Analysis of the Spatial–Temporal Characteristics, Regional Differences, and Obstacle Factors of Agricultural Modernization Development in Gansu Province, China

Abstract

Agricultural modernization is the key path and core strategy for the transformation from traditional agriculture to modern agriculture, and it constitutes the cornerstone of China’s modernization system. Gansu Province is a typical ecologically fragile area, and a multi-ethnic province in the northwest of China. In recent years, through the application of efficient water-saving technologies, the industrialization of characteristic agriculture and institutional innovation, it has initially achieved the coordinated increase in production and ecological benefits. However, the lagging infrastructure and low efficiency of factor allocation still restrict its systematic transformation process. Based on the panel data of 14 prefectures and cities in Gansu Province from 2013 to 2022, this paper constructs an evaluation index system for agricultural modernization, and reveals the spatio-temporal evolution characteristics of agricultural modernization in Gansu Province. Further, this paper combines the Theil index and the obstacle degree model to analyze the regional differences and development bottlenecks of agricultural modernization in Gansu Province. The research finds that the overall level of agricultural modernization in Gansu Province has improved but is still in a stage of continuous development. Spatially, the western and central regions have a higher level of development, while the southern region is relatively lower. The time series analysis results show that the overall regional differences in agricultural modernization in Gansu Province have narrowed. From 2013 to 2018, the differences within the regions were dominant; after 2018, they were jointly affected by both within-region and between-region differences. The results of the obstacle factor analysis show that the modernization of agricultural industrial operation is the main obstacle factor, followed by the green modernization of agriculture. Based on these findings, this paper proposes suggestions such as strengthening regional coordination, enhancing production and operation capabilities, and promoting ecological construction. It is expected that, through the continuous development of the level of agricultural modernization, the coordinated development of agricultural modernization in Gansu Province can be promoted, and further, the well-being of the people can be enhanced, and the rural revitalization strategy can be advanced in depth.

1. Introduction

Agricultural modernization is the key path for the transformation from traditional agriculture to modern agriculture and constitutes the cornerstone of China’s modernization system. Currently, the development of agricultural modernization in China is relatively lagging behind, which has become a significant shortcoming in the country’s modernization process [1]. From 2013 to 2016, the country issued the “No. 1 Document” focusing on agricultural modernization for four consecutive years. The “19th National Congress” report clearly stated the “Rural Revitalization Strategy”, emphasizing the priority development of agriculture and rural areas [2]. Among them, the “Central No. 1 Document” in 2022 further emphasized the need to deepen the practice of rural revitalization and agricultural modernization [3]. Gansu Province is a traditional agricultural province in western China, and agriculture plays a more important role in its national economy [4]. However, Gansu Province has weak agricultural foundations, complex terrain, and fragile ecology, which are key factors restricting its modernization [5,6]. Compared with the provinces with high levels of agricultural modernization in China, the level of agricultural modernization in Gansu Province is significantly lagging behind and there are large internal differences [7]. Therefore, it is particularly important to implement quantitative monitoring of the development level of agricultural modernization in Gansu, and to conduct a comprehensive analysis of the factors hindering its development (

Table 1. List of Core Views.

Scholar	Core Point	Reference
Pardey and Alston	The root cause of the difficulty for traditional agriculture to drive economic growth lies in the price fluctuations of the “income flow” caused by the imbalance between market supply and demand. Modern agriculture, after reasonable transformation, can become an important engine for economic growth. It is emphasized that there is an urgency to transform from traditional agriculture to modern agriculture.	[8]
John W. Mellor	The path to agricultural modernization varies among countries due to differences in resources, economic levels, and cultures, and it typically goes through three stages: traditional agriculture → low-capital technology agriculture → high-capital technology agriculture.	[9]
Carmen D. Deere et al.	Agricultural modernization is a modernization process with an advanced distribution mechanism.	[10]
Gordon R. Conway	From the perspective of agricultural multifunctionality, it emphasizes the role of agriculture in cultural inheritance, social development, and environmental protection; it advocates new models, such as ecological agriculture, urban agriculture, and leisure agriculture, promoting the comprehensive upgrading of agriculture and the integration of urban and rural areas.	[11]
Jiang, Fuxin	Agricultural modernization is an organic unity composed of the agricultural mechanism system, the productive forces system, and the production materials production and circulation system.	[12]
Gu, Huanzhang	Agricultural modernization is a dynamic process in which traditional production sectors gradually evolve into modern industrial sectors, emphasizing the optimization and upgrading of industrial structure.	[13]

).

Agricultural modernization has been a hot topic in academic research. As early as the 1960s, Theodore W. Schultz proposed that a transformed modern agriculture could drive economic growth [8]. John W. Mellor believed that the transformation from traditional agriculture to modern agriculture would go through three stages: traditional agriculture, low-capital technology agriculture, and high-capital technology agriculture [9]. Deere further argued that agricultural modernization is a process with advanced distribution mechanisms [10]. Additionally, Conway promoted various new models of modern agriculture from the perspectives of urban–rural integration and sustainable development based on the multi-functionality of agriculture [11]. Regarding research on China, Jiang Fuxin believed that agricultural modernization is an organic whole [12]. Gu Huanzhang regarded it as a dynamic process of the evolution from traditional production departments to modern industrial sectors [13]. Based on the above research, this paper defines agricultural modernization as a dynamic evolutionary process centered on the transformation of agricultural production methods, which is advanced through the coordinated promotion of technological innovation, institutional innovation adaptation, and optimized factor allocation to transform traditional agriculture into a modern industrial system. Research on the construction of agricultural modernization indicator systems is also abundant. For instance, van Ittersum et al. used the SEAMLESS model to construct a comprehensive indicator system containing four dimensions: economy, environment, society, and institutions [14]. Sands and Podmore built a system from the perspectives of agricultural green development models, land resource protection, and environmental pollution [15]. Carof et al. analyzed the level of agricultural modernization from four aspects: economic development, ecological environment protection, greenhouse gas emissions, and social progress [16]. Early evaluations in China focused on agricultural production itself, often measured by land productivity, labor productivity, and capital utilization rate, among other factors [17]. Liu Xiaoyue selected agricultural production means, production conditions, labor force, and output capacity as indicators to construct an evaluation system [18]. In recent years, Li and Hao, and Zhang and Meng have included agricultural science and technology levels, industrial operations, and ecological environment in the evaluation system [19,20]. Regarding the selection of evaluation methods, the entropy method [21], the TOPSIS method [22], and the analytic hierarchy process [23] are commonly used. Moreover, the Theil index [24], the ESDA method [25], and the obstacle factor method [26] have been increasingly applied in studies on regional differences and obstacle factors. In terms of influencing factors, the international academic community has focused on macro institutional environment analysis. For example, Hazell and Wood pointed out that food security, land use, and agricultural ecosystems are key factors restricting agricultural modernization [27]. Bahiigwa et al. believed that the wealth gap affects the development of agricultural modernization [28]. Waldron et al. emphasized the decisive role of government policy formulation [29]. Shu Kunliang et al. considered technological innovation as a key driving force [30]. Song Kun et al. found that direct financing has a significant positive impact on agricultural modernization [31]. In terms of research regions, there is a focus on underdeveloped areas. For instance, Dibua studied agricultural modernization in Nigeria [32]. Otchia analyzed the efficiency of agricultural modernization in the Democratic Republic of the Congo [33]. Du Yuning et al. and Wei et al. studied the regional imbalance of agricultural modernization in 31 provinces of China [34,35]. Qin Cheng et al. analyzed the development status of agricultural and rural modernization in various provinces and cities of China [36]. Li Mengjie et al. studied the regional differences and obstacle factors of agricultural modernization in Shandong Province, China [37]. Yang Qifeng et al. investigated the modernization development situation in Northeast China [38]. Lü Wenguang conducted a comprehensive evaluation of the agricultural modernization development process in Gansu Province, China [39], while Liu et al. and Zhang and Liu evaluated the agricultural modernization development level of each city and prefecture in Gansu Province, China based on a single year [40,41].

In summary, the academic community has achieved fruitful results in the research on agricultural modernization. However, there is still a need for further exploration in the dynamic expansion of its connotation, regional adaptability, and systematic analysis of the influencing mechanisms. Moreover, due to the diversity of index system construction and evaluation methods, the conclusions drawn are also different. Regarding the research on agricultural modernization in Gansu Province, the existing literature mostly focuses on either temporal or spatial differences, rarely considering both temporal and spatial scales simultaneously, and the discussion on obstacle factors is insufficient. Therefore, this paper takes Gansu Province in China as the research area and conducts a comprehensive evaluation by establishing an index system. From the perspective of time and space, the Theil index analysis method is adopted to explore the regional differentiation characteristics of agricultural modernization in various cities of Gansu Province. Further, the obstacle degree model is used to trace the obstacle factors of agricultural modernization. Through the above research, it is expected to provide countermeasures and suggestions for the strategic formulation and decision-making guidance of agricultural modernization development in Gansu Province, China. This research not only has a positive promoting effect on the development of agricultural modernization in Gansu Province, China, but its methodology and results have important reference value for other regions with similar agricultural development characteristics in China and similar regions worldwide.

2. Research Design

2.1. Overview of the Study Area and Data Sources

Figure 1 shows data from a 30 m DEM. The topography of Gansu Province, China, is mainly composed of plateaus and mountains, forming a long and narrow band. Most of the area belongs to arid and semi-arid regions. Due to geographical and climatic constraints, its economic development is lagging behind, and the development of agriculture in rural areas is slow.

This paper selects the 14 prefecture-level cities in Gansu Province as the research objects. Considering the natural geographical conditions and the integrity of administrative divisions comprehensively, Gansu Province is divided into five sub-regions: the Hexi Region, the Longdong Region, the Longdongnan Region, the Longzhong Region, and the Southern Ethnic Region for research [42] (

Table 2. Division of Sub-regions in Gansu Province.

Province	Sub-Regions	City and State
Gansu province	Longzhong Region	Lanzhou City
		Baiyin City
		Dingxi City
	Southern Ethnic Region	Linxia Hui Autonomous Prefecture
		Gannan Tibetan Autonomous Prefecture
	Hexi Region	Jiuquan City
		Jiayuguan City
		Jinchang City
		Wuwei City
		Zhangye City
	Longdongnan Region	Longnan City
		Tianshui City
	Longdong Region	Qingyang City
		Pingliang City

).

2.2. Evaluation Index System Construction

Agricultural modernization is a process of transformation from traditional agriculture to modern agriculture, involving multiple aspects, such as equipment upgrading, technological transformation, and market-oriented management [43]. This study, guided by the “14th Five-Year Plan for Promoting Modernization of Agriculture and Rural Areas” issued by the State Council and the “14th Five-Year Plan for Promoting Modernization of Agriculture and Rural Areas in Gansu Province, China”, and in light of the actual situation and data availability in Gansu Province, China, constructs an evaluation system from five dimensions, totaling twenty specific indicators (

Table 3. Index System of Agricultural Modernization.

First Level Indicators	Second Level Indicators	Calculation and Connotation of Indicators	Attribute	Weight
Modernization of agricultural science and technology innovation	A1 Water conservancy construction level (%)	Effective irrigated area/Crop planting area	+	0.034
	A2 Agricultural mechanization level (kilowatts per hectare)	Total power of agricultural machinery/Sown area of crops	+	0.045
	A3 Agricultural electrification level (KWH/person)	Total rural electricity consumption/Total rural population	+	0.063
Modernization of agricultural industry management	A4 Degree of agricultural large-scale production (hectares)	Crop sown area/rural households	+	0.101
	A5 Efficiency of agriculture, forestry, animal husbandry, and fishery services (%)	The output value of the agricultural, forestry, animal husbandry, and fishery service industry/The total output value of the agricultural, forestry, animal husbandry, and fishery	+	0.03
	A6 Adjustment of agricultural planting structure (%)	The sown area of non-food crops/the sown area of crops	+	0.047
	A7 Agricultural industry integration potential (%)	The output value of the primary industry/Regional gross domestic product	-	0.064
	A8 Optimization of agricultural industrial structure (%)	The output value of animal husbandry/The total output value of agriculture, forestry, animal husbandry, and fishery	+	0.101
Modernization of agricultural production efficiency	A9 Land productivity (yuan)	Total output value of agriculture, forestry, animal husbandry, and fishery/Total sown area of crops	+	0.053
	A10 Labor productivity (Yuan/person)	Total output value of agriculture, forestry, animal husbandry, and fishery/Number of employees in agriculture, forestry, animal husbandry, and fishery	+	0.063
	A11 Growth rate of agricultural output (%)	(Current year’s agricultural output value—Previous year’s agricultural output value)/Previous year’s agricultural output value)	+	0.047
	A12 Comprehensive grain production capacity (tons/hectare)	Total grain output/Grain planting area	+	0.071
	A13 Farmers’ income level (yuan)	Per capita disposable income of farmers	+	0.046
Modernization of green development in agriculture	A14 Ecological construction level (%)	The added value of forestry/The added value of agriculture, forestry, animal husbandry, and fishery	+	0.05
	A15 Fertilizer application level (tons/hectare)	Total output value of agriculture, forestry, animal husbandry, and fishery/Number of employees in agriculture, forestry, animal husbandry, and fishery	-	0.029
	A16 Disaster resistance and prevention capacity (%)	Area affected by disaster/Area stricken by disaster	-	0.041
Modernization of rural social development	A17 Urban–rural income ratio (%)	Per capita disposable income of rural residents/Per capita disposable income of urban residents	+	0.043
	A18 Proportion of operating income (%)	Rural residents’ operating income/Per capita disposable income of rural residents	+	0.033
	A19 Engel’s coefficient (%)	Food expenditure/Total expenditure of rural residents	-	0.037
	A20 Education, culture and entertainment consumption level (%)	Expenditure on education, culture, and entertainment/Total expenditure of rural residents	+	0.035

). Specifically, the modernization of agricultural scientific and technological innovation is reflected through three indicators: water conservancy, mechanization, and electrification levels [44,45,46]. The modernization of agricultural industrial operation encompasses five indicators, including large-scale operation, industrial structure optimization, degree of large-scale production, and efficiency of agricultural, forestry, animal husbandry, and fishery services [47,48,49]. The modernization of agricultural production efficiency is evaluated through five indicators centered on land productivity and labor productivity, comprehensively assessing the comprehensive production capacity of agriculture in Gansu Province, China [50]. The modernization of agricultural green development focuses on ecological construction, intensity of chemical fertilizer application, and disaster resistance capacity, highlighting the core position of green agriculture [51,52]. The modernization of rural social development is reflected through indicators such as the urban–rural income ratio, Engel’s coefficient, and cultural and entertainment consumption level, directly indicating the economic status and living quality of farmers [53,54]. The weights in the table are determined by the entropy method after processing the statistical data into dimensionless standardized data through the normalization method (Table 3).

2.3. Research Methods

2.3.1. Multi-Index Comprehensive Evaluation Method

The evaluation of agricultural modernization involves multiple dimensions and requires comprehensive consideration to form a comprehensive result. The entropy method, based on the theory of information entropy, is specifically designed for complex multi-attribute decision-making, and can accurately and objectively quantify the weights of indicators, ensuring the objectivity and precision of the evaluation results. Given its advantages, this paper applies the entropy weight method to the evaluation of the level of agricultural modernization in Gansu Province to achieve a comprehensive and systematic assessment [55]. The specific operational optimization is as follows:

(1)

Data standardization: Firstly, standardize the data to eliminate the influence of units and dimensions.

The formula for standardizing positive indicators is as follows:

$$X{\prime }_{ij}={\displaystyle \frac{X_{ij}-\min (X_{ij})}{\max (X_{ij})-\min (X_{ij})}}+0.0001$$

(1)

The formula for standardizing negative indicators is as follows:

$$X{\prime }_{ij}={\displaystyle \frac{\max (X_{ij})-X_{ij}}{\max (X_{ij})-\min (X_{ij})}}+0.0001$$

(2)

(2)

Calculate the feature contribution degree of the i-th evaluation object under the j-th indicator as follows:

$$Y_{ij}={\displaystyle \frac{X{\prime }_{ij}}{{\displaystyle \sum _{i=1}^{n}X{\prime }_{ij}}}}$$

(3)

(3)

The information entropy e_j of each indicator is calculated as follows:

$$e_j=-k{\displaystyle \sum _{i=1}^n{Y}_{ij}}\ln (Y_{ij}),k={\displaystyle \frac{1}{\ln n}}$$

(4)

(4)

Calculate the specific weight W_j of each indicator as follows:

$$W_j={\displaystyle \frac{1-e_j}{{\displaystyle \sum _{j=1}^{\mathrm{m}}(1-e_j)}}}$$

(5)

(5)

Calculate the index of agricultural modernization level as follows:

$$Z={\displaystyle \sum _{i=1}^m{W}_j}X{\prime }_{ij}$$

(6)

Among these, X′_ij is the dimensionless data after processing, X_ij is the original data of the jth indicator of the ith province, max(X_ij) is the maximum value of the original indicator data, min(X_ij) is the minimum value of the original indicator data, Y_ij is the proportion of the jth indicator of the ith evaluation object, e_j is the information entropy, g_j represents the coefficient of variation, W_j is the specific weight, Z is the index of rural modernization level, and m is the number of indicators.

2.3.2. Theil Index Analysis Method

The Theil index is an important tool for assessing economic and social inequality, capable of intuitively presenting regional differences and further breaking them down into inter-regional and intra-regional disparities. This paper employs the Theil index to analyze the regional differences in the level of agricultural modernization in Gansu Province. The specific calculation steps and methods are as follows [56]:

$$T={\mathrm{T}}_{\mathrm{b}}+{\mathrm{T}}_{\mathrm{w}}={\displaystyle \frac{1}{n}}{\displaystyle \sum _{\mathrm{i}=1}^{\mathrm{n}}\frac{{\mathrm{Y}}_{\mathrm{i}}}{\mathrm{y}}}\log {\displaystyle \frac{{\mathrm{Y}}_{\mathrm{i}}}{\mathrm{y}}}$$

(7)

$$T_b={\displaystyle \sum _{k=1}^K{y}_k}\log {\displaystyle \frac{y_k}{n_k/n}}$$

(8)

$$T_w={\displaystyle \sum _{k=1}^K{y}_k}({\displaystyle \sum _{i \in gk}\frac{y_i}{y_k}}\log {\displaystyle \frac{y_i/y_k}{1/n_k}})$$

(9)

The Theil index value T represents the level of agricultural modernization, with a range of 0 to 1, Y_i represents the agricultural modernization index of the i-th prefecture-level city or autonomous prefecture, y indicates the average level of agricultural modernization in Gansu Province, and n represents the number of prefecture-level cities or autonomous prefectures in Gansu Province. The n prefecture-level cities or autonomous prefectures are divided into K sub-regions, and the k-th sub-region g_k contains n_k prefecture-level cities or autonomous prefectures, y_i and y_k respectively represent the proportion of the development level index of the i-th prefecture-level city or autonomous prefecture and the k-th sub-region to the total value of the basin, and T_b and T_w respectively represent the differences between and within regions in agricultural modernization.

2.3.3. Obstacle Degree Model

The constraints and influences on the agricultural modernization evaluation system are complex and change dynamically with significant differences. This paper aims to explore the key constraints on the development of agricultural modernization in Gansu Province by using the obstacle degree model. This model can accurately quantify the degree of hindrance of evaluation indicators, identify key constraints, systematically sort out the main influencing factors, and precisely quantify their impact degrees, providing strong support for the diagnosis of obstacle factors in the rural modernization system [57]. The main calculation formula is as follows:

$$D_{ij}=1-X_{ij}$$

(10)

$$U_{ij}=W_{ij}\times D_{ij}$$

(11)

$$O_{ij}={\displaystyle \frac{U_{ij}}{{\displaystyle \sum _{j=1}^n{U}_{ij}}}}\times 100\%$$

(12)

Here, D_ij represents the deviation degree of the indicator, which is the degree of deviation between a single indicator and the maximum value, U_ij is the factor contribution degree, reflecting the influence degree of a single indicator on the overall indicator, W_ij is the indicator weight, used to measure the importance of the indicator in the overall evaluation system, and O_ij is the obstacle degree of a specific indicator, used to quantify the impact degree of a specific indicator on the modernization development of rural areas. The larger the O_ij value, the more significant the hindering effect of this indicator on the modernization development of rural areas in the region.

3. Data Processing and Result Analysis

3.1. Analysis of the Development Level of Agricultural Modernization in Gansu Province, China

3.1.1. General Characteristics

From a provincial perspective as a whole (Figure 2), the index of agricultural modernization development in Gansu Province of China has shown a significant upward trend from 2013 to 2022. Its comprehensive development index has risen from 0.33 in 2013 to 0.68 in 2022, with an average annual growth rate of 8.44%. Specifically, it can be divided into two stages.

The first stage was from 2013 to 2018. During this period, the development level of agricultural modernization in Gansu Province grew relatively slowly. There are several possible reasons. Firstly, Gansu Province is located in a remote area. The unfavorable geographical location leads to poor information flow. Farmers tend to pursue output rather than quality in production and operation, resulting in low added value for agricultural products. Secondly, agricultural production is overly dependent on cultivated land resources, which has significantly increased the carrying pressure on cultivated land. At the same time, there is a lack of sufficient attention to ecological protection. Finally, the government’s support for agricultural development is relatively insufficient. The promotion and application of agricultural science and technology are not yet in-depth, further restricting the development of agricultural modernization.

The second stage was from 2019 to 2022, during which the development of agricultural modernization in Gansu Province entered a new period of rapid growth. The main reasons for this rapid growth were the effective implementation of the targeted poverty alleviation strategy and the timely proposal and in-depth advancement of the rural revitalization strategy in 2018. The country’s emphasis on the development of agriculture and rural areas reached an unprecedented new height, providing strong policy support and a driving force for the continuous advancement of agricultural modernization in Gansu Province. With the rural revitalization strategy, Gansu Province formulated a series of measures in line with local conditions to promote the development level of agricultural modernization in the province. For instance, it proposed the “High-quality Grain Project” to drive the transformation of agricultural production models in Gansu Province towards high quality and high efficiency. Another example is promoting the “Out-of-Village and Out-of-Province” sales of agricultural products to accelerate the marketization process of agricultural products. In addition, under the impetus of e-commerce platforms, the characteristic agricultural products of Gansu have been able to enter the market more widely, significantly increasing the income levels of the farmers. Finally, the “Science and Technology for Agriculture” activities were carried out, focusing on water resource management and water-saving irrigation, promoting the popularization and application of modern agricultural technologies. This series of policy measures not only promoted the all-round development of agriculture and rural areas in Gansu Province but marked significant achievements in the construction of agricultural modernization in the province.

3.1.2. Analysis of Subsystem Characteristics

From the perspective of subsystems (Figure 3), during the period from 2012 to 2022, except for the modernization of agricultural industrial operation, all other subsystems have improved to varying degrees, as follows: (1) The modernization level of agricultural science and technology innovation has been continuously rising, with its development index increasing from 0.007 in 2013 to 0.122 in 2022. This might be attributed to the increased investment in agricultural science and technology progress and resources in Gansu Province. (2) The modernization level of agricultural industrial operation first declined and then rose. Its development index dropped from 0.236 in 2013 to 0.059 in 2018, and then began to rise after 2018. Based on the comprehensive research results, there are mainly three reasons: first, the increase in urbanization and industrialization levels has led to a decline in the proportion of the primary industry and the loss of rural labor force; second, the improvement in mechanization levels has reduced the number of personnel in the agricultural, forestry, animal husbandry, and fishery service industry, lowering its efficiency; third, Gansu Province has actively promoted the structural reform of agricultural supply sides, developed characteristic animal husbandry, and optimized the industrial structure, which has led to a certain recovery in the modernization level of agricultural industrial operation. (3) The modernization level of agricultural production efficiency has improved most significantly, with the comprehensive development index increasing from 0.027 in 2013 to 0.257 in 2022, a growth of 23 percentage points. The main reason for this trend is the progress in mechanized planting and irrigation technologies in Gansu Province, which has increased the grain yield per unit area and agricultural output value. At the same time, this process has also driven the steady increase in rural residents’ income and accelerated the modernization of agriculture. (4) The modernization level of agricultural green development has fluctuated greatly. Although Gansu Province adheres to the concept that “green mountains and clear waters are as valuable as mountains of gold and silver” and has restricted the use of pesticides and fertilizers, the fragile ecological environment and frequent natural disasters have affected the stability of production, resulting in significant fluctuations in the modernization index of agricultural green development. Targeted measures are urgently needed to enhance its stability and sustainability. (5) Finally, thanks to China’s poverty alleviation policies and rural revitalization policies, the modernization level of rural social development in Gansu Province has continued to grow.

3.1.3. The Temporal Characteristics of Agricultural Modernization Development Levels in Various Cities and Prefectures

Figure 4 presents the dynamic of the comprehensive scores of agricultural modernization levels of 14 prefectures and cities in Gansu Province, China in 2013, 2016, 2019, and 2022. The results show that Dingxi City had the highest comprehensive index of agricultural modernization at 0.761 in 2022, ranking first in the province. Linxia Prefecture ranked last with a score of 0.469. Over the past ten years, the agricultural modernization levels of all prefectures and cities have achieved positive growth. Among them, Jinchang City had the most significant increase, with its comprehensive score rising from 0.198 in 2013 to 0.683 in 2022, with an average annual growth rate of 14.75%. Zhangye, Dingxi, and Wuwei followed, with average annual growth rates of 14.26%, 13.89%, and 12.26%, respectively. Linxia Prefecture had the smallest increase, at only 4.78%. The research indicates that, since Gansu Province, China has promoted the optimization of the rural and agricultural economic structure and the construction of a modern agricultural support system, the agricultural modernization levels of all regions have improved to varying degrees.

3.2. Spatio-Temporal Differentiation Analysis of Agricultural Modernization Development Level in Gansu Province, China

This study aims to deeply explore the spatial distribution characteristics of the agricultural modernization development level in Gansu Province. By applying the natural breaks method, the agricultural modernization development level of Gansu Province is classified into six grades as follows: extremely low development level (0.198, 0.250], low development level (0.250, 0.400], medium–low development level (0.400, 0.500], medium–high development level (0.500, 0.600], high development level (0.600, 0.700], and extremely high development level (0.700, +∞). Finally, ArcGIS 10.8 software was used for spatial visualization processing.

From a spatial perspective, the development level of agricultural modernization in Gansu Province as a whole shows an unbalanced phenomenon. This uneven characteristic roughly presents a situation where the western and central regions are relatively high and the southern region is relatively low in space. This can be detailed specifically for each year (Figure 5). In 2013, there were fewer agglomeration areas, and the low agglomeration areas were mainly concentrated in the Hexi region and the central Gansu region. By 2016, the agglomeration feature in the Hexi region did not change significantly, but the agglomeration area in the central Gansu region expanded on a large scale. In 2019, the agglomeration area in the Hexi region shrank significantly, and the southern part of Gansu Province contracted to the central Gansu region and the southeastern Gansu region. In 2022, the agglomeration feature became more obvious, with two significantly high development level areas emerging in Dingxi City and Zhangye City. Around Zhangye City, there was a “high–high agglomeration” feature, and its adjacent prefecture-level cities maintained a relatively high development level. Dingxi City, on the other hand, presented a “high–low agglomeration” feature, with a relatively high level of agricultural modernization development in Dingxi City but lower levels in the surrounding prefecture-level cities.

An analysis of the distribution of prefecture-level cities with high levels of development reveals that those with a relatively high level of agricultural modernization have a high degree of overlap with the geographical distribution of major grain-producing areas. Notably, Dingxi City and Zhangye City have the highest levels of agricultural modernization. Prefecture-level cities with relatively lower levels of agricultural modernization are mainly concentrated in the southern ethnic regions. According to the data in

Table 4. Agricultural Modernization Development Levels of Various Cities in Gansu Province from 2013 to 2022.

	City	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	Average Annual Growth Rate	Annual Average Score	Final Ranking
Central Gansu Region	Lanzhou	0.235	0.199	0.372	0.46	0.554	0.582	0.581	0.629	0.596	0.546	9.82	0.4754	3
	Baiyin	0.291	0.338	0.36	0.307	0.375	0.422	0.544	0.58	0.577	0.673	11.87	0.4467	8
	Dingxi	0.236	0.303	0.425	0.334	0.287	0.44	0.558	0.596	0.673	0.761	13.89	0.4613	6
Southern Ethnic Region	Linxia	0.308	0.261	0.268	0.472	0.265	0.274	0.401	0.402	0.462	0.469	4.78	0.3582	14
	Gannan	0.36	0.5	0.352	0.335	0.527	0.404	0.474	0.469	0.478	0.555	4.93	0.4454	9
Hexi Region	Jiuquan	0.377	0.451	0.511	0.474	0.454	0.462	0.486	0.528	0.568	0.646	6.17	0.4957	1
	Jiayuguan	0.385	0.46	0.5	0.457	0.261	0.301	0.447	0.408	0.492	0.543	3.89	0.4254	11
	Jinchang	0.198	0.23	0.358	0.367	0.452	0.458	0.504	0.629	0.748	0.683	14.75	0.4627	5
	Wuwei	0.29	0.377	0.403	0.432	0.373	0.403	0.481	0.506	0.588	0.688	12.26	0.4541	7
	Zhangye	0.216	0.281	0.309	0.353	0.374	0.386	0.485	0.485	0.577	0.717	14.26	0.4183	13
Southeastern Gansu Region	Tianshui	0.252	0.327	0.385	0.387	0.375	0.432	0.536	0.502	0.58	0.588	9.87	0.4364	10
	Longnan	0.366	0.393	0.44	0.422	0.471	0.475	0.585	0.519	0.551	0.66	6.98	0.4882	2
Eastern Gansu Region	Pingliang	0.26	0.41	0.333	0.344	0.469	0.359	0.498	0.438	0.522	0.564	10.54	0.4197	12
	Qingyang	0.375	0.421	0.483	0.462	0.395	0.415	0.483	0.503	0.535	0.654	6.35	0.4726	4
	Average	0.296	0.354	0.393	0.4	0.402	0.415	0.505	0.514	0.568	0.625	7.299	0.447

, the spatial differentiation characteristics of agricultural modernization have undergone significant changes from 2019 to 2022. This change is mainly attributed to the rural revitalization strategy proposed by the Chinese government, which emphasizes the priority development of agriculture and rural areas. Against this backdrop, some prefecture-level cities have rapidly improved their levels of agricultural modernization by leveraging their natural resource endowments, advantageous geographical locations, and solid economic foundations, thus taking the lead overall. By contrast, regions such as Gannan Prefecture and Linxia Prefecture have lagged behind in the process of agricultural modernization, and the gap with cities like Zhangye and Dingxi has gradually widened.

3.3. Analysis of Regional Disparities in the Development Level of Agricultural Modernization in Gansu Province, China

3.3.1. Overall Difference Analysis

To further compare the regional differences in agricultural modernization development among various regions in Gansu Province, this paper uses the Theil index to analyze the evolution trend of regional differences in the agricultural modernization index in Gansu Province from 2013 to 2022. As shown in Figure 4, the overall difference index of Gansu Province shows a fluctuating downward trend, with the overall Theil index dropping significantly from 0.023 in 2013 to 0.008 in 2022. This trend indicates that, under the guidance of national macro-control policies, the regional coordinated development policy of agriculture in Gansu Province has been positive and effective. Among them, from 2013 to 2017, the overall differences in agricultural modernization development in Gansu Province mostly originated from within-region differences, while inter-regional differences were relatively small. Since 2018, within-region differences have decreased significantly, and the sources of differences in the level of agricultural modernization development in Gansu Province have been roughly equal between within-region and inter-region. This indicates that the sources of differences in the level of agricultural modernization development in Gansu Province have gradually evolved from being mainly within-region differences to being jointly caused by inter-region and within-region factors. This requires decision-makers to further optimize the top-level design to achieve further coordinated development among the regions (Figure 6).

3.3.2. Analysis of Inter-Regional Differences

From 2013 to 2022, the levels of agricultural modernization development among various regions were uneven and inconsistent. Table 3 provides a detailed account of the development process for each city in Gansu Province in terms of agricultural modernization. From 2013 to 2017, the differences among the regions gradually narrowed, but with the implementation of the rural revitalization strategy, the differences began to widen in 2018. Figure 5 more directly reflects the changes in differences among the regions over the past ten years. By comparing the maximum and minimum values of the agricultural modernization development levels among the regions in Gansu Province in each year, and the difference between them, the following two conclusions can be drawn. First, both the maximum and minimum values have been continuously increasing, indicating that the levels of agricultural modernization development in various regions of Gansu Province are constantly improving, which supports the previous viewpoint. Second, looking at the degree of dispersion over the past ten years, the growth rates of the maximum and minimum values are almost the same, and there is no obvious downward trend in the difference between them. This indicates that the differences in the levels of agricultural modernization development among the regions in Gansu Province still exist and are difficult to smooth out in the short term (Figure 7).

3.3.3. Analysis of Internal Regional Disparities

The comprehensive scores and rankings of agricultural modernization of the 14 prefecture-level cities in Gansu Province show that there are significant differences in the development levels of agricultural modernization among these cities, and the influencing factors of agricultural modernization development levels in each city are also different (Figure 8).

The agricultural modernization development level in the Longzhong area has grown at a relatively fast pace, with an average annual growth rate exceeding the provincial average of Gansu Province. Lanzhou, as the provincial capital, has a much stronger overall economic strength than other prefecture-level cities in the province, and its geographical advantages for promoting modern agriculture are obvious. However, the agricultural natural resources in the counties and districts under Lanzhou’s jurisdiction, such as Gaolan County, Yongdeng County, Honggu District, and Qilihe District, are relatively scarce, with a high proportion of low-yield fields and backward agricultural infrastructure, which has affected the overall development level of agricultural modernization in Lanzhou City. The average annual growth rate of Dingxi City reached 13.89%, and its development history is representative within Gansu Province. Since 2019, thanks to the in-depth implementation of the rural revitalization strategy, Dingxi City has rapidly increased its agricultural modernization development level by strengthening the brand building of characteristic agricultural products, such as potatoes, wide noodles, angelica, and astragalus, which have enhanced the product’s popularity and market competitiveness. In 2022, the score for agricultural modernization reached 0.761, ranking first in the province. Additionally, Baiyin City has a relatively high level of agricultural modernization, ranking fourth in Gansu Province. This is mainly attributed to its significant achievements in reducing the use of chemical fertilizers, which has greatly improved the index of agricultural green development. Moreover, Baiyin City is in a period of resource depletion and transformation, and the government has provided strong support for agriculture.

The level of agricultural modernization in the southern ethnic minority areas is relatively low, with growth rates not exceeding 5%. Among them, Linxia Prefecture scored only 4.69 in 2022. This area was once a deeply impoverished region, and its economic foundation is weak due to its special geographical location and harsh natural environment, resulting in particularly slow agricultural development. In recent years, the development of animal husbandry has been vigorously promoted in ethnic minority areas, such as large-scale cattle and sheep breeding, cold chain logistics, and slaughtering and processing, which has strengthened the industrial foundation, extended the industrial chain, and promoted the development of a modern industrial system. Coupled with the promotion of the construction of a major tourism brand in this region, the trend of integration of agriculture, culture, and tourism is obvious, and the income level of the farmers has significantly increased. The gradual rise of characteristic planting industries, such as highland summer vegetables and raspberries in Linxia Prefecture, has also injected new vitality into agricultural modernization. Since 2018, the level of agricultural modernization in this area has significantly improved.

The agricultural modernization development level of the five cities in the Hexi Corridor is generally high, and they are important commodity grain bases in Gansu Province. Jinchang and Jiayuguan cities belong to the suburban agriculture type, with a high degree of industrial integration. However, Jiayuguan City has a small area, weak agriculture, and strong industry; it is a typical industrial city. Zhangye, Wuwei, and Jiuquan cities belong to the irrigation agriculture area, with good land conditions and well-developed farmland water conservancy projects, and a high rate of agricultural mechanization. The agricultural modernization development level of the southeastern and eastern regions of Gansu Province has grown relatively slowly. These two regions have fragile agricultural ecological conditions and significant disadvantages in developing modern agriculture. Dryland farming still dominates. From the data analysis, it can be seen that, in cities such as Tianshui and Pingliang, farmers use a large amount of chemical fertilizers and pesticides in the planting process, which has exacerbated soil pollution and posed a serious threat to the sustainable development of agriculture.

In conclusion, the development levels of agricultural modernization vary greatly among different regions, mainly due to the low initial level and slow growth rate of agriculture. Gansu Province has complex geographical features and significant differences in agricultural production conditions, which have exacerbated the situation of low and unbalanced agricultural modernization. Although there have been achievements in narrowing regional disparities, the problems of unbalanced and inadequate development among prefecture-level cities still exist widely. Therefore, it is necessary to continuously implement coordinated development strategies within the region to promote the comprehensive development of agricultural modernization in Gansu Province.

3.4. Analysis of Obstacle Factors for the Development of Agricultural Modernization in Gansu Province, China

This study employed the obstacle degree model to analyze the negative contribution of specific indicators to the level of agricultural modernization. The results show that, during this decade, the obstacle factors of the agricultural modernization subsystem in Gansu Province have undergone complex dynamic changes (Figure 7). In 2013, the obstacle degree assessment results of the criterion layer ranked as follows: modernization of agricultural production efficiency > modernization of agricultural science and technology innovation > modernization of agricultural social development > modernization of agricultural green development > modernization of agricultural industrial operation. Among them, the obstacle degree of modernization of agricultural production efficiency was as high as 37.946%, ranking first among all subsystems. The obstacle degrees of modernization of agricultural science and technology innovation and modernization of agricultural social development were comparable, ranking second and third, respectively. These data analysis results reveal the severe challenges faced by the agricultural modernization process in Gansu Province. Specifically, Gansu Province first faces the problems of a weak agricultural foundation and backward production methods, with traditional farming methods still dominant. At the same time, the low popularization rate and application level of modern agricultural science and technology have restricted the improvement of production efficiency. In addition, the lack of farmer skills training has hindered the further release of agricultural productivity, leading to a low-efficiency and low-value-added cycle in agricultural production. Such results make it difficult to increase the farmers’ income, which in turn affects society’s willingness and confidence in agricultural production investment, exacerbating the income gap between urban and rural areas (Figure 9).

Observing the evolution of the obstacle degree of the agricultural modernization criterion layer in Gansu Province from 2013 to 2022, the obstacle degrees of the three subsystems, namely, rural social development modernization, agricultural production benefit modernization, and agricultural science and technology innovation modernization, all showed a steady downward trend. This is mainly attributed to the wide application of agricultural science and technology, the innovation of agricultural production methods, and the support of agricultural policies. This result indicates that Gansu Province has achieved remarkable results in improving agricultural production efficiency and optimizing the agricultural industrial structure. At the same time, efforts to improve the farmers’ living conditions and promote rural social undertakings have not only enhanced the farmers’ quality of life and sense of happiness but provided a more solid social foundation for agricultural modernization. However, despite the overall positive trend of agricultural modernization in Gansu Province, the obstacle degree of the agricultural production and operation modernization subsystem has continued to rise, reaching 57.727% in 2022, becoming the biggest obstacle factor. This shows that, in 2022, Gansu Province’s agricultural development model still relied on the expansion of input volume, presenting a coarse type of feature, which has led to insufficient connotative development and restricted the improvement of efficiency and benefits. Therefore, the optimization and adjustment of industrial structure and the transformation and upgrading of agriculture have become extremely urgent. Additionally, as green agriculture has become an indispensable important component in the process of agricultural modernization, efforts should be intensified to promote the green development of agriculture to achieve sustainable development.

This paper further selects the four years of 2013, 2016, 2019, and 2022 to explore the specific obstacle factors of agricultural modernization in Gansu Province, China, as well as the degree of their obstacles and the changing patterns over time. During these four years, the degree of obstacles for specific indicators was calculated, and the top eight indicators with the highest degree of obstacles were ranked (

Table 5. Ranking of Major Obstacle Factors for Agricultural Modernization Development in 2013, 2016, 2019, and 2022.

Sort	2013		2016		2019		2022
	Obstacle Index	Obstacle Degree	Obstacle Index	Obstacle Degree	Obstacle Index	Obstacle Degree	Obstacle Index	Obstacle Degree
1	Comprehensive grain production capacity	10.469	Degree of agricultural large-scale production	13.616	Degree of agricultural large-scale production	20.3	Efficiency of agriculture, forestry, animal husbandry, and fishery services	21.686
2	Labor productivity	9.476	Comprehensive grain production capacity	10.709	Efficiency of agriculture, forestry, animal husbandry and fishery services	11.969	Degree of agricultural large-scale production	18.141
3	Electrification level	9.376	Labor productivity	7.98	Optimization of agricultural industrial structure	9.977	Ecological construction level	5.725
4	Land productivity	7.947	Agricultural electrification level	7.882	Labor productivity	7.395	Agricultural industry integration potential	14.944
5	Optimization of agricultural industrial structure	7.531	Optimization of agricultural industrial structure	7.238	Agricultural electrification level	6.933	Growth rate of agricultural output	7.673
6	Farmers’ income level	6.829	Growth rate of agricultural output	7.12	Agricultural mechanization level	6.806	Agricultural mechanization level	6.38
7	Urban–rural income ratio	6.351	Agricultural mechanization level	6.762	Disaster resistance and prevention capacity	5.516	Engel’s coefficient	5.776
8	Agricultural mechanization level	5.625	Land productivity	6.052	Agricultural industry integration potential	5.235	Education, culture, and entertainment consumption level	5.384

).

In 2013, during the process of agricultural modernization in Gansu Province, China, the comprehensive grain production capacity was the primary obstacle factor, with an obstacle degree of 10.469%. The total obstacle degree of the top four factors (comprehensive grain production capacity, labor productivity, electrification level, and land output rate) was 37.2685%, reflecting the problems of weak agricultural production infrastructure, low labor quality, and low land output efficiency at that time. Grain production increase and quality improvement faced dual challenges. In 2016, the degree of scale production became the largest obstacle factor, with an obstacle degree of 13.616%, followed by comprehensive grain production capacity (10.709%). The total obstacle degree of the top four factors rose to 40.187%. This change indicated that the improvement of grain production capacity and electrification level was slow, and the reduction in the average sown area per household highlighted the severity of rural labor force outflow. By 2019, the degree of scale production remained the largest obstacle, increasing to 20.3%, and the total obstacle degree of the top four factors reached 49.641%, further confirming the lag in the improvement of grain production capacity and electrification level, as well as the continuous impact of labor force outflow on agricultural production. In 2022, the efficiency of the agricultural, forestry, animal husbandry, and fishery service industry became the primary obstacle, with an obstacle degree as high as 21.686%, and the total obstacle degree of the top four factors soared to 70.496%. Among them, the obstacle degree of ecological construction level rose to third place, highlighting the resource and environmental pressure faced by agricultural production under the background of intensified resource constraints and enhanced environmental awareness. At the same time, the obstacle degree of the industrial integration potential indicator ranked fourth, reflecting the development bottlenecks of the secondary and tertiary industries in Gansu Province, China, and the limitations of industrial integration development. Overall, over the past decade, the obstacle factors for agricultural modernization in Gansu Province, China, have gradually shifted from diversified “surface” obstacles to a few key “point” obstacles.

4. Conclusions and Recommendations

4.1. Conclusions and Discussion

This study constructed an evaluation index system for agricultural modernization and employed multi-index comprehensive measurement methods and the Theil index, among others, to measure the development level of agricultural modernization in Gansu Province from 2013 to 2022. Meanwhile, it analyzed the spatio-temporal evolution characteristics and explored the obstacles affecting its development through the obstacle degree model. This study reached the following conclusions.

Firstly, from the perspective of the evolution characteristics of the time series, the level of agricultural modernization development in Gansu Province has achieved a significant improvement, although it is still in the development stage overall. Specifically, during the period from 2013 to 2022, the agricultural modernization index of Gansu Province showed an overall upward trend. From 2013 to 2018, the index grew slowly, but since 2019, the growth rate has accelerated. Except for the agricultural industry operation modernization subsystem, which showed a downward trend from 2013 to 2017, the other subsystems all presented a fluctuating upward trend, among which the modernization of agricultural production efficiency was particularly prominent.

Secondly, from the perspective of spatial distribution characteristics, the overall development level of agricultural modernization in Gansu Province has undergone a transformation from a low level to a medium–high level. During the period from 2019 to 2022, the provincial-level cities in Gansu began to show relatively significant spatial differentiation features. By 2022, the western and central regions were relatively higher, while the southern region was relatively lower. Specifically, the development status of each prefecture-level city in Gansu Province in 2022 was as follows: Zhangye City and Dingxi City performed relatively well, while Jiuquan City, Jinchang City, Wuwei City, Baiyin City, Qingyang City, and Longnan City were at a medium level. By contrast, Jiayuguan City, Lanzhou City, Pingliang City, Tianshui City, Linxia City, and Gannan Prefecture lagged behind relatively.

Thirdly, from the perspective of regional disparity trends, the overall disparity in the level of agricultural modernization development in Gansu Province has shown a downward trend. Specifically, during the period from 2013 to 2018, intra-regional disparities constituted the main part of the overall disparity in the level of agricultural modernization development in Gansu Province. Since 2018, the sources of disparity in the level of agricultural modernization development in Gansu Province have gradually shifted to a combination of inter-regional and intra-regional disparities.

Fourthly, the analysis of influencing factors shows that the degree of hindrance of the agricultural industrial operation modernization subsystem has been continuously expanding, reaching 57.727% by 2022, becoming the main obstacle subsystem. The degree of hindrance of agricultural green modernization follows closely, while the degrees of hindrance of the other three subsystems have all shown a continuous downward trend. Specifically, by 2022, factors such as the degree of scale production, the efficiency of the agricultural, forestry, animal husbandry, and fishery service industry, the level of ecological construction, and the potential for industrial integration have gradually become the main obstacles to the modernization of agriculture in Gansu Province.

4.2. Countermeasures and Suggestions

The research results show that all regions in Gansu Province have achieved rapid development in the process of agricultural modernization. However, the imbalance in development among prefecture-level cities still exists, and the degree of development obstacles in subsystems such as modernization of agricultural industry operation shows a continuous upward trend. Based on this, this paper puts forward the following countermeasures and suggestions.

Strengthen agricultural cooperation and exchanges among regions to achieve coordinated regional development. On the one hand, promote the balanced development of agricultural modernization in underdeveloped areas through the implementation of preferential policies, financial investment, and talent introduction. On the other hand, it is necessary to remove the obstacles to the flow of agricultural modernization factors among urban and rural areas. This can be achieved by optimizing the agricultural industrial structure, widely promoting modern agricultural technologies and improving agricultural infrastructure, so as to build an effective linkage mechanism and promote the optimal allocation and sharing of resources.

To enhance the operational efficiency of the agricultural industry and promote all-round development of agricultural modernization, the following measures should be taken: (1) Improve the industrial structure, promote large-scale and diversified operations, perfect the service system, strengthen technical training and market information services, and intensify information construction, using big data, the Internet of Things, and other technological means to improve management efficiency, so as to achieve a comprehensive improvement in the efficiency of the agricultural, forestry, animal husbandry, and fishery service industry. (2) Optimize relevant policies and regulations, and establish a complete land transfer market mechanism. Encourage extensive participation of farmers and enterprises, and protect their legitimate rights and interests, thereby deepening large-scale land operation. (3) Rely on local agricultural resources, rationally plan characteristic agricultural product bases, strengthen primary processing and extend to leading enterprises and cooperatives. Build a modern agricultural industrial system with agriculture as the foundation, deep processing of characteristic agricultural products as the focus, and supplemented by leisure agriculture, rural tourism, and other service industries.

To enhance the quality of ecological construction and to promote the green development of agriculture, it is necessary to address the issue of insufficient growth momentum in the modernization subsystem of green agriculture in Gansu Province. Emphasis should be placed on ecological balance and efficient resource utilization. By promoting ecological agricultural technologies, optimizing the agricultural industrial structure, strengthening the resourceful utilization of agricultural waste, and improving the regulatory system for the agricultural and ecological environment, we can drive the coordinated progress of agricultural production and environmental protection, and achieve sustainable agricultural development.

4.3. Research Expectations

Based on a systematic assessment of the development level of agricultural modernization in the various cities and prefectures of Gansu Province, China, this study constructed an index system for measuring the development level of agricultural modernization and conducted an in-depth analysis of the spatio-temporal evolution characteristics of agricultural modernization. However, due to the limitations of the researchers’ academic capabilities and the availability of data, there are still the following aspects that need further improvement in this study.

Firstly, there are certain limitations in the selection of research samples. Due to the large time span of the research period and the absence of some key indicator data, only core evaluation indicators could be selected during the construction of the indicator system. Meanwhile, this study mainly focuses on the analysis of the current agricultural development situation of municipal administrative units, lacking refined research at the county level. This may lead to a deficiency in the systematicness and comprehensiveness of the agricultural modernization evaluation system.

Secondly, the analysis of influencing factors needs to be further deepened. Although this study has conducted a comprehensive evaluation of the level of agricultural modernization in Gansu Province, China, from five dimensions, including technological innovation, output efficiency, production and operation, green development, and rural social development, and identified the main obstacles, the development of agriculture, rural areas, and farmers itself has systematic characteristics, and there are still other potential influencing factors that have not been taken into account. Subsequent research should further expand the dimensions of discussion on relevant influencing factors in the “three rural” field to enrich the theoretical system of agricultural modernization research.