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. 2020 Feb 26;15(2):e0228624. doi: 10.1371/journal.pone.0228624

Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR

Jia Chen 1, Yalun Zhang 2, Chen Chen 2, Yan Zhang 2, Wei Zhou 2,*, Yaxin Sang 1,*
Editor: Evangelia V Avramidou3
PMCID: PMC7043801  PMID: 32101546

Abstract

We report a rapid and accurate quantitative detection method using droplet digital PCR (ddPCR) technology to identify cassava adulteration in starch products. The ddPCR analysis showed that the weight of cassava (M) and cassava-extracted DNA content had a significant linear relationship—the correlation coefficient was R2 = 0.995, and the maximum coefficient of variation of replicates was 7.48%. The DNA content and DNA copy number (C) measured by ddPCR also had a linear relationship with R2 = 0.992; the maximum coefficient of variation of replicates was 8.85%. The range of cassava ddPCR DNA content was 25 ng/μL, and the formula M = (C + 32.409)/350.579 was obtained by converting DNA content into the median signal. The accuracy and application potential of the method were verified using the constructed adulteration model.

1. Introduction

Starch is a staple and major source of calories and is often used in modern food industries. The most common types of starch in China are potato, sweet potato, cassava, corn, and wheat as defined by the China National Standard for Starch Products GB 2713–2015. The price difference is due to the availability of raw materials and the cost of production. These price differences can lead to starch adulteration [1]. Adulteration not only causes economic loss to customers but can also lead to risks of food allergy. Cassava starch is the main material in adulteration of more expensive starches, and sensitive detection techniques are thus needed to detect and deter adulteration [2]. The detection of starch mainly includes sensory tests as well as physical and chemical tests. However, these test methods are time-consuming and labor-intensive and cannot measure the extent of adulteration. Accurately identifying the degree of adulteration is difficult. Establishing a precise, rapid, and effective quantitative analysis method is thus very important.

Molecular biology can help identify adulterants via multiplex PCR, fluorescent PCR, digital PCR (ddPCR), and other PCR technologies [3]. These tools are Sensitive, fast, and useful in food science [4]; they have gradually replaced colorimetric detection methods, but these applications cannot accurately quantify adulterants in processed starches [5–6].

At the end of the 20th century, Brunetto et al. [7] proposed the concept of digital ddPCR, which distributes sample DNA evenly into a large number of reaction units and then independently performs PCR amplification on each reaction unit. The ddPCR can obtain a DNA copy number without reference to standard curve or control gene [8–10]. ddPCR offers good sensitivity, high precision, and absolute quantification. It has been analyzed in terms of copy-number variation [11,12], transgenic properties [13,14], single nucleotide polymorphisms [15], gene expression analysis [16], and microbial detection [17,18]. This technology has important application prospects because of its quantitative nature.

Here, the relationship between cassava weight and the extraction efficiency of cassava starch (i.e., tapioca) DNA was first studied. Specific primers for a cassava gene were then designed, and ddPCR technology was used to quantify the DNA and establish the relationship between extracted DNA concentration and amplified DNA copy number. This established a formula for calculating cassava weight from the copy number. A adulteration model of sweet potato and cassava was constructed to explore the applicability of this method via 50 different commercially available starch verification methods. Finally, a rapid, accurate, and quantitative detection method for cassava adulterants was constructed to complement the quantitative testing technology of cassava in starch.

2. Methods

2.1. Test materials

Sweet potato starch and tapioca were obtained from a food-processing plant (Convenience Farmer's Comprehensive Market, Nanchang Street, West Bridge District, Shijiazhuang, Hebei, China). In addition, 2 × ddPCR supermix for probes, droplet generation oil, and droplet reader oil were purchased from Bio-Rad. Primers were synthesized by Shanghai Bioengineering Co., Ltd. A deep processing food DNA extraction kit (Tiangen Company) as well as analytically pure isopropanol and anhydrous ethanol were purchased from Beijing Luqiao Company.

2.2. Experimental methods

2.2.1. DNA extraction

DNA extraction starch product was performed according to the manufacturer’s instructions. Here, 100 mg of the sample was added to 500 μL of buffer GMO1 and 20 μL of proteinase K (20 mg/mL); this was vortexed for 1 min. The solution was then incubated at 56°C for 1 h and oscillated every 15 min during the incubation. Next, 200 μL of buffer GMO2 was added and mixed well and vortexed for 1 min with 10 min of subsequent incubation at room temperature. The solution was then centrifuged at 12,000 rpm for 5 min, and the supernatant was aspirated into another centrifuge tube. Next, 0.7 mL of isopropanol was added to the supernatant and mixed well. The solution was then centrifuged at 12,000 rpm for 3 min to remove the supernatant and retain the pellet. We then added 700 μL of 70% ethanol, vortexed for 5 s, centrifuged at 12,000 rpm for 2 min on a centrifuge, and removed the supernatant. This was repeated a second time. We then opened the lid in the biosafety cabinet for 20 min to thoroughly dry the residual ethanol. Next, 20–50 μL of elution buffer TE was added and vortexed for 1 min to obtain a DNA solution. The quantity and purity of DNA were determined via a nucleic acid analyzer (NanoDrop 2000 by Thermo).

2.2.2. Reaction primer design

Primers were designed using the primer design software DNAman and Primer Premier 5.0. The cassava-specific primer sequence was designed based on the intergenic spacer of chloroplast trnL-trnF sequence—this is one of the most frequently used molecular markers of plants [19] (GenBank: EU518905.1) [20] (Table 1).

Table 1. Cassava gene primer sequence.
F-Primer 5′-3′ R-Primer 5′-3′ Probe
Cassava GGGGGATAGGTGCAGAGACT AAAAATACGGATTTGGGCCCCT FAM- TGGAGTTGACTGCGTTGCATTAGT-TAMRA
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2.2.3. ddPCR reaction system

Here, a 20 μL amplification system was used that contained 10 μL 2 × ddPCR supermix; the forward primer concentration was 10 μmol/L (1.2 μL used), and the reverse primer concentration was 10 μmol/L (1.2 μL used). The concentration was 10 μmol/L (0.4 μL used) with 4.0 μL of DNA template. The balance was ddH2O. Sterile ddH2O was used as a blank control.

2.2.4. Main operating procedures for ddPCR reactions

The fully mixed PCR reaction system was transferred to a droplet-generating card (Bio-Rad); 70 μL of the droplet-generation oil was added to the droplet-generating card, and the droplets were carded into a droplet generator (Bio-Rad) for reaction. The resulting droplets were then transferred to 96 wells of ddPCR, and the 96-well plates were sealed to prepare for the PCR reaction.

The program for the reaction denaturation was as follows: 95°C, 10 min; 94°C denaturation, 1 min; 56°C annealing, 45 s; 40 cycles; 98°C, 10 min; and 4°C for temporary storage.

After the ddPCR reaction was completed, the 96-well plate was placed in the QX200 Droplet Reader (Bio-Rad), and the sample information was sequentially input. At the beginning of the test, the instrument automatically recognizes the droplets of each sample in sequence, and the droplets were sequentially passed through two-color detection via the droplet-reading oil. The positive and negative results were determined based on the intensity of the fluorescent signal emitted by the droplets, and the number of positive and negative droplets per sample was recorded. The results were calculated using Quantasoft software after signal acquisition was completed.

2.2.5. Specific detection of cassava DNA by ddPCR

The primers specific to cassava were used to digitally amplify the genomic DNA of starch from sweet potato, cassava, potato, corn and sesame, walnut, soybean, hazelnut, beef, mutton; sterile ddH2O was used as a blank control to determine the specificity of the primer. The experimental system and operating procedures are shown above 2.2.3 and 2.2.4.

2.2.6. Determination of conversion formula between cassava weight and the copy number of ddPCR

2.2.6.1. Cassava weight and extracted DNA concentration. First, 5–100 mg of cassava samples was weighed for DNA extraction and three replicates were performed to ensure the repeatability of the experiment. They were then evaluated with Nanodrop 2000. We then established the relationship between the weight of the sample and the amount of DNA finally extracted.

2.2.6.2. Establishment of the relationship between the copy number from ddPCR and the concentration of cassava DNA. We first evaluated the relationship between copy number and DNA concentration as well as the proportion and weight of adulterated substances. The extracted DNA was diluted to a gradient of 1, 5, 10, 15, 20, and 25 ng/μL. This was then amplified and detected using ddPCR technology. Sterile ddH2O was used as a blank control. The experimental system and operating procedures are shown above in 2.2.3 and 2.2.4.

2.2.7. Construction of an adulteration model of sweet potato and cassava

An artificially constructed adulteration model of sweet potato and cassava was used to simulate the adulteration of other starch products with tapioca. This was used to evaluate ddPCR technology as a tool to identify cassava adulteration. Sweet potato starch and tapioca were mixed in different ratios for DNA extraction (Table 2). Then, DNA was extracted from 10 mg of the mixed starch samples, and 4 μL of extracted DNA was used in ddPCR. The correlation between the weight and DNA copy number of tapioca was calculated using Origin 8.6 to obtain a formula for calculating the cassava weight from the DNA copy number. The measured values of cassava weight based on this formula were compared with the actual values of cassava weight to evaluate the practical utility of this method.

Table 2. Artificially simulate the adulteration of cassava starch in sweet potato starch.
Sample A:Ba A:B A:B A:B A:B A:B A:B A:B A:B
Mass (mg) 90:10 80:20 70:30 60:40 50:50 40:60 30:70 20:80 10:90
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a A is cassava, and B is sweet potato.

2.2.8. Commercial sample inspection

To further verify the practical utility of this method, 50 different brands of starch were purchased from large supermarkets and farmers’ markets including 30 products of sweet potato starch, 12 products of potato starch, and 8 products of corn starch. Each sample was analyzed three times by ddPCR as described above.

3. Results

3.1. Specific detection of ddPCR

The cassava-specific primers were used with sweet potato, cassava, potato, corn, sesame, walnut, soybean, hazelnut, beef, and mutton. Primers were specific with no cross-reactivity with other starches tested (Fig 1). This has value in subsequent detection.

Fig 1. Validation of the specificity of cassava primers.

Fig 1

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The specificity of cassava primers were tested using the following samples: 1, beef; 2, lamb; 3, hazelnut; 4, soybean; 5, walnut; 6, sesame; 7, corn starch; 8, potato starch; 9, cassava starch; 10, sweet potato starch; and 11, ddH2O.

3.2. Determination of the conversion formula between the weight of cassava and the copy number of ddPCR

3.2.1. Cassava weight and extracted DNA concentration

Eleven weight groups ranging from 5.0 to 100.0 mg of tapioca (Table 3). The maximum coefficient of variation of replicates was 7.48%, which is much lower than the specified requirement coefficient of variation of 15%. This suggests that the data were stable and reliable. The average of the three replicates of the extracted DNA results was linearly fitted to the cassava weight and found to be linear (Fig 2); the correlation coefficient R2 was 0.995.

Table 3. Cassava DNA extraction results.
Sample name Mass (mg) DNA content (ng/μL) Average value (ng/μL) Coefficient of variation (%)
#1 #2 #3
Cassava 5.0 6.2 6.1 5.7 6 4.41
10.0 13.1 11.4 12.5 12.3 6.99
20.0 26 23.5 25.4 25 5.23
30.0 44.3 40.7 38.8 41.3 6.77
40.0 53.7 56.9 54.5 55 3.03
50.0 68.4 63.3 68.1 66.6 4.30
60.0 80.8 82.3 71.5 78.2 7.48
70.0 93.3 88.2 92.8 91.4 3.07
80.0 110.8 100.5 99.8 103.7 5.94
90.0 122.1 114.2 107.5 114.6 6.38
100.0 139.5 132.8 144.8 139 4.33
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Fig 2. Correlation between tapioca dry weight and extracted DNA.

Fig 2

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3.2.2. Detection of the relationship between the copy number of ddPCR and the concentration of cassava DNA

The extracted DNA was diluted to a gradient of 1, 5, 10, 15, 20, and 25 ng/μL; there were three replicates for each concentration, and 4 μL of DNA was used for ddPCR. The results are shown in Table 4. The copy number of cassava increased with increased DNA content. There was a significant linear relationship. The coefficient of variation was 8.85%, and this was far below the coefficient of variation required by the regulations. The average copy number and DNA content of the three replicates were linearly fitted (Figs 3 and 4) with a correlation coefficient R2 of 0.992.

Table 4. Cassava copy number under gradient DNA content.
Sample name DNA content (ng/μL) Copy number (copies/μL) Average value (copies/μL) Coefficient of variation (%)
#1 #2 #3
Cassava 1 289 326 294 303 6.63
5 1739 1797 1566 1700.7 7.07
10 2510 2896 2970 2792.3 8.85
15 4147 3567 3936 3883.3 7.56
20 4939 5649 4973 5186.7 7.72
25 7533 6327 6970 6943.3 8.69
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Fig 3. Correlation between the content and copy number of cassava starch DNA.

Fig 3

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DNA concentration was measured by NanoDrop 2000 and DNA copy number was determined by ddPCR.

Fig 4. Relationship between cassava DNA content and copy number.

Fig 4

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3.2.3. Determination of the relationship between the weight of cassava and the copy number of ddPCR

There was a significant linear relationship between the weight of cassava (M) and the content of extracted cassava DNA. And there was a certain linear relationship between the DNA content and DNA copy number (C) of cassava. Using the cassava DNA content as the intermediate conversion value, the formula is obtained for the cassava quality and the cassava DNA copy number (Table 5). The formula is M = (C + 32.409)/350.579 where M is the cassava mass (mg), and C is the amplified DNA copy number (copies/μL).

Table 5. Establishment of cassava dose response curve.
Linear curve formula R2
CDNA = 1.333M − 0.643 0.995
C = 263.0 CDNA + 136.7 0.992
M = (C + 32.409)/350.579
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CDNA = DNA concentration, C = Copy numbers, M = cassava mass

3.3. Method validation—Construction of sweet potato and cassava adulteration model

The cassava and sweet potato starch were mixed at ratios of 1:9 to 9:1 to a total of 100 mg. DNA was extracted from 10 mg of mixed starch samples, and 4 μL was taken for ddPCR. The amplification results are shown in Fig 5. The results (Table 6) show that the coefficient of variation between copy numbers was 7.54%, which is much lower than the coefficient of variation required by the regulations. The weight of the cassava in the combined sample was consistent with the actual weight, and the maximum relative error value was 10.2%. This was also within the specified error range. The accuracy and precision of the ddPCR method established here were thus verified using the sweet potato and cassava adulteration model. This suggests that the method can detect cassava in commercial starch products.

Fig 5. Copy number of cassava and sweet potato ratio.

Fig 5

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Channels 1–3: starch mixture containing 90% cassava starch; channels 4–6: starch mixture containing 80% cassava starch; channels 7–9: starch mixture containing 70% cassava starch; channels 10–12: starch mixture containing 60% cassava starch; channels 13–15: starch mixture containing 50% cassava starch; channels 16–18: starch mixture containing 40% cassava starch; channels 19–21: starch mixture containing 30% cassava starch; channels 22–24: starch mixture containing 20% cassava starch; channels 25–27: starch mixture containing 10% cassava starch; and channel 28: sterile double-distilled water.

Table 6. Analysis results of cassava with known adulterants.

Number Cassava mass (mg)a DNA Copy number (copies/μL) Average value (copies/μL) Coefficient of variation (%) Measured cassava mass (mg) Relative error (%)
1 10.0 320.9 347.2 309.3 325.8 5.96 10.22 2.2
2 20.0 701 704 668 691 2.89 20.63 3.15
3 30.0 878 961 972 937 5.48 27.65 −7.83
4 40.0 1495 1635 1409 1513 7.54 44.08 10.2
5 50.0 1723 1715 1581 1673 4.77 48.65 −2.7
6 60.0 2309 2087 2255 2217 5.22 64.16 6.93
7 70.0 2439 2504 2248 2397 5.55 69.3 −1
8 80.0 2838 2629 2822 2763 4.21 79.74 −0.32
9 90.0 3173 3318 3490 3327 4.77 95.82 6.47
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a The total mass-of the cassava and sweet potato starch mixture was 100 mg.

3.4. Detection of commercially available samples

Fifty different brands of starch were studied using the ddPCR method (Figs 6–10). The total starch weight used was 10 mg, and 4 μL of extracted DNA was taken for ddPCR. The average value of three replicate experiments was calculated (Table 7). The highest ratio of cassava adulteration in sweet potato starch was 37.38%, and 11 of the 30 sweet potato starch products had cassava adulteration. The highest measured cassava adulteration in potato starch was 9.65%, and 11 of the 30 sweet potato starch products had cassava adulteration. The highest ratio of cassava adulteration in corn starch was 10.37%, and there were 2 out of 8 samples with cassava adulteration. These results show that cassava adulteration can be quantitatively identified.

Fig 6. Actual test of commercially available samples.

Fig 6

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Channel 1–3: sample1; channel 4–6: sample2; channel 7–9: sample3; channel 10–12: sample4; channel 13–15: sample5; channel 16–18: sample6; channel 19–21: sample7; channel 22–24: sample8; channel 25–27: sample9; channel 28–30: sample10; channel31 negative; channel32 positive.

Fig 10. Actual test of commercially available samples.

Fig 10

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Channel 1–3: sample41; channel 4–6: sample42; channel 7–9: sample43; channel 10–12: sample44; channel 13–15: sample45; channel 16–18: sample46; channel 19–21: sample47; channel 22–24: sample48; channel 25–27: sample49; channel 28–30: sample50; channel31 negative; channel32 positive.

Table 7. Analysis of commercially available samples.

Sample name Number Copy number (copies/μL) Average value (copies/μL) Adulteration mass ratio (%)
#1 #2 #3
Sweet potato starch 1 331 348 305 328 10.28
2 237.1 233.5 262 244.2 7.89
3 0 0 0 0 0
4 0 0 0 0 0
5 0 0 0 0 0
6 0 0 0 0 0
7 186 193.1 190.6 189.9 6.34
8 0 0 0 0 0
9 0 0 0 0 0
10 0 0 0 0 0
11 129 136 131 132 4.69
12 0 0 0 0 0
13 0 0 0 0 0
14 132.3 133.1 139 134.8 4.77
15 383 434 407 408 12.57
16 0 0 0 0 0
17 0 0 0 0 0
18 1263 1336 1235 1278 37.38
19 449 412 456 439 13.45
20 0 0 0 0 0
21 0 0 0 0 0
22 468 442 473 461 14.07
23 0 0 0 0 0
24 109 96 107 104 3.89
25 439 445 454 446 13.65
26 0 0 0 0 0
27 0 0 0 0 0
28 0 0 0 0 0
29 0 0 0 0 0
30 0 0 0 0 0
Potato starch 1 302 290 326 306 9.65
2 152 161 152 155 5.35
3 0 0 0 0 0
4 307 273 269 283 9.0
5 0 0 0 0 0
6 0 0 0 0 0
7 218 191 188 199 6.60
8 0 0 0 0 0
9 0 0 0 0 0
10 0 0 0 0 0
11 139.5 125.1 127.2 130.6 4.65
12 0 0 0 0 0
Corn starch 1 0 0 0 0 0
2 331 325 337 331 10.37
3 0 0 0 0 0
4 0 0 0 0 0
5 0 0 0 0 0
6 0 0 0 0 0
7 253 231 227 237 7.68
8 0 0 0 0 0
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Fig 7. Actual test of commercially available samples.

Fig 7

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Channel 1–3: sample11; channel 4–6: sample12; channel 7–9: sample13; channel 10–12: sample14; channel 13–15: sample15; channel 16–18: sample16; channel 19–21: sample17; channel 22–24: sample18; channel 25–27: sample19; channel 28–30: sample20; channel31 negative; channel32 positive.

Fig 8. Actual test of commercially available samples.

Fig 8

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Channel 1–3: sample21; channel 4–6: sample22; channel 7–9: sample23; channel 10–12: sample24; channel 13–15: sample25; channel 16–18: sample26; channel 19–21: sample27; channel 22–24: sample28; channel 25–27: sample29; channel 28–30: sample30; channel31 negative; channel32 positive.

Fig 9. Actual test of commercially available samples.

Fig 9

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Channel 1–3: sample31; channel 4–6: sample32; channel 7–9: sample23; channel 10–12: sample24; channel 13–15: sample25; channel 16–18: sample26; channel 19–21: sample27; channel 22–24: sample28; channel 25–27: sample29; channel 28–30: sample30; channel31 negative; channel32 positive.

4. Discussion

ddPCR was used to accurately and quantitatively detect cassava-derived components in starch. A linear relationship among cassava weight, DNA concentration, and amplified DNA copy number was discovered. The calculation formula of weight and amplified DNA copy number can quickly report the cassava content for quantitative detection of adulterants in commercial starch products.

This study confirms the market applicability and accuracy of the method via a mixture of sweet potato and cassava starch of different ratios. The ddPCR amplification results are largely consistent with the actual weight. The maximum relative error value is 10.2%, which is within the specified error range Furthermore, statistical analysis showed that the difference between the replicate measurements is small (low coefficient of variation). These data show that this approach is reliable and can measure cassava adulteration.

In order to verify the application prospect of this study, 50 starch products of different brands were tested and analyzed. The highest weight of cassava adulteration in sweet potato starch was 37.38%, and 11 out of 30 samples had cassava adulteration. The highest ratio of cassava adulteration in potato starch was 9.65%. There were 5 samples in 12 samples with cassava adulteration. The highest measured cassava adulteration in corn starch was 10.37%; this was seen in 2 of 8 samples. The results of this series of tests indicate that there are different degrees of adulteration in commercially available starch products indicating the necessity to develop efficient detection approaches. Our method can accurately and quantitatively measure the degree of adulteration of commercially available starch. These findings may help distinguish deliberate adulteration from contamination. For example, some weight ratios of up to 10% and 30% adulteration must be deliberately adulterated, while some 3% and 4% may be due to contamination during production processes.

The method can quantitatively determine the degree of adulteration in commercially available starch. It can also work with a wide range of adulterants. Thus, ddPCR technology can discriminate between intentional fraud and unintended contamination. The method can also be applied to other types of starch testing, and this quantitative testing system is a valuable tool for surveillance of quality control, maintenance of regulatory standards and consumer advocacy.

Acknowledgments

This thesis was completed under the guidance of Prof. Yaxin Sang. His serious scientific attitude, rigorous academic spirit, and good work style inspired me. I also would like to thank Wei Zhou and Yalun Zhang for their help.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was supported by South China Agricultural University [grant number 2017YFC1601700].

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Decision Letter 0

Evangelia V Avramidou

12 Aug 2019

PONE-D-19-17769

A quantitative study of the adulteration of cassava components in starch products by droplet digital PCR

PLOS ONE

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Please include the following items when submitting your revised manuscript:

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  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Evangelia V. Avramidou, PhD

Academic Editor

PLOS ONE

Journal Requirements:

1. When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In your Methods, please specify the exact source(s) of the cassava and potato extracts used in your study.

Additional Editor Comments:

Dear Dr. Yaxin Sang,

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Overview: The manuscript presents adequate data to support use of droplet digital PCR to assess the accurate composition of cassava starch when mixed or blended with starch from other sources such as sweet potato, potato and corn. Are there some industry quality standards required for such starch products be of a certain proportion like there is for varietal wines? Is there any reference that can provide documentation of fraud by food processor? Are there health concerns (e.g. associated food allergies)? Authors indicate models were developed but the data only shows target DNA copies and correlations only. Does this count as a model? Otherwise, the science and methodology appear solid.

Specific comments:

Ln 29-30. Cassava DNA- clarify the linear relationship was with regard cassava dry weight to DNA concentration.

Ln 40-43. Recommend rewriting the first five sentences with a reference to cassava adulteration by other starch produces due to economics.

Ln 45. Sanitation tests?

Ln 53. Digital dPCR (ddPCR) and use ddPCR thereafter in this manuscript.

Ln 184-190. Needs a Table or a figure.

Ln 196 – Fig. 5 is missing.

Table 5 is incoherent without adding what the samples are. The results indicate cassava/sweet potato at different ratios which need to be included in the title or at least foot-noted.

Ln 199 maximum relative error 10.2%. Is this shown in Table 5?

Reviewer #2: The manuscript entitled ‘A quantitative study of the adulteration of cassava components in starch products by droplet digital PCR’ describes the development of a method aiming to enable the rapid and accurate detection and quantitation of cassava adulteration in starch products by utilizing droplet digital PCR technology (dd PCR).

The experiment seems well thought out and carefully executed. However certain points need to be elaborated and explained further.

1. It is not clear what was the basis of selecting the Acc gene for the PCR analysis. In fact there is no information or reference given about this gene. Could more genes be studied?

2. Have there been other studies to detect cassava adulteration previously? Have there been studies employing the other PCR technologies and what were the results? Could a comparison between other PCR technologies and dd PCR be provided?

3. It is not clear how a calculation formula was established between cassava quality, DNA concentration and copy number

On line 112 and 113 it is mentioned: “The program for the reaction denaturation was as follows: 95°C, 10 min; 94°C denaturation, 1 min; 56°C annealing, 45 s; 40 cycles; 98°C, 10 min; and 4°C for temporary storage”

The step ‘98°C, 10 min;’ refers to which part of the pcr reaction? Why it is 98°C degrees?

4. On line 127: “The experimental system and operating procedures are shown above” It is not clear what it is shown above.

5. On line 141: On line 127: “The experimental system and operating procedures are shown above” It is not clear what it is shown above.

6. Fig 1: The legend of Fig 1 needs more detail

7. Fig. 2: The legend of Fig 2 needs more detailed description

8. Fig. 3: The same. Please provide some minimal explanation of what the figure and graphs depict.

9. Fig. 5: Fig 5 is missing!

10. The Discussion section is really limited.

Overall the manuscript describes a good effort towards the employment of a rapid and accurate method to detect and quantify cassava adulteration in different starch sources using an important new technology, ddPCR, and merits to be published for reasons of knowledge transfer to the scientific community. However, the introduction, results and discussion sessions need to be described in a much more detailed and elaborate manner providing the reader with much more information on the topic and on data acquisition, in order to make it a comprehensible publication.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Raymond Yokomi

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: PONE-D-19-17769 review.pdf

Click here for additional data file. (100.7KB, pdf)
PLoS One. 2020 Feb 26;15(2):e0228624. doi: 10.1371/journal.pone.0228624.r002

Author response to Decision Letter 0

25 Sep 2019

3. Have the authors made all data underlying the findings in their manuscript fully available?

Response: Raw data has been placed in the support file.

Reviewer #1: Overview: The manuscript presents adequate data to support use of droplet digital PCR to assess the accurate composition of cassava starch when mixed or blended with starch from other sources such as sweet potato, potato and corn. Are there some industry quality standards required for such starch products be of a certain proportion like there is for varietal wines? Is there any reference that can provide documentation of fraud by food processor? Are there health concerns (e.g. associated food allergies)? Authors indicate models were developed but the data only shows target DNA copies and correlations only. Does this count as a model? Otherwise, the science and methodology appear solid.

Response:

1. There is a national standard for starch products in China (China National Standard for Starch Products GB 2713-2015), and we have cited this standard in the revised manuscript.

2. Starch adulteration has been reported before and we have cited the reference.

3. Food allergies are another concern of starch adulteration, and we have added this concern to the introduction.

4. We used a mixture of sweet potato and cassava starch to model starch adulteration.

Decision Letter 1

Evangelia V Avramidou

23 Oct 2019

PONE-D-19-17769R1

A quantitative study of the adulteration of cassava components in starch products by droplet digital PCR

PLOS ONE

Dear Dr Sang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Dec 07 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Evangelia V. Avramidou, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Dear authors,

according to reviewers opinion please proceed according to minor revision comments.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Please see pdf attachment. New edits are suggested to improve clarity of the manuscript. Mass is confusing to this reviewer in the context of this manuscript. It is preferable to use dry weight.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Raymond K. Yokomi

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: PONE-D-19-17769-R1 review.pdf

Click here for additional data file. (109.5KB, pdf)
PLoS One. 2020 Feb 26;15(2):e0228624. doi: 10.1371/journal.pone.0228624.r004

Author response to Decision Letter 1

20 Nov 2019

Dear editor：

I have completely revised the revised comments and submitted a modified version. Contact if you have any questions.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (11.6KB, docx)

Decision Letter 2

Evangelia V Avramidou

21 Nov 2019

PONE-D-19-17769R2

Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR

PLOS ONE

Dear Dr Sang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Jan 05 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Evangelia V. Avramidou, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Dear authors,

I have checked that you adopted reviewers's comments, but I still have some corrections regarding the manuscript. Please fullfill in line 31 do you mean products by "oducts"??

Furthermore, according also to reviewer's and mine opinion you should substitute word "mass" with "weight" also to tables and figures. Please make tha above corrections in order that your article can be published.

With kind regards

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Feb 26;15(2):e0228624. doi: 10.1371/journal.pone.0228624.r006

Author response to Decision Letter 2

17 Jan 2020

Reply

A rebuttal letter

Ln 2-3. Article title has been changed

Ln 7. Text has been changed

Ln 8 The text was changed to weight

Ln 12 Text has been changed

Ln 13 Text has been changed

Ln 22 Text has been changed

Ln 24. Text has been changed

Ln 26 Text has been changed

Ln 30-31. Text has been changed

Ln 34 Text has been changed

Ln 36 Text has been changed

Ln 49. Text has been changed

Ln 51 Text has been changed

Ln 57 Text has been changed

Ln 68. Text has been changed

Ln 85 Text has been changed

Ln 88 Text has been changed

Ln 110 Text has been changed

Ln 117. Text has been changed

Ln 148. Text has been changed

Ln 154 Text has been changed

Ln 161 Text has been changed

Ln 171-175 Rewritten

Ln 224 Text has been changed

Ln 227 Text has been changed

Ln 297 Text has been changed

Ln 299 Text has been changed

Ln 301 Text has been changed

Ln 303-311. Text has been changed

Attachment

Submitted filename: A rebuttal letter.docx

Click here for additional data file. (11.9KB, docx)

Decision Letter 3

Evangelia V Avramidou

22 Jan 2020

Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR

PONE-D-19-17769R3

Dear Dr. Sang,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Evangelia V. Avramidou, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Evangelia V Avramidou

28 Jan 2020

PONE-D-19-17769R3

Identification and quantification of cassava starch adulteration in different food starches by droplet digital PCR

Dear Dr. Sang:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Evangelia V. Avramidou

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: PONE-D-19-17769 review.pdf

    Click here for additional data file. (100.7KB, pdf)
    Attachment

    Submitted filename: PONE-D-19-17769-R1 review.pdf

    Click here for additional data file. (109.5KB, pdf)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (11.6KB, docx)
    Attachment

    Submitted filename: A rebuttal letter.docx

    Click here for additional data file. (11.9KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

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