Institut für Kulturpflanzenwissenschaften

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

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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.
Computing optimal allocation of trials to subregions in crop‐variety testing in case of correlated genotype effects
(2025) Prus, Maryna
The subject of this work is the allocation of trials to subregions in crop variety testing in the case of correlated genotype effects. A solution for computation of optimal allocations using the OptimalDesign package in R is proposed. The obtained optimal designs minimize linear criteria based on the mean squared error matrix of the best linear unbiased prediction of the genotype effects. The proposed computational approach allows for any kind of additional linear constraint on the designs. The results are illustrated by a real data example.
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.
How many checks are needed per cycle in a plant breeding or variety testing programme?
(2025) Piepho, Hans‐Peter; Laidig, Friedrich
Check varieties are used in plant breeding and variety testing for a number of reasons. One important use of checks is to provide connectivity between years, which facilitates comparison among genotypes of interest that are tested in different years. When long‐term data are available, such comparisons allow an assessment of realized genetic gain (RGG). Here, we consider the question of how many check varieties are needed per cycle for a reliable assessment of RGG. We propose an approach that makes use of variance component estimates for relevant random effects in a linear mixed model and plugs them into an analysis of dummy datasets set up to represent the design options being considered. Our results show that it is useful to employ a larger number of checks and to keep the replacement rate low. Furthermore, there is intercycle information to be recovered, especially when there are few checks and replacement rates are high, so modelling the cycle main effect as random pays off.
Impacts of different light spectra on CBD, CBDA and terpene concentrations in relation to the flower positions of different cannabis Sativa L. strains
(2022) Reichel, Philipp; Munz, Sebastian; Hartung, Jens; Kotiranta, Stiina; Graeff-Hönninger, Simone
Cannabis is one of the oldest cultivated plants, but plant breeding and cultivation are restricted by country-specific regulations. The plant has gained interest due to its medically important secondary metabolites, cannabinoids and terpenes. Besides biotic and abiotic stress factors, secondary metabolism can be manipulated by changing light quality and intensity. In this study, three morphologically different cannabis strains were grown in a greenhouse experiment under three different light spectra with three real light repetitions. The chosen light sources were as follows: a CHD Agro 400 ceramic metal-halide lamp with a sun-like broad spectrum and an R:FR ratio of 2.8, and two LED lamps, a Solray (SOL) and an AP67, with R:FR ratios of 13.49 and 4, respectively. The results of the study indicated that the considered light spectra significantly influenced CBDA and terpene concentrations in the plants. In addition to the different light spectra, the distributions of secondary metabolites were influenced by flower positions. The distributions varied between strains and indicated interactions between morphology and the chosen light spectra. Thus, the results demonstrate that secondary metabolism can be artificially manipulated by the choice of light spectrum, illuminant and intensity. Furthermore, the data imply that, besides the cannabis strain selected, flower position can have an impact on the medicinal potencies and concentrations of secondary metabolites.
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.
Limitations of soil-applied non-microbial and microbial biostimulants in enhancing soil P turnover and recycled P fertilizer utilization: A study with and without plants
(2024) Herrmann, Michelle Natalie; Griffin, Lydia Grace; John, Rebecca; Mosquera-Rodríguez, Sergio F.; Nkebiwe, Peteh Mehdi; Chen, Xinping; Yang, Huaiyu; Müller, Torsten
Introduction: Phosphorus recovery from waste streams is a global concern due to open nutrient cycles. However, the reliability and efficiency of recycled P fertilizers are often low. Biostimulants (BS), as a potential enhancer of P availability in soil, could help to overcome current barriers using recycled P fertilizers. For this, a deeper understanding of the influence of BSs on soil P turnover and the interaction of BSs with plants is needed. Methods: We conducted an incubation and a pot trial with maize in which we testednon-microbial (humic acids and plant extracts) and microbial BSs (microbial consortia) in combination with two recycled fertilizers for their impact on soil P turnover, plant available P, and plant growth. Results and discussion: BSs could not stimulate P turnover processes (phosphatase activity, microbial biomass P) and had a minor impact on calcium acetate-lactate extractable P (CAL-P) in the incubation trial. Even though stimulation of microbial P turnover by the microbial consortium and humic acids in combination with the sewage sludge ash could be identified in the plant trial with maize, this was not reflected in the plant performance and soil P turnover processes. Concerning the recycled P fertilizers, the CAL-P content in soil was not a reliable predictor of plant performance with both products resulting in competitive plant growth and P uptake. While this study questions the reliability of BSs, it also highlights the necessity toimprove our understanding and distinguish the mechanisms of P mobilization in soil and the stimulation of plant P acquisition to optimize future usage.
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.
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.
NAC transcription factors ATAF1 and ANAC055 affect the heat stress response in Arabidopsis
(2022) Alshareef, Nouf Owdah; Otterbach, Sophie L.; Allu, Annapurna Devi; Woo, Yong H.; de Werk, Tobias; Kamranfar, Iman; Mueller-Roeber, Bernd; Tester, Mark; Balazadeh, Salma; Schmöckel, Sandra M.
Pre-exposing (priming) plants to mild, non-lethal elevated temperature improves their tolerance to a later higher-temperature stress (triggering stimulus), which is of great ecological importance. ‘Thermomemory’ is maintaining this tolerance for an extended period of time. NAM/ATAF1/2/CUC2 (NAC) proteins are plant-specific transcription factors (TFs) that modulate responses to abiotic stresses, including heat stress (HS). Here, we investigated the potential role of NACs for thermomemory. We determined the expression of 104 Arabidopsis NAC genes after priming and triggering heat stimuli, and found ATAF1 expression is strongly induced right after priming and declines below control levels thereafter during thermorecovery. Knockout mutants of ATAF1 show better thermomemory than wild type, revealing a negative regulatory role. Differential expression analyses of RNA-seq data from ATAF1 overexpressor, ataf1 mutant and wild-type plants after heat priming revealed five genes that might be priming-associated direct targets of ATAF1: AT2G31260 (ATG9), AT2G41640 (GT61), AT3G44990 (XTH31), AT4G27720 and AT3G23540. Based on co-expression analyses applied to the aforementioned RNA-seq profiles, we identified ANAC055 to be transcriptionally co-regulated with ATAF1. Like ataf1, anac055 mutants show improved thermomemory, revealing a potential co-control of both NAC TFs over thermomemory. Our data reveals a core importance of two NAC transcription factors, ATAF1 and ANAC055, for thermomemory.
Projecting results of zoned multi-environment trials to new locations using environmental covariates with random coefficient models: accuracy and precision
(2021) Buntaran, Harimurti; Forkman, Johannes; Piepho, Hans-Peter
Multi-environment trials (MET) are conducted to assess the performance of a set of genotypes in a target population of environments. From a grower’s perspective, MET results must provide high accuracy and precision for predictions of genotype performance in new locations, i.e. the grower’s locations, which hardly ever coincide with the locations at which the trials were conducted. Linear mixed modelling can provide predictions for new locations. Moreover, the precision of the predictions is of primary concern and should be assessed. Besides, the precision can be improved when auxiliary information is available to characterize the targeted locations. Thus, in this study, we demonstrate the benefit of using environmental information (covariates) for predicting genotype performance in some new locations for Swedish winter wheat official trials. Swedish MET locations can be stratified into zones, allowing borrowing information between zones when best linear unbiased prediction (BLUP) is used. To account for correlations between zones, as well as for intercepts and slopes for the regression on covariates, we fitted random coefficient (RC) models. The results showed that the RC model with appropriate covariate scaling and model for covariate terms improved the precision of predictions of genotypic performance for new locations. The prediction accuracy of the RC model was competitive compared to the model without covariates. The RC model reduced the standard errors of predictions for individual genotypes and standard errors of predictions of genotype differences in new locations by 30–38% and 12–40%, respectively.
Urban waste fertilizer: effects on yield, nutrient dynamics, and potentially toxic element accumulation
(2025) Reimer, Marie; Möller, Kurt; Magid, Jakob; Bruun, Sander
Recycling nutrients contained in urban wastes to agriculture is essential in a circular economy. This study simultaneously compares different recycled fertilizers (household waste compost, sewage sludge, human urine) with mineral fertilization and animal manures. Tested were their long-term effects on yield, nutrient budgets, potentially toxic element (PTE) accumulation, and nitrogen (N)/carbon (C) cycle (among others N efficiency, N losses, soil C). Therefore, data from a long-term field trial and predictions from the soil–plant-atmosphere model Daisy were evaluated. Based on trial data, human urine performed similar to the mineral fertilization for yield, N efficiency (mineral fertilizer equivalent (MFE) = 81%), and nutrient budget, while sewage sludge and compost were comparable to animal manures in terms of having lower yields, N efficiencies (MFE 70% and 19% respectively) and higher nutrient imbalances, especially P and S surpluses. Compost and sewage sludge applications resulted in net PTE inputs. Yet, plant uptake and soil accumulation seemed neglectable. Model outputs predicted N losses of 34–55% of supplied N. Losses were highest for compost, followed by deep litter, manure, sewage sludge, human urine, mineral fertilization, and slurry. Nitrate leaching was the main loss pathway (14–41% of N input). Within the compost and straw-rich manure fertilization, about 25% of applied N was stored in the soil which was accompanied by an increase in soil C. The study suggests substitution of established fertilizers with recycled ones is feasible. Thereby each fertilizer has advantages and disadvantages and thus should be utilized according to its strength or in mixtures.

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