Research Articles

Spatio-temporal variation and the driving forces of tea production in China over the last 30 years

  • XIAO Zhi , 1, 2, * ,
  • HUANG Xianjin , 1 ,
  • ZANG Zheng 1, * ,
  • YANG Hong , 1, 3
  • 1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
  • 2. Kaili University, Kaili 556011, Guizhou, China
  • 3. Department of Geography and Environmental Science, University of Reading, Reading RG6 6AB, UK

Author: Xiao Zhi (1974-), PhD Candidate and Associate Professor, specialized in resources geography and land use change. E-mail:

*Corresponding author: Huang Xianjin (1968-), Professor, specialized in land use change. E-mail: or Yang Hong (1978-), lecturer, specialized in environmental science. E-mail:

Received date: 2017-03-28

  Accepted date: 2017-07-05

  Online published: 2018-03-10

Supported by

National Natural Science Foundation of China, No.41571162

National Social Science Foundation of China, No.17ZDA061


Journal of Geographical Sciences, All Rights Reserved


As a daily necessity and an important cash crop in China and many other countries, tea has received increasing attention. Using production concentration index model and industry’ s barycenter theory, we analyzed the spatio-temporal distribution of tea production and barycenter movement trajectory of tea plantations and production in China between 1986 and 2015. Driving forces of the movement were also analyzed. From 1986 to 2000, tea production in China’s Mainland of grew slowly (by 210×103 t). The continuous increase in tea yield per unit area was the primary contributor (more than 60%) to the growth in tea production during this period. Since China joined the World Trade Organization (WTO) in 2001, tea production has grown rapidly, by 1.59×106 t between 2001 and 2015. The increase in the tea plantations area is the main contributor. Over the last 30 years, the barycenters of tea production in China have moved westward from the Dongting Lake Plain to the eastern fringe of the Yunnan-Guizhou Plateau. Guizhou, Guangxi, and Sichuan in southwestern China have gradually become regions of new concentrated tea plantations and main tea production provinces. Lower cost of land and labor in southwestern China are the main drivers of the westward movement of China’s tea industry. In addition, supportive policies and the favorable natural geographical environment contribute to the westward movement of tea industry. Our research highlights the spatio-temporal variation of China’s tea production in the last three decades. The result indicates importance to make appropriate policies to promote the development of tea industry in China.

Cite this article

XIAO Zhi , HUANG Xianjin , ZANG Zheng , YANG Hong . Spatio-temporal variation and the driving forces of tea production in China over the last 30 years[J]. Journal of Geographical Sciences, 2018 , 28(3) : 275 -290 . DOI: 10.1007/s11442-018-1472-2

1 Introduction

Tea is a daily necessity in China, the UK and many other countries. Tea is also an important cash crop for many farmers in the world. In some sense, tea is one of China’s labels on the world stage. Tea has been planted and drunk in China for more than one thousand years. Since the reform and opening up policy in the late 1970s, China’s tea production has increasingly relied on policy and new technology. As the largest tea producer, China contri- buted 2.278 million tons tea in 2015, accounting for 42.94% of world production (Table 1). The tea industry has already become an important supporting industry in some tea-production regions in China (Zhang, 2012). Tea export and income from foreign countries have promoted the economic development (Su, 2011). In addition, the tea industry plays a pivotal role in upgrading agricultural structure, increasing farmers’ income, and constructing sustainable rural areas (He, 2011; Wei and Li, 2014).
Table 1 World tea production from major producers (thousand tons)
Region 1985 1990 1995 2000 2005 2010 2015
World 2290 2531 2521 2940 3537 4281 5305
China’s Mainland 432 540 588 683 935 1475 2278
India 656 720 756 847 946 966 1,209
Kenya 147 197 245 236 323 399 399
Sri Lanka 215 234 246 307 317 331 329
Turkey 137 127 103 170 222 231 259
Vietnam 31 40 40 59 133 175 170
Indonesia 132 145 144 163 156 151 129

Source: International Tea Committee (ITC), Annual Bulletin of Statistics, 1993, 2001, 2007, 2016.

Researchers have studied world tea industry mainly from the perspective of industrial economics (Ganewatta et al., 2005; Gesimba et al., 2005) and management science (Blowfield, 2003; Hazarika and Subramanian, 1999; Loconto, 2014) to promote its development. In particular, China’s tea production received wide attention. Some important and interesting conclusions have been reached. For example, (1) a tea farmer’s years of education, the size of his/her family labor force, and the location of his/her village, along with the government’s function had an insignificant impact on tea farmers’ investment intentions (Su, 2010); (2) innovations of technology and management played a significant role in promoting the development of China’s tea industry (Niu et al., 2007); and (3) the promulgation of regulations for pesticide residues had a significant negative impact on the tea trade (Chen, 2011). These conclusions were drawn primarily based on the theories of industrial economics and management without, in most cases, considering the geographical location and spatial factors.
Since joining the World Trade Organization (WTO) in 2001, China has taken more measures to adjust the structure of the agricultural and forestry industry and to optimize the urban/rural land use. In the meantime, China’s tea industry has faced a series of new challenges and opportunities, resulting in changes in China’s tea production and trade. Under the circumstance, analyses of the spatio-temporal pattern of tea industry in China and its driving forces are of theoretical value and practical significance. However, most previous studies focus on tea production in the regional perspective, without consideration of the geographical location factor which also affects the development of the tea industry. In particular, due to the data limitations, it is still unclear about the spatio-temporal pattern of the tea production pattern and its driving factors in China.
Spatial analysis is a branch of geography research (Li et al., 2017; Yao et al., 2013). Researchers have explored the sequential variation process, geographical aggregation characteristics, and influencing factors of crops, including grain (Jin, 2014; Liu et al., 2013), corn (Tan et al., 2014; Yang et al., 2016), vegetables (Ji et al., 2016), soybeans (Zhang et al., 2014), and sugar (Gao et al., 2016). However, to the best of our knowledge, the understanding of the spatial pattern of China’s tea production is still very limited. Using the production concentration index model and the industry’s barycenter theory, the current study attempts to investigate the spatio-temporal evolutionary trend of tea production in China before and after China joined the WTO. In addition, we explored the driving forces of the evolution of tea production in China. Our results provide a valuable reference for optimizing the distribution of tea production in China.

2 Data and methods

2.1 Data sources

The research period of this paper is from 1986 to 2015. The data were obtained from the Tea Database, Ministry of Agriculture, the People’s Republic of China (http://202.127.42. 157/moazzys/chaye_cx.aspx) and China Statistical Yearbook from 1986 to 2016 ( The map data were obtained from the National Geomatics Center of China (NGCC, The research areas are focused on 18 tea-producing regions in China’s Mainland (hereinafter China for convenience), while the relevant information for Taiwan is excluded from this study due to the data limitation. According to the Economic Regionalization Scheme of the National Bureau of Statistics of China, tea production regions in China are classified into eastern, central and southwestern areas (Figure 1). Because tea is planted only in part areas of Gansu, Shaanxi, Henan, and Shandong, the geometric centers of the tea-producing region in these four provinces are considered as their barycenters. For the remaining provinces, the geometric centers of the administrative region of each province are considered as their barycenters. Considering the change in the administrative relationship between Chongqing and Sichuan, 17 tea-producing provinces, cities and autono- mous regions are analyzed as the spatial units for the period before 1997, and (103.46˚E, 30.53˚N) (X, Y) are set as the barycenter coordinates of Sichuan before 1997. In 1997, Chongqing became a direct-controlled municipality. Therefore, (102.73˚E, 30.61˚N) are set as the barycenter coordinates of Sichuan after 1997.
Figure 1 Tea production areas in China

2.2 Research methods

2.2.1 Measuring tea production rates
Based on the crop yield decomposition method proposed by Zhu et al. (1997), the increase in tea production can be decomposed into three terms: the increment product in the tea plantation area and the past tea yield, the increment product in tea yield and the past area, and the increment product in the tea plantation area and the increment in tea yield. Given this decomposition, the rates of contribution (percentage) of the increment in the tea plantation area and the increment in tea yield to the increase in tea production quantity were calculated as follows (Zhu et al., 1997):
dA=(A2-A1)*1/2*(Y2-Y1)/P*100 (1)
dY=(Y2-Y1)*1/2*(A2+A1)/P*100 (2)
where dA and dY represent the rates of contribution of the increment in the tea plantation area and the increment in tea yield to tea production quantity, respectively; P represents the difference in tea production quantity between the comparison year and the base year; A1 and Y1 represent the tea production area and the tea yield in the base year; and A2 and Y2 represent the tea production area and the tea yield in the comparison year.
2.2.2 Production concentration index (PCI)
The PCI refers to the proportion of tea production in a region (the area of tea plantations in the region) in terms of the total tea production of the entire country (the total area of tea plantations in the country) during a given period. The PCI is commonly used to estimate the spatial concentration of an industry and is calculated using the following equation (Song and Zhang, 2005):
${{C}_{it}}={{{M}_{it}}}/{\sum\limits_{i=1}^{n}{{{M}_{it}}}}\;$ (3)
where Cit represents the PCI of the tea production quantity (the area of tea plantations) in province (city or autonomous region) i in China during period t; Mit represents the tea production quantity (the area of tea plantations) in province (city or autonomous region) i during period t; and n represents the total number of tea-producing provinces in China. The contribution of the tea production quantity (the area of tea plantation) in a region at a certain time to the tea production quantity (the area of tea plantation) of the entire country can be determined by calculating the PCI. In addition, the time series change in the PCI can reflect the change in the standing of a region in the entire country in terms of tea production. Therefore, the PCI can be used to horizontally and longitudinally analyze the variation in the regional pattern of tea production in China.
2.2.3 Industry’s barycenter theory
The barycenter of an industry is the barycenter of the spatial distribution of this industry in the region (Amos, 1988). Due to the different economic development rates inside the region, the barycenter of the industrial development changes constantly (Li et al., 2012). Therefore, the analysis of the location and the movement path of the barycenter of an industry is the research focus of the spatial distribution of the industry (Bai, 2015).
(1) Location of the barycenter
The location of the barycenter was calculated as follows (Zhang and Gu, 2002):
$X=\sum\limits_{i=1}^{n}{{{M}_{i}}}{{{X}_{i}}}/{\sum\limits_{i=1}^{n}{{{M}_{i}},\ }}\;Y=\sum\limits_{i=1}^{n}{{{M}_{i}}}{{{Y}_{i}}}/{\sum\limits_{i=1}^{n}{{{M}_{i}}}}\;$ (4)
where X and Y represent the geometric spatial center (barycenter) of the certain attribute of the tea industry in the region; Xi and Yi represent the coordinates of the geographical center of sub- region i; n represents the total number of administrative sub-regions; and Mi represents the numerical value of a certain attribute (e.g., crop area, crop yield) of the tea industry in sub-region i.
(2) Movement distance of the barycenter
The inter-annual spatial distance of the barycenter movement was calculated using the following equation (Sun and Zhang, 2012):
${{D}_{i-j}}=R*\sqrt{{{({{X}_{t}}-{{X}_{j}})}^{2}}+{{({{Y}_{i}}-{{Y}_{j}})}^{2}}}(i>j)$ (5)
where Di-j represents the distance over which the barycenter moves between the jth year and the ith year (km); (Xi, Yi) and (Xj, Yj) represent the geographical coordinates of the barycenter in the jth year and the ith year; and R represents the transformation coefficient of the coordinates of latitude and longitude on the earth spherical surface into a planar distance and R is111.13 in the current study.
2.2.4 Partial least squares model (PLS)
The PLS model is a new and improved method of multivariate statistical analysis based on the ordinary least squares model; and it can be employed to effectively decompose and screen system information (Nitzl, 2016). Therefore, the PLS model is suitable for the regression modeling of multiple independent variables into dependent variables and demonstrates a higher reliability when there is multi-collinearity among the variables.
In the current study, the PLS model was employed to analyze the factors affecting the spatio-temporal pattern of China’s tea industry. Tea production is a process affected by both natural and social-economic factors. The primary factors affecting the tea industry mainly include natural resource endowments, industrial policies, production technologies, labor costs, and land costs (Jiang et al., 2009; Li, 2010; Li et al., 2014; Zhang et al., 2006). In the analyses, the dependent variables include the proportion of the tea plantation area in each main tea-producing region in terms of the total tea plantations area in China (Y1) and the proportion of the tea yield in each tea-producing region in terms of the average tea yield in China (Y2) during the research period. Referring previous researches (Li, 2010; Li et al., 2014; Jiang et al., 2009; Wan, 2016; Zhang et al., 2006), the following variables were selected as independent variables: the proportion of tea plantation area in terms of the total plantation area (X1), the proportion of expenditures on the agricultural and forestry industry in terms of the general public budget revenue (X2), the proportion of turnover on the technical market in terms of gross domestic product (GDP) (X3), the ratio of the per capita income of rural residents to per capita income of urban residents (X4), and the proportion of the land value-added tax revenue in terms of the total value-added tax revenue(X5). The analyses were conducted using the software SIMCA-P11.5 (Umetrics, Umeȧ, Sweden) (Nitzl, 2016; Zang et al., 2017).

3 Results

3.1 Trend analysis and contribution analysis

In this study, trends of total tea plantation, production, and yield over the last 30 years were analyzed. In addition, the contribution factors of tea plantation area and tea yield to total tea production in China were explored.
3.1.1 Trend analysis
Overall, the tea plantation area in China increased from 1986 to 2015 (Figure 2). The expansion of tea plantations can be approximately divided into two periods by the year 2001: the slow growth period (1986-2001) and the rapid growth period (2001-2015). During the first period, the tea plantation area in China increased by only 70 thousand ha and even decreased slightly in several years. After 2001, tea plantation area grew rapidly, at an average annual rate of 7.11%.
Figure 2 Tea plantation area (thousands ha), total tea production (thousands tons), and tea yield (kg/ha) in China between 1986 and 2015
Tea yield fluctuated over the last 30 years, reaching a minimum (452 kg/ha) and a maximum (794 kg/ha) in 1986 and 2015, respectively. Although China’s tea yield has exhibited an increasing trend, it remains considerably less than the world average yield. For example, according to International Tea Committee’s Annual Bulletin of Statistics 2016, the tea yield in China was only 67.11% of the world average tea yield (3-year average) between 2013 and 2015.
With the combined effects of the two factors noted above, total tea production in China exhibited a continuously increasing trend in the last three decades. Before 2001, tea production increased slowly from 470 thousand tons in 1986 to 680 thousand tons in 2000, a mere increase of 210 thousand tons. From 2001, total tea production has grown increasingly. Notably, after the tea export quota was abolished in 2006 (Li and Liu, 2011), total tea production increased at an average annual rate of 9.24%. In 2015, total tea production in China reached 2278 thousand tons. Total tea production in China increased 1590 thousand tons between 2001 and 2015, 7.6 times of the increase between 1986 and 2000.
3.1.2 Contribution analysis
The contributions of the change in the tea plantation area and tea yield to total tea production in China were calculated using Equations (1) and (2) and results are shown in Figure 3.
Figure 3 Contribution of the increase in the tea plantation area and the tea yield to the increase in total tea production in China from 1986 to 2015 (the year 1986 is the base year)
The increase in total tea production is mainly attributed to the increased tea yield and its contribution was higher than 60% before 2001. The contribution of the increase in the tea yield peaked (98.27%) in 1998. Over the same period, the contribution of the increase in the tea plantation area to total tea production was relatively lower, less than 40%. From 2001, total tea production increased rapidly, while the contribution of the increase in tea yield decreased markedly. During this period, the tea plantation area in China increased rapidly, and the contribution of the increase in plantation area to the increase in total tea production also increased rapidly, surpassing the contribution of the increase in tea yield in 2008. During the “12th Five-Year Plan” (2011-2015), the contribution of the increase in tea plantation area to the increase in total tea production remained greater than 60%.

3.2 Spatial analysis

To further investigate the spatial pattern of tea production in China, 1990, 1995, 2000, 2005, 2010, and 2015 were selected as representative years. Based on the PCI of each tea-producing region (Figures 4 and 5) and the trajectory of the barycenter movement of tea production (Figure 6), the change of the spatial distribution of China’s tea production was analyzed.
3.2.1 The change of spatial distribution
Tea plantation area is one of the main factors affecting the total tea production. The change in the distribution of tea plantations reflects the spatial movement of China’s tea industry.
The PCI of tea plantations in eastern China decreased, whereas the PCI of tea plantations in southwestern China increased (Figure 4). Specifically, the PCI of tea plantations in the coastal regions of eastern China, such as Shandong, Jiangsu, and Hainan, stabilized in the range of 0-2 during all periods. In comparison, tea plantation area in the traditional tea-producing regions, such as Zhejiang and Fujian, increased slightly, and the PCI of tea plantations in these regions decreased gradually from over 12 (1990) to below 10 (2010). The PCI of tea plantation area in Hunan, Anhui, and Jiangxi (in central China) decreased. In comparison, the tea industry was developed vigorously in Guizhou and Sichuan (in southwestern China) and in Hubei and Henan (in central China). The tea plantation area in these regions increased markedly, and these regions gradually became the new areas of concentrated tea plantation.
Figure 4 Spatial variation in the production concentration index (PCI) of tea plantation area in provinces in China in 1990 (a), 1995 (b), 2000 (c), 2005 (d), 2010 (e), and 2015 (f)
Figure 5 shows that the spatial pattern of the total tea production in provinces changed significantly. The proportion of tea production in Fujian (in eastern China), Hubei (in central China), and Yunnan and Guizhou (in southwestern China) in terms of China’s total tea production increased markedly, by 7.18%, 3.71%, 8.58%, and 7.20%, respectively. The proportion of tea production in Henan (in central China) and Shaanxi (in western China) in terms of China’s tea production also increased obviously, by 2.06% and 2.59%, respectively. However, the proportion of the tea production in Zhejiang (in eastern China) and Hunan and Anhui (in central China) in terms of China’s total tea production decreased considerably, by 14.69%, 8.14%, and 5.12%, respectively. The proportion of tea production in Jiangsu, Jiangxi, Guangdong, and Hainan in terms of China’s tea production also decreased to varying extents. Notably, in spite of the decreased proportion of the tea production in terms of China’s total tea production, Zhejiang and Hunan ranked the 6th and 7th in terms of tea production in 2015. Overall, the standing of the traditional tea-producing regions in central and eastern China, such as Hunan, Anhui, Zhejiang, and Guangdong, gradually declined. The standing of Guizhou (in southwestern China) and Hubei (in central China) continuously increased and these two provinces, together with such traditional tea-producing regions as Fujian, Sichuan, and Yunnan, gradually became the main tea-producing regions in China.
Figure 5 Spatial variation in the production concentration index (PCI) of the total tea production in provinces in China in 1990 (a), 1995 (b), 2000 (c), 2005 (d), 2010 (e) and 2015 (f)
3.2.2 Change of barycenter
The barycenters of the tea plantation areas and total tea production in China remained on the east of the base point of the regional barycenter (Jishou City), while they moved from the Dongting Lake Plain (east of 112°46′E) to the Yunnan-Guizhou Plateau (west of 110°15′E). By 2015, they had moved westward to the Xiangxi Autonomous Prefecture and Huaihua City near the edge of the Yunnan-Guizhou Plateau (Figure 6).
Figure 6 The movement of the barycenters of the tea plantation area and total tea production in China from 1986 to 2015
From 1986 to 1990, the barycenter of the tea plantation area shifted 75 km to the southwest. During the periods of 1991-2000, 2001-2010 and 2010-2015, the barycenter of the tea plantation area shifted to the northwest, with the distance of 33 km, 168 km, and 25 km, respectively. Overall, from 1986 to 2015, the barycenters of the tea plantation shifted 291 km to northwest from Ningxiang County to Guzhang County, Hunan Province. It moved 36 km vertically (to the north) and 278 km horizontally (to the west).
In 1986, the barycenter of total tea production was located in the north of Changsha city, Hunan Province. From 1986 to 1990, it shifted 16 km to the southeast; from 1991 to 1995, it shifted 57 km to the southwest; from 1996 to 2000, it shifted 10 km to the northeast; and from 2011 to 2015, it shifted 120 km to the southwest (Table 2). Overall, from 1986 to 2015, the barycenter of tea production shifted 272 km to the southwest, moving 29 km vertically (south) and 290 km horizontally (west).
Table 2 Changes in the barycenters of the tea plantation area and total tea production in China from 1986 to 2015
Stage Year Period Shift of tea plantation
Shift of total tea production
Distance (km) Speed (km yr-1) Distance (km) Speed (km yr-1)
Before 2001 1986-1990 7th Five-Year 75 15 16 3
1991-1995 8th Five-Year 13 3 57 11
1996-2000 9th Five-Year 20 4 10 2
After 2001 2001-2005 10th Five-Year 78 16 46 9
2006-2010 11th Five-Year 90 18 82 16
2011-2015 12th Five-Year 25 5 120 24
In terms of the movement rate, the barycenter of the tea plantation area moved westward at an average rate of 9.69 km yr-1, higher than that of the barycenter of tea production of .06 km yr-1. In four periods (the 7th Five-Year, 9th Five-Year, 10th Five-Year, and 11th Five-Year), the annual movement rate of the barycenter of tea plantation area was rapid. In general, over the 7th Five-Year and 9th Five-Year plan periods, the barycenter of total tea production moved slightly east, indicating that the regional fluctuation of tea production was much greater than that of the tea plantation area and that the tea plantation area and its movement became more stable.

3.3 Driving factor analysis

3.3.1 Regression analyses
Regression analyses were individually performed based on the tea plantations area and tea yield per unit area in the eastern, central and southwestern China. The results are shown in Table 3 and Figure 7.
Table 3 Regression coefficient of the PLS model for the tea producing regions in eastern, central, and southwestern China
Variable Tea plantation area Tea yield
Eastern Central Southwestern Eastern Central Southwestern
X1 0.0602 -0.2739 0.2141 0.2481 -0.2946 0.1843
X2 0.2832 0.2646 0.2609 0.3553 0.2841 0.2298
X3 0.2092 0.1222 0.1935 -0.006 0.0875 0.2324
X4 0.4291 0.2386 0.2401 0.2048 0.2128 0.2701
X5 0.5053 0.3352 0.3096 0.4223 0.3325 0.3011
Figure 7 Variable importance projection (VIP) of five independent variables (X1-X5) of the PLS model in eastern, central, and southwestern China
Table 3 shows the driving (positive regression coefficient) and restricting (negative regression coefficient) effects of the independent variables X1-X5 on the change in tea plantation area in different regions in China. Overall, the independent factors X1-X5 are positively correlated with the tea plantation area and the tea yield, indicating that a favorable natural environment, industry-supporting policies, the application of new technologies, and labor/land costs all promote the development of the tea industry in China.
Figure 7 demonstrates the values of the variable importance projection (VIP) in the PLS model. VIP characterizes the explanatory power of an independent variable for the depen- dent variable. An independent variable with a VIP value greater than 1 is often considered as the dominant factor causing changes of the dependent variable (Zang et al., 2017). As demonstrated in Figure 7, all the factors except for X3 have relatively high explanatory power for the increases in the scale of tea plantations and tea yield per unit area.
3.3.2 Factor analysis
(1) Land and labor costs
In terms of the importance of the five factors, regardless of the increase in the tea plantation area (Figures 7a-7c) and tea yield (Figures 7d-7f), X5, which represents land costs, exerts the most significant impact (VIP>1) on the development of the tea industry in eastern, central, and southwestern China.
In addition, X4, which represents labor costs, is positively correlated with the scale of tea plantations (eastern China) and the tea yield per unit area (southwestern China) (Figures 7a and 7f), indicating that X4 is an important driver of the tea industrial development in some areas (VIP>1).
(2) Industry-supporting policies
As demonstrated in Figures 7c and 7d, X2, the supporting policies, has a substantial driving action on the expansion of the scale of tea plantations (southwestern China) and the increase in the tea yield per unit area (eastern China) (VIP>1).
(3) Natural environment
The proportion of the area for tea plantations (X1) represents the natural conditions suitable for developing the tea industry. As demonstrated in Figures 7b and 7e, X1 has relatively high explanatory power for the expansion of the scale of tea plantations and the increase in the tea yield per unit area in central China (VIP>1). Therefore, X1 has an important driving action in the central area.

4 Discussion

Tea industry is important in many countries, especially in China. Tea industry is closely related to many industries (He, 2011; Zhang, 2012) and is a powerful driver for economic development in the country (Wei and Li 2014). In this study, we analyzed the spatio-temporal pattern of China’s tea industry and explored the factors affecting the changes.

4.1 Costs of land and labor resources

Our results showed a clear westward movement of China’s tea industry. The westward movement of the barycenter of the distribution of tea production in China is favorable to the construction of an ecological civilization in the ecologically vulnerable and environmentally sensitive areas in southwestern China (Hu and Yang, 2016).
Tea production is a labor-intensive industry (Wang and Zhai, 1993). A tremendous amount of labor resource is required, from the planting of tea trees to the management of tea plantations to the picking, processing, and selling of tea leaves. Because of its relatively abundant and low-cost labor resources in southwest China, the costs of tea cultivation and processing in southwestern China are relatively smaller compared to economically developed eastern China (Li, 2010).
Tea plantation area determines the supply scale of tea production. The increase in the tea plantation area requires the input of more land resource. There are a large proportion of hills and mountains in southwestern China. Consequently, the land costs for tea plantations in southwestern China are much lower, reducing the tea production cost and providing favorable conditions to compete in tea production on the domestic and international markets.
The westward movement of the tea industry from eastern China can benefit from the relatively lower land and labor costs in southwestern China (Li, 2010), promoting the sustainable ecological development and environmental protection (Yang, 2014). Amid the westward movement of the tea industry, decision-makers in southwestern China should formulate reasonable plans for further developing the tea industry and transforming southwestern China to one of China’s main tea-producing regions, characterized by large-scale, mechanized, and standardized development (Liu et al., 2014; Yang et al., 2013a). Effective measures are also needed to minimize the impact of tea industry on precious water and soil resource in Southwest China (Yang et al., 2013b; Yang, 2016).

4.2 Supporting industrial policy

Industrial policy is one of the important means to actively intervene the economic development (Liu, 2014). The agricultural structure adjustment strategy and the national subsidy policy for the tea industry vary among regions and consequently have an important impact on the change in the regional pattern of tea production.
Since China joined the WTO in 2001, the area of tea plantations in China has entered a rapid growth period (increasing at an annual rate of 7.11%). The increase in the trade demand is the external cause of the increase in the area of tea plantations. In addition, the central government also attaches great importance to the development of the tea industry and provides strong support for the development of the tea industry through favorable industrial policies. These are the internal driving forces for the increase in the area of tea plantations. For example, Anhui introduced the Planning for the Development of the Tea Industry in Anhui (2003-2007) in 2003. Subsequently, the Ministry of Agriculture of China published the Planning for the Development of Key Tea-Producing Regions in China (2009-2015) in 2009. The central government has been gradually increasing the intensity of investment of special funds for the tea industry. Local governments have also prioritized tea production, processing, and logistics projects in the area of land use. The aforementioned actions, together with the implementation of various preferential tax policies, have resulted in the construction of a number of new standardized, large-scale tea plantation bases in various regions and promoted the rapid increase in the tea plantation area and the adjustment/upgrading of the tea industrial structure.

4.3 Natural environment

Tea quality varies with the natural geographical environment where it grows. China’s tea-producing regions are mostly located in the subtropical monsoon climate zone with hot, wet, and rainy summers. In addition, China also covers a vast area with various terrains. As a result, numerous microclimatic environments suitable for the growth of tea trees are formed (Wang and Zhai, 1993).
The natural environment in southwestern China has promoted the western movement of China’s tea industry. For example, Sichuan is located in the Sichuan Basin, which has abundant precipitation, plentiful clouds, low sunshine conditions, and high relative humidity. Therefore, Sichuan has favorable natural conditions for developing its tea industry. Relying on its low-latitude, high-altitude, low-sunshine, and cloudy geographical environment, Guizhou has become a main green-tea-producing region in China (Hu and Yang, 2016). The aforementioned conditions lay a good foundation for the westward movement of the tea industry in China. In comparison, the proportion of the area of tea plantations in Shandong, Guangdong, and Hainan (in eastern China) and in Hubei and Hunan (in central China) is relatively low, limiting the increase in the area of tea plantations.

4.4 International trade and domestic consumption

China was once world’s largest tea exporter. The gap in tea exports is narrowing between China and some member states of the Commonwealth of Nations, such as Sri Lanka and India. According to data of China’s tea imports and exports since 2001 and statistics published by relevant agencies (e.g., Department of Foreign Trade, Ministry of Commerce of China, 2015), China’s tea exports increased from 255,000 t in 2001 to 329,000 t in 2015, with an annual average growth rate of only 0.47%. Therefore, foreign demand has made little contribution to the development of China’s tea industry. Worse, global economic crisis, for example financial crises in 2008, can exacerbate the negative effect of international trade and China’s export, including tea (Lu et al., 2015; Wu et al., 2015).
According to data provided by China Tea Marketing Association, China’s domestic tea consumption increased from 206,000 t in 2001 to 2,050,000 t in 2005. Due to lack of detailed statistical data, domestic demand was excluded as an influencing factor in our analysis. However, with an average annual growth rate of 12.29%, the driving action of domestic demand on the expansion of the tea plantations area and the increase in tea yield per unit area cannot be overlooked. It seems that domestic demand makes a more important contribution to the development of China’s tea industry than foreign trade.

4.5 Innovations of technology and management

The application of new technologies can increase both tea yield and tea plantation area, which has been manifested in eastern, central, and southwestern China. Since 2000, total tea production in China has entered a period of rapid growth, at an average annual rate of 10%, mainly due to the rapid increase in the proportion of the tea plantation area in the newly established tea-producing regions where improved varieties of clonal tea were planted (Xiao et al., 2017). For example, the area proportion of clonal tea trees in Zhejiang reached 70.80% in 2013 (Liang and Shi, 2015).
In addition, new technologies can promote the updating of the tea plantation management. For example, in 2005, the Ministry of Agriculture of China introduced a series of supporting policies for establishing standardized tea plantations, requiring each main tea-producing region to construct and manage new tea plantations that meet the “ecologicalization, improved variety, normalization, and standardization” requirements; certify pollution-free, organic tea production bases. A series of standardized production technologies were increasingly used, for example, the formulated fertilization based on soil testing, disease and pest prevention and control, and the mechanized picking of tea leaves (Han et al., 2016). These policies and measures have promoted obviously the increases in the tea yield and total tea production.

4.6 Limitation and future research

Same as many studies, several uncertainties remain in the current studies. Due to data limitation, our analysis was performed based on provincial level. Because of relatively low spatial resolution, some results may be insufficiently accurate. Similarly, because of insufficient data, only five aforementioned independent variables were used in this study to investigate the factors that drive the spatial evolution of tea production in China. The representativeness of these indices may be limited to some extent. For example, factors such as foreign trade, domestic demand and the popularization and application of new technologies can also to a certain extent affect the development of the tea industry. Tea was an important trade product on the ancient Silk Road. With the comprehensive integration and rapid development of a global economy and culture, particularly in the background of “the Belt and Road Initiatives” developed by China’s government, the global tea industry will face new opportunities and challenges. The dominant factor affecting the development of tea industry may vary among regions in next decades. Therefore, future research with more accurate data will clearly increase the understanding of the development of China’s tea industry.

5 Conclusions

Based on models for measuring production rate, the PCI and barycenter, this study analyzed the regional distribution pattern and the path of the barycenter movement of China’s tea plantation area and tea production between 1986 and 2015. The driving forces of the movement of the tea industry were also analyzed. The following conclusions are obtained:
(1) The change of the tea plantations area and tea production in China can be divided into two stages by the year 2001, when China joined the WTO. In the first stage, a slow growth stage between 1986 and 2001, the increase in tea yield per unit area was the primary contributor to the growth in China’s total tea production (210×103 t). In the second stage, a rapid growth stage between 2001 and 2015, growth in total tea production (1.59×106 t) resulted primarily from an increase in the area of tea plantations. In particular, after 2011, the increase in the tea plantation area contributed steadily to more than 60% of total tea production.
(2) Over the last 30 years, there has been a clear spatial change of China’s tea industry. The standings of Hunan and Anhui (in central China), as well as the traditional tea-producing regions in the eastern coastal regions of China (e.g., Zhejiang and Guangdong), have slowly declined. The tea industry has gradually moved to the southwest with advantageous natural endowments. Guizhou, Yunnan, and Sichuan, as well as Hubei, have gradually become China’s main tea-producing provinces.
(3) During the last three decades, the barycenters of tea production in China have moved westward from the Dongting Lake Plain (east of 112°46′E) to the eastern fringe of the Yunnan-Guizhou Plateau (west of 110°15′E). The barycenter of the tea plantation area has moved roughly from “east-south” to “west-north”. The barycenter of tea production has moved roughly from “east-north” to “west-south”. In terms of the movement rate, the barycenter of the tea plantation area moved faster than the barycenter of tea production.
(4) The relatively low costs of land and labor in southwestern China lay a good foundation for the westward movement of the tea industry. In addition, the industry-supporting policies implemented by the central and local governments also ensure processes of industrial standardization, normalization and base construction. The favorable natural endowments in southwestern China have objectively encouraged China’s tea industry to gradually move southwestward.

The authors have declared that no competing interests exist.

Amos O M, 1988. Unbalanced regional growth and regional income inequality in the latter stages of development.Regional Science and Urban Economics, 18(4): 549-566.This paper empirically examines the pattern of regional income inequality displayed in advanced stages of economic development, building from the convergent phase of the inverted-U hypothesis, originally developed by Kuznets for personal income inequality, but adapted by Williamson for regional income inequality. It is hypothesized that once the inverted-U pattern is completed, regional income inequality increases, rather than remaining stable. Four analyses of intrastate per capital income inequality among countries are undertaken to test the hypothesis that regional inequality increases. Results indicate strong support for the hypothesis that regional income inequality increases in the latter stages of development.


Bai Xue, 2015. The spatial evolution of China’s economic center of gravity and the decomposition of industrial center of gravity.Inquiry into Economic Issues, (6): 18-24. (in Chinese)

Blowfield M, 2003. Ethical supply chains in the cocoa, coffee and tea industries. Greener Management International, 43(43): 14-24(11).Ethical trade is an increasingly popular approach that allows companies to manage the social and environmental dimensions of their supply chains. Yet is it able to benefit poor producers and workers in developing economies, particularly those who outside of industrial production systems?This paper examines how ethical trade is being applied to smallholder tea, coffee and cocoa growers in Asia, Africa and South America. It shows that many of the primary concerns among growers are not included in ethical trade standards. It argues that, although civil-society organisations have influenced the direction and scope of such standards (e.g. through partnerships with companies), the cultural and ideational dimensions to ethical trade impose limits on what can be modified and improved. Furthermore, the standards overlook critical aspects of business practice and their consequences for growers.The consequences of this are not only potentially detrimental for ethical trades intended beneficiaries but also for this systems corporate supporters. No matter what the business case may be for ethical trade, ultimately its success depends on accurately identifying and addressing the well-being of those in developing countries. This paper shows not only how far we are from achieving that goal but also some of the hitherto unrecognised reasons.


Chen Zongmao, 2011. Study on the problems of China’s tea industry quality and safety and environmental safety.Quality and Safety of Agro-Products, (3): 5-7. (in Chinese)

Ganewatta G, Waschik R, Jayasuriya S et al., 2005. Moving up the processing ladder in primary product exports: Sri Lanka’s “value-added” tea industry. Agricultural Economics, 33(3): 341-350.Abstract Governments in many developing countries, influenced by the experience of the East Asian newly industrialized countries, have adopted policies to enhance domestic processing of primary commodities as a tool for accelerating employment growth, export revenues, and development. Sri Lanka has traditionally exported tea in the form of bulk (commodity) teas, but alue-added teas such as packaged teas, tea bags, etc., have expanded in recent years. This article examines factors affecting the processing of value-added tea products in Sri Lanka by modeling export supply behavior. Estimates of the long-run relationship and short-run dynamics of export supply are presented and discussed. The price of value-added tea relative to bulk tea, and industry capacity, are identified as the main determinants of export supply, while exchange rate changes have no discernible effect. The policy implications of the analysis for enhancing further expansion of such value-added teas are presented. These are of interest for both policy makers and development analysts. In particular, the reasons that undermine the effectiveness of exchange rate policy as an instrument to stimulate value addition of primary products have much relevance for similar developing countries.


Gao Qun, Zhang Youwang, Ke Yangmin, 2016. Sugar yield change and contribution factors decomposition of space and time: Based on LMDI model.Economic Geography, 36(4): 99-105. (in Chinese)In order to clarify sugar crops yield change and main contribution factors in China since the reform and opening up, based on data from 1978 to 2013, space-time decomposition LMDI model was used to study the change and influencing factors of sugar production. The empirical results show that:(1) As a whole, the unit output caused by such factors as the progress of science and technology is the fundamental reason for the increase in total output of sugar.(2) In terms of plant varieties, sugar output significantly increase is the result of these factors, respectively for sugarcane production area expansion, upgrading the sugarcane yield and sugar beet yield improvement. However, sugar beet planting area is reduced to delay the speed of the total output of sugar to a certain extent.(3) From the point of regional layout, the industrial concentration of sugar production has increased significantly and presents a "moving westward" trend. There exists a significant difference both sugar yield changes and varieties decomposition effect. At the end of the article, we put forward the following suggestions: rely on modern science and technology to promote yield level, focus on promoting sugarcane large-scale production, optimization of regional layout, etc.

Gesimba R M, Langat M C, Liu G, et al. 2005. The tea industry in Kenya: The challenges and positive developments.Journal of Applied Sciences (Pakistan), 5(2): 334-336.Kenya is a tropical East African country with a wide diversity of climate and geographic regions. This diversity allows many crops to be introduced and grown successfully. Tea production has contributed significantly to the Kenyan economy and it will continue to do so. Herein a summary of significant aspects of the tea industry and positive developments, which will shape the future of tea production in Kenya, are highlighted.


Han Yu, Xiao Hongru, Song Zhiyu et al., 2016. Research on mechanization technology mode of tea plantation and management.Journal of Agricultural Science and Technology, 18(3): 74-81. (in Chinese)

Hazarika C, Subramanian S R, 1999. Estimation of technical efficiency in the stochastic frontier production function model: An application to the tea industry in Assam.Indian Journal of Agricultural Economics, 54(2): 201.Abstract Although India holds the leading position in production and export the current position of tea trade revealed that it's share in world production and export has been declining steadily over the past three decades. Export during last few decades remained around 200 million kgs. Though India has almost doubled its tea production between 1965 and 1991, still it is not sufficient to maintain India's dominant position in the world tea trade. This necessitates an analysis of production efficiency of the estates to help to formulate policy measures to remove the production constraint in the Indian tea industry particularly in Assam. Efficiency is an important factor of productivity growth as well as stability of production especially in developing agricultural economies. In view of slow growth and increasing instability in production (Bhuyan and Hazarika, 1997), the tea economy of Assam could be benefited to a great deal from inefficiency studies. Estimates on the extent of inefficiencies could help to decide whether to improve efficiency or to develop new technology to raise tea productivity in Assam. The results from this study showed that even under the existing technology potentials exists for improving the productivity with proper allocation of the existing resources. Hence proper extension strategies needs to be taken to educate the estate owners about rational use of inputs. The existence of obsolete tea bushes is one of the factors that inhibited the growth of the industry. The high percentage of vacancy and old age bushes weakened the productivity of the plantations. So the estate owners should be educated on the need for undertaking infilling, replanting and replacement planting.

He Yanyan, 2011. The development approach of concession for bigger and stronger tea industry.Hunan Agricultural Sciences, 24(10): 21-22. (in Chinese)

Hu Jicheng, Yang Li, 2016. Review of Guizhou tea industry during the 12th Five-Year Plan period and its prospect for upcoming five-year plan.China Tea Processing, (3): 19-24. (in Chinese)Guizhou has low latitude, high altitude, heavy clouds and little sunshine in China. It is one of the main production areas in China. Guizhou made great efforts to promote the transformation and upgrading of the tea industry.Great progress has been made in the ingredients, production, quality, safety, cost-effective, and competitiveness of tea during the "12th Five-Year Plan" period. What's more, the tea industry in Guizhou has transformed from quantity-oriented to quality-oriented. In the "13th Five-Year Plan" period, Guizhou will also rely on its unique ecological advantages and industrial base to make the tea industry as the strategic supported industry of the province. The goal is to make Guizhou a powerful tea production province with sustainable development.

Ji Long, Li Chongguang, Zhang Shengyong, 2016. The spatial distribution of vegetable production in China and its impact on vegetable price volatility.Economic Geography, 36(1): 148-155. (in Chinese)Revised Gini coefficient and Moran's Index are used to investigate the characteristics and dynamic changes of vegetable production in China, and then this paper analyses the mechanism and effects of the spatial distribution of vegetable production on vegetable price volatility theoretically and empirically. The results show that:(a) vegetable production in China reveals significant geographical concentration features and maintains a high level of geographical concentration accompanied by a westward shift of vegetable production.(b) the spatial distribution of vegetable production has a significant effect on vegetable price volatility by acting on the transportation costs, supply and demand in the vegetable market, and external environment. More specifically, geographical concentration of vegetable production caused higher cost of transportation, more serious imbalance between vegetable supply and demand in east China, and higher production risk in the major vegetable producing areas, which exacerbating the vegetable price volatility.(c) the impact of spatial distribution of vegetable production on price volatility reveals great differences across regions: price volatility in the major vegetable producing areas is more intense than that in the major consumer areas; moreover, price volatility in the major producing areas is mainly caused by the seasonal variation while price volatility in the major consumer areas is mainly caused by the trend change.

Jiang Hanchun, Zhao Hongying, Ge Wei, 2009. Analysis of present status and development tendency of tea industry in China.Chinese Journal of Agricultural Resources and Regional Planning, 30(3): 23-28. (in Chinese)It is worthwhile to attend and discuss how does tea industry develop in China for 5000 years ceaselessly without any decline and how will it continue to develop.Under the condition of WTO,the economic activities of tea industry in China are restricted by domestic and international environments,and also depend on our own superiorities and weak points.This paper analyzes the structure elements of tea industry and its species;evaluates its superiorities and weak points,the chances,threats,granted by outside environment under WTO condition.Before ending,it discusses the future development trend for the Chinese tea industry.

Jin Tao, 2014. Effects of cultivated land use on temporal-spatial variation of grain production in China.Journal of Natural Resources, 29(6): 911-919. (in Chinese)There are four factors which denote four types of cultivated land use by drawing on grain production calculating model: grain yield per hectare(intensity effect), cultivated land area(scale effect), planting structure(structure effect) and multiple- cropping index(degree effect). Changes of grain production in China were thus studied by quantifying the contributions from changes in cultivated land use using LMDI method. The results showed: During 1978-2012, there was more aggregated intensity effect than degree effect on the total grain increment, while there was more structure effect than scale effect on the grain reduction. Intensity effect, the largest contributor for China's grain production all the time, decreased step by step,whereas degree effect, whittling down the production in the early phase, then turned to an indispensable promoting factor for its steadily uplift. Structure effect in weakening grain output increased over time, and scale effect expanded markedly from 1998 to 2012 because of the dramatic decline in cultivated area. Spatially, grain production in eastern coastal China was evidently shrinking when the northern and western inland experienced a compensating increase during 1996-2008. The higher positive intensity effect and degree effect were observed in the northern and western peripheral region, while the highly urbanized coastal region had the higher negative scale effect and structure effect, even in some cases with negative degree effect,thus enlarging the regional disparity of China's grain production. From the decomposition findings, the paper concluded with some suggestions for cultivated land use to enhance China's grain security.


Li Erling, Pang Anchao, Zhu Jiguang, 2012. Analysis of the evolution path and mechanism of China’s agricultural agglomeration and geographic pattern.Geographical Research, 31(5): 885-898. (in Chinese)

Li Jianbao, Huang Xianjin, Yang Hong et al., 2017. Convergence of carbon intensity in the Yangtze River Delta, China.Habitat International, 60: 58-68.As China's industrialization and urbanization have grown rapidly in recent years, China's CO 2 emissions rose from 3405.1799Mt to 10,249.4630Mt from 2000 to 2013, and it has reached the highest levels in the word since 2006. Chinese government has emphasized the importance of reducing carbon emissions and set the target of reducing carbon intensity to 60–65% of 2005 levels by 2030. Investigating the convergence of carbon intensity can identify the convergence rate, which is helpful in guiding allocations of carbon intensity reduction. The Yangtze River Delta is one of the key carbon emission regions in China, with higher urbanization levels and larger carbon emissions; thus, we employed prefecture-level panel data derived from grid data between 2000 and 2010 to examine whether the convergence of carbon intensity exists across prefecture-level cities in the Yangtze River Delta. Spatial panel data models were utilized to investigate β-convergence of carbon intensity. The results indicated that carbon intensity showed divergence during 2002–2004 and σ-convergence over other periods (2000–2002 and 2004–2010). Carbon intensity exhibited stochastic convergence, indicating that the shocks to carbon intensity relative to the average level of carbon intensity are only transitory. There was a spatial spillover effect and β-convergence of carbon intensity, suggesting that prefecture-level cities with higher carbon intensity would decrease rapidly in the Yangtze River Delta. Our results highlight the importance of considering the present state of carbon intensity, spatial factors, and socioeconomic factors such as industrial structure and economic levels during allocation planning for reducing carbon intensity.


Li Shirui, Wang Zhihai, Yang Zaiqiang et al., 2014. Analysis on production status of tea plant and climate characteristics in tea regions in southern Yangtze River.Journal of Arid Meteorology, 32(6): 1007-1014. (in Chinese)It is greatly instructive to analyze climate resources characteristics for tea production. In this research,the characteristics of tea cultivar,planting area,yield,climate condition and main meteorological disasters in tea region in south area of the Yangtze River were analyzed by filed survey and data collection,and the problem and measurement were put forward. The results found that the main tea species in the south of the Yangtze River were Wuniuzao,Longjing43,Fuding white tea,Yingshuang,Molina pit,Huangshanzhong,Cuifeng,Anji white tea,etc. The planting area and yield of tea in Hubei Province were the largest,however the unit output value was the highest in Jiangsu Province,the following was Zhejiang,Hunan,Jiangxi,Anhui and Hubei. The annual mean temperature was 15- 20 ℃,the greater than or equal to 10 ℃ accumulated temperature was 4 500- 6500 ℃ ·d,the annual rainfall was 1000- 1 600 mm,the annual mean relative humidity reached 70%- 80%,and the sunshine duration remained 1 500- 1 900 h in tea region in south area of the Yangtze River. Thus,the climate in this region was abundant in sufficient heat,moist air,adequate sunshine,and was suitable for green tea growing. However,the region was a high risk area of main agro- meteorological disasters to tea.Therefore,the research on monitoring of tea plant and risk assessment of the agro- meteorological disasters should be strengthened and tea production ability should be improved to cope with climate change on the basis of making the best of GIS,RS,GPS,and we should vigorously promote refined weather service in tea regions in the south of the Yangtze River.

Li Xilin, Liu Heguang, 2011. The development pattern and trend of the world tea trade.Agricultural Outlook, 7(4): 44-48. (in Chinese)

Li Yumei, 2010. International comparison of the relationship between land productivity and China’s tea export.Journal of Agrotechnical Economics, (8): 106-116. (in Chinese)

Liang Yuerong, Shi Meng, 2015. Advances in tea plant genetics and breeding.Journal of Tea Science, 35(2): 103-109. (in Chinese)Advances in germplasm enhancement of tea breeding, techniques for identification of new tea cultivars, changes in breeding objectives, improvement of breeding program, achievements of tea breeding, system of propagation and extension of new tea cultivars were reviewed in th is paper, which provides useful information for further studies in tea genetics and breeding. Hybridization is still the major method for innovating tea breeding materials, and the physical and chemical mutagenesis methods have been extensively used, while transgenic technique remains to be further improved. Combination of the high resolution inspecting equipments and the gene identification technology with the forecasting models established by computer technology made the early identification of tea cultivars more accurate. The breeding target has been diversified after going through yield breeding, quality breeding and early flushing breeding stages. Improving early identification accuracy and shortening breeding cycle will be the aim for tea breeding technology development.

Liu Shejian, 2014. Evolution, questions and solutions to the industry policy. Academic Monthly, 46(2): 79-85. (in Chinese)Industrial policy plays an important role in stimulating industrial development and stable economic growth.Although the debates on the role of industrial policy have never ended,in practice many countries have developed appropriate industrial policies.Since late 1980s,China has planned to stimulate industrial development and stable economic growth by the introduction of the industrial policy.To parallel with the progress of economic reform and the extent of economic development,industrial policy has been divided into two stages bounded to the vear 2000.After 2000,with the deepening of economic reform and the complexity of macro economy,the trend of industrial policy's intervention in micro economy has rapidly intensified.The administrative means play an increasingly important role in industrial policy,which ro some extent hindered market-oriented economic reform.To advance the industrial development and stable economic growth,based on the current performance of existing industrial policy,it is necessary to make a new industrial policy to effectively applying the role of market,which is able to reduce the micro intervention and improve the macro effects on guidance and coordination.

Liu Y, Huang X, Yang Het al., 2014. Environmental effects of land-use/cover change caused by urbanization and policies in Southwest China karst area: A case study of Guiyang.Habitat International, 44: 339-348.Land-use/cover change (LUCC) caused by urbanization has impacted environment and become an important factor driving global change. Karst is a very fragile environment and the LUCC can cause massive change of the environment. An integrated approach was used to explore the environmental effect of LUCC with urbanization and China's ecosystem restoration projects during the period 1996 2010. The results show that the area dedicated to arable land, grassland, water area, and unused land have declined by 243.04km 2 , 22.96km 2 , 2.06km 2 and 13.61km 2 , whereas the size of forestland and construction land have increased by 153.85km 2 and 127.82km 2 , respectively. The overall environmental quality, measured using environmental quality index, has improved; however, the improvement only occurred in suburb districts. The variation of green land per capital, forestland and grassland were the main reasons for the environmental change. Further environmental degradation caused by urbanization and LUCC possibly continue in the coming decades and therefore environment protection should be the priority for the development in Karst areas.


Liu Zhenhuan, Li Zhengguo, Tang Pengqin et al., 2013. Change analysis of rice area and production in China during the past three decades.Journal of Geographical Sciences, 23(6): 1005-1018.Rice's spatial–temporal distributions,which are critical for agricultural,environmental and food security research,are affected by natural conditions as well as socio-economic developments. Based on multi-source data,an effective model named the Spatial Production Allocation Model(SPAM) which integrates arable land distribution,administrative unit statistics of crop data,agricultural irrigation data and crop suitability data,was used to get a series of spatial distributions of rice area and production with 10-km pixels at a national scale – it was applied from the early 1980s onwards and used to analyze the pattern of spatial and temporal changes. The results show that significant changes occurred in rice in China during 1980–2010. Overall,more than 50% of the rice area decreased,while nearly 70% of rice production increased in the change region during 1980–2010. Spatially,most of the increased area and production were in Northeast China,especially,in Jilin and Heilongjiang;most of the decreased area and production were located in Southeast China,especially,in regions of rapidly urbanization in Guangdong,Fujian and Zhejiang. Thus,the centroid of rice area was moved northeast approximately 230 km since 1980,and rice production about 320km,which means rice production moved northeastward faster than rice area because of the significant rice yield increase in Northeast China. The results also show that rice area change had a decisive impact on rice production change. About 54.5% of the increase in rice production is due to the expansion of sown area,while around 83.2% of the decrease in rice production is due to contraction of rice area. This implies that rice production increase may be due to area expansion and other non-area factors,but reduced rice production could largely be attributed to rice area decrease.


Lu Q, Yang H, Huang Xet al., 2015. Multi-sectoral decomposition in decoupling industrial growth from carbon emissions in the developed Jiangsu Province, China.Energy, 82: 414-425.61Multi-sectoral decomposition and decoupling were conducted to evaluate the ICE.61The industry of Jiangsu was in a weak decoupling state with an increasing trend.61The industrial output growth was the biggest driver for ICE from 2005 to 2012.61The optimization of industry structure came into play for the reduction since 2008.61Five backward and advanced industries were identified.


Loconto A, 2014. Assembling governance: The role of standards in the Tanzanian tea industry.Journal of Cleaner Production, 107: 64-73.Governing through standards has gained significant academic traction, particularly through discussions of global value chains and instruments of neoliberal private authority. Drawing from ethnographic work, I utilize examples from the tea industry in Tanzania to characterize the pragmatic nature of how standards govern at a distance in local contexts. These examples are the: 1) use of Fairtrade funds to fulfill community obligations; 2) participation in value chain actors' bids for external technical assistance; and 3) participation in donor-funded projects unrelated to standards schemes, yet enable compliance with certification requirements. The analysis reveals that the nature of these programs is a combination of historically entrenched systems and neoliberal approaches to development. By conceptualizing these standards as agencements, rather than instruments of private regulation, we are able to better capture governmentality in the Foucauldean sense as the mobilization of standards to provide public goods is a mode of governing that necessarily involves far more actors than the State alone.


Nitzl C, 2016. The use of partial least squares structural equation modeling (PLS-SEM) in management accounting research directions for future theory development.Journal of Accounting Literature, 37: 19-35.In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.


Niu Xiaojing, Gu Gouda, Zhang Chun, 2007. World tea production and trade patterns of evolution and current situation analysis.World Agriculture, (6): 29-32. (in Chinese)

Song Jia, Zhang Yueheng, 2005. Estimation of comparative advantage of agricultural product in Pan Pearl River Delta.Research of Agricultural Modernization, 26(5): 116-120. (in Chinese)This paper has adopted the methods of Production Focus Index, Revealed Comparative Advantage(RCA) and Regional Revealed Comparative Advantage(RRCA) to estimate the comparative advantage of the whole Pan Pearl River Delta and 9 provinces in it respectively. The conclusions of the analysis are:the comparative advantage of predominant farm product is not obvious in Pan Pearl River Delta, but economic crops and meat have a good developing foreground; vegetable, fruit, tea leaf, tobaccos, meet are the product that should be produced and exported emphatically; corn, oil plants, sugar and forest product should be produced and exported properly according to the resource endowment of each province; it's better to reduce the export of milk and butter. Then this paper pointed out the countermeasures and methods to accelerate the agricultural corresponding development of the district.

Su Baocai, 2010. An empirical analysis of productive investment technical efficiency and influencing factors of tea farmers in Anxi county, Fujian Province.Issues of Forestry Economics, 30(4): 346-350. (in Chinese)Based on Anxi County,Fujian Province farmers survey data,this article take it as an example,establishes Stochastic frontier production function to estimate the economic efficiency for tea production and procession,it analyzes technical efficiency change and its Influencing factors.It showed that farmers engaged in tea production and processing time,farmers engaged in tea production and processing time of the square,the tea farmers head of the household number of years of education of three explanatory variables for the impact of technical efficiency was not significant;The household head's age of tea farmers,tea Varieties,whether trained,tea earning percent in household income,tea plantations area,virtual variables of villages location type had positive relationship with the technical efficiency.The square of the tea area owned by farmers and the regional differences have negative effects on technical efficiency.

Su Zhucheng, 2011. Organization of Chinese tea industry: Performance and policy.Journal of Tea Science, 31(3): 264-272. (in Chinese)The organization of Chinese tea industry,its performance and policy,were discussed in this paper.The present organizational structure of Chinese tea industry showed some features such as small householder of tea garden,no-monopoly competition,market division between primary and refining production,processing for exportation according to giving samples and so on.From perspective of other major tea-production countries,the organizational structure was characterized by vertical proportional share-distribution in Sri Lanka,cooperation institution of farmers in Japan and exportation of black tea by auction market,which had some significant implication for us.It was suggested that,targeting the market entry of small householder of tea garden and integration of primary and refining production,industry polices should focused on innovation of institution and technology.Besides,transformation of mode of exportation transaction should also be explored.


Sun Lei, Zhang Xiaoping, 2012. Research on spatial distribution of the manufacturing in Beijing and its decomposition of center of gravity.Progress in Geography, 31(4): 491-497. (in Chinese)In the first decade of this century,Beijing has been undergoing the conversion from an industrial city to a new economic city which is more suitable for the capital city,and the transfer will have a profound and far-reaching influence on the distribution of the manufacturing in Beijing.This paper intends to represent the spatial evolution of manufacturing in Beijing in recent 10 years,using the methods of functional zonation and center of gravity calculation.In addition,by decomposing the change of the center of gravity,we also try to describe quantitatively some factors which affect the distribution of manufacturing.Firstly,by collecting and processing the statistical data of the manufacturing in Beijing,we found that the spatial distribution of manufacturing in Beijing had been expanding from the function extension area to the new urban area,and the centers of gravity of both manufacturing employment and enterprises in Beijing extended eastward.However,there are also some differences: the former to the northeast,the latter to the southeast.Secondly,we decomposed the change of the center of gravity to three effects.The result shows that both the structure effect and the spatial effect play more important roles in the change of the center of gravity of manufacturing employees,which were the dominant driving force for the change of the center of gravity of manufacturing in Beijing.It is concluded that,on one hand,we should carry out the readjustment of industrial structure,to transfer from the labor-and capital-intensive heavy chemical industries to the knowledge-and tech-intensive high-tech industries,such as manufacture of electronic and communication equipment and manufacture of computers and office work equipment;on the other hand,we should further optimize the spatial distribution of the manufacturing in Beijing,so as to shape a new closer industrial pattern among Beijing,Tianjin and Hebei province.


Tan Jieyang, Li Zhengguo, Yang Peng et al., 2014. Spatio-temporal changes of maize sown area and yield in Northeast China between 1980 and 2010 using spatial production allocation model.Acta Geographica Sinica, 69(3): 353-364. (in Chinese)Understanding crop patterns and their changes on a large scale is a critical requirement for projecting agro-ecosystem dynamics. However, tools and methods for analyzing crop sown area and yield on spatiotemporal variations are still insufficient currently. By the use of cross-entropy method, a Spatial Production Allocation Model(SPAM)was developed. Combined with geographic spatiotemporal analysis methods, a case study was further presented to analyze the spatial characteristics of maize sown area and yield in Northeast China during 1980-2010 within 5' × 5' grid cells. The results indicated the following:(1) Maize sown area mainly expanded northwards during 1980-2000(located at 44°N-48° N) and then concentrated at central and southern in Northeast China on latitudinal variations in the following years. Also it moved eastwards(located at 123°E to 127°E) and lower elevation(below 100m) as well as higher elevation(mainly from 200 m to 350 m)region on longitudinal and altitudinal variations, respectively.(2) Maize yield which has been improved largely mainly located at 42°N to 48°N and concentrated at the region below the altitude of 350 m on latitudinal and altitudinal variations, respectively, while its increase is relatively homogeneous on longitudinal variations.(3) Additionally, dominant maize proportion on a pixel scale has developed to middle-high proportion gradually during1980-2010, and maize yield located at the pixel of middle-high proportion seems higher,which reflected the trends of agglomeration and large-scale development of maize cultivation driven by market economy.


Wan Qing, Yan Fengzhu, 2006. International competitiveness of Chinese tea industry and policy implications.Resources Science, 28(4): 118-124. (in Chinese)The tea industry in China is a traditionally advantaged industry.However,the competitiveness of the Chinese tea in international market has been descending continuously since 1980's and challenged by India,Kenya,Sri Lanka and Indonesia etc.This paper makes use of the statistical data from Food and Agriculture Organization of the United Nations,by such dominant evaluation index as possession rate of international market,revealed comparative advantage index and producer's price index and its recessive evaluation index-yield of per unit area,to measure and calculate the variety of international competitiveness of tea in China,India,Sri Lanka,Kenya and Indonesia since 1980's.It has been reached the conclusion that the position of Chinese tea is basically weak on the four evaluation indexes,and obvious in revealed comparative advantage index,producer's price index and yield of per unit area.Based on empirical analysis and the five decisive factors of international competitiveness in Prof.Porter's National Diamond Model,the article puts forward the countermeasures and proposals to promote the international competitiveness of Chinese tea at the five levels of factor endowment,corporation strategy,related industry,demand factor and governmental behavior.At the level of factor endowment,emphasis should be put on the solution to the low rate of production.The new production factor should be introduced to the tea the level of corporation strategy,the tendency of the international tea competitiveness should be acclimated,and the united scale management should be promoted to seek a famous brand of famous tea.At the level of demand factor,based on the firmness of the traditional market,the newly arisen market should be expanded strongly and the concentration degree of the export market should be lowered.At the level of related industry,specialized production should be developed actively and provide the specialized productive material for tea production.At the level of the government,the boundary of administrative duty and function should be made clear within the framework of World Trade Organization.Emphasis should be put on the solution to the tea standardization,to regulate effectively tea export disorder from the sources and ends.Governmental behavior may be more critical compared with the four of the other countries,because the actual circumstance of China comes to the decision in the tea industry.


Wang Yingfeng, Zhai Haiguo, 1993. A new scheme for tea ecological environment regionalization in China.Geographical Research, 12(4): 39-45. (in Chinese)The paper having analysed the ecological environment and the tea production condition in China and also studied the ccological adaptability differences of every breed tea tree now puts forward a new scheme for tea tree ecological environment regionalization in China. The new region-alization scheme has a two -level system. The first level units have four tegions, They are south temperate zone tea-producing region (leaflet breed tea tree cultivable region), north subtropical zone tea -producing region (super quality leaflet breed tea tree normal region),subtropical zone tea - producing region( super quality leaflet tree breed optimum region), and south subtropical, tropical Zone tea-producing region (grandifoliate breed tea tree normal region). The second level units have nine regions. The new regionalization scheme,which can indicate the pro-due! ion direction of different tea producing area in China and point out the distinction of China tea production. is very important for the future development of China tea production and China tea export trade.


Wei Longbao, Li Jing, 2014. Analysis for effects of social capital and human capital of agricultural industry cluster on farmers’ income.Issues in Agricultural Economy, 35(4): 41-47. (in Chinese)

Wu C, Huang X, Yang H et al., 2015. Embodied carbon emissions of foreign trade under the global financial crisis: A case study of Jiangsu province, China.Journal of Renewable & Sustainable Energy, 7(4): 10288-10293.China has been world's largest CO2emitter since 2008 and the export contributes the majority of its CO2emissions. Global financial crisis impacted China's export and probably the carbon emission. However, there is no systematic study about the impact of global financial crisis on Chinese carbon emission embodied in international trade (EET), especially from the multi-sector perspective. This research used an input utput analysis model to estimate the total embodied carbon emissions, including direct and indirect carbon emissions in foreign trade from 2005 to 2010 in Jiangsu province, one of the most developed provinces in China. In addition, this research assessed the changes of carbon emissions embodied in foreign trade during the global financial crisis and analyzed the drivers to the changes from multi-sectors using a structural decomposition analysis. Jiangsu was a province with net export emission, and the emissions of both production-based and consumption-based increased during the 2008 financial crisis. Emissions embodied in domestic final demands (CD) increased by 139.4%, while emissions embodied in exports (CE) and emissions embodied in imports (CM) decreased by 29.36% and 81.6%, respectively, from 2008 to 2009. Energy-related sectors (electric and heat power, coal mining and dressing industry,andcoking and nuclear fuel processing industry) and manufacturing sector (textile industry) were the main contributors to the change the emissions embodied in international trade. The proportion of export's value of key sectors in all sectors increased annually by 60.7%, while the proportion of import's value grew annually by 55.2% during the global financial crisis. Despite the global financial crisis, the consumption demands were the main factors causing the increase of the total EET from 2008 to 2009. This study highlights the importance of reducing EET by adjusting the trade structure in Jiangsu province and other developed areas in China.


Xiao Zhi, Huang Xianjin, Meng Hao et al., 2017. Spatial structure and evolution of tea production in China from 2009 to 2014.Geographical Research, 36(1): 109-120. (in Chinese)Understanding of the regional changes of production layout of tea can help the decision-making for a better strategy of tea production in China. In this paper, we analyze the spatial- temporal distribution of tea plantation acreage, tea yield, well- known tea yield, tea production value and the well- known tea value using the GIS technology and gravity center theory. Moreover, we discuss the driving forces of the dynamic evolution of their centers of gravity. The results indicate that there are evident regional differences in China's tea production. Four regional tea production centers(Southwest China tea area: Yunnan, Guizhou and Sichuan; Jiangnan tea area: Hubei and Zhejiang; Southern China tea area: Fujian; Jiangbei tea area: Henan) have been formed. Fujian, Yunnan and Zhejiang provinces are major regions of tea industry in China. The change of tea production center of gravity in China shows a trend of westward movement on the whole. Although there are some differences in the paths of different indicator centers of gravity, westward movement of the center of tea production is a foregone conclusion. The tea garden area gravity centers move toward the northwest. The output of normal tea and well- known tea gravity centers move toward the southwest. The tea production value and well- known tea production value gravity centers move toward the northwest as a whole. In terms of the moving range and moving speed, the tea production value and famous tea production value gravity centers are lagging behind the output of normal tea and the well- known tea gravity centers shift. On the transfer path of the center of gravity, the size of the center of gravity of some properties, such as tea production, can directly reflect the size of the growth of the attribute in the moving region. There are several factors that affect the spatial-temporal change of tea production center of gravity. First, the government attaches great importance to the development of the tea industry and strongly support the expansion of the tea plantation acreage in China. Second, the optimization of product structure, the increase of proportion of the clonal tea plantation acreage, standardized production and popularity of mechanization are the important reasons for the growth of production of normal tea and the well- known tea. Third, the added value of normal tea and the well- known tea are mainly resulted from the expansion of the scale of tea industry and the brand management.

Yang Hong, 2014. China must continue the momentum of green law. Nature, 509(7502): 535.A plan for improved environmental protection is a good first step, but all levels of society will need to work together for it to succeed, says Hong Yang.


Yang Hong, 2016. China’s soil plan needs strong support.Nature, 536(7617): 375.The government must accompany its action plan on soil quality with effective laws and remediation measures, says Hong Yang.


Yang H, Flower R J, Thompson J R, 2013a. Pollution: China’s new leaders offer green hope.Nature, 493(7431): 163.China's scientists have high hopes that the country's new leaders (Nature 491, 161; 2012) will accelerate efforts to tackle environmental pollution. The proportion of China's Politburo Standing Committee (PSC) educated in economics and social science has increased to 86% from 22% in 5 years. This jump reflects the social problems caused by the country's rapid development from an agricultural economy (Nature 488, 261–262; 2012). Engineering solutions to water pollution and scarcity, for example, include construction of large reservoirs and transfer of water between river basins, but these have come with serious socioeconomic and environmental costs. China's new leaders should recognize that non-structural approaches can be more sustainable and ecologically beneficial (P. H. Gleick Water Int. 25, 127–138; 2000). With almost one-third of PSC members also having a legal background, green protests about pollution and resource management can now be properly handled through the judicial system. As well as increased investment, prescient actions through effective legislation are needed to deliver sustainable long-term economic benefit


Yang H, Flower R J, Thompson J R, 2013b. Sustaining China’s water resources.Science, 339(6116): 141.Comment on Science. 2012 Aug 10;337(6095):649-50.


Yang Yanzhao, Liang Yubin, Feng Zhiming et al., 2016. Temporal and spatial patterns of corn production, consumption and the balance of supply and demand in China.Research of Agricultural Modernization, 37(5): 817-823. (in Chinese)

Yao Lufeng, He Shujin, Zhao Xin, 2013. The writing of temporal and spatial variation of geography.Acta Geographica Sinica, 68(7): 1007-1011. (in Chinese)

Zang Zheng, Zou Xinqing, Song Qiaochu et al., 2017. Integrated sustainable development evaluation based on human wellbeing indices and pressure indices: A case study of the South China Sea neighboring countries. The Social Science Journal, .

Zhang Chuanzheng, Zhang Ding, Li Xinghui et al., 2006. Techniques of tea counter-season production in the tea production areas of Jiangnan. Nonwood Forest Research, 24(2): 55-58. (in Chinese)Techniques were provided for tea counter-season production in the tea production areas of Jiangnan,which included regulation of ecological conditions(i.e.temperature,light,water and humidity,and gas),plant diseases and insect pests,soil activity and fertility cultivation,and bush growth rhythm etc.It was put forward that the development trend of tea counter-season production was automatization and intelligentization.

Zhang Min, Gu Chaolin, 2002. Spatial characteristics of the recent inter-provincial flow of social-economic elements in China.Geographical Research, 21(3): 313-323. (in Chinese)This paper reveals spatial characteristics of the recent inter provincial(municipal,regional) flow of social economic elements in China. Firstly, thepaper reviewsthe studies on the trans regional flow of social economic elements in China Then, based on the survey data,it conducts a comprehensive analysis of the spatial characteristics of the productive element flow such as the inter provincial migration, passenger railway flow, airborne passenger flow,railroad freight flow and information flow, by adopting GIS spatial analysis and visualization techniques. The spatial distribution of the inter provincial flow is influencedevidently by the provincial economic status and the pattern of inter provincial economic relations The eastern China shows its great importance on the distribution of the inter provincial flow The three economic heartlands of China, Jing Jin Tang (Beijing, Tianjin, Hebei), Hu Su Zhe (Shanghai, Jiangsu, Zhejiang) and Guangdong also act as the main centers of inter provincial flow The gravity centers of all the inter provincial flows are relatively close to the population and economic centers of China, but deviate far more from the geometric center of the territory This means the spatial distribution of inter provincial flow is basically consistent with the socialand economic situationof China Further, the paper concludes the spatialdistribution of the flow of social economic elements as four fundamental patterns, which are tested in each type of the flow and two holistic styles are deduced


Zhang Peng, 2012. Feasibility study on the development of green tea industry in southern Shaanxi.Academic Periodical of Farm Products Processing, 15(9): 108-110. (in Chinese)On the basis of the analysis of development trend in Tea Industry,this paper mainly attempts to consider the tea industrial base and its resource advantages in southern Shaanxi,the present situation and problems in tea industry development.From the ecological carrying capacity,project market analysis and market prediction,technical support,benefit and risk and so on,this paper analyzes the feasibility of developing the green tea industry in southern Shaanxi and puts forward the safeguard measures.

Zhang Xiaofeng, Wang Hongzhi, Liu Luo et al., 2014. Spatial-temporal characteristics of soybean production potential change under the background of climate change over the past 50 years in China.Progress in Geography, 33(10): 1414-1423. (in Chinese)Soybean is one of the most important grain and oil crops in China. With the growth of population and the improvement of people's living standard, demands for soybean products have been increasing. At the same time global climate change has brought both beneficial and detrimental effects to soybean production, depending on the geographic areas. Using the 2010 remote sensing monitoring data of cultivated land distribution and long time series meteorological and soil data, soybean production potential in China was calculated using the AEZ model for the period from 1961 to 2010. Solar radiation, temperature, water, CO2 concentration, plant diseases and insect pests, agricultural climate restrictions, soil, terrain, and other factors were taken into consideration in the model. This study simulated long-term change of soybean production potential in China from 1961 to 2010 and analyzed the spatial-temporal characteristics of this change under the background of climate change. The results are that:(1) Significant difference was found in the spatial distribution of soybean production potential in China over the study period here was an increasing trend from south to north and west to east. The high potential zones were Northeast China Plain, Middle-Lower Yangtze River Plain, and Huang-Huai-Hai River Plain.(2)In the recent 50 years, China's soybean suitable planting areas increased continuously, while the mean soybean production potential steadily declined. The total potential yield of soybeans nationwide decreased at the beginning and then increased n the 1970 s the total potential yield of soybeans reduced by 2.181 million tons compared to that in the 1960 s. It then showed a trend of continuous growth from the 1970 s to 2000 s, and the amount gradually became larger. From the 1970 s to 2000 s the total potential yield of soybeans increased by 5.3 million tons.(3) In different regions of China soybean production potential experienced different changes. From the1960 s to the 1970 s the total potential yield of soybeans in the Middle-Lower Yangtze River Plain ranked first in China. In the 1980 s, the total potential yield of soybeans in Northeast China Plain had a spectacular increase and exceeded the Middle-Lower Yangtze River Plain and became number one in the country. The Huang-Huai-Hai River Plain ranked third. Since the 1970 s, the total potential yield of soybeans continuously declined to 65.87 million tons in the 2000 s and it was 2.85 million tons lower than in the 1960 s. This study reveals the spatial-temporal characteristics of soybean production potential change over the past 50 years in China, which has important scientific significance for the planning of soybean planting, efficient utilization of climate resources, and achieving high and stable yield of soybeans.


Zhu Defeng, Pang Qianlin, He Xiumei, 1997. Analysis on the factors of rice yield growth in China and the countermeasures for the future development.China Rice, 3(6): 3-6. (in Chinese)