Safety assessment of agricultural products and the pesticide regulation trend in China

Abstract

The sustainable development of Chinese agriculture needs to coordinate the quality and quantity of agricultural products. To verify whether government regulation can promote agricultural development by controlling pesticides, the indices of government regulation, quantity and quality of agricultural products, and pesticide use per area of cropland were calculated, and a comprehensive evaluation index and the coupling degree and coordination degree of agricultural products were analyzed by coupling function. The results showed that the coupling and coordination degree of the quality and quantity of agricultural products and the comprehensive index are improving. The regulation of pesticide use per area of cropland is a key mechanism in promoting the coordinated development of agricultural product safety. The regulation trend of agricultural development in China is to reduce pesticide usage appropriately and expand the production-possibility frontier of agricultural products.

Graphical abstract

Introduction

The Chinese government regards agricultural product safety as a basic guarantee for people’s livelihood. China’s crop sown area has remained over 120 million hectares, and the annual grain output has remained above 650 million tons in recent years, which has effectively provided food for 1.4 billion Chinese people. As evidenced by the report of The State of Food Security and Nutrition in the World (FAO 2020), the most recent estimate for 2019 shows that prior to the COVID-19 pandemic, almost 690 million people around the world went hungry. Therefore, the high and stable output of agricultural products in China has contributed to the improvement of world food security. However, China is facing difficulties and challenges such as insufficient agricultural labor supply, increased agricultural nonpoint source pollution, and potential quality and safety risks of agricultural products. In recent years, China’s food safety incidents have shown that the current management model needs to be further improved (Shao et al. 2021a, b; Song et al. 2020). Strengthening government regulation is the common international consensus to ensure the safety of agricultural products (Teng et al. 2021; Khan et al. 2015). However, China’s agricultural product safety problems have not disappeared even with strengthened government regulation (Zhong and Kong 2012; Shao et al. 2021a, b). Chinese pesticide regulatory requirements are shown in Table 1.

Table 1 Pesticide regulatory requirements in China’s No.1 Central Document

The current safety risks of China’s agricultural products are still widespread. For example, pesticide residue problems in vegetables, fruits and other kinds of agricultural products are still conspicuous (Pang 2019). Pesticide standard input is conducive to improving both agricultural production and labor-saving innovation (Kong et al. 2018; Soares and Porto 2009). Studies show that a 1% global increase in agricultural production is associated with a 1.8% increase in pesticide usage (Schreinemachers and Tipraqsa 2012). However, the increased use of pesticides has increased pest resistance to pesticides, and pesticide resistance in turn leads to increased use of pesticides, forming a vicious cycle (Li and Liang 2021; Hawkins et al. 2019). In addition, pollution of the ecological environment and dozens of human diseases are directly related to pesticide residues (Qu et al. 2011; Syed et al. 2014).

Chemical pesticide use has been cited as one of the plausible causes for the drastically declining trends observed in insect biomass (Hallmann et al. 2017). Although it is known that excessive use of pesticides may lead to the destruction of biodiversity and impose a serious negative impact on the environment (Mahmood et al. 2016), China’s agricultural product shortage still heavily depends on pesticide technology at the current level of agricultural productivity (Huang et al. 2021). A study shows that the average intensity of pesticide use in China is 2.5–5 times higher than that in developed countries, and more than 67 million hectares of crops in China are contaminated with pesticide residues every year (Wang and Gu 2013). According to FAO statistics, in 2019, the total amount of pesticides used in agricultural production in China exceeded 1.77 million tons, 4.35 times that of the USA and 4.7 times that of Brazil, making China rank first in the world. According to the Ministry of Agriculture of China, the utilization rate of pesticides in China was 36.6% in 2015, 38.8% in 2017 and 40.6% in 2020, meaning that China still lags behind developed countries such as European countries and the USA.

Existing research results have shown that policy support for and implementation of pesticide use-reduction strategies such as integrated pest management has been inadequate across regions (Van den Berg et al. 2020). The regulations on the maximum residue limit (MRL) of pesticides are closely associated with public health (Carrère et al. 2018), and these regulations and pest risk management measures have an impact on the trade of agricultural products (Federica et al. 2021; Drogue and DeMaria 2012). There is broad international consensus on the need to implement strategies to reduce dependence on chemical pesticides. In recent years, China has implemented strict regulatory policies on pesticides, and pesticide usage has gradually decreased. The main regulatory policies are shown in Table 2. The key question is whether government pesticide management can contribute to the sustainable development of agricultural systems, and there is a need to bring balance to pesticide use in agriculture for the quantity and quality of agricultural products. Finding an appropriate agri-environmental policy design represents a typical optimization problem (Nadoveza and Šimurina 2020). This paper attempts to take pesticide use and regulation in China as an example and provide a balanced view and describe the trends of pesticide regulation from the perspective of economics, with the purpose of providing a reliable reference for policy research on reducing the use of chemical pesticides in China and providing theoretical exploration and pioneering methods.

Table 2 Main pesticide regulatory policies in China

Data and methodology

Indices selection and source

Quantity evaluation index of agricultural products

Grains, vegetables and fruits are the three basic kinds of food that Chinese people eat and the three kinds of agricultural products with the highest output in China. In addition, average dietary energy supply adequacy and the grain import dependence ratio are the two important indicators reflecting the safety of agricultural products. For example, in 2021, China’s grain imports accounted for 24.1% of its total domestic production. Therefore, the quantity evaluation index in this paper includes the following five secondary indices: (1) vegetable output per area of cropland, (2) fruit output per area of cropland, (3) grain output per area of cropland, (4) average dietary energy supply adequacy (percent) (3-year average) and (5) grain import dependence ratio. ${y}_{1}$ represents the quantity evaluation index.

Quality evaluation index of agricultural products

According to the Agricultural Product Quality and Safety Law of the People’s Republic of China, the quality and safety of agricultural products means that agricultural products meet the requirements of protecting people's health and safety. In particular, it refers to the technical standards and requirements that the quality and safety level and sanitary conditions of agricultural products meet the requirements to guarantee human health and safety. Therefore, the quality evaluation index in this paper includes the following five secondary indices: (1) the qualified rate of vegetables, (2) the qualified rate of fruits, (3) the qualified rate of pesticides, (4) the ratio of patients with food-borne disease and (5) the consumer complaint ratio of food quality and safety. ${y}_{2}$ represents the quality evaluation index.

Government regulation evaluation index of agricultural product safety

The evaluation index includes the following three secondary indices: (1) investment ratio of biological pesticides and chemical pesticides (affected by national pesticide policy and national economic policy), (2) expenditure on the quality and safety of agricultural products (affected by national agricultural policy and law of China on quality and safety of agricultural products) and (3) per capita crop sown area (affected by national population policy and national land policy). x represents the government regulation evaluation index.

Mediator variable

A mediator variable is intermediate in the causal sequence relating an independent variable to a dependent variable, such that the independent variable affects the mediator variable that causes the dependent variable (Mackinnon 2015). The standard application of pesticides can guarantee the quantity and quality of agricultural products, but the nonstandard application of pesticides will affect the quality and safety of agricultural products. In 2015, the Ministry of Agriculture of the People's Republic of China issued the Zero-Growth Action Plan for Pesticide Use by 2020, taking pesticides as an important means to control the quality and safety of agricultural products. Therefore, this paper takes pesticide use per area of cropland as the mediator variable between government regulation and agricultural product safety.

Main sources of data

The main data involved in this paper are from authoritative statistical institutions, which can avoid the problem of rigor in quantitative research. The main sources of data are listed in Table 3.

Table 3 The main sources of data (2005–2019)

Coupling function

The term coupling comes from physics and can be defined as a phenomenon in which the dimensions under investigation influence each other through different links (Li et al. 2012). Coupling theory has gradually been used to measure the high-quality development index system (Jian and Nie 2020), financial development, technological innovation and economic growth (Wang and Tan 2021), and the coupling between subsystems requires mediator variables (Yang and Yang 2022). Is there a coupling effect between the quantity and quality of agricultural products? Can government pesticide regulation be used as a mediator variable? To answer the above questions, this paper refers to the research design of Miyazaki and Kinoshita (2006) and Van Heumen et al. (2009) to set up the internal coupling function of agricultural product safety.

$$y_{3} = \left[ {\frac{{\mathop \prod \nolimits_{i = 1}^{k} E_{i} }}{{\left( {\mathop \sum \nolimits_{i = 1}^{k} E_{i} /k} \right)^{k} }}} \right]^{\frac{1}{k}}$$

(1)

In Eq. (1), ${y}_{3}$ represents the coupling degree of agricultural products (0 ≤ ${y}_{3}$  ≤ 1). ${y}_{3}$ is determined jointly by the agricultural product quantity and quality evaluation index. A larger ${y}_{3}$ indicates a higher coupling degree among the agricultural subsystems. i represents the agricultural product safety subsystem. This function contains two subsystems, the quantity and quality of agricultural products (k = 2). ${E}_{i}$ represents the evaluation index of the agricultural product safety subsystem.

$$E_{i} = \mathop \sum \limits_{{j = 1_{ij} }}^{n} w_{ij} \begin{array}{*{20}c} {\left( {i = 1,2;\;j = 1,2, \ldots ,n} \right)} \\ \end{array}$$

(2)

In Eq. (2), $\lambda_{ij}$ represents a positive indicator of the jth variable in the ith subsystem.$\lambda _{ij} = \left( {x_{ij} - \min \,x_{ij} } \right)/\left( {\max \,x_{ij} - \min \,x_{ij} } \right)$. $w_{ij}$ represent the weight of the jth variable in the ith subsystem.

However, the coupling degree does not indicate whether the dimensions are developing in harmony but only the strength of the subsystem interaction, leading to an erroneous conclusion when relying solely on values calculated from Eq. (2) (Tomal 2021). Therefore, a coupling coordination degree is used to assess the degree of synergy between the subsystems, and the coupling coordination degree function is set as follows:

$$y_{4} = \left[ {y_{3} \times \left( {\alpha E_{1} + E_{2} } \right)} \right]^{\frac{1}{2}}$$

(3)

In Eq. (3), ${y}_{4}$ represents the coupling coordination degree of agricultural products (0 ≤ ${y}_{4}$  ≤ 1). A higher ${y}_{4}$ indicates a more harmonious relationship between the quantity and quality of agricultural products. ${y}_{5}=\alpha {E}_{1}+\beta {E}_{2}$; ${y}_{5}$ represents the comprehensive index of agricultural products, and $\alpha$ and $\beta$ are undetermined coefficients, $\alpha =1-\beta$. $\alpha$ and $\beta$ will be determined using Granger’s causal test.

Transmission mechanism functions

The manner in which exogenous variables affect the variables of interest is referred to as the transmission mechanism (Koop et al. 2009). In this paper, we divide the transmission mechanism into direct and indirect forms according to the influence of government regulatory policies on the safety index of agricultural products.

The basic equation of direct transmission mechanism functions is as follows:

$$y={\alpha }_{0}+{\alpha }_{1}x+\varepsilon$$

(4)

In Eq. (4),$y$ represents the evaluation index of agricultural products, including ${y}_{1}$ to ${y}_{5}$, x represents the government regulation evaluation index, $\varepsilon$ represents the stochastic disturbance team, ${\alpha }_{0}$ is a constant, and ${\alpha }_{1}$ is the regression coefficient.

Generally, the independent variable has an effect on the dependent variable through the mediator, and this process is called the mediating effect (Baron and Kenny 1986). Mediation theory can help us analyze the various shapes these relations can take, the points of application between a technology and its user, and the specific types of mediation at play (Verbeek 2015). According to the mediation theory of the coupling function (Zhao et al. 2020), the basic equation of indirect transmission mechanism functions is as follows:

$$p={\beta }_{0}+{\beta }_{1}x+\varepsilon$$

(5)

$$y={\gamma }_{0}+{\gamma }_{1}x+{\gamma }_{2}p+\varepsilon$$

(6)

In Eqs. (5) and (6), p represents pesticide use per area of cropland, and x represents the government regulation evaluation index. ${\beta }_{0}$ and ${\gamma }_{0}$ are constants, ${\beta }_{1}$ and ${\gamma }_{1}$ are the regression coefficients, and $\varepsilon$ represents the stochastic disturbance team.

Production-possibility frontier of agricultural products

In economics, a production possibilities frontier (PPF) or “transformation curve” is a graph that shows the different quantities of two goods that an economy could efficiently produce with limited productive resources. The curve illustrates that increasing the production of one good reduces the maximum production of the other good as resources are transferred away from the other good. Referring to similar research designs (Devadoss and Song 2003; Wu et al. 2021), the basic equation of the PPF of agricultural product functions is as follows:

$$N=\frac{R}{{C}_{1}}-\frac{{C}_{2}}{{C}_{1}}Q$$

(7)

In Eq. (7), N represents a quantitative index of the quantity of agricultural products, Q represents a quantitative index of the quality of agricultural products, R represents maximizing agricultural means of production at the level of existing agricultural natural resources and production technology, ${C}_{1}$ represents the cost of increasing the quantity of agricultural product per unit, and ${C}_{2}$ represents the cost of increasing the quality of agricultural product per unit. The marginal rate of transformation (MRT) is the number of units or amount of a good that must be forgone to create or attain one unit of another good. It is the number of units of N that will be foregone to produce an extra unit of Q while keeping the factors of production and technology constant. Therefore, the PPF of agricultural products is concave toward the origin.

Pesticide residue function of agricultural products

After a period of application, the pesticide will degrade to a safe level naturally due to its own characteristics and external environment. Referring to the characteristics of the elimination half-life of drugs (Greenblatt 1985) and the atomic nuclei decay modes (Poenaru et al. 1985), the basic equation of the pesticide residue function of agricultural products is created as follows:

$$Q={Q}_{0}{\left(\frac{1}{z}\right)}^\frac{t}{T}\frac{\uplambda }{\uptheta }$$

(8)

In Eq. (8), Q represents the pesticide residue, ${Q}_{0}$ represents pesticide use per area of cropland, T represents the pesticide safety interval, t represents the actual pesticide interval, z represents the dilution ratio of pesticide use per area of cropland to the pesticide maximum residual limit (MRL), λ represents the degradation coefficient of pesticides in the agricultural production environment, and θ represents the uniformity coefficient of pesticide spraying (θ ≤ 1).

Results

Descriptive analysis of the evaluation index of agricultural products

Quantity evaluation index of agricultural products

The quantity evaluation index of agricultural products from 2005 to 2019 is shown in Fig. 1. The vegetable, fruit and grain output per area of cropland in China has maintained a steady growing trend. The average dietary energy supply adequacy and grain import dependence ratio have increased slightly. As shown in Fig. 1, the quantity of agricultural products in China is relatively steady and safe.

Fig. 1

Quantity evaluation index of agricultural products

Quality evaluation index of agricultural products

The quality evaluation index of agricultural products from 2005 to 2019 is shown in Fig. 2. The qualified rate of vegetables and fruits is maintained at a high level (average above 0.96), the overall qualified rate of pesticides is maintained above 0.85, and the ratio of patients with food-borne disease has grown continuously in the past decade. As shown in Fig. 2, although the quality of agricultural products in China possesses relatively slight fluctuating asymmetries, changes are needed for further improvement of quality and safety.

Fig. 2

Quality evaluation index of agricultural products

Descriptive statistics of the main indices

The descriptive statistics of the main indices are shown in Table 4. The following indices obviously fluctuated: the indices of fruit and grain output per area of cropland, grain import dependence ratio, ratio of patients with food-borne disease, consumer complaint ratio of food quality and safety, investment ratio of biological pesticides and chemical pesticides, and expenditure on the quality and safety of agricultural products. The above indices could be influenced by the external environment or internal factors in the past 15 years. These variable indices could also become a key element of government regulation. Other indices, such as the qualified rate of vegetables, qualified rate of fruits and per capita crop sown area, remain relatively unchanged.

Table 4 Descriptive statistical results of evaluation index

Coupling and coordination degree of agricultural product safety

Evaluation index of agricultural product safety

First, the range of the evaluation index is standardized, and positive indices are used in this paper. The values range from 0 to 1. Second, the statistical product and service solutions (SPSS) software entropy method is used to calculate the weight coefficient of each index, and the results are shown in Table 5. Finally, Eq. (2) is used to calculate the evaluation index of the quantity and quality subsystem, and the results are shown in Fig. 3.

Table 5 Evaluation index of agricultural products safety

Fig. 3

Evaluation index, coupling and coordination degree of agricultural products

Calculation of coupling and coordination degree of subsystem

The coupling degree of the quantity and quality of agricultural products can be calculated by substituting the subsystem evaluation index into Eq. (1), and the results are shown in Fig. 3. The undetermined coefficients of quantitative and quality evaluation indices should be determined when calculating the degree of coordination. In this paper, the Granger causality test is used to determine the value of the undetermined coefficient, and the results are shown in Table 6. The optimum lag in the internal disturbance is a phase lag. Therefore, the undetermined coefficients of both subsystems can be approximately set to 0.5. According to the undetermined coefficient and subsystem evaluation index, the comprehensive index of agricultural products ${y}_{3}$ can be calculated, and the results are shown in Fig. 3.

Table 6 Internal disturbances in the quantity and quality of agricultural products

By substituting the undetermined coefficients and coupling degrees of the two subsystems into Eq. (3), the coordination degree can be calculated, and the results are shown in Fig. 3. According to the coupling degree (CD) and calculated values (Wang and Tang 2018), the coupling types are divided into a run-in period (0.5 ≤ CD < 0.8) and a coordinated coupling period (0.8 ≤ CD < 1.0). According to the coupling coordination degree (CCD) and calculated values (Wang and Tang 2018), the coordination types can be divided into four categories, including moderate disorder (0.2 ≤ CCD < 0.4), basic coordination (0.4 ≤ CCD < 0.5), moderate coordination (0.5 ≤ CCD < 0.8) and high coordination (0.8 ≤ CCD < 1.0). Figure 3 shows that 2005–2006 is the run-in period and 2007–2019 is the coordinated coupling period. The coupling degree can reflect that the quantity and quality of agricultural products in China are in a highly coupled state and in a developing tendency. The coordination degree showed that the quantity and quality of agricultural products in China were moderately disordered in 2005, basically coordinated from 2006 to 2007, moderately coordinated from 2008 to 2013 and 2015, and highly coordinated in 2014 and 2016–2019. The indices show that the coordination degree of the quantity and quality of agricultural products is increasing gradually and reflects the healthy development trend of China’s agricultural products market. However, according to various indices in 2019, the comprehensive index, coupling degree and coordination degree of China’s agricultural products all declined. The results show that China’s agricultural products market needs constantly strengthened government regulation, and agricultural product safety also has room to improve.

Transmission mechanisms of government regulation

First, the direct transmission mechanism is tested according to Eq. (4), and the results are shown in Table 7. Except for the quality evaluation index, the other indices have a significant relationship with the government regulation evaluation index.

Table 7 Test results of the direct transmission mechanism

Second, according to the mediation theory of the coupling function, the effects of pesticide use per area of cropland on the comprehensive index, coupling degree and coordination degree of agricultural products are discussed. According to Eq. (5), the significance of the government regulation index on mediating variables is tested, and the results are shown in Table 8. After the addition of the mediator variable, the coupling degree, coordination degree and composite index have no significant relationship with the government regulation index. Therefore, the Chinese government can regulate agricultural products by controlling pesticide use per area of cropland. This implies that pesticide use per area of cropland can be used as a mediator variable to achieve effective government regulation of agricultural products.

Table 8 Test results of the indirect transmission mechanism

Production-possibility frontier of agricultural products

According to Eq. (7), the production-possibility frontier of agricultural products is shown in Fig. 4. There are two ways to improve the quality of agricultural products. One transition is from A to B to C, and the whole transition is moving along the same production possibilities frontier. The quality of agricultural products is improved at the expense of quantity reduction. The other transition is from A to D to E, which requires that the agricultural production technology level be improved to expand the production-possibility frontier while the existing agricultural resources remain unchanged. This transition not only guarantees the stability of the quantity of agricultural products but also improves the quality of agricultural products. Comparing the two ways of agricultural product quality improvement has obvious advantages in expanding the production-possibility frontier of agricultural products.

Fig. 4

Production-possibility frontier of agricultural products

The comparison of pesticide application intensity between China and the USA is shown in Fig. 5. Although the intensity of pesticide application is affected by the regional agricultural environment and other factors, there is huge potential for pesticide reduction in China. Therefore, China urgently needs to strengthen the regulation of pesticide application and implement a policy of pesticide reduction.

Fig. 5

A comparison of pesticide application intensity between China and the USA

Trends in pesticide regulation based on agricultural product safety

The trend chart of pesticide usage and grain output in China is shown in Fig. 6. The use of pesticides in China has decreased significantly since 2015, but grain production has not decreased accordingly. Figure 6 shows that it is a feasible method to expand the production-possibility frontier of agriculture to improve the quality and safety of agricultural products by reducing pesticide use on the premise of ensuring the stability of grain production.

Fig. 6

Trends of pesticide usage and grain output from 2001 to 2019

It is the traditional driving force of agricultural development to realize the high yield and increase of agricultural products by the input of modern factors such as pesticides. However, the natural weakness of agricultural production means that it needs the support and protection of the government. Regulating pesticide usage is an important measure of government agricultural product safety regulation. Therefore, the government should first continue to implement the regulation policy of pesticide reduction and formulate the development plan of green agriculture to both stabilize the quantity and improve the quality of grain. Second, the production, sale and use of pesticides should be strictly regulated, biological pesticides should be encouraged to replace chemical pesticides, and the use of highly toxic and high-residue pesticides should be reduced. Third, governments should allocate financial funds for the research and development of new pesticides and encourage the use of new agricultural techniques to reduce pesticide use and increase grain production.

Discussion, conclusions and policy implications

Discussion

In the face of natural disasters, diseases, food trade and other uncertain factors, ensuring the safety of agricultural products is a common problem faced by many countries. The key to the safety of agricultural products is to improve the quality and safety on the basis of ensuring the quantity of agricultural products. In modern agricultural science and technology, pesticides are widely used in agricultural production. Pesticides are one of the most important factors affecting the safety of agricultural products. Studies have shown that many ecological and environmental problems and human diseases are closely related to pesticide use. Therefore, how to regulate the application of pesticides has become the focus of many countries.

To feed 1.4 billion people, China has vigorously developed the pesticide industry, which has effectively increased the quantity of agricultural products but also highlighted the problem of pesticide residues. Therefore, China has introduced a series of pesticide regulatory policies aimed at reducing the use of pesticides, thereby reducing pesticide residues and ensuring the quality and safety of agricultural products. In the past 30 years, China has experienced a great transformation from extensive pesticide development to pesticide safety management and has achieved remarkable results. China's experience in pesticide regulation can provide a practical reference for other countries.

According to the indices of agricultural product safety evaluation in this paper, the safety degree of agricultural products in China has gradually improved, which also indicates that the current pesticide regulation policy meets the requirements of agricultural development. However, in the face of new problems and challenges, can China continue to improve the safety level of agricultural products? Where is the room for improvement in China's pesticide regulatory policy? All these problems are worthy of further study and discussion.

Conclusions

In this paper, the coupling function is used to calculate the comprehensive evaluation index, coupling degree and coordination degree of agricultural products in China from 2005 to 2019. The influence of government regulation on the agricultural product evaluation index, coupling degree and coordination degree is empirically analyzed, and the trend of government pesticide regulation is proposed based on the production-possibility frontier theory of agricultural product production. This paper has the following conclusions: (1) From 2005 to 2019, the comprehensive index of quantity and quality, coupling degree and coordination degree of China’s agricultural products show a steady trend, but there is still room for improvement. The results show that the policy of pesticide regulation in China is effective. (2) As a mediator variable, pesticide use per area of cropland is a key method for the government to realize the coordinated development of the quantity and quality of agricultural products. Therefore, the formulation of an appropriate pesticide application plan is a significant part of the government to promote sustainable agricultural development. (3) Appropriate reduction of pesticide usage is a feasible method to optimize the quality and quantity structure of agricultural products in China. A critical factor for the government to achieve pesticide reduction is to expand the production-possibility frontier of agricultural products.

Policy implications

Based on the conclusions, the following policy implications can be drawn. First, coordinating the quantity and quality of agricultural products is an important part of China’s sustainable agricultural development and national food security strategy. Agricultural policies must balance the quantity and quality of agricultural products. Second, government pesticide regulation is an effective means to ensure the safety of agricultural products. Pesticide reduction is currently a crucial part of the Chinese government’s agricultural development. Third, the government should encourage technological innovation and the development of new green pesticides and reform the method of government regulation. Expanding the production-possibility frontier of agricultural products through technological innovation is a significant method to promote pesticide reduction and agricultural technical efficiency.