Abstract
Fungi inflict a great deal of damage to crops in fields and in storage facilities, causing issues such as leaf spot, wilt, rust, dieback and rot, as well as releasing mycotoxins that taint vegetation. In the current study, 25 de novo fungal isolates were taken from infected plant tissue (leaf, root and fruit), at pre- and post-harvest stages. Isolates were identified using molecular markers; 8 genera and 15 species were determined. The most common species was Penicillium spp. (40%), Aspergillus spp. (20%), Fusarium spp. (16%) and Alternaria alternata species (8%). The remaining 16% was comprised of various types of fungi, including Geotrichum candidum, Neofusicoccum parvum, Rhizopus stolonifera and Mucor fragilis. Many of these genera are known to cause significant crop damage and are notorious mycotoxin producers. An evaluation of the optimal growth temperature revealed the ideal temperatures were 30 °C for 56% of isolates, 25 °C for 28% of isolates and 20 °C for 16% of isolates. An assessment of water activity showed that 60% of isolates belonged to Penicillium and Aspergillus spp. and were mesophilic and xerophilic. Another 28% of isolates were Fusarium spp., Geotrichum candidum, Neofusicoccum parvum and Mucor fragilis, and hydrophilic. The remaining 12%, representing Alternaria alternata and Rhizopus stolonifera, were mesophilic. The current study provides accurate eco-physiological response data and molecular information for each isolate. The findings can assist the development of novel approaches to control the expansion of invasive fungal infections and minimise their deleterious consequences.
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1 Introduction
The climactic conditions and diverse geological features of the Kingdom of Saudi Arabia (KSA) support a diverse range of plant life forms [40]. The nation is home to around 2,300 plant species, belonging to 142 families [12, 19].
The Al-Baha province in southwestern KSA has six major cities: Al-Baha, Alaqiq, Almandaq, Almikhwah, Baljurashi and Qilwah. The capital of this territory is Al-Baha [11]. The region has a diverse ecological topology, with forests, mountains, ravines and areas of abundant vegetation. Al-Baha has more than 320 species of flora, comprising members of 228 genera and 75 families. Among these are many fruits, vegetables, grains and plants with medicinal applications [10]. The region has a long tradition of farming, of both native and introduced crops [19]. Consequently, the presence (or otherwise) of fungi in Al-Baha is an important issue.
Worldwide, fungi routinely induce catastrophic levels of disease in vegetation during growth and in storage. The world’s annual maize harvest, for instance, is sometimes halved as a result of fungal infection [23]. In addition, fungal organisms taint plants with mycotoxins, which can harm both animals and humans. Such harm is widely acknowledged. The International Agency for Research has highlighted the tumorigenic potential of mycotoxins [37], and the Food and Agriculture Organization has estimated that approximately half of all crops worldwide are tainted with mycotoxins in a typical year [23].
More than 400 mycotoxins are currently known. These include aflatoxins, ochratoxins, trichothecenes and fumonisins [48]. The extent of damage caused by mycotoxins varies by their type: Aspergillus, Penicillium and Fusarium spp. are recognised as causing very extensive harm to the quality and yield of crops, and have been classified among the five most hazardous species in terms of mycotoxin production.
Dates are a major crop in KSA. The country has approximately 28 million palm trees, which annually produce about 14% of the world’s dates. Research has found that between 2.7 and 33% of KSA-grown dates are lost or contaminated as a result of fungal infection [22, 52]. Some Saudi date crops have been contaminated with mycotoxin arising from Fusarium spp. [7, 8]. Crops imported into KSA have also been found to carry mycotoxins and/or have been affected by fungi. Aspergillus niger, A. flavus, Colletotrichum musae and Pencillium species are toxicogenic species that have been identified in imported vegetation [1, 3].
Several nations are considering the banning of various pesticides and fungicides from their markets [21]. This is frequently due to the association of such substances with adverse effects on humans and animals, and their deleterious effects upon advantageous, insects and fungi. Thus, the hunt is now on for alternative approaches that can eliminate or restrict the effects of harmful fungal agents [17]. Some nations have already sought to protect their vegetation from dangerous microorganisms by using more environmentally-friendly options. For example, countries such as Indonesia, Canada and Sweden have deployed various plant extracts and biological and environmental constraints [43, 47].
Fungi are influenced by ambient conditions, which can support or restrict their behaviours. An ability to recognise the conditions that deter problematic phytopathogens is indispensable to those who must protect crops during their growth and storage. The most influential conditions for fungal activity are temperature and the amount of water present. These factors affect the levels of growth, spore formation and mycotoxin synthesis. Water and temperature also influence the ability of crops to fight mycotoxin and fungal infection [7].
The ambient temperature preferences of fungi vary by species and even strains within a species. For example, Hope et al. [27] demonstrated that the preferred temperature for growth of two strains from Fusarium culmorum differed by 10°C. However, all fungi have one objective, which is to optimise their biological status and outcomes, for example through sporulation, mycelium growth and the ability to extract maximum benefit from the plants that they target [26, 36].
Water is a key determinant of the chemical and physical properties of crops. Its availability can also be used to control microbial activity. The availability of water, for example, in ambient air, in food or food products, is measured in units of water activity (aw) [16, 50]. Fungi are influenced by water activity, and have been classified into three groups according to their optimal water levels. Hydrophilic fungi favour a level greater than 0.90 aw, whereas the mesophilic group prefers water levels between 0.85 and 0.90 aw. The final group, xerophilic fungi, grow best between 0.65 and 0.85 aw [38].In favourable water activity conditions, fungal spores thrive, reducing crop yields and contaminating plants with mycotoxins [32, 50].
De novo fungal species and strains are identified precisely using molecular techniques, which is more accurate than the traditional approach of classification based upon of appearance [59]. Molecular identification methods include the use of gel electrophoresis and detecting novel sequences for BLAST analysis. This allows the identification of features that resemble those of species sequences stored in repositories such as UNITE and the National Centre for Biotechnology Information (NCBI) [49].
It is generally acknowledged that internal transcribed space (ITS) markers are the gold-standard indicators for the identification of fungi species. The ITS markers used for this purpose operate at the locus between small and large ribosomal RNA sub-units 18S, 5.8S and 28S [62]. These markers have the advantage of specificity,the conserved area within the ITS marker is almost universally seen in fungal genomes. Its polymerase chain reaction (PCR) fragment is within the range of 400–900 base pairs [13, 20]. The use of ITS1 and ITS4 primers to identify fungi is widespread, because there is substantial overlap between the 18S and 28S sub-units, and this is an area in which there is a great deal of heterogeneity among species [64].
By 2012, 175,000 lengths of ITS sequences had been linked to more than 15,000 species of fungi and stored in GenBank [56]. However, five years later the accessible data still limited, less than 1% of more than 5 million fungal species known to exist [49]. There is widespread agreement that ITS markers should generate a sequence homology of between 95 and 100% before de novo isolates be assigned to a category [35].
In this context, it should be noted that while contemporary research has done much to characterise regional species and to trace phylogenetic links with reference sequence isolates, it has rarely focused on the conditions required to promote or restrict the growth and behaviour of fungi. The current paper therefore seeks to fill this gap in the literature and to contribute to the understanding of this aspect.
2 Materials and methods
2.1 Sample collection sites and sampling
Samples were collected from 25 crop production and storage sites in the cities of Al-Baha and Baljurashi. Al-Baha is situated 2400 m above sea level, at longitudinal 41° 28′ 4 E and latitude 20° 0′ 46 N [11]. Baljurashi (19° 51′ N, 41° 33′ E) is 2000 m above sea level (Fig. 1). Consent for access was secured from all site owners. Multiple fungal samples were taken from the sites. The aim was to identify the predominant fungal pathogen at each of the 25 sites. Great care was taken to avoid the inadvertent inclusion of transient isolates, such as surface spores carried by wind onto soil or plant parts.
2.2 Isolation of fungi and preparation of stock culture
The gathered samples were rinsed in tap water, surface disinfected for 2 min in 1% sodium hypochlorite solution, then rinsed thoroughly in distilled water. The surfaces of the infected tissues (leaf, root and fruit) were scraped with a sterilised loop, to facilitate the transfer of spores and mycelia to a potato dextrose agar (PDA) medium. The spores and mycelia were cultured in PDA for 5 days at 25 °C. After this period, a 0.5 mm-sized inoculum was extracted from the edge of the culture and transferred to a fresh plate containing PDA medium, which was then sub-cultured to attain a pure isolate [1, 54]. Stock cultures of the de novo isolates were made up and kept in the stock culture bank et al.-Baha University. Table 1 describes the new isolates.
2.3 DNA extraction
Sub-culture of the colonial mycelia was carried out in potato dextrose broth to provide a greater yield of DNA. Tissue was then pulverised into a powder with a pestle and mortar using liquid nitrogen. A 150–200 mg sample was placed in a 2-ml Eppendorf tube and DNA extraction was performed using GeneJET Plant Genomic DNA Purification (Thermo Fisher Scientific®) in accordance with the manufacturer’s recommendations. The DNA was stored at − 20 °C until required.
2.4 Molecular identification and constructing phylogenetic tree
The 20 µl and 50 µl PCR protocols were established using forward (ITS1: TCCGTAGGTGAACCTGCGG) and reverse (ITS4: TCCTCCGCTTATTGATATGC) primers. The following conditions were applied: 35 cycles of initial denaturation, 95 °C for 3 min; denaturation, 94 °C for 1 min; annealing, 60 °C for 1 min; extension, 72 °C for 1 min; final extension, 72 °C for 5 min. The final product was stored at 16 °C until required.
For the 50 µl PCR, 2.5 µl DNA, 2.5 µl of 20 µM forward primer, 2.5 µl of 20-µM reverse primer, 5 µl 10× reaction buffer, 1 µl dNTPs, 3 µl MgCl2 and 0.25 µl Taq DNA polymerase were made up to 50 µl with free DNAase and RNAase water. The 20 µl PCR used the same combination, but in modified quantities. To create a negative control, the DNA was substituted with free DNAase and RNAase water. Once the PCR cycles had concluded, 5× loading dye was admixed with the PCR yield.
Then, 1 mg agarose powder was made up to a solution with 100 ml 1× TAE buffer, and heated for 2 min in a microwave oven; 5 µl of 10-mg/ml ethidium bromide was admixed. The resulting material was decanted onto a gel tray to cool and to form a solid agarose gel. The latter was then added to a gel electrophoresis tank containing 1× TAE buffer. This was connected to 90 V power for an hour (Fig. 2).
The kite protocol (Qiagen QIAquick PCR Purification Kit) was applied to purify the amplicon products. These were then dispatched to an external sequencing service (Macrongen Inc.). Sequence dimensions and quality were verified using the trace information; ambiguous bases were discarded. With the resultant data in the FASTA format, species were identified using BLAST analysis on NCBI or UNITE [49]. Any GenBank sequences exhibiting a similarity ≥ 96% were downloaded as a reference sequence for the phylogenetic element of the research. Table 2 provides details of the reference isolates [35]. Geneious Prime software, version 2022.2 (developed by Biomatters) was used to create a phylogenetic tree from the multiple sequence alignments generated by the package’s MUSCLE alignment tool, and derived from the original and reference sequences (Fig. 3). The Geneious tree builder algorithm was applied to create a phylogenetic tree founded on distance tree and neighbour joining. The Tamura-Nei model provided the genetic distance of the tree. To attain a consensus phylogenetic tree, analysis was carried out based on parsimony with a bootstrap support value set within the range 70–100%. To achieve best fit, the general time-reversible evolutionary model, including 500 bootstrap applications, was applied [6, 29].
The 25 new sequences identified in this research were placed in the NCBI GenBank. All isolates were assigned their own accession number (Table 1). These sequences were uploaded following verification of sequence quality and quantity, confirmation that the submission parameters had been met, and filing of the apposite data for the respective sequences individually.
2.5 Evaluation of growth at three temperatures
The 25 new isolates were each grown in three ambient temperatures. These were 20 °C, 25 °C and 30°C. The objective was to establish each strain’s preferred conditions. To begin isolation of the colony cultures and subcultures, 9-cm PDA Petri dishes were used, and 5-mm inoculum discs were placed at the centre point of fresh PDA Petri dishes. Five replicates for each isolate were cultured in an incubator at the given temperatures for 6 days. At that point, the radial growth dimensions as mm/day were evaluated for each sample. Figure 4 presents the growth data as a bar chart; replicate variation is indicated by the error bar [26, 36].
2.6 Growth evaluation at four points of water activity
Four sets of PDA media were prepared by adding a suitable amount of glycerol (Sigma Aldrich G9012) to create simulated media for four different water activities. These conditions were 0.995, 0.99, 0.90 and 0.85 aw. The amount of glycerol was added to 1 L of PDA medium as follows; 22.08 ml for 0.995 aw, none for 0.99 aw (as supplied by PDA manufacturer; this was used as a control), 404.8 ml for 0.90 aw and 625.6 ml for 85 aw.
Testing was conducted with an AQUALAB water activity meter. The media were poured into 9 cm petri dishes and inculcated with a 5 mm disc of fresh growth culture. Five replicates for each water activity were made for each of the 25 isolates. Each isolate was incubated at its optimal growth temperature. Radial growth measurements were taken as described above [6, 34].
3 Results and discussion
3.1 Molecular identification using its genetic marker and phylogenetic analysis
In this study, the ITS marker was initially used to confirm that the samples were fungal isolates. This was done by inspecting the PCR products on the electrophoresis gel (Fig. 2). Subsequently, the amplicon sequences for each isolate were used for blast analysis in GenBank NCBI, to identify their fungal species (Table 1).
Phylogeny derived from ITS genetic markers was used to determine the genotypes of 48 isolates. Of these, 25 were de novo and 23 were reference strains. The reference strains represented organisms from a spectrum of hosts and geographic locations (Tables 1 and 2). The topology of the Geneious phylogenetic tree, which was constructed using the neighbour-joining tree builder algorithm, revealed the hierarchical distribution of the 48 isolates that were being investigated. This ranged from 3 nodes to 2 clades to 2 major groups to 2 minor groups, 2 primary subgroups and 3 secondary subgroups (Fig. 3).
Nodes 1, 2 and 3 showed bootstrap support value (BSV) affinity of 99–100%. Both the first and third nodes were monophyletic groups, with the first node being representative of two taxa, BHU143B and AR7, which are members of the species Rhizopus stolonifera. The third node had two taxa, BHU170 and 7P1, belonging to the species Mucor fragilis. The second node encompassed the majority of taxa (44/48) and was distributed across two clades, A and B. In turn, A and B comprised 2 and 42 taxa, respectively. The majority of taxa represented monophyletic groups (i.e. they shared a common ancestor). Just 11 taxa were polyphyletic (i.e., had no common ancestor).
The first clade, A, comprised two taxa members of the Geotrichum candidum species. In contrast, the second clade, B, was composed of two major groups (B1 and B2). The group B1 had four taxa belonging to the Alternaria alternata species. The second major group, B2, had the largest number of taxa (38 out of 48).
These were further divided into two minor groups, B2.1 and B2.2. The minor group, B2.1, included 8 taxa representing the three species of the genus Fusarium at BSV 98–100%.
The other minor group, B2.2, was divided into two primary subgroups (B2.2.1 and B2.2.2). The first primary subgroup, B2.2.1, generated three secondary subgroups (B2.2.1.1, B2.2.1.2 and B2.2.1.3). The second primary subgroup, B2.2.2, included two taxa belonging to the species Neofusicoccum parvum.
The first secondary subgroup (B2.2.1.1) had two taxa belonging to Aspergillus niger. The second secondary subgroup (B2.2.1.2) has 18 taxa, with 7 out of 18 being monophyletic and the remaining 11 taxa were polyphyletic. The third secondary subgroup (B2.2.1.3) included eight taxa belonging to Aspergillus nidulans and Aspergillus flavus species at BSV 73–100% (Fig. 3).
The 15 species and 8 genera were described according to the molecular features and phylogenetic relationships identified through use of the ITS genetic markers (Fig. 3). Although ITS indicators have greatly enhanced scholars’ ability to distinguish between isolates from different species, this process may be less effective for differentiating isolates from closely related species. In the present study, most groups, (i.e. 1, 3, A and B1) revealed isolates from different species. Less genetic variation was seen within groups B2.1 and B2.2.1.3, which contained a number of strains from single species, namely Fusarium verticillioides, Fusarium equiseti, Fusarium oxysporum, Aspergillus niger and Aspergillus flavus.
These findings reflect the previously expressed view that the ITS markers are better for interspecies differentiation than they are for intraspecies differentiation. Several scholars have considered this issue with regard to the species Fusarium and Penicillium [39, 41, 42, 57]. However, for some species, such as Alternaria and Aspergillus, ITS markers offer a precise distinction both between and within species [5, 14, 25, 63].
3.2 Optimal temperature for growth of new isolates
The 25 new isolates were representative of 15 species and 8 genera. All were incubated for six days, and their growth activity in three ambient temperatures (20 °C, 25 °C and 30 °C) was quantified. The radial growth was measured for each of the five replicates, to create an error bar chart (Fig. 4 and Table 3).
Each of the new strains was allocated to one of three groups according to their optimal temperature as measured via growth outcomes. The first group comprised species isolates that grew optimally at 20 °C, which included Alternaria alternata (BHU114), Aspergillus flavus (BHU161), Mucor fragilis (BHU170) and Penicillium crustosum (BHU171). The second group of isolates grew optimally at 25 °C and included Penicillium expansum (BHU150), Penicillium glabrum (BHU132 and BHU137), Rhizopus stolonifer (BHU143B), Fusarium equiseti (BHU165), Neofusicoccum parvum (BHU167) and Aspergillus niger (BHU012). The third group had 14 isolates, which grew optimally at 30 °C. These included Penicillium expansum (BHU143A), Penicillium glabrum (BHU110, BHU112, BHU131 and BHU134), Alternaria alternata (BHU163), Fusarium verticillioides (BHU135), Aspergillus flavus two strains (BHU120 and BHU130), Geotrichum candidum (BHU162), Fusarium oxysporum (BHU007 and BHU164), Penicillium commune (BHU074B) and Aspergillus nidulans (BHU121). Figure 4 and Table 3 give further details.
It is notable that for 14 of the 25 isolates, the temperature of 30 °C provided optimal growth conditions, while seven others flourished at 25 °C, and only four grew best at 20 °C (Fig. 4 and Table 3). Variation between growth rates appeared most extreme between species, and less diverse within species. The fact that 14 isolates favoured the higher temperature of 30 °C was unsurprising, since this replicates the temperature commonly found in their original geographical habitat.
Fungi can grow in wide range of temperatures, mostly between 15 and 42 °C, but most strains favour a temperature between 20 and 30 °C. Optimal growth temperature is largely influenced by the dominant temperature in the fungus’s original geographical location [33, 46]. For example, fungal strains in Saudi Arabia prefer a growth temperature range between 25 and 30 °C, which is a moderate to high temperature. In Europe, fungi thrive in temperatures that fall between cool and moderate levels [7]
Several researchers have indicated that the temperature range of 30–35 °C is favoured by Aspergillus species (e.g. A. flavus and A. niger) [5, 25]. Meanwhile, 25 °C has been found to be the ideal temperature for the species P. camemberti and P. roqueforti [15, 59]. In Europe, temperatures generally range between 15 and 25 °C (i.e. cool to moderate) and are preferred by isolates belonging to the Fusarium species within several European habitats [27, 53].
3.3 Optimal water activity for growth
The 25 new isolates were also assessed for their growth response at four water activity points, which were 0.995, 0.99, 0.90 and 0.85 aw, as well as at their optimal temperatures over 6 days of incubation (Fig. 5 and Table 3).
In the current study, 10 strains of Penicillium spp. showed optimal growth at 0.85 aw. These were Penicillium expansum species (BHU143A and BHU150), Penicillium glabrum species (BHU110, BHU112, BHU131, BHU132, BHU134 and BHU137), Penicillium crustosum species (BHU171) and Penicillium commune (BHU074B). Additionally, five strains of Aspergillus spp. also showed optimal growth at 0.85 aw; these were Aspergillus flavus species (BHU120, BHU130 and BHU161), Aspergillus niger species (BHU012) and Aspergillus nidulans species (BHU121). Two strains of Alternaria alternata (BHU114 and BHU163) and one strain of Rhizopus stolonifer (BHU143B) grew best at 0.90 aw. Meanwhile, four isolates of Fusarium spp., Fusarium verticillioides (BHU135), Fusarium equiseti (BHU165) and Fusarium oxysporum (BHU007 and BHU164), achieved their highest growth rates at 0.995 aw. One strain of Neofusicoccum parvum (BHU167), one strain of Mucor fragilis (BHU170) and one strain of Geotrichum candidum (BHU162) grew best at 0.995 aw. Further details are in Fig. 5 and Table 3.
The growth attainment across all strains indicates substantial variability among isolates from different genera, yet low variability among isolates of the same or related species. In general, a water activity level between 0.90 and 0.99 aw seems to suit most strains, whereas 0.85 aw dramatically restricts growth in some hydrophilic species. For example, the isolates of Fusarium, Neofusicoccum, Mucor and Geotrichum genera were classified as hydrophilic because they grew best at the highest level of moisture, at 0.995aw. This finding agreed with several other published works that have found the optimal water activity for growth ranges is between 0.99 and 0.95 aw for hydrophilic fungi, such as Fusarium and Geotrichum [4, 45, 61]. In contrast, the isolates belonging to Rhizopus and Alternaria genera were classified as mesophilic because they thrived at a median level of moisture, around 0.90 aw. Rhizopus stolonifera and Alternaria alternata grew optimally at moderate temperatures and a range of water activity levels from 0.90 aw upwards [51, 66].
Interestingly, most isolates belonging to the Penicillium and Aspergillus genera, were able to grow at all levels of water activity tested, and they seemed to adapt to low levels of moisture (0.85–0.90 aw). Thus, they can be classified as being between xerophilic and mesophilic. Aspergillus flavus and Penicillium spp. could grow between 0.85 and 0.90 aw at above 15 °C [2, 24]. The highest extent of water activity had a negative impact on radial growth of Aspergillus flavu and Penicillium spp., which have been recognised as xerophilic [60]
These findings are compatible with those of other studies. For example, Fusarium, Trichoderma, Neofusicoccum, Mucor and Geotrichum species have elsewhere been described as hydrophilic [6, 31, 31, 38]. In other studies, Rhizopus and Alternaria species have been classified as mesophilic species [44, 55]. Elsewhere, Penicillium and Aspergillus species have been considered xerophilic [44, 55].
4 Conclusions and future perspectives
The Penicillium and Aspergillus species accounted for more than half of the 25 strains isolated from various locations in Al-Baha and Baljurashi in the current study. Over quarter of those isolates belonged to the Fusarium species, while the remaining isolates corresponded to Alternaria alternata, Geotrichum candidum, Neofusicoccum parvum, Rhizopus stolonifera and Mucor fragilis.
The present study notes that Penicillium and Aspergillus are the species most frequently implicated in harming fruit and vegetable crops in storage conditions. Meanwhile, Alternaria alternata and Fusarium spp. were found in more than half of the pathogenic field-harvested samples.
The phylogenetic tree, based on ITS markers, has allocated the new isolates to their correct species groups and confirmed their species identification, based on similarity to GenBank reference data. The species recognised as most commonly producing mycotoxigenic effects are Penicillium, Fusarium, Alternaria and Aspergillus [18, 58].
The present study has shown how ambient conditions, (e.g. temperature and water availability), can affect the biological activities and virulence of fungi. The growth measured in this investigation is the bedrock for sporulation and mycotoxin production, which in turn correlate with fungal pathogenic activity such as dispersal, colonisation and contamination.
Most of the tested isolates (14 out of 25), favoured a temperature of 30 °C for growth, whereas seven of the remaining isolates showed a preference for 25 °C and four isolates grew best at 20 °C. In terms of water activity’s effects on growth, 15 out of 25 isolates belonged to Penicillium and Aspergillus, and these grew at all water activity levels. However, their highest growth rates were achieved in conditions with low to medium levels of moisture. Three isolates belong to Rhizopus stolonifera and Alternaria alternata species, grew optimally at moderate levels of moisture, while seven isolates belonging to Fusarium, Neofusicoccum, Mucor and Geotrichum genera preferred high level of moisture for growth.
Table 3 presents integrated data concerning the optimal growth conditions for each of new isolate. This data can contribute to the creation of strategies to mitigate the detrimental consequences of fungal invasion of crops before and after harvest. It will also be useful in the construction of strategies to prevent the spread of fungal infestation across sites [9]. Future studies might helpfully focus on identification of the type and level of mycotoxins produced by the dominant mycotoxigenic species in this work, namely Penicillium, Aspergillus and Fusarium spp. In addition, scholars might extend the work presented here in the context of exploring or developing biological controls and plant extracts to replace fungicides.
Data availability
The molecular datasets for this work have been deposited in NCBI gene bank and their corresponding accession numbers are available in tables of this work. Also, the datasets for the optimal growth temperatures are available and attached in this work.
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Almiman, B. Effects of temperature and water activity on 25 de novo strains of pathogenic plant fungi in Al-Baha and Baljurashi cities in Saudi Arabia. J.Umm Al-Qura Univ. Appll. Sci. 10, 301–312 (2024). https://doi.org/10.1007/s43994-023-00105-x
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DOI: https://doi.org/10.1007/s43994-023-00105-x