BUSCADOR RECOLECTA

Achieving more environmentally sustainable vineyards, particularly regarding efficient water use, is paramount in semi-arid grape-growing regions. Rootstocks may be a possible strategy to address these challenges, but require a comprehensive evaluation of their effect on the scion, including ecophysiological traits. The objectives of this study were 1) to characterize the physiological response of Tempranillo cultivar grafted onto five commercial (1103 P, 110 R, 140Ru, 420 A, and SO4), and seven recently bred (RG2, RG3, RG4, RG6, RG7, RG8 and RG9) rootstocks and 2) to elucidate the relationships between agronomic and physiological traits conferred by grapevine rootstocks. This was carried out over three seasons (2018–2020) in a typical Mediterranean vineyard by determining water relations, leaf gas exchange, carbon isotope ratios and vegetative development and yield components. The results highlighted the different behaviour of ‘Tempranillo’ vines due to the rootstock effects on vine water status, photosynthetic performance, hydraulic conductance, vegetative growth and yield parameters. Overall, rootstocks inducing vigour and yield in the scion, such as 140Ru and RG8, showed higher leaf gas exchange rates and hydraulic conductance at the whole-plant level due to less negative water potentials, suggesting a higher water uptake and transport capacity than RG2, RG7 and RG9. The RG rootstocks showed a very wide range of ecophysiological responses, but only RG8 outperformed compared to the most widely used commercial rootstocks. Moreover, this response was modulated by the season and the block soil type, suggesting the importance of rootstock selection according to the edaphoclimatic conditions. Therefore, this study highlights the high potential of rootstocks to adapt to water scarcity by improving crop water productivity in vineyards and provides physiological insights for future studies and breeding programmes., This work has been financially
supported by the Spanish Ministry of Economy and Competitiveness
with FEDER co-financing, grant numbers AGL2017-83738-C3-1R
(WANUGRAPE), PDC2021-121210-C22 (WANUGRAPE4.0), and
PID2021–123305OB-C31 (UPGRAPE), and by the Government of Navarra (VIT-FEET and BEST-FEET, grant no. 0011-1365-2018-000106 and
0011-1365-2021-000068, respectively).

Choosing the most appropriate rootstock(s) is a key decision for the profitability of vineyards; therefore, there must be a sufficient range of
rootstocks in the market adapted to different environmental conditions and production objectives. However, rootstock-breeding programs
have been scarce in recent decades, and most of the rootstocks used today were bred a century ago, when the needs of the sector were very
different from today. In this work, we aimed to evaluate new rootstock candidates before their introduction in the market. An agronomic
evaluation was conducted on eight novel rootstock genotypes obtained from the first generation of the cross-pollination of 41 B Millardet et de
Grasset (41 B) and 110 Richter (110 R) grafted with ‘Syrah’ and ‘Tempranillo’ and planted in a typical vineyard of the Ebro Valley in Spain. During
the four consecutive growing seasons (2016e2019), growth, yield and berry composition parameters at harvest were collected. A linear mixedeffects model was constructed, considering year and block as random effects. Multiple factor analysis and hierarchical clustering on principal
components were performed to establish clusters of genotypes with similar behaviour. The rootstock candidates showed a very wide performance range compared to their parents. The trial allowed us to identify two very promising candidates (RG8 and RG10), whose registration
as commercial rootstocks is already in progress., This work was performed with the financial support of the
Department of Economic Development of the Government of
Navarra (Vit-Foot, Ref.: 0011-1365-2016-000079 and Vit-Feet, Ref.:
0011-1365-2018-000106, projects co-funded with FEDER funds)
and the Spanish Ministry of Science and Technology (project AGL
2017-83738-C3-1-R). Diana Marín is beneficiary of postgraduate
scholarship funded by Public University of Navarre (FPI-UPNA-
2017). Francisco Javier Abad is beneficiary of postgraduate
scholarship funded by INIA (FPI-INIA-2016).

Precise and reliable identification of specific plant diseases is a challenge within precision agriculture nowadays. This is the case of esca, a complex grapevine trunk disease, that represents a major threat to modern viticulture as it is responsible for large economic losses annually. The lack of effective control strategies and the complexity of esca disease expression make essential the identification of affected plants, before symptoms become evident, for a better management of the vineyard. This study evaluated the suitability of a near-infrared hyperspectral imaging (HSI) system to detect esca disease in asymptomatic grapevine leaves of Tempranillo red-berried cultivar. For this, 72 leaves from an experimental vineyard, naturally infected with esca, were collected and scanned with a lab-scale HSI system in the 900-1700 nm spectral range. Then, effective image processing and multivariate analysis techniques were merged to develop pixel-based classification models for the distinction of healthy, asymptomatic and symptomatic leaves. Automatic and interval partial least squares variable selection methods were tested to identify the most relevant wavelengths for the detection of esca-affected vines using partial least squares discriminant analysis and different pre-processing techniques. Three-class and two-class classifiers were carried out to differentiate healthy, asymptomatic and symptomatic leaf pixels, and healthy from asymptomatic pixels, respectively. Both variable selection methods performed similarly, achieving good classification rates in the range of 82.77-97.17% in validation datasets for either three-class or two-class classifiers. The latter results demonstrated the capability of hyperspectral imaging to distinguish two groups of seemingly identical leaves (healthy and asymptomatic). These findings would ease the annual monitoring of disease incidence in the vineyard and, therefore, better crop management and decision making., This research was supported by Public University of Navarre postgraduate scholarships (FPI-UPNA-2017), by the Spanish Ministry of Economy and Competitiveness (AGL2017-83738-C3-1R, AEI/EU-FEDER), and by the Spanish Ministry of Science, Innovation and Universities (PID2019-108392GB-I00, AEI/10.13039/ 501100011033).

The selection of genotypes best adapted to environmental conditions has traditionally focused on agronomic and grape composition parameters. However, to classify the genotypes most adapted to climate change conditions, the aim must be to focus on the ecophysiological responses that will ultimately determine their performance. The variability in water use efficiency of 13 Grenache genotypes over three-seasons was assessed under field conditions at leaf, grape and plant level. Results showed a significant effect of genotype at all three levels, and despite the large interannual variability there was a remarkable consistency among levels. Furthermore, using genotype-specific regressions it was possible to identify significant differences in the intrinsic water use efficiency response of each genotype as a function of the vine water status. The relationship between net photosynthesis and stomatal conductance, as well as carbon isotope discrimination in grapes, were also confirmed as reliable physiological indicators for selecting grapevine genotypes to future environmental conditions. Therefore, the proposed multi-level methodology was useful to quantify the intracultivar variability and the identification of more and less efficient genotypes within Grenache., I. Buesa acknowledges the funding of his postdoctoral position to Margalida Comas program (European Social Fund and the Government of the Balearic Islands). This study received the financial support of Spanish Ministry of Economy and Competitiveness with FEDER co‐funding [WANUGRAPE. AGL2017‐83738‐C3‐1R].