Método de segmentación de cultivos

Se describe un método de distribución espacial continua de la calidad del fruto dentro de una parcela de cultivo o una finca comercial que permite la segmentación de dicha finca en sectores de distinta calidad, por lo tanto las zonas con mayor precio de mercado pueden ser recolectadas independientemente; permitiendo al agricultor obtener un mapa de calidad completo de sus cultivos previo a la organización de la recolección del fruto.Peer reviewedConsejo Superior de Investigaciones CientíficasA1 Solicitud de patente con informe sobre el estado de la técnic

Genetic dissection of agronomic and quality traits based on association mapping and genomic selection approaches in durum wheat grown in Southern Spain

Climatic conditions affect the growth, development and final crop production. As wheat is of paramount importance as a staple crop in the human diet, there is a growing need to study its abiotic stress adaptation through the performance of key breeding traits. New and complementary approaches, such as genome-wide association studies (GWAS) and genomic selection (GS), are used for the dissection of different agronomic traits. The present study focused on the dissection of agronomic and quality traits of interest (initial agronomic score, yield, gluten index, sedimentation index, specific weight, whole grain protein and yellow colour) assessed in a panel of 179 durum wheat lines (Triticum durum Desf.), grown under rainfed conditions in different Mediterranean environments in Southern Spain (Andalusia). The findings show a total of 37 marker-trait associations (MTAs) which affect phenotype expression for three quality traits (specific weight, gluten and sedimentation indexes). MTAs could be mapped on the A and B durum wheat subgenomes (on chromosomes 1A, 1B, 2A, 2B and 3A) through the recently available bread wheat reference assembly (IWGSC RefSeqv1). Two of the MTAs found for quality traits (gluten index and SDS) corresponded to the known Glu-B1 and Glu-A1 loci, for which candidate genes corresponding to high molecular weight glutenin subunits could be located. The GS prediction ability values obtained from the breeding materials analyzed showed promising results for traits as grain protein content, sedimentation and gluten indexes, which can be used in plant breeding programs.Junta de Andalucía (Andalusian Regional Government) P12- AGR-0482FEDER P12- AGR-0482MINECO (Spanish Ministry of Economy, Industry and Competitiveness) AGL2016-77149-C2-1-

Quantitative analysis of almond yield response to irrigation regimes in Mediterranean Spain

Almond plantations are expanding worldwide, specifically in Spain; the new orchards are often designed under more intensive systems in comparison to the traditional rainfed orchards frequently found in the Mediterranean Sea basin. In these new areas, water is the main limiting factor, and therefore, the present research is aimed at quantitatively analyzing previous findings obtained in irrigation field trials carried out in Spain with mature almond trees. The goal was to derive applied water-production functions and compare sustained and regulated deficit irrigation strategies to provide robust information on the marginal water productivity and the preferred irrigation option to be applied under water scarcity conditions. This quantitative analysis reported a yield increase as water application increased, with the highest potential yield of about 2500 kg/ha achieved with around 1000 mm of irrigation water applied. Under severe water restrictions, similar responses were observed regardless of the deficit irrigation technique employed. In contrast, under moderate water stress, it seems more advantageous to apply a regulated deficit irrigation strategy rather than a sustained deficit strategy. The reported results are useful for deriving more sustainable irrigation protocols and highlight the need to optimize other inputs in addition to water to take full advantage of the irrigation intensification to be carried out in the new almond plantations.Publishe

Modelling canopy conductance and transpiration of fruit trees in Mediterranean areas: a simplified approach

Improving current approaches to quantify the transpiration of fruit trees is needed for water allocation purposes and to enhance the precision of water applications under full and deficit irrigation. Given that transpiration of tree crops is mainly modulated by canopy conductance (Gc) and vapour pressure deficits, we developed a functional model of tree transpiration by quantifying an average daily Gc based on radiation use efficiency and CO2 assimilation. For model calibration, an extensive experimental dataset of tree transpiration (Ep) was collected in many of the main temperate fruit tree species, namely, apricot, apple, citrus, olive, peach, pistachio, and walnut, all under non-limiting water conditions, in different orchards in Spain and California (USA). In all species, Ep was assessed by measuring sap flux with the Compensation Heat Pulse method for several months, and a transpiration coefficient (Kt) was calculated as the ratio of measured Ep to the reference evapotranspiration. For three deciduous species (apricot, peach and walnut) Kt showed maximum values close to 1, a value which stayed more or less constant throughout the summer in peach and walnut. The maximum Kt values were measured in pistachio (1.14) while they only reached 0.35 in olive and citrus trees. In the latter two species, Kt varied seasonally between 0.2 and 0.6 depending on the weather. The average Gc in July was high for apple, walnut, peach and pistachio (range 0.240-0.365 mol m-2 s-1) and low for olive and orange (range 0.074-0.100 mol m-2 s-1). The calibrated model outputs were compared against measured Ep data, suggesting the satisfactory performance of a functional model for Ep calculation that should improve the precision of current empirical approaches followed to compute fruit tree water requirement

High-resolution imagery acquired from an unmanned platform to estimate biophysical and geometrical parameters of olive trees under different irrigation regimes

The experiments were conducted in a fully-productive olive orchard (cv. Frantoio) at the experimental farm of University of Pisa at Venturina (Italy) in 2015 to assess the ability of an unmanned aerial vehicle (UAV) equipped with RGB-NIR cameras to estimate leaf area index (LAI), tree height, canopy diameter and canopy volume of olive trees that were either irrigated or rainfed. Irrigated trees received water 4–5 days a week (1348 m3 ha-1), whereas the rainfed ones received a single irrigation of 19 m3 ha-1 to relieve the extreme stress. The flight altitude was 70 m above ground level (AGL), except for one flight (50 m AGL). The Normalized Difference Vegetation Index (NDVI) was calculated by means of the map algebra technique. Canopy volume, canopy height and diameter were obtained from the digital surface model (DSM) obtained through automatic aerial triangulation, bundle block adjustment and camera calibration methods. The NDVI estimated on the day of the year (DOY) 130 was linearly correlated with both LAI and leaf chlorophyll measured on the same date (R2 = 0.78 and 0.80, respectively). The correlation between the on ground measured canopy volumes and the ones by the UAV-RGB camera techniques yielded an R2 of 0.71–0.86. The monthly canopy volume increment estimated from UAV surveys between (DOY) 130 and 244 was highly correlated with the daily water stress integral of rainfed trees (R2 = 0.99). The effect of water stress on the seasonal pattern of canopy growth was detected by these techniques in correspondence of the maximum level of stress experienced by the rainfed trees. The highest level of accuracy (RMSE = 0.16 m) in canopy height estimation was obtained when the flight altitude was 50 m AGL, yielding an R2 value of 0.87 and an almost 1:1 ratio of measured versus estimated canopy height

Divergent abiotic spectral pathways unravel pathogen stress signals across species

Plant pathogens pose increasing threats to global food security, causing yield losses that exceed 30% in food-deficit regions. Xylella fastidiosa (Xf) represents the major transboundary plant pest and one of the world’s most damaging pathogens in terms of socioeconomic impact. Spectral screening methods are critical to detect non-visual symptoms of early infection and prevent spread. However, the subtle pathogen-induced physiological alterations that are spectrally detectable are entangled with the dynamics of abiotic stresses. Here, using airborne spectroscopy and thermal scanning of areas covering more than one million trees of different species, infections and water stress levels, we reveal the existence of divergent pathogen- and host-specific spectral pathways that can disentangle biotic-induced symptoms. We demonstrate that uncoupling this biotic–abiotic spectral dynamics diminishes the uncertainty in the Xf detection to below 6% across different hosts. Assessing these deviating pathways against another harmful vascular pathogen that produces analogous symptoms, Verticillium dahliae, the divergent routes remained pathogen- and host-specific, revealing detection accuracies exceeding 92% across pathosystems. These urgently needed hyperspectral methods advance early detection of devastating pathogens to reduce the billions in crop losses worldwide.The study was partially funded by the European Union’s Horizon 2020 Research and Innovation Programme through grant agreements POnTE (635646) and XF-ACTORS (727987), as well as by projects AGL2009-13105 from the Spanish Ministry of Education and Science, P08-AGR-03528 from the Regional Government of Andalusia and the European Social Fund, project E-RTA2017-00004-02 from ‘Programa Estatal de I + D + I Orientada a los Retos de la Sociedad’ of Spain and FEDER, Intramural Project 201840E111 from CSIC, and Project ITS2017-095 Consejeria de Medio Ambiente, Agricultura y Pesca de las Islas Baleares, Spain. The views expressed are purely those of the writers and may not in any circumstance be regarded as stating an official position of the European Commission

Progress and achievements on the early detection of Xylella fastidiosa infection and symptom development with hyperspectral and thermal remote sensing imagery

Trabajo presentado en la 3rd European Conference on Xylella fastidiosa (Building knowledge, protecting plant health), celebrada online el 29 y 30 de abril de 2021.Remote sensing efforts made as part of European initiatives via POnTE, XF-ACTORS and the JRC, as well as through regional programs, have focused, among others, on the development of algorithms for the early detection of Xylella fastidiosa (Xf)-induced symptoms. Airborne campaigns carried out between 2016 and 2019 collected high-resolution hyperspectral and thermal images from infected areas in the Apulia region (Italy), in the province of Alicante and on the island of Mallorca (Spain). The remote sensing imagery collections were performed alongside field surveys and laboratory analyses to assess the presence of Xf, and the severity and incidence of disease in olive and almond trees. Radiative transfer models and machine learning algorithms were used to quantify spectral plant traits for each individual infected tree, assessing their importance as pre visual indicators of Xf-induced stress. These studies conducted across species have demonstrated that specific spectral plant traits successfully revealed Xf induced symptoms at early stages, i.e., before visual symptoms appear. The results show that spectral plant traits contribute differently to symptom detection across host species (olive vs. almond), and that abiotic-induced stress affects the performance of the algorithms used for detecting infected trees. Together, the different European initiatives studying the use of remote sensing to support the monitoring of landscapes for Xylella fastidiosa detection lead us to conclude that the early detection of Xf-induced symptoms is feasible when high-resolution hyperspectral imagery and physically-based plant trait retrievals are used, obtaining accuracies exceeding 92% (kappa>0.8). These results are essential to enable the implementation of effective control and management of plant diseases using airborne- droneand satellite-based remote sensing technologies. Moreover, these large-scale hyperspectral and thermal imaging methods greatly contribute to the future operational monitoring of infected areas at large scales, well beyond what is possible from field surveys and laboratory analyses alone

The influence of arbuscular mycorrhizal colonization on soil-root hydraulic conductance in Agrostis stolonifera L. under two water regimes

The hypothesis that mycorrhizal colonization improves the soil-root conductance in plants was experimentally tested in a growth chamber using pot cultures of Agrostis stolonifera L. colonized by Glomus intraradices. Plants were grown in 50-l pots filled with autoclaved sand/silt soil (1:1), with and without the mycorrhizal fungus. Within the mycorrhizal treatment, half of the pots remained well watered, while the other half was subjected to a progressive water deficit. Soil water potential (estimated as plant water potential measured at the end of the dark period), xylem water potential measured at the tiller base, transpiration rate, and soil water content were monitored throughout the experiment. Soil-root hydraulic conductance was estimated as the ratio between the instantaneous transpiration rate and the soil and xylem water potential difference. To obtain cultures with similar nutritional status, the P in the modified Hoagland's nutrient solution was withheld from the inoculated pots and applied only once a month. Even though there were no differences on growth or nutrient status for the mycorrhizal treatments, water transport was enhanced by the inoculum presence. Transpiration rate was maintained at lower xylem water potential values in the presence of mycorrhizae. The analysis of the relationship between soil-root hydraulic resistance and soil water content showed that mycorrhizal colonization increased soil-root hydraulic conductance as the soil dried. For these growing conditions, this effect was ascribed to the range of 6-10%. © 2009 Springer-Verlag.This work was supported by MYCOSYM-TRITON S.L. ® and by the Spanish Ministry of Science and Innovation (CONSOLIDER-RIDECO CSD2006-00067).Peer Reviewe

Uso de la termografía para la monitorización del estado hídrico y las necesidades de riego den cultivos leñosos

Seminario Ibero-Brasileño de Agricultura de Regado (Seminário Ibero-Brasileiro de Agricultura Irrigada, online, 11 y 12 de mayo de 2021

Improving the Precision of Irrigation Using High-Resolution Thermal Imagery

Trabajo presentado en la 2019 ASA-CSSA-SSSA International Annual Meeting, celebrada en San Antonio (Texas) del 10 al 13 de noviembre de 2019.The prospects of water scarcity are increasing in many areas in the world, adding more pressure for irrigated agriculture to minimize water losses and maximize water productivity. The improvements in irrigation system design and operation do not address the issues of soil and plant heterogeneity and associated variations in water demands within irrigation management units. There has been a tendency in recent decades towards increasing the size of management units to reduce labor inputs and simplify management; this approach increases the risk of widening the spatial variability within the management units. This variation relies upon static sources, such as soil properties, while others are dynamic, such as irrigation dose, plant size, and plant health. Traditional approaches proposed to manage the variability in the system design have primarily minimized differences in soil type and topography within irrigation units (map-based approach). However, multiple sources of variation are difficult to address using this approach because they are not static. Sensor-based approaches meeting the required resolutions and turnaround times provide an efficient tool to assess dynamic variations within agricultural fields. Thermal imaging acquired from UAVs or manned aircraft fulfill the requested accuracy and flexibility to deal with such dynamic variability due to the close link to transpiration. Water stress induces stomatal closure, reduces evaporative cooling and increases leaf temperature. The influence of evaporative demand on canopy temperature via air temperature and the vapor pressure deficit requires its normalization, which can be carried out using the Crop Water Stress Index (CWSI). This thermal-based approach allows conducting comparative studies in the spatial domain, but more interestingly, temporally. The opportunities derived from the analysis of the temporal and spatial variability will be reviewed, highlighting the main avenues to optimize water use in irrigated agriculture.Peer reviewe