Person:
Soba Hidalgo, David

Profile Picture

Email Address

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Soba Hidalgo

First Name

David

person.page.departamento

ORCID

person.page.upna

811354

Name

Filters

2021 - 20222
Reset filters

Settings

Author: Araus, José Luis ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationOpen Access
    Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models
    (Springer, 2022) Buchaillot, María Luisa; Soba Hidalgo, David; Shu, Tianchu; Liu, Juan; Aranjuelo Michelena, Iker; Araus, José Luis; Runion, G. Brett; Prior, Stephen A.; Kefauver, Shawn C.; Sanz Saez, Álvaro; IdAB. Instituto de Agrobiotecnología / Agrobioteknologiako Institutua
    One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties.
  • Thumbnail Image
    PublicationOpen Access
    Foliar heavy metals and stable isotope (δ13C, δ15N) profiles as reliable urban pollution biomonitoring tools
    (Elsevier, 2021) Soba Hidalgo, David; Gámez Guzmán, Angie Lorena; Úriz, Naroa; Ruiz de Larrinaga, Lorena; González Murua, Carmen; Becerril, José María; Esteban Terradillos, Raquel; Serret, Dolors; Araus, José Luis; Aranjuelo Michelena, Iker; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura
    Anthropogenic heavy metal pollution is an important health issue in urban areas, and therefore rapid and inexpensive monitoring in time and space is desirable. This study aimed (i) to assess the suitability of Tilia cordata leaves as a valuable heavy metal bioindicator, including seasonal changes in concentrations and (ii) to evaluate the use of leaf carbon and nitrogen isotope composition (δ13C and δ15N) as novel indicators of urban heavy metal pollution. Leaves were collected from three different pollution intensity locations (Bilbao, Vitoria, and Muskiz) in the Basque Country (northern Spain). Analysis of leaf heavy metals related to traffic emissions and δ13C and δ15N determinations were carried out during July-October 2018. Leaf samples from Bilbao, the most populated and traffic-intense location, showed the highest concentration of heavy metals (mainly from polluted air). Additionally, the two urban areas, Bilbao and Vitoria, showed stronger correlation between these heavy metals, indicating a traffic-related source of emissions. The source of contamination (soil or air) in relation to elements and optimal sampling time is discussed herein. On the other hand, Pearson correlation analysis revealed significant trends between leaf δ13C and δ15N and the studied heavy metals, especially Pb, Cr and Cd, supporting the hypothesis of δ13C and δ15N as tools to distinguish locations according to their heavy metal pollution levels. To our knowledge, this is the first time that δ13C and δ15N have been used as monitoring tools in heavy metal pollution and consequently more research is still needed to calibrate this tool through extensive vegetation screening.