interactions in dual cover crop mixtures and their competitiveness to suppress weeds before winter under different growing conditions. The shoot biomass share of a cover crop species in a dual-species mixture was found to be directly linked to its shoot biomass in a pure stand. Mustard and phacelia had similar effects on the shoot biomass production of the second species added to the mixture. Cruciferous species were more competitive against weeds than other cover crop species and could suppress weeds even when mixed with a less competitive partner. Weed suppression in mixtures with phacelia depended on the second component. Our results indicate that dual mixtures containing one competitive species reduce weed shoot biomass before winter, comparable to competitive pure stands. The research in this thesis shows that C content in the soil plays a crucial role in yield formation in arable cropping systems in Germany. Finally, the study has demonstrated that implementing cover crop mixtures can enhance soil C input and represent a valuable method for preserving yield potential. It was also shown that an intelligent combination of cover crop species can determine successful development and weed suppression.
Influence of cutting height on biomass yield and quality of miscanthus genotypes
(2021) Magenau, Elena; Kiesel, Andreas; Clifton‐Brown, John; Lewandowski, Iris
Commercially achieved biomass yields are often lower than those obtained in scientific plot trials and estimated by crop models. This phenomenon is commonly referred to as the ‘commercial yield gap’. It needs to be understood and managed to achieve the yield expectations that underpin business models. Cutting height at harvest is one of the key factors determining biomass yield and quality. This study quantifies the impacts of cutting heights of diverse genotypes with different morphologies and in years with contrasting weather conditions before and during harvest. Harvests were made in March 2015 and March 2018 of six diverse miscanthus genotypes planted as part of the ‘OPTIMISC project’ in 2013 near Stuttgart, Germany. Biomass yield, dry matter content and nutrient concentrations were analysed in four 10 cm fractions working upwards from the ground level and a fifth fraction with the shoot biomass higher than 40 cm. As stems are slightly tapered (i.e. diameter decreases slightly with increasing cutting height), it was hypothesized that low cutting may lead to yield gains, but that these may be associated with lower quality biomass with higher moisture and higher nutrient offtakes. We calculated average yield losses of 270 kg ha−1 (0.83%) with each 1 cm increase in cutting height up to 40 cm. Although whole shoot mineral concentrations were significantly influenced by both genotype and year interactions, total nitrogen (1.89 mg g−1), phosphorus (0.51 mg g−1), potassium (3.72 mg g−1) and calcium (0.89 mg g−1) concentrations did not differ significantly from the concentrations in the lower basal sections. Overall, cutting height had a limited influence on nutrient and moisture content. Therefore, we recommend that cutting is performed as low as is practically possible with the available machinery and local ground surface conditions to maximize biomass yield.
Lentils can absorb amino acids as a nitrogen source supporting early growth
(2025) Kröper, Alex A.; Zikeli, Sabine; Wimmer, Monika A.; Zörb, Christian
Background: Lentils ( Lens culinaris Medik.) are a valuable crop due to their high nutritional content, low environmental impact, and nitrogen‐fixing ability via rhizobacteria. Early in development, before this symbiosis is established, lentils require external nitrogen, typically supplied through fertilizers or already present in soils. Aim: This study explores whether lentils can utilize amino acids as a nitrogen source and how amino acid supplementation affects growth and nitrate uptake. Results: The findings show that lentils can absorb amino acids from soil, with no adverse effects on growth compared to mineral N fertilizers. The amino acid patterns show only slight changes in individual amino acids. NPF/NRT1, NRT2, AMT2, and DUR3 were expressed in all treatments in root tissue. LHT1 plays a minor role in the distribution of N in the shoots of lentil plants. Conclusion: Although amino acid uptake is less efficient than that of nitrate, it may still benefit young plants in organic farming until rhizobacterial symbiosis is established.
Local and systemic metabolic adjustments to drought in maize: hydraulic redistribution in a split‐root system
(2022) Werner, Lena Maria; Hartwig, Roman Paul; Engel, Isabelle; Franzisky, Bastian Leander; Wienkoop, Stefanie; Brenner, Martin; Preiner, Julian; Repper, Dagmar; Hartung, Jens; Zörb, Christian; Wimmer, Monika Andrea
Background: It is yet unknown how maize plants respond to a partial root drying under conditions of a limited total water supply, and which adaptation mechanisms are triggered under these conditions. Aims: The aims of this study were to assess whether partial root drying results in distinguishable local and systemic physiological and metabolic drought responses, and whether compensatory water uptake and/or alteration of root architecture occurs under these conditions. Methods: Maize plants were grown in a split-root system. When plants were 20 days old, the treatments ‘well-watered’, ‘local drought’ and ‘full drought’ were established for a period of 10 days. Shoot length and gas exchange were measured non-destructively, root exudates were collected using a filter system and biomass, relative water content, osmolality and proline content were determined destructively at final harvest. Results: Local drought triggered stress responses such as reduced biomass, shoot length, relative water content and increased osmolality. Maintained root growth was systemically achieved by hydraulic redistribution rather than by altering root architecture. Local and systemic osmolyte adjustments contributed to this hydraulic redistribution. Conclusions: Both local and systemic metabolic responses helped the plants to induce hydraulic redistribution, enhance water availability and in consequence plant water relations. This resulted in a surprisingly well-maintained root growth even in the drought stressed root compartment.
Long-term breeding progress of yield, yield-related, and disease resistance traits in five cereal crops of German variety trials
(2021) Laidig, Friedrich; Feike, T.; Klocke, B.; Macholdt, J.; Miedaner, Thomas; Rentel, D.; Piepho, Hans-Peter
Plant breeding and improved crop management generated considerable progress in cereal performance over the last decades. Climate change, as well as the political and social demand for more environmentally friendly production, require ongoing breeding progress. This study quantified long-term trends for breeding progress and ageing effects of yield, yield-related traits, and disease resistance traits from German variety trials for five cereal crops with a broad spectrum of genotypes. The varieties were grown over a wide range of environmental conditions during 1988–2019 under two intensity levels, without (I1) and with (I2) fungicides and growth regulators. Breeding progress regarding yield increase was the highest in winter barley followed by winter rye hybrid and the lowest in winter rye population varieties. Yield gaps between I2 and I1 widened for barleys, while they shrank for the other crops. A notable decrease in stem stability became apparent in I1 in most crops, while for diseases generally a decrasing susceptibility was found, especially for mildew, brown rust, scald, and dwarf leaf rust. The reduction in disease susceptibility in I2 (treated) was considerably higher than in I1. Our results revealed that yield performance and disease resistance of varieties were subject to considerable ageing effects, reducing yield and increasing disease susceptibility. Nevertheless, we quantified notable achievements in breeding progress for most disease resistances. This study indicated an urgent and continues need for new improved varieties, not only to combat ageing effects and generate higher yield potential, but also to offset future reduction in plant protection intensity.
Mapping and validating stem rust resistance genes directly in self-incompatible genetic resources of winter rye
(2021) Gruner, Paul; Schmitt, Anne-Kristin; Flath, Kerstin; Piepho, Hans-Peter; Miedaner, Thomas
Key message: Individual stem rust resistance genes could be directly mapped within self-incompatible rye populations. Abstract: Genetic resources of rye (Secale cereale L.) are cross-pollinating populations that can be highly diverse and are naturally segregating. In this study, we show that this segregation could be used for mapping stem rust resistance. Populations of pre-selected donors from the Russian Federation, the USA and Austria were tested on a single-plant basis for stem rust resistance by a leaf-segment test with three rust isolates. Seventy-four plants per population were genotyped with a 10 K-SNP chip. Using cumulative logit models, significant associations between the ordinal infection score and the marker alleles could be found. Three different loci (Pgs1, Pgs2, Pgs3) in three populations were highly significant, and resistance-linked markers could be validated with field experiments of an independent seed sample from the original population and were used to fix two populations for resistance. We showed that it is possible to map monogenically inherited seedling resistance genes directly in genetic resources, thus providing a competitive alternative to linkage mapping approaches that require a tedious and time-consuming inbreeding over several generations.
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.
Microbial inoculants modulate the rhizosphere microbiome, alleviate plant stress responses, and enhance maize growth at field scale
(2025) Francioli, Davide; Kampouris, Ioannis D.; Kuhl-Nagel, Theresa; Babin, Doreen; Sommermann, Loreen; Behr, Jan H.; Chowdhury, Soumitra Paul; Zrenner, Rita; Moradtalab, Narges; Schloter, Michael; Geistlinger, Joerg; Ludewig, Uwe; Neumann, Günter; Smalla, Kornelia; Grosch, Rita
Background: Field inoculation of crops with beneficial microbes is a promising sustainable strategy to enhance plant fitness and nutrient acquisition. However, effectiveness can vary due to environmental factors, microbial competition, and methodological challenges, while their precise modes of action remain uncertain. This underscores the need for further research to optimize inoculation strategies for consistent agricultural benefits. Results: Using a comprehensive, multidisciplinary approach, we investigate the effects of a consortium of beneficial microbes (BMc) ( Pseudomonas sp. RU47, Bacillus atrophaeus ABi03, Trichoderma harzianum OMG16) on maize ( Zea mays cv. Benedictio) through an inoculation experiment conducted within a long-term field trial across intensive and extensive farming practices. Additionally, an unexpected early drought stress emerged as a climatic variable, offering further insight into the effectiveness of the microbial consortium. Our findings demonstrate that BMc root inoculation primarily enhanced plant growth and fitness, particularly by increasing iron uptake, which is crucial for drought adaptation. Inoculated maize plants show improved shoot growth and fitness compared to non-inoculated plants, regardless of farming practices. Specifically, BMc modulate plant hormonal balance, enhance the detoxification of reactive oxygen species, and increase root exudation of iron-chelating metabolites. Amplicon sequencing reveals shifts in rhizosphere bacterial and fungal communities mediated by the consortium. Metagenomic shotgun sequencing indicates enrichment of genes related to antimicrobial lipopeptides and siderophores. Conclusions: Our findings highlight the multifaceted benefits of BMc inoculation on plant fitness, significantly influencing metabolism, stress responses, and the rhizosphere microbiome. These improvements are crucial for advancing sustainable agricultural practices by enhancing plant resilience and productivity.
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.

Browse

Browsing Institut für Kulturpflanzenwissenschaften by Sustainable Development Goals "13"