Instituto de Agricultura Sostenible

An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

At present and more so in the future, irrigated agriculture will take place under water scarcity. Insufficient water supply for irrigation will be the norm rather than the exception, and irrigation management will shift from emphasizing production per unit area towards maximizing the production per unit of water consumed, the water productivity. To cope with scarce supplies, deficit irrigation, defined as the application of water below full crop-water requirements (evapotranspiration), is an important tool to achieve the goal of reducing irrigation water use. While deficit irrigation is widely practised over millions of hectares for a number of reasons - from inadequate network design to excessive irrigation expansion relative to catchment supplies - it has not received sufficient attention in research. Its use in reducing water consumption for biomass production, and for irrigation of annual and perennial crops is reviewed here. There is potential for improving water productivity in many field crops and there is sufficient information for defining the best deficit irrigation strategy for many situations. One conclusion is that the level of irrigation supply under deficit irrigation should be relatively high in most cases, one that permits achieving 60-100% of full evapotranspiration. Several cases on the successful use of regulated deficit irrigation (RDI) in fruit trees and vines are reviewed, showing that RDI not only increases water productivity, but also farmers' profits. Research linking the physiological basis of these responses to the design of RDI strategies is likely to have a significant impact in increasing its adoption in water-limited areas.

Two critical limitations for using current satellite sensors in real-time crop management are the lack of imagery with optimum spatial and spectral resolutions and an unfavorable revisit time for most crop stress-detection applications. Alternatives based on manned airborne platforms are lacking due to their high operational costs. A fundamental requirement for providing <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">useful</i> remote sensing products in agriculture is the capacity to combine high spatial resolution and quick turnaround times. Remote sensing sensors placed on unmanned aerial vehicles (UAVs) could fill this gap, providing low-cost approaches to meet the critical requirements of spatial, spectral, and temporal resolutions. This paper demonstrates the ability to generate quantitative remote sensing products by means of a helicopter-based UAV equipped with inexpensive thermal and narrowband multispectral imaging sensors. During summer of 2007, the platform was flown over agricultural fields, obtaining thermal imagery in the 7.5-13-mum region (40-cm resolution) and narrowband multispectral imagery in the 400-800-nm spectral region (20-cm resolution). Surface reflectance and temperature imagery were obtained, after atmospheric corrections with MODTRAN. Biophysical parameters were estimated using vegetation indices, namely, normalized difference vegetation index, transformed chlorophyll absorption in reflectance index/optimized soil-adjusted vegetation index, and photochemical reflectance index (PRI), coupled with SAILH and FLIGHT models. As a result, the image products of leaf area index, chlorophyll content ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ab</sub> ), and water stress detection from PRI index and canopy temperature were produced and successfully validated. This paper demonstrates that results obtained with a low-cost UAV system for agricultural applications yielded comparable estimations, if not better, than those obtained by traditional manned airborne sensors.

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

Intestinal microbiota changes are associated with the development of obesity. However, studies in humans have generated conflicting results due to high inter-individual heterogeneity in terms of diet, age, and hormonal factors, and the largely unexplored influence of gender. In this work, we aimed to identify differential gut microbiota signatures associated with obesity, as a function of gender and changes in body mass index (BMI). Differences in the bacterial community structure were analyzed by 16S sequencing in 39 men and 36 post-menopausal women, who had similar dietary background, matched by age and stratified according to the BMI. We observed that the abundance of the Bacteroides genus was lower in men than in women (P<0.001, Q = 0.002) when BMI was > 33. In fact, the abundance of this genus decreased in men with an increase in BMI (P<0.001, Q<0.001). However, in women, it remained unchanged within the different ranges of BMI. We observed a higher presence of Veillonella (84.6% vs. 47.2%; X2 test P = 0.001, Q = 0.019) and Methanobrevibacter genera (84.6% vs. 47.2%; X2 test P = 0.002, Q = 0.026) in fecal samples in men compared to women. We also observed that the abundance of Bilophila was lower in men compared to women regardless of BMI (P = 0.002, Q = 0.041). Additionally, after correcting for age and sex, 66 bacterial taxa at the genus level were found to be associated with BMI and plasma lipids. Microbiota explained at P = 0.001, 31.17% variation in BMI, 29.04% in triglycerides, 33.70% in high-density lipoproteins, 46.86% in low-density lipoproteins, and 28.55% in total cholesterol. Our results suggest that gut microbiota may differ between men and women, and that these differences may be influenced by the grade of obesity. The divergence in gut microbiota observed between men and women might have a dominant role in the definition of gender differences in the prevalence of metabolic and intestinal inflammatory diseases.

With the centenary of the first descriptions of 'hypersensitiveness' following pathogenic challenge upon us, it is appropriate to assess our current understanding of the hypersensitive response (HR) form of cell death. In recent decades our understanding of the initiation, associated signalling, and some important proteolytic events linked to the HR has dramatically increased. Genetic approaches are increasingly elucidating the function of the HR initiating resistance genes and there have been extensive analyses of death-associated signals, calcium, reactive oxygen species (ROS), nitric oxide, salicylic acid, and now sphingolipids. At the same time, attempts to draw parallels between mammalian apoptosis and the HR have been largely unsuccessful and it may be better to consider the HR to be a distinctive form of plant cell death. We will consider if the HR form of cell death may occur through metabolic dysfunction in which malfunctioning organelles may play a major role. This review will highlight that although our knowledge of parts of the HR is excellent, a comprehensive molecular model is still to be attained.

The first crop chosen to parameterize and test the new FAO AquaCrop model is maize ( Zea mays L.). Working mainly with data sets from 6 yr of maize field experiments at Davis, CA, plus another 4 yr of Davis maize canopy data, a set of conservative (nearly constant) parameters of AquaCrop, presumably applicable to widely different conditions and not specific to a given crop cultivar, was evaluated by test simulations, and used to simulate the 6 yr of Davis data. The treatment variable was irrigation—withholding water after planting continuously, only up to tasseling, from tasseling onward, or intermittently, and with full irrigation (FI) as the control. From year to year, plant density (7–11.9 plants m −2 ), planting date (14 May−15 June), cultivar (a total of four), and atmospheric evaporative demand varied. The conservative parameters included: canopy growth and canopy decline coefficient (CDC); crop coefficient for transpiration (Tr) at full canopy; normalized water productivity for biomass (WP∗); soil water depletion thresholds for the inhibition leaf growth and of stomatal conductance, and for the acceleration of canopy senescence; reference harvest index (HI o ); and coefficients for adjusting harvest index (HI) in relation to inhibition of leaf growth and of stomatal conductance. With all 19 parameters held constant, AquaCrop simulated the final aboveground biomass within 10% of the measured value for at least 8 of the 13 treatments (6 yr of experiments) and also the grain yield for at least five of the cases. In at least four of the cases, the simulated results were within 5% of the measured for biomass as well as for grain yield. The largest deviation between the simulated and measured values was 22% for biomass, and 24% for grain yield. Importantly, the simulated pattern of canopy progression and biomass accumulation over time were close to those measured, with Willmott's index of agreement ( d ) for 11 of the 13 cases being ≥0.98 for canopy cover (CC), and ≥0.97 for biomass. Accelerated senescence of canopy due to water stress, however, proved to be difficult to simulate accurately; of the six cases, the index of agreement for the worst one was 0.957 for canopy and 0.915 for biomass. Possible reasons for the discrepancies between the simulated and measured results include simplifications in the model and inaccuracies in measurements. The usefulness of AquaCrop with well‐calibrated conservative parameters in assessing water use efficiency (WUE) of a crops under different conditions and in devising strategies to improve WUE is discussed.

Coeliac disease is an autoimmune disorder triggered in genetically predisposed individuals by the ingestion of gluten proteins from wheat, barley and rye. The α-gliadin gene family of wheat contains four highly stimulatory peptides, of which the 33-mer is the main immunodominant peptide in patients with coeliac. We designed two sgRNAs to target a conserved region adjacent to the coding sequence for the 33-mer in the α-gliadin genes. Twenty-one mutant lines were generated, all showing strong reduction in α-gliadins. Up to 35 different genes were mutated in one of the lines of the 45 different genes identified in the wild type, while immunoreactivity was reduced by 85%. Transgene-free lines were identified, and no off-target mutations have been detected in any of the potential targets. The low-gluten, transgene-free wheat lines described here could be used to produce low-gluten foodstuff and serve as source material to introgress this trait into elite wheat varieties.

Abstract 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 CO 2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO 2 . Introducing genotypes adapted to warmer temperatures (and also considering changes in CO 2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

The field of nanotechnology opens up novel potential applications for agriculture. Nanotechnology applications are already being explored and used in medicine and pharmacology, but interest for use in crop protection is just starting. The development of nanodevices as smart delivery systems to target specific sites and nanocarriers for controlled chemical release is discussed. Some nanotechnologies can improve existing crop management techniques in the short to medium term. Nanocapsules would help to avoid phytotoxicity on the crop by using systemic herbicides against parasitic weeds. Nanoencapsulation can also improve herbicide application, providing better penetration through cuticles and tissues, and allowing slow and constant release of the active substances. On the other hand, new crop management tools could be developed on the basis of medical applications. Nanoparticles have a great potential as 'magic bullets', loaded with herbicides, chemicals or nucleic acids, and targeting specific plant tissues or areas to release their charge. Viral capsids can be altered by mutagenesis to achieve different configurations and deliver specific nucleic acids, enzymes or antimicrobial peptides acting against the parasites. Many issues are still to be addressed, such as increasing the scale of production processes and lowering costs, as well as toxicological issues, but the foundations of a new plant treatment concept have been laid, and applications in the field of parasitic plant control can be started.

BACKGROUND: In recent years, the application of nanotechnology in several fields of bioscience and biomedicine has been studied. The use of nanoparticles for the targeted delivery of substances has been given special attention and is of particular interest in the treatment of plant diseases. In this work both the penetration and the movement of iron-carbon nanoparticles in plant cells have been analyzed in living plants of Cucurbita pepo. RESULTS: The nanoparticles were applied in planta using two different application methods, injection and spraying, and magnets were used to retain the particles in movement in specific areas of the plant. The main experimental approach, using correlative light and electron microscopy provided evidence of intracellular localization of nanoparticles and their displacement from the application point. Long range movement of the particles through the plant body was also detected, particles having been found near the magnets used to immobilize and concentrate them. Furthermore, cell response to the nanoparticle presence was detected. CONCLUSION: Nanoparticles were capable of penetrating living plant tissues and migrating to different regions of the plant, although movements over short distances seemed to be favoured. These findings show that the use of carbon coated magnetic particles for directed delivery of substances into plant cells is a feasible application.

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.

BACKGROUND AND AIMS: The great potential of using nanodevices as delivery systems to specific targets in living organisms was first explored for medical uses. In plants, the same principles can be applied for a broad range of uses, in particular to tackle infections. Nanoparticles tagged to agrochemicals or other substances could reduce the damage to other plant tissues and the amount of chemicals released into the environment. To explore the benefits of applying nanotechnology to agriculture, the first stage is to work out the correct penetration and transport of the nanoparticles into plants. This research is aimed (a) to put forward a number of tools for the detection and analysis of core-shell magnetic nanoparticles introduced into plants and (b) to assess the use of such magnetic nanoparticles for their concentration in selected plant tissues by magnetic field gradients. METHODS: Cucurbita pepo plants were cultivated in vitro and treated with carbon-coated Fe nanoparticles. Different microscopy techniques were used for the detection and analysis of these magnetic nanoparticles, ranging from conventional light microscopy to confocal and electron microscopy. KEY RESULTS: Penetration and translocation of magnetic nanoparticles in whole living plants and into plant cells were determined. The magnetic character allowed nanoparticles to be positioned in the desired plant tissue by applying a magnetic field gradient there; also the graphitic shell made good visualization possible using different microscopy techniques. CONCLUSIONS: The results open a wide range of possibilities for using magnetic nanoparticles in general plant research and agronomy. The nanoparticles can be charged with different substances, introduced within the plants and, if necessary, concentrated into localized areas by using magnets. Also simple or more complex microscopical techniques can be used in localization studies.

L ópez ‐G ranados F (2011). Weed detection for site‐specific weed management: mapping and real‐time approaches. Weed Research 51 , 1–11. Summary This work describes the current status of remote and proximal (on‐ground) weed detection systems for site‐specific weed management and discusses the limitations and opportunities of these technologies. Remote sensing based on multispectral aerial imagery can provide accurate weed maps, especially at late weed phenological stages, whereas images from high spatial resolution satellite and unmanned aerial vehicles must still be analysed. Hyperspectral images produce highly accurate maps at early and late phenological stages at a farm scale or medium spatial scale. However, this technology is not profitable, because of current operating costs, which are prohibitive. In studies of on‐ground weed seedling detection, accurate results can be obtained at a medium farm scale. Despite numerous efforts, a powerful and flexible classifier of soil, weeds and crops in a number of situations, remains the greatest challenge of this technology. The main limitations of remote and proximal sensing may be summarised in the following two points: (i) the time and education required for applying new technological advances and (ii) the high cost of the technology and the lack of compatibility of the machinery. Possible solutions might include: (i) offering an advisory service that provides technical support, agronomic knowledge and specific training courses, (ii) the development and implementation of uniform and cheaper standards, (iii) increased research of both high resolution satellite imagery exploring object‐based image analysis and pan‐sharpened imagery and unmanned aerial vehicles (UAV) and (iv) enabling the development of current prototypes of robotic weeding into commercial products. The general lack of multidisciplinary research groups can be a disadvantage when comparing the economic feasibility of site‐specific weed management with conventional systems.

The ability to edit plant genomes through gene targeting (GT) requires efficient methods to deliver both sequence-specific nucleases (SSNs) and repair templates to plant cells. This is typically achieved using Agrobacterium T-DNA, biolistics or by stably integrating nuclease-encoding cassettes and repair templates into the plant genome. In dicotyledonous plants, such as Nicotinana tabacum (tobacco) and Solanum lycopersicum (tomato), greater than 10-fold enhancements in GT frequencies have been achieved using DNA virus-based replicons. These replicons transiently amplify to high copy numbers in plant cells to deliver abundant SSNs and repair templates to achieve targeted gene modification. In the present work, we developed a replicon-based system for genome engineering of cereal crops using a deconstructed version of the wheat dwarf virus (WDV). In wheat cells, the replicons achieve a 110-fold increase in expression of a reporter gene relative to non-replicating controls. Furthermore, replicons carrying CRISPR/Cas9 nucleases and repair templates achieved GT at an endogenous ubiquitin locus at frequencies 12-fold greater than non-viral delivery methods. The use of a strong promoter to express Cas9 was critical to attain these high GT frequencies. We also demonstrate gene-targeted integration by homologous recombination (HR) in all three of the homoeoalleles (A, B and D) of the hexaploid wheat genome, and we show that with the WDV replicons, multiplexed GT within the same wheat cell can be achieved at frequencies of ~1%. In conclusion, high frequencies of GT using WDV-based DNA replicons will make it possible to edit complex cereal genomes without the need to integrate GT reagents into the genome.

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 functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site-specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches).

The development of reliable methods for the estimation of crown architecture parameters is a key issue for the quantitative evaluation of tree crop adaptation to environment conditions and/or growing system. In the present work, we developed and tested the performance of a method based on low-cost unmanned aerial vehicle (UAV) imagery for the estimation of olive crown parameters (tree height and crown diameter) in the framework of olive tree breeding programs, both on discontinuous and continuous canopy cropping systems. The workflow involved the image acquisition with consumer-grade cameras on board a UAV and orthomosaic and digital surface model generation using structure-from-motion image reconstruction (without ground point information). Finally, geographical information system analyses and object-based classification were used for the calculation of tree parameters. Results showed a high agreement between remote sensing estimation and field measurements of crown parameters. This was observed both at the individual tree/hedgerow level (relative RMSE from 6% to 20%, depending on the particular case) and also when average values for different genotypes were considered for phenotyping purposes (relative RMSE from 3% to 16%), pointing out the interest and applicability of these data and techniques in the selection scheme of breeding programs.

, nursery, at transplanting, post-transplanting), but there has been no evidence for a protocol better than another. Nonetheless, new bioformulation technologies (e.g., nanotechnology, formulation of microbial consortia and/or their metabolites, etc.) and tailor-made consortia of microbial strains should be encouraged. In conclusion, the literature offers many examples of promising BCAs, suggesting that biocontrol can greatly contribute to limit the damage caused by FWB. More efforts should be done to further validate the currently available outcomes, to deepen the knowledge on the most valuable BCAs, and to improve their efficacy by setting up effective formulations, application protocols, and integrated strategies.