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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Planting increases the abundance and structure complexity of soil core functional genes relevant to carbon and nitrogen cycling

Plants have an important impact on soil microbial communities and their functions. However, how plants determine the microbial composition and network interactions is still poorly understood. During a four-year field experiment, we investigated the functional gene composition of three types of soils (Phaeozem, Cambisols and Acrisol) under maize planting and bare fallow regimes located in cold temperate, warm temperate and subtropical regions, respectively. The core genes were identified using high-throughput functional gene microarray (GeoChip 3.0) and functional molecular ecological networks (fMENs) were subsequently developed with the random matrix theory (RMT)-based conceptual framework. Our results demonstrated that planting significantly (P < 0.05) increased the gene alpha-diversity in terms of richness and Shannon – Simpson’s indexes for all three types of soils and 83.5% of microbial alpha-diversity can be explained by the plant factor. Moreover, planting had significant impacts on the microbial community structure and the network interactions of the microbial communities. The calculated network complexity was higher under maize planting than under bare fallow regimes. The increase of the functional genes led to an increase in both soil respiration and nitrification potential with maize planting, indicating that changes in the soil microbial communities and network interactions influenced ecological functioning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The genetic architecture of leaf stable carbon isotope composition in Zea mays and the effect of transpiration efficiency on leaf elemental accumulation

With increased demand on freshwater resources for agriculture, it is imperative that more water-use efficient crops are developed. Leaf stable carbon isotope composition, δ 13 C, is a proxy for transpiration efficiency and a possible tool for breeders, but the underlying mechanisms effecting δ 13 C in C 4 plants are not known. It has been suggested that differences in specific leaf area (SLA), which potentially reflects variation in internal CO 2 diffusion, can impact leaf δ 13 C. Furthermore, although it is known that water movement is important for elemental uptake, it is not clear how manipulation of transpiration for increased water-use efficiency may impact nutrient accumulation. Here, we characterize the genetic architecture of leaf δ 13 C and test its relationship to SLA and the ionome in five populations of maize. Five significant QTL for leaf δ 13 C were identified, including novel QTL as well as some that were identified previously in maize kernels. One of the QTL regions contains an Erecta-like gene, the ortholog of which has been shown to regulate transpiration efficiency and leaf δ 13 C in Arabidopsis. QTL for δ 13 C were located in the same general chromosome region, but slightly shifted, when comparing data from two different years. Our data does not support a relationship between δ 13 C and SLA, and of the 19 elements analyzed, only a weak correlation between molybdenum and δ 13 C was detected. Together these data add to the genetic understanding of leaf δ 13 C in maize and suggest that improvements to plant water use may be possible without significantly influencing elemental homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluation of Protein Extraction Methods for Metaproteomic Analyses of Root-Associated Microbes

Metaproteomics is a powerful tool for the characterization of metabolism, physiology, and functional interactions in microbial communities, including plant-associated microbiota. However, the metaproteomic methods that have been used to study plant-associated microbiota are very laborious and require large amounts of plant tissue, hindering wider application of these methods. We optimized and evaluated different protein extraction methods for metaproteomics of plant-associated microbiota in two different plant species (Arabidopsis and maize). Our main goal was to identify a method that would work with low amounts of input material (40 to 70 mg) and that would maximize the number of identified microbial proteins. We tested eight protocols, each comprising a different combination of physical lysis method, extraction buffer, and cell-enrichment method on roots from plants grown with synthetic microbial communities. We assessed the performance of the extraction protocols by liquid chromatography-tandem mass spectrometry–based metaproteomics and found that the optimal extraction method differed between the two species. For Arabidopsis roots, protein extraction by beating whole roots with small beads provided the greatest number of identified microbial proteins and improved the identification of proteins from gram-positive bacteria. For maize, vortexing root pieces in the presence of large glass beads yielded the greatest number of microbial proteins identified. Based on these data, we recommend the use of these two methods for metaproteomics with Arabidopsis and maize. Furthermore, detailed descriptions of the eight tested protocols will enable future optimization of protein extraction for metaproteomics in other dicot and monocot plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Gene duplication and genetic innovation in cereal genomes

Organisms continuously require genetic variation to adapt to fluctuating environments, yet major evolutionary events are episodic, making the relationship between genome evolution and organismal adaptation of considerable interest. Here, by genome-wide comparison of sorghum, maize, and rice SNPs, we investigated reservoirs of genetic variations with high precision. For sorghum and rice, which have not experienced whole-genome duplication in 96 million years or more, tandem duplicates accumulate relatively more SNPs than paralogous genes retained from genome duplication. However, maize, which experienced lineage-specific genome duplication and has a relatively larger supply of paralogous duplicates, shows SNP enrichment in paralogous genes. The proportion of genes showing signatures of recent positive selection is higher in small-scale (tandem and transposed) than genome-scale duplicates in sorghum, but the opposite is true in maize. A large proportion of recent duplications in rice are species-specific; however, most recent duplications in sorghum are derived from ancestral gene families. A new retrotransposon family was also a source of many recent sorghum duplications, illustrating a role in providing variation for genetic innovations. This study shows that diverse evolutionary mechanisms provide the raw genetic material for adaptation in taxa with divergent histories of genome evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Emerging wild virus of native grass bioenergy feedstock is well–established in the Midwestern USA and associated with premature stand senescence

The North American native prairie grass Panicum virgatum (switchgrass) is a primary bioenergy feedstock candidate. Its widespread distribution and genetic diversity enable the possibility of developing this perennial grass for high production in a variety of conditions, including on marginal lands. A critical concern in feedstock development and deployment is the risk of novel pathogen emergence. Here we investigate the landscape-scale prevalence and epidemiology of a little-studied North American virus first detected in switchgrass and other grasses in bioenergy trials in the US Midwest. Switchgrass mosaic virus (SwMV, Genus Marafivirus, Family Tymoviridae) is transmitted by leafhoppers and phylogenetically sister to Maize rayado fino virus, a significant pathogen of maize in parts of the Americas. Our goal was to determine whether SwMV is uniquely limited to specific bioenergy trials or well-established and circulating more broadly. We used molecular diagnostics to quantify naturally occurring SwMV infection in leafhoppers and switchgrass in naturalistic stands throughout a large Midwestern landscape, and quantified leafhopper abundances and stand performance. Our analysis revealed that this apparently wild virus is well-established and widespread. Infection was present at nearly all sites, across diverse landscape contexts, with prevalences ranging as high as 33%–60%. Infection appeared to accumulate and persist in stands over time. It was associated with increases in premature stand senescence but not with reductions in stand height. Although wild viruses are believed to evolve benign relationships with their natural hosts, these data suggest that SwMV has potential to impact yield components. Viruses are frequently overlooked in crop development efforts, but represent the majority of emerging plant pathogens. For SwMV, it is imperative to quantify its impact on host performance, to identify the extent of any host resistance, and to assess any risks of virus spillover to agricultural plantings of other Poaceae species, including maize and sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Climate Forcing of Bioenergy Feedstocks: Insights From Carbon and Energy Flux Measurements

Bioenergy from biofuels has the potential to slow growing atmospheric carbon dioxide concentrations by reducing fossil fuel use. However, growing bioenergy feedstocks is a land-intensive process. In the United States, the recent expansion of maize bioethanol has presented some environmental costs, prompting the development of several alternative bioenergy feedstocks. These feedstocks, selected in part for traits associated with ecosystem services, may provide opportunities for environmental benefits beyond fossil fuel displacement. We hypothesized that these bioenergy ecosystems will provide direct climatic cooling through their influence on carbon and radiative energy fluxes (i.e., through albedo). To test this hypothesis, we investigated the potential cooling effect of five current or potential bioenergy feedstocks using multi-year records from eddy covariance towers. Perennial feedstocks were carbon sinks, with an annual mean net ecosystem carbon balance (NECB) of –2.7 ± 2.1 Mg C ha –1 for miscanthus, –0.8 ± 1.1 Mg C ha –1 for switchgrass, and –1.4 ± 0.7 Mg C ha –1 for prairie. In contrast, annual rotations were generally carbon sources, with an annual mean NECB of 2.6 ± 2.4 Mg C ha –1 for maize-soy and 3.2 ± 2.1 Mg C ha –1 for sorghum-soy. Using maize-soy as a baseline, conversion to alternative feedstocks increased albedo, inducing further cooling. This effect was strongest for miscanthus, with –3.5 ± 2.0 W m –2 of radiative forcing, and weakest for sorghum, with –1.4 ± 1.4 W m –2 . When feedstock effects on carbon and albedo were compared using carbon equivalents, carbon fluxes were the stronger ecosystem effect, underscoring the role of perennial species as effective carbon sinks. This work highlights the impact of feedstock choice on ecosystem processes as an element of bioenergy land conversion strategies.

09 BIOMASS FUELS↗
DOE OSTI2023

Genetic control of photoprotection and photosystem II operating efficiency in plants

Summary Photoprotection against excess light via nonphotochemical quenching (NPQ) is indispensable for plant survival. However, slow NPQ relaxation under low light conditions can decrease yield of field‐grown crops up to 40%. Using semi‐high‐throughput assay, we quantified the kinetics of NPQ and photosystem II operating efficiency (ΦPSII) in a replicated field trial of more than 700 maize ( Zea mays ) genotypes across 2 yr. Parametrized kinetics data were used to conduct genome‐wide association studies. For six candidate genes involved in NPQ and ΦPSII kinetics in maize the loss of function alleles of orthologous genes in Arabidopsis ( Arabidopsis thaliana ) were characterized: two thioredoxin genes, and genes encoding a transporter in the chloroplast envelope, an initiator of chloroplast movement, a putative regulator of cell elongation and stomatal patterning, and a protein involved in plant energy homeostasis. Since maize and Arabidopsis are distantly related, we propose that genes involved in photoprotection and PSII function are conserved across vascular plants. The genes and naturally occurring functional alleles identified here considerably expand the toolbox to achieving a sustainable increase in crop productivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Towards a dynamic photosynthesis model to guide yield improvement in C4 crops

Summary The most productive C4 food and biofuel crops, such as Saccharum officinarum (sugarcane), Sorghum bicolor (sorghum) and Zea mays (maize), all use NADP‐ME‐type C4 photosynthesis. Despite high productivities, these crops fall well short of the theoretical maximum solar conversion efficiency of 6%. Understanding the basis of these inefficiencies is key for bioengineering and breeding strategies to increase the sustainable productivity of these major C4 crops. Photosynthesis is studied predominantly at steady state in saturating light. In field stands of these crops light is continually changing, and often with rapid fluctuations. Although light may change in a second, the adjustment of photosynthesis may take many minutes, leading to inefficiencies. We measured the rates of CO 2 uptake and stomatal conductance of maize, sorghum and sugarcane under fluctuating light regimes. The gas exchange results were combined with a new dynamic photosynthesis model to infer the limiting factors under non‐steady‐state conditions. The dynamic photosynthesis model was developed from an existing C4 metabolic model for maize and extended to include: (i) post‐translational regulation of key photosynthetic enzymes and their temperature responses; (ii) dynamic stomatal conductance; and (iii) leaf energy balance. Testing the model outputs against measured rates of leaf CO 2 uptake and stomatal conductance in the three C4 crops indicated that Rubisco activase, the pyruvate phosphate dikinase regulatory protein and stomatal conductance are the major limitations to the efficiency of NADP‐ME‐type C4 photosynthesis during dark‐to‐high light transitions. We propose that the level of influence of these limiting factors make them targets for bioengineering the improved photosynthetic efficiency of these key crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Transcriptional Regulation of Grass Secondary Cell Wall Biosynthesis: Playing Catch-Up with Arabidopsis thaliana

Secondary cell wall synthesis occurs in specialized cell types following completion of cell enlargement. By virtue of mechanical strength provided by a wall thickened with cellulose, hemicelluloses, and lignin, these cells can function as water-conducting vessels and provide structural support. Several transcription factor families regulate genes encoding wall synthesis enzymes. Certain NAC and MYB proteins directly bind to the SNBE and AC elements upstream of structural genes and other transcription factors. The most detailed model of this regulatory network is established predominantly for a eudicot, Arabidopsis thaliana. In grasses, both the patterning and the composition of secondary cell walls are distinct from that of eudicots. These differences suggest transcriptional regulation is similarly distinct. Putative rice and maize orthologs of several eudicot cell wall regulators genetically complement mutants of A. thaliana or result in wall defects when constitutively overexpressed; nevertheless, aside from a maize, ZmMYB31, and a switchgrass protein, PvMYB4, function has not been tested in a grass. Similar to the seminal work conducted in A. thaliana, gene expression profiling in maize, rice, and other grasses implicates additional genes as regulators. Characterization of these genes will continue to elucidate the relationship between the transcription regulatory networks of eudicots and grasses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Changes of multispectral soil patterns with increasing crop canopy

Multispectral data and automatic data processing were used to map surface soil patterns and to follow the changes in multispectral radiation from a field of maize (Zea mays L.) during a period from seeding to maturity. Panchromatic aerial photography was obtained in early May 1970 and multispectral scanner missions were flown on May 6, June 30, August 11 and September 5, 1970 to obtain energy measurements in 13 wavelength bands. The orange portion of the visible spectrum was used in analyzing the May and June data to cluster relative radiance of the soils into eight different radiance levels. The reflective infrared spectral band was used in analyzing the August and September data to cluster maize into different spectral categories. The computer-produced soil patterns had a striking similarity to the soil pattern of the aerial photograph. These patterns became less distinct as the maize canopy increased.

Kristof, S. J.↗
NASA NTRS1985

Polar transport of 45Ca2+ across the elongation zone of gravistimulated roots

The movement of calcium across the elongation zone of gravistimulated primary roots of maize (Zea mays L.) was measured using 45Ca2+. Radioactive calcium was applied to one side of the elongation zone about 4 mm back from the root tip and the distribution of radioactivity across the root in the region of application was determined using scintillation spectrometry. The movement of 45Ca2+ across the elongation zone was non-polar in vertically oriented roots. In gravistimulated roots the movement of label was polarized with about twice as much label moving from top to bottom as from bottom to top. A variety of treatments which interfere with gravitropism was found to eliminate the polar movement of 45Ca2+ across the elongation zone. In maize cultivars which require light for gravitropic competency, dark grown roots exhibited neither gravitropism nor polar movement of 45Ca2+ across the elongation zone. Upon illumination the roots developed but gravitropic competency and gravity-induced polar movement of 45Ca2+ across the elongation zone. Similarly, roots of light-grown seedlings lost both gravitropic competency and 45Ca2+ transport polarity upon transfer to the dark. The results indicate a close correlation between calcium movement and gravitropism in primary roots in maize.

NASA Discipline Number 40-10↗
DOE OSTI2018

The impacts of four potential bioenergy crops on soil carbon dynamics as shown by biomarker analyses and DRIFT spectroscopy

Abstract Perennial bioenergy crops accumulate carbon (C) in soils through minimally disturbing management practices and large root inputs, but the mechanisms of microbial control over C dynamics under bioenergy crops have not been clarified. Root‐derived C inputs affect both soil microbial contribution to and degradation of soil organic matter resulting in differing soil organic carbon ( SOC ) concentrations, storage, and stabilities under different vegetation regimes. Here, we measured biomarker amino sugars and neutral sugars and used diffuse reflectance mid‐infrared Fourier transform spectroscopy ( DRIFTS ) to explore microbial C contributions, degradation ability, and SOC stability, respectively, under four potential bioenergy crops, M .× giganteus ( Miscanthus × giganteus ), switchgrass ( Panicum virgatum L .), a mixed prairie, and a maize ( Zea mays L .)–maize–soybean ( Glycine max(L.) Merr .) ( MMS ) rotation over six growing seasons. Our results showed that SOC concentration (g/kg) increased by 10.6% in mixed prairie over the duration of this experiment and SOC storage (Mg/ha) increased by 17.0% and 15.6% in switchgrass and mixed prairie, respectively. Conversion of row crops to perennial grasses maintained SOC stability and increased bacterial residue contribution to SOC in M .× giganteus and switchgrass by 20.0% and 15.0%, respectively, after 6 years. Degradation of microbe‐derived labile SOC was increased in M .× giganteus, and degradation of both labile and stable SOC increased in MMS rotation. These results demonstrate that microbial communities under perennial grasses maintained SOC quality, while SOC quantity increased under switchgrass and mixed prairie. Annual MMS rotation displayed decreases in aspects of SOC quality without changes in SOC quantity. These findings have implications for understanding microbial control over soil C quantity and quality under land‐use shift from annual to perennial bioenergy cropping systems.

09 BIOMASS FUELS↗
DOE OSTI2024

Genetic variation in Zea mays influences microbial nitrification and denitrification in conventional agroecosystems

Nitrogenous fertilizers provide a short-lived benefit to crops in agroecosystems, but stimulate nitrification and denitrification, processes that result in nitrate pollution, N 2 O production, and reduced soil fertility. Recent advances in plant microbiome science suggest that genetic variation in plants can modulate the composition and activity of rhizosphere N-cycling microorganisms. Here we attempted to determine whether genetic variation exists in Zea mays for the ability to influence the rhizosphere nitrifier and denitrifier microbiome under “real-world” conventional agricultural conditions. To capture an extensive amount of genetic diversity within maize we grew and sampled the rhizosphere microbiome of a diversity panel of germplasm that included ex-PVP inbreds (Z. mays ssp. mays), ex-PVP hybrids (Z. mays ssp. mays), and teosinte (Z. mays ssp. mexicana and Z. mays ssp. parviglumis). From these samples, we characterized the microbiome, a suite of microbial genes involved in nitrification and denitrification and carried out N-cycling potential assays. Here we are showing that populations/genotypes of a single species can vary in their ecological interaction with denitrifers and nitrifers. Some hybrid and teosinte genotypes supported microbial communities with lower potential nitrification and potential denitrification activity in the rhizosphere, while inbred genotypes stimulated/did not inhibit these N-cycling activities. These potential differences translated to functional differences in N 2 O fluxes, with teosinte plots producing less GHG than maize plots. Taken together, these results suggest that Zea genetic variation can lead to changes in N-cycling processes that result in N leaching and N 2 O production, and thereby are selectable targets for crop improvement. Understanding the underlying genetic variation contributing to belowground microbiome N-cycling into our conventional agricultural system could be useful for sustainability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Five Micron High Resolution MALDI Mass Spectrometry Imaging with Simple, Interchangeable, Multi-Resolution Optical System

High-spatial resolution mass spectrometry imaging (MSI) is crucial for the mapping of chemical distributions at the cellular and subcellular level. In this work, we improved our previous laser optical system for matrix-assisted laser desorption ionization (MALDI)-MSI, from ~9 μm practical laser spot size to a practical laser spot size of ~4 μm, thereby allowing for 5 μm resolution imaging without oversampling. This is accomplished through a combination of spatial filtering, beam expansion, and reduction of the final focal length. Most importantly, the new laser optics system allows for simple modification of the spot size solely through the interchanging of the beam expander component. Using 10×, 5×, and no beam expander, we could routinely change between ~4, ~7, and ~45 μm laser spot size, in less than 5 min. We applied this multi-resolution MALDI-MSI system to a single maize root tissue section with three different spatial resolutions of 5, 10, and 50 μm and compared the differences in imaging quality and signal sensitivity. We also demonstrated the difference in depth of focus between the optical systems with 10× and 5× beam expanders. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Latent Dirichlet Allocation modeling of environmental microbiomes

Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given sample, which makes untangling the interaction between an organism and its microbial environment a challenge. Here we apply Latent Dirichlet Allocation (LDA), a technique for language modeling, which decomposes the microbial communities into a set of topics (non-mutually-exclusive sub-communities) that compactly represent the distribution of full communities. LDA provides a lens into the microbiome at broad and fine-grained taxonomic levels, which we show on two datasets. In the first dataset, from the literature, we show how LDA topics succinctly recapitulate many results from a previous study on diseased coral species. We then apply LDA to a new dataset of maize soil microbiomes under drought, and find a large number of significant associations between the microbiome topics and plant traits as well as associations between the microbiome and the experimental factors, e.g. watering level. This yields new information on the plant-microbial interactions in maize and shows that LDA technique is useful for studying the coupling between microbiomes and stressed organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Prairies Thrive Where Row Crops Drown: A Comparison of Yields in Upland and Lowland Topographies in the Upper Midwest US

Cellulosic biofuel production is expected to increase in the US, and the targeted establishment of biofuel agriculture in marginal lands would reduce competition between biofuels and food crops. While poorly drained, seasonally saturated lowland landscape positions are marginal for production of row crops and switchgrass (Panicum virgatum L.), it is unclear whether species-diverse tallgrass prairie yield would suffer similarly in saturated lowlands. Prairie yields typically increase as graminoids become more dominant, but it is uncertain whether this trend is due to greater aboveground net primary productivity (ANPP) or higher harvest efficiency in graminoids compared to forbs. Belowground biomass, a factor that is important to ecosystem service provisioning, is reduced when switchgrass is grown in saturated lowlands, but it is not known whether the same is true in species-diverse prairie. Our objectives were to assess the effect of topography on yields and live belowground biomass in row crops and prairie, and to determine the mechanisms by which relative graminoid abundance influences tallgrass prairie yield. We measured yield, harvest efficiency, and live belowground biomass in upland and lowland landscape positions within maize silage (Zea mays L.), winter wheat (Triticum aestivum L.), and restored tallgrass prairie. Maize and winter wheat yields were reduced by more than 60% in poorly drained lowlands relative to well-drained uplands, but diverse prairie yields were equivalent in both topographic settings. Prairie yields increased by approximately 45% as the relative abundance of graminoids increased from 5% to 95%. However, this trend was due to higher harvest efficiency of graminoids rather than greater ANPP compared to forbs. In both row crops and prairie, live belowground biomass was similar between upland and lowland locations, indicating consistent biomass nutrient sequestration potential and soil organic matter inputs between topographic positions. While poorly drained, lowland landscape positions are marginal lands for row crops, they appear prime for the cultivation of species-diverse tallgrass prairie for cellulosic biofuel.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Advancing Tassel Detection and Counting: Annotation and Algorithms

Tassel counts provide valuable information related to flowering and yield prediction in maize, but are expensive and time-consuming to acquire via traditional manual approaches. High-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs), coupled with advanced machine learning approaches, including deep learning (DL), provides a new capability for monitoring flowering. In this article, three state-of-the-art DL techniques, CenterNet based on point annotation, task-aware spatial disentanglement (TSD), and detecting objects with recursive feature pyramids and switchable atrous convolution (DetectoRS) based on bounding box annotation, are modified to improve their performance for this application and evaluated for tassel detection relative to Tasselnetv2+. The dataset for the experiments is comprised of RGB images of maize tassels from plant breeding experiments, which vary in size, complexity, and overlap. Results show that the point annotations are more accurate and simpler to acquire than the bounding boxes, and bounding box-based approaches are more sensitive to the size of the bounding boxes and background than point-based approaches. Overall, CenterNet has high accuracy in comparison to the other techniques, but DetectoRS can better detect early-stage tassels. The results for these experiments were more robust than Tasselnetv2+, which is sensitive to the number of tassels in the image.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Using Reanalysis in Crop Monitoring and Forecasting Systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980-2010 under potential and water-imited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.

Reanalysis↗