Method for determining storage time based on propionaldehyde / hexanal cereal aroma ratio

Abstract

The application discloses a method for judging storage time based on propyl aldehyde and hexyl aldehyde grain aroma ratio, and belongs to the technical field of grain quality detection. In the prior art, the method for judging grain storage time is difficult to realize rapid, accurate and non-destructive detection, and cannot meet the relevant control requirements. The technical scheme points are as follows: a headspace gas of a to-be-detected grain sample is prepared, and is injected into a gas chromatography-ion mobility spectrometry instrument to obtain a spectrum, propyl aldehyde and hexyl aldehyde characteristic peaks derived from grain aroma are identified in the spectrum, and a peak volume ratio R=A1 / A2 is calculated; a monotonically increasing corresponding relationship between storage time and an upper limit threshold value of R value of the same variety of grains under conventional storage is established in advance, the measured R value is compared with the upper limit threshold value to judge the storage time, and when the upper limit threshold values of adjacent months do not meet the strict increasing, the adjacent months are combined into one storage period. The propyl aldehyde and hexyl aldehyde ratio in the grain aroma can be used to quickly and accurately judge the grain storage time, and provide support for grain quality evaluation, storage and circulation control.

Description

Technical Field

[0001] This invention relates to the field of grain quality testing technology. More specifically, this invention relates to a method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma. Background Technology

[0002] The storage period of grains is directly related to their freshness and edibility. Accurately determining the actual storage time of grains is a crucial foundation for grain storage management, quality traceability, and safety control. Currently, the methods for determining grain storage time in the grain storage industry are relatively limited. Traditional management models mainly rely on manual ledger registration and storage records for time verification. This method is susceptible to factors such as human error in registration, invalid archives, and gaps in information flow, resulting in insufficient reliability of time traceability results.

[0003] While existing physicochemical detection methods can be used to analyze the aging degree of grains, they mostly focus on conventional macroscopic indicators such as fatty acid value and germination rate. These indicators have long overall change cycles and small phase differences, and their changes are not obvious during the short-term storage stage of grains, making it difficult to sensitively reflect the continuous changes over storage time. Grains undergo continuous lipid oxidation metabolism during storage, and volatile aldehydes such as propionaldehyde and hexanal in grain aroma undergo regular dynamic changes with storage time. These can serve as intrinsic markers of storage duration. However, existing conventional detection equipment has limited separation and qualitative / quantitative capabilities for these trace volatile components, making it difficult to reliably obtain synchronous characteristic signals of both types of aldehydes. Grain aroma, as a comprehensive fingerprint reflecting chemical changes during storage, has not yet been effectively used for time determination due to the dynamic evolution of its components.

[0004] Conventional testing often uses the content of a single biomarker to determine quality, which is easily affected by external conditions such as grain moisture, variety, and storage environment. The data from a single test fluctuates greatly and cannot form a stable, quantifiable time correlation. At the same time, the changes in aroma components of grains are gradual across different storage months, and the boundaries between indicators of adjacent storage periods are blurred. The lack of quantitative segmentation criteria makes it difficult to achieve a precise division of storage time intervals.

[0005] For determining the storage time of grains, existing technologies have not yet established a quantitative discrimination system based on the signal ratio of volatile components in the aroma of grains. They cannot use the temporal changes in the proportion of characteristic substances to construct a standardized judgment threshold, resulting in low accuracy in determining the storage time of grains and coarse interval division, which makes it difficult to meet the actual application needs of large-scale grain storage detection. Summary of the Invention

[0006] Another objective of this invention is to provide a method for determining storage time based on the ratio of propionaldehyde to hexanal in grain aroma. Existing methods for detecting grain storage time struggle to utilize the changing patterns of characteristic volatile aldehydes during storage, lack quantitative analysis methods for the peak volume ratio of propionaldehyde to hexanal, and cannot establish a correspondence between storage time and the upper limit of the characteristic ratio threshold. Conventional determination methods are ill-suited to the dynamic changes of natural grain aging, the boundaries between adjacent storage months are ambiguous, and accurate determination of storage time cannot be achieved through interval division, resulting in a low degree of standardization in the overall detection and determination process.

[0007] Differences in the moisture content of grain samples directly affect the headspace heating equilibrium efficiency. Fixed heating time and segmented temperature modes cannot adapt to the gas release patterns of samples with different moisture contents. Moisture fluctuations can easily cause uneven release of headspace gas components, leading to deviations in subsequent detection signals. Standardized heating parameters will reduce the stability of characteristic substance extraction and cannot meet the pretreatment requirements of grains with different moisture contents.

[0008] The dissociation temperatures of starch-lipid complexes vary significantly among different grain varieties. Fixing the first-stage heating temperature can easily lead to insufficient or excessive dissociation of the complex. Abnormal dissociation states can interfere with the release rhythm of volatile aldehydes within the grain, causing distortion of the headspace analyte content and ultimately affecting the accuracy of characteristic peak signal acquisition, making it unsuitable for the universal detection requirements of multiple grain varieties.

[0009] The starch-lipid complex structure of grains with high dissociation temperatures is stable. Grinding at room temperature easily destroys endogenous volatile components, leading to loss of characteristic substances and oxidative deterioration. Conventional grinding without differentiated particle size settings results in excessively large particle sizes for high-temperature dissociation grains, insufficient component release, and overly fine powders for low-temperature grains that easily cause impurity interference. Furthermore, sample pretreatment adaptability is poor, and detection repeatability is insufficient.

[0010] The detection of volatile aldehydes in grains using gas chromatography coupled with ion mobility spectrometry lacks a defined parameter range suitable for these substances, allowing for arbitrary settings of carrier gas flow rate, column temperature, migration tube voltage, and temperature. These incompatible instrument conditions reduce the separation efficiency and migration recognition stability of small molecule aldehydes, easily leading to peak overlap and signal interference, thus affecting the accurate calculation of characteristic peak volumes and the precision of ratio determination.

[0011] Traditional storage time models rely solely on single-month data to set standards, resulting in irregular fluctuations in initial thresholds and an inability to form a strictly increasing threshold sequence. They lack parallel sample data statistics and upper quantile screening mechanisms, exhibit strong monthly data dispersion, lack reasonable time-segment merging rules, and result in disorganized storage time divisions, leading to poor consistency and reference value in detection and judgment results.

[0012] Simply increasing the threshold cannot guarantee the distinction between adjacent storage periods. The threshold difference between some adjacent months is too small, and the difference in the storage time interval is unreasonable, which can easily lead to confusion in the determination of short-term storage stages. Without the constraint of relative difference in thresholds, slight data differences are difficult to distinguish between actual storage durations, the model segmentation is not reasonable enough, and the error tolerance of detection and discrimination is low.

[0013] The lack of a unified standard for labeling storage periods leads to confusion between multi-month intervals and single-month periods after merging, easily causing ambiguity in the interpretation of test results. The inconsistent display of time period divisions hinders inspectors from quickly identifying the range of grain storage areas, reduces the standardization of test reports, and impedes the standardized promotion and unified application of this judgment method in the warehousing industry.

[0014] To achieve these objectives and other advantages according to the present invention, a method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma is provided, comprising the following steps: Step 1: Headspace Sample Preparation: Obtain the grain sample powder to be tested, weigh a quantitative amount of the sample powder and place it in a headspace vial, seal it and heat it to equilibrate to obtain the headspace gas of the sample to be analyzed. Step 2, Gas Chromatography-Ion Mobility Spectrometry (GC-IMS): Inject the sample headspace gas into the GC-IMS instrument and obtain the ion mobility spectrum of the sample under the set analytical conditions. Step 3: Characteristic substance identification and signal ratio calculation: Identify the characteristic response signal peaks of propionaldehyde and hexanal in the ion mobility spectrum, calculate the peak volume A1 of the characteristic response signal peak of propionaldehyde and the peak volume A2 of the characteristic response signal peak of hexanal, and calculate the ratio R of A1 and A2, R=A1 / A2. Step 4, Determining Storage Time: Grains of the same variety as the test samples are used in advance and stored under normal storage conditions. Samples are taken monthly and the ratio R of each sample is determined according to steps 1 to 3. Based on the dataset of ratio R for each month, a monotonically increasing correspondence between storage time and the upper limit of the threshold of ratio R is established. The upper limit of the threshold is determined by statistical quantiles. The measured ratio R of the sample to be tested is compared with the upper limit of the threshold mentioned above. The corresponding storage time is determined according to the threshold range into which the measured ratio R falls. When the upper limit of the threshold of adjacent months does not meet the strict increasing requirement, the corresponding months are merged into a storage period for determination.

[0015] Preferably, in step one, the heating equilibrium method is as follows: Based on the moisture content w of the grain sample to be tested, the total heating equilibrium time t is set, where w is expressed as a mass percentage, and: When w ≤ 12%, t = 15 minutes; When w ≥ 14%, t = 35 minutes; When 12% < w < 14%, calculate according to the linear interpolation formula t = 15 + 10×(w - 12), round the calculation result to an integer, and the unit of t is minutes; Then divide the total heating balance time t into two stages: The first stage is maintained at 50°C to 55°C for (t - 10) minutes; The second stage is maintained at 70°C to 75°C for 10 minutes.

[0016] Preferably, the first stage is maintained at 50°C to 55°C for (t - 10) minutes, and the specific temperature of the first stage is preset according to the starch-lipid complex dissociation temperature T of the cereal variety to be tested; P The dissociation temperature T P is obtained by measuring the starch-lipid complex dissociation peak temperature of the cereal of the same variety as the sample to be tested using differential scanning calorimetry; If T P ≤ 50°C, the temperature of the first stage is 50°C; If 50°C < T P < 55°C, the temperature of the first stage is T P ; If T P ≥ 55°C, the temperature of the first stage is taken as 55°C.

[0017] Preferably, when the starch-lipid complex dissociation temperature T of the cereal variety to be tested P ≥ 55°C, the following pretreatment is adopted in the process of obtaining the powder of the cereal sample to be tested in step one: Place the cereal sample to be tested under the condition of -20°C to -10°C and freeze it for 30 minutes to 60 minutes. After taking it out, use a cryogenic grinder to crush it under liquid nitrogen cooling, and sieve it to obtain a sample powder with a particle size less than 150 microns. The sample temperature during crushing is lower than 0°C; Then weigh the obtained sample powder according to the subsequent operations of step one, place it in a headspace vial, seal it and heat it to equilibrium; When the starch-lipid complex dissociation temperature T of the cereal variety to be tested P < 55°C, crush the cereal sample to be tested at room temperature to obtain a sample powder with a particle size of 300 microns to 500 microns.

[0018] Preferably, in step two, the set analysis conditions are: the carrier gas for the gas chromatography part is nitrogen, the carrier gas flow rate is 1 ml to 5 ml per minute, and the column temperature is 40°C to 80°C; the migration tube voltage for the ion mobility spectrometry part is 2000 V to 5000 V, and the migration tube temperature is 60°C to 100°C.

[0019] Preferably, in step four, monthly sampling includes: starting from month 0 when storage begins, sampling is performed every month thereafter, with at least 5 parallel samples measured in each month, to obtain a dataset of the ratios R of each storage month M, where M = 0, 1, 2, …, N, and N is the maximum number of storage months covered by the model. The upper quantile is between 85% and 95%. A strictly increasing threshold sequence and corresponding storage periods are constructed using the following steps: Calculate the upper quantile of M for each month as the initial threshold, denoted as T0, T1, T2, …, T N ; If the initial threshold sequence is T0, T1, T2, …, T N It already satisfies strict increasing condition, that is, for every i = 0,1,…,N-1, there exists T. i <T {i+1} Let K = N+1, and for j = 1, 2, …, N+1, take U j = T {j-1} Storage period S j This corresponds to a single month j-1; where, if j-1 = 0, then the storage period S j Indicated as "0 months", otherwise the storage period S j Represented as a number for that month; If the initial threshold sequence is T0, T1, T2, …, T N It does not satisfy strict increasing, that is, there exists i such that T i ≥ T {i+1} Then, adjacent months with a non-strictly increasing relationship are merged into a continuous storage period, and the upper quantile of all ratios R within the merged period is recalculated. This upper quantile is used as the upper threshold of the merged period. The above merging and recalculation process is repeated until a strictly increasing threshold sequence U1, U2, …, U is obtained. K Where K ≤ N+1; U1, U2, …, U K These correspond to the merged consecutive storage periods S1, S2, …, S, respectively. K Each storage period is represented in the form of start month-end month. If a storage period contains only a single month, it is directly represented by the number of that month. Here, K is the total number of storage periods that are finally divided. The specific rules for determining storage time are as follows: If the measured ratio R ≤ U1, then the storage time of the grain to be tested is determined to fall into storage period S1; If there exists an integer i satisfying 2 ≤ i ≤ K, and U {i-1} <R ≤ U i If the storage time of the grain to be tested falls within storage period S, then it is determined that the storage time falls within storage period S.i ; If the measured ratio R > U K If the storage time of the grain being tested is greater than N months, then it is determined that the grain has been stored for more than N months.

[0020] Preferably, the initial threshold sequence is T0, T1, T2, …, T N When the condition is strictly increasing, the relative difference d between adjacent thresholds is further calculated. i = (T {i+1} - T i ) / T i If there exists one of i such that d i If the ratio is less than 10%, then the i-th month and the (i+1)-th month are merged into a continuous storage period, and the upper quantile is recalculated using all the original ratio R data in the merged period. This upper quantile is then used as the threshold for the merged period. After each merge, if the newly obtained threshold sequence does not satisfy strict increasing, the merging and recalculation method used when the initial threshold sequence did not satisfy strict increasing is adopted to continue merging until the new threshold sequence restores strict increasing. Then recalculate the relative differences between all adjacent thresholds in the current threshold sequence, and repeat the above merging and recalculation process until the relative differences between all adjacent thresholds are not less than 10% and the current threshold sequence satisfies strict increasing, resulting in a set of strictly increasing threshold sequences U1, U2, …, U K and their corresponding continuous storage periods S1, S2, …, S K The storage time of the sample to be tested is determined according to the storage time determination rules.

[0021] Preferably, after merging two adjacent months, the resulting storage period is represented by a hyphen between the start month number and the end month number; if the storage period contains three or more consecutive months, it is still represented by the start month-end month format; if one of the storage periods ultimately contains only a single month, the number of that month is used directly.

[0022] The present invention has at least the following beneficial effects: This invention identifies the characteristic peaks of propionaldehyde and hexanal in the aroma of grains and calculates their peak volume ratios. By combining this with statistical quantiles to establish a monotonically increasing threshold correspondence, storage intervals can be accurately defined based on measured ratios. It also performs time-segmentation correction for abnormal threshold increases, effectively adapting to the aging patterns of grains during long-term storage. This overcomes the limitations of traditional experience-based judgments, improves the quantification and objectivity of grain storage time detection, and has a wider range of applications.

[0023] This invention sets the heating equilibrium time based on the differences in grain moisture content, and combines it with a two-stage gradient heating mode to adapt to the headspace volatile release characteristics of samples with different moisture contents, ensuring that grain aroma components can be fully and stably released. Linear interpolation calculation ensures that the parameters of medium-moisture samples are set reasonably, and segmented temperature control can stabilize the sample pre-equilibrium state and enhance the full release of volatile aldehydes, reducing detection errors caused by moisture and improving the consistency of sample pretreatment.

[0024] This invention combines differential scanning calorimetry (DSC) to determine the dissociation temperature, adaptively setting the first-stage heating temperature to precisely match the dissociation characteristics of different grain starch-lipid complexes. This avoids abnormal complex dissociation caused by excessively high or low temperatures, ensures stable precipitation of volatile components in grain aroma, reduces matrix interference, makes headspace gas components more closely resemble the actual storage conditions of the sample, and enhances the versatility of multi-variety detection.

[0025] This invention differentiates the pulverization method and particle size parameters based on dissociation temperature. High-temperature dissociated grains are pulverized using low-temperature cryogenic pulverization, which can inhibit the oxidation and loss of volatile aldehydes and preserve the original characteristics of grain aroma components. Differentiated particle size control can balance the release efficiency of substances with the interference of impurities, reduce the damage to the target analytes during the pulverization process, stabilize the quality of sample pretreatment, and significantly improve the repeatability of parallel sample test results.

[0026] This invention defines matching operating parameters for gas chromatography and ion mobility spectrometry, which can optimize the chromatographic separation and ion migration recognition efficiency of small molecule aldehydes. Appropriate temperature range, voltage, and carrier gas parameters can reduce interference from impurity peaks, improve the integrity of target substance peak shapes, ensure the independent distinguishability of propionaldehyde and hexanal signal peaks, accurately capture key aldehyde signals in grain aromas, provide a stable instrumental basis for accurate peak volume calculation and ratio calculation, and improve the reliability of detection data.

[0027] This invention employs data collected from multiple parallel samples, constructs an initial threshold using upper quantiles, and calibrates the threshold sequence through dynamic merging rules, thus eliminating errors caused by fluctuations in single sample data. This forms a strictly incremental standardized threshold system, standardizes the logic for dividing storage periods, clearly defines different storage cycle ranges, provides a more comprehensive basis for determining grain storage time, and directly reflects the dynamic evolution of grain aroma, significantly improving result stability.

[0028] This invention adds a constraint on the relative difference between adjacent thresholds, automatically merges storage months with low distinguishability, and continuously optimizes the threshold sequence structure. This effectively reduces the confusion between adjacent time periods, reasonably widens the numerical differences between different storage intervals, improves the scientific rigor and rationality of time segmentation, weakens the risk of misjudgment caused by minor data fluctuations, and further enhances the practical performance of the overall detection model.

[0029] This invention standardizes the text labeling format for different storage periods, clearly classifying and describing single months and combined intervals, resulting in a concise and intuitive structure. It effectively avoids interpretation bias and ambiguity in test results, unifies output standards, and facilitates rapid reading, recording, and archiving of test data by warehouse staff, improving the regularity of test reports and promoting the standardized application of this testing method in the grain storage field. Using the aldehyde analogue value in grain aroma as the core criterion, this method does not rely on subjective experience evaluation, resulting in objective and quantifiable test results.

[0030] 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

[0031] The present invention will be further described in detail below with reference to embodiments, so that those skilled in the art can implement it based on the description.

[0032] Both propionaldehyde and hexanal originate from the auto-oxidative decomposition of unsaturated fatty acids (mainly linoleic acid and linolenic acid) in grains. In the early stages of storage, short-chain aldehydes (such as propionaldehyde) are generated at a faster rate; however, as storage time increases, the accumulation rate of hexanal gradually becomes dominant. This difference in their generation kinetics leads to a generally monotonically increasing trend in the propionaldehyde / hexanal peak volume ratio under conventional storage conditions, although the rate of increase may gradually decrease. Based on this inherent law, this invention establishes a quantitative correspondence between the ratio and storage time.

[0033] This invention provides a method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma, comprising the following steps: Step 1: Headspace Sample Preparation: Obtain the grain sample powder to be tested, weigh a quantitative amount of the sample powder and place it in a headspace vial, seal it and heat it to equilibrate to obtain the headspace gas of the sample to be analyzed. Step 2, Gas Chromatography-Ion Mobility Spectrometry (GC-IMS): Inject the sample headspace gas into the GC-IMS instrument and obtain the ion mobility spectrum of the sample under the set analytical conditions. Step 3: Characteristic substance identification and signal ratio calculation: Identify the characteristic response signal peaks of propionaldehyde and hexanal in the ion mobility spectrum, calculate the peak volume A1 of the characteristic response signal peak of propionaldehyde and the peak volume A2 of the characteristic response signal peak of hexanal, and calculate the ratio R of A1 and A2, R=A1 / A2. Step 4, Determining Storage Time: Grains of the same variety as the test samples are used in advance and stored under normal storage conditions. Samples are taken monthly and the ratio R of each sample is determined according to steps 1 to 3. Based on the dataset of ratio R for each month, a monotonically increasing correspondence between storage time and the upper limit of the threshold of ratio R is established. The upper limit of the threshold is determined by statistical quantiles. The measured ratio R of the sample to be tested is compared with the upper limit of the threshold mentioned above. The corresponding storage time is determined according to the threshold range into which the measured ratio R falls. When the upper limit of the threshold of adjacent months does not meet the strict increasing requirement, the corresponding months are merged into a storage period for determination.

[0034] For example, the test subject is selected from the same variety of grain as the grain to be tested. The raw material can be sourced from a conventional grain storage facility, and normal grain free from mold, insect infestation, and impurities should be selected as the sample. When preparing the grain sample powder, a commercial grain grinder can be used for grinding. After grinding, impurities are removed by sieving. A quantitative amount of sample powder (5g, 10g, or 15g) is weighed and placed in a sealable headspace vial (glass, 20mL-100mL). After sealing, it is placed on a shelf inside a constant temperature heating module (a programmable constant temperature chamber). The heating equilibrium temperature can be set within the range of 40℃ to 80℃. The core detection equipment can be a gas chromatography-ion mobility spectrometry (GC-IMS) instrument, placed on a horizontal workbench in the laboratory. The gas outlet of the headspace vial is connected to the instrument's inlet via an inert transfer line, which can be made of stainless steel. Statistical quantiles can be selected from 85%, 90%, or 95% to set the upper limit of the threshold for storage time and the ratio R. The specific threshold values ​​can be obtained through actual measurements in long-term storage experiments of the same grain variety, such as a threshold of 0.15 for 0 months, 0.28 for 1 month, and 0.42 for 2 months. In addition, conventional storage conditions can be set as a ventilated environment with a temperature of 20°C to 25°C and a relative humidity of 50% to 70%. The characteristic response signal peaks of propionaldehyde and hexanal are identified based on their respective retention times in gas chromatography and drift times in ion mobility spectra. The retention times and drift times are determined in advance by injecting single-standard samples.

[0035] During the process, the preparation, weighing, and headspace bottle sealing of the grain sample powder to be tested are completed according to the above requirements. The sealed headspace bottle is then placed in a constant temperature heating module for heating equilibration to obtain the headspace gas of the sample to be analyzed. Subsequently, the sample headspace gas is injected into a gas chromatography-ion mobility spectrometry (GC-IMS) instrument, and the ion mobility spectrum of the sample is acquired under the set analytical conditions. The characteristic response signal peaks of propionaldehyde and hexanal are identified in the ion mobility spectrum. Using the instrument's built-in data analysis software, the peak volumes A1 and A2 of the characteristic response signal peaks of propionaldehyde and hexanal are calculated respectively, and the ratio R of A1 and A2 is calculated. Multiple sets of R value data are accumulated by sampling and testing the same variety of grain under conventional storage conditions on a monthly basis. The upper quantile is used to establish a monotonically increasing correspondence between storage time and the upper threshold. The storage time is determined by comparing the measured R value with the threshold range, and adjacent months with abnormal increases are merged.

[0036] With this technical solution, the present invention relies on the regular change of the proportion of aldehyde substances during the grain storage process to establish a quantitative detection and segmented determination mode, weakening the deviation caused by traditional empirical judgment. Through the setting of statistical thresholds and the correction of time period merging, it adapts to the slow change characteristics of natural aging of grains. The detection process is standardized and unified, and it can stably distinguish grains in different storage periods, providing a reliable detection basis for the quality control of grain storage.

[0037] In another technical solution, in step one, the method of heating balance is specifically as follows: According to the moisture content w of the待测谷物样品 (grain sample to be measured), set the total heating balance time t, where w is in mass percentage, and: When w ≤ 12%, t = 15 minutes; When w ≥ 14%, t = 35 minutes; When 12% < w < 14%, calculate according to the linear interpolation formula t = 15 + 10×(w - 12), round the calculation result to the nearest integer, and the unit of t is minutes; Then divide the total heating balance time t into two stages: The first stage is maintained at 50°C to 55°C for (t - 10) minutes; The second stage is maintained at 70°C to 75°C for 10 minutes.

[0038] Exemplarily, the moisture content w can be detected by a commercial rapid grain moisture detector, with a measurement range of 0% to 20%, and w is in mass percentage. The total heating balance time t is set according to the moisture range division, with critical nodes of 12% and 14%. The intermediate range is calculated according to the linear interpolation formula t = 15 + 10×(w - 12) and rounded to the nearest integer, with the unit of minutes. The heating equipment can be a programmable constant temperature oven, and the inside of the oven is equipped with a layered storage rack for placing headspace bottles. The temperature control accuracy is stable, and the overall layout is in the sample pretreatment area. The heating process is divided into two fixed stages. The first stage is temperature-controlled at 50°C to 55°C, and the second stage is fixed at 70°C to 75°C. The durations of the two stages are uniformly controlled by the equipment timing module. The headspace sealing component can be a high-temperature resistant silicone gasket. The program temperature rise is automatically switched between the two stages, and the switching time does not exceed 1 minute to avoid the sudden change of pressure in the headspace bottle due to the sudden change of temperature and affect the sealing performance.

[0039] It should be noted that the term "待测谷物样品" needs to be accurately translated according to the specific context. Here it is tentatively translated as "grain sample to be measured".During the process, the actual moisture content of the grain is first measured. The corresponding total heating time is then matched to the measured value. For intermediate moisture content samples, precise time parameters are calculated using a formula. The headspace vial containing the sample powder is sealed and placed inside the oven. It is first kept in a low-temperature range for initial equilibration and settling, for a period equal to the total time minus 10 minutes. Then, it automatically switches to a high-temperature environment and maintains a constant temperature for 10 minutes. This segmented gradient heating gradually releases the volatile components within the grain, mitigating the uneven release of volatiles caused by moisture differences, and stably obtaining a headspace with uniform composition to meet the requirements of subsequent instrument sample introduction and detection.

[0040] This invention employs a technical solution that uses differentiated heating conditions based on grain moisture content differences. Linear interpolation smoothly connects parameters across intermediate moisture ranges, making the pretreatment conditions more suitable for samples with different moisture contents. A two-stage temperature control method stabilizes the sample equilibrium state, reduces detection interference caused by moisture fluctuations, ensures consistent headspace gas composition, and improves the overall stability of the sample pretreatment process.

[0041] In another technical approach, the first stage is maintained at 50°C to 55°C for (t-10) minutes, with the specific temperature of the first stage determined based on the starch-lipid complex dissociation temperature T of the grain variety being tested. P Preset; dissociation temperature T P The dissociation peak temperature of starch-lipid complex in the same variety of grain as the test sample was determined by differential scanning calorimetry. If T P If the temperature is ≤ 50℃, then the first stage temperature is 50℃; If 50℃ <T P If the temperature is less than 55℃, then the temperature of the first stage is T. P ; If T P If the temperature is ≥55℃, then the first stage temperature is 55℃.

[0042] For example, the dissociation temperature T of the starch-lipid complex P Commercial differential scanning calorimetry (DSC) instruments can be used for measurement. The instrument is placed in a constant-temperature testing area in the laboratory, using the measured temperature of the grain dissociation peak as the criterion. Using 50℃ and 55℃ as temperature grading thresholds, three levels of first-stage heating temperature settings are established. The equipment uses the aforementioned constant-temperature oven, with temperature sensors embedded in the sidewalls of the cavity to monitor and lock the heating temperature in real time, ensuring stable output of the set temperature. When T... P When the temperature is equal to 50℃ or 55℃, treat it as a boundary condition: T P =50℃, take 50℃, T P =55℃, take 55℃.

[0043] During the work process, the T values ​​of the corresponding grain varieties were measured in advance. PThe numerical values ​​are matched with the first-stage heating temperature parameters based on the measured temperature range. Materials in the low-temperature range use a fixed heating temperature, while materials in the intermediate range directly use the measured dissociation temperature. Materials with high thresholds have a uniformly limited upper limit temperature. The initial equilibrium temperature is specifically adjusted to ensure that the starch and lipid complexes within the grain are in a reasonable dissociation state, guaranteeing a stable release of volatile aldehydes and reducing the detection impact of differences in the varietal matrix.

[0044] This invention employs a technical solution that adaptively adjusts the heating temperature based on the inherent physical properties of grains, avoiding abnormal complex dissociation caused by fixed temperatures and reducing matrix interference from different grain varieties. The adaptable temperature settings enhance the method's versatility, ensuring consistent detection conditions for various grain types and maintaining stable volatile matter release.

[0045] In another technical solution, when the starch-lipid complex dissociation temperature T of the grain variety being tested... P At ≥55℃, the following pretreatment is used in step one to obtain the powdered grain sample: The grain sample to be tested was frozen at -20℃ to -10℃ for 30 to 60 minutes. After being taken out, it was crushed using a low-temperature grinder under liquid nitrogen cooling and sieved to obtain sample powder with a particle size of less than 150 micrometers. The sample temperature was below 0℃ during crushing. Then, the obtained sample powder is weighed according to the subsequent operations in step one, placed in a headspace vial, sealed, and heated to equilibrium; When the starch-lipid complex dissociation temperature T of the grain variety to be tested P At temperatures below 55°C, the grain sample to be tested is pulverized at room temperature to obtain sample powder with a particle size of 300 to 500 micrometers.

[0046] For example, using 55℃ as T P For high dissociation temperature grains, pretreatment can utilize commercial low-temperature freezers, liquid nitrogen cryogenic grinders, and 150-micron stainless steel testing sieves, with the low-temperature equipment placed in the sample refrigeration and grinding area. For low dissociation temperature grains, room-temperature grinders and 300- to 500-micron separating sieves can be used. The freezing control range is -20℃ to -10℃, with freezing times selectable at 30, 45, or 60 minutes. The sample temperature is maintained below 0℃ throughout the cryogenic grinding process. For T... P Grains with a temperature of 55°C or higher are classified as high dissociation temperature grains and undergo cryogenic freezing and liquid nitrogen grinding processes. Powder that does not meet the particle size requirements after sieving should be re-ground until all particles pass through the sieve with the specified aperture.

[0047] During the work process, according to T PThe test results distinguished between two milling processes. Grains with high dissociation temperatures were first pre-cooled by low-temperature freezing, then pulverized at low temperature under liquid nitrogen protection, and sieved to obtain fine-particle-size powder. Grains with low dissociation temperatures were directly pulverized at room temperature, and sieved to obtain medium-particle-size powder. After both types of powders were prepared, they were uniformly subjected to subsequent processes such as weighing, sealing, and headspace balancing. Standardized sample preparation was completed in strict accordance with the previous steps to avoid component damage caused by incompatible pulverization methods.

[0048] Using this technical solution, the present invention sets differentiated grinding methods and particle size parameters for grains with different structural characteristics. Low-temperature grinding can reduce the oxidation loss of volatile substances, graded sieving controls powder particle size, reduces impurity interference and insufficient component release, and effectively improves the consistency of parallel sample test results.

[0049] In another technical solution, in step two, the analytical conditions are set as follows: the carrier gas for the gas chromatography section is nitrogen, the carrier gas flow rate is 1 mL to 5 mL per minute, and the column temperature is 40°C to 80°C; the migration tube voltage for the ion mobility spectrometry section is 2000 V to 5000 V, and the migration tube temperature is 60°C to 100°C.

[0050] For example, high-purity nitrogen can be used as the carrier gas in gas chromatography, with a nitrogen generator installed on the instrument's inlet side. The carrier gas flow rate is controlled between 1 mL / min and 5 mL / min, and the capillary column is fixedly mounted inside the chromatographic oven. The ion mobility spectrometry unit can be equipped with an adjustable high-voltage power supply and a temperature-controlled migration tube. The power supply module is integrated into the instrument's electrical compartment, with the migration tube voltage adjustable from 2000V to 5000V and the temperature stable between 60℃ and 100℃. In specific analyses, the flow rate and temperature can be optimized based on the separation effect of the target aldehydes, with the preferred flow rate being 3 mL / min, column temperature 60℃, migration tube voltage 3000V, and migration tube temperature 80℃.

[0051] During operation, after the instrument is powered on and warmed up, the operating parameters such as carrier gas flow rate, column temperature, migration tube voltage, and temperature are adjusted within the specified range. Chromatographic separation of the headspace mixture is achieved through stable carrier gas delivery. The separated small-molecule aldehydes enter the ion migration region, where ionization and secondary separation are completed under constant voltage and temperature conditions, forming complete and independent characteristic spectra, providing effective detection data for subsequent peak volume calculations.

[0052] By adopting this technical solution, the present invention limits the instrument operating parameters adapted to the detection of aldehyde volatiles, optimizes the component separation and ion recognition effects, reduces signal overlap and baseline interference, stabilizes the target characteristic peak morphology, ensures the accuracy of subsequent data calculation, and improves the stability of the instrument detection conditions.

[0053] In another technical solution, step four, monthly sampling includes: starting from month 0 of the storage period, sampling is performed every month thereafter, with at least 5 parallel samples measured in each month, to obtain a dataset of the ratios R of the storage months M, where M = 0, 1, 2, …, N, and N is the maximum number of storage months covered by the model. The upper quantile is between 85% and 95%. A strictly increasing threshold sequence and corresponding storage periods are constructed using the following steps: Calculate the upper quantile of M for each month as the initial threshold, denoted as T0, T1, T2, …, T N ; If the initial threshold sequence is T0, T1, T2, …, T N It already satisfies strict increasing condition, that is, for every i = 0,1,…,N-1, there exists T. i <T {i+1} Let K = N+1, and for j = 1, 2, …, N+1, take U j = T {j-1} Storage period S j This corresponds to a single month j-1; where, if j-1 = 0, then the storage period S j Indicated as "0 months", otherwise the storage period S j Represented as a number for that month; If the initial threshold sequence is T0, T1, T2, …, T N It does not satisfy strict increasing, that is, there exists i such that T i ≥ T {i+1} Then, adjacent months with a non-strictly increasing relationship are merged into a continuous storage period, and the upper quantile of all ratios R within the merged period is recalculated. This upper quantile is used as the upper threshold of the merged period. The above merging and recalculation process is repeated until a strictly increasing threshold sequence U1, U2, …, U is obtained. K Where K ≤ N+1; U1, U2, …, U K These correspond to the merged consecutive storage periods S1, S2, …, S, respectively. K Each storage period is represented in the form of start month - end month. If a storage period contains only a single month, it is directly represented by the number of that month. Here, K is the total number of storage periods that are finally divided (i.e., the number of thresholds in the threshold sequence, not the number of storage months). The specific rules for determining storage time are as follows: If the measured ratio R ≤ U1, then the storage time of the grain to be tested is determined to fall into storage period S1; If there exists an integer i satisfying 2 ≤ i ≤ K, and U {i-1} <R ≤ U iIf the storage time of the grain to be tested falls within storage period S, then it is determined that the storage time falls within storage period S. i ; If the measured ratio R > U K If the storage time of the grain being tested is greater than N months, then it is determined that the grain has been stored for more than N months.

[0054] For example, sealed grain storage tanks can be used as storage containers, and they are placed uniformly on the surface of the storage shelves. Sampling is performed monthly, with at least five parallel samples per month. All samples follow the aforementioned sample preparation and testing procedures. The upper quantiles are set at 85%, 90%, and 95%. Data statistics can be performed using standard office data processing equipment to uniformly summarize the R-value datasets for each month. The initial threshold T is then calculated based on the quantiles. M If the relative standard deviation (RSD) of the test results of parallel samples in a certain month is greater than 15%, the number of parallel samples can be appropriately increased to 8 to 10. When merging adjacent months to recalculate the upper quantile, all original R values ​​(regardless of month) within the merging period need to be merged into a single dataset, and then the upper quantile of this dataset is taken as the new threshold.

[0055] During the process, data is collected monthly starting from the zero storage period. The upper quantile of each month is calculated to obtain an initial threshold sequence, and the increasing pattern of the thresholds is verified one by one. For threshold intervals that are inverted or decreasing, adjacent storage months are merged and the upper quantile of the interval is recalculated. This process is repeated until the threshold sequence is strictly increasing. Based on the final threshold interval division rules, the interval determination and result division of grain storage time are completed.

[0056] By adopting this technical solution, the present invention combines parallel sample statistics and quantile calculation to reduce the impact of random data fluctuations. By standardizing the threshold system through standardized merging rules, the segmentation of storage time is made more reasonable, the judgment criteria are clearly quantified, and the objectivity of the test results is improved.

[0057] In another technical solution, the initial threshold sequence is T0, T1, T2, …, T N When the condition is strictly increasing, the relative difference d between adjacent thresholds is further calculated. i = (T {i+1} - T i ) / T i If there exists one of i such that d i If the ratio is less than 10%, then the i-th month and the (i+1)-th month are merged into a continuous storage period, and the upper quantile is recalculated using all the original ratio R data in the merged period. This upper quantile is then used as the threshold for the merged period. After each merge, if the newly obtained threshold sequence does not satisfy strict increasing, the merging and recalculation method used when the initial threshold sequence did not satisfy strict increasing is adopted to continue merging until the new threshold sequence restores strict increasing. Then recalculate the relative differences between all adjacent thresholds in the current threshold sequence, and repeat the above merging and recalculation process until the relative differences between all adjacent thresholds are not less than 10% and the current threshold sequence satisfies strict increasing, resulting in a set of strictly increasing threshold sequences U1, U2, …, U K and their corresponding continuous storage periods S1, S2, …, S K The storage time of the sample to be tested is determined according to the storage time determination rules.

[0058] For example, the critical value for the relative difference between adjacent thresholds is fixed at 10%, the formula for calculating the difference is uniformly fixed, and conventional calculation tools can be used for data verification. Data tables are used to uniformly organize the thresholds and difference values. After merging, the thresholds are still calculated uniformly using the upper quantile method. After each merge, the relative difference between all adjacent thresholds in the new threshold sequence needs to be recalculated, and whether the strict increasing condition is met needs to be rechecked. If the new sequence is not strictly increasing due to merging, the same iterative merging method is used: repeatedly merge all adjacent time periods with a non-strict increasing relationship in the current sequence, recalculate the upper quantile of each merged time period after each merge, and repeat this process until the sequence meets the strict increasing condition again; then check the relative difference between all adjacent thresholds again. If there are still those less than 10%, continue merging and repeat the increasing condition check and correction steps described in this paragraph (i.e., repeatedly merge non-strict increasing pairs and recalculate the upper quantile) until the sequence meets the strict increasing condition simultaneously and all adjacent relative differences are ≥10% after multiple iterations.

[0059] During the process, based on a strictly increasing threshold, the relative differences between adjacent thresholds are calculated one by one. Adjacent months with differences less than 10% are merged and integrated, and the upper limit of the interval threshold is recalculated. After merging, the increasing and difference indicators are verified again, and the process is repeatedly cyclically corrected until all adjacent thresholds simultaneously meet the requirements of strict increasing and difference limits. Sample judgment is then carried out based on the optimized threshold system.

[0060] By adopting this technical solution, the present invention adds threshold difference constraints, increases the numerical differentiation of different storage periods, weakens the judgment confusion caused by the gradual change of indicators, and optimizes the discrimination model structure through multiple rounds of correction, so that the storage time segmentation results are more in line with the actual aging law of grains.

[0061] In another technical solution, after merging two adjacent months, the resulting storage period is represented by a hyphen between the start month number and the end month number. If the storage period contains three or more consecutive months, it is still represented by the start month-end month format. If one of the storage periods ultimately contains only a single month, the number of that month is used directly.

[0062] For example, a standardized format is used to label storage periods. Single months are labeled directly with Arabic numerals, and continuous intervals are labeled with the start month and end month. Record media can be conventional text editing documents and laboratory paper record sheets. Archives are uniformly stored in a dedicated filing cabinet, and a unified expression rule is used throughout.

[0063] During the work process, after completing the merging of time periods and the division of intervals, the content is uniformly and standardized according to the coverage of the months. The numbers of a single storage month are simplified, and the start and end month combination is uniformly used for multiple consecutive months. Custom abbreviations and non-standard expressions are not used throughout the process to ensure that all test records are in a uniform and standardized format.

[0064] By adopting this technical solution, the present invention standardizes the labeling format of storage periods, avoids interpretation deviations caused by confusing expressions, and makes the test records concise and clear, which facilitates data archiving, retrieval and horizontal comparison, and meets the standardized recording requirements of batch testing work.

[0065] The specific implementation method is as follows: Example 1 Taking the japonica rice (variety: Jijing 816) harvested in a certain grain depot that year as an example, the storage time was determined according to the method of the present invention.

[0066] First, the rice variety was stored in a standard grain warehouse under normal storage conditions (temperature 20℃~25℃, relative humidity 60%~65%). Starting from the month of storage (referred to as month 0), samples were taken monthly for 12 consecutive months. After each sampling, the samples were hulled, impurities removed, pulverized using a laboratory grinder, and passed through a 60-mesh sieve to obtain uniformly sized rice powder. 10g of the powder was weighed and placed in a 100mL headspace vial, sealed, and heated at 60℃ for equilibration for 20 minutes to prepare headspace gas.

[0067] Analysis was performed using gas chromatography-ion mobility spectrometry (GC-IMS): carrier gas (nitrogen) flow rate 3 mL / min, column temperature 60℃, migration tube voltage 3000V, migration tube temperature 80℃. Headspace gas was injected into the instrument to obtain ion mobility spectra for samples from each month. Characteristic response peaks of propionaldehyde and hexanal were identified in the spectra based on pre-determined retention and drift times of propionaldehyde and hexanal standards. The peak volume A1 of propionaldehyde and peak volume A2 of hexanal for each sample were calculated using the instrument's built-in software, and the ratio R = A1 / A2 was calculated. Five samples were measured in parallel for each month, and the R values ​​of all parallel samples from each month were used to form a dataset.

[0068] The upper threshold for the R-value for each storage month was calculated using the 90th percentile: 0.15 for month 0, 0.28 for month 1, 0.42 for month 2, 0.55 for month 3, 0.67 for month 4, 0.78 for month 5, 0.86 for month 6, 0.92 for month 7, 0.96 for month 8, 0.98 for month 9, 0.99 for month 10, 1.00 for month 11, and 1.01 for month 12. This threshold sequence is strictly increasing and does not require merging of time periods.

[0069] A sample of the same rice variety with an unknown storage time was taken, and its propionaldehyde / hexanal peak volume ratio R was determined according to the same sample preparation and testing procedures. The measured R = 0.71. This measured value was compared with the above threshold sequence: 0.67 (4-month threshold) < 0.7 ≤ 0.78 (5-month threshold), therefore, the storage time of this sample was determined to be 5 months. After verification with the grain depot management personnel, the actual storage time of this sample was 5 months and 3 days, and the determination result was completely consistent with the actual situation (this embodiment did not use the relative difference merging rule; if this rule were used, adjacent months with differences less than 10% would need to be further merged).

[0070] In this embodiment, by establishing a correlation between the propionaldehyde / hexanal peak volume ratio and the threshold of the storage month, the ratio eliminates systematic errors such as sample moisture, particle size, and fluctuations in instrument injection volume. This results in a monotonically increasing and clearly distinguishable sequence of R values ​​between different months (threshold differences between adjacent months are 0.06~0.14). In contrast, the commonly used single propionaldehyde absolute peak volume method in existing technologies suffers from severe overlap in data distribution across months due to the lack of internal standard correction (the overlap ratio between adjacent months often exceeds 50%), and the threshold differences rapidly decrease to less than the fluctuation range within the month as storage time increases, making it impossible to accurately distinguish later months. Therefore, this invention overcomes the problems of existing detection methods, such as difficulty in utilizing changes in the proportion of volatile aldehydes, lack of a quantitative threshold system, blurred boundaries between adjacent months, and low standardization of detection, achieving accurate determination of grain storage time.

[0071] Example 2 Taking the hard red wheat (variety: Jimai 22) harvested in a certain grain depot that year as an example, the storage time is determined according to the method of the present invention.

[0072] First, the wheat variety was stored in a standard grain warehouse under normal storage conditions (temperature 20℃~25℃, relative humidity 60%~65%). Starting from the month of storage (referred to as month 0), samples were taken monthly for 12 consecutive months. After each sampling, the wheat samples were cleaned and purified, then pulverized using a laboratory grinder and passed through a 60-mesh sieve to obtain uniformly sized wheat powder. 10g of the powder was weighed and placed in a 100mL headspace vial, sealed, and heated at 60℃ for equilibration for 20 minutes to prepare headspace gas.

[0073] The same gas chromatography-ion mobility spectrometry (GC-IMS) analysis conditions as in Example 1 were used: carrier gas (nitrogen) flow rate 3 mL / min, column temperature 60 °C, migration tube voltage 3000 V, and migration tube temperature 80 °C. Headspace gas was injected into the instrument to obtain ion mobility spectra for samples from each month. Characteristic response signal peaks of propionaldehyde and hexanal were identified, and the peak volumes of propionaldehyde (A1) and hexanal (A2) for each sample were calculated using the instrument's built-in software, with the ratio R = A1 / A2 calculated. Five samples were measured in parallel for each month, and the R values ​​of all parallel samples from each month were used to form a dataset.

[0074] The upper threshold of the R value for each storage month was calculated using the 90th percentile: 0.14 for month 0, 0.27 for month 1, 0.41 for month 2, 0.53 for month 3, 0.66 for month 4, 0.76 for month 5, 0.84 for month 6, 0.91 for month 7, 0.94 for month 8, 0.97 for month 9, 0.98 for month 10, 0.99 for month 11, and 1.01 for month 12. This threshold sequence strictly increases, with the difference between adjacent months ranging from 0.07 to 0.13, consistent with the threshold sequence trend of japonica rice in Example 1, and the numerical deviation of each month does not exceed 0.02.

[0075] A sample of the same wheat variety with an unknown storage time was taken, and its propionaldehyde / hexanal peak volume ratio R was determined according to the same sample preparation and testing procedures. The measured R = 0.93. Comparing this measured value with the above threshold sequence: 0.91 (7-month threshold) < 0.93 ≤ 0.94 (8-month threshold), therefore, the storage time of this sample was determined to be 8 months. Verification with the grain depot management personnel confirmed that the actual storage time of this sample was 8 months and 9 days, confirming the accuracy of the determination.

[0076] This embodiment demonstrates that the method of the present invention is applicable not only to japonica rice but also to wheat, and that the threshold sequences among different grain varieties are highly consistent, thus confirming the universality of the present invention.

[0077] Example 3 Take the same batch of japonica rice (variety: Jijing 816) and adjust it to three different moisture contents: low moisture (11.2%), medium moisture (13.5%), and high moisture (15.0%). Prepare headspace samples according to the method in step one of this invention to verify the effectiveness of adjusting the heating equilibrium time and the two-stage heating based on the moisture content.

[0078] For low moisture samples (w=11.2% ≤12%), the total heating equilibrium time t=15 minutes, with the first stage (50℃) held for 5 minutes and the second stage (70℃) held for 10 minutes. For medium moisture samples (w=13.5%), the heating equilibrium time is calculated using the linear interpolation formula t=15+10×(13.5-12)=30 minutes, with the first stage (52℃, according to T... P For high-moisture samples (w=15.0% ≥14%), the total time is t=35 minutes, with the first stage (55℃) held for 25 minutes and the second stage (75℃) held for 10 minutes.

[0079] After heating and equilibrating the three samples according to the above conditions, they were analyzed under the same GC-IMS conditions as in Example 1, with each moisture level measured five times in parallel. The results showed that the characteristic peaks of propionaldehyde and hexanal in the three moisture samples were clear and well separated, and the coefficients of variation (CV) of the propionaldehyde / hexanal ratio R were 3.2%, 4.1%, and 4.5%, respectively, all less than 5%. In contrast, the control sample, heated for a fixed total time of 20 minutes at a single stage of 60°C, had a CV of 12% to 18%, and the propionaldehyde peak in the medium and high moisture samples showed obvious tailing, while the hexanal peak signal was low.

[0080] This embodiment demonstrates that by setting the total heating equilibrium time differently based on moisture content and combining it with a two-stage gradient heating, the consistency of headspace volatile release in grain samples with different moisture content can be significantly improved, reducing detection errors.

[0081] Example 4 A high starch-lipid complex dissociation temperature was selected from waxy corn (variety: Jingke Nuo 2000), and its T value was determined by differential scanning calorimetry. P =62℃. After storing the variety under standard storage conditions (temperature 20℃~25℃, relative humidity 60%~65%) for 6 months, samples were taken and divided into two groups for sample powder preparation to verify the effect of T... P Grains at ≥55℃ are processed using low-temperature freezing and liquid nitrogen grinding.

[0082] Experimental group: Following the high-temperature dissociation pretreatment procedure, the sample was frozen at -15℃ for 45 minutes, then removed and pulverized using a low-temperature grinder under liquid nitrogen cooling. The powder with a particle size of less than 150 micrometers was obtained by sieving. The sample temperature was below 0℃ throughout the pulverization process.

[0083] Control group: The sample was pulverized at room temperature (25°C) using a conventional pulverizer and sieved to obtain powder with a particle size of 300-500 micrometers.

[0084] The two groups of samples were analyzed under the same headspace equilibrium conditions (sample moisture content 13.2%, calculated t=27 minutes, first stage 53℃ for 17 minutes, second stage 73℃ for 10 minutes) and the same GC-IMS analysis conditions as in Example 1, with each group being measured in parallel 5 times.

[0085] The results showed that the peak volumes of propionaldehyde and hexanal in the experimental group were significantly higher than those in the control group (propionaldehyde increased by approximately 35%, and hexanal by approximately 28%). Furthermore, the relative standard deviation (RSD) of the R-values ​​between parallel samples in the experimental group was 3.8%, while the RSD in the control group was as high as 11.6%. The experimental group had significantly fewer impurity peaks and a more stable baseline. A t-test of the R-values ​​between the two groups showed a highly statistically significant difference (p < 0.01).

[0086] This embodiment shows that for high T P Conventional room temperature grinding of grains can lead to a significant loss or oxidation of volatile aldehydes. However, low-temperature freezing combined with liquid nitrogen grinding pretreatment can effectively preserve endogenous characteristic components and improve the intensity and stability of the detection signal.

[0087] Example 5 Using a certain variety of sorghum (variety: Liaoza 19) as the object, a 12-month storage experiment was conducted according to the method of Example 1. The 90th percentile threshold of the R value for each month was calculated to verify the time period merging rule when the relative difference between adjacent thresholds is less than 10%.

[0088] The initial threshold sequence is: October 0.16, January 0.29, February 0.43, March 0.57, April 0.70, May 0.83, June 0.92, July 1.03, August 1.10, September 1.12, October 1.13, November 1.14, December 1.15. This sequence satisfies strict increasing conditions. Further calculation of the relative difference d between adjacent thresholds is performed. i = (T {i+1} -T i ) / T i The calculation process and results are as follows: The first check calculated the relative differences between adjacent months: 81.3% for October and January, 48.3% for January and February, 32.6% for February and March, 22.8% for March and April, 18.6% for April and May, 10.8% for May and June, 12.0% for June and July, 6.8% for July and August, 1.8% for August and September, 0.9% for September and October, 0.9% for October and November, and 0.9% for November and December. Since the relative difference between July and August (6.8%) is less than 10%, and all subsequent adjacent differences are less than 10%, July and August were first merged to obtain the first merged period, "July-August". The 90th quantile was recalculated using the R-value data from all parallel samples in the original July and August data, yielding the U... 7-8 = 1.08. At this time, the threshold sequence is updated as follows: October 0.16, January 0.29, February 0.43, March 0.57, April 0.70, May 0.83, June 0.92, July-August 1.08, September 1.12, October 1.13, November 1.14, December 1.15.

[0089] The second check involved recalculating the relative differences between adjacent time periods in the new sequence: June to July-August was 17.4%, July-August to September was 3.7%, September to October was 0.9%, October to November was 0.9%, and November to December was 0.9%. Since the relative difference between July-August and September (3.7%) was less than 10%, July-August and September were merged into "July-September". Using the R-value data from the original 15 parallel samples (July, August, and September), the 90th percentile was recalculated, yielding U... 7-9 = 1.11. Update sequence: October 0.16, January 0.29, February 0.43, March 0.57, April 0.70, May 0.83, June 0.92, July-September 1.11, October 1.13, November 1.14, December 1.15.

[0090] The third check calculated the following: June to July-September: 20.7%; July-September to October: 1.8%; October to November: 0.9%; November to December: 0.9%. Combining July-September and October into "July-October," and using the 20 data points from July-October, the 90th percentile was recalculated, yielding U. 7-10 = 1.13. The sequence is updated as follows: October 0.16, January 0.29, February 0.43, March 0.57, April 0.70, May 0.83, June 0.92, July-October 1.13, November 1.14, December 1.15.

[0091] The fourth check calculated the following: June to July-October: 22.8%; July-October to November: 0.9%; November to December: 0.9%. Combining July-October and November into "July-November," and using the 25 data points from July-November, the 90th percentile was recalculated, yielding U. 7-11 =1.14. The sequence is updated as follows: October 0.16, January 0.29, February 0.43, March 0.57, April 0.70, May 0.83, June 0.92, July-November 1.14, December 1.15.

[0092] The fifth check calculated that the percentage for June and July-November was 23.9%, and the percentage for July-November and December was 0.9%. Combining July-November and December into "July-December," and using the 30 data points from July-December, the 90th percentile was recalculated, yielding U. 7-12 = 1.15. The final threshold sequence is: 0.16 for October, 0.29 for January, 0.43 for February, 0.57 for March, 0.70 for April, 0.83 for May, 0.92 for June, and 1.15 for July-December.

[0093] The relative differences between all adjacent periods in the final sequence were recalculated: 81.3% between October and January, 48.3% between January and February, 32.6% between February and March, 22.8% between March and April, 18.6% between April and May, (0.92-0.83) / 0.83 = 10.8% between May and June, and (1.15-0.92) / 0.92 = 25.0% between June and July-December. All of these differences are greater than 10%, and the sequence is strictly increasing.

[0094] The optimized threshold sequence was used to determine the unknown sample. The measured R = 1.05. Comparing the measured value with the above threshold sequence: 0.92 (6-month threshold) < 1.05 ≤ 1.15 (7-12-month threshold), therefore the storage time of the sample was determined to fall within the "7-12 months" period.

[0095] This embodiment demonstrates that by using a step-by-step merging rule, consecutive months with insufficient distinguishability (July and later) can be gradually merged into a longer storage period, ultimately resulting in a threshold sequence in which the relative difference between all adjacent periods is not less than 10% and increases strictly. This avoids misjudgment caused by excessively small threshold differences while retaining the fine distinguishing ability of the early period (0-6 months).

[0096] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and embodiments shown and described herein.

Claims

1. A method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma, characterized in that, It includes the following steps: Step 1, headspace sample preparation: Obtain the powder of the cereal sample to be tested, weigh a quantitative sample powder and place it in a headspace vial. After sealing, heat it to equilibrium to obtain the headspace gas of the sample to be analyzed; Step 2, gas chromatography-ion mobility spectrometry analysis: Inject the headspace gas of the sample into a gas chromatography-ion mobility spectrometry hyphenated instrument, and under the set analysis conditions, obtain the ion mobility spectrum of the sample; Step 3, identification of characteristic substances and calculation of signal ratio: Identify the characteristic response signal peaks of propionaldehyde and hexanal in the ion mobility spectrum, calculate the peak volume A1 of the characteristic response signal peak of propionaldehyde and the peak volume A2 of the characteristic response signal peak of hexanal respectively, and calculate the ratio R of A1 and A2, R = A1 / A2; Step 4, determination of storage time:预先采用与待测样品相同品种的谷物,在常规储藏条件下储藏,按月取样并按照步骤一至步骤三测定每个样品的比值R,基于各月份的比值R的数据集建立储存时间与比值R的阈值上限之间的单调递增对应关系,该阈值上限采用统计学上分位数确定; Previously, use cereals of the same variety as the sample to be tested, store them under conventional storage conditions, take samples monthly and measure the ratio R of each sample according to Steps 1 to 3. Based on the dataset of the ratio R for each month, establish a monotonically increasing correspondence between the storage time and the upper threshold of the ratio R, and the upper threshold is determined by the statistical quantile; 2. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 1, characterized in that, Compare the measured ratio R of the sample to be tested with the above upper threshold, and determine the corresponding storage time according to the threshold interval in which the measured ratio R falls; When the upper thresholds of adjacent months do not satisfy strict increase, merge the corresponding months into one storage period for determination. In Step 1, the method of heating to equilibrium is specifically: According to the moisture content w of the cereal sample to be tested, set the total heating equilibrium time t, where w is in mass percentage, and: When w ≤ 12%, t = 15 minutes; When w ≥ 14%, t = 35 minutes; When 12% < w < 14%, calculate according to the linear interpolation formula t = 15 + 10×(w - 12), round the calculation result to an integer, and the unit of t is minutes; Then divide the total heating equilibrium time t into two stages: The first stage is maintained at 50°C to 55°C for (t - 10) minutes; 3. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 2, characterized in that, The first stage involves holding the sample at 50℃ to 55℃ for (t-10) minutes. The specific temperature for the first stage is determined based on the starch-lipid complex dissociation temperature T of the grain variety being tested. P Preset; dissociation temperature T P The dissociation peak temperature of starch-lipid complex in the same variety of grain as the test sample was determined by differential scanning calorimetry. If T P If the temperature is ≤ 50℃, then the first stage temperature is 50℃; If 50℃ <T P If the temperature is less than 55℃, then the temperature of the first stage is T. P ; If T P If the temperature is ≥55℃, then the first stage temperature is 55℃.

4. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 3, characterized in that, When the starch-lipid complex dissociation temperature T of the grain variety to be tested P At ≥55℃, the following pretreatment is used in step one to obtain the powdered grain sample: The second stage is maintained at 70°C to 75°C for 10 minutes. Place the cereal sample to be tested under the condition of -20°C to -10°C and freeze it for 30 minutes to 60 minutes. After taking it out, use a cryogenic grinder to crush it under liquid nitrogen cooling, and sieve it to obtain a sample powder with a particle size less than 150 microns. The sample temperature during crushing is lower than 0°C; When the starch-lipid complex dissociation temperature T of the grain variety to be tested P At temperatures below 55°C, the grain sample to be tested is pulverized at room temperature to obtain sample powder with a particle size of 300 to 500 micrometers.

5. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 1, characterized in that, Then weigh the obtained sample powder according to the subsequent operations in Step 1, place it in a headspace vial, seal it and heat it to equilibrium; 6. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 1, characterized in that, In Step 2, the set analysis conditions are: The carrier gas for the gas chromatography part is nitrogen, the carrier gas flow rate is 1 ml to 5 ml per minute, and the column temperature is 40°C to 80°C; For the ion mobility spectrometry part, the migration tube voltage is 2000 V to 5000 V, and the migration tube temperature is 60°C to 100°C. In Step 4, sampling monthly includes: Starting from the 0th month at the beginning of storage, take samples monthly thereafter. At least 5 parallel samples are measured for each month to obtain the dataset of the ratio R for each storage month M, M = 0, 1, 2, …, N, and N is the maximum storage month covered by the model; The quantile is the 85% - 95% quantile. Construct a strictly increasing threshold sequence and the corresponding storage periods according to the following steps: Calculate the upper quantile of M for each month as the initial threshold, denoted as T0, T1, T2, …, T N ; If the initial threshold sequence is T0, T1, T2, …, T N It already satisfies strict increasing condition, that is, for every i = 0,1,…,N-1, there exists T. i < T {i+1} Let K = N+1, and for j = 1, 2, …, N+1, take U j = T {j-1} Storage period S j This corresponds to a single month j-1; where, if j-1 = 0, then the storage period S j Indicated as "0 months", otherwise the storage period S j Represented as a number for that month; If the initial threshold sequence is T0, T1, T2, …, T N It does not satisfy strict increasing, that is, there exists i such that T i ≥ T {i+1} Then, adjacent months with a non-strictly increasing relationship are merged into a continuous storage period, and the upper quantile of all ratios R within the merged period is recalculated. This upper quantile is used as the upper threshold of the merged period. The above merging and recalculation process is repeated until a strictly increasing threshold sequence U1, U2, …, U is obtained. K Where K ≤ N+1; U1, U2, …, U K These correspond to the merged consecutive storage periods S1, S2, …, S, respectively. K Each storage period is represented in the form of start month-end month. If a storage period contains only a single month, it is directly represented by the number of that month. Here, K is the total number of storage periods that are finally divided. The specific rules for determining storage time are as follows: If the measured ratio R ≤ U1, then the storage time of the grain to be tested is determined to fall into storage period S1; If there exists an integer i satisfying 2 ≤ i ≤ K, and U {i-1} < R ≤ U i If the storage time of the grain to be tested falls within storage period S, then it is determined that the storage time falls within storage period S. i ; If the measured ratio R > U K If the storage time of the grain being tested is greater than N months, then it is determined that the grain has been stored for more than N months.

7. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 6, characterized in that, Initial threshold sequence T0, T1, T2, …, T N When strictly increasing, calculate the relative difference d between adjacent thresholds. i =(T {i+1} - T i ) / T i If there exists one of i such that d i If the ratio is less than 10%, then the i-th month and the (i+1)-th month are merged into a continuous storage period, and the upper quantile is recalculated using all the original ratio R data within the merged period. This upper quantile is then used as the threshold for the merged period. After each merge, if the newly obtained threshold sequence does not satisfy strict increasing, the merging and recalculation method used when the initial threshold sequence did not satisfy strict increasing is adopted to continue merging until the new threshold sequence restores strict increasing. Then recalculate the relative differences between all adjacent thresholds in the current threshold sequence, and repeat the above merging and recalculation process until the relative differences between all adjacent thresholds are not less than 10% and the current threshold sequence satisfies strict increasing, resulting in a set of strictly increasing threshold sequences U1, U2, …, U K and their corresponding continuous storage periods S1, S2, …, S K The storage time of the sample to be tested is determined according to the storage time determination rules.

8. The method for determining storage time based on the ratio of propionaldehyde to hexanal grain aroma as described in claim 7, characterized in that, After merging two adjacent months, the resulting storage period is represented by a hyphen between the start month and end month numbers. If the storage period contains three or more consecutive months, it is still represented by the start month-end month format. If one of the storage periods ultimately contains only a single month, the number of that month is used directly.