Integrated emergy and economic evaluation of different planting systems in China: implications for coordinating poverty alleviation and rural revitalization

ABSTRACT

Developing high-value crop planting industries according to local conditions is an important strategy for targeted poverty alleviation, and it is also a momentous solution for agricultural structure adjustment. However, previous studies mainly have focused on their spatiotemporal evolution and economic benefits instead of their environmental impact. An in-depth analysis of high-value crop planting industries is urgently needed. Taking Linquan County as the research area, this study applied emergy and economic analyses to explore the differences among different high-value crop planting systems and wheat planting system from the perspectives of economic benefit, environmental impact and overall sustainability. The results showed that high-value crop planting systems provide more competitive economic profit than that of wheat planting. Despite the high economic benefits, the three highvalue crop planting systems intensify the purchased nonrenewable resource inputs and lead to higher environmental stress, especially the ginger planting system. Under the trade-off of economic benefit and environmental performance, peony planting is considered a promising pattern for further sustainable agriculture considering its synergistic development of photovoltaic power generation. Several policy incentives are suggested to increase the financial attractiveness of environmentally sound patterns and promote a virtuous cycle for future sustainable agriculture.

KEYWORDS:

• Emergy evaluation
• high-value crop planting system
• environmental performance; rural revitalization
• sustainability

1. Introduction

China achieved a complete victory in the battle against poverty in 2020, with 832 poverty-stricken counties and 128,000 poverty-stricken villages across the country being lifted out of poverty (Qi et al., 2022; Shan & Yang, 2019; Zhou et al., 2018). Developing high-value crop planting industries according to local conditions and building the layout of ‘one township, one industry’, ‘one village, one product’ or ‘characteristic towns’ all over the country has been demonstrated to be an important strategy in the process of precise poverty alleviation (Long & Wang, 2018; Yang & Zhang, 2021). A high-value crop planting industry is a development-oriented poverty alleviation measure based on the characteristic resource endowment of a poverty-stricken area, adhering to market orientation, and making full use of supporting policies (Zhou & Wu, 2021). It can promote the adjustment of agricultural structure and facilitate rural revitalization by developing the planting of various characteristic vegetables, fruits, Chinese medicinal materials, and so on.

Scholars have carried out numerous studies on the development of the high-value crop planting industry (Li et al., 2018; Zhang et al., 2015; Zhao et al., 2019). Some studies have focused on the spatial distribution and evolution of the high-value crop planting industry, aiming at making full use of the resource advantages of different regions and optimizing the overall layout of the planting industry (Qiao & Wang, 2012; Wu, 2018). Another group of researchers have analyzed the multilevel determinants of agricultural diversification towards high-value crops either from the socioeconomic perspective based on household survey (Birthal et al., 2020; Zhang et al., 2015), or from the geographical perspective using remote sensing (RS) and geographical information system (GIS) techniques (Su et al., 2016, 2020b). Others have examined the planting efficiency of high-value crop planting patterns and whether they could effectively help farmers increase income and eliminate poverty (Long & Wang, 2018). However, few studies have systematically considered the environmental impact and comprehensive performance of different production types. In the background of rural revitalization and ecological civilization construction (Hansen et al., 2018; Liu & Li, 2017), the development of high-value crop production not only focuses on its economic growth but also on the premise of the rational use of natural resource protection of the ecological environment (Wang et al., 2022) and exploring the sustainable development pattern that considers both economic profits and environmental sustainability (Wang et al., 2018; Zhang et al., 2019). Therefore, systematic research on different planting systems, revealing their economic benefits, environmental performance and overall sustainability, will contribute to sustainable agricultural development and improvement of the ecological environment. At the same time, this will help effectively connect rural revitalization on the basis of consolidating the achievements of poverty alleviation (Research Group on Rural Revitalization, 2021).

The emergy analysis method put forward by Odum in the 1980s satisfies these requirements very well. Rooted in ecology, thermodynamics, and general systems theory, emergy analysis offers a common denominator for quantifying both economic and environmental contributions to a system (Odum, 1996, 2000). This method considers the attributions of both nature and humans to generate products and services for an economic–environmental system, addressing the weakness of traditional energy analysis that fails in its ability to link work potential, environmental support, and wealth generated in the economy (Amiri, Asgharipour, Campbell, & Armin, 2019; Asgharipour, Amiri, & Campbell, 2020; Su et al., 2020a). As an accounting tool for quantifying the resource use efficiency, environmental cost, and overall sustainability of different planting systems, the emergy method has been widely used to evaluate agricultural systems on different kinds of scales (Amaral, Martins, & Gouveia, 2016; Xie, Huang, Choi, & Shi, 2021). To the best of our knowledge, there are few specific emergy evaluations for different high-value crop planting systems in rural China.

The general aim of this study is to quantify and compare the comprehensive performances of four different planting systems by integrating emergy and economic analyses. To approach this objective, two key issues must be addressed:

1. Are the current planting types conducive for sustainable agricultural development?

2. Which types of planting strike a balance between economic benefit and ecological conservation?

To investigate these issues, this study examined the performance high-value crop planting systems (peony, ginger and sweet potato) and the traditional wheat planting system with respect to their resource utilization, economic profit, and overall sustainability. Then, the best planting types to achieve a balance of economic and environmental benefits were explored, and optimization countermeasures for promoting rural revitalization were proposed.

2. Study area

This study focused on different planting systems in Linquan County, Anhui Province, China (Figure 1). Linquan County covers an area of 1839 km² and is located in the Huang-Huai Alluvial Plain. This region has a subtropical continental monsoonal climate with an average annual temperature of 14.9°C, annual sunshine of 4,553 h, and a mean annual rainfall of 812 mm. Linquan has beneficial natural resources, including flat land, fertile soil, and abundant water resources, which are suitable for various agricultural production. Linquan has always been a major agricultural county in Anhui Province and was once a state-level poverty county. Under the implementation of the ‘one village, one product’ strategy (Yang & Zhang, 2021), Linquan County has developed high-value crop planting industries such as ginger, sweet potatoes, mustard, Chinese medicinal materials, and oil peony. All of those industries have promoted the prosperity of the agricultural market economy, increased farmers’ income and facilitated poverty alleviation. Therefore, Linquan County was selected as a typical case to explore the economic and environmental benefits of different planting systems. The results of this study reveal the potential of different plantation types and provide recommendations for sustainable agricultural development.

Figure 1. Location of the study site and the three high-value crops in the Linquan county, China. From left to right, are peony plantation, ginger plantation, and sweet potato plantation.

3. Materials and methods

3.1. Data preparation

Due to the complicacy of the emergy analysis, the data of this study were derived from different sources, including the local statistical yearbook, government reports, field surveys, agricultural technique handbooks, emergy handbooks, and previous papers. Meteorological data pertaining to annual wind speed, sunshine, and precipitation were collected from the local statistical yearbook. Raw data on the input and output flows of the four planting systems were derived from an investigation of a large planting farmer in Linquan County in 2019. Each input and output item is the annual mean value of a certain production type in Linquan County. It is noteworthy that the wheat, ginger, and peony in Linquan County were all planted once a year, whereas the sweet potato was planted twice a year from March to September and from July to November.

The inputs considered in emergy analysis included seeds or seedlings, chemical fertilizers, pesticides, machines and tools, the labour force, diesel, and so on. Output refers to the various agricultural products of the different planting systems. It should be mentioned that some inputs, such as machine utilization or construction fees, were all converted to annual flows based on their expected useful life when included in the emergy analysis. The corresponding transformities used in emergy accounting were derived from emergy analysis handbooks and previous studies (see Tables 2–5).

3.2. Emergy analysis

Emergy is defined as the total amount of available energy that is directly or indirectly used to generate a service or product, which is expressed as solar emJoules (seJ). The ratio of the emergy required to make a product or service to its present energy is defined as the solar transformity. By multiplying units of energy and its corresponding transformity, we can calculate the emergy of a product or service (Zhang et al., 2011). Emergy analysis converts different forms of energy, resources and services into a unified dimension named emergy, which facilitates the comparison of different production systems by overcoming the difficulty of the ‘energy barrier’ (Fonseca et al., 2019). The main procedures of emergy analysis are described as follows.

3.2.1. Draw system diagrams

Based on Odum’s energy system language (Odum, 1996), the connection between the external energy sources and the internal energy flow, storage, consumption, and output of the whole system is drawn into a summary diagram of energy flow, as shown in Figure 2. The diagram shows the system’s primary energy sources, flows, and all connections among the system’s primary components, with boundaries that define the system’s inputs and outputs. The input of planting systems in Linquan County mainly includes sunlight, wind energy, rainwater, seeds, fertilizers, pesticides, machines and tools, labour, etc.

Figure 2. Emergy system diagram of the planting system in Linquan County, Anhui Province.

3.2.2. Organize emergy accounting tables

Since the main energy flows required to maintain the system are identified, the emergy of various inputs are computed by multiplying the energy content (mass or monetary value) by the relevant transformity (Zhong et al., 2018). The formula is as follows: (1) $\begin{array}{c}\mathrm{Em}=\sum {\int }_i\times \mathrm{transformit}{\mathrm{y}}_i=1\dot{,}\dots \dots ,n\end{array}$(1) where Em represents the total emergy, $f_i$ represents the input flow (energy, materials or monetary), and $\mathrm{transformit}{\mathrm{y}}_i$ denotes the transformity of a specific i flow.

The main input and output of the research system are classified and organized in the emergy accounting table (Zhao et al., 2019). The input of the research system can be divided into four parts: (1) renewable natural resources (RR), such as solar energy, wind, and rain; (2) nonrenewable natural resources (NR), such as soil loss and water consumption; (3) the renewable fraction of purchased resources (FR), such as labour, seedlings, and organic fertilizer; and (4) the nonrenewable fraction of purchased resources (FN), such as chemical fertilizers and pesticides.

The calculation in this study is based on a 15.83E + 24 seJ/yr planetary emergy baseline (Odum, 2000). For natural resources, including sunlight, wind and rain, which are all directly or indirectly from solar energy, only the largest contribution is considered to avoid double accounting (Odum, 1996). All systems were calculated on a unit area of 1 ha to ensure standard comparisons.

Moreover, the water consumption in this study was calculated in the form of standard pollution discharge, using the method revised by Su et al. (2020a) that considers agricultural pollution. Standard pollution discharge can be interpreted as the amount of water required to dilute pollutants in the water in a particular environment to the national standard concentration.

The standard pollution discharge is calculated as follows (Su et al., 2020a): (2) $P_i={\displaystyle \frac{c_i\ast Q}{c{0}_i\ast {10}^6}={\displaystyle \frac{E}{c{0}_i\ast {10}^6}}}$(2) where c_i is the real concentration, c0_i represents the standard concentration of the pollutant in the national surface water environmental quality standard (GB 3838-2002), Q is the volume of polluted water, and E is the amount of actual pollution discharge. The equation of E is as follows: (3) $E=\sum _{i}P{E}_i{C}_i(E{U}_i,\mathrm{S})$(3) where PE_i represents the total amount of pollutant generation, C_i is the runoff coefficient of the pollutant of unit i that is determined by the pollutant type and spatial characteristics (S), and EU_i represents the count of unit i.

3.2.3. Calculate emergy indicators

In this paper, the following emergy indicators are selected to evaluate the benefits and functions of different production systems (Table 1)

Table 1. Emergy flows and emergy indices used in emergy accounting.

Items	Expression
Emergy mass and flows
Local renewable resource inputs, sej/ha	RR
Local nonrenewable resource inputs, sej/ha	NR
Purchased renewable resource inputs, sej/ha	FR
Purchased nonrenewable resource inputs, sej/ha	FN
Total inputs, sej/ha	U = RR + NR + FR + FN
Yield, g/ha	Y
Emergy index
The renewable fraction (%R)	%R = (RR + FR)/U
Emergy yield ratio (EYR)	EYR = Y/(FR + FN)
Emergy investment ratio (EIR)	EIR = (FN + FR)/(RR + NR)
Environmental loading ratio (ELR)	ELR = (NR + FN)/(RR + FR)
Emergy sustainability index (ESI)	ESI = EYR/ELR

The renewable fraction (%R) represents the dependence of the system on renewable resource input. A large value of %R indicates a great dependence of the planting system on renewable resources. The emergy yield ratio (EYR) represents the ratio of emergy input to the economic return of a production system. A higher EYR value indicates a greater ability to exploit local renewable and non-renewable sources by investing economic resources from outside. The emergy investment ratio (EIR) measures the level of economic investment and the dependence of the planting system on the environmental resources. The environmental loading ratio (ELR) index evaluates the potential stress on the local environment due to the overuse of nonrenewable resources, and higher ELR means the system places more pressure on the natural environment. The emergy sustainability index (ESI) measures the sustainability of a system based on the trade-off between emergy advantages and environmental pressure. The higher the value of ESI, the more sustainable the system is.

3.3. Economic analysis

In addition to emergy analysis, traditional economic analysis was applied to explore the economic benefit gap between the high-value crop planting systems (peony, sweet potato, and ginger) and the traditional wheat planting system. Several economic indices were analyzed, such as profit and output-input ratio.

4. Result

4.1. Emergy input structure

4.1.1. Emergy input of each system

Detailed emergy flows of the four planting systems for 2019 are presented in Tables 2–5. Figure 3 provides the input structure of each planting system.

Figure 3. Major emergy inputs for the four planting systems: (A) peony, (B) ginger, (C) sweet potato, (D) wheat.

Table 2. Emergy accounting table of peony planting system (area: 1 ha).

Note	Item	Unit	Annual flow	Renewability factor	Transformity	References	Emergy
Renewable resources from the environment (RR)
1	Sunlight	J	5.00E + 13	1	1	Odum (1996)	5.00E + 13
2	Wind	J	1.13E + 10	1	2.45E + 03	Odum (1996)	2.77E + 13
3	Rain	J	4.00E + 10	1	3.10E + 04	Odum (1996)	1.24E + 15
Total RR							1.24E + 15
Nonrenewable resources from the environment (NR)
4	Soil loss	J	1.64E + 09	0	1.24E + 05	Brandt-Williams (2002)	1.81E + 14
5	Water consumption	J	1.60E + 08	0	2.55E + 05	Bastianoni and Marchettini (2000)	4.07E + 13
Total NR							2.22E + 14
Purchases resources
6	Human labour	J	1.76E + 08	0.9	1.24E + 06	Brown and Bardi (2001)	2.18E + 14
7	Seedling	J	4.50E + 09	0.05	1.15E + 05	Cohen, Brown, and Shepherd (2006)	5.18E + 14
8	Machine and tools	kg	8.00E + 00	0	6.89E + 12	Buranakarn (1998)	5.51E + 13
9	Diesel oil	J	1.43E + 09	0	9.24E + 04	Bastianoni, Campbell, Susani, and Tiezzi (2005)	1.32E + 14
10	Compound fertilizer	g	6.00E + 05	0	4.70E + 09	Liu and Chen (2007)	2.82E + 15
11	Organic fertilizer	g	9.00E + 05	0.23	1.24E + 05	Wang et al. (2017)	1.12E + 11
12	Pesticide	g	7.50E + 04	0	2.49E + 10	Brandt-Williams (2002)	1.87E + 15
Total FR							2.22E + 14
Total FN							5.39E + 15
Total input(U)							7.07E + 15
Yield(Y)
13	peony	J	6.77E + 10		9.25E + 05		6.26E + 16

Table 3. Emergy accounting table of ginger planting system (area: 1 ha).

Note	Item	Unit	Annual flow	Renewability factor	Transformity	References	Emergy
Renewable resources from the environment (RR)
1	Sunlight	J	5.00E + 13	1	1	Odum (1996)	5.00E + 13
2	Wind	J	1.13E + 10	1	2.45E + 03	Odum (1996)	2.77E + 13
3	Rain	J	4.00E + 10	1	3.10E + 04	Odum (1996)	1.24E + 15
Total RR							1.24E + 15
Nonrenewable resources from the environment (NR)
4	Soil loss	J	1.46E + 09	0	1.24E + 05	Brandt-Williams (2002)	1.81E + 14
5	Water consumption	J	7.28E + 08	0	2.55E + 05	Bastianoni and Marchettini (2000)	1.86E + 14
Total NR							3.67E + 14
Purchases resources
6	Human labour	J	2.65E + 09	0.9	1.24E + 06	Brown and Bardi (2001)	3.29E + 15
7	Seedling	J	1.44E + 13	0.05	1.15E + 05	Cohen et al. (2006)	1.66E + 18
8	Machine and tools	kg	1.00E + 01	0	6.89E + 12	Buranakarn (1998)	6.89E + 13
9	Diesel oil	J	9.54E + 08	0	9.24E + 04	Bastianoni et al. (2005)	8.81E + 13
10	Potash fertilizer	g	3.00E + 06	0	1.85E + 09	Brandt-Williams (2002)	5.55E + 15
11	Organic fertilizer	g	2.62E + 06	0.23	1.24E + 05	Wang et al. (2017)	3.25E + 11
12	Pesticide	g	1.35E + 04	0	2.49E + 10	Brandt-Williams (2002)	3.36E + 14
13	Construction deperciation	$	6.40E + 03	0.05	1.07E + 13	Jiang and Chen (1980)	6.85E + 16
Total FR							8.92E + 16
Total FN							1.64E + 18
Total input(U)							1.73E + 18
Yield(Y)
14	ginger	J	1.44E + 11		8.60E + 05		1.24E + 17

Table 4. Emergy accounting table of sweet potato planting system (area: 1 ha).

Note	Item	Unit	Annual flow	Renewability factor	Transformity	References	Emergy
Renewable resources from the environment (RR)
1	Sunlight	J	5.00E + 13	1	1	Odum (1996)	5.00E + 13
2	Wind	J	1.13E + 10	1	2.45E + 03	Odum (1996)	2.77E + 13
3	Rain	J	4.00E + 10	1	3.10E + 04	Odum (1996)	1.24E + 15
Total RR							1.24E + 15
Nonrenewable resources from the environment (NR)
4	Soil loss	J	1.46E + 09	0	1.24E + 05	Brandt-Williams (2002)	1.81E + 14
5	Water consumption	J	6.19E + 08	0	2.55E + 05	Bastianoni and Marchettini (2000)	1.58E + 14
Total NR							3.39E + 14
Purchases resources
6	Human labour	J	4.54E + 09	0.9	1.24E + 06	Brown and Bardi (2001)	5.63E + 15
7	Seedling	J	8.40E + 09	0.05	2.57E + 05	Cohen et al. (2006)	2.16E + 15
8	Machine and tools	kg	8.00E + 00	0	6.89E + 12	Buranakarn (1998)	5.51E + 13
9	Diesel oil	J	1.91E + 09	0	9.24E + 04	Bastianoni et al. (2005)	1.76E + 14
10	Compound fertilizer	g	1.35E + 06	0	4.70E + 09	Liu and Chen (2007)	6.35E + 15
11	Pesticide	g	4.50E + 03	0	2.49E + 10	Brandt-Williams (2002)	1.12E + 14
12	Greenhouse depreciation	$	3.04E + 02	0.05	1.07E + 13	Jiang and Chen (2008)	3.26E + 15
Total FR							5.34E + 15
Total FN							1.24E + 16
Total input(U)							1.93E + 16
Yield(Y)
13	sweet potato	J	1.93E + 11		1.80E + 05		3.47E + 16

Table 5. Emergy accounting table of wheat planting system (area: 1 ha).

Note	Item	Unit	Annual flow	Renewability factor	Transformity	References	Emergy
Renewable resources from the environment (RR)
1	Sunlight	J	5.00E + 13	1	1	Odum (1996)	5.00E + 13
2	Wind	J	1.13E + 10	1	2.45E + 03	Odum (1996)	2.77E + 13
3	Rain	J	4.00E + 10	1	3.10E + 04	Odum (1996)	1.24E + 15
Total RR							1.24E + 15
Nonrenewable resources from the environment (NR)
4	Soil loss	J	1.46E + 09	0	1.24E + 05	Brandt-Williams (2002)	1.81E + 14
5	Water consumption	J	2.52E + 08	0	2.55E + 05	Bastianoni and Marchettini (2000)	6.43E + 13
Total NR							2.45E + 14
Purchases resources
6	Human labour	J	3.02E + 09	0.9	1.24E + 06	Brown and Bardi (2001)	3.74E + 15
7	Seed	J	6.00E + 09	0.05	1.15E + 05	Cohen et al. (2006)	6.90E + 14
8	Machine and tools	kg	5.00E + 00	0	6.89E + 12	Buranakarn (1998)	3.45E + 13
9	Diesel	J	1.91E + 09	0	9.24E + 04	Bastianoni et al. (2005)	1.76E + 14
10	Compound fertilizer	g	9.00E + 05	0	4.70E + 09	Liu and Chen (2007)	4.23E + 15
11	Pesticide	g	6.75E + 03	0	2.49E + 10	Brandt-Williams (2002)	1.68E + 14
Total FR							3.40E + 15
Total FN							5.64E + 15
Total input(U)							1.05E + 16
Yield(Y)
12	wheat	J	1.06E + 11		3.55E + 05		3.76E + 16

With regard to the characteristic peony planting system, the total emergy input was estimated to be 7.07E + 15 sej yr⁻¹, which was the lowest of all examined systems. The compound fertilizers and pesticides constituted a large part of the total emergy input, with values of 2.82E + 15 sej yr⁻¹ and 1.87E + 15 sej yr⁻¹, respectively. Moreover, the peony planting in Linquan County was deduced to be a labour-saving planting type, with a high human labour input of 2.18E + 14 sej yr⁻¹.

The emergy input structure of the ginger planting system was less balanced than that of the other systems (Figure 3). The gross emergy input assigned to the yield was 1.73E + 18 sej yr⁻¹, the highest among the four systems. The ginger planting needed a large amount of seed ginger, which was the largest emergy investment of the system, with a value of 1.66E + 18 sej yr⁻¹. Additionally, this system had a high construction fee and K fertilizer utilization, with values of 6.85E + 16 sej yr⁻¹ and 5.55E + 15 sej yr⁻¹, respectively.

The total emergy that supports the sweet potato planting system was estimated to be 1.93E + 16 sej yr⁻¹. The natural and purchased renewable resources accounted for over 34% of the total emergy input. Since the sweet potato in Linquan County was planted twice a year, the labour force input and compound fertilizer utilization constituted a large part of the total emergy input, with values of 5.63E + 15 sej yr⁻¹ and 6.35E + 15 sej yr⁻¹, respectively. In addition, the depreciation cost for greenhouse construction also contributed greatly, with a value of 3.26E + 15 sej yr⁻¹.

For the traditional wheat planting system, the total emergy flow gathered in this system was 1.05E + 16 sej yr⁻¹. The emergy input of the wheat planting system came mainly from compound fertilizer, labour force, and rain, with values of 4.23E + 15 sej yr⁻¹, 3.74E + 15 sej yr⁻¹, and 1.24E + 15 sej yr⁻¹, respectively.

4.1.2. Comparison of the different input categories of the seven systems

All the inputs of the planting systems can be divided into four parts, including nonrenewable environmental resource emergy (NR), renewable environmental resource emergy (RR), the renewable part of the purchased resource (FR), and the nonrenewable part of the purchased resource.

1. Renewable environmental resources (RR)

Renewable environmental resources (RR) from nature, including sunlight, wind, rain, and other resources, are an essential part of maintaining agricultural planting systems (Chen et al., 2006). The renewable natural resource input of peony, sweet potato, ginger, and traditional wheat plantations accounted for 17.54%, 6.42%, 0.07%, and 11.81% of the total emergy input, respectively. This result indicated that peony planting relied more on renewable environmental resources, while ginger planting used them least.

(2)	Non-renewable environmental resources (NR)

Nonrenewable environmental resources mainly included soil erosion and water resource consumption, which may adversely affect the environment. In this paper, water resource consumption represents equal standard pollution emissions. Therefore, the higher the value is, the more serious the water environment pollution. Due to the overuse of fertilizer and pesticide, the ginger plantation caused the most pollution in the water environment among the four systems (1.86E + 14 sej/ha/yr), which was 2.88 times that of traditional wheat and 4.56 times that of peony cultivation.

(3)	Renewable fraction of purchased resources (FR)

Resources purchased from outside the systems consist of two parts: the renewable fraction of purchased resources (FR) and the nonrenewable fraction of purchased resources (FN). The renewable fraction of purchased resources mainly came from seed, labour force, and organic fertilizers. With a large amount of ginger seed input (Figure 4), the ginger planting system had the highest input of the renewable fraction of purchased resources, with a value of 8.92E + 16 sej/yr. Moreover, the peony plantation was the least labour-intensive system among the four planting systems, with a labour force input of 2.18E + 14 sej/yr.

(4)	Nonrenewable fraction of purchased resources (FN)

Figure 4. Summary diagram of the emergy flows in the four planting systems: (A) peony, (B) ginger, (C) sweet potato, (D) wheat.

Various kinds of chemical fertilizers, pesticides and construction depreciation constituted the nonrenewable fraction of purchased resource input. As shown in Figure 4, the nonrenewable fraction of purchased resources contributed a majority of the total emergy inputs in all the examined systems. Chemical fertilizer input always accounted for a large proportion in both the high-value crop planting systems and the traditional wheat planting system. The chemical fertilizer inputs of the peony, ginger, sweet potato, and wheat planting systems were 2.82E + 15 sej/ha/yr, 5.55E + 15 sej/ha/yr, 6.35E + 15 sej/ha/yr, and 4.23E + 15 sej/ha/yr, respectively. In addition, the sweet potato and ginger plantations had large construction fee inputs, in contrast with other planting systems, with values of 3.26E + 15 sej/ha/yr and 7.16E + 16 sej/ha/yr, respectively.

4.2. Emergy indicators

This paper focuses on different planting systems in Linquan County and analyzes and quantifies the environmental performances of different planting systems through multiple emergy indicators, including the renewable resource percentage (R%), emergy yield ratio (EYR), environmental loading ratio (ELR), and emergy sustainability index (ESI) (Table 6).

Table 6. Emergy indices of four planting systems in Linquan County, China.

Items	Peony	Ginger	Sweet potato	Wheat
%R	20.68%	5.21%	34.06%	44.11%
EYR	11.16	0.07	1.96	4.16
EIR	3.84	1.07E + 03	11.23	6.09
ELR	3.84	18.19	1.94	1.27
ESI	2.91	0.004	1.01	3.28

4.2.1. Renewable resource percentage (%R)

The renewable resource ratio (%R) represents the degree of dependence of the cropping system on renewable resources. The traditional planting system and high-value crop planting systems showed significant differences in %R. The %R of the high-value crop planting systems (peony, ginger, sweet potato) in Linquan County in 2019 was 20.68%, 5.21%, and 34.06% (Table 6), respectively, which was significantly lower than the 44.11% of the traditional wheat plantation. It is worth mentioning that the R% of the ginger planting system was the lowest, owing to the large amount of nonrenewable resource input, including chemical fertilizers, pesticides, and building materials. In contrast, the wheat and sweet potato planting systems could be more secure and sustainable.

4.2.2. Emergy yield ratio (EYR)

The emergy yield ratio (EYR) is used to measure the emergy return on the economic investment. The higher the EYR is, the higher the return of the system under a certain emergy input. As shown in Table 6, the EYR values of the four examined systems varied from 0.07 to 11.16. The characteristic peony planting had the highest EYR value of 11.16, indicating a higher output ratio than the other three systems. In contrast, ginger planting had the lowest EYR value of 0.07, showing that ginger production had the worst return on investment.

4.2.3. Emergy investment ratio (EIR)

The emergy investment ratio (EIR) is the ratio of the emergy input from the economy to the emergy input from the free environmental or natural resources. This index measures the level of economic investment and the dependence of the examined system on the environmental resources (Wang et al., 2014). For a higher EIR, more external purchased inputs are invested; thus, natural free resources make a smaller contribution to production. As shown in Table 6, the EIR of the peony planting system was 3.84, which was slightly lower than that of the wheat planting system (6.09) and sweet potato planting system (11.23) and much lower than that of the ginger planting system (1.07E + 03). That is, too many purchased resources, such as K fertilizer and construction fees, were invested in the ginger planting system, while the other three systems exploited more local environmental resources to gain a high yield (Cheng et al., 2017).

4.2.4. Environmental loading ratio (ELR)

The environmental loading ratio (ELR) refers to the ratio of nonrenewable resources to renewable resources invested in the system. The ELR is directly related to the fraction of renewable resources and can be considered a measure of environmental pressure due to production (Ulgiati & Brown, 1998). A high ELR value indicates high environmental stress, especially when the value is greater than 10. The ELR value of the four planting systems varied from 1.27 to 18.19. While traditional wheat had the lowest pressure on the local environment, with an ELR value of 1.27, ginger production had the highest ELR value of 18.19. Under the assumption that a loading (a nonrenewable investment) is acceptable if it is more or less of the same order of magnitude as the local renewable flows (Zhang et al., 2011), the intensive ginger planting system was far from an acceptable equilibrium with the local environment. Too much relies on purchased nonrenewable resource investment instead of renewable resources from nature in the ginger production process, resulting in high pressure on the local environment. In contrast, wheat production was well integrated within the local set of resources, and there was still potential for further investment to increase production.

4.2.5. Emergy sustainability index (ESI)

The emergy sustainability index (ESI) is the ratio of the environmental loading ratio (ELR) to the emergy investment ratio (EIR). A high ESI value indicates that the system is in benign and sustainable development. According to Table 6, the ESI of the high-value crop planting systems (peony, ginger, sweet potato) were 2.91, 0.004, and 1.01, respectively, and the traditional wheat planting had the highest ESI value of 3.28. The ginger planting system had the lowest ESI value (0.004), which was lower than 1, indicating that this system was in unhealthy development. Although it might obtain high economic benefits in the short term, it would exhaust many resources and generate great pressure on the local environment. In contrast, traditional wheat planting, as well as the characteristic peony and sweet potato planting systems, are in better development and more sustainable.

4.3. Economic analysis

The economic indices of four planting systems in Linquan County, including output/input ratio and profit, were shown in Table 7. The sweet potato planting system had the highest output/input ratio of 4.80, while wheat planting system get the lowest output/input ratio of 1.46. Although ginger plantation system had the highest profit of $5.00E + 04, its out/input ratio was lower than other two high-value crop planting systems due to its high investment on chemical fertilizers and construction fee. The economic benefit of traditional wheat cultivation, by contrast, was one to two orders of magnitude lower than that of high-value crop planting systems.

Table 7. Economic indices of four planting systems in Linquan County, China.

Items	Peony	Ginger	Sweet potato	Wheat
Output/input ratio	2.38	2.35	4.80	1.46
Profit ($)	5.99E + 03	5.00E + 04	1.65E + 04	6.52E + 02

5. Discussion

5.1. Economic and environmental benefits of different planting systems

Analyzing the comprehensive benefits of four different planting systems and exploring the planting types that can consider both economic and environmental benefits is the key to achieving rural revitalization and sustainable agricultural development. In this study, emergy and economic analyses were applied to explore the differences among different planting systems from the perspectives of economic benefits, environmental impact and overall sustainability. The trade-off conceptual diagram (Figure 5) that taking the sustainability index ESI as the X axis and economic benefit as the Y axis, could also aid in discussing the comprehensive behaviour in economic and environmental benefits of different planting systems.

Figure 5. The conceptual trade-off of economic benefits and environmental impacts of four planting systems. The position of the four planting systems on the x-axis shows the environmental sustainability (ESI), while the y-axis shows the economic benefits of each system.

In the process of precise poverty alleviation, high-value crop planting systems bring more economic profits to farmers, with economic benefits one to two orders of magnitude higher than that of traditional wheat planting (Qiu & Wu, 2021; Su et al., 2019; Zhou et al., 2018). Additionally, characteristic plantations have comparative advantages, such as increasing the quantity and quality of vegetables and improving dietary structure in terms of social benefits (Ge et al., 2019; Tieskens et al., 2017). However, the highest ELR, lowest R%, and lowest ESI values indicated that the ginger planting system in Linquan county are far less sustainable than other three planting systems despite the highest economic profit. The production process of ginger planting relied too much on purchased nonrenewable resource investment instead of natural resources, rendering less stability and sustainability of the system in the face of changes in the availability and price of raw materials for production (Ma & Wu, 2019). Moreover, the overuse of chemical fertilizers, construction materials, and pesticides would lead to more pollution and environmental pressure (Su et al., 2020a).

The 2030 Agenda for Sustainable Development states that realizing sustainable development goals must consider economic, social and ecological dimensions (Zhao et al., 2022). In that way, the sweet potato planting system and the peony planting system had better comprehensive behaviour among the four planting systems, with relatively high economic and environmental benefits. However, sweet potato cultivation requires the input of plastic film, and the plastic residuals remaining in the soil could generate a large amount of nondegradable and minimally recyclable waste, which may be discharged through incineration, landfill leaching, or microplastic residues polluting the environment (Chae & An, 2018).

In contrast, peony plantations in Linquan County are often combined with the photovoltaic industry. Photovoltaic power generation is one of the targeted poverty alleviation projects in China and has the potential to lower carbon emissions and alleviate environmental impacts (Han et al., 2020; Li, 2019; Zhang et al., 2018). The agriculture–photovoltaic complementary system that integrates food, water and energy together not only satisfies crop production and saves water resources but also promotes energy production (Farfan et al., 2019). Scholars have found that agricultural systems are a major driver of climate change, the carbon emissions coming from agriculture must be reduced so as to limit global warming well below 2 °C as stipulated in the Paris Agreement (Carlson et al., 2017; Laborde et al., 2021). Solar energy plays a critical role in contributing to the alternative energy mix to mitigate climate change and meet policy milestones (Hoffacker et al., 2017). The farm light complementary photovoltaic power station in Linquan county can made the average annual power generation of 21.88 million KWH, which can save nearly 6619 tons of standard coal for the country every year and reduce nearly 18,202 tons of carbon dioxide emissions. Furthermore, the economic benefits of the agriculture–photovoltaic complementary system can be increased by 30% compared to traditional agricultural systems (Dinesh & Pearce, 2016). Therefore, peony planting could be a better and sustainable system to achieve a win–win situation considering the synergistic development of photovoltaic power generation.

5.2. Policy implications

To consolidate the achievements of poverty alleviation and promote rural revitalization strategy, agricultural development must consider both the ‘farmer’s wealthy life’ and ‘ecological environmental beauty’. Crop yield growth and rural economic development must be based on the premise of protecting and improving the local environment (Research Group on Rural Revitalization, 2021; Ye, 2018). To achieve a ‘win–win’ situation between economic benefits and ecological environmental protection, we propose the following suggestions.

First, local governments must guide and promote the development of planting system with high ecological sustainability, especially the synergistic development of peony plantation and photovoltaic power that can contribute to mitigate climate change and meet policy milestones (Qiu & Wu, 2021). Since farmers’ land use decisions mainly consider the economic profit instead of environmental benefits, ginger plantation would be more likely selected by farmers without government policy orientation.

Second, the large-scale development of the high-value crop planting industry should be promoted. In the context of the household responsibility system, small and scattered land parcels have limited the improvement of agricultural efficiency and competitiveness and have led to the excessive use of chemical fertilizers (Su et al., 2020b; Wu et al., 2018). Therefore, it is necessary to promote the large-scale development of the high-value crop planting industry(Gaitán-Cremaschi et al., 2020), create advantageous areas for characteristic agricultural products and modern agricultural industrial parks, establish a supporting system for the high-value crop planting industry, guide the agglomeration of supporting services and related enterprises, and realize and increase competitiveness by project concentration and function integration.

Finally, targeted subsidies could be provided for ecofriendly planting behaviours. By measuring the environmental impact of different production types and formulating a series of sustainability criteria, such as soil degradation prevention, fertilizer and pesticide application control, energy saving, plastic waste recycling (Antwi-Agyei et al., 2023; Mungkung et al., 2022; Zhi et al., 2022). And differentiated subsidies could be provided according to the environmental behaviour of different planting systems.

5.3. Limitations and prospect

This research demonstrates a feasible methodology to assess the comprehensive benefits of different agricultural planting systems from the perspective of resource utilization, environmental performance, and the overall sustainability. Nonetheless, the current research still has some limitations that should be considered in the future. Firstly, we only focus on four single systems and the performance of a combination of several planting systems remains unknown. Secondly, this study covers a very short temporal period due to the data availability. Further studies could extend the temporal scope and quantify the dynamic changes of emergy fluxes in these systems.

6. Conclusions

Exploring and developing planting formats with high economic benefits and low environmental pressure is the key for agricultural upgrading in the context of rural revitalization. Integrating emergy assessment and economic analysis, this study examined the comprehensive benefits of the traditional wheat planting system and three high-value crop planting systems, including ginger, sweet potato, and peony planting. Economic indicators were applied to assess the economic profit of different planting systems, and emergy analysis was used to evaluate their environmental performance from the perspective of resource utilization, environmental pollution, and overall sustainability. The main conclusions can be summarized as follows:

1. In contrast to the traditional wheat planting system, which relies more on natural resources, high-value crop planting systems intensify the input of purchased nonrenewable resources and lead to high environmental stress and low sustainability. Of these, the ginger planting is the least sustainable system with the lowest R%, highest ELR and lowest ESI values.

2. With regard to economic benefits, the three high-value crop planting systems provide more competitive economic profits that are one or two orders of magnitude higher than that of wheat planting per hectare. These high-value crop planting systems brought wealth for local farmers and aided in alleviating poverty in Linquan County.

3. Peony planting and sweet potato planting are considered promising approaches under the trade-off of economic benefit and environmental performance. Peony planting could be a better type for achieving sustainable agriculture considering the synergistic development of photovoltaic power generation.

4. We propose several suggestions for the promotion of such environmentally sound patterns, including increasing policy support, promoting large-scale development, formulating the sustainability criteria and providing targeted subsidies.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was support by the National Natural Science Foundation of China (Grant Nos. 42201281, 42001201, 42271060, and 32201346), the Natural Science Foundation of Anhui province (Grant Nos. 2208085MD91 and 2208085QD102), and the Introducing and Stabilizing Talent Project of Anhui Agricultural University (Nos. yj2020-47 and rc402201)).