Pierre Martre

• Ph.D., D.Sc.
• Research Director at French National Institute for Agriculture, Food, and Environment (INRAE)

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...

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-...

Mechanistic modelling is gradually replacing empiricism in crop models, focusing on leaf-level physiological processes. This shift necessitates simulating crop surface temperature at infra-canopy sub-daily scales but many crop models still rely on empirical formulations for canopy temperature estimation, typically on a daily basis. We developed MON...

Grain filling is a critical process for improving crop production under adverse conditions caused by climate change. Here, using a quantitative method, we quantified post-anthesis source–sink relationships of a large dataset to assess the contribution of remobilized pre-anthesis assimilates to grain growth for both biomass and nitrogen. The dataset...

Understanding how plant phenotypes are shaped by their environments is crucial for addressing questions about crop adaptation to new environments. This study focused on analyzing the genetic variability underlying genotype-by-environment interactions and adaptation for flowering time in maize. We developed the use of a physiological reaction norm f...

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...

Given the difficulties in accessing plant roots in situ, high-throughput root phenotyping (HTRP) platforms under controlled conditions have been developed to meet the growing demand for characterizing root system architecture (RSA) for genetic analyses. However, a proper evaluation of their capacity to provide the same estimates for strictly identi...

The expression of cereal grain storage protein (GSP) genes is controlled by a complex network of transcription factors (TFs). Storage protein activator (SPA) is a major TF acting in this network but its specific function in wheat (Triticum aestivum L.) remains to be determined. Here we generated an RNAi line in which expression of the three SPA hom...

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...

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...

Nitrogen fertilization is a key agronomic lever for high crop productivity, but also an important source of N 2 O emission, a potent greenhouse gas. Process-based agroecosystem simulation models are popular tools for managing the timing and amount of fertilization, and help reduce N 2 O emissions. However, accurate simulation of N 2 O emissions at...

Leaf expansion under drought drives the trade-off between water saving for later grain production and canopy photosynthesis. Fine-tuning leaf expansion could therefore become a target of genetic progress for drought-prone environments. However, its components (branching, leaf production and elongation) may have their own genetic variability and pla...

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...

The aim of this chapter is to briefly illustrate current practices in modeling crop yield as a response to climate change and what has been learnt so far, especially in terms of multi-model assessment and comparisons. For additional information, readers are directed to the “Where to look for further information” section for links and references.

This chapter examines improving data flow and integration in models assessing the impact of climate change on agriculture. It starts by first describing model-data integration, focusing on multi-criteria calibration of mechanistic agro-ecosystem models. The chapter moves on to review informing spatio-temporal simulations through methods such as rem...

Grain storage proteins (GSPs) quantity and composition determine the end-use value of wheat flour. GSPs consists of low-molecular-weight glutenins (LMW-GS), high-molecular-weight glutenins (HMW-GS) and gliadins. GSP gene expression is controlled by a complex network of DNA-protein and protein-protein interactions, which coordinate the tissue-specif...

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...

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...

Fine tuning crop development is a major breeding avenue to increase crop yield and for adaptation to climate change. In this study, we used a model that integrates our current understanding of the physiology of wheat phenology to predict the development and anthesis date of a RILs population of durum wheat with genotypic parameters controlling vern...

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...

Extreme climatic events, such as heat waves, cold snaps and drought spells, related to global climate change, have become more frequent and intense in recent years. Acclimation of plant physiological processes to changes in environmental conditions is a key component of plant adaptation to climate change. We assessed the temperature response of lea...

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...

We assessed how the temperature response of leaf day respiration (R d) in wheat responded to contrasting water regimes and growth temperatures. In Experiment 1, well‐watered and drought‐stressed conditions were imposed on two genotypes; in Experiment 2, the two water regimes combined with high (HT), medium (MT) and low (LT) growth temperatures were...

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...

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return pe...

There is potential sources of alleles and genes currently locked into wheat-related species that could be introduced into wheat breeding programs for current and future hot and dry climates. However, neither the intra- nor the inter-specific diversity of the responses of leaf growth and transpiration to temperature and evaporative demand have been...

There are potential sources of alleles and genes currently present in wheat-related species that have the potential to be introduced into wheat breeding programs targeting current and future hot and dry climates. However, to date neither the intra- nor the interspecific diversity of the responses of leaf growth and transpiration to temperature and...

We assessed how the temperature response of leaf day respiration ( R d ) in wheat responded to contrasting water regimes and growth temperatures. In Experiment 1, well-watered and drought-stressed conditions were imposed on two genotypes; in Experiment 2, the two water regimes combined with high (HT), medium (MT) and low (LT) growth temperatures we...

Process-based crop models are popular tools to analyze and simulate the response of agricultural systems to weather, agronomic, or genetic factors. They are often developed in modeling platforms to ensure their future extension and to couple different crop models with a soil model and a crop management event scheduler. The intercomparison and impro...

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...

Reduced blue light irradiance is known to enhance leaf elongation rate (LER) in grasses but the mechanisms involved have not yet been elucidated. We investigated if leaf elongation response to reduced blue light could be mediated by stomatal induced variations of plant transpiration. Two experiments were carried out on tall fescue in order to monit...

Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modelling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the canopy light interception models of the 26 wheat (Triticum aestivum) CGMs used by the Agricultural Mo...

Durum wheat is one of the most important crops in the Mediterranean basin. The choice of the cultivar and the sowing time are key management practices that ensure high yield. Crop simulation models could be used to investigate the genotype × environment × sowing window (G × E×SW) interactions in order to optimize farmers' actions. The aim of this s...

The diversity of plant and crop process-based modeling platforms in terms of implementation language, software design, and architectural constraints limits the reusability of the model components outside the platform in which they were originally developed, making model reuse a persistent issue. To facilitate the intercomparison and improvement of...

The simulated data set described in this paper was created by an ensemble of nine different crop models: HERMES (HE), Simplace<Lintul5,Slim3, FAO-56 ET0> (L5), SiriusQuality (SQ), MONICA (MO), Sirius2014 (S2), FASSET (FA), 4M (4M), SSM (SS), DSSAT-CSM IXIM (IX). Simulations were performed for grain maize (six models) and winter wheat (eight models)...

Understanding the molecular mechanisms controlling the accumulation of grain storage proteins in response to nitrogen (N) and sulfur (S) nutrition is essential to improve cereal grain nutritional and functional properties. Here, we studied the grain transcriptome and metabolome responses to postanthesis N and S supply for the diploid wheat einkorn...

Warmer temperature with climate change will affect crop yields by shortening growth duration and increasing water demand as well as the frequency and severity of heat stress. At the same time, elevated atmospheric CO 2 concentrations will decrease rates of water use and additionally increase growth of C 3 crops like wheat. Understanding the combine...

Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variab...

Key message We propose new methods to predict genotype × environment interaction by selecting relevant environmental covariates and using an AMMI decomposition of the interaction. Abstract Farmers are asked to produce more efficiently and to reduce their inputs in the context of climate change. They have to face more and more limiting factors that...

The extraction of desirable heritable traits for crop improvement from high-throughput phenotyping (HTP) observations remains challenging. We developed a modeling workflow named "Digital Plant Phenotyping Platform" (D3P), to access crop architectural traits from HTP observations. D3P couples the Architectural model of DEvelopment based on L-systems...

Albumins and globulins (AGs) of wheat endosperm represent about 20% of total grain proteins. Some of these physiologically active proteins can influence the synthesis of storage proteins (SPs) (gliadins and glutenins) and consequently, rheological properties of wheat flour and processing. To identify such AGs, data, (published by Bonnot et al., 201...

Since 1990 the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed data base of the ca. 2,100 cited experiments and simulations in the five ARs were analysed with respect to i...

Plant and crop simulation models are powerful tools for predicting the impact of climate change, innovative crop management practices, and new trait- or gene-based breeding technologies on the production of crops and agricultural systems. In this special issue, we gather a collection of review, opinion, and primary research papers that represent th...

Improving wheat (Triticum aestivum L.) yields to meet the projected demand for food in the future requires the talents of diverse scientists. In this article, we present the rationale for crop‐model‐driven, trait‐focused collaborative research emphasizing radiation use efficiency (RUE). Improving RUE is one of the promising avenues to substantially...

Accurate predictions of the timing of physiological stages and the development rate are crucial for predicting crop performance under field conditions. Plant development is controlled by the leaf appearance rate (LAR) and our understanding of how LAR responds to environmental factors is still limited. Here, we tested the hypothesis that carbon avai...

Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to im...

Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual...

The quality of wheat grain is mainly determined by the quantity and composition of its grain storage proteins (GSPs). GSPs consist of the low (LMW‐GS) and high (HMW‐GS) molecular‐weight glutenins and gliadins. The synthesis of these proteins is essentially regulated at the transcriptional level and by the availability of nitrogen and sulfur. The re...

Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropp...

Significance The consequences of climate change on European maize yields may become positive if farmers in 2050 use the decision rules they currently follow for adapting plant cycle duration and sowing dates to the diversity of environmental conditions. Experiments and simulations show that the current genetic variability of flowering time allows i...

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on g...

Core Ideas SOC decline, due to increased temperatures, reduces wheat and maize yields globally. CO 2 increase to 540 ppm partially compensates yield losses due to increased temperatures. Accounting for soil feedbacks is critical when evaluating climate change impacts on crop yield. A critical omission from climate change impact studies on crop yie...

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multi model ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e‐mean) and median (e‐median) often seem to predict quite well. However few studies have specifically been concern...

The data set reported here includes the part of a Hot Serial Cereal Experiment (HSC) experiment recently used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat models and quantify their response to temperature. The HSC experiment was conducted in an open-field in a semiarid environment in the southwest USA. The data reported herewit...

Extreme weather events across the world cause large variations in daily seasonal temperature and precipitation, potentially reducing grain yield and negatively affecting global food security. Thus, it is important to assess if crop growth models can simulate the yield losses caused by these extreme weather events. We tested if the DSSAT-NWheat crop...

Temperatures are warming on a global scale, a phenomenon that likely will affect future crop productivity. Crop growth models are useful tools to predict the likely effects of these global changes on agricultural productivity and to develop strategies to maximize the benefits and minimize the detriments of such changes. However, few such models hav...

Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six...

Nendel 38 | Jørgen Eivind Olesen 37 | Taru Palosuo 44 | John R. Porter 42,45,46 | Eckart Priesack 39 | Dominique Ripoche 47 | Mikhail A. Semenov 48 | Claudio Stöckle 17 | Pierre Stratonovitch 48 | Thilo Streck 33 | Iwan Supit 49 | Fulu Tao 50,44

L’environnement impacte sur les pertes de rendements variablement selon la réponse des différentes variétés de blé. Les essais « rendement » multiplient les environnements distincts pour identifier quels facteurs ont la plus forte influence sur les performances de la culture. Les modèles de simulation de croissance des plantes sont des outils préci...

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, mu...

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended...

Process-based crop growth models are popular tools to analyze and understand the impact of crop management, genotype by environment interactions, or climate change. The ability to predict leaf area development is critical to predict crop growth, particularly under conditions of limited resources. Here, we aimed at deciphering growth coordination ru...

Nature Plants 3, 17102 (2017); published online 17 July 2017; corrected online 27 September 2017.

In plant breeding, one of the major challenges of genomic selection is to account for genotype-by-environment (G × E) interactions, and more specifically how varieties are adapted to various environments. Crop growth models (CGM) were developed to model the response of plants to environmental conditions. They can be used to characterize eco-physiol...

Significance Agricultural production is vulnerable to climate change. Understanding climate change, especially the temperature impacts, is critical if policymakers, agriculturalists, and crop breeders are to ensure global food security. Our study, by compiling extensive published results from four analytical methods, shows that independent methods...

Wheat grain storage proteins (GSPs) make up most of the protein content of grain and determine flour end-use value. The synthesis and accumulation of GSPs depend highly on nitrogen (N) and sulfur (S) availability and it is important to understand the underlying control mechanisms. Here we studied how the einkorn (Triticum monococcum ssp. monococcum...

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical funct...