Accepted Manuscript Identification of zucchini varieties in commercial food products by DNA typing Maria Verdone, Rosa Rao, Mariangela Coppola, Giandomenico Corrado PII:
S0956-7135(17)30391-2
DOI:
10.1016/j.foodcont.2017.07.039
Reference:
JFCO 5732
To appear in:
Food Control
Received Date: 22 May 2017 Revised Date:
28 July 2017
Accepted Date: 29 July 2017
Please cite this article as: Verdone M., Rao R., Coppola M. & Corrado G., Identification of zucchini varieties in commercial food products by DNA typing, Food Control (2017), doi: 10.1016/ j.foodcont.2017.07.039. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Identification of zucchini varieties in commercial food products by DNA typing
2
Maria Verdone, Rosa Rao, Mariangela Coppola and Giandomenico Corrado*
3
Dipartimento di Agraria, Università degli Studi di Napoli “Federico II”, via Università 100, 80055
4
Portici (NA), Italy
RI PT
1
5
* Corresponding author. Tel.: +39 081 2539294; fax: +39 081 2539481. E-mail address:
7
[email protected] (G. Corrado).
M AN U
8
12
TE D
11
Traceability, SSR, STR, molecular markers, Cucurbita pepo, DNA profile, random match probability
EP
10
Keywords
AC C
9
SC
6
1
ACCEPTED MANUSCRIPT ABSTRACT
14
DNA typing has been long proposed as a component of food traceability especially for the ability
15
to provide genetic information on processed and/or mixed commercial products. However, the
16
use of DNA testing to deliver legal evidence has been very limited in the agro-food chain, also
17
because in this field, a genetic concordance is rarely sustained with indications on the
18
interpretation and statistics of a DNA profile.
19
Zucchini is the most important and diverse horticultural group belonging to Cucurbita pepo, a
20
plant species that yields a large variety of edible fruits such as squashes and pumpkins. Challenges
21
in genetic discrimination of zucchini material exiting the agro-food chain typify the problems in
22
DNA typing of horticultural food products, because of limited allelic diversity, presence of common
23
alleles, highly processed food and genetic similarity with other edible species.
24
The aim of this work was to identify zucchini varieties in commercial products by a means of
25
Simple Sequence Repeat (SSR) analysis and to provide indications for the statistical interpretation
26
of a match. We assessed the efficacy of SSRs analyzing some of the most diffused hybrids and
27
open pollinated zucchini varieties. SSRs were also screened for transferability in DNA isolated from
28
edible organs of different plant species that are frequently present in food products containing
29
zucchini. Moreover, we demonstrate the possibility to identify the variety in food products of
30
different origins. The statistical evaluation on the rarity of DNA profiles in zucchini indicated that
31
the genetic match presented in this work cannot be attributed to chance alone. Based on this
32
evidence, the advantages and pitfalls of food DNA typing for variety identification of a horticultural
33
crop are discussed.
AC C
EP
TE D
M AN U
SC
RI PT
13
34
2
ACCEPTED MANUSCRIPT 1. Introduction
36
Cucurbita pepo L. is considered the most diverse species of its genus with respect to fruit size,
37
shape and color (Paris, 1996). This plant species yields a large variety of fruits used for culinary
38
purposes, such as pumpkin, gourd, marrow and winter and summer squash. These designations do
39
not have a precise botanical meaning because they are not associated to one particular species
40
(Paris, 1996). For instance, summer squash is a lay term to designate edible, tender fruits of C.
41
pepo that are harvested and consumed before maturity, although not all fruits of this species are
42
considered summer squashes (Whitaker & Robinson, 1986).
43
Zucchini is currently the most diffused and economically important horticultural group of C. pepo
44
(Paris, 2016b). The term zucchini is an Americanism originating from the Italian word (masculine,
45
plural) for little pumpkin (“zucca” plus a diminutive suffix) (http://www.accademiadellacrusca.it).
46
Zucchini designates a rather uniform, cylindrically-shaped fruit with length-to-broadest width ratio
47
generally comprised from 3.5 to 4.5 (Paris, 1996). Zucchini fruits, also named courgettes in English
48
speaking countries, typically have a green skin color, being harvested immature, and are eaten
49
only after cooking. However, traditional varieties with more spherical fruits (e.g. “Tondo”), grown
50
mainly in Italy and France, and more recently, varieties with yellow fruits are also included in the
51
zucchini group by plant breeders and retailers.
52
The zucchini cultivation has experienced a recent success in many countries mainly due to ease of
53
cultivation in both open-field and protected agriculture, short crop cycle, adaptability to
54
temperate and subtropical climates, suitability to low-calories diet regimes and cooking versatility.
55
The diffusion of summer squash, mainly zucchini, has increased proportionally more than many
56
other vegetables, especially in Western countries (Paris, 2016b). This success is also determined by
57
the world wide increasing consumption of fresh and frozen fruits and vegetables, principally as
AC C
EP
TE D
M AN U
SC
RI PT
35
3
ACCEPTED MANUSCRIPT alternative to canned products (Barbosa-Cánovas, Altunakar, & Mejía-Lorío, 2005; Harris &
59
Shiptsova, 2007). For instance, mixed vegetables are the second most important frozen product
60
after potatoes (Barbosa-Cánovas, et al., 2005).
61
Traceability provides the ability to characterize and certify products throughout the food chain,
62
from producers to consumers (Dabbene, Gay, & Tortia, 2014). Different technologies are required
63
for effective traceability implementation and one important element is genetic traceability (Opara,
64
2003). DNA markers are widely used molecular tools to trace or reveal the genetic identity of a
65
biological component of food and feed. For genetic traceability, preference is given to markers
66
amenable to the analysis of raw material and highly processed commercial products. Compared to
67
other analytical methods, the DNA analysis offers a great level of precision and accuracy to
68
identify the origin and composition of food in terms of botanical species or varieties (Barcaccia,
69
Lucchin, & Cassandro, 2015; Corrado, 2016).
70
Zucchini represents a challenge for DNA traceability. Because of its more recent origin, zucchini is
71
characterized by a reduced diversity compared to other C. pepo horticultural groups (Formisano,
72
et al., 2012). Moreover, genetic traceability needs to consider that zucchini is frequently present in
73
complex, mixed products (i.e. those with different vegetable ingredients). Additionally, the
74
botanical relationships between zucchini and other edible Cucurbitacae (e.g. pumpkin, gourd,
75
cucumber, etc.) may pose a limitation in the discrimination power of some DNA markers (Li Gong,
76
et al., 2012). Finally, many zucchini cultivars are hybrids, requiring co-dominant markers for an
77
easier discrimination. Among DNA markers available, Simple Sequence Repeat (SSR), also known
78
as Simple Tandem Repeats (STR), are the markers of choice in forensics (Schlötterer, 2004) and
79
they are widely used also to trace the agro-food chain because of their high polymorphism,
80
codominant nature, reproducibility and amenability to degraded DNA (Corrado, 2016).
AC C
EP
TE D
M AN U
SC
RI PT
58
4
ACCEPTED MANUSCRIPT The aim of this work was to type the DNA of zucchini varieties in commercial food products by a
82
means of SSR analysis. In order to evaluate the genetic differences among popular zucchini
83
varieties, we assessed the efficacy of SSRs by analyzing some of the most diffused hybrids and
84
open pollinated cultivars. SSRs were also screened for transferability in DNA isolated from edible
85
organs of different plant species that are frequently present in commercial products containing
86
zucchini. Finally, it was constructed a profiles database, which was used to support the statistical
87
evaluation on the rarity of DNA profiles in zucchini. This evaluation allowed discussing the
88
advantages and pitfalls of food DNA typing for variety identification of a horticultural crop.
SC
RI PT
81
AC C
EP
TE D
M AN U
89
5
ACCEPTED MANUSCRIPT 2. Material and Methods
91
2.1. Plant material and DNA isolation
92
We analysed 30 varieties of zucchini (Cucurbita pepo ssp. pepo L.) namely, ‘Altea’, ‘Anissa’, ‘Asso’,
93
‘Aurore’, ‘Aymaran’, ‘Black Beauty’, ‘Cavili’, ‘Coucourzelle’, ‘De Nice à fruit rond’, ‘Genovese’,
94
‘Genovese Antico’, ‘Giulia’, ‘Gulliver’, ‘Lanka’, ‘Mikonos’, ‘Milos’, ‘Ontano’, ‘Parthenon’,
95
‘President’, ‘Quine’, ‘Rhodos’, ‘Rigas’, ‘Romanesco’, ‘San Pasquale’, ‘Sitos’, ‘Syros’, ‘Temprano de
96
Argelia’, ‘Vertre noir maraîchère’, ‘Virginia’ and ‘Vitulia’. This set includes 20 hybrid cultivars and
97
10 open-pollinated varieties. Fruit general shape and colour are reported in Supplementary Table
98
1. Plants were grown from seed and the first true leaf was harvested and frozen in liquid nitrogen
99
for subsequent analysis. We analysed three plants per variety.
M AN U
SC
RI PT
90
For the SSR transferability experiments, DNA was isolated from fresh edible organs of the
101
following species: cabbage (Brassica oleracea L.), carrot (Daucus carotae L.), celery (Apium
102
graveolens L.), cucumber (Cucumis sativus L), onion (Allium cepa L.), pea (Pisum sativum L.), potato
103
(Solanum tuberosum L.), pumpkin (Cucurbita maxima Duchesne), tomato (Solanum lycopersicum
104
L.). Cabbage, carrot, celery, onion, pea, potato and tomato are very frequently present in
105
processed food products containing zucchini (e.g. vegetable soups, frozen mixed vegetables, etc.).
106
Cucumber and pumpkin were included because they are two edible plants belonging to the
107
Cucurbitacae family. For all plant material, DNA isolation and quantification was carried out as
108
described (Scarano, Rao, Masi, & Corrado, 2015)
109
2.2. Commercial products and DNA isolation
110
We analysed five types of commercial products containing zucchini: fresh fruits (with cylindrical or
111
round shape) from the shelf of a large-scale distribution; frozen zucchini (sliced and sold as a
112
frozen product); mixed vegetables (different clean vegetables cut to prepare a soup, raw and not
AC C
EP
TE D
100
6
ACCEPTED MANUSCRIPT seasoned, sold as a frozen product); chargrilled zucchini (sliced zucchini, chargrilled and stored in a
114
transparent glass jar with olive oil); and Caprese (aka Scapece) zucchini (canned zucchini, fried
115
with vegetable oil, seasoned with vinegar, garlic and mint leaves, stored in olive oil). Frozen
116
zucchini, mixed vegetables and chargrilled zucchini were purchased from the same retail store
117
brand. For DNA isolation, fresh and frozen products were pulverised in liquid nitrogen with a
118
mortar and pestle for subsequent manipulations. Zucchini stored in oil were first blotted on
119
kitchen towels and then centrifuged for 30 second at 1000 g on kitchen paper to remove the
120
residual liquid phase. Samples were then pulverised as described above. DNA isolation was carried
121
out using the DNeasy Plant Mini Kit (QIAGEN) according to the manufacturer’s instruction.
122
2.3. SSR analysis
123
DNA amplification reactions were conducted in a 25 μl volume containing 20ng of genomic DNA,
124
1X PCR buffer (Promega), 0.1 mM dNTPs, 0.2 μM labelled forward primer, 0.2 μM reverse primer
125
and 0.5U of Taq polymerase (Promega). The amplification reactions were carried out in a
126
Mastercycler Gradient (Eppendorf) thermocycler with the following conditions: a DNA
127
denaturation step at 94 °C for 4'; 35 cycles comprising a denaturation step at 94 °C for 45'', an
128
annealing phase at 56 °C for 45'' and elongation step at 72 °C for 90”. A final elongation phase at
129
72 °C for 15' ended the reaction. The eight SSR loci employed comprised different core structures
130
(L Gong, Stift, Kofler, Pachner, & Lelley, 2008). Primer and core sequences are reported in
131
Supplementary Table 2. Amplification products were separated by agarose gel electrophoresis to
132
verify the presence of amplified fragments. For allelic discrimination, the fluorescent fragments
133
were resolved by capillary electrophoresis in an ABI PRISM 3130 (Applied Biosystems) system
134
using the POP6 polymer (Applied Biosystems). Signal peak height and allele sizes were calculated
135
using the ABI PRISM Genotyper (v. 4.0) software (Applied Biosystems) based on the GeneScan
136
500Liz molecular weight standard (Applied Biosystems).
AC C
EP
TE D
M AN U
SC
RI PT
113
7
ACCEPTED MANUSCRIPT 2.4. Estimation of the amplicon size range for processed products.
138
DNA from processed products was amplified with primers targeting the same DNA regions. The
139
primers and their main features are reported in Supplementary Table 3. Primers were designed on
140
the "Cucurbita pepo Unigene PU020788" clone, retrieved at the International Cucurbit Genomics
141
Initiative (ICuGI) database (http://www.icugi.org/) based on sequence similarity BLAST search.
142
2.5. Data analysis
143
For each SSR locus, we calculated the number of alleles, their frequency, the Observed
144
Heterozygosity (Ho), the Polymorphic information content (PIC) (Powell, et al., 1996), the Fixation
145
Index and the Probability of identity (Hartl, Clark, & Clark, 1997). Pairwise genetic distances were
146
calculated as reported (Nei, 1972). These calculations were performed using the GenAlEx 6.5
147
software (Peakall & Smouse, 2012). Hierarchical clustering using the UPGMA algorithm was carried
148
out with the MEGA software (Tamura, Dudley, Nei, & Kumar, 2007). The calculation of the
149
expected genotype frequency (i.e. genotype probability) based on allele frequency under Hardy–
150
Weinberg expectation for random union of alleles, without taking population structure into
151
account (National Research Council, 1996). DNA profile frequency estimates were calculated by
152
considering the genotype frequency for each locus and then multiplying the frequencies across all
153
loci, yielding the Random Match Probability. For the analysis of the cumulative product of
154
genotype probability for an increasing number of SSR loci, we calculated the descriptive statistics
155
considering the probability of each scored genotype using all the combinations without repetition
156
(C) of different number of loci (Cn,k=n!/(k!(n-k)!), where n is the number of values to choose from,
157
and k the element chosen). This analysis was performed in R (Team R Core, 2000).
AC C
EP
TE D
M AN U
SC
RI PT
137
158
8
ACCEPTED MANUSCRIPT 3. Results
160
3.1. Allelic diversity
161
We analysed 30 cultivated varieties of C. pepo using eight SSRs representatives of various repeat
162
classes. Main genetic parameters of the population under investigation are presented in Table 2.
163
All the loci were polymorphic. We detected 29 alleles, whose length ranged from 65 to 236 bp, for
164
an average of 3.6 allele per locus. The mean observed heterozygosity (Ho) was just above 25% yet,
165
two loci (CMTp69 and CMTp176) had a Ho below 0.1%. The Ho did not significantly correlate with
166
the number of alleles (p >0.05; Spearman’s Rho). The PIC values indicated that the degree of
167
polymorphism in each locus was high (i.e. >0.5) for the majority (5 out of 8) of SSRs (Botstein,
168
White, Skolnick, & Davis, 1980) and that PIC significantly correlated with the number of alleles (p
169
>0.05; Spearman’s Rho). The Probability of Identity, an estimation of the probability that two
170
unrelated individuals will have by chance the same genotype, inversely correlated with the
171
number of alleles. The fixation index was substantial positive for all but two loci (CMTp98 and
172
CUTC022867) and considering the outcrossing nature of C. pepo, it may indicate an effect of
173
breeding. This hypothesis is also consistent with the presence in many loci of one allele with a
174
predominant frequency, evident especially for the multiallelic SSRs (e.g. those with more than
175
three alleles). The genetic divergence between varieties were calculated considering the SSR
176
profiles of three plants per variety using the Nei’s genetic distance between populations.
177
Hierarchical clustering illustrated that all the varieties could be discriminated (Figure 2).
178
3.2. SSR transferability
179
Although SSR markers are generally regarded as species-specific, different studies indicated that
180
the sequence similarity across related species or genera is sufficient to obtain amplification
181
products using primers designed for one plant species (Rai, Phulwaria, & Shekhawat, 2013; Saha,
AC C
EP
TE D
M AN U
SC
RI PT
159
9
ACCEPTED MANUSCRIPT Cooper, Mian, Chekhovskiy, & May, 2006; Yamamoto, et al., 2001). For instance, it is known that
183
the close botanical relationship allows the transferability of the SSR primers among cultivated
184
Curbitaceae (Li Gong, et al., 2012). Considering that zucchini processed products can be present in
185
foodstuff containing different plant species (e.g. mixed vegetables), we assessed the transferability
186
of the employed SSR primers in cabbage, carrot, celery, onion, pea, potato and tomato. Moreover,
187
we also analysed two edible Cucurbits, cucumber and pumpkin. For all these plant species, the
188
DNA was isolated from edible organs (fruits, seeds, leaves, etc.) available in grocery stores. We
189
tested the eight SSR loci in the same amplification conditions used for the analysis of the zucchini.
190
Amplifications were then subjected to capillary electrophoresis. We classified the output in three
191
categories: “no amplification” (when the fluorescent signal was similar to the background line);
192
“nonspecific amplification” (presence of more than two peaks, usually in a wide size range) and
193
“within range” (one or two well-defined peaks, whose size was within the detected allelic size
194
range for zucchini; table 2). The results are summarised in Table 3 and an illustrative example of
195
the capillary electrophoresis output is reported in Supplementary Figure 1. We did not obtain a
196
detectable amplicon for the majority of the samples (39%), while the percentage of nonspecific
197
and specific amplification were similar. The set of eight primers was not completely transferable in
198
the plant species tested and, as expected, the maximum transferability was obtained in pumpkin
199
(6 loci) and cucumber (4 loci). For the other species, the number of transferable SSR ranged from
200
three to zero. The most transferable SSR was CMTp69 (in seven plant species). The most specific
201
loci were CMTp132 and CMTp142 (transferable in one species) yet, the EST-SSR CUTC022867 was
202
transferable only in the two Cucurbitaceae analysed and, differently for the other SSRs, did not
203
yield nonspecific amplifications in the other plant species.
204
3.3. Amplificability of the DNA from commercial products
AC C
EP
TE D
M AN U
SC
RI PT
182
10
ACCEPTED MANUSCRIPT Food processing and storage can decrease the quality of the DNA that can be isolated from
206
commercial products. We analysed five types of commercial products that differ in the
207
transformation process, ranging from “no treatment” (fresh fruits) to a combination of mechanical
208
and heat treatments (Table 1). Considering the allelic range observed, we tested if the DNA
209
isolated from the food products containing zucchini can consistently yield PCR products within the
210
desired interval (up to 280 bp). To this aim, we used primers designed to amplify the same target
211
region of a single gene of the C. pepo genome (Figure 1A). By using different primer combinations,
212
the result indicated that is possible to amplify fragments within the 280-89 bp range in the
213
commercial products tested (Figure 1B, C and D).
214
3.4. Analysis of commercial products
215
Having tested the amplificability of the isolated DNA, we screened the commercial products
216
containing zucchini (Table 1) with the eight SSR markers. All the SSRs loci were able to amplify
217
consistently DNA (Figure 3). We observed, also for DNA isolated from complex food (e.g. those
218
with additional ingredients) the presence of one or two allele, confirming the codominance of the
219
markers employed. Moreover, to test for the possible presence of spurious alleles deriving from
220
other plant species, we compared the profile of the DNA isolated form mixed vegetable with the
221
one from the frozen zucchini manually separated from the commercial product, without finding
222
differences.
223
In the commercial products (including fruits), we detected in total 11 alleles, which were also
224
present in our zucchini collection. The comparison of the food samples’ and the references’
225
profiles revealed a match for the frozen zucchini and mixed vegetables. We therefore computed
226
the match probability to weight this evidence. For this estimation, we considered the allele
227
frequencies collected from all the plants analysed (90), mainly to take into account the variability
AC C
EP
TE D
M AN U
SC
RI PT
205
11
ACCEPTED MANUSCRIPT in the genetic profiles in the open pollinated varieties. The random match probability calculations
229
are reported in table 4. The expected frequency (RMP) of the genotype identified in some
230
commercial product is 2.95 x 10-4 considering our population of zucchini varieties. To interpret and
231
assess the weight of this DNA evidence, we built an accumulation curve of the possible random
232
match probability for each of the genotypes under investigation for increasing combinations of
233
loci. This analysis provided evidence on the number of loci required for reliable genetic tagging.
234
Summary statistics are reported in Supplementary Table 4. To increase readability, Figure 4
235
boxplots the log10 of the genotype frequencies according to an increasing number of SSRs. The
236
curve based on raw RMPs started to flatten with five loci (not shown) and the average genotype
237
frequency was always significantly smaller by increasing the number of SSR loci (p <0.001,
238
Wilcoxon Signed-Rank test). Increasing the number of loci also reduced data dispersion and
239
strongly limited the occurrence of outliers (i.e. values outside 1.5 times the interquartile range
240
above the upper and below the lower quartile).
SC
M AN U
TE D EP AC C
241
RI PT
228
12
ACCEPTED MANUSCRIPT 4. Discussion
243
The zucchini market, as other horticultural crops, is characterized by an increasing standardization
244
of production (i.e. uniformity in fruit shape and dimension as well as in qualitative and
245
organoleptic aspects of commercial products), which has recently boosted an interest for more
246
typical productions (Brugarolas, Martínez-Carrasco, Martínez-Poveda, & Ruiz-Martínez, 2009;
247
Johns, Powell, Maundu, & Eyzaguirre, 2013). Zucchini represents the most important and
248
cosmopolitan horticultural group of the Cucurbita genus (Paris, 1996, 2016a) and an ingredient of
249
very popular frozen products (Barbosa-Cánovas, et al., 2005) and challenges in genetic
250
characterization of zucchini food products are illustrative of the specific issues about DNA typing
251
of horticultural products.
252
This study demonstrated the possibility of using SSR markers for the characterization of different
253
zucchini varieties and the identification of the variety in commercial processed products. The DNA
254
analysis indicated that the germplasm under investigation has a number of alleles that is
255
consistent with other published works in C. pepo as well other herbaceous annual crops
256
(Bredemeijer, et al., 2002; Li Gong, et al., 2012; Shehata, Al-Ghethar, & Al-Homaidan, 2009; Singh,
257
et al., 2013). The SSRs markers were all polymorphic and their informativeness mainly correlated
258
with the number of alleles. Significant differences between SSRs were found with respect to the
259
observed heterozygosity, which may be explained by fixation of some SSRs due to association of
260
some favorable alleles. For each locus, the percentage of observed genotypes over the possible
261
ones was high (78%), indicating that our zucchini population represent a suitable panel of different
262
genotypes. The usefulness of a DNA marker is also reflected by frequencies of the most common
263
genotypes (Edwards, Hammond, Jin, Caskey, & Chakraborty, 1992). For many loci, we observed
264
the presence of common alleles, which can limit the value of the genotype’s combined frequency.
265
Moreover, the presence of alleles with high frequency renders a locus less powerful in
AC C
EP
TE D
M AN U
SC
RI PT
242
13
ACCEPTED MANUSCRIPT discriminating two unrelated individual. Based on these criteria, the CMTp257 yielded the most
267
useful results among the employed SSRs.
268
The eight loci could discriminate the varieties under investigation and proved to be suitable to
269
amplify DNA from a range of commercial products. In spite of the thermal and/or mechanical
270
treatment, we could reliably amplify PCR products up to 280 bp, a dimension that includes almost
271
all SSR loci for Cucurbita (L Gong, et al., 2008). Compared to other processed vegetables such as
272
tomato (Scarano, et al., 2015), it is likely that this dimension also reflects the fact that zucchini are
273
not peeled and, if not frozen, they are stored in oil.
274
SSR transferability may represent an advantage for plant forensics mainly because it allows
275
reducing the cost and effort to develop SSRs for orphan plant species (Craft, Owens, & Ashley,
276
2007). Our work indicated that caution should be applied when analyzing a complex food mixture
277
because of the possibility to obtain within-range allelic profiles also from very different species.
278
For mixed vegetables, the data suggest that the profile of the isolated product does not come
279
from multiple sources. It is fair to add that zucchini was the only Cucurbit in this commercial
280
product. Large differences were present in the cross-species transferability of the SSRs, implying
281
that a preliminary screening of SSR markers is useful, if not necessary, when aiming at the genetic
282
traceability of mixed products. Interestingly, the EST-SSR CUTC022867 did not yield nonspecific
283
amplifications in non-Cucurbits. EST-SSRs are thought to be more transferable in closely related
284
species (Varshney, Graner, & Sorrells, 2005), and the possibility that genic SSRs are less
285
transferable in more distant taxonomic ranks (e.g. across genera) should be tested analyzing a
286
larger panel of SSRs.
287
The significance of non-human DNA typing for court use has advanced recently especially for
288
animal species and products (Johnson, Wilson-Wilde, & Linacre, 2014; Linacre, et al., 2011). The
AC C
EP
TE D
M AN U
SC
RI PT
266
14
ACCEPTED MANUSCRIPT relevance is much more limited for the plant sector (Iyengar, 2014), in spite of a wide range of
290
applications (Barcaccia, et al., 2015; Corrado, 2016; Ferri, et al., 2015). While DNA typing cannot
291
be considered anymore a novel approach, a limitation of its use in forensic plant genetics is
292
represented by the strength of statistical interpretations (Sensabaugh & Kaye, 1998). A number of
293
studies have identified the genetic makeup of plant-derived food products yet, hardly ever this
294
information is accompanied by an estimate of a profile frequency (Craft, et al., 2007; Howard,
295
Gilmore, Robertson, & Peakall, 2009). To this aim, the allele frequency information from our
296
database was used to assess relative rarity of DNA profiles. This analysis underlined the
297
importance of the number of loci under investigation. Although the SSR loci employed displayed
298
large difference in their discriminating power, the accumulation curve gives reason to believe that
299
the rarity of a full DNA profile frequency estimate in zucchini could be significantly lowered by
300
adding more SSR loci. The shortage of statistical analysis for the interpretation of the rarity of
301
genetic profile in horticultural crops does not allow an evaluation of the general probability values
302
(Foreman & Evett, 2001). For cultivated plants, the random match probability represents the
303
frequency of an SSR profile expected to occur in a population of cultivars, rather than individuals
304
(Craft, et al., 2007). It is difficult to put forward an estimate of the cultivated zucchini varieties,
305
mainly because varieties are registered as C. pepo (hence including marrow, pumpkin, winter
306
squash as well as different horticultural types of summer squash). Based on the catalogues of main
307
breeding companies, a sensible estimation of the number of zucchini varieties currently sold in
308
Italy should be around 50-60, which suggests that the genetic match presented in this work cannot
309
be attribute to chance alone. A main priority to strengthen the use of DNA testing of horticultural
310
products in courts will be to establish international database of genetic profile. Further studies
311
should also explore genetic differentiation and population substructure, which is likely to be
312
present when comparing different horticultural groups of C. pepo.
AC C
EP
TE D
M AN U
SC
RI PT
289
15
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
313
16
ACCEPTED MANUSCRIPT 314
Acknowledgments
315
The research activity was supported by the “Valorizzazione di produzioni ortive campane di
316
eccellenza
317
PON02_00395_3215002. MC was supported by a scholarship of the Regione Campania, POR
318
Campania FSE 2014/2020, RIS: Salute, biotecnologie, agroalimentare.
strumenti
di
genomica
avanzata”
(GenHORT)
project,
RI PT
con
AC C
EP
TE D
M AN U
SC
319
17
Code
ACCEPTED MANUSCRIPT References
321
Barbosa-Cánovas, G. V., Altunakar, B., & Mejía-Lorío, D. J. (2005). Freezing of fruits and vegetables:
322
An agribusiness alternative for rural and semi-rural areas (Vol. 158): Food & Agriculture
323
Org, FAO Agricultural Services Bulletin
324 325
RI PT
320
Barcaccia, G., Lucchin, M., & Cassandro, M. (2015). DNA barcoding as a molecular tool to track down mislabeling and food piracy. Diversity, 8(1), 2.
Botstein, D., White, R. L., Skolnick, M., & Davis, R. W. (1980). Construction of a genetic linkage map
327
in man using restriction fragment length polymorphisms. American journal of human
328
genetics, 32(3), 314.
M AN U
SC
326
Bredemeijer, G. M. M., Cooke, R. J., Ganal, M. W., Peeters, R., Isaac, P., Noordijk, Y., Rendell, S.,
330
Jackson, J., Roder, M. S., Wendehake, K., Dijcks, M., Amelaine, M., Wickaert, V., Bertrand,
331
L., & Vosman, B. (2002). Construction and testing of a microsatellite database containing
332
more than 500 tomato varieties. Theoretical and Applied Genetics, 105(6-7), 1019-1026.
TE D
329
Brugarolas, M., Martínez-Carrasco, L., Martínez-Poveda, A., & Ruiz-Martínez, J. (2009). A
334
competitive strategy for vegetable products: traditional varieties of tomato in the local
335
market. Spanish Journal of Agricultural Research, 7(2), 294-304.
337
Corrado, G. (2016). Advances in DNA typing in the agro-food supply chain. Trends in Food Science
AC C
336
EP
333
& Technology, 52, 80-89.
338
Craft, K. J., Owens, J. D., & Ashley, M. V. (2007). Application of plant DNA markers in forensic
339
botany: genetic comparison of Quercus evidence leaves to crime scene trees using
340
microsatellites. Forensic science international, 165(1), 64-70.
341 342
Dabbene, F., Gay, P., & Tortia, C. (2014). Traceability issues in food supply chain management: A review. Biosystems Engineering, 120, 65-80.
18
ACCEPTED MANUSCRIPT 343
Edwards, A., Hammond, H. A., Jin, L., Caskey, C. T., & Chakraborty, R. (1992). Genetic variation at
344
five trimeric and tetrameric tandem repeat loci in four human population groups.
345
Genomics, 12(2), 241-253. Ferri, G., Corradini, B., Ferrari, F., Santunione, A., Palazzoli, F., & Alu, M. (2015). Forensic botany II,
347
DNA barcode for land plants: Which markers after the international agreement? Forensic
348
Science International: Genetics, 15, 131-136.
RI PT
346
Foreman, L. A., & Evett, I. W. (2001). Statistical analyses to support forensic interpretation for a
350
new ten-locus STR profiling system. International Journal of Legal Medicine, 114(3), 147-
351
155.
M AN U
SC
349
352
Formisano, G., Roig, C., Esteras, C., Ercolano, M. R., Nuez, F., Monforte, A. J., & Picó, M. B. (2012).
353
Genetic diversity of Spanish Cucurbita pepo landraces: an unexploited resource for
354
summer squash breeding. Genetic resources and crop evolution, 59(6), 1169-1184. Gong, L., Paris, H. S., Nee, M. H., Stift, G., Pachner, M., Vollmann, J., & Lelley, T. (2012). Genetic
356
relationships and evolution in Cucurbita pepo (pumpkin, squash, gourd) as revealed by
357
simple sequence repeat polymorphisms. Theoretical and Applied Genetics, 124(5), 875-891.
358
Gong, L., Stift, G., Kofler, R., Pachner, M., & Lelley, T. (2008). Microsatellites for the genus
359
Cucurbita and an SSR-based genetic linkage map of Cucurbita pepo L. Theoretical and
360
Applied Genetics, 117(1), 37-48.
362 363 364
EP
AC C
361
TE D
355
Harris, J. M., & Shiptsova, R. (2007). Consumer demand for convenience foods: Demographics and expenditures. Journal of Food Distribution Research, 38(3), 22. Hartl, D. L., Clark, A. G., & Clark, A. G. (1997). Principles of population genetics (Vol. 116): Sinauer associates Sunderland.
19
ACCEPTED MANUSCRIPT 365
Howard, C., Gilmore, S., Robertson, J., & Peakall, R. (2009). A Cannabis sativa STR genotype
366
database for Australian seizures: forensic applications and limitations. Journal of forensic
367
sciences, 54(3), 556-563.
369
Iyengar, A. (2014). Forensic DNA analysis for animal protection and biodiversity conservation: a review. Journal for Nature Conservation, 22(3), 195-205.
RI PT
368
Johns, T., Powell, B., Maundu, P., & Eyzaguirre, P. B. (2013). Agricultural biodiversity as a link
371
between traditional food systems and contemporary development, social integrity and
372
ecological health. Journal of the Science of Food and Agriculture, 93(14), 3433-3442.
373
Johnson, R. N., Wilson-Wilde, L., & Linacre, A. (2014). Current and future directions of DNA in
M AN U
374
SC
370
wildlife forensic science. Forensic Science International: Genetics, 10, 1-11. Linacre, A., Gusmao, L., Hecht, W., Hellmann, A., Mayr, W., Parson, W., Prinz, M., Schneider, P., &
376
Morling, N. (2011). ISFG: recommendations regarding the use of non-human (animal) DNA
377
in forensic genetic investigations. Forensic Science International: Genetics, 5(5), 501-505.
380 381
Press.
Nei, M. (1972). Genetic distance between populations. The American Naturalist, 106(949), 283292.
EP
379
National Research Council. (1996). The evaluation of forensic DNA evidence: National Academies
AC C
378
TE D
375
382
Opara, L. U. (2003). Traceability in agriculture and food supply chain: a review of basic concepts,
383
technological implications, and future prospects. Journal of Food Agriculture and
384
Environment, 1, 101-106.
385
Paris, H. S. (1996). Summer squash: history, diversity, and distribution. HortTechnology, 6(1), 6-13.
386
Paris, H. S. (2016a). Genetic Resources of Pumpkins and Squash, Cucurbita spp. In Plant Genetics
387
and Genomics: Crops and Models (pp. 1-44). New York, NY: Springer New York.
20
ACCEPTED MANUSCRIPT 388 389 390 391
Paris, H. S. (2016b). Germplasm enhancement of Cucurbita pepo (pumpkin, squash, gourd: Cucurbitaceae): progress and challenges. Euphytica, 208(3), 415-438. Peakall, P. E., & Smouse, R. (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics, 28, 2537-2539. Powell, W., Morgante, M., Andre, C., Hanafey, M., Vogel, J., Tingey, S., & Rafalski, A. (1996). The
393
comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis.
394
Molecular breeding, 2(3), 225-238.
RI PT
392
Rai, M. K., Phulwaria, M., & Shekhawat, N. (2013). Transferability of simple sequence repeat (SSR)
396
markers developed in guava (Psidium guajava L.) to four Myrtaceae species. Molecular
397
biology reports, 40(8), 5067-5071.
M AN U
SC
395
Saha, M. C., Cooper, J. D., Mian, M. R., Chekhovskiy, K., & May, G. D. (2006). Tall fescue genomic
399
SSR markers: development and transferability across multiple grass species. Theoretical
400
and Applied Genetics, 113(8), 1449-1458.
403 404
commercial processed tomato products. Food Control, 51, 397-401. Schlötterer, C. (2004). The evolution of molecular markers—just a matter of fashion? Nature
EP
402
Scarano, D., Rao, R., Masi, P., & Corrado, G. (2015). SSR fingerprint reveals mislabeling in
Reviews Genetics, 5(1), 63-69.
AC C
401
TE D
398
405
Sensabaugh, G., & Kaye, D. H. (1998). Nonhuman DNA evidence. Jurimetrics Journal,38 1-16.
406
Shehata, A. I., Al-Ghethar, H. A., & Al-Homaidan, A. A. (2009). Application of simple sequence
407
repeat (SSR) markers for molecular diversity and heterozygosity analysis in maize inbred
408
lines. Saudi journal of biological sciences, 16(2), 57-62.
409
Singh, N., Choudhury, D. R., Singh, A. K., Kumar, S., Srinivasan, K., Tyagi, R., Singh, N., & Singh, R.
410
(2013). Comparison of SSR and SNP markers in estimation of genetic diversity and
411
population structure of Indian rice varieties. PLoS One, 8(12), e84136. 21
ACCEPTED MANUSCRIPT 412 413
Tamura, K., Dudley, J., Nei, M., & Kumar, S. (2007). MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Molecular biology and evolution, 24(8), 1596-1599.
414
Team R Core. (2000). R language definition. Vienna, Austria: R foundation for statistical computing.
415
Varshney, R. K., Graner, A., & Sorrells, M. E. (2005). Genic microsatellite markers in plants: features and applications. TRENDS in Biotechnology, 23(1), 48-55.
RI PT
416
Whitaker, T., & Robinson, R. (1986). Squash breeding. Breeding vegetable crops, 209-242.
418
Yamamoto, T., Kimura, T., Sawamura, Y., Kotobuki, K., Ban, Y., Hayashi, T., & Matsuta, N. (2001).
419
SSRs isolated from apple can identify polymorphism and genetic diversity in pear. TAG
420
Theoretical and Applied Genetics, 102(6), 865-870.
M AN U
SC
417
421 422
AC C
EP
TE D
423
22
ACCEPTED MANUSCRIPT 424
TABLES
425
427
Table 1: Commercial products analysed and their main features. Product
Mechanical Treatment
Heat treatment
Fruits from the shelf (cylindrical and round) Frozen zucchini Mixed Vegetables (frozen) Chargrilled, in olive oil* Fried in oil (Caprese/Scapece)* *: pasteurised product
No
No
Yes (slices) Yes (dice) Yes (slices) Yes (slices)
No No Yes (grilled) Yes (fried)
No Yes No Yes
SC
428
Other vegetable ingredients No
RI PT
426
AC C
EP
TE D
M AN U
429
23
ACCEPTED MANUSCRIPT Table 2: Main genetic indices of the zucchini genotypes under investigations.
CMTp69
65-75
CMTp98
212-236
CMTp132
141-165
CMTp142
150-196
CMTp176
93-109
CMTp257
123-147
CMTp260
120-156
CUTC022867 124-139 Mean SE
PI Na 5
Ho PIC F 0.067 0.528 0.874 0.200
0.215
0.068
0.640
0.878
3
0.289
0.376
0.232
0.432
0.767
4
0.144
0.561
0.743
0.239
0.617
2
0.078
0.299
0.740
0.536
0.817
6
0.395
0.674
0.414
0.164
0.426
4
0.400
0.610
0.344
0.224
0.506
3
0.500
0.524
0.047
0.310
3.625 0.498
0.259 0.057
0.473 0.057
0.433 0.113
0.352 0.059
0.600
Legend: Na: number of alleles; Ho: Observed heterozygosity; He: Expected Herozygosity; F: Fixation index; PI: Probability of identity at a locus, MAF: major allele frequency.
434
AC C
EP
TE D
435 436
MAF 0.664
2
431 432 433
0.271
RI PT
Size range (bp)
SC
Locus SSR
M AN U
430
24
ACCEPTED MANUSCRIPT
CMTp98
CMTp132
P. sativum
WR
NONSP
NOAMP
NOAMP
WR
WR
NONSP
NOAMP
D. carotae
WR
WR
NOAMP
NONSP
NOAMP
WR
NONSP
NOAMP
C. sativus
WR
NONSP
NOAMP
NOAMP
WR
NONSP
WR
WR
C. maxima
WR
NONSP
WR
NONSP
WR
WR
WR
WR
S. tuberosum
WR
WR
NONSP
NOAMP
NOAMP
NONSP
NONSP
NOAMP
A. graveolens
WR
WR
NONSP
WR
NOAMP
NONSP
NONSP
NOAMP
A. cepa
NOAMP
NONSP
NONSP
NOAMP
NOAMP
NOAMP
NONSP
NOAMP
B. oleracea
NOAMP
NONSP
NONSP
NOAMP
NOAMP
NONSP
NOAMP
NOAMP
WR
NOAMP
NOAMP
NOAMP
NONSP
NOAMP
NONSP
NOAMP
CMTp176
M AN U
TE D
S. lycopersicum
CMTp142
CMTp257
RI PT
CMTp69
SC
Table 3: Transferability of the SSRs in other plant species.
CMTp260
CUTC022867
AC C
EP
Legend: NONSP: nonspecific PCR products; NOAMP: no PCR amplification; WR: within-range PCR amplicon (see Table 2 for the allelic size range considered).
25
ACCEPTED MANUSCRIPT Table 4: Genotype frequency of the SSR profiles of the two identified processed food products. For each locus, the table reports the frequency of the alleles in the genotypes of the zucchini plant varieties under investigation (n=90) and the expected frequency of the genotype. For each locus, the table also reports the number of alleles and the observed genotype in our population over the theoretical number of genotypes possible [(n x (n+1))/2]. Identified Sample
Population
Allele I
Allele II
Expected
frequency
frequency
Genotype
Alleles
Observed/Possible
RI PT
Locus
genotypes
frequency 0.664
0.664
0.415
5
CMTp98
0.878
0.878
0.770
2
CMTp132
0.767
0.767
0.588
CMTP142
0.617
0.617
0.380
CMTp176
0.817
0.817
CMTp257
0.426
0.148
CMTp260
0.506
0.506
CUTC022867
0.600
0.333
6/15 3/3
SC
CMTp69
5/6
4
8/10
M AN U
3
2
3/3
0.126
6
9/21
0.123
4
8/10
0.400
3
6/6
AC C
EP
TE D
0.667
26
ACCEPTED MANUSCRIPT Supplementary Table 1: Plant varieties under investigation and their main features Fruit general shape
Fruit colour (intensity)
Altea Anissa Asso Aurore Aymaran Black Beauty Cavili Coucourzelle De Nice à fruit rond Genovese Genovese Antico Giulia Gulliver Lanka Mikonos Milos Ontano Parthenon President Quine Rhodos Rigas Romanesco San Pasquale Sitos Syros Temprano de Argelia Vertre noir maraîchère Virginia Vitulia
cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical tapered cylindrical globular tapered cylindrical tapered cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical cylindrical tapered cylindrical cylindrical tapered cylindrical cylindrical
grey green (dark) green (medium) green (dark) green (very light) green (dark) green (very light) grey green (very light) green (very light) green (very light) green (light) green (medium) green (light) green (medium) green (medium) grey green (dark) green (medium) green (dark) green (medium) grey green (very light) grey green (light) green (dark) green (very light) green (dark) green (very light) green (light)
SC
M AN U
TE D
EP
AC C
Legend: H: hybrid; OP: open-pollinated variety.
27
Type H H H H H OP H OP OP OP OP H H H H H H H H H H H OP OP H H OP OP OP H
RI PT
Variety
ACCEPTED MANUSCRIPT Supplementary Table 2. SSR loci employed in this study and their main features.
Primer label (forward)
GCAGAGGAGAAGTGGGTTTG CTTTATCCGACCAAGCGTTC
(AAG)9
6-FAM
CMTp142
TCAACCAAGTGCCAATCTCA ACTGATCCACCGACTGATACG
(TC)12+5
VIC
CMTp257
CACGAAGATTTGATGGCCTTA GGATTGGGATGGTGAAGATG
(CGT)11
PET
CMTp260
CCCTAGACCCATCATAGTCG ACATTTGGTTACTTCCCCATT
(CAT)7
NED
CMTp69
ATACTTGCTCCCCAAGTTTA AAATAAAAAGACAACGTAATGGT
(TATT)4
VIC
CMTp176
CCTGGACTTCCACATCAGTT ACTACGTGTCTCTGCAGGAAG
(TC)12
6-FAM
CMTp132
CCATTTCCATTTCCATTTCA AGGTTAGAAACAGGGGGAATC
CUTC022867
TTGGACAATCTGAGGAAGTTGG TTGGACAATCTGAGGAAGTTGG
SC
CMTp98
AC C
EP
TE D
M AN U
Primer sequences (5' to 3')
RI PT
core
Locus SSR
28
(GAT)12
NED
(AGC)8
PET
ACCEPTED MANUSCRIPT Supplementary table 3: Primers employed for the amplification of the Elongation Factor 1 alpha gene.
Primer sequence (5’ to 3’)
GC-EF1pepo-RVa
CACGAACAGCAAAACGACCC
GC-EF1pepo-RVb
CTTGGTCACCTTTGGCTCCC
GC-EF1pepo-FW
GTATTGCCACACCTCCCCAC
EF1A-FW
ATTCGAGAAGGAAGCTGCTG
EF1A-RV
TTGGTGGTCTCAAACTTCCAC
AC C
EP
TE D
M AN U
SC
RI PT
Primer
29
ACCEPTED MANUSCRIPT Supplementary Table 4: Descriptive statistics of the random match probability (RMP) values for an increasing number of SSR loci. The RMP values for the population under investigation were obtained considering the combinations (without repetition) from 1 to 8 SSR loci. Descriptive statistics were then obtained using the summary() function in R. IQR: Interquartile Range. . Number of SSR loci 2
3
4
5
6
7
8
RI PT
1 1.37E-03
6.77E-06
1.20E-07
0.00E+00
7.30E-09
4.26E-09
0.00E+00
2.19E-09
1st Quartile
1.23E-01
1.98E-02
3.32E-03
5.76E-04
1.04E-04
1.93E-05
3.78E-06
5.24E-07
Median
3.60E-01
7.97E-02
1.86E-02
4.05E-03
8.71E-04
1.85E-04
4.30E-05
8.11E-06
Mean
3.60E-01
1.28E-01
4.51E-02
1.49E-02
5.75E-03
2.08E-03
7.49E-04
2.67E-04
3rd Quartile
5.88E-01
2.08E-01
5.74E-02
1.67E-02
5.32E-03
1.53E-03
4.05E-04
1.11E-04
Maximum
1.00E+00
7.70E-01
5.14E-01
3.02E-01
1.25E-01
5.02E-02
1.91E-02
4.88E-03
IQR
4.65E-01
1.88E-01
5.41E-02
4.01E-04
1.10E-04
M AN U
SC
Minimum
AC C
EP
TE D
1.61E-02
30
5.21E-03
1.51E-03
ACCEPTED MANUSCRIPT Figure legends Figure 1 Hierarchical clustering (UPGMA algorithm) of the C. pepo varieties based on Nei’s genetic distance. The dendrogram shows that the 30 cultivars analyzed were discriminated.
RI PT
Figure 2 Amplificability of DNA isolated from commercial products. (A) Scheme of the annealing of the primers to the Elongation Factor 1-alpha gene (not to scale). (B) PCR with the EF1A-FW and EF1A-RW primers; (B) PCR with the GC-EF1A-pepo-FW GC-EF1Apepo-RVb; (C) PCR with the GC-
SC
EF1Apepo-FW and GC-EF1Apepo-Rva. 1: 1 kb + DNA ladder (ThermoFisher); 2: water negative control; 3: positive control (leaf DNA); 4: cylindrical fruit; 5: mixed vegetables; 6: frozen zucchini; 7:
M AN U
chargrilled zucchini; 8: fried zucchini. See table 1 for a description of the commercial products. Figure 3 Agarose gel electrophoresis of PCR reactions with the CMTp260 primers using the DNA isolated from different commercial food products. 1: 1 kb DNA ladder (Thermo Fisher); 2: water
TE D
negative control; 3: positive control (leaf DNA); 4: cylindrical fruit; 5: rounded fruit; 6: mixed vegetables; 7: frozen zucchini; 8: chargrilled zucchini; 9: fried zucchini. See table 1 for a description of the commercial products
EP
Figure 4 Box and whisker plot of the random match probability (RMP) values of the genotypes
AC C
under investigation as function of an increasing number of SSRs (considering all the combinations without repetition of different number of loci). To increase readability, RMP values are displayed in logarithmic scale.
Supplementary Figure 1 Examples of electrophoretic profiles obtained in the SSR transferability test. Panel A and B are an example electropherograms classified as «no amplification» (A: CMTp69 amplification of cabbage DNA; B: CMTp69 amplification of onion DNA). Panel C and D are an example of electropherograms classified as «nonspecific amplification» (C: CMTp98 amplification 31
ACCEPTED MANUSCRIPT of pea DNA; D: CMTp98 amplification of pumpkin DNA). Panel E and F are an example of electropherogram classified as “within range” (E: CMTp69 amplification of cucumber DNA; F: CMTP69 amplification of pumpkin DNA). Panel G and H are an example of electropherograms obtained with zucchini DNA using the CMTp69 primers. In each panel, the allelic bar is present at
RI PT
the top, while in the squares below the peaks it is reported the allelic dimensions (at the second decimal digit; sz) and peak height (Ht) in relative fluorescence units. The different colours are selected by the analysis software (GeneMapper v.4.0) according to the fluorochrome of the
AC C
EP
TE D
M AN U
SC
primer.
32
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT
Highlights
•
We used SSR markers for DNA typing of zucchini varieties in commercial products encompassing different levels of food processing We assessed SSR transferability in closely related Cucurbits and other horticultural species
•
DNA typing identified the zucchini varieties in two commercial products
•
We provide indications for the statistical interpretation of the observed genetic
RI PT
•
SC
concordance
AC C
EP
TE D
M AN U
• The identified matches cannot be attributed to chance alone