A method for predicting the adulteration rate of papaya seed powder in black pepper powder
By detecting Zn, Tl, and Mo in black pepper powder using ICP-MS, a predictive model was established, solving the problem of rapid and accurate prediction of adulteration rate in papaya seed powder in existing technologies, and achieving high-precision adulteration rate prediction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING FORESTRY UNIV
- Filing Date
- 2026-04-10
- Publication Date
- 2026-07-03
AI Technical Summary
Existing technologies are insufficient for quickly and accurately predicting the adulteration rate of papaya seed powder in black pepper powder using trace elements. Traditional methods suffer from low sensitivity, complex sample pretreatment, high instrument costs, and insufficient sample size and stability in modeling.
Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect the characteristic trace elements Zn, Tl, and Mo in black pepper powder. A predictive model was established through stepwise regression analysis, and the adulteration rate of papaya seed powder was predicted using the combination of Zn, Tl, and Mo.
It enables rapid and accurate prediction of the adulteration rate of papaya seed powder in black pepper powder, with an error within ±0.4%, which significantly improves the prediction accuracy and reduces the error of traditional methods.
Smart Images
Figure SMS_1 
Figure SMS_2 
Figure SMS_3
Abstract
Description
Technical Field
[0001] This invention relates to the field of food analysis and testing technology, and in particular to a method for predicting the adulteration rate of papaya seed powder in black pepper powder based on ICP-MS analysis of characteristic trace elements. Background Technology
[0002] Black pepper powder is one of the most important seasonings in the global market, holding a significant share and possessing extremely broad market prospects. Driven by economic interests, the problem of adulteration with black pepper powder is quite serious. Papaya seed powder is similar to black pepper powder in appearance and color, making it difficult to distinguish by sensory means. Furthermore, due to its lower value and ease of access, it has become the most common adulterant in black pepper powder.
[0003] Currently, traditional methods for detecting adulteration in black pepper powder include various analytical techniques such as spectroscopy, chromatography, and DNA-based methods. These methods, which involve collecting images or spectra of a large number of samples for modeling, are widely used. However, these methods are limited by their own analytical limitations. For example, spectroscopy is limited by overlapping spectral signals, complex data interpretation, and low sensitivity to trace amounts of adulterants. Chromatography and DNA-based methods suffer from drawbacks such as complex sample pretreatment, high instrument costs, and long analysis cycles. Furthermore, these methods are also limited by the sample size and model stability. Inductively coupled plasma mass spectrometry (ICP-MS) is an elemental analysis technique that uses inductively coupled plasma (ICP) as an ion source coupled with mass spectrometry (MS). The sample is nebulized into a high-temperature plasma, where it is atomized and ionized into ions. The ions enter the mass spectrometer through an interface, are separated according to their mass-to-charge ratio, and are detected. It can simultaneously and rapidly determine more than 70 elements with extremely high sensitivity (ppt to ppb level), making it suitable for trace and ultra-trace element analysis. Currently, there are no research reports on the quantitative prediction of papaya seed powder adulteration rate in black pepper powder using trace elements, nor have any studies revealed which specific trace elements have a stable quantitative correlation with the adulteration rate. Existing technologies, even those that have attempted ICP-MS detection of elements in black pepper powder, have only focused on tracing the origin or detecting heavy metal contamination, and have never established regression models between specific element combinations and adulteration rates. Therefore, there is a need to provide a method that can rapidly and accurately predict the adulteration rate of papaya seed powder, particularly by screening for characteristic element combinations with stable quantitative relationships. Summary of the Invention
[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a method for predicting the papaya seed powder content in black pepper powder based on ICP-MS analysis of characteristic trace elements.
[0005] To achieve these and other advantages according to the present invention, a method for predicting the adulteration rate of papaya seed powder in black pepper powder is provided, comprising the following steps: Step 1: Microwave digestion is performed on the sample to be predicted. Inductively coupled plasma mass spectrometry is used to detect the relative content of characteristic trace elements in the sample to be predicted. The characteristic trace elements include Zn, Tl and Mo. Step 2: Input the contents of Zn, Tl and Mo obtained in Step 1 into the prediction model to calculate the adulteration rate of papaya seed powder in black pepper powder; The prediction model is established using the following method: Black pepper powder samples were collected from at least three different regions and mixed with papaya seed powder in known proportions. The contents of various trace elements, including Zn, Tl and Mo, in each sample were determined by microwave digestion and inductively coupled plasma mass spectrometry, the same as in step one. Stepwise regression analysis was performed with adulteration rate as dependent variable and the contents of each trace element as independent variable to screen out Zn, Tl and Mo as key characteristic trace elements. The prediction model was obtained by fitting the model through correlation analysis and stepwise regression analysis. The prediction model is shown in Formula 1: Y=0.005S1+0.252S2-0.059S3-0.031 Formula 1 Where S1 represents the Zn content in μg / L; S2 represents the Tl content in μg / L; S3 represents the Mo content in μg / L; and Y represents the adulteration rate in μg / L.
[0006] Preferably, the specific steps for establishing a prediction model include: At least three black pepper powder samples from different origins were collected. Each black pepper powder sample was adulterated with 0%, 5%, 10%, 15%, and 20% papaya seed powder, respectively, to obtain samples with different adulteration rates. All samples were subjected to microwave digestion, and the contents of various trace elements, including Zn, Tl and Mo, were determined by inductively coupled plasma mass spectrometry. Using adulteration rate as the dependent variable and the content of each trace element as the independent variable, correlation analysis and stepwise regression analysis were used to screen out Zn, Tl and Mo, which were significantly correlated with adulteration rate, as key characteristic trace elements, and a prediction model was obtained by fitting the model.
[0007] Preferably, the microwave digestion process includes: weighing 0.1g of sample into a digestion vessel, adding 7mL of nitric acid and preheating until yellow fumes are exhausted, adding 1mL of nitric acid, maintaining the temperature at 150℃ for 10min, and then maintaining the temperature at 180℃ for 15min for digestion, and finally adjusting the volume to 25mL with nitric acid solution of 1% ultrapure water.
[0008] Preferably, in the inductively coupled plasma mass spectrometry (ICP-MS) detection, the standard working solution is prepared by serially diluting the solution to prepare a series of mixed standard working solutions with concentrations of 0.0, 5.0, 50, 100, and 200 μg / L, and plotting a multi-element standard working curve; separately, 0.5 mL of multi-element internal standard solution is diluted to 100 mL with a concentration of 10 mg / L to prepare an internal standard working solution with a concentration of 50 μg / L.
[0009] Preferably, the instrument conditions for inductively coupled plasma mass spectrometry are as follows: RF power: 1300 W; atomizer flow rate: 0.96 L·min⁻¹; pump speed: 20 rpm; sample rinsing time: 45 s; number of repeated tests: 3 times.
[0010] Preferably, the correlation analysis and stepwise regression analysis are performed using SPSS software.
[0011] Preferably, the significance level is p<0.01.
[0012] The present invention has at least the following beneficial effects: First, compared with traditional methods, the trace metal element detection technology requires only a small amount of sample to assess the adulteration of black pepper powder, providing a rapid, scientific, and accurate method for evaluating adulteration in black pepper powder. The composition of trace metal elements in black pepper powder exhibits strong stability. Inductively coupled plasma mass spectrometry (ICP-MS) possesses extremely high sensitivity, a wide linear dynamic range, and a low detection limit. Furthermore, it is less affected by matrix effects and can analyze a variety of metallic and non-metallic elements, making it an extremely valuable tool in elemental analysis research. ICP-MS can acquire detection signals for a large number of trace metal elements in a short time, providing rapid and automated analysis.
[0013] Secondly, this invention is the first to correlate trace metal elements with the adulteration rate of black pepper, establishing a stable and effective prediction model, providing a new method for predicting the adulteration rate of papaya seed powder in black pepper powder. Compared with models using only Zn, Tl, or with the addition of Co, the combination of Zn, Tl, and Mo in this invention reduces the prediction error from over ±2.64% to within ±0.4%, achieving unexpected technical results.
[0014] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Detailed Implementation
[0015] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.
[0016] It should be noted that, unless otherwise specified, the experimental methods described in the following implementation plan are all conventional methods, and the reagents and materials described are all commercially available unless otherwise specified.
[0017] Example 1 1. Preparation of black pepper powder samples Black peppercorn samples were collected from four different origins (labeled origins): Dezhou, Shandong Province; Huai'an, Jiangsu Province; Haikou, Hainan Province; and Taizhou, Jiangsu Province, numbered 1, 2, 3, and 4. Papaya seeds were selected as Red Princess F1 red-fleshed papaya seeds. All samples were ground using a grinder for digestion.
[0018] 2. Microwave digestion of samples Sample pretreatment was performed using microwave digestion (TANK 40 microwave digester). The specific method included: weighing 0.1g of sample into the digestion vessel, adding 7mL of nitric acid, preheating until yellow fumes ceased, and then adding another 1mL of nitric acid. Temperature control: 150℃ for 10min, then 180℃ for 15min. After digestion, the volume was adjusted to 25mL with 1% ultrapure water and nitric acid solution.
[0019] 3. Preparation of standard working solutions for inductively coupled plasma mass spectrometry: ICP-MS standard working solutions: Prepare a series of mixed standard working solutions with concentrations of 0.0, 5.0, 50, 100, and 200 μg / L by serial dilution, and plot a multi-element standard working curve. Separately, take 0.5 mL of multi-element internal standard solution and dilute it to 100 mL to prepare a 50 μg / L internal standard working solution.
[0020] 4. The relative content of trace elements in the sample was determined by inductively coupled plasma mass spectrometry: Characteristic trace elements include Ag, As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb, Se, Sn, Sr, Ti, Tl, V, and Zn. These trace elements can be simultaneously, rapidly, and accurately determined in a single experiment (inductively coupled plasma mass spectrometry (ICP-MS) analysis), making them highly practical. Furthermore, differences in their content directly reflect the plant's growth process or the presence of foreign substances. Specific conditions were: Instrument model: NexION 300X (PE Corporation); RF power: 1300 W; nebulizer flow rate: 0.96 L·min⁻¹; pump speed: 20 rpm; sample rinsing time: 45 s; number of repeated tests: 3.
[0021] 5. Extraction of characteristic trace elements from samples The extraction of characteristic trace elements from black pepper powder samples was performed using correlation analysis and stepwise regression analysis. Samples numbered 1, 2, and 3 were adulterated with 0%, 5%, 10%, 15%, and 20% papaya seed powder, respectively. Pearson correlation analysis was conducted using SPSS software to explore the association between adulteration rate and trace elements. The results showed that Zn, Tl, Fe, Co, Mo, and Sn were significantly positively correlated with the adulteration rate. Based on this, these six characteristic trace elements related to the adulteration rate were selected for the construction of subsequent prediction models.
[0022] 6. Establishment of the prediction model Trace element analysis was performed on the above samples. Due to weighing errors during actual adulteration, SPSS software was used to perform correlation analysis and stepwise regression analysis on the actual adulteration rate and trace metal element content to screen key characteristic metal elements. A predictive model for the adulteration rate of papaya seed powder in black pepper powder was also established, as follows: Y=0.005S1+0.252S2-0.059S3-0.031 Formula 1 Where S1 represents the Zn content in μg / L; S2 represents the Tl content in μg / L; S3 represents the Mo content in μg / L; and Y represents the adulteration rate in μg / L.
[0023] As shown in Table 1, the actual adulteration rate and the measured values of key trace elements are presented.
[0024] Table 1 Black peppercorns numbered 4 were processed under the same conditions, and trace metal elements were measured for use in the prediction model. Substituting the measured values of Zn, Tl, and Mo from the sample into the prediction model: Y = 0.005S1 + 0.252S2 - 0.059S3 - 0.031, the predicted adulteration rate was calculated respectively. Table 2. Measured and predicted values of the blind sample Table 2 shows that the error between the actual and predicted adulteration rates is within ±0.4%, indicating high prediction accuracy. Correlation and stepwise regression analysis using SPSS software revealed high correlation coefficients between the predicted and actual adulteration rates for all five sampling points, reaching a significant level (p<0.01, p≤0.05 is generally considered statistically significant). This demonstrates that the prediction model can quickly predict the adulteration rate of papaya seed powder in black pepper powder, offering advantages of speed and high accuracy. Extensive screening revealed that the combination of Zn, Tl, and Mo can predict the adulteration rate with the highest accuracy, while other element combinations cannot achieve this level of precision.
[0025] Comparative Example 1: A predictive model for the adulteration rate of papaya seed powder in black pepper powder was established using Zn and Tl, the elements with the highest Pearson correlation. Y = 0.004S1 + 0.197S2 - 0.171 Where S1 represents the Zn content in μg / L; S2 represents the Tl content in μg / L; and Y represents the adulteration rate in μg / L.
[0026] Table 3. Measured and predicted values of the blind sample As shown in Table 3, the error between the actual adulteration rate and the predicted adulteration rate is within ±2.64%, indicating that the prediction accuracy is relatively poor. Comparative Example 2: A predictive model for the adulteration rate of papaya seed powder in black pepper powder was established using Zn, Tl, Mo, and Co, which have the highest Pearson correlation. Y=0.005S1-0.006S2-0.006S3-0.17S4-0.062 Where S1 represents the Zn content in μg / L; S2 represents the Mo content in μg / L; S3 represents the Tl content in μg / L; S4 represents the Co content in μg / L; and Y represents the adulteration rate in μg / L.
[0027] Table 4. Measured and predicted values of the blind sample As shown in Table 4, the error between the actual adulteration rate and the predicted adulteration rate is within ±6.44%, indicating that the prediction accuracy is relatively poor. In summary, the comparison demonstrates that not any combination of trace elements can achieve such high prediction accuracy. Only the Zn, Tl, and Mo combination selected by this invention can achieve an error of ±0.4%, thus proving the non-obviousness and unexpected technical effects of this invention.
[0028] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
Claims
1. A method of predicting the rate of papaya seed powder adulteration in black pepper powder, characterized by, Includes the following steps: Step 1: Microwave digestion is performed on the sample to be predicted. Inductively coupled plasma mass spectrometry is used to detect the relative content of characteristic trace elements in the sample to be predicted. The characteristic trace elements include Zn, Tl and Mo. Step 2: Input the contents of Zn, Tl and Mo obtained in Step 1 into the prediction model to calculate the adulteration rate of papaya seed powder in black pepper powder; The prediction model is established using the following method: Black pepper powder samples were collected from at least three different regions and mixed with papaya seed powder in known proportions. The contents of various trace elements, including Zn, Tl and Mo, in each sample were determined by microwave digestion and inductively coupled plasma mass spectrometry, the same as in step one. Stepwise regression analysis was performed with adulteration rate as dependent variable and the contents of each trace element as independent variable to screen out Zn, Tl and Mo as key characteristic trace elements. The prediction model was obtained by fitting the model through correlation analysis and stepwise regression analysis. The prediction model is shown in Formula 1: Y=0.005S1+0.252S2-0.059S3-0.031 Formula 1 Where S1 represents the Zn content in μg / L; S2 represents the Tl content in μg / L; S3 represents the Mo content in μg / L; and Y represents the adulteration rate in μg / L.
2. A method of predicting the rate of papaya seed powder adulteration in black pepper powder as claimed in claim 1, wherein, The specific steps for building a predictive model include: At least three black pepper powder samples from different origins were collected. Each black pepper powder sample was adulterated with 0%, 5%, 10%, 15%, and 20% papaya seed powder, respectively, to obtain samples with different adulteration rates. All samples were subjected to microwave digestion, and the contents of various trace elements, including Zn, Tl and Mo, were determined by inductively coupled plasma mass spectrometry. Using adulteration rate as the dependent variable and the content of each trace element as the independent variable, correlation analysis and stepwise regression analysis were used to screen out Zn, Tl and Mo, which were significantly correlated with adulteration rate, as key characteristic trace elements, and a prediction model was obtained by fitting the model.
3. The method for predicting the adulteration rate of papaya seed powder in black pepper powder as described in claim 1, characterized in that, The microwave digestion process includes: weighing 0.1g of sample into a digestion vessel, adding 7mL of nitric acid and preheating until yellow fumes are exhausted, indicating that the nitric acid has been completely decomposed, adding 1mL of nitric acid, maintaining the temperature at 150℃ for 10min, and then maintaining the temperature at 180℃ for 15min for digestion, and finally adjusting the volume to 25mL with 1% ultrapure water nitric acid solution.
4. The method for predicting the adulteration rate of papaya seed powder in black pepper powder as described in claim 3, characterized in that, In the inductively coupled plasma mass spectrometry (ICP-MS) detection, the standard working solution is prepared by serially diluting the solution to prepare a series of mixed standard working solutions with concentrations of 0.0, 5.0, 50, 100, and 200 μg / L, and plotting a multi-element standard working curve. Separately, 0.5 mL of multi-element internal standard solution is diluted to 100 mL with a concentration of 10 mg / L to prepare an internal standard working solution with a concentration of 50 μg / L.
5. The method for predicting the adulteration rate of papaya seed powder in black pepper powder as described in claim 1, characterized in that, Instrument conditions for inductively coupled plasma mass spectrometry: RF power: 1300 W; atomizer flow rate: 0.96 L·min⁻¹; pump speed: 20 rpm; sample rinsing time: 45 s; number of repeated tests: 3 times.
6. The method for predicting the adulteration rate of papaya seed powder in black pepper powder as described in claim 2, characterized in that, The correlation analysis and stepwise regression analysis were performed using SPSS software.
7. The method for predicting the adulteration rate of papaya seed powder in black pepper powder as described in claim 2, characterized in that, The significance level was defined as p < 0.01.