G C A T
T A C G
G C A T
genes
Article
Trade in Zambian Edible Orchids—DNA
Barcoding Reveals the Use of Unexpected
Orchid Taxa for Chikanda
Sarina Veldman 1, * , Seol-Jong Kim 1 , Tinde R. van Andel 2 , Maria Bello Font 3 ,
Ruth E. Bone 4 , Benny Bytebier 5 , David Chuba 6 , Barbara Gravendeel 2,7,8 ,
Florent Martos 5,9 , Geophat Mpatwa 10 , Grace Ngugi 5,11 , Royd Vinya 10 ,
Nicholas Wightman 12 , Kazutoma Yokoya 4 and Hugo J. de Boer 1,2
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Department of Organismal Biology, Systematic Biology, Uppsala University, Norbyvägen 18D,
75236 Uppsala, Sweden; seoljong.kim@gmail.com (S.-J.K.); h.d.boer@nhm.uio.no (H.J.d.B.)
Naturalis Biodiversity Center, P.O. Box 9517, 2300 RA Leiden, The Netherlands;
tinde.vanAndel@naturalis.nl (T.R.v.A.); barbara.gravendeel@naturalis.nl (B.G.)
Natural History Museum, University of Oslo, Postboks 1172, Blindern, 0318 Oslo, Norway;
mariabellofont@hotmail.com
Royal Botanic Gardens, Kew, Richmond, Surrey TW9 3AB, UK; R.Bone@kew.org (R.E.B.);
K.Yokoya@kew.org (K.Y.)
Bews Herbarium, School of Life Sciences, University of KwaZulu-Natal, Pr. Bag X01, Scottsville 3209,
South Africa; Bytebier@ukzn.ac.za (B.B.); florentmartos@gmail.com (F.M.); grace.ngugi@yahoo.com (G.N.)
Department of Biological Sciences, University of Zambia, Box 32379 Lusaka, Zambia; david.chuba@unza.zm
Institute of Biology Leiden, Leiden University, P.O. Box 9505, 2300 RA Leiden, The Netherlands
University of Applied Sciences Leiden, Zernikedreef 11, 2333 CK Leiden, The Netherlands
Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d’histoire naturelle, CNRS,
Sorbonne Université, EPHE, CP50, 45 rue Buffon 75005 Paris, France
School of Natural Resources, The Copperbelt University, PO Box 21692 Kitwe, Zambia;
gmpatwa@gmail.com (G.M.); royd.vinya@gmail.com (R.V.)
East African Herbarium, National Museums of Kenya, P.O. Box 40658-00100 Nairobi, Kenya
Homegarden Landscape Consultants Ltd., P/Bag 30C, Chilanga, Lusaka, Zambia;
homegarden.nicholas@gmail.com
Correspondence: sarina.veldman@ebc.uu.se; Tel.: +46-737828087
Received: 24 October 2018; Accepted: 22 November 2018; Published: 30 November 2018
Abstract: In Zambia, wild edible terrestrial orchids are used to produce a local delicacy called chikanda,
which has become increasingly popular throughout the country. Commercialization puts orchid
populations in Zambia and neighbouring countries at risk of overharvesting. Hitherto, no study
has documented which orchid species are traded on local markets, as orchid tubers are difficult to
identify morphologically. In this study, the core land-plant DNA barcoding markers rbcL and matK
were used in combination with nrITS to determine which species were sold in Zambian markets.
Eighty-two interviews were conducted to determine harvesting areas, as well as possible sustainability
concerns. By using nrITS DNA barcoding, a total of 16 orchid species in six different genera could
be identified. Both rbcL and matK proved suitable to identify the tubers up to the genus or family
level. Disa robusta, Platycoryne crocea and Satyrium buchananii were identified most frequently and
three previously undocumented species were encountered on the market. Few orchid species are
currently listed on the global International Union for the Conservation of Nature (IUCN) Red List.
Local orchid populations and endemic species could be at risk of overharvesting due to the intensive
and indiscriminate harvesting of chikanda orchids, and we therefore encourage increased conservation
assessment of terrestrial African orchids.
Genes 2018, 9, 595; doi:10.3390/genes9120595
www.mdpi.com/journal/genes
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Keywords: CITES; chikanda; conservation; DNA barcoding; orchids; species identification
1. Introduction
Terrestrial orchids have been used for medicinal and culinary purposes for centuries [1], with the
most notable example being the use of orchid tubers to make salep, a traditional Turkish creamy
drink or ice cream, consumed in Asia Minor and several countries on the Balkan peninsula [1–4].
In south-eastern Africa, terrestrial orchid tubers are mixed with peanut flour, salt, baking soda and
chili powder to make a traditional Zambian meat-like cake known as chikanda or African polony [5–7].
Although initially not highly regarded [8], chikanda has more recently become popular throughout the
country. It is sold as a snack along the streets, on markets, in supermarkets and on the menu of high-end
restaurants [9] and recipes; in addition, cooking tutorial videos can be found online [10]. Orchids used
for chikanda are harvested exclusively from the wild, and although it is unlikely that traditional village
consumption poses a serious threat to orchid populations, the increased popularity and subsequent
commercialization of chikanda has led to the exhaustion of Zambian orchid resources [7]. Collecting
tubers means the end of a perennial and generally long-lived orchid, since the entire plant is removed
in the harvesting process.
Soweto market in the Zambian capital Lusaka is the hub of the chikanda trade. Surveys performed
on this market have shown that a large part of the chikanda tubers sold are sourced from Tanzania and
that Zambian chikanda orchids are collected from the Luwingu, Mporokoso and Kasama districts in
the Northern Province and Serenje in the Central province [6,7]. According to local chikanda vendors,
another region with a flourishing chikanda trade is the Kitwe region in the Copperbelt Province, but so
far, no surveys have been performed there. Despite international legislation initiated by the Convention
on International Trade in Endangered Species of Wild Fauna and Flora (CITES) banning cross-border
trade, an estimated 2–4 million orchid tubers are transported annually from Tanzania to Zambia [7,11].
Import from the surrounding countries of Angola, Democratic Republic of the Congo (DRC), Malawi
and Mozambique is also documented [7,9]. Orchid species originally reported as ingredients for
chikanda are Disa robusta N.E.Br. and Satyrium buchananii Schltr. [11,12], whereas at least 32 species
belonging to the genera Brachycorythis, Disa, Eulophia, Habenaria, Roeperocharis and Satyrium were
recently suggested to be used for chikanda production based on collections in the field [11,13–18] and
one metabarcoding study of ready-made chikanda cakes [18]. To date, however, no study has identified
the orchids traded at the local markets, since the tubers lack sufficient morphological characters for
taxonomic identification to species level [7,18]. Local classification systems categorize the tubers based
on texture, harvesting locality, soil color and phenology, but these are not likely to be congruent with
scientific classifications [5,14].
Knowing which orchid species are currently being collected for the expanding chikanda trade
enables the identification of species susceptible to overharvesting and can inform conservation
planning. Molecular methods such as DNA barcoding can be applied to identify samples when
morphological diagnostic characters for identification are lacking [19]. DNA barcoding and
metabarcoding has proven to be effective in the authentication of commercial wood species (Jiao, 2018),
medicinal plants [20] and salep-producing orchids on Iranian markets [4]. The analysis of ingredients
in Tanzanian chikanda cake with DNA metabarcoding revealed the presence of 21 different orchid
species [18], but a DNA barcoding approach has not yet been applied to individual orchid tubers used
to make this product. The aim of this study was to test to what extent the use of standard molecular
markers yields robust identification of chikanda orchid tubers traded on Zambian markets. Molecular
identification can enable the mapping of the harvesting and trade of specific Zambian orchid species
and facilitate the identification and implementation of targeted conservation strategies. Within that
framework, this study also aimed to identify conservation issues associated with the chikanda trade,
and addresses the following questions: (1) Which species are used for chikanda production in the
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Lusaka and Kitwe districts of Zambia, and what is their geographic origin? (2) Can chikanda tubers be
identified up to species level using DNA barcoding? (3) How do local classification systems relate to
scientific species concepts? (4) What are the main conservation issues associated with chikanda trade
in the Lusaka and Kitwe districts?
2. Materials and Methods
2.1. Interviews and Sample Collection
Fieldwork in Zambia was conducted in 2016 in the Kitwe, Kalulushi, Luanshya, Ndola, Mufulira,
Chingola and Chililabomwe districts of the Copperbelt Province, the Kapiri Mposhi and Serenje
districts in the Central Province, and in the capital Lusaka (Figure 1). Semi-structured interviews were
conducted with harvesters, middlemen and vendors to obtain insight into chikanda commercialization,
harvesting times, preferences and availability. The questionnaires consisted of three sections, one on
informant and interview characteristics, one with general questions about chikanda posed to all
informants, and a third section with questions more specifically designed for each interviewee category:
harvester, middleman and vendor. All research was conducted in accordance with the International
Society of Ethnobiology Code of Ethics [21]. Ethical clearance was obtained from the Humanities
and Social Science Research Ethics Committee of the University of Zambia. The interviews were
performed in English or Bemba, with a translator affiliated with the University of Zambia and the
Copperbelt University. Informants were selected using the snowball technique [22] by asking
people
Commented
[MX1]: incorrect ref order, 22
whether they could direct us to people harvesting or selling chikanda. All informants wereYou
provided
jumped the numbers in between.
with information about the study and signed a prior informed consent sheet. Fieldwork took place
during June and July, the peak season for chikanda [7], to ensure the collection of both fresh and
dried chikanda tubers on the market and in the field. A collection was made each time a specific
vernacular chikanda type was bought from a specific vendor, and assigned a collection number (SJK1,
SJK2, etc.). Each individual tuber within the collection received a subsample number within that
collection (SJK1.1, SJK1.2, SJK 1.16, etc.). The fresh tubers were sliced and stored with silica gel in
plastic bags. All chikanda samples were brought to Sweden under a CITES inter-institutional exchange
agreement between the University of Zambia (ZM001) and the Botany Section of the Evolutionary
Museum in the Evolutionary Biology Center in Uppsala (SE009). Export permission was obtained
from the Zambian CBD and Nagoya Protocol focal point at the Ministry of Natural Resources and
Environmental Protection. Upon arrival in Sweden, some of the chikanda tubers had sprouted.
Those were transferred to the Uppsala Botanical Garden for cultivation and subsequent sampling of
fresh leaf tissue for DNA barcoding as well as morphological identification.
Figure 1. Map of Zambia with an overview of interview localities and reported provenance of the
chikanda tubers. Dot size corresponds to the number of informants.
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2.2. Reference Taxon Sampling
Herbarium specimens were collected with associated silica-dried material for DNA extraction
and spirit collections during fieldwork in Zambia in January and February 2017. All material was
collected and exchanged in accordance with national and international legislation. The collections
were deposited at the Division of Forest Research (Kitwe, Zambia) and RBG Kew (UK) and field
identifications verified at the Bews Herbarium (South Africa). A total of 94 novel Orchidaceae reference
vouchers were collected for this study, representing 4 Brachycorythis, 9 Disa, 16 Habenaria, 6 Satyrium
species and 26 species of other orchid genera. Voucher specimens of all taxa sampled are listed in
Table S1 (Supplementary Materials). In addition, 88 nrITS, 71 matK and 45 rbcL Habenaria sequences
generated for a forthcoming phylogenetic study [21], and 510 nrITS, 522 matK and 213 rbcL sequences
corresponding to 311, 325 and 100 taxa in the previously mentioned orchid genera downloaded from
GenBank were included in the reference database.
2.3. From Sample to Sequence
Out of the 1284 individual tubers in 48 different sample collections, 304 samples were selected for
DNA extraction. To assess the orchid species present in each collection, a few tubers per sample (2–8)
were extracted if the sample was morphologically homogenous, whereas more (6–33) were selected
if the sample seemed diverse. In the selection process, we aimed to select tubers of different shapes
and sizes to cover the potential species diversity in each collection. Since the selection appeared
to be representative for each collection, it was not deemed necessary to extract DNA from each
individual tuber in all market collections. DNA was extracted using a CTAB protocol [23] modified
with 3 to 5 extra washing steps with STE buffer (0.25 M sucrose, 0.03 M Tris, 0.05 M EDTA) [4,24]
to reduce the gelatinization effect of the large amount of polysaccharides in the starch-rich orchid
tubers. Total DNA was stored in 70–100 µL 10 mM Tris-HCl buffer, pH 8.0. DNA concentration was
measured with a Qubit 3.0 fluorometer (Thermo Fisher Scientific, Oakwood, GA, USA). The core land
plant barcoding markers rbcL and matK were amplified using the primers and protocols described in
Kress et al. [25] and Dunning and Savolainen [23] respectively. The reactions were performed in a total
reaction volume of 25 µL with 14.725 µL ddH2 O, 2.5 µL DreamTaq Buffer (Thermo Fisher Scientific,
Oakwood, GA, USA), 0.5 µL 25 mM dNTP, 0.65 µL 2% bovine serum album (BSA), 0.125 µL DreamTaq
Polymerase, 2.5 µL 5 pmol forward and reverse primer and 1.5 µL template DNA. Nuclear ribosomal
ITS was amplified using the Sun et al. [26] primers and protocol in a total reaction volume of 25 µL
containing 15.25 µL ddH2 O, 2.5 µL DreamTaq Buffer (Thermo Fisher Scientific), 0.5 µL 25 mM dNTP,
0.125 µL 2% BSA, 0.125 µL DreamTaq Polymerase (Thermo Fisher Scientific), 2.5 µL 5 pmol forward
and reverse primer and 1.5 µL template DNA. For ITS, an additional protocol was used with Q5
high-fidelity polymerase; reactions were performed in a total reaction volume of 23.5 µL including
10.875 µL ddH2 O, 5 µL Q5 reaction buffer, 0.5 µL 25 mM dNTP, 5 µL Q5 GC enhancer, 0.125 µL
Q5 high-fidelity polymerase, 1.5 µL 5 pmol forward and reverse primer and 0.5 µL template DNA.
The PCR program for the ITS primers in combination with the Q5 polymerase was an initial heating
step of 30s at 98 ◦ C, 35 cycles of 10s 98 ◦ C, 30s 56 ◦ C, 30s 72 ◦ C, and a final elongation of 2min at 72 ◦ C.
PCR products were cleaned using eight-times diluted ExoSAP (Thermo Fisher Scientific) and analysed
on an ABI3730XL Sanger sequencer by Macrogen Europe (Amsterdam, The Netherlands). The obtained
trace files were assembled using Pregap4 and Gap4 [27] as implemented in the Staden package [28].
Sequences shorter than 200 bp were discarded from the analysis and all sequences were deposited
in NCBI GenBank (Table S2, Supplementary Materials). The NCBI BLAST algorithm was used to
assess the identification of all the obtained query sequences using the Python BLAST tabular parser
script (https://github.com/SLAment/Genomics/blob/master/BLAST/BLAST_tabularparser.py).
Similarity scores, query coverage, expect value (E-value), and maximum identity percentage were
calculated, and all the information of the top 5 hits were automatically mined and tabulated per marker
(Tables S3–S5, Supplementary Materials) and summarized per individual tuber sample (Table S6,
Supplementary Materials).
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2.4. Phylogenetic Analysis and Species Identification
Alignments for nrITS, matK and rbcL were made using AliView [29], combing the query sequences
and local reference databases consisting of sequences from NCBI GenBank and reference collections
from fieldwork and unpublished data from collaborators [21]. Species identification was performed
using the Bayesian implementation of the Poisson tree processes model (bPTP), as it has been shown
to outperform the generalized mixed Yule coalescent (GMYC) approach as well as Operational
Taxonomic Unit (OTU)-picking methods when evolutionary distances between species are short
enough [30]. For all alignments, a maximum likelihood (ML) search for the best-scoring tree was
performed using the RAxML web server [31] to generate input trees for species identification analysis
using bPTP [30]. The default setting, GTRCATI, was used to implement the CAT approximation,
and the final tree was evaluated using the traditional GTR model. The bPTP.py script setting was
100,000 Markov chain Monte Carlo (MCMC) iterations for all trees, a sampling interval thinning value
of 100, a burn-in of 25%, and a random seed of 1234. No outgroup was defined. The generated
convergence curve was visually confirmed. The description of each voucher is built up as follows:
‘sample #_BLAST search result_identification %_reported city/region of the origin_the country,’;
for example: ‘SJK04.09_S.buchananii_97.893_Mwinilunga_Zambia’ (Figures S1–S3, Supplementary
Materials). For the reference sequences, the accession number and species names are described for
Disa and Satyrium. The reference Habenaria species and others are described as their species name and
voucher (sample) number.
3. Results
3.1. Market Surveys and Interviews
We visited 25 markets in ten Zambian cities: seven cities in the Copperbelt Province, two in
the Central Province, and one in Lusaka (Figure 1). Eighty-two persons involved in chikanda trade
were interviewed, of which 8 were harvesters, 44 middlemen, 29 vendors and one informant was
both harvester and middleman. The term ‘harvesters’ refers to people collecting chikanda in the field,
‘middlemen’ to people selling either dried or fresh chikanda orchid tubers on the market, and ‘vendors’
to informal street vendors selling ready-made chikanda cakes contained in a basket carried on the
head. Since one of the harvesters also acted as middleman, in total, 83 individual interviews were
conducted: 72 participants were female and 10 were male. The ages of the respondents varied between
18 and 78, with an average of 41 years. The majority of the respondents belonged to the Bemba tribe
(62%), while the other respondents (38%) belonged to smaller ethnic groups. Most interviews were
conducted in the Copperbelt Province (55), eight in the Central Province and 19 in Lusaka.
3.2. Local Classification System
Fifty-three different vernacular names for the various chikanda tuber types were recorded during
the interviews. The most common way to distinguish between chikanda tubers was by using the
terms original (myala) and fake (mbwelenge or msekelele). In some cases, it was the shape of the tuber
that was used to differentiate between the different tubers: mshilamshila means root-like in Bemba
and referred to the elongated, root-shaped tubers, whereas mampanda referred to the heart-shaped
tubers. It also appeared common to use the origin of the tuber as a trade name: mwinilunga, chozi,
luwingu and kasama are, for example, all Zambian city names, sumbawanga and iringe refer to Tanzanian
cities (Sumbawanga and Iringa) and angola refers to one of the countries bordering Zambia. In some
cases, the chikanda tubers were sold pre-mixed, whereas other vendors marketed the different types of
tubers separately. The morphology and size of the tubers varied both within and between collections
of a certain chikanda type. Tubers could be heart-shaped, rounded, egg-shaped to elongated and
almost root-like. The largest tubers were the heart-shaped ones, which could be up to 5 cm long and
6 cm wide. The elongated tubers were up to 9 cm long with a maximum width of 2 cm. Harvesters,
middlemen and vendors themselves indicated that they distinguish the tubers based on the size of
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the granules inside the tubers, which can be large or small, and in some tubers, a concentric ring was
said to be present. Figure 2 illustrates the different tuber types and ready-made chikanda that were
encountered on the local markets, as well as some of the orchid species producing these tubers.
Figure 2. Chikanda tubers, cake and orchids. (a) Myala—real chikanda; (b) Mbwelenge—fake chikanda;
(c) Mshilamshila—supposedly Brachycorythis sp.; (d) Mampanda. (e–g); Chikanda cake; (h) Disa
robusta; (i) Disa welwitschii; (j) Platycoryne crocea; (k) Satyrium carsonii; (l) Satyrium buchananii; (m)
Satyrium kitimboense; (n) Brachycorythis cf. friesii; Photographs (a–g) by Seol-Jong Kim, (h) by Robert v.
Blittersdorff, (i,k,l) by Nicholas Wightman, (j) by Warren McCleland, (m) by Ruth E. Bone and (n) by
Sarina Veldman.
3.3. Chikanda Trade and Availability
Many participants had a relatively long experience (an average of 13.5 years) in the chikanda trade.
They indicated that they were asked by family, friends or neighbors to get involved in the chikanda
business, or simply because it seemed to be a profitable industry. Some of the participants, especially
harvesters, stated that they started collecting chikanda because the plants were easily accessible and
were found growing close to their areas of residence. In general, people involved in the chikanda
trade indicated that this work alone did not suffice to fully support themselves and their families,
and these traders therefore supplemented their income by trading additional natural products such
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as fruits, maize, groundnuts, beans, mushrooms, snacks, herbs, and kapenta (a dried fish from Lake
Tanganyika). In Lusaka, however, income generated with chikanda trade seemed to be sufficient for
subsistence, and this suggests that there are significant local differences in profits generated in the
chikanda business.
The chikanda trade was structured in several different ways. Some of the middlemen loaded
the orchid tubers in trucks directly from the harvesting areas and brought them to larger cities such
as Lusaka and Kitwe, whereas others relied on agents to gather a specified amount of chikanda
tubers, which they paid for through the East-African mobile payment system M-Pesa and received
as cargo from one of the local buses. In addition to the Tunduma and Nakonde markets that are
the trade hubs between Tanzania and Zambia, other centers of trade were identified on the border
with the DRC (Chililabombwe and Kasumbalesa) and Angola (Mwinilunga), where both chikanda
tubers and ready-made chikanda cake were sold. An overview of all interview localities and the
reported provenance of the chikanda tubers is given in Figure 1. Most of the participants indicated that
chikanda plants are becoming locally rare. Middlemen emphasized the decrease of quantity, whereas
harvesters were concerned about the decline in both quantity and quality (size and preferred chikanda
type), which may also depend on the species. The participants from urban areas stated that access to
chikanda tubers was managed by the chief of each tribe, who seasonally designated the harvestable
dambo (wet meadow) within the chiefdom so that the collectors could maintain the quality of the
harvests. Nevertheless, interviewed harvesters found in the dambo areas of Serenje (Central Province)
claimed to be free to harvest tubers whenever available.
3.4. Molecular Identification of Traded Orchids
During the DNA extraction, many samples formed a thick jelly-like layer in the extraction tubes,
despite repeated washing steps with STE buffer. This resulted in a very small water phase and is
likely to have negatively influenced the downstream steps of the extraction process. The average DNA
concentration of the chikanda tuber samples was 4.96 ng/µL, while the average DNA concentration
from leaf samples from chikanda orchids was 28.5 ng/µL. Out of the 304 samples selected for DNA
extraction, 232 samples produced detectable DNA. Amplification was attempted for each barcoding
marker for all of the samples. A nrITS sequence was obtained for 159 samples, rbcL for 117 samples and
matK only for 45 samples. Sequences from all three markers were obtained for 40 samples, sequences
from two markers for 58 samples, and 55 samples only yielded sequences for a single marker. Analysis
of the inter- and intraspecific variation of nrITS was performed for 141 sequences representing 124 Disa
species, 73 sequences representing 59 Habenaria species and 110 sequences representing 67 Satyrium
species. In the case of matK 135 sequences belonging to 122 Disa species were included, 507 Habenaria
sequences belonging to 239 species and 116 sequences belonging to 60 Satyrium species. For rbcL,
the available reference material was quite limited: 45 sequences for 37 Habenaria species, eight Satyrium
sequences for two species, and four Disa sequences for four species.
A graphical overview of the inter- and intraspecific variation per genus and per marker can be
found in Figure 3. The interspecific variation for nrITS was significantly higher as compared with
matK and rbcL in all three genera: on average, 10.2% in Disa, 9.51% in Satyrium and 8.75% in Habenaria.
For matK, the interspecific variation was 2.39% for Disa, 2.79% for Habenaria and 1.39% for Satyrium.
The intraspecific distances for nrITS and matK were, respectively, 1.37% and 0.61% for Disa, 1.98%
and 0.36% for Habenaria and 1.45% and 0.48% for Satyrium, The limited reference sequences that were
available for rbcL showed little pairwise interspecific distances (1.44% for Disa, 0.82% for Habenaria
and 1.13% for Satyrium) and only allowed for the intraspecifc distance calculation of Habenaria (0.38%),
indicating that rbcL is not suitable as a barcode for the species-level identification of chikanda orchids.
The calculated thresholds were subsequently used to evaluate the identifications made with the online
and standalone Basic Local Alignment Search Tool (BLAST).
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Figure 3. Boxplots showing the inter- and intraspecific variation for Disa (a), Habenaria (b) and Satyrium
(c) based on genetic diversity.
In total, 15 orchid species were identified using DNA barcoding: Brachycorythis sp. SJK7, Disa
caffra Bolus, D. celata Summerh., D. robusta N.E.Br., D. satyriopsis Kraenzl., D. welwitschii Rchb. f.,
Disa sp. SJK4.1., Habenaria sp. SJK31.15, H. aff. helicoplectrum Summerh., Habenaria cf. sp. DO112,
Platycoryne crocea Rolfe, Satyrium buchananii Schltr., S. carsonii Rolfe, and S. kitimboense Kraenzl., as well
as one species in an unidentified genus, which seems to be closely related to Habenaria based on the
similarity-based BLAST identification. Additionally, one orchid that flowered from a sprouting tuber
was identified based on morphology as Brachycorythis cf. friesii (Schltr.) Summerh.
bPTP analysis for matK and rbcL showed a lumping of several supposedly different species
within one clade on several occasions (Figures S1 and S2, Supplementary Materials). In the case
of nrITS, the bPTP outcome tree often reflected the expected species boundaries, although the
posterior probabilities on the nodes were often too low to determine with confidence if species
identification had been performed correctly (Figure S3, Supplementary Materials). Something that
could be observed from both the nrITS BLAST identification, as well as the bPTP analysis, was that
some of the identifications showed ambiguity: in collection SJK41, SJK44 and SJK46, some samples
were identified unambiguously as Platycoryne crocea, whereas others showed a mix of Habenaria and
Platycoryne top hits. The matK BLAST identification showed an unambiguous P. crocea identification
for these samples, despite the presence of several Habenaria species in the reference database and
despite the fact that matK shows a lower level of interspecific variation. A similar observation could
be made for several Disa samples, but here a geographic pattern could be observed. The samples
that could unambiguously be identified as D. robusta were all collected from Tanzania, the original
source of the reference sequence. Some of the Zambian samples also showed D. robusta as the closest
relative, but not with a high enough percentage identity match to confirm this identification. The
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bPTP result in this case shows a lumped and mixed clade with several Disa species and several other
samples included, which confirms that sequence divergence is too limited to resolve the relationship.
These samples were identified as Disa sp. 1, to reflect the fact that they all grouped together in
the same clade. In other cases, such as for certain Habenaria species, we named the closely related
sequences in the identification, whereas in this case the clade was too large to allow for this, since it
contained the following sequences: Disa engleriana Kraenzl., D. erubescens Rendle., D. miniata Summerh.,
D. ochrostachya Rchb.f., D. satyriopsis, D. ukingensis Schltr., D. verdickii De Wild., D. welwitschii, D. zombica
N.E.Br., an unidentified Disa species and several samples that showed a highest percentage identity
match with D. robusta, D. satyriopsis and D. welwitschii. The posterior probability for this clade is only
0.25, and combined with the posterior probabilities present on the within-species nodes, indicates a lot
of uncertainty for this identification.
Overall, the most frequently encountered species were Satyrium buchananii, with 41 samples in
eleven different collections, Platycoryne crocea, with 19 samples in three different collections, and Disa
robusta, with 4–16 samples in two to seven different collections. Myala or original chikanda seems to
contain D. robusta, D. welwitschii and S. buchananii. Mbwelenge or fake chikanda seems to correspond
only to S. buchananii and mshilamshila to one or several Brachycorythis species. Kasebelele and kapapa
referred to Habenaria spp., P. crocea, S. carsonii and S. kitimboense. The mixed collections contained all of
the above-mentioned species as well as an unidentified Habenaria species. An overview of the local
chikanda classification types, their collection numbers, identifications and number of samples can be
found in Table 1.
Table 1. Overview of the different local chikanda classification types, their collections and the identified
scientific species.
Vernacular Name
Reported Origin
Barcoding IDs
# Samples
Fungulwe
SJK16
unknown
Iringe
SJK17
Tanzania
John White
SJK39
Mporokoso, Zambia
1
1
1
1
Kabula seke
SJK46
Serenje, Zambia
Kapapa
SJK44
Mporokoso, Zambia
Kasebelela, John White and
Myala
SJK41
Chinsali and Mporokoso, Zambia
and Tanzania
Kasebulela and Kapapa
SJK11
Luwingu, Zambia
Disa robusta
Satyrium buchananii
Satyrium carsonii
Satyrium buchananii
Habenaria sp. (Clade H. schimperiana, H. kyimbilae,
H. microsaccos
Platycoryne crocea
Platycoryne crocea
Habenaria cf sp. DO122 (Clade H. schimperiana,
H. kyimbilae, H. microsaccos
Platycoryne crocea
Platycoryne sp./Habenaria sp.
Satyrium kitimboense
Satyrium carsonii
Satyrium buchananii
Satyrium sp.
Satyrium buchananii
Brachycorythis sp.
Brachycorythis sp.
Brachycorythis cf. friesii
Disa robusta
Disa welwitschii
Satyrium buchananii
Disa robusta
Satyrium buchananii
Satyrium buchananii
Disa welwitschii
Satyrium buchananii
Disa robusta
Disa satyriopsis
Disa caffra
Disa robusta
Habenaria cf sp. DO122 (Clade H. schimperiana,
H. kyimbilae, H. microsaccos
Satyrium buchananii
Satyrium carsonii
Habenaria aff. helicoplectrum (BB3151)
Disa miniata
Disa robusta
Disa welwitschii
Satyrium buchananii
Satyrium carsonii
Disa celata
Disa welwitschii
Satyrium buchananii
Mbwelenge
Mshilamshila
Myala
Collections
SJK5
Luwingu, Zambia
SJK32
SJK7
Serenje, Zambia
Luwingu, Zambia
SJK12
Kawamba, Zambia
SJK4
Mwinilunga, Zambia;
SJK18
Sumbawanga, Tanzania
Myala
SJK37
Kawambwa, Zambia
Myala and nampanda
SJK21
Luapula, Zambia
Ntonkonshi
Sumbawanga
SJK25
SJK20
Democratic Republic of Congo
Sumbawanga, Tanzania
Mixed
SJK31
Serenje, Zambia
Unknown-mixed
SJK19
Luwingu, Zambia
SJK8
Mwinilunga, Zambia
SJK9
Luwingu, Zambia
SJK13
Kawamba, Zambia
Unknown
1
7
6
4
4
2
6
5
11
1
6
1
1
1
4
1
4
4
1
1
2
1
1
1
1
1
1
6
1
1
1
2
1
2
1
1
1
3
Genes 2018, 9, 595
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4. Discussion
4.1. Species Used for Chikanda
Using DNA barcoding as an identification tool for chikanda tubers sold on local Zambian
markets has allowed us to determine for the first time which orchid species are sold on local
markets. Previous studies identifying orchids used for chikanda relied on voucher collections made
with collectors in the field and their morphological identification, which requires a qualified orchid
taxonomist [6,11,13,16,17]. Additionally, relying on local harvesters for details on chikanda collection
might not always lead to collection in the areas where actual intensive harvesting is taking place,
since some harvesters do not like to divulge where the best places to harvest are, and in some initial
harvesting areas, such as the Kitulo Plateau in Tanzania’s Southern Highlands, collection is now
prohibited [32]. The current study identified 16 orchid species present on the markets, including
at least three previously undocumented ones: Brachycorythis cf. friesii, Platycoryne crocea and an
unidentified species in a genus, which appears to be closely related to Habenaria, but is not present in
our reference database.
Orchids used for chikanda seem to be harvested from several provinces in Zambia, as well as
at least two regions in Tanzania. Moreover, three international chikanda trade hubs in towns on
or close to the border with the DRC (Chililabombwe and Kasumbalesa) and Angola (Mwinilunga)
were identified, in addition to the already known trade hub Tunduma-Nakonde on the Tanzanian
border [7,11]. However, unlike what has been reported in other studies, no harvest from Malawi was
mentioned by the people interviewed in this study, which could mean that trade from this country
is currently not taking place. Another explanation is that this information is lost en route and that
only Tanzania, being geographically closer and thus more easily accessible for the Bemba people,
is mentioned as a region of origin for chikanda traded in Zambia.
4.2. DNA Barcoding Performance
Since the term DNA barcoding was coined in 2003 [19], a plethora of studies applying DNA
(meta)barcoding has been performed ranging from retrieving orchids from paleoenvironments [33],
preserved in mammoth dung [34], to the identification of Iranian orchid tubers used for salep [4]. In this
study, a combined use of the core plant markers matK and rbcL and the nuclear ribosomal ITS region
was used to attempt the species-level identification of tubers traded on Zambian markets. Although
genetic distance calculations showed limited interspecific distances between closely related species
for all three barcoding markers, DNA barcoding allowed for species-level identification for several
of the frequently sold chikanda species. The data shows that the core land-plant DNA barcoding
markers rbcL and matK were not suitable because of the limited variability between species (matK and
rbcL), amplification problems (matK), and/or a limited sequence reference database (rbcL). Similar
performance has been reported in other barcoding studies and indicates that the use of these core
land plant markers might not be suitable for the analysis of samples with degraded DNA and for the
identification of closely related species [35–37]. nrITS was shown to be more suitable as a barcode
marker to distinguish between different chikanda species, but is not discriminative enough to enable
reliable species level identification in certain orchid clades, such as the clade with Platycoryne crocea,
P. buchananiana and Habenaria buchananii; the clade with H. schimperiana, H. kyimbilae and H. microsaccos
and the clade containing Disa sp. 1. Another drawback of nrITS is the presence of multiple ITS
paralogs in the ribosomal genome. Usually, these copies would show high similarities due to concerted
evolution [38,39], but this is not always the case [40–43]. In our case, potentially different nrITS
ribotypes became fixed in different orchid populations, and having only one of them in our reference
database could lead to the unresolved identifications observed. Our bPTP results show that even
nrITS has too low a resolution to reliably identify species with high posterior probability support
using this method. It does demonstrate, however, how valuable the use of tree-based methods can
be, since it shows the relations between the sequences and can be used to determine if some of the
Genes 2018, 9, 595
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unidentified samples are likely to belong to the same species or a different species within the same
genus. Even if no species-level identification can be made for these samples, it is possible to use
the clustering to determine the diversity of species used. Although several samples can only be
reliably identified as Habenaria sp., we find that they are likely to belong to at least three different
species (Habenaria aff. helicoplectrum, Habenaria cf. sp. DO122 in the clade with H. schimperiana,
H. kyimbilae and H. microsaccos and lastly the Platycoryne sp./Habenaria sp., which group together
with H. buchananii, P. buchananiana and P. crocea. Expansion of the reference database, by including
at least one individual per species, and preferably multiple individuals per species from different
populations and countries, could ultimately solve the remaining challenges, and this seems the way
forward for the identification of the traded chikanda tubers, as well as other species unidentifiable
by morphology. Similar studies using DNA barcoding for the identification of unknown samples
show comparable results for the employed barcoding markers. In a study on the identification of
orchids used for salep, nrITS showed a sequencing success more than three times higher than matK
as well as a two-fold higher species-level identification success [4]. Moreover, the similarity-based
approach seemed to outperform the tree-based identification method (ML) in this study as well with
57% and 39% species-level identifications, respectively. nrITS also shows the highest identification
performance in studies on the identification of medicinal plants [44,45], which supports the idea that
it is advisable to add a more discriminative marker to the two core land-plant barcodes in studies
where it is needed to distinguish between closely-related species. Moreover, our results stress the need
for a phylogenetically underpinned taxonomic framework, which is currently available for Disa [46]
and Satyrium [47], but not yet for Habenaria and related genera. A remaining limitation is the limited
DNA extraction and amplification result, which could potentially be improved by experimenting with
different extraction methods and primer pairs that would allow the amplification of segments of the
matK marker [48–50].
4.3. Local Versus Scientific Classification of Chikanda
The results of our identifications of chikanda orchids traded in Zambia show that the local
classification systems for chikanda are not congruent with the botanical classification of orchid
species. The orchids sold on the markets were grouped according to area of origin, tuber consistency
preference, or shape of the tuber, but often the tubers offered for sale were mixtures. The different
local types of chikanda sometimes show a variation in orchid species that are identified within these
local groupings. When we look at the chikanda type known as kapapa, for example, SJK44 contains
Platycoryne crocea, whereas SJK11, which is supposed to be a mix of kasebelela and kapapa, only seems to
contain Satyrium species. In the case of other chikanda types, there seems to be more consistency: myala
or real chikanda referred to Disa robusta, D. welwitschii and S. buchananii, mshilamshila samples were
identified as Brachycorythis species and mbwelenge or fake chikanda was made of S. buchananii. However,
our previous study on the analysis of Tanzanian chikanda cakes showed that the cake made with fake
chikanda tubers also contained Disa miniata, Satyrium anomalum, S. comptum, S. elongatum, S. riparium, S.
shirense and S. volkensii, indicating that there might be some differences between fake chikanda samples
as well [18]. It is well known in the literature that local species concepts are not necessarily congruent
with scientific classifications and that species might be subject to over- or under-differentiation [51,52].
In this case, the grouping of the orchids according to the area of origin, shape or consistency preference
or plainly under the general term chikanda is clearly a case of under-differentiation, as a much higher
diversity was retrieved when employing DNA barcoding. In order to more reliably identify the orchid
species used for a particular chikanda type, more samples per local classification need to be analyzed.
4.4. Orchid Availability and Conservation
In recent decades, chikanda has made a remarkable leap in popularity. The first record of chikanda
use made by Audrey Richards [8] described the relish as a poor man’s food, eaten in times of famine.
Recent studies, from 2002 onwards, show that chikanda has emerged as a Zambian snack which
Genes 2018, 9, 595
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is popular throughout the country. Studies on chikanda report that, with this rise in popularity,
the orchid harvest has escalated and is pressuring local Zambian orchid populations as well as those in
neighboring countries [7,9,11,53]. Many people involved in the chikanda trade indicated that chikanda
plants were becoming scarce, and many were concerned about both the quality as well as the quantity of
the orchids available. Our study also confirmed a significant international trade network for chikanda
sources in several regions in Tanzania, as well as in the Democratic Republic of Congo and Angola.
In our current study, we found at least 16 different orchid species sold as chikanda on the Zambian
markets and an overview of previous studies contains 46 species reported to be used for chikanda
(Table S7). This brings us from the use of an initial two orchid species reported for chikanda [12] to a
total of 49 species in eight different genera. The increased harvesting pressure, in combination with
the indiscriminate harvesting and use of many more species than earlier assumed, poses a threat to
nearly half of the terrestrial orchids occurring in these regions. Despite the establishment of Kitulo
National Park in Tanzania, with orchid conservation as a prime concern, it seems that harvesting
continues even there, since iringe tubers found in this study come specifically from this region [6,11].
Currently, there are only seven Disa species from Zambia and surrounding countries registered on the
global IUCN Red List and no species from other genera used for chikanda [54]. Most of the orchid
species used for chikanda seem to have a widespread distribution, but local populations as well as
endemic species could be at risk of overharvesting, and we urge the addition of the most frequently
traded chikanda species, such as Disa robusta and Satyrium buchananii, to the IUCN Red List. Although
no reduction in commerce is evident, the people involved in the chikanda trade seem genuinely
concerned about the welfare of local orchids and to be interested in exploring other options. Since
the chikanda harvesters especially seem to be in a vulnerable position, where they have to rely on
surrounding natural resources to secure their livelihoods [15], it is essential that, when trying to protect
orchids used for chikanda, the situation of the people dependent on the trade be taken into account as
well. Currently, the development of sustainable cultivation of chikanda orchids is being attempted
in collaboration with the Cape Institute of Micropropagation (Barrydale, South Africa), and possible
alternative sources of income for the people involved in chikanda trade, such as honey production,
are being explored [55]. Alternatively, since the purpose of the chikanda orchids is mainly to bind
and create an elastic structure for the cake, it might be possible to encourage the use of an alternative
source of starch to replace the tubers.
5. Conclusions
DNA barcoding using the nuclear ribosomal ITS marker proved to be useful in identifying
terrestrial orchid species traded as chikanda on local Zambian markets and outperformed identification
using the core land-plant barcoding markers matK and rbcL. Sixteen orchid species, including three
previously undocumented ones, were identified from marketed chikanda tubers, bringing the total
number of orchid species used for chikanda to at least 49. The species most frequently found on
the markets were Disa robusta, Satyrium buchananii and Platycoryne crocea. However, the results are
only as good at the reference material, and an expanded reference database in combination with
an underpinned phylogenetic framework for Habenaria and related genera would likely improve
the reliability of the identifications. Tubers are harvested from various regions in Zambia and
Tanzania, and additional international chikanda trade hubs have been identified on the border with the
Democratic Republic of Congo and Angola. People involved in the chikanda trade indicate that both
orchid quality and quantity are decreasing and are willing to consider alternatives to the chikanda
trade to secure their income.
Supplementary Materials: The following supplementary figures and tables are available online at http://www.
mdpi.com/2073-4425/9/12/595/s1, Figure S1. bPTP analysis of all chikanda matK query and reference samples;
query samples identifiers are the collection number and the BLAST identification; reference samples from GenBank
have their 2-letter, 6-numeral accession numbers as identifier; other reference samples have their collection number
and identification based on morphology as identifier. Figure S2. bPTP analysis of all chikanda rbcL query and
reference samples; query samples identifiers are the collection number and the BLAST identification; reference
Genes 2018, 9, 595
13 of 15
samples from GenBank have their 2-letter, 6-numeral accession numbers as identifier; other reference samples
have their collection number and identification based on morphology as identifier. Figure S3. bPTP analysis
of all chikanda nrITS query and reference samples; query samples identifiers are the collection number and
the BLAST identification; reference samples from GenBank have their 2-letter, 6-numeral accession numbers
as identifier; other reference samples have their collection number and identification based on morphology as
identifier. Table S1. Brahms RDE file of novel voucher specimens of orchid taxa samples in this study; for a
thorough explanation of the column headers we refer to the online support material of the BRAHMS project [56].
Table S2. Genbank accession numbers of the chikanda tuber sequences. Table S3. Hit table with the first 5 BLAST
top hits per sample for nrITS. Table S4. Hit table with the first 5 BLAST top hits per sample for matK. Table S5. Hit
table with the first 5 BLAST top hits per sample for rbcL. Table S6. Successfully sequenced samples with their
vernacular name, reported origin, identification based on sequence-similarity for nrITS and matK, identification
based on the tree-based bPTP analysis and the consensus ID. Table S7. Orchid species used for chikanda according
to literature.
Author Contributions: S.V., R.B. and H.d.B. conceived and designed the study in collaboration with S.J.K., D.C.,
R.V. and N.W.; S.J.K. performed the chikanda collection and interviews in collaboration with D.C., G.M., N.W.
and R.V; R.B., N.W. and K.Y. collected reference vouchers in the field, which were identified in collaboration
with B.B.; B.B, G.N and F.M. provided the reference sequence database for Habenaria species and some species
in closely related genera; S.J.K. performed the labwork for the chikanda collections and M.B.F. for the reference
collections; S.J.K. performed the data analysis under supervision of S.V. and H.d.B.; S.V. and S.J.K. wrote the
manuscript in consultation with the other authors and the manuscript was edited and reviewed in detail by B.G.,
T.v.A. and H.d.B.
Funding: This research was funded by the Darwin Initiative (UK Government) Grant No. 23034 and Netherlands
Organisation for Scientific Research (NWO) TASENE grant W 02.29.102 and Swedish Research Council grants
VR-SRL D0664801 and VR-UF E0347601.
Acknowledgments: The authors would like to thank the participants in the study for sharing their knowledge
and Simon Hultby from the Uppsala Botanical Garden for growing the sprouted chikanda orchid tubers.
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Kasparek, M.; Grimm, U. European trade in Turkish Salep with special reference to Germany. Econ. Bot.
1999, 53, 396–406. [CrossRef]
Ece Tamer, C.; Karaman, B.; Utku Copur, O. A traditional Turkish beverage: Salep. Food Rev. Int. 2006, 22,
43–50. [CrossRef]
Kreziou, A.; de Boer, H.; Gravendeel, B. Harvesting of salep orchids in north-western Greece continues to
threaten natural populations. Oryx 2015, 1–4. [CrossRef]
Ghorbani, A.; Gravendeel, B.; Selliah, S.; Zarré, S.; Boer, H. DNA barcoding of tuberous Orchidoideae: a
resource for identification of orchids used in Salep. Mol. Ecol. Resour. 2017, 17, 342–352. [CrossRef] [PubMed]
Davenport, T.R.B.; Ndangalasi, H.J. Orchid Harvest—An Assessment of the Harvesting and Trade of Orchid Tubers
Across Tanzania’S Southern Highlands; Wildlife Conservation Society: New York, NY, USA, 2001; p. 23.
Bingham, M.G. Chikanda trade in Zambia. Orchid Conserv. News 2004, 4, 22–25.
Veldman, S.; Otieno, J.N.; van Andel, T.; Gravendeel, B.; de Boer, H.J. Efforts urged to tackle thriving illegal
orchid trade in Tanzania and Zambia for chikanda production. TRAFFIC Bull. 2014, 26, 47–50.
Richards, A.I. Land, Labour and Diet in Northern Rhodesia: An Economic Study of the Bemba Tribe; Oxford
University Press: Oxford, UK, 1939.
Bingham, M.G. Chikanda an unsustainable industry. The Lowdown Magazine. 2007, 4.
Temzie Bites Zambian Food|Chikanda African Ham (Polony) Recipe. 2017. Available online: https:
//www.youtube.com/watch?v=mDGKx-GOLoA (accessed on 24 October 2018).
Davenport, T.R.B.; Ndangalasi, H.J. An escalating trade in orchid tubers across Tanzania’s Southern
Highlands: assessment, dynamics and conservation implications. Oryx 2003, 37, 55–61. [CrossRef]
Cribb, P.J.; Leedal, G.P. The mountain Flowers of Southern Tanzania: A Field Guide to the Common Flowers;
AA Balkema: Rotterdam, NL, USA, 1982.
Nyomora, A.M.S. Distribution and abundance of the edible orchids of the Southern Highlands of Tanzania.
Tanzanian J. Sci. 2005, 31, 45–54. [CrossRef]
Genes 2018, 9, 595
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
14 of 15
Mapunda, L.N.D. Edible Orchids in Makete District, the Southern Highlands of Tanzania: Distribution,
Population and Status. Master’s Thesis, Swedish Biodiversity Centre, Uppsala Universitet (Sweden),
Uppsala, Sweden, 2007.
Challe, J.F.; Price, L.L. Endangered edible orchids and vulnerable gatherers in the context of HIV/AIDS in
the Southern Highlands of Tanzania. J. Ethnobiol. Ethnomedicine 2009, 5, 41. [CrossRef] [PubMed]
Kasulo, V.; Mwabumba, L.; Munthali, C. A review of edible orchids in Malawi. J. Hortic. For. 2009, 1, 133–139.
Hamisy, C.W. Development of conservation strategies for the wild edible orchid in Tanzania. Prog. Rep.
Rufford Small Grants Found. 2010.
Veldman, S.; Gravendeel, B.; Otieno, J.N.; Lammers, Y.; Duijm, E.; Nieman, A.; Bytebier, B.; Ngugi, G.;
Martos, F.; van Andel, T.R.; et al. High-throughput sequencing of African chikanda cake highlights
conservation challenges in orchids. Biodivers. Conserv. 2017, 1–18. [CrossRef]
Hebert, P.D.N.; Cywinska, A.; Ball, S.; de Waard, J. Biological identifications through DNA barcodes. Proc. R.
Soc. B 2003, 270, 313–322. [CrossRef] [PubMed]
Raclariu, A.C.; Heinrich, M.; Ichim, M.C.; Boer, H. Benefits and limitations of DNA barcoding and
metabarcoding in herbal product authentication. Phytochem. Anal. 2017. [CrossRef] [PubMed]
Martos, F.; Le Péchon, T.; Ngugi, G.; Pailler, T.; Bellstedt, D.U.; Linder, H.P.; Bytebier, B. Phylogenetic
relationships amongst the African genera of the tribe Orchideae (Orchidaceae). Manuscript in prep. 2018.
Goodman, L.A. Snowball sampling. Ann. Math. Stat. 1961, 148–170. [CrossRef]
Dunning, L.T.; Savolainen, V. Broad-scale amplification of matK for DNA barcoding plants, a technical note:
AMPLIFICATION OF matK FOR DNA BARCODING PLANTS. Bot. J. Linn. Soc. 2010, 164, 1–9. [CrossRef]
Shepherd, L.D.; McLay, T.G. Two micro-scale protocols for the isolation of DNA from polysaccharide-rich
plant tissue. J. Plant Res. 2011, 124, 311–314. [CrossRef] [PubMed]
Kress, W.J.; Wurdack, K.J.; Zimmer, E.A.; Weigt, L.A.; Janzen, D.H. Use of DNA barcodes to identify flowering
plants. Proc. Natl. Acad. Sci. USA 2005, 102, 8369–8374. [CrossRef] [PubMed]
Sun, Y.; Skinner, D.Z.; Liang, G.H.; Hulbert, S.H. Phylogenetic analysis of Sorghum and related taxa using
internal transcribed spacers of nuclear ribosomal DNA. Theor. Appl. Genet. 1994, 89. [CrossRef] [PubMed]
Bonfield, J.K.; Smith, K.F.; Staden, R. A new DNA sequence assembly program. Nucleic Acids Res. 1995, 23,
4992–4999. [CrossRef] [PubMed]
Staden, R. The Staden sequence analysis package. Mol. Biotechnol. 1996, 5, 233–241. [CrossRef] [PubMed]
Larsson, A. AliView: A fast and lightweight alignment viewer and editor for large datasets. Bioinformatics
2014, 30, 3276–3278. [CrossRef] [PubMed]
Zhang, J.; Kapli, P.; Pavlidis, P.; Stamatakis, A. A general species delimitation method with applications to
phylogenetic placements. Bioinformatics 2013, 29, 2869–2876. [CrossRef] [PubMed]
Stamatakis, A.; Hoover, P.; Rougemont, J. A rapid bootstrap algorithm for the RAxML web servers. Syst. Biol.
2008, 57, 758–771. [CrossRef] [PubMed]
Davenport, T.R.B.; Bytebier, B. Kitulo Plateau, Tanzania-a first African park for orchids. Orchid Rev. 2004,
112, 161–165.
Boessenkool, S.; Mcglynn, G.; Epp, L.S.; Taylor, D.; Pimentel, M.; Gizaw, A.; Nemomissa, S.; Brochmann, C.;
Popp, M. Use of Ancient Sedimentary DNA as a Novel Conservation Tool for High-Altitude Tropical
Biodiversity. Conserv. Biol. 2014, 28, 446–455. [CrossRef] [PubMed]
Van Geel, B.; Aptroot, A.; Baittinger, C.; Birks, H.H.; Bull, I.D.; Cross, H.B.; Evershed, R.P.; Gravendeel, B.;
Kompanje, E.J.; Kuperus, P. The ecological implications of a Yakutian mammoth’s last meal. Quat. Res. 2008,
69, 361–376. [CrossRef]
Kress, W.J.; Erickson, D.L. A two-locus global DNA barcode for land plants: the coding rbcL gene
complements the non-coding trnH-psbA spacer region. PLOS ONE 2007, 2, e508. [CrossRef] [PubMed]
Fazekas, A.J.; Burgess, K.S.; Kesanakurti, P.R.; Graham, S.W.; Newmaster, S.G.; Husband, B.C.; Percy, D.M.;
Hajibabaei, M.; Barrett, S.C.H. Multiple multilocus DNA barcodes from the plastid genome discriminate
plant species equally well. PLOS ONE 2008, 3, e2802. [CrossRef] [PubMed]
Kool, A.; de Boer, H.J.; Krüger, Å.; Rydberg, A.; Abbad, A.; Björk, L.; Martin, G. Molecular Identification of
Commercialized Medicinal Plants in Southern Morocco. PLoS ONE 2012, 7, e39459. [CrossRef] [PubMed]
Elder, J.F.; Turner, B.J. Concerted Evolution of Repetitive DNA Sequences in Eukaryotes. Q. Rev. Biol. 1995,
70, 297–320. [CrossRef] [PubMed]
Genes 2018, 9, 595
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
15 of 15
Ganley, A.R.D.; Kobayashi, T. Highly efficient concerted evolution in the ribosomal DNA repeats: Total
rDNA repeat variation revealed by whole-genome shotgun sequence data. Genome Res. 2007, 17, 184–191.
[CrossRef] [PubMed]
Harpke, D.; Peterson, A. Non-concerted ITS evolution in Mammillaria (Cactaceae). Mol. Phylogenet. Evol.
2006, 41, 579–593. [CrossRef] [PubMed]
Feliner, G.; Rosselló, J. Better the devil you know? Guidelines for insightful utilization of nrDNA ITS in
species-level evolutionary studies in plants. Mol. Phylogenet. Evol. 2007, 44, 911–919. [CrossRef] [PubMed]
Zheng, X.; Cai, D.; Yao, L.; Teng, Y. Non-concerted ITS evolution, early origin and phylogenetic utility of ITS
pseudogenes in Pyrus. Mol. Phylogenet. Evol. 2008, 48, 892–903. [CrossRef] [PubMed]
Xu, B.; Zeng, X.-M.; Gao, X.-F.; Jin, D.-P.; Zhang, L.-B. ITS non-concerted evolution and rampant hybridization
in the legume genus Lespedeza (Fabaceae). Sci. Rep. 2017, 7, 40057. [CrossRef] [PubMed]
Chen, S.; Yao, H.; Han, J.; Liu, C.; Song, J.; Shi, L.; Zhu, Y.; Ma, X.; Gao, T.; Pang, X.; et al. Validation of
the ITS2 region as a novel DNA barcode for identifying medicinal plant species. PLoS ONE 2010, 5, 1–8.
[CrossRef] [PubMed]
Mezzasalma, V.; Bruni, I.; Fontana, D.; Galimberti, A.; Magoni, C.; Labra, M. A DNA barcoding approach
for identifying species in Amazonian traditional medicine: The case of Piri-Piri. Plant Gene 2017, 9, 1–5.
[CrossRef]
Bytebier, B.; Dirk, U.; Bellstedt, H. Peter Linder A New Phylogeny-Based Sectional Classification for the
Large African Orchid Genus Disa. Taxon 2008, 57, 1233–1251.
Van der Niet, T.; Linder, H.P. Dealing with incongruence in the quest for the species tree: A case study from
the orchid genus Satyrium. Mol. Phylogenet. Evol. 2008, 47, 154–174. [CrossRef] [PubMed]
Whitten, W.M.; Blanco, M.A.; Williams, N.H.; Koehler, S.; Carnevali, G.; Singer, R.B.; Endara, L.; Neubig, K.M.
Molecular phylogenetics of Maxillaria and related genera (Orchidaceae: Cymbidieae) based on combined
molecular data sets. Am. J. Bot. 2007, 94, 1860–1889. [CrossRef] [PubMed]
Johnson, L.A.; Soltis, D.E. matK DNA Sequences and Phylogenetic Reconstruction in Saxifragaceae s. str.
Syst. Bot. 1994, 19, 143. [CrossRef]
Pridgeon, A.M.; Solano, R.; Chase, M.W. Phylogenetic relationships in Pleurothallidinae (Orchidaceae):
Combined evidence from nuclear and plastid DNA sequences. Am. J. Bot. 2001, 88, 2286–2308. [CrossRef]
[PubMed]
Cunningham, A.B. Applied Ethnobotany: People, Wild Plant Use and Conservation; Earthscan: London, UK, 2001;
ISBN 1853836974.
Martin, G.J. Ethnobotany: A Methods Manual; Earthscan: London, UK, 2004.
Bingham, M.G.; Smith, P.P. Southern African Plant Red Data Lists: Zambia; Golding, J.S., Bandeira, S.O., Eds.;
SABONET: Pretoria, South Africa, 2002.
IUCN IUCN Red List of Threatened Species. Version 2017-3. 2018.
Bone, R.E.; Wightman, N.; Vinya, R.; Veldman, S.; Yokoya, K.; Hargreaves, S.; Kendon, J.; Crous, H.
Edible wild orchid trade: sustaining livelihoods and biodiversity in Zambia. Darwin Initiative Main
Project Annual Report. 2017.
Filer, D. BRAHMS V5. 6202 Botanical Research and Herbarium Management System (Software). 2007.
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).