Angela Iori

Dr. Angela Iori


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 April 2020 in Biomolecules
Verified
Journal Article
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VSValeria Scala
Valeria Scala
CPChiara Pietricola
Chiara Pietricola
VFValentina Farina
Valentina Farina
MBMarzia Beccaccioli
Marzia Beccaccioli
SZSlaven Zjalic
Slaven Zjalic
AIAngela Iori
Angela Iori
The Septoria Leaf Blotch Complex (SLBC), caused by the two ascomycetes Zymoseptoria tritici and Parastagonospora nodorum, can reduce wheat global yearly yield by up to 50%. In the last decade, SLBC incidence has increased in Italy; notably, durum wheat has proven to be more susceptible than common wheat. Field fungicide treatment can efficiently control these pathogens, but it leads to the emergence of resistant strains and adversely affects human and animal health and the environment. Our previous studies indicated that active compounds produced by Trametes versicolor can restrict the growth of mycotoxigenic fungi and the biosynthesis of their secondary metabolites (e.g., mycotoxins). Specifically, we identified Tramesan: a 23 kDa α-heteropolysaccharide secreted by T. versicolor that acts as a pro-antioxidant molecule in animal cells, fungi, and plants. Foliar-spray of Tramesan (3.3 μM) on SLBC-susceptible durum wheat cultivars, before inoculation of causal agents of Stagonospora Nodorum Blotch (SNB) and Septoria Tritici Blotch (STB), significantly decreased disease incidence both in controlled conditions (SNB: −99%, STB: −75%) and field assays (SNB: −25%, STB: −30%). We conducted these tests were conducted under controlled conditions as well as in field. We showed that Tramesan increased the levels of jasmonic acid (JA), a plant defense-related hormone. Tramesan also increased the early expression (24 hours after inoculation—hai) of plant defense genes such as PR4 for SNB infected plants, and RBOH, PR1, and PR9 for STB infected plants. These results suggest that Tramesan protects wheat by eliciting plant defenses, since it has no direct fungicidal activity. In field experiments, the yield of durum wheat plants treated with Tramesan was similar to that of healthy untreated plots. These results encourage the use of Tramesan to protect durum wheat against SLBC.

12 June 2024 in Agronomy
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Journal Article
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PVPatrizia Vaccino
Patrizia Vaccino
Maurizio AntonettiMaurizio Antonetti
Maurizio Antonetti
CBCarlotta Balconi
Carlotta Balconi
ABAndrea Brandolini
Andrea Brandolini
Silvia CappellozzaSilvia Cappellozza
Silvia Cappellozza
IVIgnazio Verde
Ignazio Verde
Conservation, characterization and exploitation of agrobiodiversity are key factors to guarantee food security and face future challenges such as climate changes. These issues are the subject of a series of international agreements, such as the Convention of Biological Diversity, with its Nagoya Protocol, and the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA) adopted in 2001 and entered into force in 2004. Italy ratified the Treaty in 2004 and instituted a long-lasting program, RGV-FAO, to implement it. CREA is one of the three organizations involved in the RGV-FAO Program, together with the National Research Council (CNR) and Reti Semi Rurali. CREA maintains a total of 40,186 accessions including cereals, vegetables, fruits, forages, industrial crops, forest and woody crops, medicinal and aromatic plants, and their wild relatives. Accessions are conserved using different ex situ conservation systems (seeds, in vivo plants, vegetative organs and in vitro plantlets), and characterized using genetic, morpho-phenological and/or biochemical methods. Herein, we will present the CREA long-lasting program RGV-FAO with some examples of the use of plant genetic resources in breeding programs, including molecular approaches. Some critical issues related to access and benefit sharing in PGRFA, such as the Nagoya Protocol and the Digital Sequence Information, will be discussed, highlighting their potential impact on food security and on the advancement of knowledge.

17 May 2026 in Agriculture
Verified
Journal Article
Open access
PDF file
ACALESSANDRO CAMMERATA
ALESSANDRO CAMMERATA
VFViviana Del Frate
Viviana Del Frate
AIAngela Iori
Angela Iori
Francesco GallucciFrancesco Gallucci
Francesco Gallucci
Early and non-destructive identification of fungal contamination in cereals is essential to support post-harvest management, reduce economic losses, and mitigate food safety risks along the wheat supply chain. Among filamentous fungi, Alternaria spp. are widespread contaminants of durum wheat and producers of toxic secondary metabolites such as alternariol (AOH), whose early detection remains analytically challenging. The aim of this study was to evaluate the potential of near-infrared transmittance (NIT) spectroscopy as a rapid, non-destructive pre-screening tool for the early identification of Alternaria-contaminated durum wheat lots and associated AOH risk. Samples from three durum wheat cultivars were artificially inoculated with Alternaria spp. and monitored over time. NIT spectra (570–1100 nm) were acquired in transmittance mode and analyzed using partial least squares (PLS) regression, focusing on the 870–1100 nm spectral region. Clear and time-dependent spectral differences were observed between inoculated and control samples, with the strongest discriminative features at 834 and 966 nm. Classification performance was high, with area under the curve (AUC) values between 0.96 and 0.97. ELISA analysis confirmed progressive AOH accumulation in inoculated kernels, consistent with the observed spectral changes, while control experiments excluded autoclaving and visual grain damage as confounding factors. From an applied perspective, the results indicate that NIT spectroscopy can support post-harvest decision-making as a rapid pre-screening approach, enabling the prioritization of suspect wheat lots for confirmatory analytical testing. Multivariate analysis further confirmed the consistency of spectral differences across datasets.