Berry fruits have been implicated in the lessening or prevention of diseases, and account for a large percentage of the fruits consumed as part of the human diet [1]. Berry fruits are also widely used in processed and derived products, including dried and canned fruits, yogurt, drinks, jams and jellies, as well as fresh and frozen fruits [2]. It has been amply demonstrated that berry fruits contain antioxidant and anti-inflammatory polyphenols, such as anthocyanins and phenolic acids, which play an important role in aging [3] and the prevention and treatment of cardiovascular disease [4] and cancer [5]. Therefore, consumption of berry fruits has been rapidly increasing worldwide.

Food fraud, which exploits food buyers for economic benefit, has a long history. The United States Grocery Manufacturers Association estimates that food fraud costs the global food industry $10–$15 billion annually, affecting about 10% of all sold commercial foods [6]. In response, various technologies incorporating molecular markers and biochemical analysis as two examples have been developed for prevent food fraud involving plants, such as saffron [7], orange [8], Orostachys japonica [9], and Cynanchum wilfordii [10]. However, prevention of food fraud for berry fruits is relatively unexplored. In general, chemical analysis is time-consuming and has limitations related to repeatability and reproducibility [11]. As an alternative to chemical assays, DNA-based assays are considered excellent tools for the identification of plant species in commercial foods. However, research on the classification of berry fruit based on DNA is also scant. DNA-based methods for detecting contamination with berry fruits in commercial foods are needed.

Chloroplast genes are generally present in hundreds of copies per cell, and chloroplast genomes are protected from decomposition during food processing since they are enclosed by two membrane layers [12]. Thus, chloroplast genomes have been widely used in plant species identification to develop species-specific detection methods [13] as well as in evolutionary studies. In particular, the chloroplasts maturase K (matK) and RubisCO large-subunit genes (rbcL) have proven to be excellent for DNA barcoding-based species identification [14, 15]. The use of DNA barcoding for plant species identification has been studied [16, 17]. In addition, the trnLtrnF region is frequently used along with matK and rbcL for DNA barcoding-based species identifications due to the extensive polymorphisms among species [18, 19].

DNA-based polymerase chain reaction (PCR) analyses have been widely used for preventing food fraud because of its economic and timesaving advantages compared to biochemical analyses. In particular, the high accuracy and sensitivity of quantitative real-time PCR (qPCR) assays could enable the detection of very low levels of target DNA in commercial foods. In this study, we developed four berry fruit species-specific molecular markers using DNA polymorphisms of chloroplast genes with the aim of utilizing the markers to prevent food fraud, and verified their application in commercial berry fruit food products.

Materials and methods

Sample preparation

Four species of berry fruits were used (Table 1): aronia (Aronia melanocarpa), blackberry (Rubus fruticosus), cranberry (Vaccinium macrocarpon), and strawberry (Fragaria × ananassa). All were purchased from Korea plant nursery (, Taean, Korea). A total of 18 commercial berry fruit products were purchased from local or oversea markets (Table 1).

Table 1 Commercial berry products used in this study

Genomic DNA extraction

Genomic DNAs of all fruit leaves and commercial products were extracted using the i-genomic Plant DNA Extraction Mini Kit (iNtRON Biotechnology, Seongnam, Korea) according to the manufacturer`s protocol. Extracted genomic DNA concentration was measured using a Qubit® 2.0 Fluorometer (Invitrogen, Life Technologies, Grand Island, NY, USA) with a Qubit dsDNA BR Assay Kit (Invitrogen). The amplification capacity of the extracted DNA was assessed with universal plant primer pairs that target a conserved 18S rRNA nuclear region [20].

Sequence alignment and primer design

Three chloroplast gene regions (matK, rbcL, and trnL-F) were used to develop species-specific molecular markers. All berry fruit chloroplast sequences were downloaded from the National Center for Biotechnology Information (NCBI, Downloaded chloroplast sequences were aligned using ClustalW2 ( and Software Bio-edit 7.2 (Ibis Biosciences, Carlsbad, CA, USA). The species-specific primer pairs were designed using Beacon Designer™ (PRIMER Biosoft, Palo Alto, CA, USA). All designed primer sets were synthesized by a commercial service (Macrogen, Seoul, Korea). The primer sequences used in this study are listed in Table 2.

Table 2 Information of developed primers used in this study

Real-time PCR analysis

qPCR was carried out in a final volume of 20 µL using a CFX Connect™ Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) with SYBR Green dye. The reaction mixture consisted 10 µL of SYBR® Green TOP real qPCR 2xPreMIX (Enzynomics™, Daejeon, Korea), 10 ng of genomic DNA and 10 pmol of each primer sets, with adjustment to a final volume of 20 μL with PCR-grade water. The experiment conditions were as follows: 10 min at 95 °C, followed by 45 cycles of 10 s at 95 °C, annealing at the appropriate annealing temperature (Tm) and time of each primer pair, and 30 s at 72 °C. The PCR products were denatured at 95 °C for 10 s and then annealed at 65 °C for 5 s. This step was followed by a melt-curve analysis at temperatures ranging from 60 to 95 °C. For sensitivity analysis, fruit leaf DNAs of each species were diluted tenfold into five series (0.001–10 ng/μL) and used for real-time PCR. In addition, extracted each commercial product DNAs was quantitated to 10 ng and used for real-time PCR.

Cloning of PCR amplicons

To identity PCR products amplified from the correct target regions, they were cloned using commercial product RBC T&A Cloning Vector (Real Biotech Corporation, Taipei, Taiwan) and a ligation mix (TaKaRa Bio, Shiga, Japan) according to the manufacturer’s protocol. Conventional PCR was performed using TaKaRa Ex Taq™ DNA polymerase (TaKaRa Bio). PCR reaction was performed with an initial denaturation 5 min at 95 °C, followed by 35 cycles of 10 s at 95 °C, 30 s at Tm °C (each primer), 1 min at 72 °C, and finally 5 min at 72 °C. Then, the amplicon was cloned into the T&A Vector and plasmid DNA was purified using the Plasmid Mini-Prep Kit (Elpis Biotech, Daejeon, Korea). Nucleotide sequences were analyzed by a commercial service (Macrogen).

Determination of amplification efficiency, correlation coefficient, and limit of detection (LOD)

To evaluate the correlation between DNA concentration and cycle threshold (Ct), standard curves were obtained using tenfold diluted DNA samples of the four berry fruits species at concentrations of 0.001–10 ng. The correlation coefficient (R2) was determined by using the linear regression method (R2 ≥ 0.98) [21]. The amplification efficiency was calculated on the basis of the standard curve using the equations E = 10−1/slope, and efficiency (%) = (E−1) × 100. The LOD was regarded as the analytical concentration at which the method detected the presence of a target gene in at least 95% of true-positive biological samples (< 5% of false-negative results) [22].

Results and discussion

Species-specific qPCR primers design

Three chloroplast gene sequences (matK, trnL-F, and rbcL) of the four berry fruits were obtained from NCBI. The chloroplast sequences were aligned using ClustalW2 to identify single nucleotide polymorphisms (SNPs) or InDels (insertions and deletions) among the four berry fruits. A host of SNPs and/or InDels were found in each of three genes among the sequences (Additional file 1: Fig. S1), suggesting that the differences could be useful for designing the species-specific primers.

Species-specific primers were designed using a commercial program based on SNPs or InDels of the berry fruit cpDNA sequences. Since DNA of foods tends to be degraded into short fragments during food processing steps, such as heat treatment, small PCR products are better amplified compared to large PCR products in processed foods [23]. Therefore, we designed eight species-specific primer pairs that could amplify short amplicons of 94–224 bp to detect target species in processed foods (Table 2). All species-specific primers were designed based on two or more SNPs to clearly distinguish each berry fruit (Additional file 1: Fig. S1).

Evaluation of the amplification efficiency and sensitivity of the species-specific primers

We evaluated the efficiency and sensitivity of the developed primers for qPCR analyses using tenfold serially diluted DNA (10–0.001 ng) of each fruit and examining individual statistical measurements using a regression analysis. The quality of extracted DNAs of each fruits was first evaluated by qPCR using universal plant primer pairs [20]. The 18S rRNA was efficiently amplified in all samples, with Ct values in the range of 14.12–14.35. Then, efficiencies of all species-specific primers were confirmed to be in the range of 88–108% with a strong correlation coefficient (R2 > 0.99) for the target species (Table 3). In addition, the slopes of the linear equations for the target species ranged from − 3.13 to − 3.63. However, the correlation coefficient of non-target (other) species was not evident in all the developed primer pairs (Fig. 1). These results suggest that the developed primer pairs could be very suitable for detecting the target species. To confirm whether the PCR amplicons were derived from the correct target regions, the products were cloned and sequenced. No differences were found between both sequences NCBI deposited and amplified by the primer (Additional file 1: Fig. S2). Subsequently, target-specificities of the developed primers were evaluated using end-point PCR (30 cycles) and the amplicons were visualized by agarose gel electrophoresis (Fig. 2a). All PCR products were amplified with each of the desired size in the genomic DNA. In addition, sharp peaks were obvious for the target species in PCR products amplified with each of the developed primer pairs (Fig. 2b). These findings suggest that the develop primer pairs could be useful for distinguishing between the four berry fruit species.

Table 3 Slope, correlation coefficient, efficiency, and Ct values obtained by qPCR assay using the developed primers
Fig. 1
figure 1

Standard curves obtained by analyzing serially diluted DNAs of the four berry fruits. The standard curves were obtained on the basis of efficiency and correlation of coefficient (R2) of DNA extracted from the plant leaves. The x-axis and the y-axis represent log DNA concentration and Ct value, respectively

Fig. 2
figure 2

a PCR products (30 cycles) of each species-specific primer sets were electrophoresed to confirm cross-reactivity, b melt peak analysis to confirm amplification of a single PCR amplicon. M, 1 kb Plus DNA ladder marker; Lane 1, aronia; Lane 2, blackberry; Lane 3, cranberry; Lane 4, strawberry

Application of the primers to commercial food products of berry fruits

To gauge the applicability of the developed primer pairs, 18 commercial products were purchased from local or oversea markets and then tested. Prior to applying the commercial foods, the universal primers were used to test whether the DNA extracted from the food products were suitable for the qRT-PCR assay. Results of the qPCR analysis with the universal plant primer pairs (18S rRNA amplification) showed low Ct values in the range of 12.83–17.15 for all products, indicating that the quality of the extracted DNA was suitable for further assays.

Based on qPCR results, Ct values of the 18 commercial products were determined (Table 4). All Ct values amplified with target primers were lower than the LOD (10 pg Ct values). However, Ct values with non-target primers were higher than the LOD. Our results for all 18 commercial products were consistent with the indicated ingredients, suggesting that the developed primer pairs would be useful to detect the target berry species in commercial foods.

Table 4 The amplified Ct values of 18 commercial berry food products by qPCR using the developed primer sets

Fruits are commonly processed to fruit juices. The market sectors for fruit juices have been rapidly growing. Therefore, highly priced fruit juices have been targets for food adulteration and fraud [24]. Since the most frequent profit-procedures are simple dilution with water, the addition of sugar or cheap alternatives, a host of non-targeted high-performance liquid chromatography-mass spectrometry metabolomics fingerprinting techniques coupled with chemometric analysis have been developed for the juice-type food authenticity testing [24]. Since the impact of berry fruits intake on human health, performance, and disease as superfoods have been firmly established, they have been commonly consumed worldwide in fresh and processed forms, such as dried powders and teas [5]. Therefore, alternative detection technologies would be useful for detection of berry fruit adulteration and fraud.

SYBR Green-based qPCR analysis is a useful tool for the detection and quantification of species-specific nucleotides. This method is faster and more stable than other chemical assays [25]. SYBR Green-based techniques can detect other plant species in processed foods, such as hazelnuts [26], almonds [27], DNA allergens [28], and C. wilfordii and C. auriculatum [10]. In this study, we report the development of a DNA-based SYBR Green qPCR assay for rapid and sensitive species-specific detection (up to 10 pg DNA) of four berry fruits. In additional, the markers were applied successfully to 18 commercial berry fruit foods. The developed molecular markers could be useful for detection of food fraud and adulteration in commercial berry fruits foods markets.