Biodegradable mulching film service life prediction model based on climatic factor correction

Abstract

The invention relates to the field of mulching film detection, and provides a biodegradable mulching film service life prediction model based on climatic factor correction, and an establishment method of the model of the prediction method comprises the following steps: recording yt as a physicochemical property index in a field use experiment process at different time; according to the construction method, a predicted value of yt is decomposed into a standard curve value only changing along with time and a deviation between an actual observation result and a standard curve, the two parts are predicted through a statistical model to obtain the predicted value, and parameter correction of an environmental factor part is added. By analyzing the relationship between the aging behaviors of the mulching film in a natural environment and a special environment and combining a statistical theory, an environmental aging evaluation index system of the mulching film is established, so that a'life-environmental factor 'prediction model of the mulching film is constructed, and the relationship between environmental factors and the service life of the mulching film is clarified. A new thought is provided for reducing white pollution of soil and developing, popularizing and applying the biodegradable film with timeliness.

Description

Technical Field

[0001] The invention relates to the field of biodegradable ground film detection, and in particular to a biodegradable ground film service life prediction model based on climate factor correction. Background Art

[0002] Ground film is one of the important materials for agricultural production. Ground film covering can increase temperature, retain moisture, reduce soil salinity, prevent diseases and insects, and inhibit weeds. Its wide application has led to a significant increase in my country's agricultural productivity and a change in production methods. Polyethylene is widely used as ground film products due to its excellent performance.

[0003] At present, the ground film developed with biodegradable materials can be decomposed into carbon dioxide, methane and water by microorganisms existing in nature, and has become a research hotspot. However, this type of ground film is sensitive to environmental factors such as temperature, humidity, ultraviolet rays, wind, etc. These factors may cause the ground film to age and crack prematurely, thus affecting its use effect and lifespan.

[0004] Different natural environments have uncertainties in the aging, degradation and failure of mulch films. Understanding the aging and failure mechanism of biodegradable mulch films and predicting their service life in natural environments are of great significance for promoting the use of biodegradable mulch films and promoting sustainable agricultural development.

[0005] At present, the established method for predicting the service life of biodegradable mulch can explain the relationship between the physical and chemical properties of the mulch during the indoor UV aging process and the field use process. However, when establishing the model, the failure and aging mechanism of the biodegradable mulch is ignored, that is, the impact of environmental diversity on the failure and aging of the mulch. As a result, this life prediction method has the disadvantage that the results of laboratory artificial accelerated aging studies cannot be accurately connected with the results of outdoor natural aging studies.

[0006] The inventor disclosed a method for predicting the life of biodegradable mulch in the prior application CN115711845A. Through indoor high-temperature ultraviolet accelerated aging tests, regression equations were established corresponding to different physical and chemical indicators, and the observation results of the field use process were used to calculate the hypothetical days of high-temperature ultraviolet accelerated aging use, and the regression equation between the field use process days and the hypothetical days of high-temperature ultraviolet accelerated aging use was obtained. However, this prediction method does not comprehensively consider the impact of environmental factors on the service life of degradable mulch. Summary of the invention

[0007] In view of the shortcoming that an accurate model cannot be established based on laboratory artificial accelerated aging and outdoor natural aging data, the present invention provides a "lifespan-environmental factor" prediction model for biodegradable mulch films based on climate factor correction. On the basis of field use experiments and indoor accelerated aging experiments, parameter correction of the environmental factor part is added. By analyzing the relationship between the aging behavior of mulch films in natural environments and special environments, combined with statistical theory, the relationship between environmental factors and the service life of mulch films is clarified, and a "lifespan-environmental factor" prediction model for mulch films is constructed. This is of great significance for understanding the aging failure mechanism of biodegradable mulch films and predicting their service life in natural environments, as well as for promoting the use of biodegradable mulch films and promoting sustainable agricultural development.

[0008] Due to my country's vast territory and complex and diverse climatic environment, we combined the use environment of the ground film in the process of establishing the prediction model, and selected conventional climate parameters such as temperature, humidity, ultraviolet rays, wind force, etc., which may cause the ground film to age and crack prematurely and affect its use effect and lifespan as correction parameters. We also analyzed the impact of the environment on the service life from a statistical perspective and revealed the failure and aging mechanism of the ground film. This will help to clarify the interaction between the aging behavior of the ground film and environmental factors, build a service life prediction model, and make the prediction of the ground film life more accurate.

[0009] This invention uses field use experiment (CED) and indoor accelerated experiment (UAD), combined with analytical technology and statistical theory, to explore the environmental aging behavior of ground film. The relationship between the aging behavior of ground film in natural environment and special environment is analyzed, and combined with statistical theory, an environmental aging evaluation index system of ground film is established, and then a "life-environmental factor" prediction model of ground film is constructed, which clarifies the relationship between environmental factors and the service life of ground film, and provides new ideas for reducing soil "white pollution" and the development, promotion and application of time-effective biodegradable films.

[0010] The present invention provides a prediction model for the service life of biodegradable mulch films based on climate factor correction. On the basis of establishing the correlation between the physical and chemical properties of the mulch films in the field use experiment and the indoor accelerated experiment, the above relationship is corrected in combination with environmental factors such as light intensity, ultraviolet index, and solar radiation to construct a prediction model for the "service life-environmental factors" of the mulch films.

[0011] The method for establishing the prediction model is as follows: t The construction method is to use the physical and chemical property indicators of the field experiment process at different times. t The predicted value of is decomposed into the standard curve value (y 室外标准 ) and the deviation between the actual observations and the standard curve The two parts are predicted by the statistical model, namely:

[0012]

[0013] The specific steps include:

[0014] S1. Construction of the standard curve of physical and chemical property indexes during the field use experiment, assuming that t1 is the experimental days corresponding to the indoor accelerated experiment (unit: day), t2 is the experimental days corresponding to the field use experiment (unit: day), and based on the relationship between the two, the field use standard curve is obtained from the indoor standard curve, including the following steps:

[0015] 1). Physical and chemical properties based on indoor accelerated test indicators t The observed data changing with time t1, we get Functional relationship with t1:

[0016]

[0017] 2). Substitute the corresponding physical and chemical property indexes at each time period t2 into formula (2), calculate the time t1 used indoors to reach the same value, and establish the functional relationship between t1 and t2:

[0018]

[0019] 3). Substitute equation (3) into equation (2) to obtain the standard curve fitting result for field use:

[0020] y 室外标准 =c(t2) (4)

[0021] S2. Deviation e t Construction of multivariate nonlinear regression model influenced by environmental factors

[0022] 1). Take the main meteorological indicators as light, ultraviolet index, solar radiation, temperature, and humidity (cumulative), which are recorded as X1-X5 respectively;

[0023] The difference between (1) and (4) is the deviation e t The inventor believes that it is mainly affected by the changes in meteorological indicators, so he selected meteorological indicators for principal component analysis and combined them with the observed values ​​of meteorological indicators to construct e t Functional relationship with principal component analysis;

[0024] 2). Since X1-X5 has strong multicollinearity, we first perform principal component analysis on them. According to the principle of contribution rate>80%, we select the first principal component Z1:

[0025] Z1=h(x1,x2,x3,x4,x5) (5)

[0026] 3). Substitute the observed values ​​of each meteorological index in the field experiment into formula (5) to obtain the relevant characteristic value of Z1 to construct the deviation e t Functional relationship with Z1:

[0027]

[0028] S3. Prediction of physical and chemical properties and membrane material life during field use experiments

[0029] Substituting the experimental days t2 and the corresponding main meteorological indicators into equations (4) and (6), the predicted values ​​of the physical and chemical properties of the field use experiment can be obtained from equation (1):

[0030] The materials of the degradable mulch film targeted by the present invention include PBAT and auxiliary materials, wherein the auxiliary materials are one or more of PLC, PUB, PLA, PHB, PBT, PHA, and PPCP, and the thickness of the mulch film is 3-30 μm.

[0031] Preferably, the material of the degradable mulch film further comprises an additive, and the additive is one or more of talcum powder, mica flakes, talcum powder, potassium humate, silicon dioxide, and lignin.

[0032] Preferably, the mass ratio of PBAT, auxiliary materials and additives in the degradable mulch film is (100-70):(20-0.2):(10-0.12).

[0033] Preferably, after the above-mentioned degradable mulch material and additives are made into composite masterbatch, the composite masterbatch is used to prepare the degradable mulch; the preparation method of the composite masterbatch is: drying the degradable mulch material at 30-100°C for 5-15h, then adding it to a high-speed mixer and mixing it for 5-30min, and finally adding it to a twin-screw extruder for melt granulation, the feed rate is 50-200g / min, the screw speed is 70-300rpm, and the temperature settings of the seven temperature zones of the extruder are: 100-200℃ / 100-200℃ / 100-200℃ / 100-200℃ / 100-200℃ / 100-200℃ / 100-200℃ to obtain the composite masterbatch.

[0034] Preferably, the preparation method of the degradable mulch film is: drying the composite masterbatch at 50-110°C for 5.5-13h, adding the composite masterbatch into a single-screw film blowing machine for extrusion film blowing, the screw speed is 20-100rpm, and the temperatures of the five temperature zones of the film blowing machine are set to 110-210°C / 110-210°C / 110-210°C / 110-210°C / 110-210°C to obtain a biodegradable mulch film with a film thickness of 3-30μm.

[0035] As a preferred method, the annual UV intensity of the field experiment (CED) is 3-50W / m 2 , the temperature is -25℃-40℃, and the annual average precipitation is 300-900mm. The experimental period is 3-15 months. Starting from the day of film covering, samples are collected every 15-20 days from the field head. After that, the edge of the film is compacted to prevent scratching. The collected samples are washed with distilled water, dried naturally, and then the performance is characterized.

[0036] Preferably, the indoor accelerated test (UAD) is carried out by an indoor high temperature ultraviolet accelerated aging test method, the light source is a UV-A lamp (wavelength 320-420nm), and the ultraviolet light intensity is 0.2-3W / m 2 The mulch film samples were first exposed to ultraviolet light (20-150℃) in an aging box for 1-12h, and then condensed in the dark (20-70℃) for 1-12h. The light and dark cycles were repeated 1-20 times with a cycle of 2-22h. The sampling period was 2 days. After the samples were collected, they were naturally dried and then the performance was characterized.

[0037] Preferably, the physical and chemical properties include one or more of longitudinal tensile strength, longitudinal elongation at break, light transmittance, haze, transverse elongation at break, transverse tensile strength, and water vapor permeability.

[0038] The prediction effect is evaluated by combining indicators such as mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE).

[0039] After evaluation, this prediction model meets the actual application needs. The above algorithm can be used as a standard prediction model construction method to predict the outdoor physical and chemical properties during field use experiments based on meteorological indicators and experimental days for different membrane materials, and determine the predicted lifespan based on the prediction results and reference national standards.

[0040] The significance analysis shows that by analyzing the interaction between the aging behavior of mulch film and environmental factors, environmental factor parameters are introduced into the model for correction. The functional equation of the life prediction model obtained has a good fit with the actual field use experimental data and can be used as a prediction model for the service life of mulch film in the field.

[0041] The invention establishes a function equation of a life prediction model of a biodegradable mulch film and a mathematical modeling method thereof; provides theoretical support for the life prediction of the biodegradable mulch film, and has important economic, social and ecological benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1The "life-time-environmental factor" prediction model diagram established with the longitudinal elongation at break as the prediction index in Example 1: A is a curve diagram of the observed and predicted longitudinal elongation at break during the field use experiment (CED), and B is a curve diagram of the linear relationship between the observed days and the predicted days during the CED process;

[0043] Figure 2 The "life-time-environmental factor" prediction model diagram established with longitudinal elongation at break as a prediction index in Example 2: A is a curve diagram of observed and predicted longitudinal elongation at break during a field use experiment (CED), and B is a curve diagram of the linear relationship between observed days and predicted days during the CED process;

[0044] Figure 3 The "life-span-environmental factor" prediction model diagram established with the longitudinal elongation at break as the prediction index in Example 3: A is a curve diagram of the observed and predicted longitudinal elongation at break during the field use experiment (CED), and B is a curve diagram of the linear relationship between the observed days and the predicted days during the CED process. DETAILED DESCRIPTION

[0045] In order to better understand the present invention, the content of the present invention is further explained below in conjunction with examples, but the content of the present invention is not limited to the following embodiments.

[0046] The physical and chemical properties described in the following examples are longitudinal tensile strength, longitudinal elongation at break, and light transmittance; further preferred physical and chemical indicators to be tested are haze, transverse elongation at break, transverse tensile strength, and water vapor transmission rate.

[0047] The method for establishing the prediction model is:

[0048] S1. Construction of standard curves for physical and chemical properties of field use experiments. Let t1 be the number of experimental days (unit: day) corresponding to the indoor accelerated experiment, and t2 be the number of experimental days (unit: day) corresponding to the field use experiment. Based on the relationship between the two, the field use standard curve is obtained from the indoor standard curve, that is:

[0049]

[0050] The specific steps include:

[0051] 1). Physical and chemical properties based on indoor accelerated test indicators 室内标准 The observed data changes with time t1, and we get y 室内标准 Functional relationship with t1:

[0052]

[0053] 2). Substitute the corresponding physical and chemical property indexes at each time period t2 into formula (2), calculate the time t1 used indoors to reach the same value, and establish the functional relationship between t1 and t2:

[0054]

[0055] 3). Substitute equation (3) into equation (2) to obtain the standard curve fitting result for field use:

[0056] y 室外标准 =c(t2) (4)

[0057] S2. Deviation e t Construction of multivariate nonlinear regression model influenced by environmental factors

[0058] 1). Take the main meteorological indicators as light, ultraviolet index, solar radiation, temperature, and humidity (cumulative), which are recorded as X1-X5 respectively;

[0059] The difference between (1) and (4) is the deviation e t The inventor believes that it is mainly affected by the changes in meteorological indicators, so he selected meteorological indicators for principal component analysis and combined them with the observed values ​​of meteorological indicators to construct e t Functional relationship with principal component analysis;

[0060] 2). Since X1-X5 has strong multicollinearity, we first perform principal component analysis on them. According to the principle of contribution rate>80%, we select the first principal component Z1:

[0061] Z1=h(x1,x2,x3,x4,x5) (5)

[0062] 3). Substitute the observed values ​​of each meteorological index in the field experiment into formula (5) to obtain the relevant characteristic value of Z1 to construct the deviation e t Functional relationship with Z1:

[0063]

[0064] S3. Prediction of physical and chemical properties and membrane material life during field use experiments

[0065] 1. Substitute the experimental days t2 and the corresponding main meteorological indicators into equations (4) and (6), respectively. The predicted values ​​of the physical and chemical properties of the field use experiment can be obtained from equation (1):

[0066]

[0067] Example 1

[0068] A biodegradable mulch film, the mass percentage of its raw material composition is:

[0069] PBAT 89%

[0070] PLA 6%

[0071] Talc 5%

[0072] The preparation process of the biodegradable composite masterbatch is as follows: drying the above raw materials at 90°C for 7h, then adding them to a high-speed mixer and mixing them for 20min, and finally adding them to a twin-screw extruder for melt granulation, the feed rate is 180g / min, the screw speed is 260rpm, and the temperature settings of the seven temperature zones of the extruder are: 180°C / 190°C / 190°C / 195°C / 195°C / 185°C / 185°C to obtain a composite masterbatch.

[0073] The preparation process of the biodegradable mulch film is as follows: drying the obtained composite masterbatch at 90°C for 7.5h, then adding the masterbatch into a single-screw film blowing machine for extrusion and film blowing, the screw speed is 40rpm, and the temperatures of the five temperature zones of the film blowing machine are set to: 140°C / 150°C / 155°C / 150°C / 145°C to obtain a biodegradable mulch film with a film thickness of 20μm.

[0074] The indoor accelerated test (UAD) adopts the indoor high temperature ultraviolet accelerated aging test method. The light source is UV-A lamp (wavelength 380nm) and the ultraviolet light intensity is 2.5W·m -2 The mulch film samples were first exposed to a UV box at 100°C for 8 hours in an aging box, and then condensed at 20°C in the dark for 4 hours. The light and dark cycles were repeated 10 times with 12 hours as a cycle. The sampling period was 2 days. After the samples were collected, they were naturally dried and then the performance was characterized.

[0075] The annual UV intensity of the field use experiment (CED) is 3-50W / m 2 , the temperature is -25℃-40℃, and the annual average precipitation is 300-900mm. The experimental period is 10 months. Starting from the day of film covering, samples are collected every 15 days from the field head. After that, the edge of the film is compacted to prevent scratching. The collected samples are washed with distilled water, dried naturally, and then the performance is characterized.

[0076] The process of establishing the longitudinal elongation at break life prediction model is as follows:

[0077] 1) Establish the relationship between the longitudinal elongation at break (y) and the aging days (t1) during the UAD process and obtain the indoor standard curve:

[0078] y 室内标准 =200.8744exp(-0.131t1) (1)

[0079] Goodness of fit R2 =0.997, the fitting effect is good.

[0080] 2) Combine the longitudinal elongation at break value during CED with the indoor standard curve to obtain the estimated number of days of UAD

[0081]

[0082] 3) Based on estimated days Establish the actual number of days t2 for CED and the estimated number of days for UAD The relationship between:

[0083]

[0084] Goodness of fit R 2 =0.986, the fitting effect is good.

[0085] 4) By combining formula (1) and formula (3), we can get the outdoor standard curve:

[0086] y 室外标准 =200.8744exp(-0.0153t2) (4)

[0087] 5) Define the differences between data caused by environmental factors in CED experiments as "residuals" (e):

[0088] e=y 观测 -y 标准 (5)

[0089] 6) The five meteorological indicators were standardized to obtain X1*, X2*, X3*, X4*, and X5* (corresponding to the cumulative amount of light, UV index, solar radiation, temperature, and humidity, respectively), and then principal component analysis was performed.

[0090] 7) From Table 1, we can see that the cumulative contribution rate of the first principal component Z1 is 98.2%, so the first principal component is selected.

[0091] Table 1. Correlation matrix of principal component contribution

[0092]

[0093] 8) From Table 2, we can get the expression of the first principal component Z1:

[0094] Z1=0.7897X1*+0.4976X2*+0.5278X3*+0.3327X4*+0.5149X5* (6)

[0095] Table 2 Principal component eigenvector table

[0096]

[0097]

[0098] 9) Substitute the observed values ​​of the meteorological indicators into formula (6) to obtain the score of Z1, take the observed results of e as the dependent variable, take the scores of the principal components of Z1 as the independent variables, and construct the relationship between e and Z1:

[0099] e=3.569-4.598Z1-4.327Z1 2 -0.339Z1 3 (7)

[0100] Goodness of fit R 2 =0.909. The significance analysis shows that the fitting effect is good.

[0101] 10) Finally, after substituting formula (7) into formula (5) and combining it with formula (4), the life prediction equation is obtained:

[0102] y 预测 =200.8744exp(-0.0153t2)+(3.569-4.598Z1-4.327Z1 2 -0.339Z1 3 ) (8)

[0103] Figure 1 The "life-span-environmental factor" prediction model diagram established with the longitudinal elongation at break as the prediction index in Example 1 is as follows: A is a curve diagram of the observed and predicted longitudinal elongation at break during the field use experiment (CED), and B is a curve diagram of the linear relationship between the observed days and the predicted days during the CED process; it can be seen from the figure that the functional equation of the life prediction model obtained by adding environmental factors and combining the mathematical modeling method has a good fit, which indicates that the model can predict the service life of the mulch in the field, and can provide theoretical support for the life prediction of PBAT-based biodegradable mulch.

[0104] Example 2

[0105] A biodegradable mulch film, the mass percentage of its raw material composition is:

[0106] PBAT 88%

[0107] PPCP 3%

[0108] Potassium Humate 9%

[0109] The preparation process of the biodegradable composite masterbatch is as follows: drying the above raw materials at 70°C for 10 hours, then adding them to a high-speed mixer and mixing them for 15 minutes, and finally adding them to a twin-screw extruder for melt granulation, the feed rate is 120g / min, the screw speed is 160rpm, and the temperature settings of the seven temperature zones of the extruder are: 190°C / 195°C / 195°C / 198°C / 193°C / 190°C / 185°C to obtain a composite masterbatch.

[0110] The preparation process of the biodegradable mulch film is as follows: drying the obtained composite masterbatch at 75°C for 11 hours, and then adding the masterbatch into a single-screw film blowing machine for extrusion and film blowing. The screw speed is 90rpm, and the temperatures of the five temperature zones of the film blowing machine are set to: 150°C / 160°C / 170°C / 150°C / 150°C, to obtain a biodegradable mulch film with a film thickness of 22μm.

[0111] The indoor accelerated test (UAD) adopts the indoor high temperature ultraviolet accelerated aging test method. The light source is UV-A lamp (wavelength 360nm) and the ultraviolet light intensity is 1.9W / m 2 The mulch film samples were first exposed to ultraviolet light at 70°C in an aging box for 12 hours, and then condensed at 35°C in the dark for 4 hours. The light and dark cycles were repeated 20 times with 16 hours as a cycle. The sampling period was 2 days. After the samples were collected, they were naturally dried and then the performance was characterized.

[0112] The annual UV intensity of the field use experiment (CED) is 3-50W / m 2 , the temperature is -25℃-40℃, and the annual average precipitation is 300-900mm. The experimental period is 10 months. Starting from the day of film covering, samples are collected every 15 days from the field head. After that, the edge of the film is compacted to prevent scratching. The collected samples are washed with distilled water, dried naturally, and then the performance is characterized.

[0113] The process of establishing the longitudinal elongation at break life prediction model is as follows:

[0114] 1) Establish the relationship between the longitudinal elongation at break (y) and the aging days (t1) during the UAD process and obtain the indoor standard curve:

[0115] y 室内标准 =226.4795exp(-2.368t1)+12.6 (1)

[0116] Goodness of fit R 2 =0.989, the fitting effect is good.

[0117] 2) Combine the longitudinal elongation at break value during CED with the indoor standard curve to obtain the estimated number of days of UAD

[0118]

[0119] 3) Based on estimated days Establish the actual number of days t2 for CED and the estimated number of days for UAD The relationship between:

[0120]

[0121] Goodness of fit R 2 =0.976, the fitting effect is good.

[0122] 4) By combining formula (1) and formula (3), we can get the outdoor standard curve:

[0123] y 室外标准 =226.4795exp(-0.1729t2)+12.6 (4)

[0124] 5) Define the differences between data caused by environmental factors in CED experiments as "residuals" (e):

[0125] e=y 观测 -y 标准 (5)

[0126] 6) The five weather indicators were standardized to obtain X1*, X2*, X3*, X4*, and X5* (corresponding to the cumulative amount of light, UV index, solar radiation, temperature, and humidity, respectively), and then principal component analysis was performed.

[0127] 7) From Table 3, we can see that the cumulative contribution rate of the first principal component Z1 is 96.7%, so the first principal component is selected.

[0128] Table 3. Correlation matrix of principal component contribution

[0129]

[0130] 8) From Table 4, the expression of the first principal component Z1 is obtained:

[0131] Z1=0.6629X1*+0.3217X2*+0.4825X3*+0.6452X4*+0.3368X5* (6)

[0132] Table 4 Principal component eigenvector table

[0133]

[0134]

[0135] 9) Substitute the observed values ​​of the meteorological indicators into formula (6) to obtain the score of Z1, take the observed results of e as the dependent variable, take the scores of the principal components of Z1 as the independent variables, and construct the relationship between e and Z1:

[0136] e=32.649-7.341Z1-3.486Z1 2 +0.22Z1 3 (7)

[0137] Goodness of fit R 2 =0.939. The significance analysis shows that the fitting effect is good.

[0138] 10) Finally, after substituting formula (7) into formula (5), combined with formula (4), the life prediction equation is obtained:

[0139] y 预测 =226.4795exp(-0.1729t2)+12.6+(32.649-7.341Z1-3.486Z1 2 +0.22Z1 3 ) (8)

[0140] Figure 2 The "life-span-environmental factor" prediction model diagram established with the longitudinal elongation at break as the prediction index in Example 2: A is a curve diagram of the observed and predicted longitudinal elongation at break during the field use experiment (CED), and B is a curve diagram of the linear relationship between the observed days and the predicted days during the CED process; it can be seen from the figure that the functional equation of the life prediction model obtained by adding environmental factors and combining the mathematical modeling method has a good fit, which indicates that the model can predict the service life of the mulch in the field, and can provide theoretical support for the life prediction of PBAT-based biodegradable mulch.

[0141] Example 3

[0142] A biodegradable mulch film, the mass percentage of its raw material composition is:

[0143] PBAT 85%

[0144] PPCP 16%

[0145] Talc 9%

[0146] The preparation process of the biodegradable composite masterbatch is as follows: drying the above raw materials at 100°C for 6 hours, then adding them to a high-speed mixer and mixing them for 30 minutes, and finally adding them to a twin-screw extruder for melt granulation, the feed rate is 110g / min, the screw speed is 230rpm, and the temperatures of the seven temperature zones of the extruder are set to: 170°C / 185°C / 185°C / 195°C / 190°C / 185°C / 180°C to obtain a composite masterbatch.

[0147] The preparation process of the biodegradable mulch film is as follows: drying the obtained composite masterbatch at 70°C for 12.5h, then adding the masterbatch into a single screw film blowing machine for extrusion and film blowing, the screw speed is 55rpm, and the temperatures of the five temperature zones of the film blowing machine are set to: 170°C / 180°C / 185°C / 180°C / 175°C, and the biodegradable mulch film is obtained, and the thickness of the mulch film is 25μm.

[0148] The indoor accelerated test (UAD) adopts the indoor high temperature ultraviolet accelerated aging test method. The light source is UV-A lamp (wavelength 400nm) and the ultraviolet light intensity is 1.9W / m 2 The mulch film samples were first exposed to ultraviolet light at 60°C in an aging box for 6 hours, and then condensed at 35°C in the dark for 6 hours. The light and dark cycles were repeated 20 times with 12 hours as a cycle. The sampling period was 2 days. After the samples were collected, they were naturally dried and then the performance was characterized.

[0149] The annual UV intensity of the field use experiment (CED) is 3-50W / m 2 , the temperature is -25℃-40℃, and the annual average precipitation is 300-900mm. The experimental period is 10 months. Starting from the day of film covering, samples are collected every 20 days from the field head. After that, the edge of the film is compacted to prevent scratching. The collected samples are washed with distilled water, dried naturally, and then the performance is characterized.

[0150] The process of establishing the longitudinal elongation at break life prediction model is as follows:

[0151] 1) Establish the relationship between the longitudinal elongation at break (y) and the aging days (t1) during the UAD process and obtain the indoor standard curve:

[0152] y 室内标准 =199.5719exp(-1.629t1)(1)

[0153] Goodness of fit R 2 =0.999, the fitting effect is good.

[0154] 2) Combine the longitudinal elongation at break value during CED with the indoor standard curve to obtain the estimated number of days of UAD

[0155]

[0156] 3) Based on estimated days Establish the actual number of days t2 for CED and the estimated number of days for UAD The relationship between:

[0157]

[0158] Goodness of fit R 2 =0.965, the fitting effect is good.

[0159] 4) By combining formula (1) and formula (3), we can get the outdoor standard curve:

[0160] y 室外标准 =199.5719exp(-1.285t2)(4)

[0161] 5) Define the differences between data caused by environmental factors in CED experiments as "residuals" (e):

[0162] e=y 观测 -y 标准 (5)

[0163] 6) The five weather indicators were standardized to obtain X1*, X2*, X3*, X4*, and X5* (corresponding to the cumulative amount of light, UV index, solar radiation, temperature, and humidity, respectively), and then principal component analysis was performed.

[0164] 7) From the table, we can see that the cumulative contribution rate of the first principal component Z1 is 95.5%, so the first principal component is selected.

[0165] Table 5. Correlation matrix of principal component contribution

[0166]

[0167] 8) From Table 6, the expression of the first principal component Z1 is obtained:

[0168] Z1=0.6371X1*+0.3596X2*+0.4632X3*+0.3643X4*+0.8562X5*(6)

[0169] Table 6 Principal component eigenvector table

[0170]

[0171]

[0172] 9) Substitute the observed values ​​of the meteorological indicators into formula (6) to obtain the score of Z1, take the observed results of e as the dependent variable, take the scores of the principal components of Z1 as the independent variables, and construct the relationship between e and Z1:

[0173] e=27.3192-5.861Z1-8.914Z1 2 +1.21Z1 3 (7)

[0174] Goodness of fit R 2 =0.967. The significance analysis shows that the fitting effect is good.

[0175] 10) Finally, after substituting formula (7) into formula (5), combined with formula (4), the life prediction equation is obtained:

[0176] y 预测 =199.5719exp(-1.285t2)+(27.3192-5.861Z1-8.914Z1 2 +1.21Z1 3 ) (8)

[0177] Figure 3 The "life-span-environmental factor" prediction model diagram established with the longitudinal elongation at break as the prediction index in Example 3: A is a curve diagram of the observed and predicted longitudinal elongation at break during the field use experiment (CED), and B is a curve diagram of the linear relationship between the observed days and the predicted days during the CED process; it can be seen from the figure that the functional equation of the life prediction model obtained by adding environmental factors and combining the mathematical modeling method has a good fit, which indicates that the model can predict the service life of the mulch film in the field, and can provide theoretical support for the life prediction of PBAT-based biodegradable mulch films.

[0178] The above embodiment is one of the specific implementation modes selected by the present invention. The common changes and substitutions made by those skilled in the art within the scope of this technical solution should be included in the protection scope of the present invention.

Claims

1. A prediction model for the service life of biodegradable mulch film based on climate factor correction, characterized in that: The model building method of the prediction method is as follows: t The construction method is to use the physical and chemical property indicators of the field experiment process at different times. t The predicted value of is decomposed into two parts: the standard curve value that only changes with time and the deviation between the actual observation result and the standard curve. The predicted value is obtained by predicting the two parts separately through the statistical model, namely: The specific steps include: S1. Construction of the standard curve of physical and chemical property indexes during the field use experiment, assuming that t1 is the experimental day corresponding to the indoor accelerated experiment, and t2 is the experimental day corresponding to the field use experiment, and based on the relationship between the two, the field use standard curve is obtained from the indoor standard curve, including the following steps: 1). Physical and chemical properties based on indoor accelerated test indicators t The observed data changing with time t1, we get Functional relationship with t1: 2). Substitute the corresponding physical and chemical property indexes at each time period t2 into formula (2), calculate the time t1 used indoors to reach the same value, and establish the functional relationship between t1 and t2: 3). Substitute equation (3) into equation (2) to obtain the standard curve fitting result for field use: and 室外标准 =c(t2) (4) S2. Deviation e t Construction of multivariate nonlinear regression model influenced by environmental factors 1). Take the main meteorological indicators as light, ultraviolet index, solar radiation, temperature, and humidity, which are recorded as X1-X5 respectively; 2). Perform principal component analysis on X1-X5, and select the first principal component Z1 based on the principle that the contribution rate is >80%: Z1=h(x1,x2,x3,x4,x5) (5) 3). Substitute the observed values ​​of each meteorological index in the field experiment into formula (5) to obtain the relevant characteristic value of Z1 to construct the deviation e t Functional relationship with Z1: S3. Prediction of physical and chemical properties and membrane material life during field use experiments Substituting the experimental days t2 and the corresponding main meteorological indicators into equations (4) and (6), the predicted values ​​of the physical and chemical properties of the field use experiment can be obtained from equation (1):

2. The prediction method according to claim 1, characterized in that: The materials of the degradable mulch film include PBAT and auxiliary materials, wherein the auxiliary materials are one or more of PLC, PUB, PLA, PHB, PBT, PHA, and PPCP, and the thickness of the mulch film is 3-30 μm.

3. The prediction method according to claim 2, characterized in that: The material of the degradable ground film also includes additives, and the additives are one or more of talcum powder, mica flakes, talcum powder, potassium humate, silicon dioxide, and lignin.

4. The prediction method according to claim 3, characterized in that: The mass ratio of PBAT, auxiliary materials and additives in the degradable mulch film is (100-70):(20-0.2):(10-0.12).

5. The prediction method according to any one of claims 2 to 4, characterized in that: After the above-mentioned degradable mulch material and additives are made into composite masterbatches, the composite masterbatches are used to prepare degradable mulch; the preparation method of the composite masterbatch is as follows: the material of the degradable mulch is dried at 30-100°C for 5-15h, then added to a high-speed mixer and mixed for 5-30min, and finally added to a twin-screw extruder for melt granulation, the feed rate is 50-200g / min, the screw speed is 70-300rpm, and the temperature settings of the seven temperature zones of the extruder are: 100-200°C / 100-200°C / 100-200°C / 100-200°C / 100-200°C / 100-200°C / 100-200°C to obtain the composite masterbatch.

6. The prediction method according to claim 5, characterized in that: The preparation method of the degradable mulch film is as follows: drying the composite masterbatch at 50-110°C for 5.5-13h, adding the composite masterbatch into a single-screw film blowing machine for extrusion and film blowing, the screw speed is 20-100rpm, and the temperatures of the five temperature zones of the film blowing machine are set to 110-210°C / 110-210°C / 110-210°C / 110-210°C / 110-210°C to obtain a biodegradable mulch film with a thickness of 3-30μm.

7. The prediction method according to claim 1, characterized in that: The annual UV intensity in the field experiment is 3-50W / m 2 The temperature is -25℃-40℃, and the average annual precipitation is 300-900mm; the experimental period is 3-15 months. Starting from the day of film covering, samples are collected every 15-20 days from the edge of the field. The edge of the film is then covered with soil and compacted to prevent it from being scratched. The collected samples are washed with distilled water, dried naturally, and then the performance is characterized.

8. The prediction method according to claim 1, characterized in that: The indoor accelerated test is carried out by an indoor high temperature ultraviolet accelerated aging test method, the light source is a UV-A lamp with a wavelength of 320-420nm; the ultraviolet light intensity is 0.2-3W / m 2 The mulch film samples were first exposed to ultraviolet rays at 20-150℃ in an aging box for 1-12h, and then condensed in the dark at 20-70℃ for 1-12h. The light and dark cycles were repeated 1-20 times with a cycle of 2-22h. The sampling period was 2 days. After the samples were collected, they were naturally dried and then the performance was characterized.

9. The prediction method according to claim 1, characterized in that: The physical and chemical properties include one or more of longitudinal tensile strength, longitudinal elongation at break, light transmittance, haze, transverse elongation at break, transverse tensile strength, and water vapor transmission rate.

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