Evaluation method for storage period of cherry tomatoes and application

Abstract

The invention relates to a cherry tomato storage period evaluation method and application, and belongs to the technical field of analysis and detection. The method for evaluating the storage period of the cherry tomatoes comprises the following steps: acquiring a cherry tomato sample; loading into a headspace bottle and incubating to obtain a headspace gas; carrying out headspace-gas chromatography-ion mobility spectrometry detection; vOCal analysis software is adopted for data collection; carrying out qualitative analysis on the volatile components by adopting a database; a cherry tomato classification model is constructed by adopting a multivariate statistics method, so that cherry tomato samples in different storage periods are classified. The evaluation method disclosed by the invention can be used for monitoring, classifying and judging the change of the volatile components of the cherry tomato samples under different storage conditions, and has the characteristics of high throughput, fast response, good repeatability, high accuracy and strong analysis capability.

Description

Technical Field

[0001] The present invention relates to the technical field of analytical detection, and in particular to an evaluation method and application for the storage period of cherry tomatoes. Background Art

[0002] Tomato (Solanum lycopersicum) is one of the important economic fruit and vegetable crops, and is widely used in the fields of fresh food and food processing. As an excellent strain of tomato, cherry tomato (Solanum lycopersicum var. Cerasiforme) is deeply welcomed by the market due to its small fruit shape, sour and sweet taste, rich aroma, rich nutrition and other characteristics, and has gradually become the mainstream category in the fruit and vegetable market. With the improvement of consumer demand, consumers have put forward higher requirements for the flavor and post-harvest quality of fruits and vegetables. As the core index determining its commercial value and consumer acceptance, fruit flavor has received more and more attention.

[0003] The overall flavor of tomatoes is jointly composed of soluble solids (sugar-acid ratio) and volatile components (VOCs). Among them, VOCs include aldehydes, esters, alcohols, ketones and other aroma-active components, and their composition and concentration will change significantly with factors such as storage temperature, storage humidity, and storage time, thereby affecting the judgment of fruit freshness, flavor identification and final commerciality, and playing a decisive role in the flavor perception of fruits.

[0004] At present, the evaluation of tomato storage quality is mostly based on sensory analysis or the determination of conventional physical and chemical indexes such as hardness, color, and soluble solids. Although it can reflect the maturity state of fruits to a certain extent, it cannot deeply reveal the essence of flavor changes, especially it is difficult to quantify and track the dynamic change process of VOCs. Traditional volatile component analysis methods such as gas chromatography-mass spectrometry (GC-MS), although having high resolution and good qualitative ability, have complex pretreatment, long detection period, and high instrument cost, and are not suitable for the application requirements of rapid detection after fruit and vegetable picking and actual storage and transportation scenarios.

[0005] Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) is a newly emerging gas detection technology. By analyzing the differences in the migration speeds of target compounds in the gas phase and combining with the GC chromatographic retention time for two-dimensional identification, it can achieve non-destructive, rapid, and high-throughput detection of VOCs in complex mixed systems, with advantages such as high sensitivity, rapid response, and simple operation. However, the current application of HS-GC-IMS technology in the analysis of the storage flavor of tomatoes after picking is still in its infancy. There is still a lack of dynamic analysis of the changes in VOCs and key VOCs identification methods for the whole process of cherry tomato storage; some related research mostly stays at the static detection level and fails to combine fingerprint maps, multivariate statistical analysis, and sample classification model construction to achieve a scientific evaluation and deterioration warning of the flavor changes of cherry tomatoes during storage; especially at two typical storage temperatures, refrigeration and normal temperature, there has been no systematic study to reveal the mechanism of the influence of storage temperature on the change law of VOCs in cherry tomatoes and its visualization expression path.

[0006] Therefore, there is an urgent need in the existing technology to develop a comprehensive evaluation scheme based on the HS-GC-IMS platform, integrating the construction of volatile component maps and statistical discrimination methods, which can quickly identify, differentially extract, and trend-evaluate the VOCs in cherry tomatoes during storage. Summary of the Invention

[0007] The purpose of the present invention is to provide an evaluation method and application for the storage period of cherry tomatoes, in order to solve the problems in the existing quality evaluation methods for cherry tomatoes during storage, such as long detection cycle, complex operation, and difficulty in quickly identifying the change trend of VOCs.

[0008] In order to achieve the above-mentioned invention purpose, the present invention provides the following technical solutions:

[0009] The present invention provides an evaluation method for the storage period of cherry tomatoes, including the following steps:

[0010] (1) Collect cherry tomato fruits at the red-ripe stage, take samples after storage to obtain cherry tomato samples;

[0011] (2) Put the cherry tomato samples into headspace vials and incubate to obtain headspace gas;

[0012] (3) Perform headspace-gas chromatography-ion mobility spectrometry detection to obtain the detection results;

[0013] The gas chromatography conditions are as follows: the chromatographic column type is MXT-WAX, the column temperature is 40 - 80 °C, the carrier gas is nitrogen, the purity of the carrier gas is ≥99.999%, and the carrier gas flow rate gradient is as follows: from 00:00.000 min to 02:00.000 min, the carrier gas flow rate is 1 - 5 mL / min; from 02:00.001 min to 10:00.000 min, the carrier gas flow rate rises from 1 - 5 mL / min to 5 - 20 mL / min; from 10:00.001 min to 20:00.000 min, the carrier gas flow rate rises from 5 - 20 mL / min to 50 - 150 mL / min; it is maintained at 50 - 150 mL / min for 5 - 20 min; the total running time is 25 - 40 min;

[0014] The ion mobility conditions are as follows: the length of the drift tube is 40 - 70 mm, the drift voltage is 2000 - 3000 V / cm, the temperature of the drift tube is 40 - 60 °C, the drift gas is nitrogen, the purity of the drift gas is ≥99.999%, the drift gas flow rate is 50 - 100 mL / min, and the ionization source is a tritium source ( 3 H), positive ion mode;

[0015] (4) Use VOCal analysis software to collect data on the test results to obtain the fingerprint spectrum of volatile components; use a database for qualitative analysis of volatile components to obtain the qualitative results of volatile components;

[0016] (5) Use multivariate statistical methods to analyze the fingerprint spectrum and qualitative results of volatile components, construct a cherry tomato classification model, and thus classify cherry tomato samples at different storage periods.

[0017] Preferably, in step (1), the storage temperature is 4 - 25 °C and the storage time is 0 - 5 d.

[0018] Preferably, in step (2), the incubation temperature is 60 - 90 °C, the incubation time is 5 - 30 min, and the incubation rotation speed is 250 - 750 rpm.

[0019] Preferably, in step (3), the injection conditions for the detection are as follows: the injection temperature is 60 - 100 °C and the injection volume is 100 - 1000 μL.

[0020] Preferably, the database in step (4) includes the NIST database and the IMS database.

[0021] Preferably, the multivariate statistical methods in step (5) include principal component analysis, cluster analysis, and fingerprint similarity analysis.

[0022] The present invention also provides the application of the above evaluation method in evaluating and / or monitoring the quality of cherry tomatoes during the storage period.

[0023] The present invention has the following technical effects and advantages:

[0024] The present invention constructs an evaluation method for the storage period of cherry tomatoes that does not require complex pretreatment of cherry tomato samples, is rapid in detection, and simple in operation. The overall detection process can be completed within 40 minutes, significantly improving the processing efficiency of post-harvest samples compared with the prior art. It is applicable to the rapid detection of a large number of cherry tomato samples during the storage period, and has the advantages of high throughput, fast response, and no need for derivatization;

[0025] Compared with the traditional GC-MS method, the evaluation method of the present invention has obvious advantages in terms of sensitivity, resolution, and retention of the original volatile organic compounds (VOCs). It is particularly suitable for the identification of typical complex VOCs with a boiling point < 300 °C, and has the advantages of good repeatability, high accuracy, and strong analytical ability;

[0026] The evaluation method of the present invention realizes the visual identification and trend prediction of the VOCs differences in cherry tomato samples under different storage temperatures and storage times by constructing the fingerprint map of VOCs and combining multivariate statistical methods such as PCA and FSA. It can not only provide theoretical support for the post-harvest commercial quality supervision and storage and transportation cycle control of cherry tomatoes, but also play an important technical support role in the fields of post-harvest physiological research of cherry tomatoes, cold chain logistics quality control, and fresh food standardization grading. At the same time, it provides a practical tool for the storage quality management and flavor deterioration warning of cherry tomatoes, and has good application value and industrial application prospects. Description of the Drawings

[0027] Figure 1 It is a three-dimensional topographic map of HS-GC-IMS of VOCs in each group of cherry tomato samples, where the X-axis is the migration time (Dt), the Y-axis is the retention time (Rt), and the Z-axis is the peak signal intensity;

[0028] Figure 2 It is a two-dimensional morphological difference map of HS-GC-IMS of VOCs in each group of cherry tomato samples. Taking the CK-0d group as the control, the red area is the cherry tomato samples with significantly higher VOCs signal intensity than the control, the blue area is the cherry tomato samples with significantly lower VOCs signal intensity than the control, and the white area is the cherry tomato samples with no obvious difference in VOCs signal intensity from the control;

[0029] Figure 3 It is the fingerprint map of VOCs in each group of cherry tomato samples, where the red spots are the VOCs with high-intensity response signals, and the white spots are the VOCs with low-intensity response signals;

[0030] Figure 4The comparison results of the fingerprint spectra of VOCs in each group of cherry tomato samples are shown. The horizontal rows are the VOC signal bands of each group of cherry tomato samples, the vertical columns are the response signals of each VOC, the red spots are the VOCs with high-intensity response signals, the blue spots are the VOCs with low-intensity response signals, and the white spots are the VOCs with medium-intensity response signals;

[0031] Figure 5 The PCA analysis diagram of VOCs in each group of cherry tomato samples is shown. The X-axis is the score of the VOCs in each group of cherry tomato samples on the principal component 1 (PC1), and the Y-axis is the score of the VOCs in each group of cherry tomato samples on the principal component 2 (PC2);

[0032] Figure 6 The Euclidean distance diagram of VOCs between each group of cherry tomato samples is shown;

[0033] Figure 7 The heat map of the cluster analysis of VOCs in each group of cherry tomato samples is shown. The abscissa is the VOCs of each group of cherry tomato samples, and the ordinate is each group of cherry tomato samples. Specific implementation mode

[0034] The present invention provides a method for evaluating the storage period of cherry tomatoes, comprising the following steps:

[0035] (1) Collect cherry tomato fruits at the red-ripe stage, take samples after storage to obtain cherry tomato samples;

[0036] (2) Put the cherry tomato samples into headspace bottles and incubate to obtain headspace gas;

[0037] (3) Perform headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) detection to obtain detection results;

[0038] The gas chromatography conditions are as follows: the chromatographic column type is MXT-WAX, the column temperature is 40-80°C, preferably 60°C; the carrier gas is nitrogen, the carrier gas purity is ≥99.999%, and the carrier gas flow rate gradient is: from 00:00.000min to 02:00.000min, the carrier gas flow rate is 1-5mL / min, preferably 2mL / min; from 02:00.001min to 10:00.000min, the carrier gas flow rate increases from 1-5mL / min to 5-20mL / min, preferably from 2m L / min increased to 10mL / min; from 10:00.001min to 20:00.000min, the carrier gas flow rate increased from 5-20mL / min to 50-150mL / min, preferably from 10mL / min to 100mL / min; maintained at a carrier gas flow rate of 50-150mL / min for 5-20min, preferably maintained at a carrier gas flow rate of 100mL / min for 10min; the total operation time is 25-40min, preferably 30min;

[0039] The ion migration conditions are as follows: the migration tube length is 40 to 70 mm, preferably 53 mm; the migration voltage is 2000 to 3000 V / cm, preferably 2700 V / cm; the migration tube temperature is 40 to 60° C., preferably 45° C.; the migration gas is nitrogen, the purity of the migration gas is ≥99.999%, the migration gas flow rate is 50 to 100 mL / min, preferably 75 mL / min; the ionization source is a tritium source ( 3 H), positive ion mode;

[0040] (4) Using VOCal analysis software to collect data on the test results and obtain the fingerprint of volatile components (VOCs); using the database to perform qualitative analysis of VOCs and obtain qualitative results of VOCs;

[0041] (5) Multivariate statistical methods were used to analyze the fingerprints and qualitative results of VOCs, and a cherry tomato classification model was constructed to classify cherry tomato samples at different storage periods.

[0042] In the present invention, the red ripe period in step (1) is the period when more than 90% of the cherry tomato fruits are fully colored;

[0043] The storage temperature in step (1) is 4 to 25° C. and the storage time is 0 to 5 days;

[0044] The mass of the cherry tomato sample in step (1) is 2 to 5 g, preferably 3 g.

[0045] In the present invention, the volume of the headspace bottle in step (2) is 20 mL, purchased from Shandong Haineng Scientific Instrument Co., Ltd.;

[0046] The incubation temperature in step (2) is 60 - 90°C, preferably 80°C; the incubation time is 5 - 30 min, preferably 15 min; and the incubation rotation speed is 250 - 750 rpm, preferably 500 rpm.

[0047] In the present invention, the sample injection conditions for the detection in step (3) are: the sample injection temperature is 60 - 100°C, preferably 85°C; the sample injection volume is 100 - 1000 μL, preferably 500 μL; and splitless injection is used.

[0048] In the present invention, the database in step (4) includes the NIST database and the IMS database.

[0049] In the present invention, the multivariate statistical methods in step (5) include principal component analysis (PCA analysis), cluster analysis, and fingerprint similarity analysis (FSA analysis).

[0050] The present invention also provides the application of the described evaluation method in evaluating and / or monitoring the quality of cherry tomatoes during the storage period.

[0051] The technical solutions provided by the present invention will be described in detail below in conjunction with the embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0052] The test base of the present invention is the experimental farm of the Zhejiang Academy of Agricultural Sciences, located in Hangzhou, Zhejiang Province (30°27′N, 120°2′E);

[0053] The test materials of the present invention are cherry tomatoes of the Zheyingfen No. 1 variety, from the Zhejiang Academy of Agricultural Sciences;

[0054] Among the instruments of the present invention, the MXT-WAX capillary chromatographic column (30 m × 0.53 mm, 1.0 μm) is purchased from Restek Corporation, USA, The gas chromatography-ion mobility spectrometry combined instrument and VOCal analysis software (V.0.4.03) are purchased from Gesellschaft für Analytische Sensorsysteme mbH, Germany, and the headspace vials are purchased from Shandong Haineng Scientific Instruments Co., Ltd., and the PAL3-RSI series II static headspace automatic sampler is purchased from CTCAnalytics AG, Switzerland.

[0055] Example 1: Evaluation of the storage period of cherry tomatoes

[0056] (1) Sample collection and incubation: In April 2024, cherry tomato plants of the Zheyingfen No. 1 variety were planted in the experimental farm of the Zhejiang Academy of Agricultural Sciences with a row spacing of 50 cm and a plant spacing of 40 cm; in July 2024, cherry tomato fruits at the fully colored red-ripe stage with over 90% fruits harvested were divided into groups of 4℃-1d, 4℃-2d, 4℃-3d, 4℃-4d, 4℃-5d, 25℃-1d, 25℃-2d, 25℃-3d, 25℃-4d, 25℃-5d. The cherry tomato fruits in each group were stored at 4℃ or 25℃ for 1d, 2d, 3d, 4d or 5d respectively, and the non-stored cherry tomato fruits were used as the control (CK-0d group); after the storage ended, 10 cherry tomato fruits were taken from each group, mixed and homogenized, and then 3g of cherry tomato samples were put into 20mL headspace vials and incubated at 80℃ and 500rpm for 15min to obtain headspace gas;

[0057] (2) HS-GC-IMS detection: Use type gas chromatography-ion mobility spectrometry to perform HS-GC-IMS detection on the headspace gas of each group in step (1) to obtain the detection results. Set the injection mode of the headspace gas as splitless injection, the injection temperature as 85℃, and the injection volume as 500μL;

[0058] Gas chromatography conditions are as follows: The chromatographic column type is MXT-WAX capillary chromatographic column, with a specification of 30m×0.53mm and a diameter of 1.0μm. The column temperature is 60℃, the carrier gas is high-purity nitrogen (purity ≥99.999%), and the carrier gas flow rate gradient is: from 00:00.000min to 02:00.000min, the carrier gas flow rate is 2mL / min; from 02:00.001min to 10:00.000min, the carrier gas flow rate linearly rises from 2mL / min to 10mL / min; from 10:00.001min to 20:00.000min, the carrier gas flow rate linearly rises from 10mL / min to 100mL / min and continues to maintain for 10min; the total running time is 30min;

[0059] Ion mobility conditions are as follows: Use a tritium source ( 3 H) as the ionization source, positive ion mode, the migration tube length is 53mm, the migration voltage is 2700V / cm, the migration tube temperature is 45℃, the migration gas is high-purity nitrogen (purity ≥99.999%), and the migration gas flow rate is 75mL / min;

[0060] (3) Data collection and analysis: The Gallery Plot plugin and Reporter plugin of VOCal analysis software (V.0.4.03) were used to collect data on the test results, obtaining the three-dimensional topographic map of HS-GC-IMS, the two-dimensional morphological difference map of HS-GC-IMS, and the fingerprint map of VOCs, and measuring the retention time (Rt) of VOCs, as Figures 1 to 3 shown; the NIST database and IMS database were used for two-dimensional qualitative analysis of the retention index (RI) and migration time (Dt) of VOCs to identify the qualitative results of 75 VOCs such as aldehydes, esters, alcohols, and ketones in each group of cherry tomato samples, as shown in Table 1; the Dynamic PCA plugin was used to perform principal component analysis (PCA analysis), cluster analysis, and fingerprint similarity analysis (FSA analysis) on the fingerprint map and qualitative results of VOCs in each group of cherry tomato samples to construct a cherry tomato classification model that can visually characterize VOCs, so as to classify the cherry tomato samples at different storage periods, as Figures 4 to 7 shown.

[0061] Table 1 Volatile components of cherry tomato samples under different storage conditions

[0062]

[0063]

[0064]

[0065]

[0066] The data collection results show that the signal response intensities of VOCs in cherry tomato samples are significantly different under different storage conditions. For example, the signal response intensities of VOCs such as (E)-2-hexenal, ethyl acetate, and 1-hexanol at 25°C show a decreasing trend, while intermediate metabolites such as 2-pentylfuran and 2-ethylfuran accumulate in the later stage of storage. Multiple key VOCs in cherry tomato samples show a continuous downward trend within 0 to 5 days. Specifically, the peak area of ethanol at 25°C decreases by 50.08%, showing strong storage sensitivity. The peak area of triethylamine-D at 25°C decreases by 1.28%, showing strong storage sensitivity. The peak area of pentanal-D decreased by 40.7% at 25°C and only decreased by 23.9% at 4°C, indicating that higher storage temperature can accelerate its volatilization or metabolic loss; the peak area of pentanal-D decreased by 40.4% at 25°C and decreased by 11.3% at 4°C, showing significant temperature response differences, indicating that it is a potential temperature deterioration marker; the peak area of benzaldehyde decreased by 34.1% at 25°C and decreased by 26.0% at 4°C, that is, there were large fluctuations in the signal response intensity at both storage temperatures, indicating that its stability performance was poor; the decrease in ethyl acetate-D at 4°C was the most significant, reaching 67.8%, and the peak area decreased by 27.4% at 25°C, indicating that it was more susceptible to low temperature environment; comprehensive comparison showed that the signal response intensity of most ester and aldehyde VOCs decreased faster at 25°C, and low-temperature storage at 4°C was more conducive to delaying the loss of typical fragrant VOCs in cherry tomatoes;

[0067] The results of VOCs fingerprints showed that VOCs such as ethanol, ethyl acetate, and benzaldehyde had strong signal responses at 0 days, and the signal response intensity decreased significantly at the 5th day of storage, indicating that the overall aroma intensity and complexity of cherry tomatoes decreased with the extension of storage time.

[0068] The results of PCA analysis showed that the explanation rates of PC1 and PC2 for data variation were 56.96% and 19.57% respectively, and the total explanation rate was 76.53%, which can be used to distinguish cherry tomato samples with different storage periods; the distribution of cherry tomato samples without storage and stored for 5 days in the PC1 direction was the farthest, indicating that the VOCs structure of cherry tomatoes without storage and stored for 5 days was the most different, and the distribution of VOCs of cherry tomatoes stored for 1 to 4 days was in the middle and gradually transitioned;

[0069] The results of cluster analysis showed that the cherry tomato samples were divided into three different regions. Region 1 showed that cherry tomatoes stored at 4 °C always exhibited a relatively high VOCs signal response intensity throughout the storage period, and were related to the odors of fresh, green grass, fruity, and green fragrance. Region 2 showed that when the cherry tomatoes had not been stored, the signal response intensities of 16 VOCs in them were relatively high, making the cherry tomatoes have typical fresh, sweet, and fruity flavors. As the storage period extended, the VOCs of cherry tomatoes stored at 25 °C were significantly different from those at the initial stage of storage, while 4 °C could inhibit the formation of some VOCs and the generation of off-flavor compounds, while retaining certain key VOCs.

[0070] In summary, the evaluation method of the present invention can be used to construct a cherry tomato classification model that can visually characterize VOCs during storage.

[0071] As can be seen from the above embodiments, the present invention provides an evaluation method and application for the storage period of cherry tomatoes. The evaluation method of the present invention constructs a VOCs fingerprint map, quickly identifies the VOCs differences among cherry tomato samples under different storage conditions, combines multivariate statistical methods to monitor and classify the VOCs changes of cherry tomato samples under different storage conditions, and has the advantages of high throughput, fast response, good repeatability, high accuracy, and strong analysis ability.

[0072] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for evaluating the storage period of cherry tomatoes, characterized in that, The following steps are involved: (1) collecting cherry tomato fruits at the red ripe stage, sampling after storage, and obtaining cherry tomato samples; (2) placing the cherry tomato sample into a headspace bottle and incubating to obtain headspace gas; (3) headspace-gas chromatography-ion mobility spectrometry detection to obtain the detection results; Gas chromatography conditions are as follows: the chromatographic column type is MXT-WAX, the column temperature is 40-80°C, the carrier gas is nitrogen, the carrier gas purity is ≥99.999%, and the carrier gas flow gradient is: from 00:00.000min to 02:00.000min, the carrier gas flow rate is 1-5mL / min; from 02:00.001min to 10:00.000min, the carrier gas flow rate increases from 1-5mL / min to 5-20mL / min; from 10:00.001min to 20:00.000min, the carrier gas flow rate increases from 5-20mL / min to 50-150mL / min; the carrier gas flow rate is maintained at 50-150mL / min for 5-20min; the total running time is 25-40min; The ion migration conditions are as follows: the length of the migration tube is 40 - 70 mm, the migration voltage is 2000 - 3000 V / cm, the temperature of the migration tube is 40 - 60 °C, the migration gas is nitrogen, the purity of the migration gas is ≥99.999%, the flow rate of the migration gas is 50 - 100 mL / min, and the ionization source is a tritium source ( 3 H), positive ion mode; (4) Using VOCal analysis software to collect data on the test results and obtain the fingerprint of volatile components; using the database to perform qualitative analysis of the volatile components and obtain the qualitative results of the volatile components; (5) Multivariate statistical methods were used to analyze the fingerprints and qualitative results of volatile components, and a cherry tomato classification model was constructed to classify cherry tomato samples at different storage periods.

2. The evaluation method according to claim 1, characterized in that, The storage temperature in step (1) is 4 to 25° C., and the storage time is 0 to 5 days.

3. The evaluation method according to claim 2, wherein The incubation temperature in step (2) is 60-90° C., the incubation time is 5-30 min, and the incubation speed is 250-750 rpm.

4. The evaluation method according to claim 3, wherein The injection conditions for the detection in step (3) are: injection temperature of 60-100°C and injection volume of 100-1000 μL.

5. The evaluation method according to claim 4, wherein The database described in step (4) includes the NIST database and the IMS database.

6. The evaluation method according to claim 5, wherein The multivariate statistical methods described in step (5) include principal component analysis, cluster analysis and fingerprint similarity analysis.

7. Use of the evaluation method according to any one of claims 1 to 6 in evaluating and / or monitoring the quality of cherry tomatoes during storage.

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