USING PEST ANALYSIS TO EXPLORE THE

IMPACT AND MECHANISM OF CHINESE

AND AMERICAN BREEDING PATENTS ON

THE DEVELOPMENT OF AGRICULTURAL

SCIENCE AND TECHNOLOGY

Changyun Lu

• Library, China Agricult ural University, Beijing, 100083, China

• Information Research Center of China Agricultural University, Beijing, 100083,

China

Longjiao Zhu

• Coll Food Sci & Nutr Engn, Beijing Adv Innovat Ctr Food Nutr & Human Hlth,

China Agricultural University, Beijing, 100083, China

Wentao Xu

• Coll Food Sci & Nutr Engn, Beijing Adv Innovat Ctr Food Nutr & Human Hlth,

China Agricultural University, Beijing, 100083, China

Yuan Cao*

• Library, China Agricultural University, Beijing, 100083, China

• Information Research Center of China Agricultural University, Beijing, 100083,

China

•E-mail: caoy1004@cau.edu.cn

Reception: 10 January 2024 | Acceptance: 26 January 2024 | Publication: 19 February 2024

Suggested citation:

Lu, C., Zhu, L., Xu, W. and Cao, Y. (2024). Using PEST analysis to explore the

impact and mechanism of Chinese and American breeding patents on

the development of agricultural science and technology. 3C TIC.

Cuadernos de desarrollo aplicados a las TIC, 13(1), 117-137. https://doi.org/

10.17993/3ctic.2024.131.117-137

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ABSTRACT

In recent years, PEST analysis and its application in decision-making has become a

hot topic, and this paper proposes a new model of PEST analysis based on neutral

cognitive map static analysis.The proposed framework consists of five activities,

identifying PEST factors and sub-factors, modeling the interrelationships among

PEST factors, calculating centrality measures, categorizing the factors, and ranking

the factors.The results show that the impact factor of the US breeding patent on the

development of agricultural science and technology has reached the level of

interrelationship, and the uncertainty is included in the analysis. Using this model to

analyze the impact of U.S.-China breeding patents on the development of agricultural

science and technology, we ranked the factors according to their interrelationships

and incorporated uncertainty into the analysis. The results showed that the impact

factor of U.S. breeding patents on the development of agricultural science and

technology reached 0.70, and the index of the Gross Agricultural Product (GAP)

caused by patents was greater than 100. The quantitative analysis of the impact of

Sino-US cooperation in agricultural science and technology using PEST analysis has

scientifically and accurately grasped the quantitative law of Sino-US agricultural

science and technology cooperation.

KEYWORDS

Agricultural science and technology; Breeding patents; PEST analysis; Neutral

cognitive map; Breeding technology

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INDEX

ABSTRACT .....................................................................................................................2

KEYWORDS ...................................................................................................................2

1. INTRODUCTION .......................................................................................................4

2. LITERATURE REVIEW .............................................................................................5

3. CONSTRUCTING AN IMPACT MECHANISM FOR AGRICULTURAL SCIENCE AND

TECHNOLOGY DEVELOPMENT BASED ON PEST ANALYSIS ...........................6

3.1. PEST analytical framework ................................................................................6

3.2. Impact of U.S.-China Breeding Patents on Agricultural Science and Technology

Development ...........................................................................................................7

3.2.1. Political factors ............................................................................................7

3.2.2. Economic factors .........................................................................................7

3.2.3. Social factors ...............................................................................................8

3.2.4. Technical factors ..........................................................................................9

4. MODELING OF INFLUENCING FACTORS .............................................................9

4.1. Data Acquisition .................................................................................................9

4.2. Model building ..................................................................................................11

4.3. Impact factor metrics ........................................................................................13

4.3.1. Computational centrality measure .............................................................13

4.3.2. Factor classification ...................................................................................14

4.3.3. Ranking factors .........................................................................................14

5. MECHANISM OF ACTION ANALYSIS ...................................................................15

5.1. Performance of Chinese and U.S. Breeding Patents on Different PEST

Dimensions ...........................................................................................................15

5.2. The role of breeding patents in the development of agricultural science and

technology ............................................................................................................17

5.2.1. Changes in the agricultural economy ........................................................17

5.2.2. U.S. Imports of Chinese Agricultural Products ..........................................18

6. CONCLUSION ........................................................................................................19

FUNDING ......................................................................................................................20

REFERENCES ..............................................................................................................20

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1. INTRODUCTION

For thousands of years, the development of agricultural science and technology

has contributed to the growth of human population and the expansion of social

complexity [1].In fact, the ability to meet the basic needs of the world's food supply

and to gradually improve the quality of life of the rich people in the employment of

fewer and fewer people is mainly due to the development of agricultural science and

technology. At present, in the context of economic globalization and rapid

development of science and technology, it is important to explore the impact and

mechanism of the Chinese and U.S. patents in the area of agricultural science and

technology development [2]. Currently, in the context of economic globalization and

rapid development of science and technology, it is of great significance to investigate

the impact and mechanism of Sino-US breeding patents on agricultural science and

technology development[2].As the world's two largest economies, the progress of

China and the United States in the field of agricultural science and technology has a

far-reaching impact on the global food security and sustainable agricultural

development[3]. The new technologies created by China and the United States in the

field of agriculture can significantly increase the world's agricultural production and

maintain the sustainability of the world's agricultural development. the promotion of

new disease-resistant hybrid varieties, the reduction of the use of pesticides, the

scientific prevention and control of biological pests, the improvement of cultivation

technology of agricultural products, etc. agricultural science and technology can

increase the production of agricultural products, and promote agricultural

development. Intellectual property management is not only related to the incentive

mechanism of technological innovation, but also affects the competitive pattern of the

global agricultural market [4].In addition, with the global climate change and

population growth brought about by the pressure of food supply, improve crop yield

and adaptability has become an urgent need, which is the core goal of the innovation

of breeding technology [5].Therefore, an in-depth understanding of the development

of the U.S. and Chinese breeding patent situation, the differences in patent policy and

its impact on the development of their respective and global agricultural science and

technology. Therefore, in-depth understanding of the development of Chinese and

American breeding patents, patent policy differences and their impact on the

development of their respective and global agricultural science and technology is the

key to grasp the pulse of the global agricultural science and technology development,

guide the future development of agricultural policy and promote international

cooperation.

This paper utilizes PEST analysis to systematically analyze the impact and

mechanism of agricultural science and technology development, and

comprehensively assesses the factors from political, economic, social and

technological dimensions, so as to provide powerful strategic support for promoting

the healthy development of agricultural science and technology and global agricultural

cooperation. In order to reduce the dependence between the influencing factors, this

paper employs the NCM to model the integrated structure of the sub-factors of

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PESTEL, and to stratify and refine the impact of agricultural science and technology

through the measurement of the influencing factors. In order to reduce the

dependence between the influencing factors, this paper adopts NCM to model the

comprehensive structure of PESTEL sub-factors, and to refine the influence of

agricultural science and technology by stratifying the influence of the influencing

factors through the measurement of the influencing factors.In the exploration and

analysis, the performance of Sino-US breeding patents in different PEST dimensions

and the role of breeding patents on the development of agricultural science and

technology are used to validate the reasonableness of the methodology of this paper,

so as to comprehensively and systematically sort out the history of the cooperation

between China and the United States in agricultural science and technology and to

summarize the basic mode of the cooperation in agricultural science and technology

between China and the United States. We quantitatively analyze the influence of Sino-

US agricultural science and technology cooperation.

2. LITERATURE REVIEW

Zhang, F et al. elaborated the mechanism of agricultural science and technology

innovation to promote the green development of agriculture through spatial spillover

from the perspective of multi-dimensional approach, from the perspective of factor

spillover path and product spillover path, and measured the level of China's

agricultural green development by using grey correlation analysis and analyzed the

spatial and temporal evolution of the green development of China's agriculture [6].

Wang, Y proposed a program design for the intelligent platform of agricultural science

and technology park, and listed the basic content of the construction of the intelligent

park. The proposed intelligent platform program design applies new ICT technologies

such as 5G, artificial intelligence, cloud computing, Internet of Things, mobile Internet,

etc., and solves the problems faced by traditional agricultural science and technology

parks for a long time such as lack of experience in service, poor integrated security,

low operational efficiency, high management cost, and difficult business innovation [7].

Mahapatra, B. used autoregressive distributed lag combined with F-test and

investigated the impact of agricultural credit on total cereal, grain and rice production

using ARDL regression modeling framework. The empirical results of bounded F-test

showed that there was a statistically significant relationship between agricultural credit

and total cereal, millet and rice production at 1% level, which verified the long-run

equilibrium relationship in the model [8].Wang, Z designed a set of agricultural digital

greenhouse system based on ZigBee wireless sensor network technology. At the

same time, in the corresponding data acquisition and processing problems, this paper

adopts the PID controller under the particle filtering optimization technology to

optimize the error of the corresponding data acquisition system, eliminate the

corresponding noise and interference, so as to ensure the stability and effectiveness

of the corresponding data acquisition system in the digital greenhouse, reduce the

power consumption of the whole system, and ensure the stable transmission of

data[9].

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Aragie, E applied economic modeling in economics to assess the relative efficiency

of alternative investment choices for agricultural performance and household welfare.

To explain the linkages, as well as the direct and indirect impacts of alternative public

expenditure policies, the study used a general equilibrium model of Ethiopia calibrated

according to a well-decomposed socio-accounting matrix representing the structure of

the economy in the year 2010 [10]. Gurnovich, T. The innovation and investment

processes in the agricultural economy were studied by using system analysis

methods taking into account the manifestations of the trend of digitization of the agro-

industry. Structural changes and imbalances in the process of investment and

innovation in the agricultural sector of the economy were revealed. Statistical and

economathematical methods were used to forecast the development of agricultural

production [11].Habtewold, The impact of climate-smart agricultural technology on

multidimensional poverty of rural households in Ethiopia was used by T. To estimate

the impact of the mentioned technology, propensity score matching and endogenous

switching regression methods were used. The increase in income/consumption by

increasing the returns to production reduces the technology-induced multidimensional

poverty. This impact is transmitted more through the non-food expenditure pathway.

Finally, the impact of technology adoption on the Finally, the impact of technology

adoption on multidimensional poverty reduction has also been revealed [12].Treurniet,

M. used exogenous variation in the probability of a baseline survey to estimate the

impact of a baseline survey on the adoption by subsistence farmers of a new

agricultural technology that improves food security, and found that acceptance of the

survey had a large and statistically significant impact [13].

3. CONSTRUCTING AN IMPACT MECHANISM FOR

AGRICULTURAL SCIENCE AND TECHNOLOGY

DEVELOPMENT BASED ON PEST ANALYSIS

3.1. PEST ANALYTICAL FRAMEWORK

PEST analysis is used to assess these four external factors related to the business

situation, when including environmental and legal factors, it is called PESTEL, i.e., the

analysis of political, economic, socio-cultural, technological, environmental, and legal

factors [14]. In the use of PEST analysis to explore the impact and mechanism of the

influence of the Chinese and American breeding patents on the development of

agricultural science and technology, PEST analysis framework provides a

comprehensive method to examine the various external environmental factors. The

PEST analysis framework is shown in Figure 1, and the framework includes four main

dimensions: political, economic, social, and technological. The PEST analysis

framework is shown in Fig. 1, which includes four main dimensions: political,

economic, social and technological. This will help identify opportunities and

challenges, provide decision support for policy makers and the industry, and promote

the healthy and sustainable development of agricultural science and technology.

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Figure 1. PEST analysis framework

3.2. IMPACT OF U.S.-CHINA BREEDING PATENTS ON

AGRICULTURAL SCIENCE AND TECHNOLOGY

DEVELOPMENT

3.2.1. POLITICAL FACTORS

The governments of China and the United States influence the protection and

application of breeding patents through the formulation of relevant policies and legal

frameworks. Intellectual property laws, the duration of patent protection, and the

regulation and restriction of biotechnology all have a direct impact on the development

and application of breeding technologies [15-16]. trade agreements and diplomatic

relations between China and the United States also have an impact on breeding

patents. the provisions of trade agreements on agricultural products and

biotechnology affect technology exchanges and market access. The level of

government funding and support for research in agricultural science and technology

has a significant impact on the innovation and application of breeding patents, and

government-sponsored research programs may drive the development of new

varieties and technological innovations. government public policies, including attitudes

toward genetically modified products and consumer right-to-know policies, may also

affect the market acceptance and application of breeding patents. In some cases,

breeding technologies and patents are also linked to national security and food safety

policies, and breeding technologies that improve crop yields and resilience may be

considered part of a national food safety strategy.

3.2.2. ECONOMIC FACTORS

The development of breeding patents requires significant R&D investment, and the

rate of development of new technologies and varieties is determined by the

investment made by companies and research institutions in the U.S. and China. the

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patent system provides a level of protection that encourages such investment in the

hope of obtaining a return on that investment through exclusivity during the term of the

patent. the holder of a patented technology can gain a competitive advantage in the

marketplace, influencing the price of seed and the planting choices of farmers. at the

same time, a market with a high degree of patent concentration can lead to market

monopolization and affect fair competition. At the same time, markets with high patent

concentration can lead to market monopolization and affect fair competition in the

marketplace. patent protection for breeding technologies also plays an important role

in international trade. the entry of patented products for export is affected by differing

IPR protection laws and market access rules in different countries, which has a direct

impact on the competitiveness of the U.S. and China in the global marketplace for

agricultural products. patented technologies for breeding affect the cost and efficiency

of agricultural production. New breeding technologies can improve crop yields and

resistance to pests and diseases, reduce the cost of agricultural production, and

increase farmers' income [17].

3.2.3. SOCIAL FACTORS

Public attitudes towards breeding technologies, especially transgenic technologies,

have a direct impact on the market acceptance of breeding patents, and societal

concerns about food safety and environmental impacts may lead to boycotts or

restrictions on certain breeding technologies, thus affecting the commercialization of

these technologies.The degree of societal awareness of intellectual property rights

(IPRs) protection, especially in the agricultural sector, has a significant impact on the

filing and enforcement of breeding patents [18]. In societies with strong awareness of

intellectual property protection, patents are likely to be better defended, thus

stimulating more innovation and investment. breeding patents, especially those

involving gene editing and transgenic technologies, often lead to moral and ethical

debates in society, which may influence the formulation of governmental policies, and

consequently, the development and application of breeding technologies. the degree

of importance that societies attach to education and training in agricultural science

and technology determines the training of human resources in the field of agricultural

science and technology. The level of social emphasis on education and training in

agricultural science and technology determines the cultivation of human resources

and dissemination of technology in the field of agricultural science and technology,

and a high level of scientific education and technical training can accelerate the

progress of agricultural science and technology by facilitating the understanding and

application of breeding technology. changes in consumer demand for food products,

such as the preference for organic and non-GMO products, can affect the commercial

prospects of patents on breeding technology, and the market demand for crops with

specific characteristics, such as higher nutritional value and better taste, can also

drive breeding technology. Market demand for specific crop characteristics, such as

higher nutritional value and better taste, will also drive the direction of breeding

technology.

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3.2.4. TECHNICAL FACTORS

The existence of breeding patents encourages technological innovation, particularly

in areas such as gene editing and transgenic technologies, and patent protection

provides inventors with a window of time to recoup their R&D investment, thereby

stimulating additional R&D activities and innovation attempts. patenting standards and

specifications for breeding technologies differ in the U.S. and China, affecting the

direction of the technologies and the scope of their application. the technical

standards in the patenting and approval process determine which innovations can be

protected and disseminated. Breeding patents affect the accessibility and diffusion of

technologies, and the licensing of patented technologies determines how easily they

can be applied and under what conditions they can be used by other researchers and

developers. the patent system facilitates technology transfer and international

cooperation to a certain extent. Through patent licensing and cooperative

agreements, advanced breeding technologies can cross national boundaries and

contribute to the development of global agricultural science and technology [19].The

development of breeding technologies has a direct impact on the efficiency and

sustainability of agricultural production.For example, new drought- or disease-

resistant varieties can increase crop yields and reduce the reliance on chemical

fertilizers and pesticides, thus contributing to the sustainable development of

agriculture.

4. MODELING OF INFLUENCING FACTORS

4.1. DATA ACQUISITION

PEST analysis is a premise analysis whose main function is to identify the

environment in which a company or project operates and to provide data and

information to enable the organization to anticipate new situations and circumstances

[20], Figure 2 shows the process of data collection for agro-technology influencing

factors.

Political factors include government regulation of business, commercial law, labor

legislation, tax legislation, legislation in the field of import and export regulation,

competition protection, consumer protection, and environmental protection laws. It can

be expressed as , , , where

is the

government support index,

is the financial support for agricultural science and

technology from government agricultural policy, and

is the total agricultural science

and technology development budget. is the trade relationship index,

is the

volume of agricultural trade between China and the U.S., and is the total volume of

agricultural trade. is the intellectual property protection index, is the number of

patents on breeding, and

is the total number of patents on agricultural science

and technology.

GSl =G/T

TR I =A/T

IPPI =P/TP

TR I

IPPI

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Economic factors include i.e. inflation,

, interest rate, exchange rate,

unemployment etc. as well as ratio, intensity and type of contest between small,

medium and large enterprises, private and state owned property etc. denoted as

, , . Where

is agricultural investment as a percentage of ,

is investment in the agricultural

sector, and is the to the overall state of the country's economy.

the price volatility of agricultural products,

is the highest point of the price of key

agricultural products,

is the lowest point of the price of key agricultural products,

is the average price.

is the ratio of agricultural research and

development expenditures,

is the expenditures on agricultural research and

development, is the total agricultural expenditures.

Socio-cultural factors

cover demographic trends including age, sex, number of

people, natural growth rate, birth rate, death rate, population migration, educational

level and social groups in the population, cultural beliefs and values, and people's

individual needs. i.e., ,

, and

. where is the Population Growth Rate,

is the end of the

year population, and is the beginning of the year.

is the Consumer

Concern Index, which is the score of the survey on consumer concern about the

quality and sustainability of agricultural products, and the total survey score.

Consumer Concern Survey Score on Quality and Sustainability of Agricultural

Products, is Total Survey Score.

is Rural Education Level, ER is

Percentage of Educated Population in Rural Areas, is Total Population.

The analysis of technological factors covers innovation and creativity, technology

transfer, availability and access to patents, attitudes of researchers toward copyright,

and availability and access to the services of research institutes, which can be

denoted as , , and , where

is the Agricultural Technological Innovation Index,

is the number of new patents in

the field of agriculture, and is the total number of patents.

is the Digital

Agriculture Adoption Rate,

is the number of agricultural operators that have

adopted digital technologies, and

is the total number of agricultural operators;

is the index of cross-country scientific research cooperation,

is the

number of joint research projects between China and the U.S. in the field of

agricultural science and technology, and

is the total number of research

projects.

GDP

AIG =I/GDP

PVR = (Pmax −Pmin)/Pavg

RDEP =R&D/TA

GDP

PVR

Pmax

Pmin

Pavg

RDEP

R&D

PGR = (Pend −Pstart)/Pstar t

CSl =CC/TCC

REI =ER /TR

PGR

Pend

Pstar t

CSI

TCC

REI

ATI =NP/TP

DAI =DA /TA

ICPI =CRC/TRC

ATI

DAI

ICPI

CRC

TRC

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Figure 2. Data acquisition process

4.2. MODEL BUILDING

The interdependence between the analyzed factors. In addition, the structure of the

factors and sub-factors is characterized by ambiguity, vagueness and uncertainty.

Therefore, this study proposes a model to solve the problems encountered in the

process of measuring and evaluating the PEST analysis. The composition of the

model is shown in Fig. 3. The interdependence between the sub-factors is also taken

into account. The comprehensive structure of the PESTEL sub-factors is modeled

using the NCM.A quantitative analysis is also carried out on the basis of the static

analysis.

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Figure 3. Proposed framework for PEST analysis.

Neutral logic was introduced in 1995 as a generalization of fuzzy logic, especially

intuitionistic fuzzy logic. The logical proposition P is characterized by three neutral

components.

(1)

Where is the degree of truth, is the degree of falsity and

is the degree of

uncertainty.

A neutral matrix is a matrix in which the elements have been replaced by

elements in , where

is a ring of neutral integers. a neutral map is a

map in which at least one of the edges is a neutral edge. a cognitive map is called a

neutral cognitive map if uncertainty is introduced into the cognitive map. the NCM

uses neutral logic to represent the uncertainty and uncertainty in the cognitive map. a

NCM is a directed graph in which at least one edge is uncertainty as represented by

the dashed line, an example of a fuzzy neutral cognitive map is shown in Fig. 4. An

example of a fuzzy neutral cognitive map is shown in Figure 4. The static analysis

results of the mental model in the form of NCM are in the form of neutral numbers.

Finally, a de-neutralization process is applied to give the final ranking values. In this

study, the model is extended and detailed to deal with the classification and

prioritization of factors.

NL(P)=(T,I,F)

a= (aij)

⟨R∪I⟩

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Figure 4. Fuzzy Neutrosophic Cognitive Maps example.

4.3. IMPACT FACTOR METRICS

4.3.1. COMPUTATIONAL CENTRALITY MEASURE

The following metrics are computed using the absolute values of the NCM

adjacency matrix.

1. The out-degree is the row sum of the absolute values of the variables in

the neutral adjacency matrix, showing the cumulative strength of the

connections of the exit variables.

(2)

2. Input is the column sum of the absolute values of the variables, showing

the cumulative strength of the input variables.

(3)

3. The total degree of centrality of a variable, , is the sum of its in- and out-

degrees, which is then calculated as follows.

od(vi)

cij

d(vi) =

∑

i=1

id(vi)

d(vi) =

∑

i=1

td(vi)

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(4)

4.3.2. FACTOR CLASSIFICATION

Factors are categorized according to the following rules.

1. Transmitter variables have positive or uncertain out-degree and zero in-

degree .

2. Receiver variables have positive or uncertain in-degree , and zero out-

degree .

Ordinary variables have non-zero in-degrees, and ordinary variables can be

more or less receiver or transmitter variables, depending on the ratio of their in-

degrees to their out-degrees.

4.3.3. RANKING FACTORS

The process of de-neutralization gives the number of intervals of centrality. this is

based on the maximum and minimum values of I. Neutrality values are transformed in

intervals with two values, the maximum and the minimum [0,1].

The contribution of a variable in a cognitive map can be understood by calculating

its degree centrality, which shows how well the variable is connected to other

variables and what is the cumulative strength of these connections. the median of the

extremes is used to give the centrality value.

(5)

Then:

(6)

Hierarchical refinement of the impact of breeding technology on agricultural science

and technology based on PEST, the variables were ranked as shown in Table 1 for

factor prioritization and/or reduced values.

td(vi)=od(vi)+id(vi)

od(vi)

id(vi)

od(vi)

λ([

a1,a2

])

A>B⇔

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Table 1. The hierarchical model of PEST of breeding patents.

5. MECHANISM OF ACTION ANALYSIS

5.1. PERFORMANCE OF CHINESE AND U.S. BREEDING

PATENTS ON DIFFERENT PEST DIMENSIONS

The data on the political, economic, social and technological dimensions of

breeding patents in China and the United States were collected through the data

collection system, and hypothetical analyses were conducted to investigate the

significance of the impact of these factors on breeding patents.Table 2 shows the

results of the hypothetical analyses.The policy factor represents the impact of the

political environment on breeding patents, including policy support, changes in the

law, etc.The economic impact factor includes R&D investment, market size, etc.The

social impact factor reflects social attitudes, consumer preferences, etc.The

technological impact factor represents technological progress, innovation speed,

etc.The number of breeding patents is the number of applications filed by the country

in a given year. The social influence factor reflects the social attitude and consumer

preference, etc. The technology influence factor represents the technological progress

and innovation speed, and the number of breeding patents is the number of breeding

patent applications in a specific year.The political influence factor of China and the

United States increases year by year from 2019 to 2021, and by 2022, the technology

influence factor reaches 0.70, and the economic influence factor reaches 0.60, which

reflects that the governments of the two countries increase the number of breeding

patents during this period. This reflects that the governments of the two countries

have increased their policy support for agricultural science and technology during this

period, such as providing more R&D funds and optimizing the intellectual property

protection system, etc. This improvement in the policy environment may have played

a positive role in promoting the application and implementation of breeding patents.

Political Economic Social Technology

Political stability

(P1) Labor force level (E1) Entrepreneurial spirit

(S1)

Government

investment measures

(T1)

Intellectual

Property (P2)

Investment incentive

measures (E2) Purchase product (S2)

Government support

for scientific research

(T2)

Environmental

Protection Law

(P3)

National Income (E3)

Citizen attitudes

towards breeding

technology (S3)

Technological

Innovation (T3)

Positive media

promotion (S4)

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Table 2. Hypothesis Analysis Results

The NCM was used to identify and model the interdependencies. The weights of

the NCM are shown in Table 3.The weights are all below 0.5.

Table 3. Neutrosophic Adjacency Matrix

Time Country

Political

influence

factors

Economic

impact

factors

Social

impact

factors

Technical

impact

factors

Number

breeding

patents

2019 United

States 45 0.60 0.50 0.70 150

2019 China 0.50 0.55 0.45 0.65 130

2020 United

States 0.47 0.62 0.52 0.72 155

2020 China 152 0.58 0.48 0.68 135

2021 United

States 49 0.65 0.55 0.75 160

2022 China 0.55 0.60 0.50 0.70 140

P1 P3 E1 E2 E3 S1 S2 S3 S4 T1 T2 T3 P1

P1 00000000000.70.60

P3 00000.400000001

E1 0000000000000

E2 0000000.6000000

E3 000000.30.4000000

S1 00000000.800000

S2 0000000000000

S3 0000000000000

S4 0000000000000

T1 0000000000000

T2 0000.2000000000

T3 000001100.40.5000

00000000.4000000

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5.2. THE ROLE OF BREEDING PATENTS IN THE

DEVELOPMENT OF AGRICULTURAL SCIENCE AND

TECHNOLOGY

5.2.1. CHANGES IN THE AGRICULTURAL ECONOMY

China and the United States agricultural science and technology cooperation,

directly promote China's agricultural science and technology level, and the level of

agricultural science and technology is called the important driving force of the

development of the agricultural economy. therefore, this paper adopts the trade in

agricultural products as a measure of the index to measure the impact of China-US

cooperation in agricultural science and technology on the agricultural economy has a

certain degree of reality and reasonableness. figure 5 for the species of the country's

agricultural output value index in the year 2001-2023 ring changes in the trend of

agricultural output value index, from the From the point of view of agricultural output

value index, after excluding the price fluctuation factor, the output value index of

agriculture, forestry, animal husbandry, fishery, plantation, forestry, pasture and fishery

are all greater than 100 except for a few years, indicating that China's agricultural

output value is still showing an obvious year-on-year growth, which also fully

demonstrates the momentum of China's agricultural development.

From 2001 to 2023, the index of agricultural output value shows an overall trend of

first growth and then decline, and gradually tends to stabilize, in which the index of

total output value and agricultural output value reached the maximum value in 2008,

while the index of forestry, animal husbandry and fishery output value reached the

maximum value in 2007, from the point of view of the stability of the index of recent

years, they are all stable at 105 or above, that is, in recent years, the index of total

output value of agriculture is still showing obvious growth year by year, which also

shows that China's agriculture has a rapid development momentum. From the

perspective of the flat stability of the chain index in recent years, they are all stabilized

at 105 or above, which means that the agricultural industry has shown a coordinated

growth in recent years, and the growth rate of the chain index is around 5%.｡

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Figure 5. 2001-2023 trend of the output value index

5.2.2. U.S. IMPORTS OF CHINESE AGRICULTURAL PRODUCTS

Agricultural products is the final reflection of the results of agricultural science and

technology, China and the United States agricultural trade is an important carrier of

agricultural science and technology cooperation between the U.S. and China. China

and the United States agricultural products there are greater complementarity, in

recent years in the agricultural trade in the cooperation is becoming closer and closer.

figure 6 for the U.S. imports of agricultural products from China's total amount and

share of the 2009 year, the U.S. exports of agricultural products year-on-year will be

reduced by 17 billion U.S. dollars, while the amount of China's exports of agricultural

products to the United States will be Further increase, to 3.42 billion U.S. dollars, the

past four years China's total exports of agricultural products to the U.S. has doubled.

from the development trend, 1990-2008 U.S. imports of agricultural products from

China's total amount and share of the total amount of obvious growth. 1990 U.S.

imports of agricultural products from China's amount of 273 million U.S. dollars,

accounting for the U.S. value of the total value of agricultural products imported

1.19%. 2008 U.S. imports of agricultural products of Chinese origin and share of the

total value of the U.S. value of 1.19%. In 2008, the total value of U.S. imports of

agricultural products of Chinese origin amounted to 3454 million U.S. dollars, an

increase of 11.65 times compared with 1990, with an average annual growth rate of

15.14%. 2008 imports of agricultural products of Chinese origin accounted for the

proportion of U.S. imports of agricultural products to the total value of 4.29%, an

increase of 3.1 percentage points compared with 1990.

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Figure 6. Total amount and proportion of U. S. imports of agricultural products from China

6. CONCLUSION

In this paper, the impact and mechanism of U.S. breeding patents on the

development of agricultural science and technology is taken as the target, and the

PEST analysis combined with the static analysis of sexual cognitive map is used to

construct the model of the impact factors and validate it. The conclusions are as

follows.

1. For the performance of Chinese and American breeding patents in different

PEST dimensions, by 2022, the technological impact factor reaches 0.70, and

the economic impact factor reaches 0.60, reflecting that the governments of

the two countries have increased their policy support for agricultural science

and technology during this period, and this improvement in the policy

environment may play a positive role in promoting the application and

implementation of breeding patents.

2. In the analysis of the role of breeding patents on the development of

agricultural science and technology, Chinese and American breeding patents

make China's total agricultural output value is greater than 100, and in 2008,

imports of agricultural products of Chinese origin accounted for the proportion

of total U.S. imports of agricultural products also rose to 4.29%.

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FUNDING

This work was supported by Young Elite Scientist Sponsorship Program by BAST

[BYESS2022133], National Key Research and Development Program of China

[2022YFF0607900], 2115 Talent Training Plan of China Agricultural University

[00109012] and Key Research and Development Program of Hebei Province

[21372801D].

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