A method for evaluating postharvest immediate storage environment of fruits and vegetables

Abstract

This invention relates to a method for evaluating the immediate post-harvest storage environment of fruits and vegetables, addressing the problem that current methods for evaluating the post-harvest storage and transportation environment of fruits and vegetables can only reflect the fruit quality after a period of storage, failing to determine and assess the trend of the immediate environment's impact on fruit and vegetable quality. This method places sample slices under the same storage environment as fruits and vegetables of the same batch, allowing the three newly synthesized lignin monomers to be developed in four different fluorescence channels. Fluorescence intensity is weighted and statistically analyzed based on different cell regions of the fruit and vegetable slices, and the impact of the current storage environment on changes in fruit and vegetable quality is evaluated based on the statistical structure. This invention uses the newly synthesized lignin monomers of fruits and vegetables under different environments within a certain period to evaluate the impact of the immediate storage environment on fruit and vegetable quality. This method fully considers the comprehensive influence of different cell types, different lignin monomer types, and the ratio of newly synthesized lignin to existing lignin on the decline in fruit and vegetable quality, and uses this as a basis to evaluate the suitability of the current environment for fruits and vegetables, thereby guiding the optimization of the fruit and vegetable storage and transportation environment.

Description

Technical Field

[0001] This invention belongs to the field of fruit and vegetable storage, and relates to a method for evaluating the immediate post-harvest storage environment of fruits and vegetables. Background Technology

[0002] my country is a major producer and consumer of fruits and vegetables globally, with an annual output exceeding 1 billion tons. However, due to factors such as inadequate post-harvest storage conditions and outdated technology, the annual post-harvest loss rate for fruits and vegetables in my country is approximately 20%-30%. Therefore, the continuous improvement of post-harvest cold chain logistics technology for fruits and vegetables is a powerful measure to maintain their freshness, slow down quality decline, enhance market competitiveness, expand the spatial and temporal supply range of fruits and vegetables, and improve product economic benefits.

[0003] Studies have shown that fruits and vegetables undergo vigorous respiration and metabolism and rapid aging after harvest. The large accumulation of lignin is the main reason for the decline in postharvest quality, and it is closely related to the texture, color, postharvest physiology, and diseases of fruits and vegetables. (Zhang Xu, Wang Xiaojia, Li Sichen, et al. Research progress on lignin biosynthesis and regulation during citrus fruit granulation. Zhejiang Journal of Agricultural Sciences [J], 2019.31:2131-2140.) (Xue Weiwen, Zhou Xianfang, Zhang Zhaoqi, et al. Research progress on the effects of postharvest lignin accumulation and its regulation on the quality of fruits and vegetables. Journal of Horticulture [J], 2022.49:2023-2036.) (Chen Tinghui, Zeng Jiaqing, Luo Weihua, et al. Effects of different storage temperatures on postharvest quality and lignification of okra. Preservation and Processing [J], 2023.23:7-14.)

[0004] Lignin in fruits and vegetables is composed of three monomers polymerized on the cell wall. The distribution of different monomers varies in different plants and cells, and the responses of different lignin monomers to different stresses also vary (Cesarino I Structural features and regulation of lignin deposited upon biotic and abiotic stresses. Curr Opin Biotechnol[J],2019.56:209-214.).

[0005] Currently, there are methods for evaluating the impact of post-harvest storage and transportation environment on lignin accumulation in fruits and vegetables. These methods mainly use chemical extraction to measure the average total lignin content in homogenates of fruits and vegetables before and after storage, in order to analyze the average impact of storage and transportation environment on lignin accumulation in fruits over a period of time, thereby establishing a coupling mechanism between environment and changes in fruit and vegetable quality.

[0006] Biochemical measurements and analyses are time-consuming and labor-intensive, lacking information on changes in the content of different lignin monomers and the distribution of lignin in in-situ tissue cells. Furthermore, physiological indicators under a single storage environment are insufficient to reflect the trend of deterioration in fruit and vegetable quality. Fruits and vegetables consist of plant organs with specific external morphology and internal structure, composed of various tissues and cells, performing specific physiological functions, including roots, stems, leaves, flowers, fruits, and seeds. The accumulation of lignin in different tissues and cells has varying effects on the quality of different types of fruits and vegetables. On the other hand, the post-harvest cold chain logistics environment for fruits and vegetables changes rapidly and is highly uniform. For example, the trends in fruit quality change often differ depending on the shelf used during transportation, the area of ​​the cold storage, the storage time, and the stage after harvest.

[0007] Therefore, biochemical analysis methods are insufficient to accurately evaluate the impact of different times and storage environments during the postharvest logistics process of fruits and vegetables on fruit quality, and to establish a mechanism for coupling environment and fruit and vegetable quality.

[0008] Click chemistry is based on the introduction of orthogonal groups through bio-metabolic labeling to specifically label target molecules. It has advantages such as no byproducts, readily available raw materials, and simple reaction conditions (Simon C, Lion C, Spriet C, et al. One, Two, Three: A Bioorthogonal Triple Labelling Strategy for Studying the Dynamics of Plant Cell Wall Formation In Vivo. Angew Chem Int Ed Engl[J], 2018.57:16665-16671.). In the study of lignin metabolites in biological samples, it allows for the investigation of the distribution changes of different monomers of newly synthesized lignin in tissue cells under active conditions (Morel O, Lion C, Neutelings G, et al. REPRISAL: mapping lignification dynamics using chemistry, data segmentation, and ratiometric analysis. Plant Physiol[J], 2022.188:816-830.). Therefore, by using click chemistry technology to visualize the in-situ, real-time lignin synthesis content and distribution of living fruits and vegetables under different postharvest storage conditions, a faster, more accurate, and comprehensive assessment of the current storage environment can be achieved. This can help to more accurately optimize postharvest cold chain logistics preservation technology, improve preservation efficiency, reduce preservation energy consumption, and enhance product economic benefits. Therefore, a timely, rapid, and refined method for assessing environmentally coupled changes in fruit and vegetable quality is needed. Studying the trends in fruit and vegetable quality changes under different storage and transportation conditions can guide the optimization of postharvest cold chain logistics technology, maximizing the postharvest economic benefits of fruits and vegetables. Summary of the Invention

[0009] The purpose of this invention is to address the problem that current methods for evaluating the post-harvest storage and transportation environment of fruits and vegetables can only reflect the quality of the fruit after a period of storage, and cannot determine and assess the trend of the immediate environment's influence on the quality of fruits and vegetables. This invention provides a method for evaluating the immediate post-harvest storage environment of fruits and vegetables, assessing the trend of quality changes in the immediate environment, analyzing the quality change patterns under different conditions at different stages of the post-harvest cold chain logistics process, and evaluating the optimal cold chain logistics environment for different fruits and vegetables at different stages. This has important reference value for optimizing post-harvest cold chain logistics technology for fruits and vegetables.

[0010] The technical solution adopted by this invention to solve its technical problem is: a method for evaluating the immediate post-harvest storage environment of fruits and vegetables, characterized by comprising the following steps:

[0011] Step 1: Randomly sample fruits and vegetables from the same storage environment and the same batch, and select X samples of fruits and vegetables, numbering them sequentially as: 1, 2, 3...X;

[0012] Step 2: Slice and number each sample separately;

[0013] Step 3: Place the obtained sample slices and fruits and vegetables of the same batch in the same storage environment. During the storage process, the fruits and vegetables will synthesize three new lignin monomers on the basis of the existing lignin, which are denoted as H monomer, G monomer and S monomer respectively. Based on click chemistry technology, fluorescent labeling is carried out by incubating and feeding the three lignin monomers. The incubation time is denoted as T.

[0014] Step 4: For each sample slice, obtain the autofluorescence distribution map P of lignin at 404nm. L Fluorescence distribution of the newly synthesized H monomer labeled at 488 nm (P) H Fluorescence distribution of the newly synthesized G monomer labeled at 561 nm (P) G Fluorescence distribution of the newly synthesized S monomer labeled at 647 nm (P) S ;

[0015] Step 5: Set the fluorescence threshold for the fluorescence distribution map to remove background fluorescence; statistically analyze the distribution of existing lignin and each newly generated lignin monomer in the cellular regions of the sample slice, using the autofluorescence distribution map of lignin at 404 nm (P0). L For example, the fluorescence distribution P of all samples was statistically analyzed. L The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is denoted as: The average fluorescence intensity of the thin-walled cell region is denoted as The average fluorescence intensity of the vascular bundle region is denoted as Statistical analysis of fluorescence distribution P for all samples H The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is The average fluorescence intensity in the thin-walled cell region was The average fluorescence intensity in the vascular bundle region is Statistical analysis of fluorescence distribution P for all samples G The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is The average fluorescence intensity in the thin-walled cell region was The average fluorescence intensity in the vascular bundle region is Statistical analysis of fluorescence distribution P for all samples S The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is The average fluorescence intensity in the thin-walled cell region was The average fluorescence intensity in the vascular bundle region is

[0016] Step 6: The influence of lignin in different regions on the quality of fruits and vegetables varies. Weighting coefficients are set for lignin in different regions to establish a weighting formula. Based on the weighting formula, the weighted sum of fluorescence intensity O of existing lignin in different cell regions is calculated; the weighted sum of fluorescence intensity N of newly synthesized lignin in different cell regions is calculated based on the weighting formula.

[0017]

[0018] N = a*N1 + b*N2 + c*N3

[0019]

[0020]

[0021]

[0022] Wherein: a, b, c are the weighting coefficients of the influence of lignin in the outer fruit and vegetable peel cells, parenchyma cells, and vascular bundle cells on fruit and vegetable quality; N1, N2, and N3 represent the weighted fluorescence intensity of newly synthesized lignin in the outer fruit and vegetable peel cells, parenchyma cells, and vascular bundle cells, respectively; d1, e1, f1, d2, e2, f2, d3, e3, and f3 represent the weighting coefficients of the influence of different lignin monomers on fruit and vegetable quality in different cell regions, respectively.

[0023] Step 7: Calculate based on the obtained O, N, and T values

[0024] X represents the hourly rate of deterioration of fruit and vegetable quality under the current storage and transportation conditions. The larger the X value, the faster the deterioration of fruit and vegetable quality, and the less suitable the current storage and transportation environment is, requiring changes to storage and transportation parameters or methods. Y represents the ratio of the current degree of deterioration of fruit and vegetable quality to the original quality of fruit and vegetables. When X values ​​are the same, the larger the Y value, the less suitable the current storage and transportation environment is.

[0025] Preferably, in step 2, the thickness of the slices should not exceed 200 μm, the width should not exceed 2 cm, and the length should not exceed 4 cm; if the radius of the fruit or vegetable exceeds 2 cm, then slicing into pieces is preferred.

[0026] Preferably, in step 3, the required storage environment time T is between 4h and 48h.

[0027] Preferably, in step 6, the weighting coefficients of a, b, and c must satisfy a+b+c=1.

[0028] As a preferred option, in step 6, the weighted coefficients a, b, and c for different types of fruits and vegetables are set according to the following rules: For fruits and vegetables that are eaten after peeling, such as loquat, mango, and lettuce, the coefficient a is reduced and the coefficients b and c are increased; for stem vegetables, such as celery, carrots, and bamboo shoots, the coefficient c is increased and the coefficients a and b are reduced; for fleshy fruits that can be eaten with the peel, such as apples, pears, and peaches, the coefficients a and b are increased and the coefficient c is reduced.

[0029] As a preferred option, for fruits and vegetables that are eaten after peeling, the coefficient of a should not exceed 0.2; for stem vegetables, the coefficient of c should not be less than 0.5; and for fleshy fruits that can be eaten with the peel, the coefficient of a should not be less than 0.3 and the coefficient of b should not be less than 0.5.

[0030] As a preferred option, in step 6, the weighting coefficients of d1, e1, f1, d2, e2, f2, d3, e3, f3 need to satisfy d1+e1+f1=1, d2+e2+f2=1, d3+e3+f3=1.

[0031] As a preferred option, based on the distribution patterns of lignin G and S monomers in the cell wall, the required coefficient values ​​should satisfy the following: among d1, e1, and f1, f1 is the largest; among d2, e2, and f2, e2 is the largest; and among d3, e3, and f3, f3 is the largest. If the tested fruits and vegetables are dicotyledonous plants, their lignin H monomer content is relatively low, having less impact on fruit and vegetable quality, thus allowing for a significant reduction in the d1, d2, and d3 coefficients.

[0032] As preferred values, 1>f1>0.6, 1>e2>0.5, 1>f3>0.5.

[0033] The beneficial effects of this invention are as follows: by evaluating the impact of the current storage environment on the quality change trend of fruits and vegetables by using newly synthesized lignin monomers in fruits and vegetables under different environments within a certain period of time; this method fully considers the comprehensive impact of different cell types, different lignin monomer types, and the ratio of newly synthesized lignin to existing lignin in fruits and vegetables on the decline in quality, and uses this as a basis to evaluate the suitability of the current environment for fruits and vegetables, thereby guiding the optimization of the storage and transportation environment for fruits and vegetables. Attached Figure Description

[0034] The invention will now be further described with reference to the accompanying drawings.

[0035] Figure 1 This is a differential interference contrast micrograph of loquat fruit slices stored at 0°C according to the present invention.

[0036] Figure 2 This is an existing lignin autofluorescence distribution diagram of loquat fruit slices stored at 0℃ in the 404nm band.

[0037] Figure 3This is a fluorescence distribution diagram of the newly synthesized H monomer in the 488nm band of a slice of loquat fruit stored at 0℃ according to the present invention.

[0038] Figure 4 This is a fluorescence distribution diagram of the newly synthesized G monomer, which is developed at 561 nm wavelength, from loquat fruit slices stored at 0°C according to the present invention.

[0039] Figure 5 This is a fluorescence distribution diagram of the newly synthesized S monomer in the 647nm band, showing the color development of loquat fruit slices stored at 0℃ according to the present invention.

[0040] Figure 6 This is a differential interference contrast micrograph of loquat fruit slices after they were stored at 0°C and transferred to a shelf environment at 20°C.

[0041] Figure 7 This is an existing autofluorescence distribution diagram of loquat fruit slices stored at 0°C and transferred to a 20°C shelf environment, as presented in this invention, in the 404nm wavelength band.

[0042] Figure 8 This is a fluorescence distribution diagram of the newly synthesized H monomer in the 488nm band, showing the color of loquat fruit slices that were stored at 0℃ and transferred to a 20℃ shelf environment according to the present invention.

[0043] Figure 9 This is a fluorescence distribution diagram of the newly synthesized G monomer in the 561nm band, showing the color of loquat fruit slices that were stored at 0℃ and transferred to a 20℃ shelf environment according to the present invention.

[0044] Figure 10 This is a fluorescence distribution diagram of the newly synthesized S monomer in the 647nm band, showing the color of loquat fruit slices that were stored at 0°C and transferred to a 20°C shelf environment according to the present invention.

[0045] Figure 11 This is a differential interference contrast micrograph of loquat fruit slices stored at 5°C according to the present invention.

[0046] Figure 12 This is an existing autofluorescence distribution diagram of loquat fruit slices stored at 5°C in the 404nm band.

[0047] Figure 13 This is a fluorescence distribution diagram of the newly synthesized H monomer in the 488nm band, showing the color development of loquat fruit slices stored at 5℃ according to the present invention.

[0048] Figure 14 This is a fluorescence distribution diagram of the newly synthesized G monomer, which is obtained by color development of loquat fruit slices stored at 5°C in the 561nm band.

[0049] Figure 15 This is a fluorescence distribution diagram of the newly synthesized S monomer in the 647nm band, showing the color development of loquat fruit slices stored at 5℃ according to the present invention.

[0050] Figure 16-30 In order Figure 1-15 Color inversion image. Detailed Implementation

[0051] The present invention will be further described below with reference to specific embodiments and accompanying drawings.

[0052] Example 1: A method for evaluating the immediate postharvest storage environment of fruits and vegetables, comprising the following steps:

[0053] Step 1: Randomly sample fruits and vegetables from the same storage environment and the same batch, and select X samples of fruits and vegetables, numbering them sequentially as: 1, 2, 3...X;

[0054] Step 2: Slice and number each sample separately;

[0055] Step 3: Place the obtained sample slices and fruits and vegetables of the same batch in the same storage environment. During the storage process, the fruits and vegetables will synthesize three new lignin monomers on the basis of the existing lignin, which are denoted as H monomer, G monomer and S monomer respectively. Based on click chemistry technology, fluorescent labeling is carried out by incubating and feeding the three lignin monomers. The incubation time is denoted as T.

[0056] Step 4: For each sample slice, obtain the autofluorescence distribution map P of lignin at 404nm. L Fluorescence distribution of the newly synthesized H monomer labeled at 488 nm (P) H Fluorescence distribution of the newly synthesized G monomer labeled at 561 nm (P) G Fluorescence distribution of the newly synthesized S monomer labeled at 647 nm (P) S ;

[0057] Step 5: Set the fluorescence threshold for the fluorescence distribution map to remove background fluorescence; statistically analyze the distribution of existing lignin and each newly generated lignin monomer in the cellular regions of the sample slice, using the autofluorescence distribution map of lignin at 404 nm (P0). L For example, the fluorescence distribution P of all samples was statistically analyzed. L The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is denoted as: The average fluorescence intensity of the thin-walled cell region is denoted as The average fluorescence intensity of the vascular bundle region is denoted as Statistical analysis of fluorescence distribution P for all samples H The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is The average fluorescence intensity in the thin-walled cell region was The average fluorescence intensity in the vascular bundle region is Statistical analysis of fluorescence distribution P for all samples G The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is The average fluorescence intensity in the thin-walled cell region was The average fluorescence intensity in the vascular bundle region is Statistical analysis of fluorescence distribution P for all samples S The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is The average fluorescence intensity in the thin-walled cell region was The average fluorescence intensity in the vascular bundle region is

[0058] Step 6: The influence of lignin in different regions on the quality of fruits and vegetables varies. Weighting coefficients are set for lignin in different regions to establish a weighting formula. Based on the weighting formula, the weighted sum of fluorescence intensity O of existing lignin in different cell regions is calculated; the weighted sum of fluorescence intensity N of newly synthesized lignin in different cell regions is calculated based on the weighting formula.

[0059]

[0060] N = a*N1 + b*N2 + c*N1

[0061]

[0062]

[0063]

[0064] Wherein: a, b, c are the weighting coefficients of the influence of lignin in the outer fruit and vegetable peel cells, parenchyma cells, and vascular bundle cells on fruit and vegetable quality; N1, N2, and N3 represent the weighted fluorescence intensity of newly synthesized lignin in the outer fruit and vegetable peel cells, parenchyma cells, and vascular bundle cells, respectively; d1, e1, f1, d2, e2, f2, d3, e3, and f3 represent the weighting coefficients of the influence of different lignin monomers on fruit and vegetable quality in different cell regions, respectively.

[0065] Step 7: Calculate based on the obtained O, N, and T values

[0066] X represents the hourly rate of deterioration of fruit and vegetable quality under the current storage and transportation conditions. The larger the X value, the faster the deterioration of fruit and vegetable quality, and the less suitable the current storage and transportation environment is, requiring changes to storage and transportation parameters or methods. Y represents the ratio of the current degree of deterioration of fruit and vegetable quality to the original quality of fruit and vegetables. When X values ​​are the same, the larger the Y value, the less suitable the current storage and transportation environment is.

[0067] Example 2: Based on the method of Example 1, taking 'Luoyang Qing' loquat fruit as an example,

[0068] Let a = 0.1, b = 0.6, and c = 0.3; when X < 0.2 and Y < 10%, the storage environment is considered suitable.

[0069] d1=0.1, e1=0.2, f1=0.7;

[0070] d2=0.1, e2=0.5, f2=0.4;

[0071] d3=0.1, e3=0.3, f3=0.6.

[0072] The 'Luoyangqing' loquat fruit samples were incubated for 36 hours under three different conditions: 0℃ storage, 0℃ storage followed by 20℃ shelf storage, and 5℃ storage.

[0073] The fluorescence distribution diagram of 'Luoyang Qing' loquat samples stored at 0℃ is shown below. Figure 1-5 The statistics are as follows:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086] N1 = 2.064676256

[0087] N2 = 112.0552042

[0088] N3 = 10.47868855

[0089] N = 70.58319669

[0090] 0 = 5.28109011

[0091] T=36

[0092] X = 1.960644352

[0093] Y = 37.1257508%.

[0094] The fluorescence distribution diagram of 'Luoyang Qing' loquat samples stored at 0℃ and then transferred to a shelf environment at 20℃ is shown in the figure. Figure 6-10 The statistics are as follows:

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] N1 = 7.126657

[0108] N2 = 467.17511

[0109] N3 = 39.455844

[0110] N = 232.37493

[0111] 0 = 2.426241

[0112] T=36

[0113] X = 8.134846881

[0114] Y = 335.286007%.

[0115] The fluorescence distribution diagram of 'Luoyang Qing' loquat samples stored at 5℃ is shown below. Figure 11-15 The statistics are as follows:

[0116]

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128] N1 = 0.011197787

[0129] N2 = 6.270760807

[0130] N3 = 2.311442895

[0131] N = 4.574061581

[0132] 0 = 0.633539798

[0133] T=36

[0134] X = 0.127057266

[0135] Y = 20.0551357%.

[0136] because Figure 1-15 Against a black background, fluorescence in the image is not readily visible to the naked eye; therefore, for Figure 1-15 Inverting the image in Photoshop serves as a control; the actual calculation and analysis process described above is performed using... Figure 1-15Based on the above statistical data, 'Luoyang Qing' loquat fruit is best stored at 0℃ for short-term storage; 5℃ is the most suitable storage environment for longer storage; when sold in a storage environment of 20℃, the quality of 'Luoyang Qing' loquat fruit deteriorates rapidly and it is not suitable for sale on a 20℃ shelf. It should be sold on a low-temperature shelf.

Claims

1. A method for evaluating the immediate postharvest storage environment of fruits and vegetables, characterized in that: Includes the following steps: Step 1: Randomly sample fruits and vegetables from the same storage environment and the same batch, and select X samples of fruits and vegetables, numbering them sequentially as: 1, 2, 3...X; Step 2: Slice and number each sample separately; Step 3: Place the obtained sample slices and fruits and vegetables of the same batch in the same storage environment. During the storage process, the fruits and vegetables will synthesize three new lignin monomers on the basis of the existing lignin, which are denoted as H monomer, G monomer and S monomer respectively. Based on click chemistry technology, fluorescent labeling is carried out by incubating and feeding the three lignin monomers. The incubation time is denoted as T. Step 4: For each sample slice, obtain the autofluorescence distribution map P of lignin at 404nm. L Fluorescence distribution of the newly synthesized H monomer labeled at 488 nm (P) H The fluorescence distribution of the newly synthesized G monomer labeled at 561 nm (P) G Fluorescence distribution of the newly synthesized S monomer labeled at 647 nm (P) S ; Step 5: Set the fluorescence threshold of the fluorescence distribution map to remove background fluorescence; The distribution of existing lignin and newly generated lignin monomers in cellular regions of sample slices was statistically analyzed separately, and the autofluorescence distribution of lignin at 404 nm was used as the basis for the analysis. L For example, the fluorescence distribution P of all samples was statistically analyzed. L The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is denoted as: The average fluorescence intensity of the thin-walled cell region is denoted as The average fluorescence intensity of the vascular bundle region is denoted as ; Statistical analysis of fluorescence distribution P for all samples H The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is denoted as: The average fluorescence intensity of the thin-walled cell region is denoted as The average fluorescence intensity of the vascular bundle region is denoted as ; Statistical analysis of fluorescence distribution P for all samples G The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is denoted as: The average fluorescence intensity of the thin-walled cell region is denoted as The average fluorescence intensity of the vascular bundle region is denoted as ; Statistical analysis of fluorescence distribution P for all samples S The average fluorescence intensity of the peel area of ​​Chinese and foreign fruits and vegetables is denoted as: The average fluorescence intensity of the thin-walled cell region is denoted as The average fluorescence intensity of the vascular bundle region is denoted as ; Step 6: The degree of influence of lignin in different regions on the quality of fruits and vegetables varies. Weighting coefficients are set for lignin in different regions to establish a weighting formula. Based on the weighting formula, the weighted sum of the fluorescence intensity of existing lignin in different cell regions is calculated. The weighted sum N of the fluorescence intensity of newly synthesized lignin in different cell regions was calculated based on a weighted formula. Wherein: a, b, c are the weighting coefficients of the influence of lignin in the outer fruit and vegetable peel cells, parenchyma cells, and vascular bundle cells on fruit and vegetable quality; N1, N2, and N3 represent the weighted fluorescence intensities of newly synthesized lignin in the outer fruit and vegetable peel cells, parenchyma cells, and vascular bundle cells, respectively; d1, e1, f1, d2, e2, f2, d3, e3, and f3 represent the weighting coefficients of the influence of different lignin monomers on fruit and vegetable quality in different cell regions, respectively. Step 7: Calculate based on the obtained O, N, and T values ; X represents the hourly rate of deterioration of fruit and vegetable quality under the current storage and transportation conditions. The larger the X value, the faster the deterioration of fruit and vegetable quality, and the less suitable the current storage and transportation environment is, requiring changes to storage and transportation parameters or methods. Y represents the ratio of the current degree of deterioration of fruit and vegetable quality to the original quality of fruit and vegetables. When X values ​​are the same, the larger the Y value, the less suitable the current storage and transportation environment is.

2. The method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 1, characterized in that: In step 2, the thickness of the slices should not exceed 200μm, the width should not exceed 2cm, and the length should not exceed 4cm; if the radius of the fruit or vegetable exceeds 2cm, then it should be sliced ​​into pieces.

3. The method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 1, characterized in that: In step 6, the weighting coefficients of a, b, and c must satisfy a+b+c=1.

4. A method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 1 or 3, characterized in that: In step 6, the weighted coefficients a, b, and c for different types of fruits and vegetables are determined according to the following rules: For fruits and vegetables that are eaten after peeling, decrease coefficient a and increase coefficients b and c; for stem vegetables, increase coefficient c and decrease coefficients a and b; for fleshy fruits that can be eaten with the peel, increase coefficients a and b and decrease coefficient c.

5. A method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 4, characterized in that: For fruits and vegetables that are eaten after peeling, the coefficient of a should not exceed 0.2; for stem vegetables, the coefficient of c should not be less than 0.5; for fleshy fruits that can be eaten with the peel, the coefficient of a should not be less than 0.3 and the coefficient of b should not be less than 0.

5.

6. A method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 1, characterized in that: In step 6, the weighting coefficients of d1, e1, f1, d2, e2, f2, d3, e3, f3 need to satisfy d1+e1+f1=1, d2+e2+f2=1, d3+e3+f3=1.

7. A method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 1 or 6, characterized in that: Based on the distribution patterns of lignin G and S monomers in the cell wall, the required coefficient values ​​satisfy the following: among d1, e1, and f1, f1 is the largest; among d2, e2, and f2, e2 is the largest; and among d3, e3, and f3, f3 is the largest.

8. A method for evaluating the immediate postharvest storage environment of fruits and vegetables according to claim 7, characterized in that: 。

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