Senthold Asseng

• PhD, DSc
• Professor at Technical University of Munich

Spring frost remains a major climatic risk for winter wheat production. However, frost risk is often overlooked in climate change studies, especially those that rely on process-based crop models. This study assesses the spring frost risk for winter wheat in South Korea using observed trial data, a process-based crop model, and a large ensemble of c...

AgMIP-Wheat is an international wheat crop modeling community team within the Agricultural Model Intercomparison and Improvement Project (AgMIP), closely linked with field experimentation. The wheat team has compared wheat crop models against detailed field experimental measurements and has shown for the first time among climate change impact model...

Uncertainties of waterlogging impacts simulations for wheat growth are unknown due to absence of multi-model. In this study, we present the largest multi-model intercomparison to date, examining waterlogging impacts on wheat growth. Our findings indicate that individual crop models can accurately simulate measured wheat grain yields under various w...

Context or problem In recent decades, compounding weather extremes and plant diseases have increased wheat yield variability in France, the largest wheat producer in the European Union. Objective or research question How these extremes might affect future wheat production remains unclear. Methods Based on department level wheat yields, disease, and...

Neural networks are powerful machine learning models, but their reliability and trust are often criticized due to the unclear nature of their internal learned relationships. We explored neural network learning behavior in wheat yield prediction using game theory-based methods (SHapley Additive exPlanations, Shapley-like, cohort Owen), examined data...

The Internet of Things (IoT) seeks to achieve seamless device connectivity and data sharing, thereby enhancing automation, efficiency, and insights in various fields of application. By delivering real-time data, IoT is essential for systems that aim to model and map the physical world to digital formats, such as digital twins or metaverses. In the...

High-yielding traits can potentially improve yield performance under climate change. However, data for these traits are limited to specific field sites. Despite this limitation, field-scale calibrated crop models for high-yielding traits are being applied over large scales using gridded weather and soil datasets. This study investigates the implica...

This paper describes the data set that was used to test the accuracy of twenty-nine crop models in simulating the effect of changing sowing dates and sowing densities on wheat productivity for a high-yielding environment in New Zealand. The data includes one winter wheat cultivar (Wakanui) grown during six consecutive years, from 2012-2013 to 2017-...

While multi-model ensembles (MMEs) of seasonal climate models (SCMs) have been used for crop yield forecasting, there has not been a systematic attempt to select the most skillful SCMs to optimize the performance of a MME and improve in-season yield forecasts. Here, we propose a statistical model to forecast regional and national wheat yield variab...

Both climate and impact models are essential for understanding and quantifying the impact of climate change on agricultural productivity. Multi-model ensembles have highlighted considerable uncertainties in these assessments, yet a systematic approach to quantify these uncertainties is lacking. We propose a standardized approach to attribute uncert...

Increasing global food demand will require more food production¹ without further exceeding the planetary boundaries² while simultaneously adapting to climate change³. We used an ensemble of wheat simulation models with improved sink and source traits from the highest-yielding wheat genotypes⁴ to quantify potential yield gains and associated nitroge...

Hybrid intelligence - arising from the sensible, targeted fusion of human minds and cutting-edge computational systems-holds great potential for enhancing the sustainability of agriculture. Leveraging the combined strengths of both collective human and artificial intelligence helps identify and stress-test pathways towards the reconciliation of bio...

Elevated surface ozone (O3) concentrations can negatively impact growth and development of crop production by reducing photosynthesis and accelerating leaf senescence. Under unabated climate change, future global O3 concentrations are expected to increase in many regions, adding additional challenges to global agricultural production. Presently, fe...

Optimizing irrigation and nitrogen (N) fertilizer management in irrigated potato crops grown on sandy soils in subtropical regions such as in northeastern Florida, USA is essential to sustain a high yield and to minimize leaching. N applications in this region typically occur at approximately 25-30 days prior to planting (Npre), at emergence (Neme)...

The impact of climate data multivariate bias-adjustment methods versus univar-iate on crop model results was estimated. • Crop model results improved when input data was treated using multivar-iate methods compared to univariate methods. • Multivariate methods maintain the variables correlation as required by crop models. • This result is attribute...

Problem: Wheat (Triticum aestivum L.) yields may be reduced by projected rainfall decline due to climate change as well as environmental protection demands for less nitrogen (N) fertilizer inputs. Research question: Therefore, our study aims to determine how projected decreases in rainfall due to climate change and the reduction of N fertilizer inp...

Brazil is a major global grain exporter yet imports about 40% of the wheat it consumes every year. To meet domestic demand, Brazilian wheat production could be expanded into the vast areas of the Cerrado. Self-sufficiency would require transforming at least 0.5 million hectares of pasture into irrigated crop land or 2 million hectares if rainfed. L...

Wheat blast is a devastating disease caused by the fungal pathogen Magnaporthe oryzae pathotype Triticum that has spread to both neighbouring and distant countries following its emergence in Brazil in the 1980s. Under climate change conditions, wheat blast is predicted to spread primarily in tropical regions. Here we coupled a wheat crop simulation...

To address the rising global food demand in a changing climate, yield gaps (Y G), the difference between potential yields under irrigated (Y P) or rainfed conditions (Y WL) and actual farmers' yields (Y a), must be significantly narrowed whilst raising potential yields. Here, we examined the likely impacts of climate change (including changes in cl...

As the intensity and frequency of extreme weather events are projected to increase under climate change, assessing their impact on cropping systems and exploring feasible adaptation options is increasingly critical. Process-based crop models (PBCMs), which are widely used in climate change impact assessments, have improved in simulating the impacts...

This paper delineates the contemporary landscape, challenges, and prospective developments in human-centred artificial intelligence (AI) within the ambit of smart farming, a pivotal element of the emergent Agriculture 5.0, supplanting Agriculture 4.0. Analogous to Industry 4.0, agriculture has witnessed a trend towards comprehensive automation, oft...

Climate change challenges efforts to maintain and improve crop production in many regions. In this Review, we examine yield responses to warmer temperatures, elevated carbon dioxide and changes in water availability for globally important staple cereal crops (wheat, maize, millet, sorghum and rice). Elevated CO2 can have a compensatory effect on cr...

National wheat yield depends on climate conditions and usually remains unknown until harvest. In-season knowledge can be provided by wheat yield forecast systems, supporting the decision-making of farmers, food traders, or policymakers. In this study, we improved a previously developed statistical wheat yield model to forecast trend-corrected wheat...

Linked climate and crop simulation models are widely used to assess the impact of climate change on agriculture. However, it is unclear how ensemble configurations (model composition and size) influence crop yield projections and uncertainty. Here, we investigate the influences of ensemble configurations on crop yield projections and modeling uncer...

This document is the proposal for the consortium FAIRagro in the framework of the National Research Data Infrastructure (NFDI) in Germany. The proposal was submitted to the German Research Foundation (DFG) in Nov 2021. The proposal was finally accepted with a revised working program in Feb 2023. All financial resources (personnel, material, direct...

Increasing genetic wheat yield potential is considered as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulat...

Elevated surface ozone (O3) concentrations can negatively impact growth and development of crop production by reducing photosynthesis and accelerating leaf senescence. Under unabated climate change, future global O3 concentrations are expected to increase in many regions, adding additional challenges to global agricultural production. Presently, fe...

Brazil supplies half of the world's exported soybeans. Forecasting its national soybean yield before harvest could help mitigate disruptions in food supply. The objective of this study is to develop a national soybean yield forecasting system for Brazil based on machine learning (ML) models. Twenty years (2001-2020) of municipality yield, the Ocean...

Waterlogging affects millions of hectares traditionally used for food production every year. Despite this, existing literature and process-based frameworks enabling simulation of waterlogging are sparse. Here, we reveal a lack of field experiments that have enumerated effects of waterlogging on plant growth. We call for more research on waterloggin...

Grain production must increase by 60% in the next four decades to keep up with the expected population growth and food demand. A significant part of this increase must come from the improvement of staple crop grain yield potential. Crop growth simulation models combined with field experiments and crop physiology are powerful tools to quantify the i...

Presentation of the 6th AGROVOC Editorial Meeting 2023 in Freising, Germany

not yet peer-reviewed

The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchma...

The authors present the goals and current work of the respective Task Areas. Special consideration is given to Use Case 3 ("Streamlining pest and disease data to advance integrated pest management"), the challenges, objectives, expected outcomes, and requirements for the various work areas in the consortium. In each Task Area, explicit reference wa...

National crop yields are difficult to estimate during a crop season and are usually only known after crop harvest. The goal of this study was to develop a simple methodology to estimate national wheat yields that could be easily applied to any country and crop. Twenty years of readily available global gridded monthly climate data (0.5 •) across whe...

France suffered, in 2016, the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information, and yield physiology. The 2016 yield was composed of up to 40% fewer...

Increasing global food demand will require more food production without further exceeding the planetary boundaries, while at the same time adapting to climate change. We used an ensemble of wheat simulation models, with sink-source improved traits from the highest-yielding wheat genotypes to quantify potential yield gains and associated N requireme...

CONTEXT - Technological innovations in agriculture are mainly driven by the maxim: increase productivity at any costs. Today, in the face of climate change and an unprecedented loss of biodiversity, this approach is reaching its limits. Meeting global nutrition needs while achieving sustainability is one of the greatest challenges for modern agric...

Crop phenology has a major influence on crop yield and is a major aspect of crop response to global warming. Process-based models of phenology are often used to predict the effect of weather on the development rate of crops through their growth phases, but such models are associated with large uncertainties, as demonstrated by the large variability...

Zusammenfassung FAIRagro ist ein Konsortium in der Nationalen Forschungsdateninfrastruktur (NFDI) in Deutschland um Forschungsdaten der Agrosystemforschung FAIR – d. h. auffindbar (F), zugänglich (A), interoperabel (I) und für andere Forschende domänenübergreifend nachnutzbar (R) zu machen. In der deutschen Forschungslandschaft rund um nachhaltige...

Vertical farming allows for year-round cultivation of a variety of crops, overcoming environmental limitations and ensuring food security. This closed and highly controlled system allows the plants to grow in optimal conditions, so that it reaches maturity faster and yields more than on a conventional outdoor farm. However, one of the challenges of...

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Wheat is the most widely grown food crop, with 761 Mt produced globally in 2020. To meet the expected grain demand by mid-century, wheat breeding strategies must continue to improve upon yield-advancing physiological traits, regardless of climate change impacts. Here, the best performing doubled haploid (DH) crosses with an increased canopy photosy...

The war in Ukraine threatened to block 9% of global wheat exports, driving wheat prices to unprecedented heights. We advocate, that in the short term, compensating for such an export shortage will require a coordinated release of wheat stocks, while if the export block persists, other export countries will need to fill the gap by increasing wheat y...

Adaptive management of crop growing periods by adjusting sowing dates and cultivars is one of the central aspects of crop production systems, tightly connected to local climate. However, it is so far underrepresented in crop-model based assessments of yields under climate change. In this study, we integrate models of farmers’ decision making with b...

Low-temperature stress in late spring poses a serious threat to winter wheat production. In three-year environment-controlled phytotron experiments at both elongation and booting stages, we observed that short-term low-temperature stress decreased leaf area and stem, limited leaf photosynthetic system, and severely reduced grain yield, especially i...

Building a resilient and sustainable agricultural sector requires the development and implementation of tailored climate change adaptation strategies. By focusing on durum wheat (Triticum turgidum subsp. durum) in the Euro-Mediterranean region, we estimate the benefits of adapting through seasonal cultivar-selection supported by an idealised agro-c...

Potatoes are a mainstay of human diets and 4 million metric tons are produced annually in the United States. Simulations of future crop production show that climate change is likely to reduce the yields of the major grain crops around the world, but the impacts on potato production have yet to be determined. A model ensemble consisting of five proc...

Fruit quality is of increasing importance for consumers but is a complex trait for growers, as it is affected by environment, genotype, and crop management interactions. Decision support tools, such as computer models that simulate crop growth and development can help optimize production but require further improvement to simulate quality aspects....

Wheat blast is a devastating fungal disease of wheat crops. The disease emerged in Brazil in the 1980s and is now spreading across continents, so it is urgent to calculate the potential for wheat blast spread and estimate the impact on wheat yield globally. By coupling a wheat crop simulation model with a new wheat blast model, quantitative estimat...

Current wheat crop management practices in the Nile Delta of Egypt are unsustainable due to the overuse of limited water resources. Therefore, the aim of this study was to investigate opportunities to maximize wheat yield and resource efficiency including irrigation water use efficiency (WUE), nitrogen use efficiency (NUE), and solar radiation use...

Supplementary infromation ad Senapati et al 2022 Nature Food

Global food security requires food production to be increased in the coming decades. The closure of any existing genetic yield gap (Yig) by genetic improvement could increase crop yield potential and global production. Here we estimated present global wheat Yig, covering all wheat-growing environments and major producers, by optimizing local wheat...

A c c e p t e d M a n u s c r i p t 3 Highlight An ensemble of 29 wheat crop models simulates seasonal wheat growth well under locally recommended sowing conditions, but needs improvements to capture the yield response to early sowing, especially under high sowing density. Abstract Crop multi-model ensembles (MME) have proven to be effective in inc...

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of a MME to capture crop response to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to cl...

Crop simulation models are robust tools that enable users to better understand crop growth and development in various agronomic systems for improved decision making regarding agricultural productivity, environmental sustainability, and breeding. Crop models can simulate many agronomic treatments across a wide range of spatial and temporal scales, a...

Oilseed flax (Linum usitatissimum L.) is an important oil crop, and the SIMPLE model is a very effective tool to simulate crop production. In this study, to adapt the SIMPLE model for the overall improvement of flax production and yield, three promising cultivars of North China—Longya Hybrid No. 1, Baxuan No. 3 and Zhangya No. 2—were selected. Expe...

As crop yields are pushed closer to biophysical limits, achieving yield gains becomes increasingly challenging and will require more insight into deterministic pathways to yields. Here, we propose a wiring diagram as a platform to illustrate the interrelationships of the physiological traits that impact wheat yield potential and to serve as a decis...

Strawberry is a high-value horticultural crop with a global market and it has a strong regional importance in production areas such as Florida. Strawberry growers face many challenges related to weather, cultivation, and markets. Decision support tools can help optimize strawberry production but require sound models or other predictive tools as a f...

A recent trend in crop modeling has been the use of multi-model ensembles (MMEs) for impact assessment, especially as it relates to climate change. Studies have shown that, compared to individual models, the mean or median of a MME is a better predictor that is more accurate in making predictions and capable of providing model uncertainty informati...

Warming due to climate change has profound impacts on regional crop yields, and this includes impacts from rising mean growing season temperature and heat stress events. Adapting to these two impacts could be substantially different, and the overall contribution of these two factors on the effects of climate warming and crop yield is not known. Thi...

Food systems are increasingly challenged to meet growing demand for specialty crops due to the effects of climate change and increased competition for resources. Here, we apply an integrated methodology that includes climate, crop, economic and life cycle assessment models to US potato and tomato supply chains. We find that supply chains for two po...

Wheat production in Brazil is insufficient to meet domestic demand and falls drastically in response to adverse climate events. Multiple, agro-climate-specific regression models, quantifying regional production variability, were combined to estimate national production based on past climate, cropping area, trend-corrected yield, and national commod...

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of process-based models and has an important impact on simulated values. We propose a novel method of developing guidelines for calibration of process-based models, based on development of recommendations fo...

The vulnerability of wheat to climate change is accelerating at an increasing rate. This paper reviews the climate change trends, climate change impacts, quantification methods and adaption options in the arid and semi-arid environment. The temperature of mid-latitude of Asia may increase 2.4°C during the wheat season. Different studies reported th...

During the past decade, the interest in using crop models for research, education, extension, outreach and in the private sector has rapidly increased. The iCROPM 2020 Symposium entitled ‘Crop Modeling for the Future’, held in February 2020, therefore, provided a great opportunity for over 400 scientists from 50 different countries to exchange info...

The combination of advances in knowledge, technology, changes in consumer preference and low cost of manufacturing is accelerating the next technology revolution in crop, livestock and fish production systems. This will have major implications for how, where and by whom food will be produced in the future. This next technology revolution could bene...

Temperature response curves under diurnal oscillating temperatures differ from those under constant conditions for all stages of the Phytophthora infestans infection cycle on potatoes. We developed a mechanistic model (BLIGHTSIM) with an hourly time step to simulate late blight under fluctuating environmental conditions and predict late blight epid...

Cassava is an important crop in the developing world. The goal of this study was to review published cassava models (18) for their capability to simulate storage root biomass and to categorize them into static and dynamic models. The majority (14) are dynamic and capture within season growth dynamics. Most (13) of the dynamic models consider enviro...

Temperature affects many life processes, but its effect might be expected to differ among eukaryotic organisms inhabiting similar environments. We reviewed literature on temperature thresholds of humans, livestock, poultry, agricultural crops, and sparse examples of fisheries. We found that preferable and harmful temperatures are similar for humans...

[This corrects the article DOI: 10.1016/j.dib.2020.106639.].

Climate change affects global agricultural production and threatens food security. Faster phenological development of crops due to climate warming is one of the main drivers for potential future yield reductions. To counter the effect of faster maturity, adapted varieties would require more heat units to regain the previous growing period length. I...

Plant diseases are major causes of crop yield losses globally, yet their effects represent a poorly documented source of uncertainty in crop modelling. Ignoring the effects of plant diseases in crop models may lead to large overestimations of current and future crop production levels. Simulation modelling must be seen as a necessary instrument to u...

Wheat (Triticum aestivum) is the most widely grown food crop in the world threatened by future climate change. In this study, we simulated climate change impacts and adaptation strategies for wheat globally using new crop genetic traits (CGT), including increased heat tolerance, early vigor to increase early crop water use, late flowering to revers...

Accurately predicting crop development stage is key to simulating growth and yield formation in crop models. Low temperature stress is a major limitation to global wheat production and can significantly slow down wheat development rate. In a four-year environment-controlled phytotron experiments, detailed phenology datasets were obtained for low te...

Predicting wheat phenology is important for cultivar selection, for effective crop management and provides a baseline for evaluating the effects of global change. Evaluating how well crop phenology can be predicted is therefore of major interest. Twenty-eight wheat modeling groups participated in this evaluation. Our target population was wheat fie...

Predicting phenology is essential for adapting varieties to different environmental conditions and for crop management. Therefore, it is important to evaluate how well different crop modeling groups can predict phenology. Multiple evaluation studies have been previously published, but it is still difficult to generalize the findings from such studi...