Molecular Characterization of Diaporthe Species Associated With Hazelnut Defects

Synergistic Recruitment of Symbiotic Fungi by Potting and Scleroderma bovista Inoculation Suppresses Pathogens in Hazel Rhizosphere Microbiomes

This study explored how potted treatments (with and without Scleroderma bovista inoculation) shape rhizosphere microbial diversity in hazel across five soils using split-root cultivation. Three treatments (control, split-root, split-root with S. bovista) were analyzed for root growth and microbial dynamics. S. bovista inoculation consistently enhanced root parameters (number, tips) in all soils. Potted treatments (with and without S. bovista inoculation) altered microbial features (OTU/ASV), with only 0.9-3.3% of features remaining unchanged. At the class level, potting increased Agaricomycetes abundance while reducing Sordariomycetes, a trend amplified by S. bovista. Potting decreased species richness estimates (ACE and Chao1), while both treatments lowered diversity index (Shannon index). Potted treatments without S. bovista inoculation drove stronger shifts in species composition than inoculation. Findings reveal potting and S. bovista synergistically recruit symbiotic fungi via root exudates, establishing disease-suppressive communities that selectively inhibit pathotrophic fungi (particularly plant pathogen Coniothyrium and fungal parasite Cladobotryum) while roughly maintaining non-pathogenic saprotrophic microbes essential for organic matter decomposition. This work provides insights for optimizing hazel orchard management and ectomycorrhizal agent development.

Fusarium and Hazelnut: A Story of Twists and Turns

In recent years, the number of reports of Fusarium in association with hazelnut (Corylus avellana) has been increasing worldwide, related to both pathogenic aptitude and endophytic occurrence. However, the assessment of the real ecological role and relevance to plant health of these fungi has been impaired by uncertainty in species identification, deriving from both the evolving taxonomic structure of the genus and an inaccurate use of molecular markers. In this paper, the characterization of two hazelnut endophytic strains isolated in Poland is reported with reference to their secondary metabolite profiles and interactions with pests and pathogens. Our results are indicative of a possible role of these strains in defensive mutualism which could be related to the production of several bioactive compounds, especially cyclohexadepsipeptides of the enniatin family. At the same time, these biochemical properties create some concern for the possible mycotoxin contamination of hazelnut products.

Molecular Characterization and Pathogenicity of Diaporthe Species Causing Nut Rot of Hazelnut in Italy

Hazelnut (Corylus avellana), a nut crop that is rapidly expanding worldwide, is endangered by a rot. Nut rot results in hazelnut defects. A survey was conducted in northwestern Italy during 2020 and 2021 to identify the causal agents of hazelnut rots. Typical symptoms of black rot, mold, and necrotic spots were observed on hazelnuts. The prevalent fungi isolated from symptomatic hazelnut kernels were Diaporthe spp. (38%), Botryosphaeria dothidea (26%), Diplodia seriata (14%), and other fungal genera with less frequent occurrences. Among 161 isolated Diaporthe spp., 40 were selected for further analysis. Based on morphological characterization and multilocus phylogenetic analysis of the ITS, tef-1α, and tub2, seven Diaporthe species were identified as D. eres, D. foeniculina, D. novem, D. oncostoma, D. ravennica, D. rudis, and D. sojae. D. eres was the main species isolated from hazelnut rots, in particular from moldy nuts. The pathogenicity test performed on hazelnuts 'Tonda Gentile del Piemonte' using a mycelium plug showed that all the Diaporthe isolates were pathogenic on their original host. To our knowledge, this work is the first report of D. novem, D. oncostoma, and D. ravennica on hazelnuts worldwide. D. foeniculina, D. rudis, and D. sojae were reported for the first time as agents of hazelnut rot in Italy. Future studies should focus on the comprehension of epidemiology and climatic conditions favoring the development of Diaporthe spp. on hazelnut. Prevention and control measures should target D. eres, representing the main causal agents responsible for defects and nut rot of hazelnuts in Italy.

Diaporthe Species on Palms: Molecular Re-Assessment and Species Boundaries Delimitation in the D. arecae Species Complex

Due to cryptic diversification, phenotypic plasticity and host associations, multilocus phylogenetic analyses have become the most important tool in accurately identifying and circumscribing species in the Diaporthe genus. However, the application of the genealogical concordance criterion has often been overlooked, ultimately leading to an exponential increase in novel Diaporthe spp. Due to the large number of species, many lineages remain poorly understood under the so-called species complexes. For this reason, a robust delimitation of the species boundaries in Diaporthe is still an ongoing challenge. Therefore, the present study aimed to resolve the species boundaries of the Diaporthe arecae species complex (DASC) by implementing an integrative taxonomic approach. The Genealogical Phylogenetic Species Recognition (GCPSR) principle revealed incongruences between the individual gene genealogies. Moreover, the Poisson Tree Processes' (PTPs) coalescent-based species delimitation models identified three well-delimited subclades represented by the species D. arecae, D. chiangmaiensis and D. smilacicola. These results evidence that all species previously described in the D. arecae subclade are conspecific, which is coherent with the morphological indistinctiveness observed and the absence of reproductive isolation and barriers to gene flow. Thus, 52 Diaporthe spp. are reduced to synonymy under D. arecae. Recent population expansion and the possibility of incomplete lineage sorting suggested that the D. arecae subclade may be considered as ongoing evolving lineages under active divergence and speciation. Hence, the genetic diversity and intraspecific variability of D. arecae in the context of current global climate change and the role of D. arecae as a pathogen on palm trees and other hosts are also discussed. This study illustrates that species in Diaporthe are highly overestimated, and highlights the relevance of applying an integrative taxonomic approach to accurately circumscribe the species boundaries in the genus Diaporthe.

Exploring Differences in Culturable Fungal Diversity Using Standard Freezing Incubation-A Case Study in the Limestones of Lemos Pantheon (Portugal)

In this study, we explored the biodiversity and abundance of culturable fungi in four samples associated with different biodeterioration outlines collected from the Lemos Pantheon, a limestone-built artwork in Portugal. We compared the results from prolonged standard freezing with those previously obtained from fresh samples to analyze differences in the obtained community and assess the effectiveness of the standard freezing incubation protocol in uncovering a different segment of culturable fungal diversity. Our results showed a slight decrease in culturable diversity, but over 70% of the obtained isolates were not present in the previously studied fresh samples. We also identified a high number of potential new species with this procedure. Moreover, the use of a wide variety of selective culture media positively influenced the diversity of the cultivable fungi obtained in this study. These findings highlight the importance of developing new protocols under varying conditions to accurately characterize the culturable fraction in a given sample. The identification and study of these communities and their possible contribution to the biodeterioration process is crucial knowledge for formulating effective conservation and restoration plans to prevent further damage to valuable cultural heritage assets.

Mycotoxin Contamination in Hazelnut: Current Status, Analytical Strategies, and Future Prospects

Hazelnuts represent a potential source of mycotoxins that pose a public health issue due to their increasing consumption as food ingredients worldwide. Hazelnuts contamination by mycotoxins may derive from fungal infections occurring during fruit development, or in postharvest. The present review considers the available data on mycotoxins detected in hazelnuts, on fungal species reported as infecting hazelnut fruit, and general analytical approaches adopted for mycotoxin investigation. Prompted by the European safety regulation concerning hazelnuts, many analytical methods have focused on the determination of levels of aflatoxin B1 (AFB1) and total aflatoxins. An overview of the available data shows that a multiplicity of fungal species and further mycotoxins have been detected in hazelnuts, including anthraquinones, cyclodepsipeptides, ochratoxins, sterigmatocystins, trichothecenes, and more. Hence, the importance is highlighted in developing suitable methods for the concurrent detection of a broad spectrum of these mycotoxins. Moreover, control strategies to be employed before and after harvest in the aim of controlling the fungal contamination, and in reducing or inactivating mycotoxins in hazelnuts, are discussed.

DEFHAZ: A Mechanistic Weather-Driven Predictive Model for Diaporthe eres Infection and Defective Hazelnut Outbreaks

The browning of the internal tissues of hazelnut kernels, which are visible when the nuts are cut in half, as well as the discolouration and brown spots on the kernel surface, are important defects that are mainly attributed to Diaporthe eres. The knowledge regarding the Diaporthe eres infection cycle and its interaction with hazelnut crops is incomplete. Nevertheless, we developed a mechanistic model called DEFHAZ. We considered georeferenced data on the occurrence of hazelnut defects from 2013 to 2020 from orchards in the Caucasus region and Turkey, supported by meteorological data, to run and validate the model. The predictive model inputs are the hourly meteorological data (air temperature, relative humidity, and rainfall), and the model output is the cumulative index (Dh-I), which we computed daily during the growing season till ripening/harvest time. We established the probability function, with a threshold of 1% of defective hazelnuts, to define the defect occurrence risk. We compared the predictions at early and full ripening with the observed data at the corresponding crop growth stages. In addition, we compared the predictions at early ripening with the defects observed at full ripening. Overall, the correct predictions were >80%, with <16% false negatives, which confirmed the model accuracy in predicting hazelnut defects, even in advance of the harvest. The DEFHAZ model could become a valuable support for hazelnut stakeholders.

Fungi Occurrence in Ready-to-Eat Hazelnuts (Corylus avellana) From Different Boreal Hemisphere Areas

The present study evaluated the fungal contamination of ready-to-eat dried hazelnuts considering for the first time the application of the same condition drying process of several hazelnut cultivars from different boreal hemisphere areas. Fifty lots of hazelnuts (Corylus avellana), belonging to eight cultivars from seven regions in four countries, were analyzed for fungal microbiota, describing both load levels and species diversity. For this purpose, a polyphasic approach consisting of morphological examination (optical and scanning electron microscope observation) and molecular characterization [PCR-DGGE analysis and sequence analyses of the internal transcribed spacer (ITS)] was performed. The results show that different fungal populations occur in dried hazelnuts regardless of their geographical area of production. Although some varieties appear to be relatively less susceptible, species related to Aspergillus, such as A. commune and A. ochraceus, Penicillium, including P. commune, P. solitum, and P. expansum, and Rhizopus, for instance, R. stolonifer and R. oryzae, have generally been found. A related character "hazelnut cultivar-fungi" was found for species related to the genera Trichoderma and Fusarium, including F. oxyxporum, F. solani, and F. falciforme. All 14 species found are known to host pathogenic strains. Therefore, their presence in a ready-to-eat product, such as dried hazelnuts, can pose a real danger to the consumer. Based on these considerations, the development of new protective strategies seems highly desirable. The species-level description of the contaminating fungal community acquired through this study is the starting point for the development of tailor-made protective biotechnologies.

Rotten Hazelnuts Prediction via Simulation Modeling-A Case Study on the Turkish Hazelnut Sector

The quality defects of hazelnut fruits comprise changes in morphology and taste, and their intensity mainly depends on seasonal environmental conditions. The strongest off-flavor of hazelnuts is known as rotten defect, whose candidate causal agents are a complex of fungal pathogens, with Diaporthe as the dominant genus. Timely indications on the expected incidence of rotten defect would be essential for buyers to identify areas where hazelnut quality will be superior, other than being useful for farmers to have the timely indications of the risk of pathogens infection. Here, we propose a rotten defect forecasting model, and we apply it in the seven main hazelnut producing municipalities in Turkey. We modulate plant susceptibility to fungal infection according to simulated hazelnut phenology, and we reproduce the key components of the Diaporthe spp. epidemiological cycle via a process-based simulation model. A model sensitivity analysis has been performed under contrasting weather conditions to select most relevant parameters for calibration, which relied on weekly phenological observations and the post-harvest analyses of rotten incidence in the period 2016-2019, conducted in 22 orchards. The rotten simulation model reproduced rotten incidence data in calibration and validation datasets with a mean absolute error below 1.8%. The dataset used for model validation (321 additional sampling locations) has been characterized by large variability of rotten incidence, in turn contributing to decrease the correlation between reference and simulated data (R ² = 0.4 and 0.21 in West and East Black Sea region, respectively). This denotes the key effect of other environmental and agronomic factors on rotten incidence, which are not yet taken into account by the predictive workflow and will be considered in further improvements. When applied in spatially distributed simulations, the model differentiated the rotten incidence across municipalities, and reproduced the interannual variability of rotten incidence. Our results confirmed that the rotten defect is strictly dependent on precipitation amount and timing, and that plant susceptibility is crucial to trigger fungal infections. Future steps will envisage the application of the rotten simulation model to other hazelnut producing regions, before being operationally used for in-season forecasting activities.

Draft Genome Sequence of a New Fusarium Isolate Belonging to Fusarium tricinctum Species Complex Collected From Hazelnut in Central Italy

In summer 2019, during a survey on the health status of a hazelnut orchard located in the Tuscia area (the province of Viterbo, Latium, Italy), nuts showing symptoms, such as brown-grayish spots at the bottom of the nuts progressing upward to the apex, and necrotic patches on the bracts and, sometimes, on the petioles, were found and collected for further studies. This syndrome is associated with the nut gray necrosis (NGN), whose main causal agent is Fusarium lateritium. Aiming to increase knowledge about this fungal pathogen, the whole-genome sequencing of a strain isolated from symptomatic hazelnut was performed using long Nanopore reads technology in combination with the higher precision of the Illumina reads, generating a high-quality genome assembly. The following phylogenetic and comparative genomics analysis suggested that this isolate is caused by the F. tricinctum species complex rather than F. lateritium one, as initially hypothesized. Thus, this study demonstrates that different Fusarium species can infect Corylus avellana producing the same symptomatology. In addition, it sheds light onto the genetic features of the pathogen in subject, clarifying facets about its biology, epidemiology, infection mechanisms, and host spectrum, with the future objective to develop specific and efficient control strategies.

Cytospora and Diaporthe Species Associated With Hazelnut Canker and Dieback in Beijing, China

Hazelnut (Corylus heterophylla Fisch.) is an important nut crop in China but has been declining owing to the destructive effects of fungal branch canker and dieback. The identification and management of these pathogens are difficult because of the lack of attention to branch canker, insufficient understanding of phylogenetic, and overlapping morphological characteristics of the pathogens. In total, 51 strains were isolated from Chinese wild hazelnut in this study, and three species of Cytospora and two of Diaporthe were identified through morphological observation and multi-locus phylogenetic analyses (ITS, act, rpb2, tef1-α, and tub2 for Cytospora; ITS, cal, his3, tef1-α, and tub2 for Diaporthe). Three new species, Cytospora corylina, C. curvispora, and Diaporthe corylicola, and two known species, Cytospora leucostoma and Diaporthe eres, grew at 5-30°C and a pH of 3.0-11.0, with optimum growth at approximately 25°C and pH 4.0-7.0. Additionally, the effects of six carbon sources on mycelial growth were investigated. This study explored the main pathogenic fungi species of Corylus heterophylla, completed the corresponding database of pathogenic fungi information, and clarified their biological characteristics. Moreover, the results of this study provided a theoretical basis for Corylus heterophylla disease management and prevention in China.

The HADES Yield Prediction System - A Case Study on the Turkish Hazelnut Sector

Crop yield forecasting activities are essential to support decision making of farmers, private companies and public entities. While standard systems use georeferenced agro-climatic data as input to process-based simulation models, new trends entail the application of machine learning for yield prediction. In this paper we present HADES (HAzelnut yielD forEcaSt), a hazelnut yield prediction system, in which process-based modeling and machine learning techniques are hybridized and applied in Turkey. Official yields in the top hazelnut producing municipalities in 2004-2019 are used as reference data, whereas ground observations of phenology and weather data represent the main HADES inputs. A statistical analysis allows inferring the occurrence and magnitude of biennial bearing in official yields and is used to aid the calibration of a process-based hazelnut simulation model. Then, a Random Forest algorithm is deployed in regression mode using the outputs of the process-based model as predictors, together with information on hazelnut varieties, the presence of alternate bearing in the yield series, and agro-meteorological indicators. HADES predictive ability in calibration and validation was balanced, with relative root mean square error below 20%, and R² and Nash-Sutcliffe modeling efficiency above 0.7 considering all municipalities together. HADES paves the way for a next-generation yield prediction system, to deliver timely and robust information and enhance the sustainability of the hazelnut sector across the globe.

Ecology of Diaporthe eres, the causal agent of hazelnut defects

Diaporthe eres has been recently reported as the causal agent of hazelnut defects, with characteristic brown spots on the kernels surface and internal fruit discoloration. Knowledge regarding the ecology of this fungus is poor but, is critical to support a rationale and effective hazelnut crop protection strategy. Therefore, a study was performed to describe and model the effect of different abiotic factors such as temperature (T, 5-35°C, step 5°C) and water activity (aw 0.83-0.99, step 0.03) regimes on D. eres mycelial growth, pycnidial conidiomata development and asexual spore production during a 60-day incubation period. Alpha conidia germination was tested in the same T range and at different relative humidities (RH = 94, 97 and 100%) over 48 h incubation period. Fungal growth was observed from the first visual observation; regarding pycnidia and cirrhi, their development started after 8 and 19 days of incubation, respectively and increased over time. The optimum T for growth was 20-25°C and for pycnidia and cirrhi development was 30°C; aw ≥ 0.98 was optimal for the tested steps of the fungal cycle. The best condition for conidial germination of D. eres was at 25°C with RH = 100%. Quantitative data obtained were fitted using non- linear regression functions (Bete, logistic and polynomial), which provided a very good fit of the biological process (R2 = 0.793-0.987). These functions could be the basis for the development of a predictive model for the infection of D. eres of hazelnuts.