**5.2 Oviposition behaviour**

Studies into oviposition in the genus *Philornis* have revealed that species spanning diverse larval feeding habits are oviparous [1, 9, 31, 73, 74]. This current view has previously been hotly debated, in part because the majority of species remain unstudied. Laboratory rearing and field observation have confirmed that *P. downsi* is oviparous [45, 56, 57, 75]. *Philornis* flies enter and oviposit in nests regardless of nesting phase or nestling age but have not been observed to enter nests abandoned by the parent birds during the incubation phase [45, 47]. From in-nest video recordings, *P. downsi* flies have been observed entering nests throughout the day, but generally during dusk between 1500 and 1800, with visiting rates peaking around 1700 [45, 64]. Visit length averaged 1.3–1.5 min and occurred most commonly when the adult host is away from the nest and completed once the adult host returned [45, 64]. Eggs have been generally deposited on nesting material and the base of the nest [45, 57], however on one occasion, eggs have been also laid directly by the naris of a nestling [45]. A genetic study of *P. downsi* larvae estimated that 1–6 adult females (average ~3 females) oviposit within a single nest, supporting previous observations of different sized larval groups within nests and suggesting repeated nest infestations throughout the nestling period [7, 65].

**59**

*Taxonomic Shifts in* Philornis *Larval Behaviour and Rapid Changes in* Philornis downsi*…*

*Philornis downsi* is one of the most generalist species within the genus, known to infest 38 host species across avian taxa [5, 6, 76]. However, this high host number may reflect the large number of studies focused on *P. downsi* due to its invasive

It is currently unclear how *Philornis* species in general or *P. downsi* in particular find their hosts. Preliminary studies into the role of semiochemicals and volatiles in host nests as an attractant for *P. downsi* have produced inconclusive results [70]. Long-term ornithological field studies have provided some hints that the intensity of host cues may be relevant for *P. downsi* search behaviour, or alternatively that the density of host nests influences *P. downsi* oviposition behaviour. Aggregated host nests may attract *P. downsi* females due to an increase in olfactory or visual cues. These aggregated nests also provide a greater opportunity for *P. downsi* females to infest multiple nests. Indeed, small tree finch nests (*Camarhynchus parvulus*) Gould (Passeriformes: Thraupidae) with close neighbours contained more *P. downsi* larvae compared to solitary, more isolated nests [16]. Nests in areas of lower nesting density (i.e., lowlands) have been more likely to contain the offspring of a single *P. downsi* female than nests in areas of higher nesting density (i.e., highlands) that are more likely to contain the offspring of many *P. downsi* females [65]. Video recordings of adult *P. downsi* have been made inside the nests of the small ground finch (*Geospiza fuliginosa*) Gould (Passeriformes: Thraupidae), medium ground finch (*G. fortis*) Gould (Passeriformes: Thraupidae), small tree finch (*C. parvulus*) and Galápagos flycatcher (*Myiarchus magnirostris*) Gould (Passeriformes: Tyrannidae) [45, 64] (Pike et al. in prep). However, despite a combination of video recorders inside or outside the nest across studies, the recordings did not reveal information

A metagenomic study into *P. downsi* larval microbiome sampled from different host species found an effect of host diet on the gut bacterial community of *P. downsi* larvae [77]. Larvae retrieved from strictly insectivorous warbler finch (*Certhidea olivacea*) Gould (Passeriformes: Thraupidae) nests have a different microbiome structure compared with larvae parasitising hosts with broader dietary preferences (ground and tree finches, *Geospiza* and *Camarhynchus* sp., respectively) [77]. The gut microbiome also differed between *P. downsi* larvae (blood diet) and adults (plant diet), supporting the hypothesis that *P. downsi* microbiome changes during development and according to diet [77]. Further behavioural, biochemical and genetic studies are needed to understand *P. downsi* oviposition across host species,

**6. Changes in** *P. downsi* **behaviour since colonising the Galápagos Islands**

There is evidence that the oviposition behaviour of female *P. downsi* has changed

since its discovery on the Galápagos archipelago. *Philornis downsi* flies are now known to oviposit during any stage of the nesting cycle [45]. In the first decades following initial discovery of *P. downsi* in Darwin's finch nests, changes in the proportions of instar classes among *P. downsi* have been observed, with evidence that oviposition occurred earlier and more synchronously in the nesting phase in the later years of the study [54]. Synchronisation in oviposition date may lead to an increase in larval competition for host resources, and as a consequence result in increased virulence for nestlings that must contend with a greater number of large,

**5.3 Effects of host species on** *Philornis* **behaviour and microbiome**

about *P. downsi* search behaviour from its flight behaviour.

host locating behaviour and host specificity.

**6.1 Age of larval cohort in host nests**

*DOI: http://dx.doi.org/10.5772/intechopen.88854*

status on the Galápagos Islands [15, 16].

*Taxonomic Shifts in* Philornis *Larval Behaviour and Rapid Changes in* Philornis downsi*… DOI: http://dx.doi.org/10.5772/intechopen.88854*

#### **5.3 Effects of host species on** *Philornis* **behaviour and microbiome**

*Philornis downsi* is one of the most generalist species within the genus, known to infest 38 host species across avian taxa [5, 6, 76]. However, this high host number may reflect the large number of studies focused on *P. downsi* due to its invasive status on the Galápagos Islands [15, 16].

It is currently unclear how *Philornis* species in general or *P. downsi* in particular find their hosts. Preliminary studies into the role of semiochemicals and volatiles in host nests as an attractant for *P. downsi* have produced inconclusive results [70]. Long-term ornithological field studies have provided some hints that the intensity of host cues may be relevant for *P. downsi* search behaviour, or alternatively that the density of host nests influences *P. downsi* oviposition behaviour. Aggregated host nests may attract *P. downsi* females due to an increase in olfactory or visual cues. These aggregated nests also provide a greater opportunity for *P. downsi* females to infest multiple nests. Indeed, small tree finch nests (*Camarhynchus parvulus*) Gould (Passeriformes: Thraupidae) with close neighbours contained more *P. downsi* larvae compared to solitary, more isolated nests [16]. Nests in areas of lower nesting density (i.e., lowlands) have been more likely to contain the offspring of a single *P. downsi* female than nests in areas of higher nesting density (i.e., highlands) that are more likely to contain the offspring of many *P. downsi* females [65]. Video recordings of adult *P. downsi* have been made inside the nests of the small ground finch (*Geospiza fuliginosa*) Gould (Passeriformes: Thraupidae), medium ground finch (*G. fortis*) Gould (Passeriformes: Thraupidae), small tree finch (*C. parvulus*) and Galápagos flycatcher (*Myiarchus magnirostris*) Gould (Passeriformes: Tyrannidae) [45, 64] (Pike et al. in prep). However, despite a combination of video recorders inside or outside the nest across studies, the recordings did not reveal information about *P. downsi* search behaviour from its flight behaviour.

A metagenomic study into *P. downsi* larval microbiome sampled from different host species found an effect of host diet on the gut bacterial community of *P. downsi* larvae [77]. Larvae retrieved from strictly insectivorous warbler finch (*Certhidea olivacea*) Gould (Passeriformes: Thraupidae) nests have a different microbiome structure compared with larvae parasitising hosts with broader dietary preferences (ground and tree finches, *Geospiza* and *Camarhynchus* sp., respectively) [77]. The gut microbiome also differed between *P. downsi* larvae (blood diet) and adults (plant diet), supporting the hypothesis that *P. downsi* microbiome changes during development and according to diet [77]. Further behavioural, biochemical and genetic studies are needed to understand *P. downsi* oviposition across host species, host locating behaviour and host specificity.


2.1.2. Synthesis of [PbBr2(L2)]n∞·0.5nH2O (**2**)

Compound **2** was synthesized by adopting the procedure similar to that of **1** using Ea (0.24 mL, 4 mmol) and HBr (0.15 mL, 4 mmol) in place of solid Ea·HCl, and dry Pb(NO3)2 instead of its solution. Orange prisms of **2** suitable for X-ray crystallography were formed within a week after addition of i PrOH (3 mL) to the orange solution. Yield based on Pb(NO3)2: 31%.  Analysis calculated for C8H11Br2N2O1.5Pb (526.20): C, 18.26; H 2.11; N 5.32%. Found: C 18.45; H 2.15; N 5.47%.

## 2.1.3. Synthesis of [PbBr2(L3)]2 (**3**)

Compound **3** was synthesized by adopting the procedure similar to that of **2** using En (0.26 mL, 4 mmol) in place of Ea. Yellow plate-like crystals of **3** suitable for X-ray crystallography were formed within a week after addition of i PrOH (3 mL) to the orange solution. Yield based on Pb(NO3)2: 38%. FT–IR (ν, cm−1): 3076, 3060, 3008, 2920, 2898, 1662, 1652, 1586s, 1564, 1474, 1434, 1374, 1306s, 1218, 1148, 1104, 1036, 1000s, 986, 942, 782, 748, 626, 506, 406. 1H NMR (400 MHz, DMSO-*d*6): δ (ppm) 8.99 (m, 2H, py), 8.86 (s, 2H, −N=CH−py), 8.01 (m, 4H, py), 7.60 (m, 2H, py), 4.17 (s, 4H, =NCH2CH2N=). Anal. Calcd for C14H14Br2N4Pb (605.30): C, 27.78; H 2.33; N 9.26%. Found: C 28.04; H 2.45; N 9.38%.

#### *2.2. Single Crystal Structure Determination of 1–3*

Crystallographic data for the structures were collected on an Oxford Diffraction Gemini (**1**) and Bruker D8 Quest diffractometers (**2**, **3**) using Mo *Kα* (*λ* = 0.71073 Å) radiation. Following analytical absorption corrections and solution by direct methods, the structures were refined against *F*2 with full-matrix least-squares using the program SHELXL-2019/2 [20]. Anisotropic displacement parameters were employed for the non-hydrogen atoms. The (N22, N23A) cation in **1** was modelled as being disordered over two sets of sites with site occupancies constrained to 0.701(5) and its complement. The hydroxyl and water molecule hydrogen atoms (**1**, **2**) were located from the experimental data and refined with O−H distances restrained to their idealized values. Other hydrogen atoms were added at calculated positions and refined by the use of a riding model with isotropic displacement parameters based on those of the parent atom. Details of the data collection and processing, structure solution and refinement are summarized in Table 1, while the selected bond lengths and

angles are presented in Table 2. CCDC 2217143, 2223148 and 2223147 contain the supplementary crystallographic data for this paper. These data can be obtained free of charge from the Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk/data-request/cif.

**Table 1.** Crystallographic parameters and refinement data for **1**−**3**.

#### *2.3. Theoretical Calculations*

The ORCA 5.0.3 package [21,22] was used for all DFT calculations. Range-separated ωB97M-V functional [23] with the ZORA-def2-TZVPP basis sets [24] and SARC/J auxiliary basis set [25,26] were used for all atoms except of Pb, for which the SARC-def2-TZVPP [25] basis set was applied. *AutoAux* keyword [27] was used to generate other auxiliary basis sets in all cases. The zero-order regular approximation (ZORA) [28] was used because of the presence of heavy elements. The crystal field was accounted for by means of the conductorlike polarizable continuum model (C-PCM) [29] with *ε* = infinity. The SCF optimization convergence criteria were settled with *VeryTightSCF* keywords, and integration grids of high density (*Defgrid3* keyword) were employed. Analysis of bond critical points and non-covalent interactions indexes was performed using the Multiwfn 3.8 program [30]. Visualization of the reduced density gradient [31] isosurfaces was performed by means of VMD 1.9.4a53 program [32].

#### **3. Results and Discussion**

#### *3.1. Synthesis and Characterization*

The mechanism of the formation of a substituted imidazo[1,5-*a*]pyridinium cation has been suggested by us before [8]. In the present study, the primary addition of Ea·HCl to FA aqueous solution yields 2-(methyleneamino)ethanol (Scheme 2). The subsequent 2-PCA attack on the protonated Schiff base A initiates condensation with the intermediate B. The intramolecular nucleophilic attack onto the aldehyde carbon atom by the amine nitrogen brings the product of cyclization C, which experiences an irrevocable dehydration reaction affording the aromatic heterocyclic cation [L1]+. The dehydration of the five-membered ring results in the formation of two double bonds and the delocalization of the positive charge on N atoms in a resonance structure. The reaction does not require the presence of metal ions.

**Scheme 2.** Proposed mechanism of the formation of [L1]+cation.

The lead chloride hybrid perovskite **1** formed by self-assembly from the in situ prepared monovalent organic cations, Pb2+ and chloride ions at an overall 1PbCl2:4CH2O: 4Ea·HCl:4(2-PCA) mole ratio. It is insoluble in alcohols and water and slightly soluble in *N*,*N*-dimethylformamide (DMF) and dimethylsulfoxide (DMSO); it is indefinitely stable in air. Similar reaction procedures that used Ea or En combined with HBr did not afford the respective imidazo[1,5-*a*]pyridinium cations, presumably due to the insufficient acid strength.

The IR spectra of **1**−**3** confirmed the presence of aromatic rings, alkyl and other functional groups (Figures S1–S3). The spectrum of the hybrid compound **1** demonstrates a distinctive pattern, which was suggested to characterize the imidazo[1,5-*a*]pyridinium skeleton [8,11,12]: the sharp very strong peaks attributed to aromatic C–H vibrations (3116–3060 cm−1), medium intensity sharp bands at 1654 and 1544 cm−1 associated with heterocyclic ring stretching, an intense absorption at 1150 cm−1 and three peaks in the region of out-of-plane C–H bending (796, 750 and 636 cm−1). The very intense band, due to ν(O–H) vibration at 3400 cm−1, dominated the spectrum; another intense absorption was ascribed to C–O stretching (1076 cm−1). In the case of compounds **2** and **3**, the aromatic ν(C– H) bands above 3000 cm−1 are much weaker. The spectrum of compound **2** is dominated by a peak at 1048 cm−1 due to ν(C–O), while the absorption of moderate intensity due to O–H stretching (3392 cm−1) is broad. ν(C=N) + ν(C=C) stretching frequencies of the metal coordinated Schiff bases are observed at 1654, 1590 cm−1 (**2**) and 1652, 1586 cm−1 (**3**).

The compounds are easily distinguishable by their 1H NMR spectra that demonstrate the sets of signals, as well as the correct alkyl/aromatic proton ratios expected for [L1]+ cations and the Schiff base ligands. In the room temperature (r.t.) spectrum of compound **1** in DMSO-*d*6, CH protons in the imidazolium ring appear as singlets at δ = 10.01 and 8.32 ppm, the alkyl groups protons are observed as multiplets at 4.67 and 3.92 ppm. The imine protons in **2** and **3** are detected at 8.50 and 8.86 ppm, respectively, while the protons of CH2 groups appear as two multiplets at 3.76 and 3.71 (**2**) and one multiplet at 4.17 ppm (**3**). The hydroxyl protons in **1** and **2** are observed distinctly at 5.23 and 4.40 ppm, respectively.

#### *3.2. Structural Description of 1–3*

The asymmetric unit of the lead chloride hybrid **1** is comprised of two [L1]+ cations, [Pb2Cl6] 2– anionic fragment and water molecule of crystallization (Figure 1). Two crystallographically non-equivalent cations configurations are very similar; the (N22, N23A) cation is disordered over two sites, with occupancies of 0.701(5) and 0.299(5)-. The pyridinium rings bond distances of their fused heterocyclic cores are uneventful; the N−C bond lengths in the imidazolium entities fall in the range 1.331(7)–1.414(6) Å. The N atoms are planar, showing a sum of three angles of 360◦. In the cores, the five- and six-membered rings are nearly coplanar, with the respective dihedral angles of 1.35, 1.73 and 2.98◦.

**Figure 1.** Asymmetric units and principal atom labelling for [L1]2n[Pb2Cl6]n∞·nH2O (**1**) and [PbBr2(L2)]n∞·0.5nH2O (**2**) with the 50% probability ellipsoids. The major component of the disordered (N22, N23A) cation of **1** is shown.

The distorted octahedral environment of Pb1 atom in the anionic motif consists of two terminal, two *μ*2-Cl and two *μ*3-Cl atoms, while the distorted octahedron around Pb2 is built of two *μ*2-Cl and four *μ*3-Cl ligands (Figure 2a). The metal–chloride distances vary in the range 2.6509(14)–3.1516(14) Å. The average value of 2.907 Å is reasonable for Pb(II) ions in chloroplumbates(II) with strong ionic Pb–Cl bonds [33,34]; the *cis* and *trans* angles at the metal atom fall in the ranges of 77.50(4)–107.33(5)◦ and 162.86(5)–177.20(4)◦, respectively (Table 2), showing a strong degree of distortion of the metal polyhedra. The PbCl6 octahedra are joined by three-edge- and five-edge-sharing into a 1D twin lead(II) chloride wire of 10.344 Å width, lying in the *a*-axis direction (Figure 2a,b). The bulkier 2-(2-hydroxyethyl)- 2H-imidazo[1,5-*a*]pyridinium cation in **1**, if compared to its methyl analogue [8], expectedly templated the formation of a low-dimensional anionic perovskite frame, however, with a different type of a double chain. This set of connectivity modes within a double chain was not observed in the lead(II) chloride hybrid compounds in accordance with our survey of the Cambridge Structural Database [35]. The type of edge-sharing within a double haloplumbate(II) chain shown in the inset of Figure 2b is more frequent and found in, for example, 1D lead chloride perovskites with substituted diammonium and piperidinium dications [6,36].

**Table 2.** *Cont.*

[a] Symmetry codes: 1 *x* − 1, *y*, *z*; 2 −*x*, −*y* + 1, −*z* + 1; 3 −*x* + 1, −*y* + 1, −*z* + 1; 4 1/2 − *x*, *y*, 1/2 + *z*.

In the crystal, non-equivalent [L1]+ cations of **1** form separate stacks parallel the *a-*axis with the fused heterocyclic cores of neighboring entities being strictly coplanar (Figure 2c). Centrosymmetically related trans-oriented [L1]+ cations are stacked with varying levels of offset, showing the ring centroid distances of 3.456, 3.651 Å for (N12, N13A) and 3.839, 5.258 Å for (N22, N23A) cations enabling the possibility of weak π-bonding [37]. Hydrogen bonds of O−H···O/Cl and C−H···O/Cl types with the involvement of the OH group of the organic cation and water molecule (Table 3) strengthen the hybrid salt structure. The introduction of OH group on the cation enabled a stronger interaction between cationic and anionic counterparts in **1** through additional conventional hydrogen bonding, which is absent in the lead chloride hybrid with methyl derivative of [L1]+ cation [8]. The new type of a double chain realized in **1** may also be considered a result of such a modification of the organic cation.

**Figure 2.** (**a**) Fragment of the 1D twin offset chloroplumbate(II) chain in **1**. The symmetry codes have the same numbering as those in Table 2; (**b**) polyhedral representation of the same fragment; the inset shows a common type of edge-sharing within a double haloplumbate(II)wire; (**c**) fragment of the crystal packing of **1** demonstrating spatial arrangement of the organic and inorganic counterparts (the major component of the disordered (N22, N23A) cation is shown).

**Table 3.** Geometry of hydrogen bonds for **1**−**3** (Å and ◦) [a].

**Table 3.** *Cont.*

[a] Symmetry codes: 1 –*x* + 1, –*y*, –*z* + 1; 2 –*x*, –*y*, –*z* + 1; 3 *x* – 1, *y*, *z*; 4 –*x* + 1, –*y*, –*z*; 5 –*x* + 1, –*y* + 1, –*z*; 6 –*x* + 1, –*y* + 1, –*z* + 1; 7 –*x*, –*y* + 1, –*z* + 1; 8 −*x* + 1/2, *y*, *z* + 1/2; 9 −*x* + 1/2, *y*, *z* + 1/2; 10 −*x,* −*y* + 1*,* −*z*; 11 −*x* − 1/2*, y, z +* 1/2; 12 −*x* − 1/2, *y*, *z* − 1/2; 13 *x*, −*y* + 3/2, *z* − 1/2; 14 *x* – 1, *y* + 1, *z*; 15 *x* + 1, *y* – 1, *z*; 16 *x* + 1, *y*, *z*. [b] H bonds for the major component of the disordered (N22, N23A) cation are given.

Lead halide hybrid **2**, which crystallizes in the orthorhombic space group *Pccn*, consists of a 1D monobromo-bridged lead(II) polymer and water molecules of crystallization. The asymmetric unit of **2** is shown in Figure 1. In the double-sided, organically decorated chain structure, the nearest six-coordinate environment of each metal atom is formed by one tridentate Schiff base, one terminal and two *μ*2-Br ligands (Figure 3a,b). The neutral Schiff base ligand chelates the Pb1 ion by the N1 atom of the pyridyl ring, the imine N2 atom and O1 atom of the ethanol group with an average value of the Pb1−N distances of 2.57 Å, and the Pb−O1 bond [2.839(7) Å] being significantly elongated (Table 2). The metal distances to terminal and bridging bromide atoms are similar, with an average of 3.03 Å falling in the usual range for 1D lead(II) bromide systems [38,39]. The additional Pb···Br2{1/2 − *x*, y, −1/2 + *z*} contact of 3.378 Å is appreciably larger than the sum of the Shannon ionic radii of the octahedral lead(II) cation and bromide anion [*r*(Pb2+) + *r*(Br−) = 3.15 Å] and is barely significant in the construction of the bromoplumbate(II) chain. The bond angles at the Pb1 atom vary from 61.8(2) to 123.3(2)◦ and from 146.36(15) to 160.70(3)◦ (Table 2), evidencing the severe distortion of the metal polyhedron. The closest Pb···Pb separation within the chain is 4.4144(6) Å. In the crystal, two bromoplumbate(II) chains related by a crystallographic two-fold axis form a hydrophilic channel to host water molecules held by O–H···O hydrogen bonds (Figure 3c, Table 3). Numerous C–H···Br contacts result in a 3D supramolecular architecture.

Complex **3** belongs to the triclinic space group *P*¯ı; the dimeric molecule is located on an inversion centre (Figure 4). The geometry of Pb1 atom is that of an irregular pentagonal bipyramid, the equatorial plane consisting of four nitrogens from the tetradentate chelate L3 and the centrosymmetrically related bromide ligand Br1{1 − *x*, 1 − *y*, 1 − *z*} of the dimer, with two other bromides—Br1 and Br2—occupying apical positions. The Pb–N bond distances within the range of 2.621(6)–2.804(6) Å (Table 2) agree well with those of two other known Pb(II) complexes with L3 [40,41]. The Pb1–Br1{1 − *x*, 1 − *y*, 1 − *z*} bond is elongated at 3.2525(8) Å, in contrast to the average Pb1–Br1/Br2 bond length of 3.014 Å. The *cis* angles at the lead atom vary from 60.4(2) to 95.75(12)◦; the *trans* angles fall in the range 121.93(19)−176.39(16)◦. In the dimer, the Pb···Pb' separation is 4.7239(5) Å.

**Figure 3.** (**a**) Fragment of the double-side organically decorated bromoplumbate(II) chain in **2** [symmetry code: i 1/2 − *x*, *y*, 1/2 + *z*]; (**b**) polyhedral representation of the same fragment; (**c**) fragment of the crystal packing viewed down the *c*-axis showing spatial arrangement of two bromoplumbate(II) chains to form a hydrophilic channel filled with water molecules.

**Figure 4.** (**a**) Molecular structure and principal atom labelling of [PbBr2(L3)]2 (**3**), ellipsoids are shown at the 50% probability level [symmetry code: i 1 − *x*, 1 − *y*, 1 − *z*]; (**b**) the same molecule in a polyhedral form; (**c**) fragment of the 3D supramolecular network in **3** stabilized with C–H···Br hydrogen bonds (shown in blue, H atoms omitted).

In the solid state, the dimeric molecules of **3** are stacked identically, forming columns parallel to the *ab* plane, with the Pb2Br4 moieties in the column being strictly coplanar (Figure 4c). The minimal Pb···Pb distance in the lattice is 8.1348(6) Å; no effective πoverlap is observed. C–H···Br hydrogen bonding (Table 3) consolidates an extended supramolecular 3D network structure (Figure 4c). The contacts strength depends on their direction in the crystal lattice. In the *ab* plane, the interactions are represented by four distinct crystallographically independent C–H···Br hydrogen bonds with *d*(C···Br) < 3.9 Å (Table 3). Every dimeric molecule of **3** forms 16 respective contacts with the four nearest molecules in the *ab* plane. The dimeric molecules along the *c* axis are bridged by weaker C–H···Br hydrogen bonds with *d*(C···Br) > 3.9 Å (Table 3).

#### *3.3. Hirshfeld Surface and QTAIM Analyses*

The set of intermolecular interactions in complex **1** can be viewed as a combination of contacts between crystallographically independent (N12, N13A) and (N22, N23A) [L1]+ cations, negatively charged [Pb2Cl6]n 2n– chains and water molecules. The HS of both [L1]+ cations surrounding a fragment of the [Pb2Cl6]n 2n– chain is shown in Figure 5. Here, and further on, the colours on the surface correspond to shortened contacts (red), van der Waals (vdW) interactions (white) and contacts with longer distances (blue).

**Figure 5.** Hirshfeld surface mapped over *d*norm of (N12, N13a) and (N22, N23A) [L1]+ cations for compound **1** (view along the *a* axis, the major component of the disordered (N22, N23A) cation is shown).

Both [L1]+ cations reveal involvement in several distinct hydrogen bonds (Table 3), which are identifiable in the fingerprint plots (Figure 6). The plots are characterized by broad segments of H···H interactions (Figure 6), while the C···C ones are much less abundant (5.4 and 4.3% for (N12, N13A) and (N22, N23A) independent cations, respectively, Figure S4).

The weak interactions between the stacked cations were evaluated by the analysis of reduced density gradient (RDG) [31] of the electron density calculated at the ωB97M-V/ZORA-def2-TZVPP level using crystallographic atomic coordinates (Figure 7). In line with the HS analysis results, the non-covalent contacts in the tetramer {(N12, N13A)-[L1]4·2H2O}4+ are mostly characterized by the broad vdW areas between stacked imidazo[1,5-*a*]pyridine moieties. These findings indicate that [L1]+ cations in their stacks are too offset to engage in appreciable π-bonding. At the same time, the chain of (N12, N13A)-[L1]+ cations is supported by the strong attractive interactions involving water molecules (O121–H121···O01W), for which the electron density at the bond critical

point—*ρ*BCP(**r**) (3, −1) between the H121 and O01W atoms—is 0.02504 a.u. According to the dependence for charged assemblies reported in [42], the obtained value of *ρ*BCP(**r**) corresponds to 39.3 kJ mol−1 of binding energy (BE) between the (N12, N13A)-[L1]+ cation and water molecule. However, as the BE vs. *ρ*BCP(**r**) dependences [42] were developed for assemblies with a single overall charge (in contrast to 4+ charge of the tetramer), the obtained binding energy value has only indicative significance.

**Figure 7.** Reduced density gradient surfaces (isovalue of 0.5) showing vdW interactions (green area) between [L1]+ cations and strong hydrogen bonds with participation of water molecules in the crystal structure of **1** (the major component of the disordered (N22, N23A) cation is shown). The colour scheme corresponds to the sign(λ2)*ρ*(**r**) function with the second largest eigenvalue of the Hessian of electron density, λ2, at respective points: negative (blue, strong attraction), nearly zero (green, vdW interaction), positive (red, strong repulsion).

The monomeric fragment [PbBr2(L2)] of the 1D chain in complex **2** was used to construct the Hirshfeld surface (Figure 8). The fingerprint plots disclose several distinct non-covalent contacts mostly H···O and H···Br in nature (Figures 8 and S5). The strongest hydrogen bonds between O1 and O1W atoms are reflected by sharp "peaks" having the shortest *d*e and *d*i distances in the fingerprint plots (Figures 8 and S5). The *ρ*BCP(**r**) electron density at BCP between H1 and O1W atoms was estimated as 0.01986 a.u., from which the binding energy of the respective contact can be evaluated as –15.4 kJ mol−1 (according to the equation for non-charged assemblies [42]). This energy strength can be classified as "weak-to-medium" [42]. The RGD isosurfaces of the vdW contacts between the aromatic groups in **2** are shown in Figure 9.

**Figure 8.** Top left: fragment of the crystal structure of **2** viewed down the *c* axis showing the HS of the fragment [PbBr2(L2)]. Top right: selected fingerprint plots. Bottom: contributions of the specific Xi···Xe contacts.

**Figure 9.** Reduced density gradient surfaces (isovalue of 0.5) showing vdW interactions (green area) between aromatic fragments and strong hydrogen bonds involving water molecule for compound **2**.

The dimeric molecules of **3** create a network of non-covalent interactions, of which the highest contribution (40.9%) to the HS is from numerous H···H contacts (Figures 10 and S6). The latter form a broad surface with no distinct directions (Figure 11), except of the C8–H8A···H8A1−C81 ( 1 =2– *x*, –*y*, –*z*) interaction between methylene groups [*d*(C···C) = 4.379(15) Å] and a pair of weak interactions between pyridine rings C13–H13A···H14A–C141 and C14–H14A···H13A–C131 [ 1 =2– *x*, 1 – *y*, 1 – *z*; *d*(C···C) = 4.072(18) Å]. As can be seen from the particular Hirshfeld surface, the Br···H and H···Br contacts are mostly located in the *ac* plane (Figure 11). Since the molecules of **3** has no electrical charge, the strengths of these contacts can be estimated [42] from the *ρ*BCP(**r**) electron density with sufficient precision (Table 4).

**Figure 10.** Left: Hirshfeld surface of the dinuclear molecule of **3** surrounded by the closest molecules (view along the *b* axis). Right: selected fingerprint plots of the respective surface. Bottom: contributions (in %) of specific Xi···Xe interactions.

**Figure 11.** Hirshfeld surface of the dinuclear molecule of **3** highlighting regions of specific interactions.

**Table 4.** Electron density at the H···Br BCP and respective binding energies for selected intermolecular contacts in the structure **3** [a].

[a] binding energies were estimated according to the equation for non-charged assemblies [42]; [b] symmetry operations have the same numbering as those in Table 3.

Inspection of the geometry and Hirshfeld surface suggests the existence of the contact C8–H8B···C61 [ 1 = 1 – x, 1 – y, –z; *d*(C···C) = 3.722(10) Å, ∠(C–H···C) = 161.1◦] between methylene CH2 group and imine carbon atom of the neighboring molecules. However, despite the hydrogen atom being clearly oriented towards C6 one, the respective bond critical point is located rather between H8B and C51 atoms (Figure 12). Further analysis of the RDG isosurfaces disclosed the existence of a broad non-covalent interaction region between H8B donor and C41, C51 and C61 ( 1 = 1 – x, 1 – y, –z) atoms as acceptors containing 0.0054 electrons (Figure 12). The negative *q*bind index [43] of this domain (–0.00046383) accounts for a weak attractive interaction. The aromatic moieties of the ligand L3 in the molecule of **3** contact each other through vdW interactions (Figure S7).

**Figure 12.** Top: plots of the Laplacian of the electron density in the real space, ∇2*ρ*(r), for selected weak contacts. Bottom left: 2D cut plane of the RDG function for the same projection as in the top left plot. Bottom right: 3D isosurface of the RDG (isovalue of 0.5) illustrating non-covalent interactions in the H8B—C41/C51/C61 groups of atoms (1 = 1 – x, 1 – y, –z).

#### *3.4. Optical Properties of 1–3*

The optical diffuse reflectance spectra of all the compounds were measured using powder samples at r.t. (Figure 13a). According to the analysis of the spectra by the Tauc plot based on the assumption of direct band gap, [*F*(*R*)*h*ν] 2 vs. *h*ν (where *F*(*R*) denotes the Kubelka–Munk function, *h*ν is photon energy in eV), the optical band gap values of **1**, **2** and **3** were estimated to be 3.36, 3.13 and 2.96 eV, respectively (Figure 13b). The values of **1** and **2** are comparable to those of reported 1D hybrid lead perovskites, such as [H2bpp]Pb2Cl6 (3.55 eV), [H2bpp]Pb2Br6 (3.30 eV; bpp = 1,3-bis(4-pyridyl)-propane) [38], [2,6-dmpz]3Pb2Br10 (3.12 eV; 2,6-dmpz = 2,6-dimethylpiperazine), [hex]PbBr3 (3.41 eV; hex = hexamethyleneimine), [hep]PbBr3 (3.50 eV; hep = heptamethyleneimine) [39]. Using density functional theory calculations, [2,6-dmpz]3Pb2Br10, [hex]PbBr3 and [hep]PbBr3 were found to be direct band gap semiconductors [39]. Their valence band maximum (VBM) is composed of mixed Br-p and Pb-s orbitals, while empty Pb-p orbitals constitute conduction band minimum (CBM). In the case of two H2bpp hybrid lead halides, the VBM was derived from hybridization of Pb-6p and Cl-3p or Br-4p orbitals, and CBM mainly originated from the C-2p/N-2p states of the bicyclic organic cations [38].

**Figure 13.** Diffuse reflectance spectra measured using powder samples of **1**–**3** at r.t. (**a**) and the Tauc plots in the range 2.5–4 eV based on the assumption of direct band gap calculated from the reflectance spectra of **1**–**3** (**b**).

Within the series of 1D and 2D lead bromide hybrids [39], the electronic structure was suggested to depend on the connectivity mode of PbBr6 octahedra, where the cornerconnected compound [4-amp]PbBr4 [4-amp-4-(aminomethyl)piperidine] exhibits the smallest band gap value (2.93 eV). The face-sharing compounds [hex]PbBr3 and [hep]PbBr3 possess larger band gaps than [2,6-dmpz]3Pb2Br10 with the edge- and corner-connecting structure. The band gaps successively going up from "corner-sharing" to "edge-sharing" and further "face-sharing" have also been observed in the lead iodide perovskite-derived organic–inorganic hybrids [44]. The band gaps of edge-sharing **1** and corner-sharing **2** perovskites follow the general trend.

#### **4. Conclusions**

In this study, we aimed to explore the templating effect of imidazo[1,5-*a*]pyridiniumbased cation with hydroxyl functionality on the dimensionality of the lead halide anionic framework and connectivity modes of the [PbHal6] 4– octahedra, as well as H-bonding interactions in the resulting hybrid lead halide perovskite. To this aim, Ea·HCl was used in the developed protocol for the synthesis of substituted imidazo[1,5-*a*]pyridinium cations by the acid catalyzed oxidative cyclocondensation of FA, amine and 2-PCA. The obtained in

situ [L1]+ cation directed the formation of the 1D chloroplumbate [L1]2n[Pb2Cl6]n∞·nH2O (**1**), revealing a new type of the [Pb2Cl6]∞ twin chain constructed from three-edge- and fiveedge-sharing PbCl6 octahedra. In the case of [PbBr2(L2)]n∞·0.5nH2O (**2**) and [PbBr2(L3)]2 (**3**), the introduction of HBr—the necessary acid component and source of bromide anions directly to the reaction media subverted the expected oxidation cyclization and instead facilitated the amine-aldehyde condensation between 2-PCA and Ea or En, respectively. The isolated hybrid lead bromide **2** features a chain of corner-sharing PbBr3N2O octahedra, decorated with the tridenate Schiff base ligands on both sides. In the 0D dimer **3**, two irregular PbBr3N4 pentagonal bipyramids are connected by edge sharing. The Hirshfeld surface and QTAIM analyses disclosed the presence of numerous weak interactions between molecular and polymeric fragments in the structures of **1**–**3**. The band gaps of **1** (3.36 eV) and **2** (3.13 eV) with different connectivity follow the general trend of edge-sharing perovskites exhibiting larger band gaps than corner-sharing structures.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www. mdpi.com/article/10.3390/cryst13020307/s1, Figure S1: IR spectrum of [L1]2n[Pb2Cl6]n∞·nH2O (**1**); Figure S2: IR spectrum of [PbBr2(L2)]n∞·0.5nH2O (**2**); Figure S3: IR spectrum of [PbBr2(L3)]2 (**3**); Figure S4: Selected fingerprint plots of the (N12, N13A) and (N22, N23A, major component) [L1]+ cations in the crystal structure of **1** showing Xi···Xe interactions (where X = Cl, O, C or H); Figure S5: Selected fingerprint plots of the fragment [PbBr2(L2)] in the crystal structure of **2** showing Xi···Xe interactions (where X = Br, O, C or H); Figure S6: Selected fingerprint plots of the dinuclear molecule of **3** showing Xi···Xe interactions (where X = Br, N, C or H); Figure S7: Reduced density gradient surfaces (isovalue of 0.5) showing weak vdW interactions (green area) between aromatic fragments of the ligands L3 in the molecular structure of **3** (lead and bromine atoms were excluded from calculations).

**Author Contributions:** Conceptualization, O.Y.V.; methodology, O.Y.V. and D.S.N.; investigation, O.Y.V., E.A.B., O.V.N. A.N.S. and D.S.N.; writing—original draft preparation, O.Y.V. and D.S.N.; writing—review and editing, O.Y.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** The work was performed with the support of the Ministry of Education and Science of Ukraine (project 22BP037-13, grant for the perspective development of the scientific direction 'Mathematical sciences and natural sciences' at the Taras Shevchenko National University of Kyiv) and the Fundação para a Ciência e Tecnologia (FCT), Portugal (projects UIDB/00100/2020, UIDP/00100/2020, and LA/P/0056/2020 of Centro de Química Estrutural, contracts IST-ID/086/2018 and IST-ID/117/2018).

**Data Availability Statement:** Crystallographic data for the structures reported can be obtained free of charge from the Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk/data-request/cif (accessed on 27 January 2023) quoting the deposition numbers CCDC 2217143 (**1**), 2223148 (**2**) and 2223147 (**3**).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.


**2. Definition of pulmonary rehabilitation**

Pulmonary rehabilitation (PR), which is a cornerstone in the non-pharmacological management of COPD, is defined by the American Thoracic Society/European Respiratory Society (ATS/ERS) as a "comprehensive intervention based on a thorough patient assessment followed by patient-tailored therapies that include, but are not limited to, exercise training, education, and behavior change, designed to improve the physical and psychological condition of people with chronic respiratory disease [2, 3]. PR is an evidence-based, multidisciplinary, and comprehensive intervention for patients with chronic lung disorders who are symptomatic and have some disability. Through stabilizing or reversing systemic signs of the disease, pulmonary rehabilitation aims to reduce symptoms, optimize functional state, increase participation, and reduce healthcare costs. To put it another way, depending on the stage of the disease, a symptomatic COPD patient has some functional compromise that can be rectified by rehabilitation [3]. In recent years, there has been increasing interest in the role of PR in the acute setting (either during or shortly after a hospital admission for AECOPD) [2].

Health behavior change is vital for optimization and maintenance of benefits from any intervention in chronic care, and PR has taken a lead in implementing strategies

**Figure 1.** *Spectrum of support for chronic obstructive pulmonary disease [5].* *Current and Contemporary Developments in Pulmonary Rehabilitation DOI: http://dx.doi.org/10.5772/intechopen.107050*

to achieve this goal. This model may provide more clarity on the material and methods used to achieve various levels of support. It aids in the defining of terminology and may assist practitioners in determining a person's requirements and the amount of care necessary [4]. Healthcare professionals interested in the field might use this tool to help construct interventions, identify appropriate outcome measures, and define the intervention in a standardized way. The most comprehensive PR program, which includes self-management, should be prioritized for the most severe patients, which is referred to as integrated care (**Figure 1**). The minimal "action plan" intervention may be sufficient for less complicated patients with basic demands [5]. Longterm health maintenance in the face of a progressive disease is challenging. Several studies have suggested that the only approach to maintain changes in health status is to change one's behavior. Cognitive behavioral approaches have been offered as therapies that could help people change their habits. The text recognizes self-efficacy as a critical component of behavior change. Behavior modification may be more successful if weaknesses in self-efficacy are identified and manipulated [5].

## **3. Rationale and outcomes**

Recent evidence-based reviews have confirmed the effect of PR on COPD outcomes, including improved exercise capacity, reduced dyspnea and leg discomfort, improved quality of life (QoL), enhanced self-efficacy, and improved activities of daily living. PR has positive impacts on lung health without having any discernible impact on standard lung function tests like forced expiratory volume in one second (FEV1) [3]. The fact that PR lessens the systemic symptoms of COPD and its prevalent comorbidities provides a clear explanation for this discrepancy. Peripheral muscle dysfunction as a result of physical inactivity or systemic inflammation, muscle wasting, inadequate self-management skills, anxiety, and depression are all significant systemic effects of COPD [5]. Systemic effects and comorbid conditions contribute to the disease burden and might be amenable to therapy. For example, physical conditioning of leg muscles through exercise training reduces lactate production and decreases ventilator load. COPD patients with a decreased ventilatory load can breathe more slowly during exercise, reducing dynamic hyperinflation. These effects usually reduce exertional dyspnea, even without a change in FEV1 [3, 5].


**1. Introduction**

Tree nuts have high nutrient contents, including oils, proteins, and carbohydrates [1]. Due to their high pleasant flavor and various benefits for human health, tree nuts have gained increasing popularities worldwide, and are consumed as healthy snacks or food ingredients for cooking [2]. The global market of tree nuts was reported at US\$88.8 billion in 2020, and it is expected to grow continuously to US\$103 billion by 2027 [3]. Commonly consumed tree nuts include almonds, walnuts, pistachios, pecans, macadamia nuts, hazelnuts, and cashews, etc. Among them, almonds, walnuts, and pistachios are the most popular types, accounting for almost 70% of total tree nuts production in the world [4]. The global production mass of almonds, walnuts, and pistachios in 2020 were: 1,700,000, 2,300,000 and 985,000 metric tons, respectively, which increased 15%, 20% and 37%, respectively, compared to the 2019 harvest season [5].

Tree nuts are usually harvested in a relative short harvest season (about 1–2 months from late summer to early fall). The harvested nuts need to fulfill the year-round consumption. Almost all tree nuts are composed of a thick and wet hull that wraps the shell and kernel inside at harvest (**Figure 1**). As the result, freshly harvested tree nuts usually have high initial moisture contents (IMCs) and water activity. Such characteristics make fresh tree nuts vulnerable to spoilage and quality deterioration after harvesting [7, 8]. Therefore, artificial drying is critical to preserve the quality and safety of the nuts. Meanwhile, since tree nuts are rich in unsaturated fatty acids [9, 10], their oil quality is sensitive to the thermal drying

**Figure 1.**

*The photos of walnut, almond and pistachio at different stages of drying (in-hull, in-shell, unpeeled kernel, and peeled kernel) [6].*

process [11–13]. Thus, tree nuts need to be dried appropriately and efficiently after harvesting to ensure the quality, safety, and market value of dried products [14–18].

Prior to harvest, plants usually have very good natural defense mechanisms against microbial spoilage. After harvesting, the high moisture contents (MCs) and nutrient contents make them vulnerable to microbial spoilages. Any food safety problems associated with the regional tree nuts production could cause international outbreaks and significantly impact the human health [19–21]. Drying alone usually cannot achieve adequate disinfection and disinfestation. Therefore, further disinfection and disinfestation are critical for extending the shelf life and safety of the dried products [22, 23]. Depending on the type of the final products, further processing, such as roasting, blanching and kernel peeling, may also be needed to produce desired products for consumption.

In addition, thermal and chemical processing of tree nuts are energy intensive and cause significant environmental impacts [24, 25]. It is worthy of noticing that the food production sector is responsible for one-quarter of the world's total greenhouse gas emissions [26] and consumed 200 EJ energy per year [27]. The fastgrowing population, increasing production volume and market demands for food production will put more pressure and challenges on the industries for higher processing throughput and efficiency [28]. In the 2021 United Nations Climate Change Conference (COP 26), the world leading countries have committed to achieve 'net zero' carbon neutrality goals by 2050 [29, 30], which needs contributions from all sectors, including the postharvest processing of tree nuts.

In the following sections, the current status, recent advances, and challenges in the postharvest processing technologies are summarized using walnuts, almonds and pistachios as examples.

#### **2. Conventional harvest and postharvest processing methods**

Due to similar hull-shell-kernel multiplayer structures (**Figure 1**), the postharvest processing operations, including cleaning, dehulling and drying, etc. are similar for different types of tree nuts. Meanwhile, due to the differences in the shell conditions, MCs and lipid compositions, the processes have some differences.

In California and Australia, almonds are shaken off trees when they are mature and dried on-ground in orchards (**Figure 2**), taking advantage of the hot and dry

**Figure 2.**

*Harvesting and post-harvest processing of almonds: (A) almond shaking; (B) on-ground drying; (C) stockpiling; (D) off-ground harvester (figures obtained from industrial partner or taken by the author's lab).*

weather during the harvest season [31, 32]. Conventional drying process takes 7–14 days depending on the weather condition, until the overall MC of whole almonds achieved about 12% on wet basis (while the kernel moisture reaches about 6%). Dried almonds are swept together into windrows and picked up by machineries, which are then stockpiled outdoor for temporary storage. The stockpiles are aerated, which allows the product moisture to equilibrate before mechanically cleaned and de-hulled with abrasive huller [33]. Currently, two major problems with this procedure are: (1) the sweeping and picking up generate large amount of dust, which spreads away in the air and causes pollution [34]; (2) almonds contact the soil directly while drying on-ground, which induces severe insect damage and microbial spoilage [35, 36]. In Europe (mainly Spain), almonds are harvested off-ground and de-hulled in-field, which are then dried in silo dryers with air [31]. Recently, the Almond Board of California (ABC) and Almond Board of Australia are also supporting research in developing off-ground harvesting technology to mitigate the problems of conventional harvesting [37]. Meanwhile, it brings up critical needs to dry the high-moisture almonds artificially and efficiently and to handle the large volume of production in the short harvest season for product quality and safety.

The harvesting method of walnuts are similar to almonds. However, since walnut shell is harder and thicker than that of the almond, natural drying is not efficient enough to dry the inside of them. If the walnuts stay too long on the ground, microbial spoilage becomes significant. Therefore, after drying on the orchard floors for several days, the walnuts are mechanically swept and transferred for washing, mechanical de-hulling and artificial drying of in-shell walnuts with hot air (HA) heating [38]. Typically, walnuts are dried at around 43°C (110°F) until the MC of the walnuts are below 8% (w.b.) in the bin dryers (**Figure 3**).

**Figure 3.**

*Typical harvesting and postharvest processing of walnuts: (A) walnut shaking; (B) hulling and washing section; (C) hot air drying bins.*

This process can take as long as 24 h [39]. This conventional heated air drying method has the advantages of large processing capacity and relatively low operating cost [2]. Currently, there are three major concerns with this process: (1) the efficiency and throughput of the current drying method may not fulfill the growing production volume, resulting in significant product loss due to insufficient or inappropriate drying [5]; (2) walnut drying is very energy-intensive [2, 40] and causes large amount of carbon emission, thus efficient drying methods are needed to improve the sustainability; (3) freshly harvested walnuts have wide distribution of IMCs [41]. Drying the walnuts with different MCs together leads to over-dried or under-dried products, causing quality deterioration, food safety risk, and energy waste [42]. Therefore, it is desirable to sort the walnuts with different MCs first based on MCs and conduct the drying separately to improve moisture uniformity in products and avoid problems from current drying methods.

Pistachios are commonly harvested off-ground and dried artificially (**Figure 4**). Pistachio nuts have hard and naturally enclosed shell, which significantly restrict the moisture transfer rate, and natural drying is not popular [44]. In a typical process, pistachios are firstly de-hulled, washed, and dried with HA to pop-open the shells. A second hulling process is then used to remove the remaining hulls to obtain the in-shell pistachios. After that, the open-shell nuts and closed-shell nuts are separated with a rotating sieve [45]. After removing the remaining foreign

#### **Figure 4.**

*Harvesting and post-harvest processing of pistachios in California: (A) off-ground harvesting [43]; (B) mechanical dehulling; (C) cylindrical hot air drying.*

materials, defected or stained nuts, the pistachios may be further dried in batch or continuous dryers with HA the kernel reaches 5% MC to ensure the safety of the dried nuts [46–48].


**3.2.2 Functional architecture of the broadband communications manager**

Functional architecture of the BCM is based on message exchange between the manager itself and two types of external entities such as terrestrial applications and train-side systems. The BCM is divided into 5 modules (Fig. 4) that handle processing and deployment of all the functionality.

Fig. 4. Functional architecture of BCM, composed of five modules: Terrestrial Application Handler, Train-Side Systems Handler, Request Manager, Activity Log and Management Console.

To have a global vision of the performance of the BCM, it is necessary to focus on three modules which carry out the most important functionality:

1. **Terrestrial Applications Handler.** It will be responsible for managing all the messages exchanged between each terrestrial application and the BCM. Its basic functionality is to receive the XML messages coming from terrestrial applications and generate an appropriate response. This communication is bidirectional, and it is the responsibility of the terrestrial application to start and finish it.

To streamline the management of communications between terrestrial applications and the BCM, the connections are managed independently (through a dedicated thread). The main functionality offered by this module would be the next one:

This module is similar to the Terrestrial Applications Handler. It receives XML messages from the communication module of each train and generates the responses. In this case, the primary goal of the module is to indicate when a train is connected to a WiFi network and its IP address. This data is very important for terrestrial applications to communicate with train-side systems.

There is a very important task that Train Communication Module manages, it is: the disconnection or closure of the connection between the train and the BCM. When a train reaches a station with WiFi connectivity, it connects to the WiFi network and establishes a communication with the BCM. After that, two scenarios can occur: in the first one, the train has no pending communication request from terrestrial applications. In this case, the manager sends a connection ending message to the train and the connection is closed. In the second scenario, a train is disconnected from the WiFi network because of its movement or a

Fig. 4. Functional architecture of BCM, composed of five modules: Terrestrial Application Handler, Train-Side Systems Handler, Request Manager, Activity Log and Management

To have a global vision of the performance of the BCM, it is necessary to focus on three

1. **Terrestrial Applications Handler.** It will be responsible for managing all the messages exchanged between each terrestrial application and the BCM. Its basic functionality is to receive the XML messages coming from terrestrial applications and generate an appropriate response. This communication is bidirectional, and it is the responsibility of

To streamline the management of communications between terrestrial applications and the BCM, the connections are managed independently (through a dedicated thread). The main

Establish and close the connection between terrestrial applications and the BCM.

exchanged between the communication module of each train and the BCM.

Receive communication completed messages from terrestrial applications.

Send messages to a terrestrial application in order to start communication requests.

2. **Train-Side Systems Handler.** It will be responsible for managing all the messages

This module is similar to the Terrestrial Applications Handler. It receives XML messages from the communication module of each train and generates the responses. In this case, the primary goal of the module is to indicate when a train is connected to a WiFi network and its IP address. This data is very important for terrestrial applications to communicate with

There is a very important task that Train Communication Module manages, it is: the disconnection or closure of the connection between the train and the BCM. When a train reaches a station with WiFi connectivity, it connects to the WiFi network and establishes a communication with the BCM. After that, two scenarios can occur: in the first one, the train has no pending communication request from terrestrial applications. In this case, the manager sends a connection ending message to the train and the connection is closed. In the second scenario, a train is disconnected from the WiFi network because of its movement or a

modules which carry out the most important functionality:

the terrestrial application to start and finish it.

Receive communication requests.

train-side systems.

functionality offered by this module would be the next one:

Console.

communication failure. The manager is constantly checking if the connection with the train is lost so this situation is detected as soon as it happens. There is a problem when the connection fails in the middle of a communication between a terrestrial application and a train-side system because the communication request has not finished correctly. To solve this problem, the next time the train connects to the BCM it sends back the start message of the broken communication to the terrestrial application in order to regain restart the communication. This pattern is repeated until the communication request is completed correctly, or is discarded because it exceeded the threshold of retries.

3. **Request Manager.** It will be responsible for managing communication requests between terrestrial applications and train-side systems, and to control when and under what circumstances the requests need to be attended.

As discussed above, the BCM splits communication shifts to terrestrial applications based on requests that they have performed. These requests are grouped by train, so the manager handles requests addressed to each train independently. The communication request for each train is sorted by the following criteria: (1) priority, which represents the 'urgency' by which a request must be addressed; (2) retries, it is taken into account the number of attempts to start a communication, to avoid the monopolization of the communication channel; and (3) parallelism, the manager can handle communications from multiple applications simultaneously with several trains.

The priorities associated with the communication requests are managed centrally and the BCM assigns these priorities to each terrestrial application. In addition, the manager also controls the train-side systems that can communicate with each single terrestrial application, identifying the ports that can be accesses by each of those terrestrial applications.

To complete the communication shifts service and management algorithm, it has prepared a final criteria, variable in this case (Noh-sam & Gil-Haeng, 2005). This approach takes into account two factors that are related directly with the communications that have been carried out previously. (1) The first factor is based on the calculation of average duration that takes the communications of a particular application. (2) The second factor takes into account the average duration of trains stopping in a particular station. Thus, the manager calculates a numeric value that represents the fitness of serving a request, knowing that the lower average duration of both factors will be most appropriate, since the risk of communication to be split because the train leaves the station will be less. Once calculated this criteria, it is used to discern which communication request is served, if the criteria explained a few paragraphs above is not sufficient

4. **Management Console (MC) and Activity Log (AL).** As for the remaining two modules, the MC contains a small management utility for monitoring the status of existing communication requests, and cancelling or changing the priority of unfinished requests. Through this interface it is possible to configure parameter and information settings of the BCM such as terrestrial applications, train-side systems, communication ports and priorities. The MC utility is based on standard design patterns like Model View Controller (MVC) so that in the future this presentation layer can be replaced by a more suitable one. The other supporting module is the AL. It stores each of the activities undertaken by the BCM.

To validate the improvement in the management of broadband communications produced by the BCM, there were a series of laboratory tests, which have subsequently been carried out in a real scenario. At first, the Broadband Communications Manager was tested in devising single communications between train and CCTV application. But to prove the performance improvement of the available bandwidth use, it has been necessary to include other terrestrial applications such as a document updating tool, and two other fictitious applications that simulate communications with the train.

The performance tests have taken into account two key parameters: 'train-to-earth' data transfer average time; and average waiting time between each communication. Table 1, shows the results obtained in the management of communications between four terrestrial applications (with different volume of data) and a train at the same station without the Broadband Communications Manager, while the second table shows the same scenario with the Broadband Communications Manager.

In the first table we can see that the absence of a communications manager allows communications to be made in parallel sharing the bandwidth. This greatly slows down the transfer rate, increasing the transfer time as the volume of information grows.

Table 2. Results with the Broadband Communications Manager.

The second table shows how communications are conducted from smaller to larger amounts of data transferred thanks to the algorithm developed for the communication request service. The average time of transfer is lower than in Table 1, and the fact that communications are conducted one-by-one implies that there is a timeout that does not exist if they were carried out all at same time. At the conclusion of the tests it was determined that communications are carried out about 30% faster with the Broadband Communications Manager than without it, although there are wait times.


*3.2. Dataset*

The LS-SSDD-v1.0 dataset is widely used for SAR image intelligent interpretation [51–54]. The characteristic of small ships with large-scale backgrounds in LS-SSDD is close to actual satellite images; thus, we adopted the LS-SSDD-v1.0 dataset to verify the effectiveness of Lite-YOLOv5. Table 3 shows the details of the LS-SSDD dataset.

**Table 3.** Details of the LS-SSDD-v1.0 dataset.

From Table 3, there are 15 large-scale images (cover width ~250 km) numbered by 00.jpg to 15.jpg from different places (Tokyo, Adriatic Sea, etc.), polarizations (VV, VH), and scenes (land, sea). Considering the computing power of the GPU, we simply divided the original large-scale images into 800 × 800 sub-images without embellishment, keeping to the method of Zhang et al. [24]. Since there were fifteen 24,000 pixels × 16,000 pixels largescale images, the total sub-image number was 9000. Finally, according to Zhang et al. [24], the LS-SSDD-v1.0 dataset was divided into a training set for training learning and a test set for result performance evaluation via the ratio of 2:1.


**7.3. Pungency**

**6. Genome-Wide Association Study (GWAS)**

270 Next Generation Sequencing - Advances, Applications and Challenges

association mapping in tomato [175].

ovary and normal fleshy fruit development.

**7.2. Tuber**

The advent of NGS technologies provides a large number of sequence variants (mainly SNPs) within a shorter period. These sequence variants can be utilized for QTL mapping, GWAS, and germplasm characterization. The establishment of an association between genotype and phenotype is a very challenging task. For crop improvement, it is necessary to determine the genetic basis of the agronomic trait. GWAS is a powerful technique for detecting natural variation and fine mapping of QTL underlying complex traits [174]. It requires a collection of individuals or a population of diverse genotypes and highly polymorphic markers that showed genome-wide distribution. This is a very robust method, in comparison to biparental cross-mapping, to map multiple traits simultaneously. In tomato, Shirasawa et al. [77] reported the whole genome resequencing of six tomato cultivars and detected 1.5 million SNPs by mapping the reads onto the reference genome (SL2.40). They utilized Illumina GoldenGate assay for genotyping of 1536 SNPs in 663 tomato accessions. There was no population structure observed when analyzing the genetic relationship using the STRUCTURE software. Further, they identified a total of nine SNP loci that were found to be associated with eight morpho‐ logical traits. To overcome the low polymorphism in cultivated tomato (*S. lycopersicum*), they used genome admixture of the cultivated and its wild ancestor (*S. pimpinellifolium)* for

**7. Next-generation sequencing toward translational research**

These TFs are consistently found to be involved in plant embryo development.

The transcriptome studies in Solanaceae crops such as potato revealed the identification of transcription factors associated with fruit development. A total of 632 lineage-specific genes were identified, of which 289 genes were asterid specific and 343 were potato specific [23]. They identified 290 genes, including *pectin esterase*, *lipoxygenase*, and *malate synthase*. *Leafy Cotyledon 1* (*LEC 1*) and transcriptional factor *B3* were found to be co-expressed in fruit tissues.

In tomato, using NGS technologies, several SNPs successfully differentiating between cherry type and round/beef type tomatoes were identified [80]. The SNP data revealed that cherry tomatoes share more SNPs with *S. pimpinellifolium*, a wild relative of the tomato. This revealed a close phylogenetic relationship of cherry tomato with the wild type. Several SNPs belonged to the chromosomal region that harbors genes/QTLs related to fruit weight, size, shape, and color, indicating that the SNPs may be used to explore the other fruit traits. In a miRNA study, it was observed that the transgenic tomato plants harboring AtMIR156b precursor resulted in abnormal flower and fruit morphology [130], indicating that mir156b plays crucial role in

The transcriptome of tuber tissue showed the presence of several transcripts that are specific for tuber. Around 90 genes were co-expressed in tuber, including the genes involved in starch

**7.1. Fruit traits (size, shape, ripening, and development)**

Pungency is a special and economically important quality trait only found in pepper fruits, and it has been studied extensively [7, 43]. NGS technology has a wide scope to explore this trait and provides insights into the capsaicinoid pathway revealing the genes/loci associated with pungency. The transcriptome profiling of *C. frutescens* revealed the identification of three structural genes, namely, dihydroxyacid dehydratase (DHAD), Thr deaminase (TD), and prephenate aminotransferase (PAT) involved in the capsaicinoid biosynthesis pathway [43]. They claimed the identification of several new candidate genes involved in the capsaicinoid pathway. The comparative transcriptomic study of pepper with potato and tomato showed that the different capsaicinoid pathway genes were expressed during placenta development at 16 DPA, 25DPA, and mature green stages of pepper fruits, but their orthologous genes hardly showed any expression in tomato and potato fruit [7]. The study confirmed the specificity of capsaicinoid pathway in the development of pungency in pepper fruit.


**2.3. ESBWR Passive Containment Cooling System (PCCS)**

The PCCS is a passive system which removes the decay heat released to the containment and maintains the containment within its pressure limits for design basis accidents such as a LOCA. The schematic of the PCCS is shown in Figure 4. The PCC heat exchangers receive a steam-gas mixture from the Dry Well (DW), condense the steam and return the condensate to the RPV via the Gravity Driven Cooling System GDCS pools. The non condensable gas is vented to the Wet Well (WW) gas space through a vent line submerged in the Suppression Pool (SP). The venting of the non condensable gas is driven by the differential pressure between the DW and WW. The PCCS condenser, which is open to the containment, receives a steam-gas mixture supply directly from the DW. Therefore, the PCCS operation requires no sensing, control, logic or power actuated devices for operation. The PCCS consists of six PCCS condensers. Each PCCS condenser is made of two identical modules and each entire PCCS condenser two-module assembly is designed for 11 MWt capacity. The condenser condenses steam on the tube side and transfers heat to the water in the IC/PCC pool. The evaporated

steam in the IC/PCC pool is vented to the atmosphere. PCCS condensers are located in the large open IC/PCC pool, which are designed to allow full use of the collective water inventory.

Reliability of Passive Systems in Nuclear Power Plants 31

functional schematic and an example of containment pressure transient following typical

**Figure 6.** Example of containment pressure transient following typical low pressure core melt scenario.

PSA methodology widely used in the nuclear power industry is deemed helpful to the safety assessment of the facility and along the correspondent licensing process: probabilistic safety assessment can provide insights into safety and identify measures for informing

The first comprehensive application of the PSA dates back to 1975, to the United States Nuclear Regulatory Commission's (U.S. NRC) Reactor Safety Study [4]. Since that pioneering study, there has been substantial methodological development, and PSA techniques have

low pressure core melt scenario.

**Figure 5.** ABWR Passive heat removal system

**3. Overview of PSA**

designers of the safety of the plant.

**Figure 4.** Passive containment cooling condenser arrangement


*Is There Still Room to Improve Medicinal Herbs (Functional Herbs) by Gene Editing for Health? DOI: http://dx.doi.org/10.5772/intechopen.104323*

difference occurs in the next generation of organism, biallelic may be provided, and heterozygous and homozygous mutations may be generated [48]. Svitashev et al. [49] and Woo et al. [50] have conducted studies with lettuce, rice, and corn to get successful mutations and modified fields with no alien DNA and marker. In addition, some microalgae, namely *C. reinhardtii*, *Chlamydomonas*, and *P. tricornutum*, have been edited successfully without cytotoxic effects [45, 51, 52]. According to the literature, genome editing with CRISPR/Cas engineering for single nucleotide resolution editing, multiple gene editing, transcriptional regulation, and genome-wide modifications of *Saccharomyces cerevisiae* have been shown [53, 54]. *S. cerevisiae* is an important eukaryotic yeast for the biosynthesis and biofuels [55, 56]. However, there are still some limitations and challenges, in particular the application of CRISPR could limit the effectiveness of yeast processing.

All these technologies have been reported for improving plant micronutrients, such as flavonoids, phenols, saponins, tannins, etc. [57]. These are bioactive compounds known as medicines that are important to health. In particular, the CRISPR/

#### **Table 1.**

*Some nutritional quality-improved foods by gene-editing technologies (Prepared according to literatures; Ku and Ha [64], Scarano et al. [65], Dey et al. [66]).*

Cas9 technology can be used to target genes in medicinal plants and their compounds. In addition, this technology can tolerate environmental stress along with quality and performance. There have been successful studies about plant biosynthetic pathways with CRISPR/Cas9, such as tomato for gamma-aminobutyric acid, banana, and rice for beta carotene [58–61]. Also, CRISPR/Cas9 is an effectible technology for bacterial resistance of herbs and plant-derived products and against climate changes [62, 63]. Genome editing technology involves more controlled mutations, and genetic improvement is less time-consuming.

Biotechnology approaches have been interpreted in the context of genome editing technologies over the years. Secondary plant metabolites that belong to genome technology are pharmacologically important as well as nutritional (**Table 1**). However, the editing of the genome is still in its beginnings in plants and their contents. As new and interesting results are obtained in this field, new technologies will emerge.


**4. Conclusions**

In this study, various Schi ff bases and their NiII complexes were synthesized. All the prepared ligand and complexes were analyzed via C, H, and N analyses. They were assigned molecular structures and geometries using information obtained from UV-Vis, magnetic susceptibility, and X-ray crystallography, all of which corresponded to square-planar geometry in the solid state. The Hirshfeld surface analysis was used to study intermolecular interactions. This analysis revealed that the O···H, H···H and π··· π contacts were the most significant in the crystal array of the compounds *NiMesalen, NiMeOsalen*, and *NiMeOsalphen*, and O···H, H···H, Cl···H and π··· π contacts in the crystal array of the compound *Nisalphen*. The no classical hydrogen bonding and π··· π stacking information conveyed by Hirshfeld surface analysis were consistent with the crystal structure analysis. The substituents and the N/N bridge a ffected the crystal packing and electronic properties of nickel. According to the structures obtained for *Nisalphen, NiMeOsalen,* and *NiMeOsalphen*, it was possible to observe that the addition of an aromatic ring in the N/N bridge increased the number on π··· π and C-H··· π interactions and decreased their length. Substituents also played an important role in crystal packing for *NiMeOsalen* and *NiMeOsalphen.* i.e., a higher contribution for the O···H interaction. Due to this contribution, the length of π··· π interactions were minor in both complexes. In N/N aliphatic bridge complexes, the substituents also had an important role. The E1/2 depended on the electron-withdrawn or electron-donor nature of the R (R') substituent, which followed a correlation with the σp of Hammet in such a way that, for the electron-donor substituent, -OH and -CH3 decreased the half-wave potential, instead favoring nickel's reductor ability.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2073-4352/10/7/616/s1, Table S1. Atomic coordinates (x 104) and equivalent isotropic displacement parameters (Å2 103) for compound NiMe*salen.* U(eq) is defined as one third of the trace of the orthogonalized Uij tensor. Table S2. Atomic coordinates (×104) and equivalent isotropic displacement parameters (Å2 × 103) for compound NiMeO*salen*. U(eq) is defined as one third of the trace of the orthogonalized Uij tensor. Table S3. Atomic coordinates (x 104) and equivalent isotropic displacement parameters (Å2 × 103) for compound NiMeO*salphen*. U(eq) is defined as one third of the trace of the orthogonalized Uij tensor. Table S4. Atomic coordinates (×104) and equivalent isotropic displacement parameters (Å2 × 103) for compound Ni*salphen*. U(eq) is defined as one third of the trace of the orthogonalized Uij tensor. Table S5. Bond lengths [Å] and angles [◦] for compound Ni*salphen*. Table S6. E ffective magnetic moment and number of unpaired electrons of NiII complexes. Table S7. 1H-NMR values for the ligands and nickel complexes. Table S8. 13C-NMR values for the ligands and nickel complexes. Figure S1. Normalized contact distance (dnorm, defined in terms of de, di, and the van der Waals radii of the atoms) mapped on the Hirshfeld surface of the compound NiMeO*salen*, represented with one surrounding moiety to visualize the intermolecular interaction. Figure S2. Hirshfeld surface with dnorm mapped and fingerprint plots for compound NiMe*salen*, with C···H interaction (first row) and H···H, O···H interactions (row 2–3). The color ranges from dark blue to red with increasing frequency (relative area of the surface), corresponding to each kind of interaction. Figure S3. Normalized contact distance (dnorm, defined in terms of de, di, and the van der Waals radii of the atoms) mapped on the Hirshfeld surface of the compound NiMeO*salen*, represented with one surrounding moiety to visualize the intermolecular interaction. Figure S4. Hirshfeld surface with dnorm mapped and fingerprint plots for NiMeO*salen*, with C···H interaction (first row) and H···H, O···H interactions (row 2–3). The color ranges from dark blue to red with increasing frequency (relative area of the surface) corresponding to each kind of interaction. Figure S5. Normalized contact distance (dnorm, defined in terms of de, di, and the van der Waals radii of the atoms) mapped on the Hirshfeld surface of the compound NiMeO*salphen*, represented together with one surrounding moiety to visualize the intermolecular interaction. Figure S6. Hirshfeld surface with dnorm mapped and fingerprint plots for compound NiMeO*salphen*, with C···H interaction (first row) and H···H, O···H interactions (row 2–3). The color ranges from dark blue to red with increasing frequency (relative area of the surface) corresponding to each kind of interaction. Figure S7. Normalized contact distance (dnorm, defined in terms of de, di, and the van der Waals radii of the atoms) mapped on the Hirshfeld surface of the compound Ni*salphen*, represented together with one surrounding moiety to visualize the intermolecular interaction. Figure S8. Hirshfeld surface with dnorm mapped and fingerprint plots of the two molecules name A and B in compound Ni*salphen* for C···H interaction (first row) and H···H, Cl···H interactions (row 2–3). The color ranges from dark blue to red with increasing frequency (relative area of the surface) corresponding to each kind of interaction. Figure S9. UV-vis of NiMeO*salen* in DMSO solution. Figure S10. UV-vis NiMe*salen* in DMSO solution. Figure S11. UV-vis NiOH*salen* in DMSO solution. Figure S12. UV-vis of Ni*salen* in DMSO solution. Figure S13. UV-vis of NiCl*salen* in DMSO solution. Figure S14. UV-vis of NiBr*salen* in DMSO solution. Figure S16. UV-vis NiMeO*salphen* in DMSO solution. Figure S17. UV-vis NiOH*salphen* in DMSO solution. Figure S18. UV-vis Ni*salphen* in DMSO solution. Figure S19. UV-vis NiCl*salphen* in DMSO solution. Figure S20. UV-vis NiBr*salphen* in DMSO solution. Figure S21. 1H-NMR of NiMeO*salen* in DMSO-d6. Figure S22. 13C-NMR of NiMeO*salen* in DMSO-d6. Figure S23. 1H-NMR of NiMe*salen* in chloroform. Figure S24. 13C-NMR of NiMe*salen* in chloroform. Figure S25. 1H-NMR of NiOH*salen* in DMSO-d6. Figure S26. 13C-NMR of NiOH*salen* in DMSO-d6. Figure S27. 1H-NMR of Ni*salen* in chloroform. Figure S28. 13C-NMR of Ni*salen* in chloroform. Figure S29. COSY spectrum of Ni*salen* in chloroform. Figure S30. HSQC spectrum of Ni*salen* in choloform. Figure S31. 1H-NMR of NaCl*salen* in chloroform. Figure S32. 1H-NMR of NiBr*salen* in chloroform. Figure S33. 1H-NMR of NiNO2*salen* in DMSO-d6. Figure S34. 1H-NMR of NiOH*salphen* in DMF-d7. Figure S35. 13C-NMR of NiOH*salphen* in DMF-d7. Figure S36. COSY spectrum of NiOH*salphen* in DMF-d7. Figure S37. HSQC spectrum of NiOH*salphen* in DMF-d7. Figure S38. 1H-NMR of NiMeO*salphen* in CDCl3. Figure S39. COSY spectrum of NiMeO*salphen* in CDCl3. Figure S40. Voltammogram of NiMeO*salen* 1 mM in DMSO. Figure S41. Voltammogram of NiMe*salen* 1 mM in DMSO. Figure S42. Voltammogram of NiOH*salen* 1 mM in DMSO. Figure S43. Voltammogram of Ni*salen* 1 mM in DMSO. Figure S44. Voltammogram of NiCl*salen* 1 mM in DMSO. Figure S45. Voltammogram of NiBr*salen* 1 mM in DMSO. Figure S46. Voltammogram of NiNO2*salen* 1 mM in DMSO.

**Author Contributions:** Conceptualization, C.S.N.-R. and A.S.-B.; methodology, C.S.N.-R., A.S.-B., and F.L.O.-V.; software, M.F.-A.; formal analysis, C.S.N.-R., A.S.-B., J.C.G.-R., and M.F.-A.; investigation, L.R.-A.; direction and resources, L.R.-A.; data curation, M.F.-A.; writing—original draft preparation, C.S.N.-R., A.S.-B., and M.F.-A.; writing—review and editing, L.R.-A. and J.C.G.-R., supervision,. L.R.-A.; project administration, L.R.-A.; funding acquisition, L.R.-A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** We thank USAII for elemental analysis, mass spectrometry, nuclear magnetic resonance tests and chromatography coupled to mass spectrometry tests; PAPIIT IN230020 for financial support and PAPIIT IN217613 for scholarships (CSNR, and ASB).

**Conflicts of Interest:** The authors declare no conflict of interest.


**2. Material and Methods**

### *2.1. Identification of wbm-*Like *Gene*

To identify the *wbm* location on a wheat chromosome, a 75-amino acid (aa) sequence of *wbm* protein [11] was employed as a query for tBLASTn search against the expressed sequence tags (EST) collection of NCBI, and an EST clone (BQ606004.1, https://www.ncbi.nlm.nih.gov/nuccore/BQ606004.1/) was found. This EST has a 225-base pair (bp) open reading frame predicted by ORFfinder (https: //www.ncbi.nlm.nih.gov/or ffinder/), and the corresponding protein sequence was identical to original *wbm* protein. Using this EST sequence, we next conducted a nucleotide BLAST search against the IWGSC RefSeq v1.0 ([21]) reference genome assembly of wheat Chinese Spring (https://urgi.versailles. inra.fr/blast/, [22]) and the NCBI WGS database.

### *2.2. Multiple Alignment of wbm and Related Protein and Nucleotide Sequences*

To compare *wbm* and *wbm-like* with the related sequences from other species and cultivars nucleotide BLAST [23] was performed against the latest assembly of their genomes (wheat cultivars: https://wheatis.tgac.ac.uk/grassroots-portal/ [24], http://www.10wheatgenomes.com/; *S. cereale*: https://webblast.ipk-gatersleben.de/ryeselect/, other species: https://plants.ensembl.org/ Triticum\_aestivum/ [25], https://urgi.versailles.inra.fr/blast/blastresult.php) using default parameters. The *wbm*-similar sequences were retrieved, and open reading frames (ORFs) were predicted using ORFfinder software (https://www.ncbi.nlm.nih.gov/or ffinder/). Corresponding ORF sequences overlapping with *wbm* hits and deduced protein sequences were aligned by ma fft [26] with standard parameters and visualized using UGene (Version 33, UNIPRO, LLC, Novosibirsk, Russia,) [27].