A prediction model for the service life of biodegradable mulch based on climate factor correction

Abstract

The present invention relates to the field of plastic film detection, and provides a prediction model for the service life of biodegradable plastic films based on climate factor correction. The model establishment method of the prediction method is as follows: Denote y t as the physical and chemical property indexes during the field use experiment at different times. This construction method decomposes the predicted value of y t into two parts: a standard curve value that only changes with time and the deviation between the actual observation result and the standard curve. The predicted values obtained by separately predicting the two parts through a statistical model are added with parameter correction of the environmental factor part. By analyzing the relationship between the aging behaviors of plastic films in natural environments and special environments, and combining statistical theories, an environmental aging evaluation index system for plastic films is established, and then a "life-environment factor" prediction model for plastic films is constructed to clarify the relationship between environmental factors and the service life of plastic films, providing new ideas for reducing soil "white pollution" and the development, promotion, and application of time-effective biodegradable films.

Description

Technical Field

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

[0002] Mulch film is one of the important material resources for agricultural production. Mulch film covering can play roles such as increasing temperature, preserving soil moisture, reducing soil salinity, preventing diseases and pests, and suppressing weeds. Its wide application has led to a significant improvement in China's agricultural productivity and a change in the production mode. Polyethylene is widely used as a mulch film product due to its excellent properties.

[0003] Currently, mulch films developed from biodegradable materials, which can be decomposed into carbon dioxide, methane, and water by microorganisms existing in nature, have become a current research hotspot. However, the sensitivity of such mulch films to environmental factors, such as temperature, humidity, ultraviolet rays, wind force, etc., these factors may cause the mulch film to age and crack prematurely, thereby affecting its use effect and service life.

[0004] The aging degradation and failure of mulch films in different natural environments are uncertain. Understanding the aging failure mechanism of biodegradable mulch films and predicting their service life in natural environments is of great significance for promoting the use of biodegradable mulch films and promoting the sustainable development of agriculture.

[0005] Currently, the established prediction methods for the service life of biodegradable mulch films, although they can clarify the relationship between the physical and chemical properties of mulch films during indoor ultraviolet aging and field use processes, when establishing the model, they ignore the combination of the failure aging mechanism of biodegradable mulch films, that is, the impact of environmental diversity on the failure aging of mulch films. Therefore, this life prediction method has the disadvantage that the research results of laboratory artificial accelerated aging cannot be accurately connected with the research results of outdoor natural aging.

[0006] The inventor disclosed a method for predicting the life of biodegradable mulch films in the prior application CN115711845A. Through indoor high-temperature ultraviolet accelerated aging tests, regression equations were established corresponding to different physical and chemical indexes, and the imaginary high-temperature ultraviolet accelerated aging service days were calculated using the observation results during field use, and a regression equation between the field use days and the imaginary high-temperature ultraviolet accelerated aging service days was obtained. However, in this prediction method, the influence of environmental factors on the service life of degradable mulch films was not comprehensively considered. 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 standard curves of physical and chemical properties during field experiment, assuming t 1 is the experimental days corresponding to the indoor accelerated test (unit: day), t 2 is the number of experimental days corresponding to the field use experiment (unit: day). 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 Over time t 1 The observed data of the change is obtained With t 1 Functional relationship:

[0016]

[0017] 2). Set each time period t 2 Substitute the corresponding physical and chemical property index into formula (2) to calculate the time t taken to reach the same value in the room 1 , establish t 1 With t 2 Functional relationship:

[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(t 2 ) (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), respectively denoted as X 1 -X 5 ;

[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). Due to X 1 -X 5It has strong multicollinearity. First, we perform principal component analysis on it. According to the principle of contribution rate>80%, we select the first principal component Z 1 :

[0025] Z 1 =h(x 1 ,x 2 ,x 3 ,x 4 ,x 5 ) (5)

[0026] 3). Substitute the observed values ​​of each meteorological index in the field experiment into formula (5) to obtain Z 1 The relevant eigenvalues ​​of constructing the deviation e t With Z 1 Functional relationship:

[0027]

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

[0029] The number of experimental days t 2 and the corresponding main meteorological indicators and are substituted into equations (4) and (6) respectively. From equation (1), the predicted values ​​of the physical and chemical properties of the field use experiment can be obtained:

[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 making the above-mentioned degradable plastic film material and additive into a composite masterbatch, the degradable plastic film is prepared by using the composite masterbatch; the preparation method of the composite masterbatch is as follows: drying the material of the degradable plastic film at 30-100 °C for 5-15 h, then adding it to a high-speed mixer and mixing for 5-30 min, and finally adding it to a twin-screw extruder for melt granulation, with a feeding rate of 50-200 g / min, a screw rotation speed of 70-300 rpm, and the temperatures of the seven temperature zones of the extruder set as: 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.

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

[0035] Preferably, the annual ultraviolet light intensity in the field use experiment (CED) is 3-50 W / m 2 , the air temperature is -25 °C - 40 °C, and the annual average precipitation is 300-900 mm. The experimental period is 3-15 months. Starting from the day of film mulching, samples are taken every 15-20 days from the field head, and then the edges of the plastic film are covered with soil and compacted to prevent it from being blown up. The collected samples are washed with distilled water, air-dried naturally, and then the performance is characterized.

[0036] Preferably, the indoor accelerated test (UAD) is carried out by the indoor high-temperature ultraviolet accelerated aging test method. The light source is selected as a UV-A lamp (wavelength 320-420 nm), and the ultraviolet light intensity is 0.2-3 W / m 2 , the plastic film sample is first exposed to ultraviolet light (20-150 °C) for 1-12 h in an aging chamber, and then condensed in the dark (20-70 °C) for 1-12 h. Taking 2-22 h as a cycle, the light and dark cycles are repeated 1-20 times. The sampling period is 2 days. After collecting the samples, they are air-dried naturally and then the performance is 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 transmission rate.

[0038] The prediction effect is evaluated by combining indexes 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 1 The "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 of physical and chemical property indicators during field use experiment, assuming t 1 is the experimental days corresponding to the indoor accelerated test (unit: day), t 2 is the number of experimental days corresponding to the field use experiment (unit: day). 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 Over time t 1 The observed data of the change is obtained 室内标准 With t 1 Functional relationship:

[0052]

[0053] 2). Set each time period t 2 Substitute the corresponding physical and chemical property index into formula (2) to calculate the time t taken indoors to reach the same value 1 , establish t 1 With t 2 Functional relationship:

[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(t 2 ) (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), respectively denoted as X 1 -X 5 ;

[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). Due to X 1-X 5 It has strong multicollinearity. First, we perform principal component analysis on it. According to the principle of contribution rate>80%, we select the first principal component Z 1 :

[0061] Z 1 =h(x 1 ,x 2 ,x 3 ,x 4 ,x 5 ) (5)

[0062] 3). Substitute the observed values ​​of each meteorological index in the field experiment into formula (5) to obtain Z 1 The relevant eigenvalues ​​of constructing the deviation e t With Z 1 Functional relationship:

[0063]

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

[0065] 1. Set the experimental day t 2 and the corresponding main meteorological indicators are substituted into equations (4) and (6) respectively, and 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 longitudinal elongation at break (y) and aging days (t 1 ) to obtain the indoor standard curve:

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

[0079] Goodness of fit R 2 =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 Actual number of days to establish CED 2 and UAD estimated days 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(-0.0153t 2 ) (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) Standardize the five meteorological indicators to obtain X 1 *、X 2 *、X 3 *、X 4 *、X 5 *(corresponding to the cumulative amount of light, UV index, solar radiation, temperature and humidity respectively), followed by principal component analysis.

[0090] 7) From Table 1, we can see that the first principal component Z 1 The cumulative contribution rate of 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 first principal component Z 1 The expression is:

[0094] Z 1 =0.7897X 1 *+0.4976X 2 *+0.5278X 3 *+0.3327X 4 *+0.5149X 5 * (6)

[0095] Table 2 Principal component eigenvector table

[0096]

[0097]

[0098] 9) Substitute the observed values ​​of the meteorological indicators into equation (6) to obtain Z 1 The score of e is used as the dependent variable, and Z is used as the 1 The scores of the principal components of are independent variables, constructing e and Z 1 The relationship is:

[0099] e=3.569-4.598Z 1 -4.327Z 1 2 -0.339Z 1 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(-0.0153t 2 )+(3.569-4.598Z 1 -4.327Z 1 2 -0.339Z 1 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 longitudinal elongation at break (y) and aging days (t 1 ) to obtain the indoor standard curve:

[0115] y 室内标准 =226.4795exp(-2.368t 1 )+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 Actual number of days to establish CED 2 and UAD estimated days 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(-0.1729t 2 )+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) Standardize the five weather indicators to obtain X 1 *、X 2 *、X 3 *、X 4 *、X 5 *(corresponding to the cumulative amount of light, UV index, solar radiation, temperature and humidity respectively), followed by principal component analysis.

[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, we can get the first principal component Z 1 The expression is:

[0131] Z 1 =0.6629X 1 *+0.3217X 2*+0.4825X 3 *+0.6452X 4 *+0.3368X 5 * (6)

[0132] Table 4 Principal component eigenvector table

[0133]

[0134]

[0135] 9) Substitute the observed values ​​of the meteorological indicators into equation (6) to obtain Z 1 The score of e is used as the dependent variable, and Z is used as the 1 The scores of the principal components of are independent variables, constructing e and Z 1 The relationship is:

[0136] e=32.649-7.341Z 1 -3.486Z 1 2 +0.22Z 1 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(-0.1729t 2 )+12.6+(32.649-7.341Z 1 -3.486Z 1 2 +0.22Z 1 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 longitudinal elongation at break (y) and aging days (t 1 ) to obtain the indoor standard curve:

[0152] y 室内标准 =199.5719exp(-1.629t 1 )(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 Actual number of days to establish CED 2 and UAD estimated days 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(-1.285t 2 )(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) Standardize the five weather indicators to obtain X 1 *、X 2 *、X 3 *、X 4 *、X 5 *(corresponding to the cumulative amount of light, UV index, solar radiation, temperature and humidity respectively), followed by principal component analysis.

[0164] 7) From the table we can see that the first principal component Z 1 The cumulative contribution rate of 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, we get the first principal component Z 1 The expression is:

[0168] Z 1 =0.6371X 1 *+0.3596X 2 *+0.4632X 3 *+0.3643X 4 *+0.8562X 5 *(6)

[0169] Table 6 Principal component eigenvector table

[0170]

[0171]

[0172] 9) Substitute the observed values ​​of the meteorological indicators into equation (6) to obtain Z 1 The score of e is used as the dependent variable, and Z is used as the 1 The scores of the principal components of are independent variables, constructing e and Z 1 The relationship is:

[0173] e=27.3192-5.861Z 1 -8.914Z 1 2 +1.21Z 1 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(-1.285t 2 )+(27.3192-5.861Z 1 -8.914Z 1 2 +1.21Z 1 3 ) (8)

[0177] Figure 3The "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 method for predicting the service life of biodegradable mulch 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: and t =and 室外标准+ and t (1) 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 property indicators based on indoor accelerated tests 室内标准 The observed data changes with time t1, and we get y 室内标准 Functional relationship with t1: yes 室内标准 =f(t1) (2) 2). Substitute the corresponding physical and chemical property indexes at each time period t2 into formula (2), calculate the time t1 taken indoors to reach the same value, and establish the functional relationship between t1 and t2: t1=g(t2) (3) 3). Substitute (3) into (2) to obtain the field standard curve fitting result: 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 meteorological indicators as light, ultraviolet index, solar radiation, temperature, and humidity, and record them as X1-X5 respectively; 2). Perform principal component analysis on X1-X5, and select the first principal component Z1 based on the principle of contribution rate > 80%: Z1= h （ x 1， x 2， x 3， x 4， x 5） （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: have been t =m(Z1) (6) S3. Prediction of physical and chemical properties and membrane material life during field use experiments Substituting the experimental days t2 and the corresponding meteorological indexes into equations (4) and (6), the predicted value y of the physical and chemical property index of the field use experiment can be obtained from equation (1): t .

2. The prediction method according to claim 1, characterized in that: The materials of the biodegradable 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 biodegradable mulch 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 biodegradable 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 biodegradable 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 5-15 hours, then added to a high-speed mixer and mixed for 5-30 minutes, and finally added to a twin-screw extruder for melt granulation, the feed rate is 50-200 g / min, the screw speed is 70-300 rpm, 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 biodegradable mulch film is as follows: drying the composite masterbatch at 50-110°C for 5.5-13 h, 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 was 3-50 W / m 2 The temperature is -25℃-40℃, and the average annual precipitation is 300-900 mm. 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 320-420 nm; 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 1-12 h, and then condensed in the dark at 20-70 ℃ for 1-12 h. The light and dark cycles were repeated 1-20 times with a cycle of 2-22 h. 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.

Images