Friedrich Longin is the head of the Wheat Breeding group at the State Plant Breeding Institute of the University of Hohenheim

Topic: Future supply chains need to integrate nutrients - what does that mean for breeding

Links: https://weizen.uni-hohenheim.de/en/111370

Khaoula El Hassouni is a post-doctoral researcher in the BETTERWHEAT project at the State Plant Breeding Institute of the University of Hohenheim.

Topic: Multi-omics analysis for wheat improvement across the supply chain

Abstract: Combining phenomics, genomics and proteomics of 282 European bread wheat cultivars to provide a comprehensive understanding of genetic and protein factors leading to better trait selection and overall wheat improvement.

Biography: Her research aims to understand the genomic and proteomic architecture and environmental variability of quality and health related traits in wheat. Khaoula did her PhD in plant breeding at the International Center for Agricultural Research in the Dry Areas (ICARDA) and the University of Mohamed 5th through a project funded by Grains Research and Development Corporation (GRDC). During her PhD she worked on understanding the plant adaptive mechanisms and molecular basis of tolerance to drought, heat and mineral toxicities in durum wheat.

Kim Steige is head of the Biotechnology group at the State Plant Breeding Institute of the University of Hohenheim

Topic: GWAS of 2,600 proteins in bread wheat

Thomas Miedaner is head of the Rye Breeding group at the State Plant Breeding Institute of the University of Hohenheim.

Topic: Breeding for fungal disease resistances in small-grain cereals

Abstract: The aim of any breeding activity is to achieve genetic improvement in important traits, of which disease resistances are among the most important. Resistance to powdery mildew in wheat, leaf rust and Rhynchosporium in hybrid rye had a high genetic gain in a long-term study, while it is lower for leaf rust and Septoria tritici blotch in wheat and absent for yellow rust and Fusarium head blight in wheat. The durability of disease resistances is mainly determined by the mode of inheritance (monogenic vs. quantitative) and the population dynamics of the fungal pathogens. In Europe, inheritance is based mainly on monogenic resistances in wheat leaf and stem rust, a mixture of monogenic and quantitative resistances in wheat yellow rust, and pure quantitative resistances in Fusarium head blight in wheat, triticale, and rye. Breeding progress of the latter is hampered by the use of dwarfing genes. Fusarium head blight resistance, although difficult to achieve, is one of the most durable resistances available. In contrast, leaf rust resistance has the highest ageing effects in all cereals, i.e. resistance is significantly reduced over the lifetime of a variety due to adaptation of the highly dynamic leaf rust populations by frequent sexual recombination. Older concepts such as varietal mixtures or the cultivation of segregating varieties also improves durability of some pathosystems. In the future, genome editing could provide whole series of new resistance alleles that could potentially outpace the high reproduction rate of pathogen populations for the first time.

Biography: Thomas Miedaner’s expertise is in rye breeding and cereal resistance genetics including genomics-based methods. He is head of the Rye & Biotic Stress Research Group at the State Plant Breeding Institute since 1988 and works on genetic and molecular analyses of host resistances to several rusts (yellow rust, stem rust, leaf rust), ergot, and Fusarium diseases in wheat, triticale, rye, and maize.

Recent publications:

Miedaner, T., and Garbelotto, M. (2024). Human-mediated migration of plants, their pathogens and parasites. Journal of Plant Pathology. https://doi.org/10.1007/s42161-024-01589-0

Miedaner, T., Flamm, C., and Oberforster, M. (2024). The importance of Fusarium head blight resistance in the cereal breeding industry: case studies from Germany and Austria. Plant Breeding, 143, 44-58. https://doi.org/10.1111/pbr.13098213

Karl Schmid is Professor and Head of the group Crop Biodiversity and Bioinformatics at the Institute of Plant Breeding, Seed Science and Population Gentics.

Topic: Advancing Quinoa Breeding: Leveraging Genetic Diversity for Improved Cultivation and Value Chain Integration in Central Europe

Abstract: Quinoa, an ancient crop with favorable characteristics for cultivation in stressful environments, offers high-quality grain but has been little improved by modern plant breeding techniques. This has restricted its competitiveness in European agriculture. By leveraging the genetic diversity present in traditional quinoa cultivars and applying contemporary breeding methods, we aim to develop new quinoa varieties that are attractive for cultivation, enhance the diversity of crop rotation, and provide ecological benefits. Our work focuses on utilizing the native genetic diversity in quinoa to identify traits conducive to local adaptation in central Europe. Additionally, we aim to develop a quinoa ideotype that optimizes various phenotypic traits relevant for cultivation and utilization. Key traits targeted include yield and yield components, maturity, disease resistance, and grain quality. To achieve these goals, we employ genome-wide association studies (GWAS), QTL mapping, genomic prediction, and targeted crosses of suitable parents to develop advanced breeding material.

I will present the current status of our work on quinoa and presents perspectives on how improved quinoa varieties can be integrated into a supply chain, improving both agricultural productivity and ecological sustainability.

Biography: Karl Schmid is a professor and head of the research group "Crop Biodiversity and Breeding Informatics" at the Institute of Plant Breeding, University of Hohenheim. His research interests focus on identifying and utilizing useful genetic variation for plant breeding in various crop species and their wild ancestors, employing population genetics and quantitative genetics approaches. Karl Schmid studied biology and obtained his PhD from the University of Munich. His scientific career includes a postdoctoral position at Cornell University and group leader positions at the Max-Planck Institute of Chemical Ecology in Jena, Germany, and the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) in Gatersleben, Germany. Before joining the University of Hohenheim, he was a full Professor of Genetics at the Swedish University of Agricultural Sciences (SLU) in Uppsala, Sweden. Additionally, he serves as president of the German Quinoa Association.

Anurag Daware is PostDoc in the group Crop Biodiversity and Bioinformatics at the Institute of Plant Breeding, Seed Science and Population Geentics.

Topic: From Historical Data to Modern Efficiency: The Evolution of DUS Testing in Maize

Abstract: The registration of plant varieties plays a critical role in ensuring agricultural biodiversity, protecting breeders’ rights, and facilitating the commercialization of new cultivars. A cornerstone of this process is the Distinctness, Uniformity, and Stability (DUS) testing, which assesses whether a new variety is clearly distinguishable from existing ones, consistent in its essential characteristics, and stable across generations. Despite its importance, DUS testing faces several challenges, including the subjective nature of phenotypic assessments, the time-consuming nature of field trials, and the potential for environmental influence on trait expression. To address these issues, the integration of molecular markers has been proposed as a means to enhance the efficiency and reliability of DUS testing. Molecular markers offer a more precise, objective, and rapid approach to assessing genetic distinctness and uniformity, thereby potentially reducing the reliance on extensive field evaluations and expediting the variety registration process. In this  context we have cataloged the genetic diversity of important European Maize varieties. Further by utilizing Genome-Wide Association Studies (GWAS) and genomic prediction, we have identified markers linked with DUS traits. These markers can be potentially used to make DUS testing in Europe more efficient. Ultimately, these advancements in DUS testing can streamline the supply chain, ensuring that new, high-quality plant varieties reach the market more swiftly and reliably.

Biography: His current research focuses on developing strategies for using molecular markers to enhance the efficiency of DUS testing in maize. Anurag completed his PhD at the National Institute of Plant Genome Research in New Delhi, India. His PhD work involved exploring the genetic architecture underlying superior grain traits in improved Basmati rice and also led to the development of the Rice Pan-genome Genotyping Array (RPGA).

Tobias Würschum is Professor of Plant Breeding at the Institute of Plant Breeding, Seed Science and Population Genetics at the University of Hohenheim.

Topic: Genetic variation of the maize ionome in response to phosphorus fertilization

Biography: The Department of Plant Breeding is involved in various aspects of modern plant breeding. The main areas of research are in breeding methodology and selection theory, precision phenotyping, development and optimisation of molecular and genomic methods for plant breeding and their integration into breeding programmes, and phenotypic, genetic and molecular characterisation of traits.

Friedrich Laidig is a senior researcher at Biostatistics Unit, Institute of Crop Science, Hohenheim University since 2014, working on projects concerning modelling and analysis of long-term variety trials to estimate breeding progress of important agronomic traits including CFP and GHG emissions.

Topic “Is nitrogen use efficiency neglected in registration trials?"

Abstract Based on registration trials of cereals and winter oilseed rape in Germany, long-term breeding progress for NUE and related traits was quantified. Genotypic, environmental and genotype x environmental variation, correlation and heritability coefficients for the crops specific testing regimens were estimated. The results highlight the contribution of crop breeding to achieve progress in NUE and reducing adverse environmental impact.

Biography After completing his training as a farmer and subsequent practical experience as farmer, Friedrich Laidig studied Agronomy and Plant Breeding at Hohenheim University following graduate studies at the Statistics Department, Iowa State University, he received a PhD in Applied Mathematics and Statistics from Hohenheim University. At the German Federal Plant Variety Office, Hannover, he was head of Statistics and Data Analysis Section and Department Head of the Central Division until he retired in 2014.

Christian Flachenecker is leading the European Breeding Activities for winter oilseed rape at NPZ.

Topic: Innovations in Rapeseed Breeding: Oil and Protein for Sustainable Supply Chains

Abstract: The era of genomic selection offers new opportunities to save time and resources in hybrid breeding programs. In winter oilseed rape breeding genomic selection strategies help to increase selection intensity, selection accuracy and shorten the breeding cycle. In addition the identification and establishment of heterotic groups improves the efficiency of genomic selection and ultimately increases oil and protein yield for sustainable supply chains.

Biography: Christian Flachenecker has considerable expertise in plant breeding, quantitative genetics, agronomy, data analysis and statistics. He has implemented quantitative genetics and genomic techniques in commercial breeding programs. Christian Flachenecker is the speaker of the AG Winterraps in Germany, he is member of the UFOP/SFG committee on variety examination and member of the committee obtention and GT recherche colza in France.

Education:

2003-2006: PhD in Agricultural Sciences, University of Hohenheim, Stuttgart, Germany

1998-2002: Studies of Agrobiology, University of Hohenheim, Stuttgart, Germany

Employment:

since 2017: Winter oilseed rape breeding leader at Norddeutsche Pflanzenzucht Hans-Georg Lembke KG, Holtsee

2014-2016: Corn Breeder at Dow AgroSciences S.A.S, Carcarés, France

2008-2013: Corn Breeder and Station Leader, Dow AgroSciences GmbH, Lichtenau, Germany

2006-2008: Corn Breeder at Südwestsaat GbR, Lichtenau, Germany

Recent publications:

Krenzer D., Frisch, M, Beckmann, K, Kox T, Abbadi A, Flachenecker C, Snowdon RS, Herzog E (2024) Simulation-based establishment of base pools for a hybrid breeding program in winter rapeseed. Theor Appl Genet.  doi.org/10.1007/s00122-023-04519-3

Terraillon, J., Roeber F.K., Flachenecker C., Frisch M. (2023) Training set designs for prediction of yield and moisture of maize test cross hybrids with unreplicated trials. Frontiers in plant science. https://doi.org/10.3389/fpls.2023.1080087

Bettina Müller is Head of Data Science (Sugar Beet) at Strube D&S GmbH.

Topic: New breeding concepts with big data within the sugar beet breeding

Abstract: High throughput phenotyping and phenomic selection can increase the selection gain and accuracy of the sugar beet breeding. Different sensors, like RGB, thermal and multispectral are used in the sugar beet fields to detect new genetic material for different sugar beet diseases. As well as environmental data of the fields and NIR wavelengths of the harvested plots are used for phenomic selection in the sugar beet.

Biography:

Education:

2007-2011: PhD in Agriculture, University of Hohenheim, Stuttgart, Germany

2004-2007: Studies of Agriculture, University of Göttingen, Germany

2000-2004: Studies of Bioinformatics, University of Applied Sciences, Weihenstephan, Germany

Employment:

since 2023: Head of Data Science at Strube D&S

2011-2023: Sugarbeet breeder and Bioinformatics at Strube Research

Muhammad Afzal is a Postdoctoral Researcher at the State Plant Breeding Institute (LSA), Wheat Research Group. His PhD research focused on "Deciphering the potential of large-scale proteomics to improve product quality and nutritional value in different wheat species".

Topic: Utilization of Machine Learning for Optimal Prediction of Wheat Quality

Abstract: Bread wheat is one of the most important staple crops playing a pivotal role to sustainably feed the growing world population. Due to a constant demand for products of high quality, the end-use quality of wheat is a crucial criteria to evaluate genotypes for their quality along the wheat supply chain. In the Betterwheat project, we investigated a diverse panel of 282 old and modern bread wheat cultivars originating from different European countries across six environments (three locations over two years) for agronomic performance, disease resistance as well as numerous quality and nutritional traits. Direct measurement of wheat quality traits, critical for determining baking performance and dough properties, is often costly, time-consuming, and requires large sample sizes. In addition, the increasing availability of computational capabilities/tools and advanced statistical techniques offers an opportunity to streamline these processes through predictive modeling. Therefore, we aimed to leverage sophisticated machine learning techniques to predict end-use quality traits using simple-to-measure or fewer parameters. The data from different quality testing methods such as grain protein content, SDS, grain hardness, wet gluten, glutograph, several parameters from glutopeak and rapid visco analyser were used to predict target traits. A range of machine learning models, from linear regression to complex ensemble algorithms, were applied. The proposed approach holds potential to reduce reliance on direct measurements by predicting complex traits using simpler parameters. By integrating statistical tools and diverse data, this framework can potentially enable rapid and cost-effective assessment of end-use quality of wheat genotypes, and thereby can support breeders and industrial stakeholders in decision-making to provide high-quality wheat products for the consumers.

Biography: Currently, he is working on the project "BETTERWHEAT" in collaboration with industrial partners, aiming to improve the wheat crop. His focus lies on the use of statistical techniques, including a diverse array of machine learning algorithms, to optimally predict wheat quality by leveraging data from multiple sources. Additionally, his role involves the use of association mapping to study the genetic architecture of economically and nutritionally important traits.

Vincent Braun is a PhD candidate in the soybean group of the State Plant Breeding Institute at the University of Hohenheim

Topic: Optimizing NIRS preprocessing

Biography: After working as a consultant for two years, he has now returned to university to work on soybean breeding and delve even deeper into the world of quantitative genetics. Both the demand and supply of soybeans from Germany have increased steadily in recent yeras. However, due to climate change, weather extremes such as long dry spells are on the rise, posing major challenges for farmers. Vincent works on the SENSOJA project, which aims to accelerate breeding progress using drones, advanced sensor technology and phenomic selection. In this way, we try to take a step forward in the fight against climate change and contribute to solving future challennges.

Peter Risser is the head of the Kirschgartshausen Experimental Farm of Südzucker AG.

Topic: Südzucker Group - Get the Power of Plants - Challenges from Crop Production to Plant Based Solutions

Abstract: Founded in 1926, the Südzucker Group is one of the leading food industries with about 100 production locations worldwide and about 10.3 billion Euro revenues annually. Initially focused on processing sugar beet, the company today aims to develop plant-based solutions for food, animal feed, energy and many other innovative applications. The company is processing more than 30 million tonnes of renewable agricultural raw materials per year. To promote sustainable sugar beet production, Südzucker operates its own Research Farm in Kirschgartshausen.

Challenges from crop production to plant based solutions are shown in three examples:

1. Sugar beet is our main crop with perfect examples how breeding can help our farmers to achieve high yield in combination with high sugar content as well as tolerance/resistance against pests and diseases. The last years SBR (Syndrome Basses Richesse) has become a major problem in Southwest of Germany. Therefore, all breeding efforts are needed to find tolerant varieties and to better understand the disease.
2. Faba bean is a new crop within Südzucker Group. We start to produce protein concentrate to replace meat, but also as part of new recipes in bakery, snacks, beverages or sweets. The choice is a special variety with high yield, high protein content in combination with less antinutrients. Breeding is helping to achieve consumer demands in taste and flavor as well as famers needs to have stable and resistant varieties.
3. Our understanding of sustainablitiy is “growing in balance”. We focus on eight impact areas which includes reducing our greenhouse gas emissions as well as sustainable farming. At Research Farm Kirschgartshausen we started in 2018 to integrate flower strips in our fields to enhance biodiversity. The monitoring done by IFAB in Mannheim shows significant effects on insects, especially the promotion of pollinators. Birds use it as well as rabbits and deer. For the agricultural sector it is important to find the right balance between producing secure food for all of us and protecting our natural resources as well.

Biography: Growing up on a sugar beet farm in Rheinland-Pfalz, near the Offstein sugar factory in Southwest Germany, Peter Risser developed a deep-rooted passion for agriculture from a young age. This passion led him to pursue higher education at the University of Hohenheim in Stuttgart, where he earned a Master of Science degree. His academic journey continued at the University of Hohenheim's State Plant Breeding Institute, where he completed a PhD under the guidance of Prof. Miedaner, focusing on resistance breeding in winter wheat against Septoria tritici blotch.

In 2010, Peter Risser began his professional career with the Südzucker Group, joining the Agricultural Research and Advisory Service within the Business Unit Sugar & Beets. Through dedication and expertise, he rose to the position of Head of Research Farm Kirschgartshausen in 2018, within the Business Unit Agriculture at Südzucker AG in Mannheim.

In his current role, he is at the forefront of innovative agricultural practices. His main areas of focus include alternative weed control methods, enhancing biodiversity through integrated flower strips, and advancing precision farming and digitalization. He is also committed to promoting sustainable farming practices through extensive field trials, guided tours, training courses, workshops, and public relations efforts.

With a blend of academic excellence and practical experience, Peter Risser continues to drive forward the field of sustainable agriculture, making significant contributions to the future of farming.

Hans Peter Piepho was appointed Professor of Biostatistics at the University of Hohenheim, Stuttgart, Germany in 2001. He has been working as an applied statistician in agricultural research for more than 30 years. His main interests are related to statistical procedures as needed in plant genetics, plant breeding and cultivar testing. Recent interests include envirotype- and marker-enabled breeding, spatial methods for field trials and experimental design for various applications including two-phase experiments and multi-environment trials.

Topic: Factor-analytic variance-covariance structures for prediction into a target population of Environments

Abstract: Finlay-Wilkinson regression is a popular method for modelling genotype-environment interaction in plant breeding and crop variety testing. When environment is a random factor, this model may be cast as a factor-analytic variance-covariance structure, implying a regression on random latent environmental variables. This paper reviews such models with a focus on their use in the analysis of multi-environment trials for the purpose of making predictions in a target population of environments. We investigate the implication of random versus fixed effects assumptions, starting from basic analysis-of-variance models, then moving on to factor-analytic models and considering the transition to models involving observable environmental covariates, which promise to provide more accurate and targeted predictions than models with latent environmental variables. 

Carina Meyenberg is a PhD candidate in the wheat research group at the State Plant Breeding Institute at the University of Hohenheim. Her current research focus is on phenomic prediction in different wheat species using near infrared spectra (NIRS). Moreover, Carina will work on a simulation to identify efficient wheat breeding schemes that implement phenomic prediction. After her graduation, Carina aims at a career in a private breeding company.

Topic: Genomics based prebreeding

Mario Jekle is Professor and Department Director of Plant-based Foods at the University of Hohenheim

Topic: Plant quality in the future: A science perspective

Biography: Prof. Dr. Mario Jekle is the Director of the Department of Plant-based Foods and First Vice Dean of the Faculty of Natural Sciences at the University of Hohenheim in Stuttgart, Germany. His research covers the fractionation of functional plantbased biopolymers, the modification and structurization of these biopolymers and finally a reverse food engineering for a specific design of food properties. One strong focus is additive manufacturing of (edible) biomaterials, where he combines his interdisciplinary competencies of material sciences and process engineering.