Journal of Food Quality
Volume 2021 (2021), Article ID 5536241, 12 pages
https://doi.org/10.1155/2021/5536241

Research Article

Multielement Principal Component Analysis and Origin Traceability of Rice Based on ICP-MS/MS

Yan Wang, Xiaoxuan Yuan, Linan Liu, Junmei Ma, Sufang Fan, Yan Zhang, and Qiang Li

Hebei Food Safety Key Laboratory, Hebei Food Inspection and Research Institute, Shijiazhuang 050000, China

Correspondence should be addressed to Yan Zhang; snowwinglv@126.com and Qiang Li; liqiang@nepp.com.cn

Received 2 March 2021; Revised 3 September 2021; Accepted 6 September 2021; Published 24 September 2021

Academic Editor: Antonio J. Signes-Pastor

Copyright © 2021 Yan Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

In this experiment, inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) was used to determine the content of 30 elements in rice from six places of production and to explore the relationship between the multielement content in rice and the producing area. The contents of Ca, P, S, Zn, Cu, Fe, Mn, K, Mg, Na, Ge, Sb, Ba, Ti, V, Se, As, Sr, Mo, Ni, Co, Cr, Al, Li, Cs, Pb, Cd, B, In, and Sn in rice were determined by ICP-MS/MS in the SQ and MS/MS mode. By passing H₂, O₂, He, and NH₃/He reaction gas into the ICP-MS/MS, respectively, the interference was eliminated by means of in situ mass spectrometry and mass transfer. The detection limit of each element was 0.0000662–0.144 mg/kg, and the limit of quantification was in the range of 0.000221–0.479 mg/kg, the linear correlation coefficient was greater or equal to 0.9987 (R² ≥ 0.9987), and the detection results had low detection limit and great linear regression. Recovery of the method was in the range of 80.6% to 110.5% with spike levels of 0.10–100.00 mg/kg, and relative standard deviations were lower than 10%. For the multielement content of rice from different producing areas, the principal component factor analysis can get six principal component factors, 87.878% cumulative contribution rate, and the distribution of the principal component scores of each element and different producing areas. Based on the multielement content and cluster analysis, the samples were accurately divided into two major categories and six subcategories according to the places of production, which proved that there was a significant correlation between the multielement content in rice and the place of production, so that the place of rice origin can be traced.

1. Introduction

Rice is the main staple food of our country, which contains sugar, protein, fat and dietary fiber, and other main nutrition elements and also contains a lot of necessary trace elements, such as Ca, Fe, Zn, Se, and other mineral elements [1]. Heavy and toxic metals, especially As and Cd, present due to environmental pollution are taken up by the rice plant [2–5]. In China, rice varieties are rich and diverse, with large planting area span and large quality difference. China is a vast country with diverse climatic and geographical conditions, and the crops have different biological characteristics and physical and chemical indexes. Therefore, it is valuable to analyze and compare the differences of multielement contents in rice from south to north China and to provide theoretical basis and technical support for distinguishing rice from different places of origin.

At present, the origin traceability indexes in food mainly include stable isotope [6–11], multielement composition [12, 13], characteristic content of organic component [14, 15], DNA fingerprint [16], and near-infrared spectrum [17–21]. There are some common problems in multielement analysis, such as few element types, high detection limit of low content elements, and unquantifiable trace elements. The determination methods of poly element contents in rice include an electrochemical method, atomic absorption spectroscopy (AAS) [22], atomic fluorescence spectrometry (AFS) [23], inductively coupled plasma optical emission spectrometer (ICP-OES) [24], and inductively coupled plasma mass spectrometry (ICP-MS) [25, 26]. However, there are some common problems in these methods, which hamper the rapid determination of trace elements in rice, thus causing the reduction of the accuracy of traceability of multielement composition in rice. The advantage of the ICP-MS/MS method is to reduce elemental interference [27]. Alexander Simpson et al. [28]. found that by using ICP-MS/MS and NH₃ reagent gas, isotope interference can be reduced and the sensitivity of ¹⁷⁶Lu and ¹⁷⁶Yb can be improved. In terms of multielement determination, ICP-MS/MS has higher accuracy and greater diversity of elements than ICP-MS [29]. Among them, when measuring P, S, Sr, and other specific elements, O₂ and other reaction gases were used to accurately determine the element content by mass transfer [30, 31]. The advantage of the ICP-MS/MS method lies in the determination of ultratrace elements [32]. It can reduce the detection limit, which cannot be achieved by general ICP-MS and other detection methods.

In this paper, ICP-MS/MS was first used to determine the 30 elements’ contents in rice from six rice-production areas in Anhui, Guangxi, Guangdong, Jilin, Heilongjiang, and Inner Mongolia. Under SQ and MS/MS models [33], He, NH₃/He [34], O₂ [35], and H₂ [36] were selected as reactive gases for different elements to eliminate mass spectrum interference and reduce detection limit, and the relationship between the element content and the origin was studied by principal component analysis and cluster analysis, which provides technical support for quality control and origin traceability of rice.

2. Materials and Methods

2.1. Reagents and Solutions

Li, Na, Mg, Al, B, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ge, As, Se, Sr, Mo, Cd, In, Sn, Sb, Cs, Ba, Pb, Sc, Bi, Rh, and Y element standard solution (1000 μg/mL, Guobiao Testing & Certification Co., Ltd., Beijing, China), GBW0043, GBW10044, and GBW10045 Rice reference materials (Institute of Geophysical and Geochemical Exploration IGGE, Langfang, China), 65% BV-III grade of HNO₃ (Beijing Institute of Chemical Reagents, Beijing, China), 30% H₂O₂ (Sinopharm Chemical Reagent Co., Ltd., Beijing, China), and deionized water (18.2 MΩ/cm), prepared by using the Milli-Q system (Millipore, Bedford, MA), were used.

2.2. Sample Collection and Preparation

The samples were collected from six rice-producing areas in Anhui Province, Guangxi Province, Guangdong Province, Jilin Province, Heilongjiang Province, and Inner Mongolia. We purchased common local rice samples with large planting areas in each rice market, a total of 18 batches. Three independent packages were purchased for each batch, and mixed samples were taken to ensure uniformity. The rice samples of each batch were hulled, ground, crushed, and stored in a sealed, low-temperature, and dark place.

In a PTFE digestion tank, each rice sample which weighs 0.3–0.5 g (accurate to 0.001 g) was added to 4 mL HNO₃ and 1 mL 30% H₂O₂ and soaked for 3–4 h or overnight, the upper cap was screwed, and it was digested with the microwave digestion instrument (CEM MARS6, CEM, Matthews, USA). The conditions of the microwave digestion instrument are shown in Table 1. Then, they were placed on the temperature-controlled electric heating plate (BHW-09C, Shanghai Botong Chemical Technology Co., Ltd., Shanghai, China) and heated at for 20–30 min for degassing. After cooling, the samples were diluted to 50 mL with deionized water and shook well for later use. For each group of samples, blanks (deionized water and reagents) and reference materials were included throughout the entire sample preparation and analytical process.

Table 1: The condition of microwave digestion.

Step
Climbing time (min)
Hold time (min)
Temperature (°C)
Power (W)

1
06 : 00
03 : 00
120
1500

2
08 : 00
06 : 00
155
1500

3
08 : 00
15 : 00
180
1500

2.3. Inductively Coupled Plasma Tandem Mass Spectrometry Analysis

This experiment was carried out by tandem mass spectrometry. The concentration of 30 isotopes (⁷Li, ²³Na, ²⁴Mg, ²⁷Al, ¹¹B, ³¹P, ³²S, ³⁹K, ⁴⁴Ca, ⁴⁷Ti, ⁵¹V, ⁵²Cr, ⁵⁵Mn, ⁵⁶Fe, ⁵⁹Co, ⁶⁰Ni, ⁶³Cu, ⁶⁶Zn, ⁷²Ge, ⁷⁵As, ⁷⁸Se, ⁸⁸Sr, ⁹⁵Mo, ¹¹¹Cd, ¹¹⁵In, ¹¹⁸Sn, ¹²¹Sb, ¹³³Cs, ¹³⁷Ba, and ²⁰⁸Pb) in rice was determined by inductively coupled plasma tandem mass spectrometry (Agilent 8900 Series, Agilent, USA). 1 μg/mL mixed solution of Li, Y, Co, Tl, Ce, and Mg was used as the tuning solution, and 0.10 rps speed of the peristaltic pump was used to continuously feed the solution. Through the tuning program, the conditions of no gas, H₂, O₂, He, and NH₃/He multimode analysis methods were optimized. In the no-gas mode, the monitored ions were 7, 89, and 205. In the He mode, the monitored ions were 59, 89, and 205. In the H₂ mode, the monitored ions were Q₁ = Q₂ = 59, 89, and 205. In the O₂ mode, the monitored ions were Q₁ = Q₂ = 59, Q₁ = 89/Q₂ = 105, and Q₁ = Q₂ = 205. In the NH₃/He mode, the monitored ions were Q₁ = Q₂ = 59, Q₁ = 89/Q₂ = 191, and Q₁ = Q₂ = 205. Under different modes, RF power was 1550 W, auxiliary gas was 0.90 L/min, plasma gas was 15.0 L/min, sampling depth was 8.0 mm, and extraction lens was −7.6 V. The instrument’s other conditions of ICP-MS/MS are shown in Table 2.

Table 2: Instrument parameters of ICP-MS/MS.

Instrument conditions
No-gas mode
H₂ mode
He mode
O₂ mode
NH₃/He mode

Q₁ deflection voltage(V)
−3.0
1.0
−3.0
1.0
1.0

Q₂ deflection voltage(V)
−3.0
−18.0
−15.0
−10.0
−12.0

Collision pool gas
—
H₂
He
O₂
NH₃/He

Gas flow rate of collision pool (L·min⁻¹)
—
7.0
5.0
4.5
4.5/1.0

Deflection voltage of eight-stage pole (V)
−8.0
−18.0
−18.0
−3.0
−5.0

For the selection of element determination mode and reagent gas, this method involves two modes: the SQ (single quadrupole) standard mode and MS/MS tandem mode. There are He and no-gas reagent gas modes in the SQ mode and He, NH₃/He, H₂, O₂, and no-gas reagent gas modes in the MS/MS mode. The elements are measured in all modes, and the mode with the lowest detection limit of each element is determined as the best measurement mode.

Through the measured experimental conditions and methods, the elements Sc, Y, Rh, and Bi were used as the internal standard elements. Analyzing the experimental data can get a linear fitting standard curve with the X-axis as the concentration point and the Y-axis as the response value. Through this standard curve, the detection limit and background equivalent concentration of the analysis element can be obtained by calculating the element standard deviation. The linear correlation coefficient and range, internal standard elements, limit of detection (LOD), and limit of quantification (LOQ) are shown in Table 3.

Table 3: Linear range and detection limit of isotopes.

Calibration (μg/L)
R²
Internal standard
LOD (mg/kg)
LOQ (mg/kg)

⁷Li
0∼100
0.9998
Sc
0.000659
0.0220

²³Na
0∼1000
0.9999
Sc
0.144
0.479

²⁴Mg
0∼1000
0.9999
Sc
0.00372
0.0124

²⁷Al
0∼100
0.9987
Sc
0.0907
0.302

¹¹B
0∼100
0.9995
Sc
0.0375
0.125

³¹P
0∼1000
0.9994
Sc
0.0204
0.0679

³²S
0∼1000
0.9997
ScO
0.0614
0.205

³⁹K
0∼1000
1.0000
Sc
0.0291
0.0970

⁴⁴Ca
0∼1000
1.0000
Sc
0.105
0.351

⁴⁷Ti
0∼100
0.9999
ScO
0.00219
0.00731

⁵¹V
0∼100
0.9999
ScO
0.000946
0.00315

⁵²Cr
0∼100
0.9997
ScO
0.00521
0.0174

⁵⁵Mn
0∼1000
1.0000
Sc
0.00148
0.00495

⁵⁶Fe
0∼1000
1.0000
Sc(NH₃)₂
0.0170
0.0567

⁵⁹Co
0∼100
1.0000
Sc(NH₃)₂
0.000510
0.00170

⁶⁰Ni
0∼100
1.0000
Sc(NH₃)₂
0.00133
0.00444

⁶³Cu
0∼1000
1.0000
Sc
0.00474
0.0158

⁶⁶Zn
0∼1000
1.0000
Sc
0.0115
0.0383

⁷²Ge
0∼100
1.0000
Y
0.000206
0.000686

⁷⁵As
0∼100
1.0000
YO
0.00250
0.00832

⁷⁸Se
0∼100
1.0000
Y
0.00152
0.00507

⁸⁸Sr
0∼100
1.0000
Y
0.000929
0.00310

⁹⁵Mo
0∼100
0.9999
YNH₃
0.000605
0.00202

¹¹¹Cd
0∼100
1.0000
Rh
0.0000662
0.000221

¹¹⁵In
0∼100
0.9998
Rh
0.00123
0.00410

¹¹⁸Sn
0∼100
1.0000
Rh
0.00176
0.000588

¹²¹Sb
0∼100
1.0000
Rh
0.000196
0.000653

¹³³Cs
0∼100
1.0000
Rh
0.000227
0.000756

¹³⁷Ba
0∼100
1.0000
Rh
0.00158
0.00525

²⁰⁸Pb
0∼100
1.0000
Bi
0.000949
0.00317

At the same time, the content of each element in rice reference materials (GBW10043, GBW10044, and GBW10045) was determined, the standard value was compared, and the recovery rate was calculated to prove the accuracy and reliability of the method, and the recovery experiment was conducted.

2.4. Statistical Analysis

All analyses were conducted in triplicate. The results reported were the average of these three replicates. Each sample was considered as an assembly of 30 variables represented by the data of chemical information. The analysis data and the fitted linear regression curve were analyzed by Agilent Mass Hunter software (Agilent Inc., USA). A normal distribution test of multielements, principal component analysis, and clustering analysis were performed with SPSS 25.0 software (SPSS, IBM Corp., USA).

3. Results and Discussion

3.1. Mass Spectrometry Mode Selection and Interference Elimination

In this experiment, the SQ (single quadrupole) standard mode and MS/MS tandem mode were used to simultaneously determine the concentration of multielement. The elements were measured in different modes and different reaction gas modes, and the element detection limit was used as the criterion to determine the best measurement mode for each element. The results are shown in Table 4.

Table 4: Isotope mass spectrometry.

Mode
Reaction gas
Mass number
Eliminate interference

⁷Li
MS/MS
NH₃/He
Q₁ = Q₂ = 7
In situ mass spectrometry

²³Na
MS/MS
H₂
Q₁ = Q₂ = 23
In situ mass spectrometry

²⁴Mg
MS/MS
NH₃/He
Q₁ = Q₂ = 24
In situ mass spectrometry

²⁷Al
MS/MS
H₂
Q₁ = Q₂ = 27
In situ mass spectrometry

¹¹B
MS/MS
NH₃/He
Q₁ = 11, Q₂ = 60
Mass transfer

³¹P
MS/MS
O₂
Q₁ = 31, Q₂ = 47
Mass transfer

³²S
MS/MS
O₂
Q₁ = 32, Q₂ = 48
Mass transfer

³⁹K
MS/MS
O₂
Q₁ = Q₂ = 39
In situ mass spectrometry

⁴⁴Ca
MS/MS
NH₃/He
Q₁ = Q₂ = 44
In situ mass spectrometry

⁴⁷Ti
MS/MS
O₂
Q₁ = 47, Q₂ = 63
Mass transfer

⁵¹V
MS/MS
O₂
Q₁ = 51, Q₂ = 67
Mass transfer

⁵²Cr
MS/MS
O₂
Q₁ = 52, Q₂ = 68
Mass transfer

⁵⁵Mn
MS/MS
H₂
Q₁ = Q₂ = 55
In situ mass spectrometry

⁵⁶Fe
MS/MS
NH₃/He
Q₁ = 56, Q₂ = 90
Mass transfer

⁵⁹Co
MS/MS
NH₃/He
Q₁ = 59, Q₂ = 93
Mass transfer

⁶⁰Ni
MS/MS
NH₃/He
Q₁ = Q₂ = 60
In situ mass spectrometry

⁶³Cu
SQ
He
Q₂ = 63
—

⁶⁶Zn
MS/MS
H₂
Q₁ = Q₂ = 66
In situ mass spectrometry

⁷²Ge
MS/MS
H₂
Q₁ = Q₂ = 72
In situ mass spectrometry

⁷⁵As
MS/MS
O₂
Q₁ = 75, Q₂ = 91
Mass transfer

⁷⁸Se
MS/MS
H₂
Q₁ = Q₂ = 78
In situ mass spectrometry

⁸⁸Sr
MS/MS
H₂
Q₁ = Q₂ = 88
In situ mass spectrometry

⁹⁵Mo
MS/MS
NH₃/He
Q₁ = Q₂ = 95
In situ mass spectrometry

¹¹¹Cd
SQ
No gas
Q₂ = 111
—

¹¹⁵In
MS/MS
H₂
Q₁ = Q₂ = 115
In situ mass spectrometry

¹¹⁸Sn
SQ
He
Q₂ = 118
—

¹²¹Sb
SQ
No gas
Q₂ = 121
—

¹³³Cs
MS/MS
O₂
Q₁ = Q₂ = 133
In situ mass spectrometry

¹³⁷Ba
MS/MS
NH₃/He
Q₁ = Q₂ = 137
In situ mass spectrometry

²⁰⁸Pb
SQ
No gas
Q₂ = 208
—

The interference was eliminated by making full use of the collision mode between the element and the reaction gas. In the SQ mode, the mass ions of ⁶³Cu, ¹¹¹Cd, ¹¹⁸Sn, ¹²¹Sb, and ²⁰⁸Pb had the characteristics of high abundance value and less interference. The corresponding Q₂ mass number was the only one that needs to be set during the determination.

In the MS/MS mode, the NH₃/He mixture gas collided with ⁷Li, ²⁴Mg, ⁴⁴Ca, ⁶⁰Ni, ⁹⁵Mo, and ¹³⁷Ba ions in the reaction cell, H₂ collided with ²³Na, ²⁷Al, ⁵⁵Mn, ⁶⁶Zn, ⁷²Ge, ⁷⁸Se, ⁸⁸Sr, and ¹¹⁵In ions, and O₂ collided with ³⁹K and ¹³³Cs ions, respectively. The interference was eliminated by in situ mass spectrometry, which means the elements only collide with the reaction gas and do not combine with each other. Therefore, the mass number of the front and after tetrodes to be set remains unchanged (Q₁ = Q₂). However, the system will still have the same amount of heterotopic number signal superposition interference and double charge ion interference; for example, ions Ni⁺⁺, SiH, CO, and NO may interfere with ³¹P; ions Zn⁺⁺, NO, and OO may interfere with ³²S; ions CAr and ArO interfere with ⁵²Cr; ions ArCl, CaCl, and CoO interfere with ⁷⁵As; ions ArO and MnH interfere with ⁵⁶Fe; and ions Sn⁺⁺, NiH, and MgCl interfere with ⁵⁹Co. Therefore, in the determination of some specific elements, if the reactant gas and the element collide with each other to generate ions with a new mass number, the abovementioned interferences can be better avoided. In addition, when the gas collided with the analysis element, new mass ions were formed in the reaction, that is, mass transfer (Figure 1). In the experiment, NH₃/He mixture gas can react with ¹¹B⁺ and ⁵⁶Fe⁺ to form ¹¹B⁴⁹NH(NH₃)₂⁺ and ⁵⁶Fe(¹⁴NH₃)₂⁺ cluster ions. Also, the O₂ mode was more widely used, which can undergo mass transfer with ³¹P⁺, ³²S⁺, ⁴⁷Ti⁺, ⁵¹V⁺, ⁵²Cr⁺, ⁷⁵As⁺, and generated ³¹P¹⁶O⁺, ³²S¹⁶O⁺, ⁴⁷Ti¹⁶O⁺, ⁵¹V¹⁶O⁺, ⁵²Cr¹⁶O⁺, and ⁷⁵As¹⁶O⁺ cluster ions, respectively.

Figure 1: Interference cancellation model of the MS/MS mode. The ions collided with gas in the ORC.

3.2. Standard Material Determination and Precision

Multielement determination was performed on the standard materials GBW10043, GBW10044, and GBW10045, and the results are shown in Table 5. The average recoveries of element content of reference materials were in the range between 82.9% and 115%.

Table 5: Recovery rate of reference materials.

Recovery (%)
As
B
Ba
Ca
Cd
Co
Cr
Cs
Cu
Fe
Ge
K
Li
Mg
Mn
Mo
Na
Ni
P
Pb
S
Sb
Se
Sr
Sn
Ti
V
Al
Zn
In

GBW10043
92.6
91.6
92.6
95.2
109
89.4
91.7
103
92.2
104
106
96.5
92.8
105
96.5
88.6
95.3
90.6
102
89.5
95.3
106
105
95.6
ND
94.8
105
92.6
95.6
ND

GBW10044
95.1
93.8
104
105
108
90.2
93.5
107
85.6
108
109
94.8
107
103
91.5
85.7
92.1
105
106
115
90.7
108
109
96.1
ND
93.8
109
90.2
94.1
ND

GBW10045
96.3
103
105
93.8
102
96.5
107
87.5
93.8
95.6
112
95.9
111
96.5
90.3
82.9
94.8
92.8
103
106
93.1
110
103
92.8
ND
91.1
113
93.5
103
ND

∗ND means not detected.

The recoveries of analytes were evaluated by adding the standard solutions with three different concentration levels to the known amounts of samples. The data of recovery and precision are given in Table 6, and the average recoveries of element content in rice were in the range between 80.6% and 110.5%. The RSDs were in the range of 0.4%–8.9%. The measurement results show that this method has high accuracy and meets the requirements of analysis and measurement.

Table 6: The spike recovery and reproducibility of the spiked sample (n = 6).

Element
Background (mg/kg)
Added (mg/kg)
Recovery (%)
RSD (%)

As
0.127
10
105.3
3.5

1
108.1
3.2

0.1
104.6
1.1

B
0.506
10
98.6
0.6

1
86.1
2.8

0.1
105.8
1.6

Ba
0.351
10
94.3
2.8

1
95.2
2.6

0.1
82.8
8.9

Ca
41.6
100
93.6
0.9

50
95.4
2.2

10
102.5
1.6

Cd
0.0272
10
107.6
5.8

1
92.5
0.9

0.1
108.6
3.5

Co
0.00675
10
91.6
4.5

1
95.3
4.1

0.1
106.8
0.9

Cr
0.0138
10
84.3
5.0

1
93.5
1.5

0.1
89.6
1.1

Cs
0.00152
10
110.5
0.6

1
92.3
2.8

0.1
94.2
2.3

Cu
2.06
10
95.1
0.5

1
96.7
4.1

0.1
97.6
4.8

Fe
2.45
10
105.6
2.3

1
103.9
6.8

0.1
107.5
0.5

Ge
0.00261
10
85.3
2.4

1
96.4
2.9

0.1
95.8
6.3

K
510
100
84.3
2.5

50
82.2
2.7

10
93.6
4.1

Li
0.00365
10
109.5
0.9

1
106.4
2.2

0.1
93.6
5.4

Mg
105
100
104.3
3.6

50
106.4
1.1

10
83.2
1.8

Mn
7.46
10
92.6
2.0

1
91.1
1.5

0.1
93.7
2.9

Mo
0.496
10
94.5
0.4

1
105.6
7.1

0.1
93.2
3.8

Na
1.97
10
108.9
4.5

1
103.7
4.8

0.1
82.6
1.5

Ni
0.168
10
91.6
0.5

1
106.3
0.8

0.1
87.5
1.6

P
448
100
101.2
1.3

50
104.5
2.9

10
93.4
3.5

Pb
0.00152
10
89.9
6.6

1
104.2
1.7

0.1
106.6
0.9

S
552
100
80.6
1.1

50
85.9
0.7

10
93.8
2.5

Sb
0.000154
10
106.4
3.9

1
95.3
3.3

0.1
92.8
0.6

Se
0.0274
10
94.7
2.5

1
95.9
2.1

0.1
84.6
0.8

Sr
0.163
10
106.4
0.7

1
108.5
0.9

0.1
84.9
5.3

Sn
ND
10
104.3
1.4

1
96.1
5.6

0.1
95.6
2.0

Ti
0.0865
10
85.3
1.7

1
91.8
0.8

0.1
85.9
7.6

V
0.00594
10
92.7
1.6

1
108.5
1.5

0.1
106.9
0.8

Al
ND
10
94.5
2.6

1
93.7
2.1

0.1
105.2
1.0

Zn
10.9
100
92.3
6.8

50
82.8
4.6

10
94.6
3.7

In
ND
10
91.5
2.5

1
85.4
8.9

0.1
96.3
1.9

∗ND means not detected.

3.3. Multielement Analysis of Samples

There are obvious differences in the content of Ba, Ge, Co, Cu, Cr, Ti, S, Ca, Mg, Na, Li, and other elements in rice from different producing areas in north and south China. In southern China, there are differences in the content of Na, Mg, K, Ca, V, Ge, Cs, Ba, and other elements in rice produced in Anhui Province, Guangxi Province, and Guangdong Province. However, in northern China, there are obvious differences in the content of B, Na, Ca, P, Cr, Mn, Ni, Co, Zn, Sr, Mo, Cs, and other elements in batches of rice in Jilin Province, Heilongjiang Province, and Inner Mongolia (Table 7). The contents of Al, In, and Sn were not detected.

Table 7: Element content of rice.

Li
B
Na
Mo
Al
As
Ca
P
S
Ti
V
Cr
Mn
Ni
Cu
Fe
Sb
Pb
Ge
In
Sr
K
Sn
Cd
Se
Mg
Co
Cs
Ba
Zn

A-1
3.47
0
1.91
0.546
0
0.124
41.5
436
569
77.6
5.17
13.6
7.05
0.122
2.11
2.37
0.135
0
2.62
0
0.148
513
0
26.8
21.5
96.6
6.68
1.57
0.316
10.9

A-2
0
0
1.35
0.484
0
0.106
40.5
466
581
75.3
3.68
19.7
7.60
0.114
2.55
1.95
0.0227
0
2.64
0
0.120
517
0
52.0
34.3
98.2
7.53
1.13
0.297
12.4

A-3
1.90
0
1.73
0.546
0
0.117
40.2
494
605
72.6
4.85
11.8
9.94
0.130
2.39
2.15
0.0625
0.368
2.75
0
0.139
524
0
201
28.2
89.9
7.49
1.20
0.304
12.3

X-1
9.56
0.506
4.80
0.502
0
0.134
48.3
540
630
45.6
8.33
5.22
8.43
0.130
2.31
2.79
0.350
16.6
1.91
0
0.121
701
0
5.59
38.9
172
5.94
1.79
0.187
11.8

X-2
4.84
0.333
4.44
0.485
0
0.112
49.3
528
624
51.7
7.81
0
9.54
0.129
3.15
2.32
0.245
2.76
2.44
0
0.132
739
0
28.9
27.9
200
6.29
1.91
0.190
11.9

X-3
1.39
0
3.63
0.474
0
0.115
48.1
499
611
82.2
7.98
7.99
9.45
0.117
3.04
2.53
0.116
1.15
2.31
0
0.128
716
0
150
26.8
167
6.35
1.24
0.178
11.6

D-1
1.52
0
1.04
0.459
0
0.126
37.1
456
599
42.6
5.17
11.5
8.63
0.136
2.06
1.77
0.159
0
1.13
0
0.137
593
0
39.7
59.4
52.6
6.94
9.94
0.194
11.6

D-2
1.57
0
1.03
0.317
0
0.0618
37.8
450
581
43.3
5.35
13.7
10.9
0.113
2.96
1.81
0.177
0
1.71
0
0.180
578
0
175
23.0
54.1
6.95
10.9
0.205
11.7

D-3
1.46
0
0.563
0.514
0
0.112
38.6
463
606
79.4
4.15
9.15
9.10
0.116
2.10
1.73
0.125
0.216
1.59
0
0.116
685
0
169
61.3
69.6
6.94
12.6
0.224
11.0

J-1
5.46
0.283
21.3
0.270
0
0.0930
50.0
409
448
21.8
7.34
34.5
10.1
0.0611
1.26
1.74
0.150
5.97
0.529
0
0.137
537
0
9.17
24.5
120
2.78
0.734
0.0479
10.4

J-2
6.45
0.233
19.5
0.201
0
0.0858
52.4
413
436
38.4
6.74
34.8
10.1
0.0508
1.12
2.91
0.136
0
0.630
0
0.156
514
0
3.49
14.3
124
2.84
0.695
0.0486
9.27

J-3
7.10
0.245
16.6
0.254
0
0.111
54.1
454
467
36.6
9.47
41.9
10.6
0.0597
1.15
2.22
0.984
0
0.520
0
0.131
526
0
3.10
34.1
128
2.64
0.624
0.0508
10.5

H-1
2.64
0.0219
5.66
0.470
0
0.106
47.9
448
514
36.2
7.68
55.2
10.4
0.126
1.72
2.34
0
8.65
0.969
0
0.103
549
0
5.73
24.7
124
4.84
1.05
0.0357
13.6

H-2
2.63
0
6.63
0.406
0
0.166
47.1
450
481
36.3
6.95
59.4
10.4
0.106
1.60
2.05
0.105
0
0.911
0
0.0802
516
0
15.5
53.0
114
4.95
1.56
0.0375
12.6

H-3
3.10
0.0311
4.05
0.414
0
0.0646
45.8
428
495
56.5
6.03
61.9
9.83
0.106
1.32
2.44
0.209
0
0.949
0
0.102
472
0
4.26
16.0
105
4.39
1.19
0.0343
12.8

N-1
5.97
0
13.0
0.363
0
0.110
41.0
499
525
19.9
5.22
65.8
7.12
0.0515
1.43
2.99
0.089
0
0.972
0
0.182
616
0
4.69
25.8
127
3.90
0.833
0.0247
11.2

N-2
5.19
0.0377
10.9
0.376
0
0.0900
45.1
519
537
23.1
5.72
61.4
7.25
0.0515
1.51
2.93
0.104
1.20
0.948
0
0.191
582
0
3.87
21.4
125
4.45
0.741
0.0292
10.4

N-3
4.65
0
11.9
0.340
0
0.0902
41.5
510
529
21.7
5.62
59.5
7.03
0.0791
1.60
2.52
0.100
0.302
0.808
0
0.189
591
0
3.00
26.6
119
4.50
0.637
0.0202
10.8

The data unit is mg(kg), among which the element data unit of Li, Ti, V, Cr, Co, Ge, Se, Cd, Sb, Cs, and Pb is μg(kg). A- Anhui Province, X- Guangxi Province, D- Guangdong Province, J- Jilin Province, H- Heilongjiang Province, N- Inner Mongolia.

We conducted further statistical analysis on the abovementioned experimental data, by calculating the standard deviation of each element and judging the difference of each element in different regions according to the degree of dispersion of the value of each element. As shown in Figure 2, the standard deviations of S, P, K, Cd, Mg, and other elements were large, and the degree of dispersion was relatively higher than that of other elements, which can be initially used as indicative elements for traceability.

Figure 2: The degree of dispersion.

3.4. Multielement Normal Distribution Test

The Kolmogorov–Smirnov test was conducted on the content of 30 elements in rice from different origins. The asymptotic significance (bilateral) value was calculated. The content data of 24 elements obeyed normal distribution.

3.5. Principal Component Analysis

Principal component analysis (PCA) is a multivariate statistical analysis method that analyses a few variables which can reveal the internal structure sufficiently by studying the relationship between multiple original variables.

According to the rule that the characteristic value is greater than 1 and the cumulative variance contribution rate is greater than 80%, six principal component factors were obtained through rotation and extraction factors, and the total contribution rate was 87.878%, indicating that the experimental data can fully reflect the original information (Table 8).

Table 8: Results of principal component analysis.

Component
Initial eigenvalue
Rotate the sum of squares loading

Total
Variance (%)
Accumulate (%)
Total
Variance (%)
Accumulate (%)

1
10.41
38.56
38.56
7.547
27.95
27.95

2
4.800
17.78
56.34
4.870
18.04
45.99

3
3.142
11.64
67.97
3.225
11.94
57.94

4
2.243
8.306
76.28
3.223
11.94
69.87

5
1.850
6.852
83.13
2.809
10.41
80.28

6
1.282
4.749
87.88
2.052
7.599
87.88

The first principal component is mainly composed of S, Ti, Ni, Cu, Co, Ge, Mo, Cd, Cs, Ba, Zn, and Se elements. The second principal component is mainly composed of Li, B, Mg, K, Ca, P, V, Pb, Fe, and As elements. The third principal component is mainly composed of Mn and Sb elements (Table 9). The first principal component, the second principal component, and the third principal component were used to analyze the contribution of the principal components of samples from different origins (Figure 3). The contribution scores of the principal components of samples from the same origin were concentrated, while the distribution of different origins is scattered. On the whole, rice samples from the north and south of China have a large difference in the contribution scores of the principal components which can be clearly distinguished. This result has certain guiding significance for the distinction of rice from different production places.

Table 9: Contribution value of the element’s principal component.

Element
Component

1
2
3
4
5
6

Li
−0.697
0.551
−0.164
0.167
0.154
−0.115

B
−0.367
0.753
0.162
0.324
0.003
−0.068

Na
−0.927
−0.009
−0.038
0.184
−0.016
−0.114

Mg
−0.318
0.846
−0.124
−0.167
−0.185
0.045

K
0.324
0.644
−0.263
0.291
0.289
0.282

Ca
−0.684
0.515
0.360
0.011
−0.278
−0.083

P
0.236
0.617
−0.559
−0.079
0.253
0.182

S
0.855
0.381
−0.277
0.102
0.108
0.094

Ti
0.772
0.070
0.141
0.016
−0.375
−0.333

V
−0.512
0.660
0.405
0.087
−0.092
0.132

Cr
−0.693
−0.380
−0.096
−0.508
0.140
0.175

Mn
−0.091
−0.002
0.794
0.261
−0.281
0.353

Ni
0.847
0.248
0.297
−0.177
−0.010
0.113

Cu
0.809
0.346
−0.112
0.180
−0.213
0.212

Fe
−0.476
0.361
−0.587
−0.277
−0.133
−0.014

Co
0.984
0.033
−0.093
−0.020
−0.007
0.000

Zn
0.472
0.092
0.364
−0.633
−0.052
0.401

Ge
0.818
0.301
−0.192
−0.039
−0.363
−0.216

Se
0.432
−0.003
0.368
0.081
0.778
−0.154

Sr
−0.221
−0.212
−0.822
0.384
−0.008
0.107

As
0.244
0.383
0.273
−0.316
0.480
−0.448

Mo
0.822
0.277
−0.040
−0.395
0.056
−0.117

Cd
0.715
−0.172
0.034
0.380
−0.209
0.165

Sb
−0.368
0.308
0.329
0.438
0.062
−0.237

Cs
0.547
−0.332
0.152
0.521
0.399
0.247

Ba
0.860
0.097
−0.044
0.198
−0.203
−0.350

Pb
−0.087
0.706
0.132
−0.114
0.148
0.236

Figure 3: Score distribution of principal component analysis.

3.6. Cluster Analysis

The contents of multielements in rice from different areas were analyzed by cluster analysis. The samples were successfully divided into two categories (the north and south of China) and six subcategories (six rice-producing areas) by the method of intergroup connection (Figure 4). The results show that there were obvious differences in the contents of multielements in rice from different producing areas, and they had certain regional characteristics. Therefore, by measuring the multielement content of rice, it is possible to accurately classify the samples according to the place of origin and finally realize the traceability of the production place of the rice.

Figure 4: Systematic clustering of element content. A- Anhui Province, X- Guangxi Province, D- Guangdong Province, J- Jilin Province, H- Heilongjiang Province, and N- Inner Mongolia.

4. Conclusions

In this experiment, the ICP-MS/MS method was developed to determine the content of 30 elements in rice from different production areas. The determination mode and reaction gas conditions were optimized, and the optimal determination conditions were selected for each element in five determination modes of no gas, H₂, O₂, He, and NH₃/He. In addition, in situ mass spectrometry and mass transfer technology were used to eliminate the interference and reduce the detection limit. To achieve the determination of ultratrace elements, we established a complete detection method, which provided a method basis for rice origin traceability. Through the principal component analysis of the multielement content of 18 batches of samples from different origins, the distribution of the six principal components of the samples and the characteristic elements of each principal component were determined. Through cluster analysis, the samples were accurately classified according to the place of production based on the multielement content, which proved that there was a significant correlation between the content of multielement in rice and the place of production, providing technical support and research direction for the traceability of the origin of rice.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this article.

Authors’ Contributions

YZ, QL, and YW conceived and designed the study. YW and LNL performed the experiments. YW and XXY wrote the paper. YZ, QL, JMM, and SFF reviewed and edited the manuscript. All authors read and approved the manuscript.

Acknowledgments

This work was supported by the National Key Research and Development Program of China (Project no. 2018YFC1603400), State Administration for Market Regulation Special Technical Support Program (Project no. 2019YJ009), and Scientific Research Projects of Hebei Market Supervision and Administration Bureau (Project no. 2021ZC07).

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