308 research outputs found
Ecophysiological Recovery of Micropropagated Olive Cultivars: Field Research in an Irrigated Super-High-Density Orchard
No full textThis research focuses on the seasonal patterns of the ecophysiological recovery of four olive cultivars (Arbequina, Coratina, Frantoio, and Urano), both micropropagated and self-rooted, grown in a mature, irrigated, super high-density (SHD) orchard under Mediterranean conditions (Southern of Italy). The aim was to observe the impact of the micropropagation method on the ecophysiological responses. Ecophysiological parameters, including leaf water potential (LWP), stomatal conductance (gs), net photosynthetic rate (Pn), and transpiration rate (E) were assessed. Self-rooted trees consistently exhibited superior gs, E, and Pn recovery compared to the micropropagated ones. ‘Arbequina’ maintained elevated levels of Pn under water-deficit conditions. ‘Coratina’ exhibited increases in gs and E after irrigation. ‘Frantoio’ demonstrated recovery capabilities, with lower LWP and higher Pn under stress. ‘Urano’ micropropagated trees achieved higher gs values in mid-summer, while self-rooted trees sustained higher Pn later in the season. This field research highlighted the important role of the propagation method in optimizing the physiological performance of olive cultivars in SHD orchards. Furthermore, it highlighted the necessity of long-term studies on the effects of propagation methods and their interactions with other farming practices
Ecological optima show the potential diffusion of minor tree crops in Xylella fastidiosa subsp. pauca-infected areas through a GIS-based approach
No full textSite selection analysis is a fundamental methodology for the regeneration of Xylella fastidiosa subsp. pauca (Xfp) infected areas, with the introduction of Xfp immune/resistant tree crop species. The diffusion of these species could be assessed by combining ecological optima data, climate and soil attributes of the study area, and GIS tools. The study aimed to evaluate the potential suitability of eight Xfp immune tree crops, including Neglected and Underutilized Species (NUS) drought-resistant and new species, as follows: carob, hawthorn, prickly pear, mulberry, loquat, walnut, persimmon, and avocado. The use of GIS tools allowed the integration of different layers, such as climate and soil, to contribute to the identification of suitable areas for the cultivation of these tree crops helping the policy-makers to define plans for land use at a regional scale. Following the ecological optima, which represents the ideal environmental conditions for each species, this analysis provided valuable insights into the compatibility of the selected tree crops with the prevailing environmental factors in the affected area. Carob revealed its remarkable adaptability and drought resistance, presenting the broadest suitability. Hawthorn and Loquat also exhibited high adaptability, indicating their potential contribution to agricultural diversification and ecological balance. Conversely, crops like Avocado, Prickly pear, and Walnut, despite their economic value, demonstrated limited adaptability due to their specific soil and climate requirements. These findings can potentially contribute to the development of strategies for the policy-makers, aimed at diversifying and enhancing the resilience of agricultural systems, facing the problem of emerging quarantine pathogens and the incoming climate change, and highlighting the possibility of opening new cultivation scenarios in the zones affected by Xfp
Physical Ripening Indices Improve the Assessment of Mechanical Harvesting Time for Olive Cultivars Resistant to Xylella fastidiosa subsp. pauca
No full textXylella fastidiosa subsp. pauca (Xfp) is a significant threat to Mediterranean agriculture,
particularly impacting olive trees in southern Italy, causing Olive Quick Decline Syndrome. Resistant
olive cultivars, such as ‘Leccino’ and ‘Fs-17’, have been identified as alternatives to restore the oliviculture
within the infected areas. ‘Frantoio’ and ‘Cipressino’ are included in ongoing studies on genetic
resistance to Xfp. The mechanization of olive harvesting is essential for reducing production costs in
the olive oil sector. Two systems, trunk shakers and over-the-row machines, are used depending on
the tree density and canopy structure, with super-high-density systems offering advantages in terms
of cost and efficiency. This study investigates the feasibility of using simple and non-destructive
indices to assess the optimal mechanical harvesting time. Different physical ripening indices, including
detachment force, fresh weight, pigmentation, and firmness, were measured on four olive
cultivars (‘Fs-17’, ‘Leccino’, ‘Frantoio’, ‘Cipressino’) in southern Italy over two years. The study found
that the pigmentation index had a strong relationship with the detachment index, particularly for
‘Fs-17’, and ‘Leccino’, providing a reliable non-destructive measure for optimal harvesting time. The
results indicate that the optimal harvesting times for mechanical harvesting are early September for
‘Cipressino’, early October for ‘Fs-17’, and mid-October for ‘Frantoio’ and ‘Leccino’
Use of explainable artificial intelligence with high-resolution satellite imagery to assess water status and vine shoot growth in grapevine (Vitis vinifera L.)
No full textGrapevine is an essential socio-economic crop in the Mediterranean regions. However, its cultivation is threatened by
climate change, particularly due to the increase in drought events. Traditional indicators of plant water status, i.e., predawn leaf water potential (Ψpd), are helpful but labor-intensive. Furthermore, another index based on visual assessment
of the shoot apex (i.e., iG-Apex), has been recently used to evaluate the water stress of grapevine plants. The application
of remote sensing technologies and machine learning models gives the possibility to monitor grapevine spatio-temporal
variability of plant physiological indicators in a non-destructive way. This study aims to develop an explainable artificial
intelligence (XAI) framework to predict Ψpd and iG-Apex in two rainfed vineyards using high-resolution multispectral
imagery from the Planet SuperDove constellation. Five machine learning models—extreme gradient boosting, random forest, support vector regressor, ElasticNet, and Linear Regression—were trained and compared. Extreme gradient boosting
achieved the best performance for Ψpd prediction (R2 = 0.778), while random forest outperformed for iG-Apex prediction
(R2 = 0.615). SHAP and ICE analyses were carried out for models’ explainability. The analyses revealed that visible and
NIR bands were the most important predictors, influencing both Ψpd and iG-Apex prediction. Our results highlight the
potential of combining XAI and remote sensing to support grapevine management under Mediterranean conditions, providing a useful tool for early water stress detection
Performance of the Fermi-LAT silicon strip tracker after 14 years of operation
No full textThe Large Area Telescope (LAT) is the primary instrument onboard the Fermi Gamma-ray Space Telescope launched on June 11 2008. It is an imaging, wide field-of-view, gamma-ray telescope, covering the energy range from 30 MeV to more than 300 GeV. The LAT tracker is formed by silicon strip planes alternated with tungsten foils and is used to convert the incoming photon into an electron-positron pair and to measure its direction. Here we describe the performance of the LAT tracker, that has been constantly monitored using calibration and science data. In particular we show that, after almost 14 years of continuous operation in space, the fraction of defective channels is less than 0.5% while the readout noise increased less than 5%
Gamma-ray blazar spectra with H.E.S.S. II mono analysis: The case of PKS 2155-304 and PG 1553+113
No full textArchitectural approach to evaluate the design and management of almond cultivars suitable for super high-density orchards
No full textIntroductionThe almond tree is a major global nut crop, and its production has surged dramatically in recent years. Super high-density (SHD) planting systems, designed to optimize resource efficiency and enhance precocity, have gained prominence in almond cultivation. A shift in cropping systems toward sustainable intensification (SI) pathways is imperative, and so maximizing branching density within the canopies of SHD trees is crucial to establish and maintain productive potential, especially for hedge-pruned trees. This study investigates the influence of different almond cultivars grafted onto a novel growth-controlling rootstock on tree architectural and growth parameters in a SHD orchard. This open field research provided valuable insights for the development and application of new tools and methods to increase productivity and sustainability in almond growing.MethodsThree cultivars (Lauranne® Avijour, Guara Tuono, and Filippo Cea) were evaluated in Gravina in Puglia (BA) over a two-year period. Canopy growth parameters, such as canopy volume and trunk cross-sectional area, and architectural traits, like branching density, branching angle, number and length of subterminal shoots, and number of brachyblasts, were measured through qualitative and quantitative measurements.Results and discussionResults revealed significant differences in tree height, canopy thickness, width, volume, and vigor among the cultivars. Architectural traits, including branch parameters, brachyblast parameters, and subterminal shoots, varied among the cultivars. Lauranne displayed a more compact well-distributed canopy and exhibited the lowest vigor. Filippo Cea showed the highest vigor and the greatest canopy volume. Tuono had a higher number of buds and bud density. The best ideotype for SHD orchards is a smaller tree, with high branching density and smaller trunk diameters, i.e. the vigor. Cv. Lauranne seemed to be the best cultivar, mostly with the lowest tree vigor of all the cultivars involved. These findings provide valuable insights for almond growers and breeders seeking to optimize orchard design and management for enhanced SHD orchards productivity and sustainability. Future research will explore the relationship between canopy architecture and yield parameters, considering different scion/rootstock combinations in different environmental conditions
Polarization Properties of the Weakly Magnetized Neutron Star X-Ray Binary GS 1826–238 in the High Soft State
No full textCapitanio, Fiamma et al.--Full list of authors: Capitanio, Fiamma; Fabiani, Sergio; Gnarini, Andrea; Ursini, Francesco; Ferrigno, Carlo; Matt, Giorgio; Poutanen, Juri; Cocchi, Massimo; Mikusincova, Romana; Farinelli, Ruben; Bianchi, Stefano; Kajava, Jari J. E.; Muleri, Fabio; Sanchez-Fernandez, Celia; Soffitta, Paolo; Wu, Kinwah; Agudo, Ivan; Antonelli, Lucio A.; Bachetti, Matteo; Baldini, Luca; Baumgartner, Wayne H.; Bellazzini, Ronaldo; Bongiorno, Stephen D.; Bonino, Raffaella; Brez, Alessandro; Bucciantini, Niccolo; Castellano, Simone; Cavazzuti, Elisabetta; Ciprini, Stefano; Costa, Enrico; De Rosa, Alessandra; Del Monte, Ettore; Di Gesu, Laura; Di Lalla, Niccolo; Di Marco, Alessandro; Donnarumma, Immacolata; Doroshenko, Victor; Dovciak, Michal; Ehlert, Steven R.; Enoto, Teruaki; Evangelista, Yuri; Ferrazzoli, Riccardo; Garcia, Javier A.; Gunji, Shuichi; Hayashida, Kiyoshi; Heyl, Jeremy; Iwakiri, Wataru; Jorstad, Svetlana G.; Karas, Vladimir; Kitaguchi, Takao; Kolodziejczak, Jeffery J.; Krawczynski, Henric; La Monaca, Fabio; Latronico, Luca; Liodakis, Ioannis; Maldera, Simone; Manfreda, Alberto; Marin, Frederic; Marinucci, Andrea; Marscher, Alan P.; Marshall, Herman L.; Mitsuishi, Ikuyuki; Mizuno, Tsunefumi; Ng, C. -Y.; O'Dell, Stephen L.; Omodei, Nicola; Oppedisano, Chiara; Papitto, Alessandro; Pavlov, George G.; Peirson, Abel L.; Perri, Matteo; Pesce-Rollins, Melissa; Petrucci, Pierre-Olivier; Pilia, Maura; Possenti, Andrea; Puccetti, Simonetta; Ramsey, Brian D.; Rankin, John; Ratheesh, Ajay; Romani, Roger W.; Sgro, Carmelo; Slane, Patrick; Spandre, Gloria; Tamagawa, Toru; Tavecchio, Fabrizio; Taverna, Roberto; Tawara, Yuzuru; Tennant, Allyn F.; Thomas, Nicholas E.; Tombesi, Francesco; Trois, Alessio; Tsygankov, Sergey S.; Turolla, Roberto; Vink, Jacco; Weisskopf, Martin C.; Xie, Fei; Zane, SilviaThe launch of the Imaging X-ray Polarimetry Explorer (IXPE) on 2021 December 9 has opened a new window in X-ray astronomy. We report here the results of the first IXPE observation of a weakly magnetized neutron star, GS 1826−238, performed on 2022 March 29–31 when the source was in a high soft state. An upper limit (99.73% confidence level) of 1.3% for the linear polarization degree is obtained over the IXPE 2–8 keV energy range. Coordinated INTEGRAL and NICER observations were carried out simultaneously with IXPE. The spectral parameters obtained from the fits to the broadband spectrum were used as inputs for Monte Carlo simulations considering different possible geometries of the X-ray emitting region. Comparing the IXPE upper limit with these simulations, we can put constraints on the geometry and inclination angle of GS 1826–238. © 2023. The Author(s). Published by the American Astronomical Society.J.P. and S.S.T. acknowledge support from Russian Science Foundation grant 20-12-00364 and Academy of Finland travel grants 349144, 349373, and 349906. J.P. and J.J.E.K. were supported by Academy of Finland grant 333112.Peer reviewe
- …
