Baekdusan volcano stratigraphy and petrography of the volcanic products simplified after Wei et al. [7, 28, 29].
\r\n\tThis book is intended to provide a series of peer reviewed chapters that the guest editor believe will aid in increasing the quality of the research focus across the growing field of grain and seeds compound functionality research. Overall, the objective of this project is to serve as a reference book and as an excellent resource for students, researchers, and scientists interested and working in different functional aspects of grain and seed compounds, and particularly for the scientific community to encourage it to continue publishing their research findings on grain and seed and to provide basis for new research, and the area of sustainable crop production.
\r\n\t
When active volcanoes are located in strategic and controversial territory with a history of political and military conflicts [1, 2], their studies and the better understanding of how those volcanoes work are much more difficult, especially when the earth scientists have to deal with mitigation measures to protect the population living around [3–6]. This is surely the case of an active volcano known by a few until 15 years ago, situated between the China and North Korea borders, called by different names by the countries that surround it. The name of the volcanic field surrounding Tianchi(=Cheonji) caldera lake is 长白頭山 in Chinese characters which means “White Head Mountain” These characters are Romanized as Baegdu-san, Baekdu-san, or Paektu-san in Korea, Hakuto-san in Japan, and Changbaishan(長白山) in China [7, and references therein]. From now on, we will use the Korean name, Baekdusan, to avoid confusion. Baekdusan volcano has recently become of greater interest to volcanologists after the sign of unrest during the period 2002–2009, with several volcanic precursors such as volcanic earthquake, surface inflation, specific volcanic gas emission, higher temperatures of hot springs [8–10], which have prompted the Eastern Asian Volcanological Community to pay major attention to this volcano by establishing a Volcanological Observatory (the Chinese Tianchi Volcanological Observatory has collected data since 1999 [11]) and by setting up an improved monitoring network around the volcano [12, 13]. Since 2012, the South Korean scientists have also taken steps in this direction, and the National Emergency Management Agency of Korea (Ministry of Public Safety and Security of Korea) has sponsored a vast research project on Baekdusan volcano (NEMA-BAEKDUSAN-2012-1-2), granted from the Volcanic Disaster Preparedness Centre (MPSS-NH-2015-81), and through the Natural Hazard Mitigation Research Group. Under the auspices of these groups, we analyzed the hazards from pyroclastic density currents and their impact on the population and infrastructures around Baekdusan volcano [14]. Further, we present arguments as to why this volcano has many characteristics as a potential site for the development of the conditions that can cause a super-eruption. Thus, we must also consider this extreme event if we do have to prepare for the next eruption, as it would have a global impact [15].
\nRegional setting of Baekdusan (Tianchi) volcano. Symbols mean the following. ○ Densely populated city or town: (a) Erdaobaihe; (b) Songjianghe; (c) Changbai; (d) Hyesan; (e) Baishan; (f) Fusong; (g) Lushuihe; (h) Yanji, and (i) Tumen. ° Populated village. ∆ Mountain tops with the elevation asl. Baekdusan (Tianchi) volcano. Capital letters indicate places referred to in text: T, Baekdusan (Tianchi) volcano; W, Wangtiane volcano; B, Bukpotaesan volcano; Z, Zhenfengshan volcano; SH, Songhua River; YL, Yalu(Aprok) River; and TM, Tumen (Duman) River.
\nA. Regional tomography from the surface down to 1,300 km depth along a cross-section line shown on the inset map. The velocity perturbation scale is shown below the cross section. White dots denote earthquakes. The two dashed lines show the 410 and 670 km discontinuities. The red and black triangles show the active volcanoes. The surface topography along the profile is shown at the top of the tomographic image. The blue lines on the inset map denote the major plate boundaries (modified from [17]). B. A sketch showing the main features of the upper-mantle structure around Baekdusan volcano in East Asia, emphasizing the possible relationship between the intraplate volcanism and deep earthquakes in the Pacific slab [17], DXAL, Daxing-Anling (modified from [17]).
Siping–Changbaishan–Japan seismic profile of the structure of Changbaishan area [24].
Baekdusan volcano is an intraplate stratovolcano included in the larger Changbaishain area, where we can list a series of intraplate volcanoes (Wangtiane volcano, Bukpotaesan volcano, Zhenfengshan volcano, [7], Figure 1). Cenozoic intraplate basalts are widely distributed around the Changbaishan volcanic area. Beneath the Baekdusan volcano, a prominent low-velocity anomaly with a plume-like shape has been imaged in the upper mantle by P-wave tomography [16, 17]. This suggests an upwelling of hot and wet material from the mantle transition zone (410–670 km [18]), where a stagnant subducted Pacific slab produces fluids and deep earthquakes through faults preserved in the stagnant slab. Hence, fluids and magmas may be supplied to the upper mantle under Baekdusan volcano, unlike beneath other volcanic and nonvolcanic areas in NE Asia, because large deep earthquakes occur frequently in the vicinity (a distance of about 200 km) of the Baekdusan volcano. At least some of these earthquakes are caused by the reactivation of faults which were produced within the plate, even after plate subduction. Further, the fluids could be released to the overlying mantle wedge from the preserved faults in the slab when large deep earthquakes occur. As a result, the Baekdusan volcano has to be considered much more active and prominent than other intraplate volcanoes in NE Asia [9, 10], because more magmas are produced from the fluids released from the slab by the deep earthquakes [19]. Further, Kuritani et al. [20] use the trace element and Pb isotope data to demonstrate the intense hydration of the big mantle wedge beneath the Baekdusan volcano, through two different dehydration events of an ancient stagnant slab (~1.5 Gyr) and the most recent subducted Pacific slab (Figure 2A and B show the most recent setting). The wet mantle wedge is likely to result in more frequent rise of diapiric wet melts, as shown from the tomography [17, references therein], and develop a deep hot zone intruded by mafic sills repeatedly at the MOHO depth or/and scattered in the lower crust [21, and references therein]. Enrichment in fluid-mobile elements (e.g. Cs, Ba, K, Sr, U, Pb), a lack of enrichment in nonfluid-mobile elements (e.g. Nb, Ta, Ti, etc), together with specific isotopic signatures (e.g. 87Sr/86Sr, 206Pb/204Pb) in island-arc basalt or subduction- related magmatism are interpreted as a result of metasomatism of the magma source by slab-derived fluids or melts. Their detailed investigation has helped to establish the current, rather empirical, model of slab dehydration and subduction-related melting processes. But, according to petrochemical characteristics and magma genesis of Holocene volcanic rocks at Mt. Baekdusan [22], trace elements from the Baekdusan volcano do not indicate significant contributions from a subduction slab of the Pacific plate. Volcanic activity in Mt. Baekdusan summit during Holocene resulted from intraplate magmatism [after 23, 24], caused by upwelling of asthenospheric mantle under extensional tectonic conditions (Figure 3 [24]). Hot zone melts are H2O-rich as in Baekdusan volcano (e.g., Millennium eruption [25]). Consequently, they have low viscosity and density, and can readily detach from their source and ascend rapidly. Crystallization begins only when the ascending magma intersects its H2O-saturated liquidus at shallow depths. Decompression and degassing are the driving forces behind crystallization, which take place at shallow depths on timescales of decades or less. Degassing and crystallization at shallow depths lead to large increases in viscosity and stalling of the magma to form volcano-feeding magma chambers [26, 27]. The above model is well confirmed from the study of Wei [24] at the Baekdusan volcano. The heating of the deep crust was inefficient in early times, because much of the basalts erupted out directly, and much of the heat from magma was not used to heat the wall rocks. Annan and Sparks [27] state that there is an initial incubation period in which the basalt intrusions solidify. Generation of silicic melts initiates when the solidus temperature of either the basalt magma or the surrounding crust is reached. At an intrusion rate of 50 m per 10,000 years, incubation periods in the range 105–106 years are estimated, consistent with geochronology and stratigraphy at Baekdusan volcano, with its evolution from mafic to silicic volcanism (the stratigraphy and geochronology will be treated in the next section). Once a zone of residual partial melt develops in the deep hot zone and starts to prevent the basalt from eruption, the temperature rises more efficiently, and the production of residual melt is accelerated. Large amounts of evolved residual silicic melt have been formed in the last 10,000 years and then intruded into the upper crust to form magma chambers large enough to result in the caldera-forming explosive eruptions. The repose time between eruptions of size similar to the Millennium eruption was about thousands of years, one order greater than less-explosive parasitic eruptions of hundreds of years [7].
\n\n\nThe volcanic activity at the Baekdusan volcano goes back as far as nearly 25 Ma B.P [7, 28, 29]. Wei et al. [7] describe the volcanic activity in three stages: early shield-forming; middle cone-construction; and late ignimbrite-forming eruptions. The volcanic rocks were alkaline and tholeiitic basalts during the shield stage, trachyte and comendite lavas, and their pyroclastic equivalents during the cone-construction stage, and mostly comenditic pyroclastic rocks in the final stage (Table 1, Figure 4). However, Yang et al. [30] affirm on the basis of a large amount of age and stratigraphic data (40Ar/39Ar, U-series disequilibria) that Baekdusan volcano has been more active in the last 20 ka (~19, 16, 11 ka) than that was previously thought. From historical records, several authors [31, 32] affirm the high frequency of eruptive events, and since the Millennium eruption, more than 31 eruptive events have been documented, most of which are the Plinian eruptions with volcanic ash that dispersed into the regions in the vicinity of the volcano. Many authors concord that the last explosive eruptions are in chronological order, 1668 AD (Figure 5), 1702 AD (Figure 6), and 1903 AD (Figure 7) [32–34]. In Figure 4 is shown the Baekdusan volcano’s geological map with all the terrains outcropping (see the legend of Figure 4 for more major details). The shield-forming stage lasted from the Miocene into the early Pleistocene. Alkali olivine and tholeiite basalt form the main part of a shield-like lava plateau that covers an area of 7,200 km2 centered at Cheonji. In addition to the eruptions from central vents, there also were fissure eruptions, as evidenced by feeder dikes along the headwaters of the Tumen (Duman) and Heishihe Rivers. The youngest shield basalts are located near Cheonji cone and are overlain by the alkaline trachytes of the cone, except in the northwestern part of the shield. The shield basalts are ∼150 m thick near the Baishan Forestry Center in the headwaters of the Yalu River (Aprok River). The cone-construction stage lasted from ∼1.0 Ma to perhaps as young as ∼20 ka. The latter is about the age of the youngest trachyte lava on the caldera rim near Tianwenfeng (K–Ar, 19 ± 5 ka) and one of the youngest comendite lavas, Qixiangzhan, which was dated recently at 17 ± 1 ka. This stage was characterized by eruption of trachyte and comendite lavas and pyroclastic rocks, and dominated by trachyte lava effusion from the center of Cheonji volcano. The cone-construction stage has been subdivided into four stratigraphic formations for the main cone and the Laofangzixiaoshan part of the shield (Table 1). In general, outcrops of lava decrease image with elevation on the cone. In plane view, the eastern sector of the cone consists of younger trachytes, whereas older lavas are distributed more widely. However, all the rocks share similar geochemical compositions and appear to be genetically related. The young Laohudong basalts are sparsely distributed as monogenetic vents around the caldera. Its largest and most explosive Plinian eruption occurred around 946–947 AD and is known as the “Millennium eruption.”
\nStages | \n\n | Formation and age | \n\n | Lithologies | \n
---|---|---|---|---|
\n | \n | Liuhaojiie Tuff Ring (1903 AD) | \n\n | Comendite phreatomagmatic eruption | \n
Late: | \n\n | Wuhaojie (1702 AD) | \n\n | White gray comentite fine glass | \n
Igninbrite- | \n\n | Baguamiao (1668 AD) | \n\n | Dark gray trachyte ignimbrite and pumice | \n
forming | \n\n | \n | \n | \n |
\n | \n | \n | \n | White gray comentite ignimbrite and | \n
\n | \n | Millennium eruption (~936–1200 AD) | \n\n | Air fall pumice with minor trachyte | \n
\n | \n | \n | \n | Ignimbrite and air fall pumice | \n
\n | \n | \n | \n | \n |
\n | \n | Qixiangzhan (17 ka) | \n\n | Comentite lava and pyroclasts | \n
Middle: Cone | \n\n | Baitoushan III (0.02–0.22 Ma) | \n\n | Trachyte and comendite lava | \n
construction | \n\n | Baitoushan II (0.25–0.44 Ma) | \n\n | Trachyte with Laohudong basalt | \n
\n | \n | Baitoushan I (0.53–0.61 Ma) | \n\n | Trachyte | \n
\n | \n | Laofangzixiaoshan (0.75–1.17 Ma) | \n\n | Basalt | \n
\n | \n | Xiaobaishan (0.75–1.17 Ma) | \n\n | Trachyandesite and trachyte | \n
\n | \n | \n | \n | \n |
\n | \n | \n | \n | \n |
\n | \n | Baishan (1.48–1.66 Ma) | \n\n | Basalt | \n
Early: Shield- | \n\n | Toudao (2.35–5.02 Ma) | \n\n | Basalt | \n
forming | \n\n | Naitoushan (15.6–22.6 Ma) | \n\n | Basanite, Basalt | \n
Geological map of the summit area of Baekdusan volcano. Northeast distribution of the basaltic shield, trachytic composite cone, and the comenditic ignimbrite sheet of the Baekdusan volcano. 1, Torrent deposit, the fourth debris flow (1994); 2, The third fan-shaped debris flow; 3, 1903 phreatomagmatic eruption; 4, The second fan-shaped debris flow; 5, Dark trachytic ignimbrite and surge (1668); 6, Dark trachytic fallout (1668); 7, The first fan-shaped debris flow; 8, Rock fall deposit; 9, Fallout (?1413–1668); 10, Outer flank dark lahar; 11, The Millennium ignimbrite and secondary deposits; 12, The Millennium valley and pond ignimbrite; 13, The Millennium eruption comenditic Plinian fallout; 14, Outer flank avalanche deposits; 15, Qixiangzhan distal comenditic lava; 16, Qixiangzhan middle comenditic lava; 17, Qixiangzhan proximal comenditic lava; 18, Qixiangzhan calstogenic lava, comendite, and obsidian; 19, Ice ground brown and gray trachytic ignimbrite, lahar; 20, Heifengkou Lag breccias (3950 ±120 a); 21, Upper trachyte and comendite cone (0.04–0.2 Ma); 22, Middle trachyte cone (0.25–0.44 Ma); 23, Lower trachyte cone (0.53–0.61 Ma); 24, Xiaobaishan trachyandesite and trachyte (1–1.49 Ma); 25, Laohudong parasitic basalt and scoria (0.32–0.34 Ma); 26, Laofangzixiaoshan basalt (0.31–0.58 Ma); 27, Baishan basalt (0.93–1.39 Ma); 28, Toudao basalt (1.91–2.77 Ma); 29, Comendite dyke; 30, Trachytic welded tuff dyke; 31, Trachyte dyke; 32, Ring and radioactive faults; 33, Caldera rim; 34,Avalanche scar; 35,Vent; 36, Hot spring; 37, Inferred geologic boundary; 38, Flow units boundary; 39, Facies boundary; 40, National boundary. β, Basalt; τ, Trachyte; λ, Comendite; π, Porphyry dyke (modified from [7]; Yun, unpublished data).
The Buguamiao welded ignimbrite of the 1668 AD pyroclastic flow eruption is shown in all the pictures. The outcrops are in the vicinity of the Tianchi caldera. In the Baguamiao ignimbrite is also apparent its welded character.
The 1702 AD pyroclastic flow eruption on the summit of the cliff.
The 1903 AD pyroclastic flow deposits. The outcrop is separated by levels. The 1° level belongs to the 1702 AD eruption, and the others belong to the 1903 pyroclastic flow eruption. It is clear that the thickness of the 1903 deposit is near the caldera.
Distribution of pyroclastic density currents of the Millennium eruption in China side. Numbers are thickness (m). Units C and F are the two pyroclastic flow levels.
This eruption has a volcanic explosivity index (VEI) of 7, comparable to the 1815 eruption of Tambora in Indonesia. Horn and Schmincke [25] have suggested that the Cheonji eruption column reached ca 25 km in height, injecting about 9 ×1010 kg of volatile halogens into the atmosphere, with an estimated volume of pyroclastic material on the order of ~100 km3. Volcanic ash from the eruption has been found 1,000 km away from the site of the eruption. A 5 cm thick deposit was observed in southern Hokkaido, Japan [38]. Accordingly, the Millennium eruption of the Baekdusan Cheonji volcano has been considered as one of the greatest volcanic eruptions of the past 2000 years.
\nStratigraphy of the Millennium eruption on the eastern slope of Baekdusan volcano (modified from [35]). pfa, pyroclastyc fall deposit; pfl, pyroclastic flow deposits; dfl, debris flow deposits.
One of the most largest destructive eruptions from the Baekdusan volcano occurred on Earth in the last millennium, about 1,000 years ago, and it is named the Millennium eruption [25, 29, 34, 35]. It involved more than ~100 km3 of magma erupted [10], and the Plinian column was estimated to have had a height of 25 km. A widespread ash-fall deposit has been traced across the Sea of Japan to Hokkaido, and it is several centimeters thick, at more than 1,000 km from the source [35, 37]. Unwelded pyroclastic flows associated with collapse events of the Plinian eruption column extended to more than 70 km from the crater rim (Figure 8). The Millennium eruption formed a large caldera with a diameter of about 5 km and an area of 20 km2, forming the Cheonji (Tianchi = Sky) lake. Currently, the lake has a maximum depth of 374 m and an area of ~ 9.8 km2, with a water surface elevation of 2,189 m. It has a volume of 2 km3. A composite stratigraphic section of the Millennium eruption is given by Machida et al. ([35]; Figure 9). According to Machida et al. [35], the section is broadly composed of five levels (A, B, C, E, F; for major details, see Figure 9). Figure 10 shows some unwelded Millennium pyroclastic flow outcrops with relative thicknesses and sites. However, there is a controversy if the complete volcanological section of the Millennium eruption has to be interpreted as a single continuous eruption rather than one with two distinct pulses, with the initial phase anticipating the major phases of tens or hundreds of years [39]. The scientific literature reports a large range of ages for the Millennium eruption [40]. The results show a variety of periods ranging from approximately AD eighth to fourteenth centuries, which are the dates of the Balhae(= Bohai) and Goryeo dynasties [40, and references therein]. The last geochronological data (radiocarbon wiggle-match dating) on the Millennium eruption show a much more restricted range, respectively, of 938–939 AD [41], 946–947 AD [42], and 1024 AD [28].
\nMillennium unwelded pyroclastic flow outcrops at the north and south flanks of the caldera with the respective thicknesses. (A) Millennium eruption pyroclastic flow deposits, northern slope: 20 m thickness. (B) Millennium eruption pyroclastic flow deposits, southern slope: 60 m thickness.
The scenarios envisaged here are based on the large amount of data that have been collected by the Korean research project, CATER2011-5210 [36], and by the new literature produced [25, 32–34, among others] in order to assign a selected VEI (Volcanic Explosivity Index [43]). The main parameters are summarized in Table 2 (VEI, maximum volume erupted, and column height) for each eruption. The volumes considered for just the pyroclastic density currents are obviously less than the total volume and are listed in Table 3. Figure 11 shows that between several volcanic-related disasters, the pyroclastic density currents have to be considered the most dangerous, given the number of fatalites in the last 2,000 years.
\nEruption date | \nVEI | \nVolume (m3) | \nColumn height (km) | \n
---|---|---|---|
1903 AD eruption | \n2 | \n106–108 | \n1–5 | \n
3 | \n3–15 | \n||
1668–1702 AD eruption | \n4 | \n108–1010 | \n10–25 | \n
5 | \n>25 | \n||
Millennium eruption | \n7 | \n1011–1012 | \n>25 | \n
Summary of the main parameters for the 1093 AD, 1702 AD, 1668 AD, and the Millennium eruptions. Volumes are taken from Newhall and Self [43] compared with the VEI for each eruption.
Eruption type | \nRunout length (m) | \nVolume (m3) | \nInitial velocity (m/s) | \nTime duration (s) | \n
---|---|---|---|---|
\n1903-type\n | \n\n~3000\n | \n\n10\n\n7\n\n–10\n\n8\n\n | \n\n30\n | \n\n3600\n | \n
\n1668–1702 type\n | \n\n~4000–5000\n | \n\n10\n\n9\n\n | \n\n50\n | \n\n>3600\n | \n
\nMillennium eruption\n | \n\n7–80,000\n | \n\n10\n\n10\n\n | \n\n80–300\n | \n\n>3600\n | \n
Statistical percentage of fatalities for volcanic-related phenomena in last 2000 years. Pyroclastic density current is the most deadly phenomena in the last 2,000 years (Figure taken from the web and modified).
Branney and Kokelaar [44] illustrate in detail how different types of pyroclastic density currents originate (Figure 12). From Figure 12, the pyroclastic density currents most likely to occur at Beakdusan volcano are the following: A, B, C, depending on the size and the amount of interaction with external water. For laterally moving systems, the pyroclastic density currents can be identified as two end-member types: (A) Concentrated currents or pyroclastic flows, (B) Dilute currents or pyroclastic surges (Note that these are often a spectrum, with gradations in between). The end-member A has the following main characteristics:
It has solids in concentrations of tens of volume percentage, and so they have higher densities than surges.
They have a free surface, above which solids’ concentration decreases sharply.
Transport of material is by fluidization, and most flows are considered to be laminar.
Velocities vary, typically by 10s of meters per second up to several hundred meters per second, inferred from the heights of obstacles overcome by flows.
Origins of pyroclastic density currents. (A) Short single-surge current derived by momentary collapse from a Plinian eruption column. (B) Sustained current derived from prolonged pyroclastic fountaining. The height of the jet (gas thrust) that feeds the current may vary and is transitional into (C). (C) A sustained current derived from a prolonged low pyroclastic fountaining explosive eruption. (D) Current with a single (or multiple) surge derived from lateral blasts initiated by catastrophic decompression of a magmatic and/or hydrothermal system. (E) Single-surge current derived from a collapsing lava dome or flow front. Hot rock avalanches generate turbulent density currents. (F) Deposit-derived pyroclastic density current caused by gravitational collapse and avalanching of unstable loose ignimbrite. The current may be a single-surge or more sustained where the collapse is retrogressive. Most large-volume ignimbrites derive from current types (B) and (C), which may involve periods of quasi-steady flow. Many may include significant components derived from currents of type (F) [44, 45]. For Baekdusan, we chose the following three types: Soufriere, Pelee, and Merapi types (modified from [62]).
The end-member B has the following main characteristics:
It contains less than 0.1–1.0% by volume of solids, even near ground surface, and so they are relatively of low density.
They are density-stratified, with the highest particle concentration near the ground surface.
Material is transported primarily by turbulent suspension.
Transport system is modeled as one that loses particles by sedimentation, which depletes the system of mass. Eventually, the system may become buoyant, in which case it becomes a plume.
Velocities vary, typically by 10s of meters per second, but they can also be much faster [44–48].
4D immersive visualization of the simulated partial column collapse scenario at Vesuvius. The collapse of the volcanic eruption column and the propagation of pyroclastic density currents (PDCs), for selected medium-scale (sub-Plinian) eruptive scenarios at Vesuvius, Italy (modified from [55]).
In fluid dynamics, the equations that govern the concentrated current are well known [49, 50], and the mathematics based on this volcanic phenomena is broadly used to model pyroclastic flows, along with other gravity currents: avalanches, seafloor turbidity currents, lahars, and lava flows. Two numerical codes apply these equations with small differences: Titan2D [51] and Volcflow [52, 53], but so far they have not produced any modeling for diluted currents. The only numerical code that models the diluted currents is called PDAC [54]. An application is shown for Somma-Vesuvius volcano, where pyroclastic density currents are modeled on the data of the 1631 AD sub-Plinian eruption ([55]; Figure 13). Kelfourn [53] tried to model two-fluid model block-ash flows and cloud-ash surge at Merapi volcano, developing new equations, but there is not yet an agreement (Kelfourn, personal communication). The importance of modeling diluted currents together with dense currents for the hazard of an explosive active volcano is commonly witnessed from the volcanological history, as seen in the work of Mastrolorenzo [56] who demonstrate the causes of mortality in PDCs at Pompeii and surroundings, on the basis of a multidisciplinary volcanological and bioanthropological study. Field and laboratory studies of the eruption products and victims, merged with numerical simulations and experiments, indicate that heat was the main cause of death. Their results show that exposure to at least 250°C hot surges at a distance of 10 km from the vent was sufficient to cause instant death, even if people were sheltered within buildings. Despite the fact that impact force and exposure time to dusty gas declined toward PDCs’ periphery up to the survival conditions, lethal temperatures were maintained up to the PDCs’ extreme depositional limits. This study suggests that diluted currents are very dangerous, and if the runout of the pyroclastic flow must be chosen, it is always underestimated when considering diluted currents, especially for large eruption.
\nAs indicated in Table 1, the 1903 AD, 1668–1702 AD, and the Millennium eruptions are characterized by the following VEI, respectively: 2–3, 4–5, and ~7. From the classification of Newhall and Self [43], the magnitude of each eruption with all the volcanological parameters can be deduced. If we compare the total volume ejected from Baekdusan volcano in the last Millennium activity with the most devastating eruptions in the recent history of volcanology, it appears that the two most recent eruptions shown, from Mount St. Helens and Mount Pinatubo, each caused extensive damage and received intense media interest. Ejected volumes, however, were only about 1/10,000 (St. Helens) and 1/500 (Pinatubo) of the volumes associated with either the 74 ka Toba or the 2 Ma Yellowstone super-eruptions. Even the 1883 Krakatau eruption, which accounted for over 35,000 deaths, was smaller than the Toba and Yellowstone eruptions by two orders of magnitude. The 1815 Tambora eruption, which had an ejected volume of less than 5% of those of Toba or Yellowstone and was distinctly less than “super,” affected global climate and was responsible for over 50,000 deaths (Figure 14A and B [57]). The 1903 AD eruption can be compared to two recent eruptions: (A) Nevado del Ruiz, Colombia, 1985, (B) Soufrière Hills, West Indies, 1995 (Figure 14B). The two eruptions of 1668–1702 AD of similar size can be compared to the following eruptions: (A) Soufrière Hills, West Indies, 1995, (B) Mount St. Helens, USA, 1980 (Figure 14B). The Millennium eruption may have been slightly larger than the 1815 Tambora eruption, Indonesia. Millennium eruption can be considered a super-eruption alike other eruptions (e.g., Campanian Ignimbrite, Campi Flegrei, Napoli [58]; Figure 15). This assumption is confirmed from some South Korean scientists that during the 2nd International Workshop for Volcanic Disaster Preparedness at Chungbuk National University, Korea affirmed that the Millennium eruption could have been as high as 7 VEI. Further, Xu et al. [42, 59] suggest that the Millennium eruption was a Toba-like "ash giant/sulfur dwarf" and had much smaller global climatic impacts. Sun et al. [60] confirm that the eruption most probably occurred around AD 940s, 7 years after the Eldgjá eruption on Iceland, and examining the eruption’s potential for climate-forcing using the sulfate records from the ice cores, they conclude that it was unlikely to have had a global impact. Zircons U–Th data of Millennium eruption indicate that magma resided only ~8 ka prior to eruption. Therefore, Baekdusan volcano can produce catastrophic, explosive eruptions in the foreseeable future [36]. Thus, Baekdusan is the most active volcano in China [14], and it is a high-risk volcano because more than 100,000 people live on or near the slopes, with the addition of many tourists.
\nA. Relative volumes of pyroclastic material erupted from the large eruption in the 2 Ma [57]. B. Classification of the VEI modified after [4] (modified from [57]).
The Volcanic Explosivity Index (VEI) is calculated with a logarithmic-based scale of erupted mass, as well as past examples, estimated frequency, and probability. It includes large eruptions from 40 km3 in magma volume up to the largest super-eruptions known (modified from [15]).
The size of the 1903 AD eruption has been evaluated, and consequently some Titan2D simulations are presented, taking into account where the vents of the 1903 AD, 1668 AD, and 1702 AD were located. Five vent locations are considered: three inside the caldera lake and two outside the caldera, as illustrated in Figure 16. The simulations start with an initial column (or pile) that collapses. The column is a vertical cylinder with a diameter 250 m and the height Hcol (Table 4). In Figure 17 we report the thickness of the deposit when the flow is stopped. We consider 1 h (3,600s) after the initial collapse of the eruption column which can be formed by the Plinian eruption. The scenario performed shows, according to the vent locations, that the flow moves in diverse directions (NE, SE) with a thickness of 3 m, and that if the vent is located inside the caldera the flow fills the caldera with a thickness of 5 m. If the vent is on the border of the caldera, the flow will deposit thickly, mostly in the northern valley, the upper stream region of Erdaobaihe (Figure 17 [34, 61]).
\nLocation of the considered vents for the Titan2D simulation of the small-scale 1903 AD eruption.
Number | \nVent | \nInt. frict. | \nBed. Frict | \nHcol (m) | \nDiameter (m) | \nVolume (m3) | \n
---|---|---|---|---|---|---|
1 | \nA | \n30 | \n25 | \n1000 | \n250 | \n4.9 × 107 | \n
2 | \nA | \n30 | \n16 | \n1000 | \n250 | \n4.9 × 107 | \n
3 | \nA | \n25 | \n16 | \n1000 | \n250 | \n4.9 × 107 | \n
4 | \nA | \n25 | \n16 | \n2000 | \n250 | \n9.8 × 107 | \n
5 | \nB | \n25 | \n16 | \n2000 | \n250 | \n9.8 × 107 | \n
6 | \nC | \n25 | \n16 | \n2000 | \n250 | \n9.8 × 107 | \n
7 | \nD | \n25 | \n16 | \n2000 | \n250 | \n9.8 × 107 | \n
8 | \nE | \n25 | \n16 | \n2000 | \n250 | \n9.8 × 107 | \n
Parameters used to simulate the pyroclastic flow of 1903 AD eruption needed by Titan2D code.
Results of the Titan2D simulation for a small-scale scenario (VEI 3) similar to the 1903 AD eruption [34, 61].
Possible area covered by a pyroclastic density current of the size of the 1668–1702 AD eruption. The runout chosen could have been underestimated so that the impact would be more severe than expected.
From the pyroclastic density currents scenario of the 1668–1702 AD eruptions with a runout around 5,000 m (Figure 18), two densely populated cities which are nearest to Baekdusan volcano would suffer significant damage: Erdaobaihe and Songjianghe. Possibly, the pyroclastic density currents could also affect two other cities located slightly further away, such as Fusong and Lushuihe. In the case of the Millennium eruption, considering only the direct impact, without considering the indirect effect which in the case of such eruption could be severe, and considering an underestimation of the runout, the following cities will be hit: Erdaobaihe, Songjianghe, Changbai, Huishan, Baishan, Fusong, Lushuihe, and Tumer (Figure 19).
\nPossible area covered by a pyroclastic density current of the size of the Millennium eruption. The runout chosen could have been underestimated so that the impact would be more severe than expected and surely of regional scale, if not global.
The worst-case scenario is surely an eruption of a colossal size (Millennium eruption), but it has to be excluded from the scenario of the 1668–1702 AD eruption. In this case, the hazard and the risk must be evaluated carefully, and the population around Baekdusan volcano must be informed in detail. We think in this case, the population at risk is not aware of the possible hazard of the volcano. In all sorts of circumstances, the population has to be alerted. Every sign of unrest has to be monitored and communicated to everybody involved in the decision-making to the people. As far as we are concerned there is not a robust monitoring system around Baekdusan volcano, especially on North Korea side. An emergency plan must be created for Baekdusan volcano.
\nIn the near future, there are several points in research direction that the Asian scientists could undertake, if they have not done yet: (A) Evolution of the Baekdusan volcano plumbing system in the least 20,000 years. (B) Developing an open source numerical code to model diluted density currents (surge) for the worst-case scenario, (C) Making an event tree study of Baekdusan volcano like that of Somma-Vesuvius volcano, Napoli, Italy.
\nThis research was supported by a grant [MPSS-NH-2015-81] through the Natural Hazard Mitigation Research Group funded by Ministry of Public Safety and Security of Korean government. Thanks to Dr. Giovanni Macedonio for helping in making the simulation of Figure 17 at Osservatorio Vesuviano, INGV, Napoli, Italy. Thanks to Chris Hawkesworth for an early review of the manuscript. Thanks to Steve Sparks to critically looking at the manuscript and addressing the journal for the content of the manuscript.
\nHoney is a natural sweet substance used by human beings since ancient times. The first written evidence of honey was found in a Sumerian tablet dating back to 2100–2000 B.C. [1]. Honey is defined by the European Union as “the natural sweet substance produced by Apis mellifera bees from the nectar of plants or from secretions of living parts of plants or excretions of plant-sucking insects or the living parts of plants, which the bees collect, transform by combining with specific substances of their own, deposit, dehydrate, store, and leave in honeycombs to ripen and mature” [2, 3]. Honey can be classified following its origin, the way it has been harvested and processed. Following honey origin, it is categorised into blossom, honeydew, monofloral and multifloral honeys. Blossom honey is obtained mainly from the nectar of flowers while honeydew or forest honey is produced by bees after they collect “honeydew” from plant saps. Monofloral honey is arising predominantly from a single botanical origin with above 45% of total pollen content from the same plant species, and is named after that plant, such as citrus, manuka and acacia honey [4]. Multifloral honey is also known as polyfloral honey. It has several botanical sources where none is predominant, for example, meadow blossom honey and forest honey. Honey is an important, distinct and widely used food product for nutrient, cosmetic and medicinal purposes.
\nThe main composition of honey is carbohydrates or sugars, which represent 95% of honey dry weight. Honey is a complex mixture of concentrated sugar solution with main ingredients of fructose and glucose. The average ratio of fructose to glucose is 1.2:1 [5]. Sucrose is present in honey at about 1% of its dry weight. The exact proportion of fructose to glucose in any honey depends largely on the source of the nectar. It also contains bioactive compounds like organic acids, proteins, amino acids, minerals, polyphenols, vitamins and aroma compounds [6, 7]. The protein content of honey is normally less than 0.5% with a small fraction of enzymes. The overall quality of honey such as taste, colour and other physical properties are contributed by the non-volatile compounds like sugar, amino acids, minerals and phenolic compounds while aroma of honey is mainly contributed by the volatile components [8]. The compositional criteria prescribed in existing honey directive are requirements relating to concentrations of acidity, apparent reducing sugar which is calculated as invert sugar and apparent sucrose, 5-hydroxymethylfurfural (HMF), mineral content, moisture and water-insoluble solids [9]. HMF is formed from reducing sugars in honey in acidic environment and often used to evaluate honey quality as it is strongly correlated to ageing and overheating of honey [10]. It is set at maximum limit of 40 mg/kg in honey (with a higher limit of 80 mg/kg for tropical honey) by the Codex Alimentarius Standard commission [11].
\nHoney has various biological properties including antimicrobial, anti-viral, anti-inflammatory, wound and sunburn healing, antioxidant, anti-parasitic, anti-diabetic, anti-mutagenic and anti-tumoral activities [5, 12, 13, 14, 15, 16, 17]. Recent pharmacological studies have revealed that natural honeys have potential to reduce risk of gastric and cardiovascular diseases [18] and have beneficial effects on fertility and ameliorating hormones related to fertility [19, 20, 21]. With many beneficial properties, honey is highly priced and is also the major target of adulteration.
\nHoney has become the target of adulteration with sugar and/or syrups, for example, cheaper sweeteners from beet or canes like corn syrups (glucose), high fructose corn syrup (HFCS), saccharose syrups, and invert sugar syrups in several countries [22]. In some places, honey is adulterated by bee feeding with sugars or syrups to produce artificial honey. Adulterated honey in the market is often labelled and sold as pure honey and artificial honeys are mislabeled for its botanical or geographical origin [23]. The monofloral honeys are main target for mixing with cheaper multifloral honeys. Monofloral honeys, being the most appreciated by consumers are recognised as better-quality products and they have higher market values [24]. Identification of pure honey and its authenticity have been done based on honey properties. As it becomes an important task for processors, retailers, consumers and regulatory authorities, various analytical methods to measure honey authenticity have been used to detect these honey frauds (Figure 1).
\nConventional and modern analytical methods used for honey authentication.
The classical approach in honey authentication studies is used for determining its botanical origin. Sensory and physicochemical analyses are used in determining monofloral honey origins while the melissopalynological analysis is commonly used to identify floral pollen grains present in honey by microscopic examination [25]. The melissopalynological approach however may not be appropriate for some types of honey like the citrus as the level of pollen content is variable and normally little [26]. The proportion of pollen content is dependent on the plant species, collection season and the nectar yield in male and female flowers. In some cases, pollen can be filtered out in the bee’s honey sac and added fraudulently in honey [27]. Due to the significant natural variation of pollen content, this method is now accompanied with sensory analysis and determination of certain physicochemical characteristics. The number of physicochemical parameters necessary for a complete characterisation is very high and melissopalynology has disadvantages of being slow, very tedious to implement and requires a considerable amount of training.
\nDue to the limitations of the classical authentication techniques, more reliable modern analytical methods are used to determine botanical and geographical origins of honey. The studies include measuring carbohydrate (sugar) profiles [28], mineral content [29], phenolic and flavonoid compositions [30], aroma profile [31, 32] and amino acid composition [33] using advanced analytical tools like chromatographic techniques [28], mass spectrometry (MS)-based techniques [34, 35], vibrational spectroscopy like infrared (IR) and Raman techniques [36], nuclear magnetic resonance (NMR) [37], stable isotope analysis [38, 39] and others such as flame ionisation detectors (FID) or sensor arrays [40, 41].
\nSeveral authors studied on the detection of adulterants like exogenous sugars or additions of sugar syrups by evaluating carbohydrate with different analytical techniques [42, 43, 44]. Honey is principally constituted by a mixture of different saccharides such as glucose, fructose, tri- and tetrasaccharides while other components are present only in very minimum amount [45]. Botanical classification of honey was previously studied using sugar profile and recently high-performance liquid chromatography (HPLC) and chemometric analysis are used to determine sugar profiles of honey [46, 47]. For evaluating floral origin of honey, its volatile composition is determined using headspace solid-phase microextraction (SPME) and gas chromatography coupled to mass spectrometry (GC–MS) [48]. Researchers have also integrated these techniques with chemometric analysis to classify botanical origin of honeys [48, 49]. In chemometric techniques, principal component analysis (PCA) and linear discriminant analysis (LDA) are used to determine the most influencing variables and similarities in studied honey samples [50, 51]. Recent studies have demonstrated the use of molecular genetics approach in determining composition and geographical origins of honey [24], and entomological origins of honey [52, 53, 54, 55]. The advantages and limitations of each analytical technique are reviewed and compared in the following sections.
\nPhysicochemical parameters such as pH, sugar content, proline, enzymatic activity, moisture content, ash content, diastase activity, free acidity and hydroxymethylfufural (HMF) content could provide useful information of honey origin. Nozal Nalda et al. [46] found significant differences of honey samples in terms of 15 mineral contents (except for iron and zinc) and 8 physicochemical parameters (except for sucrose and HMF) in their large-scale study on 73 different honeys of 7 botanical origins of the ling, heather, rosemary, thyme, honeydew, spike lavender and French lavender honeys. The classification of three monofloral Serbian honeys, the acacia, sunflower and linden could be based on variables such as electrical conductivity (0.10–0.76 mS/cm), free acidity (7.80–42.70 meq/kg) and pH (3.17–5.85) [56]. Silvano et al. [57] reported significant differences in the mean value of HMF, colour, electrical conductivity and sucrose content for honeys harvested from different apiaries such as agricultural, hill and meadow zones of the southeast region of Buenos Aires province in Argentina. Table 1 presents other comparative studies on physicochemical parameters of different types of honeys by investigators from different regions [49, 50, 58, 59, 60, 61, 62, 63]. The physiochemical properties of honey are highly dependent on the type of flowers visited by bees, as well as influenced by seasonal, geographical and climatic conditions. Kek et al. [52, 53] have used physicochemical, antioxidant properties and various chemical profiles which included proximate composition, predominant sugars, HMF content, diastase activity, mineral and heavy metal contents to classify honey by its entomological origin, that is, following the bee speciation of honey bees (Apis spp.) or stingless bees (Heterotrigona spp.).
\nAnalytical techniques | \nSamples | \nReferences | \n
---|---|---|
Melissopalynological | \n10 Lavender and 10 Lavandin honeys | \n[66] | \n
Palynological | \n20 Moroccan honey samples from sunflower, crucifer, carob tree, loeflingia, heather, mint and wood sage | \n[58] | \n
Sensory properties | \n205 Slovenian honey from different geographical regions | \n[50] | \n
24 multifloral honey samples | \n[57] | \n|
11 brands of bottled honey from the Indian market | \n[60] | \n|
21 locally produced Danish honeys | \n[64] | \n|
49 commercial Spanish monofloral honeys | \n[65] | \n|
Chesnut honeys | \n[67] | \n|
Physicochemical properties | \n73 honeys from 7 botanical origins: ling, heather, rosemary, thyme, honeydew, spike lavender and French lavender | \n[46]* mineral | \n
30 Uruguayan samples, Eucalyptus spp., Citrus spp., Baccharis spp. and multifloral | \n[49]* chemical | \n|
205 Slovenian honey from different geographical regions | \n[50] | \n|
201 samples from 3 unifloral Serbian honeys: acacia, sunflower and linden | \n[56] | \n|
24 multifloral honey samples | \n[57] | \n|
20 Moroccan honey samples from sunflower, crucifer, carob tree, loeflingia, heather, mint and wood sage | \n[58]* colour | \n|
22 Brazilian honey of Eucalyptus and Citrus spp. | \n[59]* ash | \n|
11 brands of bottled honey from the Indian market | \n[60] | \n|
26 honey samples from beekeepers in Lithuania | \n[61]* carbohydrate & electrical conductivity | \n|
77 honey samples: 53 blossom and 24 suspected honeydew | \n[62] | \n|
67 samples of Indian honeys | \n[63]* trace metal | \n|
5 raw Malaysian honey from 4 bee species and 3 commercial honey | \n[52, 53]* chemical, mineral & antioxidant | \n
Physicochemical techniques used for identification of honey.
Other properties included in studies besides the general physicochemical properties.
The sensory properties variation within honeys due to flora in local habitat can be mirrored by pollen analysis or sensorial studies for honey recognition. Stolzenbach et al. [64] reported that Danish honeys had distinct and unique flavours related to its origin of location. Coupled with sensorial analysis, Castro-Vazquez and co-workers used GC–MS to profile volatile compounds of 49 Spanish honey samples from different botanical origins of citrus, rosemary, eucalyptus, lavender, thyme and heather [65] followed by identifying floral marker origins for lavender and lavandin honeys [66]. Lavandin honey is a monofloral product of recent proliferation obtained from a hybrid of the species Lavandula angustifolia and Lavandula latifolia. In their study, high concentrations of g-nonalactone, farnesol and acetovanillone, which were identified for the first time as components of honey aroma and lactones, dehydrovomifoliol, 4-methoxyacetophenone and decanal were suggested as chemical markers for authenticating lavandin monofloral honey. Similar approach of chemical and sensory characteristics of honey was used to classify chestnut honey geographically [67].
\nDifferent chromatographic techniques have been reported to determine sugar, amino acids, phenolic and flavonoid profiles of honey samples (Table 2). In the early days, Doner et al. [68] determined maltose/isomaltose ratios of honeys and high fructose corn syrup using gas chromatographic (GC) method. They reported that ratios higher than 0.51 indicated adulteration. Kushnir [69] demonstrated a thin layer chromatography separation for oligosaccharides in honey after sample clean-up by a charcoal-Celite column. Later, Lipp et al. [70] developed a medium-pressure liquid chromatography method using a charcoal/celite mixture for detection of conventional and high fructose syrup in honey at a level as low as 1% of the total mixture. Honey adulterated with commercial sweeteners could be identified easily based on the sucrose level which was slightly higher than the sucrose content of natural honey [71]. Ouchemoukh et al. [28] investigated sugar profiles of 50 honey samples from different regions of Algeria by HPLC with pulsed amperometric detection (PAD) where 11 sugars were quantified. The average values of fructose and glucose were in the range of 35.99–42.57% and 24.63–35.06%, respectively. The sucrose, maltose, isomaltose, turanose and erlose were found in nearly all the analysed samples, while raffinose and melezitose were present in few samples. Cordella et al. [43] used high performance anion exchange chromatographic method with pulsed amperometric detection (HPAEC-PAD) to detect adulterated honey samples with industrial bee-feeding sugar syrups. Morales et al. [72] determined high molecular weight oligosaccharides of 9 sugar syrups and 25 honey samples using HPAEC-PAD for detection of honey adulterated with corn syrups and high fructose corn syrup (HFCS). Xue et al. [73] developed an HPLC-diode-array detection (DAD) method to detect honey adulteration using rice syrup and identified the adulterant compound from rice syrup as 2-acetylfuran-3-glucopyranoside. Puscas et al. [74] developed a simple and economical analytical method for detecting adulteration of some Romanian honeys based on high-performance thin-layer chromatography (HPTLC) combined with image analysis. The method was then applied for quantitative analysis of glucose, fructose and sucrose contents from different types of commercially available Romanian honeys. Cotte et al. [75] have developed a method using LC coupled with a pulsed amperometric detector (PAD) to assay fructose and glucose, and GC coupled with a flame ionisation detector (FID) to determine the entire profile of di- and trisaccharides.
\nSugar profiles | \nSamples | \nReferences | \n
---|---|---|
HPLC | \n2 nectar and honeydew honeys of different geographical and floral origin | \n[70] | \n
HPLC-PAD | \n50 honey samples from different regions of Algeria | \n[28] | \n
HPAEC-PAD | \nFir, rosemary, chestnut and thyme honeys | \n[43] | \n
17 artisanal and 8 commercial honeys | \n[72] | \n|
HPLC-DAD | \n160 honey samples from Acacia, jujube, rape, linden, litchi, clover and multifloral | \n[73] | \n
HPTLC | \n15 commercial honeys from 3 types of flowers: lime, polyfloral and acacia | \n[74] | \n
GC–MS/FID and LC- PAD | \n280 French honeys from 7 monofloral varieties: 50 acacia, 38 chestnut, 28 rape, 53 lavender, 37 fir, 38 linden and 36 sunflower | \n[75] | \n
Amino acid profiles | \n||
GC | \n45 honey samples from the UK, Australia, Argentina and Canada | \n[76] | \n
HPLC | \nA variety of different honey samples | \n[77] | \n
280 French honeys from 7 monofloral varieties: 50 acacia, 38 chestnut, 28 rape, 53 lavender, 37 fir, 38 linden and 36 sunflower | \n[78] | \n|
7 different floral types of Serbian honey: acacia, linden, sunflower, rape, basil, giant goldenrod and buckwheat | \n[80] | \n|
LC-ECD | \n29 honeys: 12 of floral origin and 17 from honeydew | \n[79] | \n
10 acacia honeys and 10 rape honeys | \n[81] | \n|
Phenolic and/or flavonoid profiles | \n||
HPLC | \n9 monofloral eucalyptus honeys from Australia | \n[82, 84] | \n
Australian Melaleuca, Guioa, Lophostemon, Banksia and Helianthus honeys | \n[8, 83] | \n|
Polish honey from heather and buckwheat | \n[85] | \n|
119 unifloral honeys from 14 different geographical regions | \n[87] | \n|
7 honey samples: acacia, sulla, thistle and citrus honeys | \n[88] | \n|
4 types of Spanish honey: floral origin of citrus, rosemary and polyfloral and forest origin of honeydew | \n[92] | \n|
3 Malaysian tropical honeys: Tualang, Gelam and Borneo and 1 Manuka honey | \n[93] | \n|
HPLC-DAD | \n40 samples of Robinia honey from Croatia | \n[30] | \n
38 sage honey samples from Croatia | \n[89] | \n|
5 types of honey: 2 milk vetch, 1 wild chrysanthemum, 1 jujube flower and 1 acacia | \n[94] | \n|
HPLC-ECD | \nChinese citrus honey | \n[90] | \n
HPLC-UV | \n90 Italian honeys | \n[86] | \n
HPLC-UV and GC–MS | \nLemon blossom honey and orange blossom honey | \n[91] | \n
Chromatography-based techniques used for honey authentication.
Gilbert et al. [76] determined 17 free amino acids in 45 honey samples collected from the UK, Australia, Argentina and Canada by using GC. Pawlowska and Armstrong [77] used HPLC methods to determine concentrations of proline, leucine and phenylalanine and their enantiomeric ratios from various honey samples. Cotte et al. [78] claimed to be the first to use HPLC system to discriminate different botanical origins of honey using acid amino analysis. They were successful in characterising Lavender honey. Iglesias et al. [79] developed a reliable and simple method of liquid chromatography–electrochemical detection (LC-ECD) to detect adulteration of acacia honey which was added with rape honey at different levels. Fingerprints of authentic honeys showed that contents of chlorogenic acid were higher in acacia honey, while those of ellagic acid were much lower in rape honey. The free amino acids profile of seven different floral types of Serbian honey (acacia, linden, sunflower, rape, basil, giant goldenrod and buckwheat) from 6 different regions were analysed to discriminate honeys by their botanical origins [80]. Wang et al. [81] suggested chlorogenic acid and ellagic acid as possible markers of acacia and rape honeys authenticity study using LC-ECD.
\nCurrently, research is predominantly focused on determination of phenolic and flavonoid profiles due to their pharmacological properties. Many studies have reported phenolic and flavonoid profiles of honey in relation to botanical and geographical origins using various chromatography techniques [8, 82, 83, 84, 85, 86, 87]. The determination of phenolic compounds in honey includes removal of matrix components (especially sugars) and analysis of pre-concentration of analytes using HPLC techniques [88]. Yao et al. [82, 83] analysed phenolic acids and flavonoids along with two abscisic isomers related to botanical origins of nine monofloral Eucalyptus honeys and other five botanical species (Melaleuca, Guioa, Lophostemon, Banksia and Helianthus) from Australia. In Croatia, flavonoid profiles of Robinia honeys [30] from two production seasons and monofloral sage honey [89] were measured using HPLC/DAD method. The respective honeys showed a common and specific flavonoid profile, but the contents varied between seasons. Liang et al. [90] established a sensitive and accurate method using HPLC-ECD for simultaneous separation and determination of four phenolic compounds, including caffeic acid, p-coumaric acid, ferulic acid and hesperetin in Chinese citrus honey which were 6–14 times greater than those obtained with DAD. Escriche et al. [91] evaluated flavonoids (naringenin, hesperetin, chrysin, galangin, kaempferol, luteolin, pinocembrin and quercetin) and phenolic acids (caffeic acid and p-coumaric acid) together with 37 volatile compounds in the differentiation between lemon blossom honey (Citrus limon) and orange blossom honey (Citrus spp.). Naringenin and caffeic acid were the main components in all samples. They have concluded that botanical origin affected the profile of flavonoids and phenolic compounds sufficiently to permit discrimination of honeys, that is, hesperetin in citrus honey, kaempferol, chrysin, pinocembrin, caffeic acid and naringenin in rosemary honey, and myricetin, quercetin, galangin and particularly p-coumaric acid in honeydew honey [92]. Khalil et al. [93] investigated phenolic acid and flavonoid contents of Malaysian Tualang, Gelam and Borneo tropical honeys in comparison with Manuka honey. A total of six phenolic acids (gallic, syringic, benzoic, trans-cinnamic, p-coumaric and caffeic acids) and five flavonoids (catechin, kaempferol, naringenin, luteolin and apigenin) were identified. Jasicka-Misiak et al. [85] determined phenolic profiles of Polish honey samples from heather (Calluna vulgaris L.) and buckwheat (Fagopyrum esculentum L.). The results revealed that the samples of the same unifloral honeys registered a similar qualitative but slightly quantitatively different phenolic characteristic profiles. Perna et al. [86] identified and quantified phenolic acids, flavonoids and vitamin C in 90 Italian honeys of different botanical origins (chestnut, sulla, eucalyptus, citrus and multifloral) using HPLC–UV analysis. The results showed a similar but quantitatively different phenolic profile of the studied honeys. Zhang et al. [94] described the use of second-order calibration for development of HPLC-DAD method to quantify nine polyphenols in five types of honey samples. Greek unifloral honeys (pine, thyme, fir and orange blossom) were analysed and classified according to botanical origin based on phenolic content (quercetin, myricetin, kaempferol, chrysin and syringic acid) by HPLC analysis [87]. Recently, Campone et al. [88] described a novel approach for a rapid analysis of 5 phenolic acids and 10 flavonoids in honey using dispersive liquid-liquid microextraction followed by HPLC analysis. The proposed new method, compared with commonly used method in analysis of phenolic compounds in honey, provided similar or higher extraction efficiency with exception of the most hydrophilic phenolic acids. These chromatographic techniques provide quite complex chromatograms and coupled with appropriate analyses, can classify honey according to their botanical, geographical and entomological origins.
\nThe LC–MS and GC–MS methods are used to separate and identify semi-volatile and volatile components in honey. Volatiles influence chiefly to honey flavour and to its variation of floral origin. Table 3 shows various mass spectrometry techniques used for detection of honey origin. The headspace (HS) solid-phase microextraction (SPME) is the most preferred technique for determining concentration of honey volatiles [91, 95, 96]. With the HS-SPME followed by GC/MC analysis, various volatile components in honey have been detected, identified and quantified, for example, 35 volatile components from Spanish honeys [97], 62 compounds from 28 Greek honeys [98], 31 compounds from 16 samples from mostly European countries [99] and 26 commonly available volatiles in 70 authentic Turkish honey from 9 different floral types [100]. Bianchi et al. [101] developed a HS-SPME method and characterised 40 volatile compounds of Italian thistle honey. In Spain, Soria et al. [102] differentiated honey origins of mountain and plain by characterising their volatile compositions using 46 artisanal honey samples from different places of Madrid province. Later in 2019, the same co-workers characterised Spanish honeys to their botanical origin using 132 volatile compounds from 40 honey samples [103]. Although volatile compounds can be used to differentiate honey according to country, Juan-Borrás et al. [104] concluded that botanical origin differentiates honey samples better than geographical origin in their research using acacia, sunflower and tilia honeys from Spain, Romania, and Czech Republic. In extension to HS-SPME/GC–MS, Baroni et al. [48] used chemometric to determine organic volatile compound pattern to characterise 42 unifloral honey samples from 5 floral origins while Aliferis et al. [105] used finger-printing to discriminate and classify Greek honeys by their plants and geographical origins. Spanik et al. [106] and Verzera et al. [35] developed a new analytical approach based on enantiomeric ratio investigation of chiral volatile constituents using SPME-GC–MS to evaluate authenticity of honeys.
\nVolatile Profiles | \nSamples | \nReferences | \n
---|---|---|
GC–MS | \n80 raw unifloral honey: acacia, sunflower and tilia or lime from Spain, Romania and Czech Republic | \n[104] | \n
70 Turkish honey from 15 different geographical regions | \n[100]*LC/MS for free amino acids | \n|
SPME/GC–MS | \n36 samples of orange honey | \n[35]*chiral volatile compounds | \n
42 unifloral honey samples from 5 floral origins: alfafa, sunflower, white clover, carob and calden | \n[48]*chemometrics | \n|
28 thyme honeys samples from different locations all over Greece | \n[98] | \n|
Commercial types of European honey | \n[99] | \n|
46 artisanal honey samples collected in Madrid province, Central Spain | \n[102] | \n|
40 commercial honey samples | \n[103] | \n|
Rapeseed, chestnut, orange, acacia, sunflower and linden honeys | \n[106]*chiral volatile compounds | \n|
HS-SPME/GC/MS | \n7 samples of thistle honey | \n[101] | \n
77 unifloral honey samples of different botanical origins | \n[105]*fingerprinting | \n|
HS-SPME/GC × GC-TOF-MS | \n374 honey samples of Corsican, non-Corsican–French, Italian, Austrian, Irish and German | \n[31, 34] | \n
SIFT-MS | \n9 New Zealand honeys: beech honeydew, clover, kamahi, manuka, rata, rewarewa, tawari, thyme and vipers bugloss | \n[109] | \n
10 Ohio and Indiana honey samples: star thistle, blueberry, clover, cranberry and wildflower | \n[110] | \n|
SPME and LC-DAD-ESI/MS | \nAcacia, linden, chestnut, fir, spruce, floral and forest honeys from Slovenia | \n[51] | \n
HPLC-DAD-MS/MS | \nStrawberry tree honeys | \n[111] | \n
187 honey samples: 98 chaste honey and 89 rape honey | \n[112] | \n|
SPME and UPLC-PDA-MS/MS | \nManuka, honeydew, heather, chestnut, and eucalyptus honeys from various geographical origins and ages | \n[113] | \n
UPLC-Q/TOF-MS | \nSunflower, lime, clover, rape and honeydew honey | \n[114] | \n
Sugar Profile (Carbohydrates and Syrups) | \n||
GC–MS | \nHoneys from avocado, strawberry tree, willow, loquat, almond tree, fir, evergreen oak, Anthyllis cytisoides, Satureja montana, Teide broom, agave and tajinaste | \n[45] | \n
20 honey samples: 16 nectar and 4 honeydew honeys | \n[107] | \n|
107 floral honeys: heather, rosemary, eucalyptus and citrus | \n[108] | \n
Mass spectrometry-based techniques used for honey authentication.
Additional feature of measurements.
Besides volatile components in honey, GC–MS has also been used to identify sugar compounds in honey. de la Fuente et al. [45] identified various carbohydrate markers in identifying botanical origins of Spanish honey such as disaccharide maltulose and carbohydrate alcohols of perseitol in avocado honeys and melezitose and quercitol in evergreen oak honeys. Carbohydrate composition of 20 honey samples (16 nectar and 4 honeydew honeys) and 6 syrups has been studied by GC and GC–MS in order to detect differences between both sample groups. The presence of difructose anhydrides (DFAs) in these syrups was described for the first time [107]. Ruiz-Matute et al. [108] developed a GC–MS method for the detection of honey adulteration with high fructose inulin syrups. Inulotriose proved to be the best marker of honey adulteration with these syrups since it was not detected in any of the analysed honey samples.
\nBeyond HS-SPME, Cajka et al. [31] and Stanimirova et al. [34] investigated the use of the system with comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) to analyse volatile components in honey samples. Langford et al. [109] and Agila and Barringer [110] used selected ion flow tube-mass spectrometry (SIFT-MS), a growing technology that quantifies volatile organic compounds at low concentrations (usually parts-per-trillion, ppt levels) to determine aromas arise from volatile organic compounds in headspace of different monofloral honeys from New Zealand and Ohio, and Indiana, respectively. Furfural, 1-octen-3-ol, butanoic and pentanoic acids were the volatiles with the highest discriminating power among the different types of floral honey [110]. Bertoncelj et al. [51] used diode array detection system and electrospray ionisation mass spectrometry (LC-DAD-ESI/MS) to analyse flavonoid profiles of seven types of Slovenian honey upon solid-phase extraction followed by liquid chromatography to study their botanical origins. The performance liquid chromatography–diode array detection–tandem mass spectrometry (HPLC–DAD–MS/MS) method was used to trace floral origin of strawberry tree honey [111] and chaste honey and rape honeys [112]. Kaempferol, morin and ferulic acid were used as floral markers to distinguish chaste honey from rape honey. Oelschlaegel et al. [113] used photodiode array detection (PDA) with ultra-performance liquid chromatography (UPLC-PDA-MS/MS) to analyse volatile composition of numerous Manuka honeys after solid-phase extraction and identified kojic acid, unedone, 5-methyl-3-furancarboxylic acid, 3-hydroxy-1-(2-methoxyphenyl)penta-1,4-dione and lumichrome in Manuka honey for the first time. Other technologies used include the system of Ultra Performance Liquid Chromatography-Quadrupole/Time of flight-mass spectrometry (UPLC-Q/TOF-MS) where it was possible to identify several components which cannot be detected by diode array using combination of detection with retention time for accurate molecular mass to obtain phenolic acids and flavonoids from ethyl acetate extracts of different honeys (sunflower, lime, clover, rape and honeydew) [114].
\nThe stable isotope ratio analysis using mass spectrometry may be used to detect adulterated honey samples based on the principle of different δ13C or 13C/12C ratio [115, 116, 117]. Honey-producing plants, as well as sugar beets belong to the C3 plants while sugar cane, corn and other major source of adulterating syrups are from the C4 plants. Their different photosynthetic pathways result in a different metabolic enrichment of the 13C isotope. The slower reacting 13CO2 is depleted to a larger extend in C3 plants than in C4 plants during the CO2 fixation (kinetic isotope effect). Thus, it is possible to detect the addition of cheap C4 sugar because of its different δ13C value ranging from −22 to −33δ‰ for honey from C3 plants, −10 to −20δ‰ for honey from C4 plants and −11 to −13.5δ‰ in honey from Crassulacean Acid Metabolism plants (pineapple and cactus). When C4 sugar is added to pure honey, the δ13C value of honey will be altered where honey with δ13C values less negative than −23.5‰ is suspected to be adulterated. The protein extracted from honey can be used as an internal standard for the determination of adulteration in honey as the corresponding δ13C of protein extract will remain constant. The difference in δ13C between honey and its associated protein extract accepted is −1δ‰ deviation at least, which provides the international benchmark of 7% of C4 sugar added [116]. Table 4 lists honey authentication studies based on IRMS analysis.
\nIsotope δ13C | \nSamples | \nReference | \n
---|---|---|
IRMS | \n49 samples of honey | \n[115] | \n
40 samples of honey of various botanical origins produced in Brazil, and 8 imported samples, 1 from Argentina, 3 from the USA and 4 from Canada | \n[116] | \n|
73 Italian honey samples from 6 varieties: chestnut, eucalyptus, heather, sulla, honeydew and wildflower | \n[117] | \n|
100 pine honey samples | \n[118] | \n|
13 different brands of honey samples | \n[120] | \n|
271 Slovenian honey samples from 7 floral types and 4 geographical regions | \n[38]* δ15N | \n|
EA-IRMS | \n140 honeys from 7 different botanical origins: acacia, chestnut, rapeseed, lavender, fir, linden and sunflower | \n[121] | \n
31 Turkish honey from different sources and regions: flower, pine and chestnut and 43 commercial honey | \n[123] | \n|
58 honey samples: Northeast China black bee, chaste, acacia, clover, chaste, flowers and jujube honeys | \n[124] | \n|
Commercial honey | \n[22] | \n|
516 authentic honeys from 20 European countries | \n[39]* δ2H, δ15N, δ34S | \n|
HPLC-IRMS | \n79 commercial honey samples | \n[119] | \n
EA/LC-IRMS | \n451 authentic honeys | \n[122] | \n
IRMS and SNIF-NMR | \n102 French honey from 97 varieties: acacia, chestnut, rape, lavender, fir, linden and multifloral | \n[44] | \n
Flow isotope IRMS | \nManuka honey from New Zealand | \n[125] | \n
Isotope-based techniques to determine botanical and geographical origins of honey.
Include other isotopes measurements.
Most honey adulteration studies using carbon isotope ratio mass spectrometry (IRMS) are tested on the addition of C4 plant sugars such as HFCS in Turkish pine honey [118], beet sugar products or corn syrup addition in Spanish honey [115] and HFCS, glucose syrup from corn starch and saccharose syrups from beet sugar [22]. Cabanero et al. [119] determined individual sugars like sucrose, glucose and fructose 13C isotope ratios from honeys of various botanical and geographical origins sources which have been adulterated with beet sugar (C3) and/or C4 sugars like cane sugar, cane syrup, isoglucose syrup and high-fructose corn syrup (HFCS). They developed the first isotopic method that allows beet sugar addition detection. Cengiz et al. [120] provided further validation parameters, such as the limit of detection, limit of quantification and recovery for honey adulteration detection method developed using IRMS.
\nBesides carbon isotope ratios for sugar and protein, Kropf et al. [38] used the nitrogen stable isotope in honey authentication study using 271 honey samples from 4 different geographical regions of Slovenia while Schellenberg et al. [39] used multiple element stable isotope ratios of hydrogen, carbon, nitrogen and sulphur stable for 516 authentic honeys from 20 European regions. Daniele et al. [121] developed a method to discriminate honeys from seven botanical origins, based on organic acid analysis. The authors suggested that by combining various organic acid contents and values of isotopic ratio through statistical processing by PCA, it is possible to discriminate honey samples as a function of their botanical origin.
\nThe IRMS system used are also enhanced with an elemental analyser and to a liquid chromatograph [122, 123, 124] in studies to determine adulteration of C4 plant sugar content in honey. Cotte et al. [44] used site-specific natural isotopic fractionation determined by NMR to first determine their potentials for characterising the substance and then to detect adulteration. They found that the system is limited by detection of a syrup spike starting only at 20%. Frew et al. [125] used a continuous flow IRMS in their adapted method for removing pollen in Manuka honey to improve authenticity detection.
\nFourier Transform-infrared (FTIR) spectroscopy, near infrared (NIR) and FT-Raman spectroscopy methods have also proved their great potential in food authentication studies. In recent years, these spectroscopic techniques have achieved wide acceptance in the field of food sciences for quantitative and qualitative analysis because of its advantages of collecting high-spectral-resolution data over a wide spectral range. They have been applied successfully in honey authentication studies from the aspects of identification of honey origins and determination of adulterants (Table 5).
\nTechnique | \nSamples | \nReferences | \n
---|---|---|
NIR | \n74 commercial honey | \n[131] | \n
Avocado honey | \n[130] | \n|
167 unfiltered honey samples and 125 filtered honey samples | \n[133] | \n|
Honey from 6 floral origins | \n[134] | \n|
30 honey samples from Galicia | \n[135] | \n|
75 honey samples from Ireland | \n[138] | \n|
68 honey samples from 6 floral origins: Brassica spp., Zizyphus spp., Citrus sp., Robinia pseudoacacia, Vitex negundo var. heterophylla and multiflora | \n[139] | \n|
144 honey samples: 70 unadulterated honey samples from different apiary of Beijing and 74 honey samples from local grocery stores | \n[140]*fibre optic diffuse reflectance | \n|
Authentic, unfiltered honeys of Corsican and non-Corsican | \n[132]* spectral fingerprinting | \n|
FTIR | \n37 honey samples from different regions in the world | \n[36] | \n
1075 honey samples from Germany | \n[136] | \n|
FT-NIR | \n364 samples from 7 unifloral and polyfloral honeys | \n[126] | \n
421 honey samples | \n[128] | \n|
FTMIR | \n144 honey samples from 7 different crops, polyfloral and honeydew honeys | \n[129] | \n
Commercial honey, orange blossom, clover and buckwheat | \n[137] | \n|
Front-Face Fluorescence Spectroscopy | \n371 samples from 10 unifloral and polyfloral honeys | \n[127] | \n
FT-Raman | \nHoney samples of clover, orange and buckwheat | \n[142] | \n
Corsican samples from other geographical origins: France, Italy, Austria, Germany and Ireland | \n[143] | \n|
i-Raman | \n74 authentic honey samples from 10 floral origins | \n[141] | \n
FTMIR-ATR | \n99 authentic honey samples from artisanal beekeepers in Ireland | \n[146] | \n
580 samples of artisanal Irish honeys | \n[147] | \n|
FTIR-ATR | \n150 honey samples from Europe and South America | \n[148] | \n
Honey samples from 4 different states of Mexico | \n[149] | \n
Infrared spectroscopy-based techniques used in honey authentication.
Additional features of measurements.
Ruoff and co-workers have used chemometric evaluations of the spectra measured in various European honeys using near-infrared spectroscopy [126] and front-face fluorescence spectroscopy [127] to authenticate botanical and geographical origins of honey. Important physical and chemical measurands in honey such as sucrose and fructose/glucose ratio using near-infrared spectrometry [128] and by mid-infrared spectrometry (MIR) [129] were also helpful for assessing honey adulteration. Dvash et al. [130] reported the application of NIR reflectance spectroscopy to determine concentration of perseitol, a sugar that is specific to avocado honey. Qiu et al. [131] studied influences of various sample presentation methods and regression models and presented that the spectroscopic technique could accurately determine moisture, fructose, glucose, sucrose and maltose contents in honey samples. Woodcock and co-workers used chemometric tools in NIR spectroscopic studies to differentiate different geographical origins of honey which included Corsican and non-Corsican [132], and honeys from Ireland, Mexico, Spain, Argentina, Czech and Hungary [133]. Using NIR, Liang et al. [134] has successfully classified 147 honey samples from six floral origins at perfect classification rate of 100% and Latorre et al. [135] differentiated Galacian honey by protected “Mel de Galicia” geographical location. Using FTIR, Etzold and Lichtenberg-Kraag [136] determined various botanical origins of honey based on physical–chemical characterisation while Wang et al. [36] determined geographical origins based on sugar profiles. For honey adulterants like commercial syrup including glucose and fructose, Sivakesava and Irudayaraj [137] classified simple and complex sugar adulterants using mid-NIR, Downey et al. [138] and Zhu et al. [139] have reported the use of transflectance spectra while Chen et al. [140] used a fibre optic diffuse reflectance probe in their NIR systems.
\nThe other different spectroscopy technique in material characterisation is known as the FT-Raman spectroscopy. It measures relative frequencies at which a sample scatters radiation unlike the IR spectroscopy, where it measures absolute frequencies at which a sample absorbs radiation. Li et al. [141] studied the potential of Raman spectroscopy for detecting fructose corn syrup and maltose syrup adulterants in honey. Paradkar and Irudayaraj [142] investigated on adulterants like cane and beet invert in honey. Pierna et al. [143] used FT-Raman spectroscopy to differentiate Corsican honeys from other regions in France, Italy, Austria, Germany and Ireland.
\nDespite being relevant in honey authentications, IR or Raman spectroscopic techniques are known to give problems to food samples during analysis as prolonged exposure of food sample to laser beam may lead to sample destruction due to heat. The water absorption is very intense in the mid-IR region. A shorter irradiation time and increasing number of scans are recommended to avoid this problem [144]. de la Mata et al. [145] performed attenuated total reflection (ATR) to overcome this problem. FTIR spectroscopy and attenuated total reflection (ATR) sampling technique were used to study botanical origin of honey sample at mid-infrared spectra [146, 147]. Hennessy et al. [148] used the similar but with a germanium ATR to verify origin of honey samples from Europe and South America. Gallardo-Velázquez et al. [149] quantified three different adulterants, corn syrup, HFCS and inverted sugar (IS) in honeys of four different locations in Mexico.
\nNuclear magnetic resonance (NMR) spectroscopy provides important structural information for a wide variety of food components and is recognised as one of the main analytical techniques for authentication of food products as it is strongly focused on both structural and chemical characterisation [150, 151]. Table 6 lists researches which have used NMR technique to authenticate honey samples in relation to geographical or botanical origins and honey adulteration. The more common NMR experiments are the one-dimensional (1D) referred as NMR at 1H or 13C spectra and the two-dimensional (2D) NMR referred as the classical 1H13C heteronuclear multiple-bond correlation (HMBC). One-dimensional 1H NMR spectra was used to profile saccharides of honey from different countries [152, 153]. Boffo et al. [154] discriminated botanical origins of Brazlian honeys from the eucalyptus, citrus and wildflower origins. Donarski et al. [37] used cryoprobe 1H NMR spectroscopy for verification of Corsican honey’s geographical locations in Europe and later used biomarkers to identify botanical origins of sweet chestnut and strawberry-tree honeys [155]. Zielinski et al. [3] proposed phenylacetic acid and dehydrovomifoliol as markers of Polish heather honey, confirmed 4-(1-hydroxy-1-methylethyl)cyclohexane-1,3-dienecarboxylic acid as a marker of lime honey and reported that formic acid and tyrosine as the most common characteristic compounds of buckwheat honey. Using signals of protons and carbon of the methylene group of quercitol in 1H and 13C NMR spectra of honey, Simova et al. [156] identified and discriminated oak honeydew honey from all other honey types of honeydew honeys. Quercitol is considered as a good botanical marker for the genus Quercus which the oak tree belongs. Beretta et al. [157] used 1H NMR profile coupled with electrospray ionisation-mass spectrometry (ESI-MS) and two-dimensional NMR analyses to seek reliable markers of the botanical origin of Italian honeys. Lolli et al. [158] used both 1H NMR and heteronuclear multiple bond correlation spectroscopy (HMBC) to characterise five different floral sources of Italian honey. 1H NMR spectra of chloroform extracts was developed and used to study non-volatile organic honey components for botanical origin characterisation of chestnut, acacia, linden and polyfloral honeys where specific markers were identified for each of the six monofloral Italian honeys [159, 160]. Bertelli et al. [42] investigated adulterated honey falsified by intentional addition of different concentrations of commercial sugar syrups using one-dimensional (1D) and two-dimensional (2D) NMR coupled with multivariate statistical analysis. Ribeiro and co-workers used low field nuclear magnetic resonance spectroscopy (LF 1H NMR) to classify Brazilian honeys into eight different botanical sources [161] and to differentiate honey adulterated by HFCS in different concentrations from 0% (pure honey) to 100% (pure high fructose corn syrup) [162].
\nSpectrum | \nSamples | \nReferences | \n
---|---|---|
\n1 H NMR | \n35 honey samples from multifloral, heather, lime, rape, buckwheat and acacia | \n[3] | \n
180 Corsican honey samples | \n[37] | \n|
57 samples from different countries | \n[153] | \n|
46 honey samples from flowers of citrus, eucalyptus, assa-peixe and wildflowers | \n[154] | \n|
374 samples from Austria, France, Germany, Ireland and Italy | \n[155] | \n|
118 honey samples of 4 different botanical origins: chestnut, acacia, linden and polyfloral | \n[159]*chloroform extracts | \n|
353 honey samples from acacia, chestnut, linden, orange, eucalyptus, honeydew and polyfloral | \n[160]*chloroform extracts | \n|
\n1H NMR and 13C NMR | \n23 samples of polyfloral and 18 samples of acacia honey | \n[152] | \n
24 honey samples of oak and others | \n[156] | \n|
\n1H NMR and 1H-13C HMBC | \n63 authentic and 63 adulterated honey samples | \n[42] | \n
71 honey samples: robinia, chestnut, citrus, eucalyptus and polyfloral | \n[158] | \n|
\n1H NMR-ESI-MS and 1H-13C HMBC | \n44 commercial Italian honeys from 20 different botanical sources | \n[157] | \n
LF1H NMR | \nPure blossom honey samples | \n[162] | \n
80 samples from eucalyptus, orange, Barbados cherry, cashew tree, assa-peixe, assa-lipto and Cipo-Uva | \n[161] | \n
Nuclear magnetic resonance (NMR) techniques in honey authentication.
Additional features of measurements.
Honey contains only about 0.2% protein [163] and it originates from bee and nectar of plants [164, 165]. Honey proteins appear in the form of enzymes, predominantly diastase (amylase), invertase and glucose oxidase. Others, including catalase and acid phosphatase, can also be present, depending on the type of floral source and recently proteolytic enzymes have been described in honey. The major proteins in honey possess different molecular weights depending on its bee species. Thus, protein- and DNA-based honey authentication methods such as the sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE) and real-time PCR are used to identify, authenticate and classify honey samples (Table 7).
\nProtein-based methods | \nSamples | \nReferences | \n
---|---|---|
Western-blot | \nHoneys from Prosopis caldenia, Prosopis sp., Eucalyptus sp., Helianthus annuus, Melilotus albus and Larrea divaricata\n | \n[168] | \n
Honey samples from beekeepers and markets throughout Korea | \n[169] | \n|
RJ proteins from Slovakia | \n[170] | \n|
ELISA | \nRJ protein Apalbumin 1 in honey samples from acacia, linden, rapeseed, dandelion and chestnut | \n[171] | \n
SDS-PAGE | \nNative and foreign bee-honeys | \n[167] | \n
Honeys from Prosopis caldenia, Prosopis sp., Eucalyptus sp., Helianthus annuus, Melilotus albus and Larrea divaricata\n | \n[168] | \n|
Honey samples from beekeepers and markets throughout Korea | \n[169] | \n|
Australian honey samples | \n[166]* high-resolution 2-dimensional electrophoresis | \n|
DNA-based methods | \n||
Manual tracking plant, fungal, and bacterial DNA | \nCommercial, eucalyptus and lemon honeys | \n[174] | \n
Manual, QIAQuick PCR Purification Kit | \nHoneydew honey with multifloral, wild flower and rape honeys, Acacia-with multifloral honey | \n[177] | \n
CTAB | \n1 pine honey, 2 wild honey, 5 polyfloral honey | \n[175]* pollen | \n
3 different apiaries | \n[176] | \n|
Other commercial kits methods besides CTAB | \n||
NucleoSpin Plant, Wizard methods and DNeasy Plant Mini Kit | \n\nCalluna vulgaris, Lavandula spp., Eucalyptus spp. and a multifloral honey | \n[24] | \n
NucleoSpin Isolation Food Kit, Wizard Magnetic DNA Purification and DNeasy Mericon Food Kit | \n14 types of raw honey from Apis dorsata, Apis mellifera, Apis cerana\n | \n[54, 55] | \n
DNeasy Tissue Kit | \nOne regional origin (Pyrenean honey) and one worldwide mix of different honeys (wild flower honey) | \n[172] | \n
Molecular techniques for honey authentication.
Additional features of measurements.
RJ, Royal jelly.
Marshall and Williams [166] used SDS-PAGE, the high-resolution two-dimensional electrophoresis method with methylamine-incorporating silver stain to characterise trace proteins of Australian honeys. Their study revealed that honey protein constituents are predominantly of bee origin. Lee et al. [167] used SDS-PAGE to differentiate native bee-honey (NBH) and foreign bee-honey (FBH) from different molecular weight found in major protein of NBH at 56 kDa and FBH at 59 kDa which were used as protein markers to differentiate NBH and FBH. Baroni et al. [168] reported on the development of a novel method based on honey proteins to determine floral origin of honey samples using SDS-PAGE immunoblot or Western-Blot techniques. The Western-Blot is done to confirm the presence, absence and expression level of a protein of interest using specific antibodies while SDS-PAGE separates protein based on molecular weight. Won et al. [169] distinguished honey produced by two different bee species, Apis mellifera and Apis cerana by the difference in molecular weight of their major proteins (56 and 59 kDa) using SDS–PAGE and later used the purified proteins as antigens for antibody reactions in rats. The Western-blot method verified differences in major proteins’ surface structure thus can be used to differentiate the different honey bee species. Besides honey, royal jelly, another product secreted by honeybee workers as food to be fed to the larvae which will be raised as the potential queen bee, is known to have high protein contents. Simuth et al. [170] reported the presence of royal jelly (RJ) proteins in honey collected from nectars of different plants, origin and regions and in honeybee’s pollen by Western-blot analysis using polyclonal antibodies raised against water-soluble RJ-proteins. They authors suggested that the Apalbumin-1 is a common component of honeybee products and thus is an appropriate marker tool for detecting adulteration of honey by means of immunochemical methods. Bilikova and Simuth [171] developed the 55 kDa major protein of royal jelly, named apalbumin 1 (an authentic protein of honey and pollen pellet), and quantified it by an enzyme-linked immunosorbent assay (ELISA) using specific polyclonal anti-apalbumin 1 antibody.
\nIn recent food authentication methods, DNA-based method is used and regarded as the most reliable, rapid and reproducible technique to detect adulteration and origin of food materials (Table 7). Valentini et al. [172] proposed a new method for investigating plant diversity and geographical origin of honey using a DNA barcoding approach that combines universal primers and massive parallel pyro-sequencing. Laube et al. [173] developed a DNA-based method for characterisation of plant species in honey which further used as geographical origin indication. They identified PCR markers for detection of plant species related to “Miel de Corse”, a protected designation of origin honey and “Miel de Galicia”, a protected geographical indication (PGI) honey as well as German and English honeys. Soares et al. [24] used DNA-based methods to identify botanical species of honey. They used five DNA extraction methods combined with three different sample pre-treatments on four honey samples, three monofloral and one multifloral. The different DNA extraction procedures were compared in terms of DNA integrity, yield, purity and amplification targeting universal and ADH1 specific genes of C. vulgaris where they identified monofloral heather honey successfully. Although these molecular techniques give appreciable results, a prior knowledge about the plant species is required to identify origin of honey samples. Besides detecting plants, Olivieri et al. [174] used DNA-based methods to detect fungi and bacteria in honey due to potential risks evoked by microorganisms, allergens or genetically modified organisms. Guertler et al. [175] developed an automated DNA extraction method from pollen in honey. The authors altered several components and extraction parameters and compared the optimised method with a manual CTAB buffer-based DNA isolation method. The automated DNA extraction was faster and resulted in higher DNA yield and sufficient DNA purity. The results obtained from real-time PCR after automated DNA extraction are also comparable to that of manual DNA extraction procedure. Jain et al. [176] introduced a protocol for DNA extraction from honey using modified CTAB-based protocol. Waiblinger et al. [177] described an in-house and interlaboratory validation of a DNA extraction method from pollen in a unifloral rape honey with several multifloral honeys. While most DNA studies on honey have focused on botanical species identification, Kek et al. [54, 55] have determined the best DNA extraction of bees in honey and introduced entomological identification of honey based on bee mitochondrial 16S rRNA and COI gene sequences.
\n\nTable 8 presents other methods which included instrumental and improvised analytical procedures used for honey identification and authentication. Cordella et al. [178, 179] used differential scanning calorimetry (DSC) to study thermal behaviour of honeys to detect adulterations effects, that is, sugar syrups and classify honeys (Robinia, Lavender, Chestnut and Fir). Hernandez et al. [180] characterised different types of honey produced in the Canary Islands according to their mineral contents using atomic absorption spectrophotometry. Guo et al. [181] used an open-ended coaxial-line technology and a network analyser at 10–4500 MH to detect sucrose–adulterated honey using a sucrose content sensor where permittivity of different adulterated and pure honeys was measured. Pure honey possessed higher dielectric constant when compared with pure sucrose syrup. Roshan et al. [182] used UV spectroscopy together with chemometric techniques to develop a simple model developed to describe authentication of monofloral Yemeni Sidr honey. Tuberoso et al. [183] assessed colour coordinates of 17 unifloral honeys types from different geographic locations in Europe using spectrophotometric method. Wang et al. [184] determined geographical origin of honey based on fingerprinting and barcoding of proteins in honey by using matrix assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI TOF MS). The protein fingerprints were used to differentiate geographical origins of honey samples produced from different countries and various states of the USA, including Hawaii. Dominguez et al. [185] studied geographic origin classification of honey samples from Argentina by a conventional flow-batch system with a simple webcam to capture digital images. In this technique, analytical information is generated from colour histograms obtained from digital images using different colour models such as red–green–blue (RGB), hue–saturation–brightness (HSB) and Grayscale. Gonzalez-Miret et al. [186] analysed mineral content and colour characteristics of 77 honey samples to classify them following botanical origin. de Alda-Garcilope et al. [187] characterised six monofloral honeys and two multifloral Spanish honeys to their protected designation of origin “Miel de Granada” using their metal content. Chen et al. [188] used inductively coupled plasma mass spectrometry (ICP-MS) and chemometrics data of 12 mineral elements to classify Chinese honeys to their botanical origins. Using simple gravimetric method, Felsner et al. [59] characterised monofloral honeys by its ash content, a parameter that has been associated with floral source of honey samples with the hierarchical design. For analysis of honey classification for authentication purposes, data collected needs strong statistical analysis such as multivariate analysis, regression analysis or chemometrics like principal component analysis (PCA) and linear discriminant analysis (LDA). More advanced techniques include the chemical finger printing technique for indicating a unique pattern.
\nTechniques | \nSamples | \nReferences | \n
---|---|---|
Gravimetric method for ash | \n22 eucalyptus and citrus honey samples from Brazil | \n[59] | \n
Differential scanning calorimetry | \n\nLavandula, Robinia and Fir honeys | \n[179] | \n
Atomic absorption spectrophotometry | \n116 samples of monofloral and multifloral honeys | \n[180] | \n
Dielectric properties of honey | \nChinese jujube, yellow locust tree and Chinese milk-vetch | \n[181] | \n
UV spectroscopy | \n38 honey (13 genuine monofloral Sidr honeys (Ziziphus spinachristi), 14 Sidr honeys, 5 polyfloral and 6 non-Sidr honeys) | \n[182] | \n
UV–visible spectrophotometer | \n305 samples from 17 unifloral honey types | \n[183] | \n
Fingerprinting and barcoding of proteins by MALDI TOF MS | \n16 honey samples | \n[184] | \n
Digital image-based flow-batch system | \n210 honey samples from southwest of the province of Buenos Aires and Argentina | \n[185] | \n
Multivariate analysis of colour and mineral composition | \n77 honey samples collected in Spain | \n[186] | \n
Atomic absorption spectrometry | \n6 monofloral honeys and 2 multifloral Spanish honeys | \n[187] | \n
ICP-MS | \n163 honey samples from 4 types of honey: linden, vitex, rape and acacia | \n[188] | \n
Other techniques used in honey authentication.
Determination of honey authenticity by its geographical or botanical origins and its purity is the most important criteria to ensure its safety and quality. The older techniques of melissopalinology, for example, may need to be coupled with newer and more advanced technique to provide higher precision and accuracy of investigation. Strong analytical methods and procedures are necessary for in-depth analysis of data obtained from instrumental measurements for meaningful research in honey authentication. With new knowledge and information of honey origins and authenticity, there rise the need to update current standards of the Codex Alimentarius and the European Union to incorporate newer information and guidelines for standardisation of honey qualities with respect to authenticity. Newer profiles may include components like the aliphatic organic acids, amino acids, volatile components, flavonoids, carbohydrates, phenolic acids and proteins instead of just the sugar profiles. Guidelines towards discrimination botanical and geographical origin may also be implemented. This review provides insights to encourage researchers to further explore novel detection technologies in authentication studies of food materials.
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\\n\\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
\\n\\nA Conflict of Interest can be identified at different phases of the publishing process.
\\n\\nIntechOpen requires:
\\n\\nCONFLICT OF INTEREST - AUTHOR
\\n\\nAll Authors are obliged to declare every existing or potential Conflict of Interest, including financial or personal factors, as well as any relationship which could influence their scientific work. Authors must declare Conflicts of Interest at the time of manuscript submission, although they may exceptionally do so at any point during manuscript review. For jointly prepared manuscripts, the corresponding Author is obliged to declare potential Conflicts of Interest of any other Authors who have contributed to the manuscript.
\\n\\nCONFLICT OF INTEREST – ACADEMIC EDITOR
\\n\\nEditors can also have Conflicts of Interest. Editors are expected to maintain the highest standards of conduct, which are outlined in our Best Practice Guidelines (templates for Best Practice Guidelines). Among other obligations, it is essential that Editors make transparent declarations of any possible Conflicts of Interest that they might have.
\\n\\nAvoidance Measures for Academic Editors of Conflicts of Interest:
\\n\\nFor manuscripts submitted by the Academic Editor (or a scientific advisor), an appropriate person will be appointed to handle and evaluate the manuscript. The appointed handling Editor's identity will not be disclosed to the Author in order to maintain impartiality and anonymity of the review.
\\n\\nIf a manuscript is submitted by an Author who is a member of an Academic Editor's family or is personally or professionally related to the Academic Editor in any way, either as a friend, colleague, student or mentor, the work will be handled by a different Academic Editor who is not in any way connected to the Author.
\\n\\nCONFLICT OF INTEREST - REVIEWER
\\n\\nAll Reviewers are required to declare possible Conflicts of Interest at the beginning of the evaluation process. If a Reviewer feels he or she might have any material, financial or any other conflict of interest with regards to the manuscript being reviewed, he or she is required to declare such concern and, if necessary, request exclusion from any further involvement in the evaluation process. A Reviewer's potential Conflicts of Interest are declared in the review report and presented to the Academic Editor, who then assesses whether or not the declared potential or actual Conflicts of Interest had, or could be perceived to have had, any significant impact on the review itself.
\\n\\nEXAMPLES OF CONFLICTS OF INTEREST:
\\n\\nFINANCIAL AND MATERIAL
\\n\\nNON-FINANCIAL
\\n\\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
\\n\\nAcademic Editors and Reviewers are required to declare any non-financial, financial and material Conflicts of Interest that could influence their fair and balanced evaluation of manuscripts. If such conflict exists with regards to a submitted manuscript, Academic Editors and Reviewers should exclude themselves from handling it.
\\n\\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
\\n\\nEXAMPLES:
\\n\\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\\n\\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\\n\\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\\n\\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\\n\\nPolicy last updated: 2016-06-09
\\n"}]'},components:[{type:"htmlEditorComponent",content:"In each instance of a possible Conflict of Interest, IntechOpen aims to disclose the situation in as transparent a way as possible in order to allow readers to judge whether a particular potential Conflict of Interest has influenced the Work of any individual Author, Editor, or Reviewer. IntechOpen takes all possible Conflicts of Interest into account during the review process and ensures maximum transparency in implementing its policies.
\n\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
\n\nA Conflict of Interest can be identified at different phases of the publishing process.
\n\nIntechOpen requires:
\n\nCONFLICT OF INTEREST - AUTHOR
\n\nAll Authors are obliged to declare every existing or potential Conflict of Interest, including financial or personal factors, as well as any relationship which could influence their scientific work. Authors must declare Conflicts of Interest at the time of manuscript submission, although they may exceptionally do so at any point during manuscript review. For jointly prepared manuscripts, the corresponding Author is obliged to declare potential Conflicts of Interest of any other Authors who have contributed to the manuscript.
\n\nCONFLICT OF INTEREST – ACADEMIC EDITOR
\n\nEditors can also have Conflicts of Interest. Editors are expected to maintain the highest standards of conduct, which are outlined in our Best Practice Guidelines (templates for Best Practice Guidelines). Among other obligations, it is essential that Editors make transparent declarations of any possible Conflicts of Interest that they might have.
\n\nAvoidance Measures for Academic Editors of Conflicts of Interest:
\n\nFor manuscripts submitted by the Academic Editor (or a scientific advisor), an appropriate person will be appointed to handle and evaluate the manuscript. The appointed handling Editor's identity will not be disclosed to the Author in order to maintain impartiality and anonymity of the review.
\n\nIf a manuscript is submitted by an Author who is a member of an Academic Editor's family or is personally or professionally related to the Academic Editor in any way, either as a friend, colleague, student or mentor, the work will be handled by a different Academic Editor who is not in any way connected to the Author.
\n\nCONFLICT OF INTEREST - REVIEWER
\n\nAll Reviewers are required to declare possible Conflicts of Interest at the beginning of the evaluation process. If a Reviewer feels he or she might have any material, financial or any other conflict of interest with regards to the manuscript being reviewed, he or she is required to declare such concern and, if necessary, request exclusion from any further involvement in the evaluation process. A Reviewer's potential Conflicts of Interest are declared in the review report and presented to the Academic Editor, who then assesses whether or not the declared potential or actual Conflicts of Interest had, or could be perceived to have had, any significant impact on the review itself.
\n\nEXAMPLES OF CONFLICTS OF INTEREST:
\n\nFINANCIAL AND MATERIAL
\n\nNON-FINANCIAL
\n\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
\n\nAcademic Editors and Reviewers are required to declare any non-financial, financial and material Conflicts of Interest that could influence their fair and balanced evaluation of manuscripts. If such conflict exists with regards to a submitted manuscript, Academic Editors and Reviewers should exclude themselves from handling it.
\n\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
\n\nEXAMPLES:
\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\n\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\n\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\n\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\n\nPolicy last updated: 2016-06-09
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