Assessment of Climate Adaptability in the Late-Maturing Citrus Industry in Sichuan Province

Abstract

Sichuan Province is the largest inland area for late-maturing citrus fruit production in China, and its climate conditions are a primary consideration for the cultivation of late-maturing citrus fruits. Based on meteorological data from 2010 to 2020 for the 18 prefecture-level cities and autonomous prefectures in Sichuan Province that cultivate late-maturing citrus fruits, along with the traditional method of dividing the advantages of citrus and the calculation of comparative advantage using factor endowment coefficients, we identified the annual average temperature, annual accumulated temperature ≥ 10 °C, average temperatures in July and January, annual precipitation, and annual sunshine hours as input indicators. We selected the resource endowment coefficient as the output indicator and used the DEA–Malmquist index model to evaluate the climate adaptability of Sichuan’s late-maturing citrus fruit industry. The analysis results indicate that the overall climate conditions in Sichuan are suitable for the growth of late-maturing citrus fruits. However, extensive cultivation of similar varieties has led to a decline in resource endowment across different regions. The use of arable land for cultivating late-maturing citrus fruits has also reduced climate adaptability. Policies that contradict climate adaptability do not support sustainable development within Sichuan’s late-maturing citrus fruit industry.

1. Introduction

The citrus industry is a cornerstone of agricultural production in rural areas of China and represents the primary fruit industry in Sichuan Province [1]. Since 2010, the late-maturing citrus sector in Sichuan has undergone rapid expansion. By the end of 2020, the cultivation area for late-maturing citrus fruits had reached 173.42 thousand hectares, constituting over 60% of the national cultivation area for such fruits. The output exceeded 2.1 million tons, ranking first nationwide (data source: “Agricultural Science and Technology Trends” 2021, Volume 3, published by Sichuan Academy of Agricultural Sciences: Impact of Frost and Snow Damage on Late-maturing Citrus Fruits in Sichuan Province and Recommendations for Mitigation Measures). Among Sichuan’s 20 prefecture cities and autonomous prefectures known for late-maturing citrus cultivation, 18 are primarily dedicated to growing late-maturing citrus fruits. The predominant cultivar types include hybrid citrus/mandarin oranges (such as ‘Eiyuu 38’, ‘Harvest’, ‘Shiranuhi’, ‘Genpi’, and ‘Woqing’) and orange varieties (Tarocco Blood Orange and its selected strains) as well as mid-to-late-maturing orange types that are cultivated using techniques that leave the fruits on trees until the following year for harvesting (e.g., ‘Navel Orange’ and ‘Valencia Orange’) [2].

Climatic conditions are the top consideration for late-maturing citrus cultivation, with temperature, light, and precipitation being key meteorological factors that directly affect the quality of citrus fruits. The suitability of a place for late-maturing citrus cultivation is mainly evaluated through citrus regional classification. Scholars have mainly analyzed the climatic conditions for citrus growth from the perspectives of irrigation water requirements [3,4,5,6], light, and heat [7], and they have used methods such as the analytical hierarchy process for citrus regional classification [8,9,10]. China’s citrus regional classification began in the late 1980s, and the National Citrus Regional Classification Coordination Group conducted the first national citrus production regional classification in China using the annual heat accumulation, annual average temperature, January average temperature, extreme temperature, and occurrence frequency as the main indicators [11]. In 2003, the Ministry of Agriculture and Rural Affairs formulated the “Citrus Advantage Region Development Plan”, designating the Sichuan citrus production area as the “Three Belt One Base” Yangtze River Upper and Middle Reaches Sweet Orange Belt Advantage Zone [12]. In the late 20th century, the Institute of Citrus, Chinese Academy of Agricultural Sciences, and scholars from Sichuan Province also conducted a comprehensive planting advantage zone division for the Sichuan citrus industry [13], but the aforementioned planning was mainly targeted at the then-widely promoted medium-ripening citrus varieties with maturity concentrated from October to December. Late-maturing citrus has different light and heat requirements, with the late-maturing/late-harvested fruits in particular having strict requirements for winter low temperatures and the following spring’s high temperatures. The above-mentioned regional division is no longer suitable as a guideline for the development of the late-maturing citrus industry. In 2021, Wang Xun and others used GIS spatial analysis technology to calculate the values of each climate element based on the meteorological data from 145 weather stations in Sichuan Province from 1981 to 2010 and used the Delphi method to determine the weight of regional division indicators. Combining the risk area division of two main meteorological disasters, winter frost and spring high temperature, they obtained a regional division map of the climatic suitability of late-maturing citrus at the municipal and county level [14].

In practical late-maturing citrus cultivation, the 18 prefecture-level cities and autonomous prefectures in Sichuan engaged in late-maturing citrus production have not implemented a planting layout based on municipal districts, prefecture-level cities and autonomous prefectures, and autonomous prefecture-level cities and autonomous prefectures. They have overlooked the suitability of the local climate and other natural conditions for citrus growth, opting instead to cultivate the same late-maturing citrus variety across entire prefecture-level cities or autonomous prefectures. This indiscriminate expansion of citrus production beyond market demand has resulted in subpar fruit quality and reduced consumer demand and has ultimately led to overcapacity within the local citrus industry. Consequently, this has caused a decline in income for fruit farmers without effectively guiding regional division for optimal late-maturing citrus cultivation practices [15].

In order to underscore the pivotal role of climate conditions and other natural resources in citrus production, as well as to address the issue of homogeneous competition in late-maturing citrus cultivation, some scholars have recently advocated for assessing the comparative advantages of developing the citrus industry in a particular region through a comparison of “resource endowment”. The theory of resource endowment originated in the early 20th century when Swedish economists Heckscher and Ohlin disregarded differences in production technology between countries and explained that variations in factor endowments were responsible for disparities in international trade [16]. According to the Heckscher–Ohlin hypothesis, factor endowment refers to the resources possessed by a country, also known as resource endowment [17]. The development strategy of a region should be based on its resource endowment, focusing on products and industries with comparative advantages [18]. Resource endowment analysis in agricultural development primarily utilizes the resource endowment coefficient (EF_it) as an evaluation index [19]. Scholars such as Deng Xiuxin [20], Qi Chunjie [21], Xiang Yun [22], and Tang Dacheng [23] have employed resource endowment coefficients to study comparative advantages in citrus production across China as well as in regions including Hunan, Chongqing, and Guangxi.

The resource endowment coefficient places greater emphasis on economic efficiency and does not incorporate key meteorological factors as indicators in its calculation method. As a result, the specific method for citrus regional division does not utilize the resource endowment coefficient but instead relies on expert scoring and overlay methods [19,24]. In these approaches, the determination of weights is susceptible to human interference, leading to significant differences in regional division results based on varying indicator weights. In recent years, scholars have applied the DEA–Malmquist model to calculate total factor productivity across different industries [25,26,27,28,29,30]. This approach eliminates the need for determining indicator weights and effectively mitigates the adverse effects of subjective weighting. It excels in addressing issues related to multi-input, multi-output efficiency measurement and provides an objective and effective means of handling non-expected outputs such as environmental impact factors [31].

In consideration of this, the present study seeks to achieve an effective integration of citrus regional division and resource endowment coefficients. It uses key meteorological factors in traditional citrus regional division as input indicators and resource endowment coefficients for the late-maturing citrus industry as output indicators. The DEA–Malmquist model is employed to assess the climate adaptability of 18 prefecture-level cities and autonomous prefectures for late-maturing citrus cultivation in Sichuan from 2010 to 2020. This evaluation aims to provide new methodological insights and practical guidance for the scientific and rational spatial layout of late-maturing citrus cultivation.

2. Materials and Methods

2.1. Study Area Overview

Sichuan Province is located in the southwestern part of China, between 92°21′–108°33′ E and 26°03′–34°19′ N, with great differences in landscape from east to west and complex terrain. The climate is clearly zonal and vertical. According to the natural geographical division, Sichuan Province can be divided into three parts: the Sichuan Basin, Northwest Sichuan Plateau, and Southwest Sichuan Mountains. Of these, the Sichuan Basin has good heat conditions, with warm and humid weather all year round, small temperature differences between day and night, large temperature differences between year and year, warm winters and hot summers, and short sunshine time. The Northwest Sichuan Highland Plateau has a cold temperate climate, with dry and warm valleys and cold and wet mountains, cold winters and cool summers, insufficient water and heat, and abundant sunshine. The Southwest Sichuan Mountains have a higher temperature all year round, a larger temperature difference between day and night and a smaller temperature difference between year and year, it is cold in the morning cold and warm at midday, with no clear seasons, long sunshine time and less rainfall, with a clear dry and wet season [18,32]. Based on the actual planting situation of late-maturing citrus in Sichuan Province, this study selected 18 prefecture-level cities and autonomous prefectures, including Chengdu, Zigong, Liuzhou, Deyang, Mianyang, Guangyuan, Suining, Neijiang, Leshan, Nanchong, Meishan, Yibin, Guang’an, Dazhou, Ya’an, Bazhong, Ziyang, and Liangshan, as the study area. By the end of 2020, the study area had a late-maturing citrus planting area of 173.42 square kilometers, accounting for 100% of the total late-maturing citrus planting area in Sichuan Province, and there was a yield of 2.1 million tons, accounting for 100% of the total yield of late-maturing citrus in Sichuan Province (the production and planting area data of late-maturing citrus fruits were derived from the Sichuan Statistical Yearbook 2021, with the proportions calculated by the author). From 2010 to 2020, the study area had an average annual temperature of 18 °C, an average annual precipitation of 1098 mm, and an average annual sunshine duration of 1209 h (the annual mean temperature, annual precipitation, and annual sunshine hours of the study area from 2010 to 2020 were obtained from the Sichuan Statistical Yearbook 2011–2021, and the annual sunshine hours of the study area from 2019–2020 were obtained from the Statistical Yearbook of Sichuan Provinces 2020–2021). A division map of the study area is shown in Figure 1.

2.2. Sources of Data

This study obtained meteorological data, including the planting area, yield, and revenue of late-maturing citrus from the statistical yearbook column of Sichuan Provincial Statistical Bureau (website for the materials: https://tjj.sc.gov.cn/scstjj/c105855/nj.shtml, accessed on 15 December 2023). The dataset also encompassed annual average temperature, annual accumulated temperature ≥ 10 °C, average temperatures for July and January, annual precipitation, and annual sunshine hours. Missing data from the Sichuan Provincial Statistical Yearbook were retrieved from the statistical yearbook columns of various prefecture-level cities and autonomous prefectures. All data covered the period from 2010 to 2020.

2.3. Research Methodology

2.3.1. Resource Endowment Coefficient

According to scholars such as Zhu Dawei [33], Ma Huilan [34], Zhu Fanglin [35], and Hu You [36], the resource endowment coefficient in the agricultural industry is generally calculated by comparing the share of a specific resource within a country or region at a higher level of regional division to its share in the overall value of that resource at the same higher level of regional division. The calculation formula is as follows:

$$E{F}_{it}=\frac{V_{it}/V_i}{Y_{it}/Y_i}$$

(1)

In Formula (1), $E{F}_{it}$ denotes the resource endowment coefficient for late-maturing citrus production in region $i$ at time $t$, while $V_{it}$ and $Y_{it}$ represent the late-maturing citrus yield and agricultural output in region $i$ at time $t$. Furthermore, $V_i$ and $Y_i$ signify the yield and agricultural output of the higher-level region in region $i$ at time $t$. If 0 < $E{F}_{it}$ < 1, it indicates that the region’s late-maturing citrus production lacks a resource endowment advantage; if 1 ≤ $E{F}_{it}$ < 2, it suggests that the region’s late-maturing citrus production possesses a resource endowment advantage; if $E{F}_{it}$ ≥ 2, then it signifies that the region’s late-maturing citrus production has a strong resource endowment advantage.

2.3.2. Climate Suitability Classification

Analysis of Climatic Conditions Suitable for the Growth of Late-Maturing Citrus Fruits

(1) Temperature. Citrus fruits thrive in warm and humid climates, and temperature is a critical determinant of their distribution and growth. Late-maturing citrus varieties have particularly stringent temperature requirements. Firstly, they necessitate sufficient heat accumulation. Heat deficiency is a primary limiting factor for late-maturing citrus cultivation, with late-maturing varieties requiring a minimum of 4000 degree-days above 10 °C for optimal growth [14]. Secondly, specific requirements exist for the minimum winter temperatures. Late-maturing citrus must be safeguarded against frost damage during the winter, with the average minimum temperature in the coldest month not falling below 5 °C and extreme low temperatures needing to be higher than −2 °C to ensure safe overwintering of the fruit [37]. Thirdly, there are upper limits for summer high temperatures. The optimal temperature range for late-maturing citrus growth is 24–28 °C; when temperatures rise to 35 °C, short-term heat stress can occur, while temperatures exceeding 38 °C will completely halt tree growth [38].

(2) Moisture. Environmental moisture conditions significantly influence the size, juice yield, and flavor profile of citrus fruits. A relatively humid ecological setting is more conducive to the growth of late-maturing citrus fruits. Late-maturing citrus cultivation necessitates an annual precipitation of over 1000 mm [39], as inadequate rainfall can lead to small fruit and inferior flavor. Furthermore, annual precipitation should not surpass 1500 mm [40], as excessive rainfall can result in a bland fruit flavor and susceptibility to fruit splitting.

(3) Light Exposure. Adequate light exposure is essential for promoting the growth and improving the fruit quality of late-maturing citrus trees, although excessive light intensity can also lead to pathogenic issues. Late-maturing citrus trees thrive best with a daily sunshine duration of 1200–1500 h [13]. Excessive light exposure, particularly during summer, can result in sunburn damage on the fruit’s sun-facing skin due to strong light stress and high temperature stress. This damage manifests as yellow-brown patches, and in severe cases, it can cause the formation of “hard scars” on the fruit with a spongy texture in the flesh, rendering it unsuitable for consumption.

Classification of Climate Adaptability for Late-Maturing Citrus Industry

Incorporating the research methodologies of scholars such as Wang Xun [14] and Liu Wu [41], and taking into consideration data availability, this study identified six key meteorological factors for assessing the climate adaptability of late-maturing citrus industry in Sichuan. These factors included the annual average temperature, annual accumulated temperature ≥ 10 °C, average temperature of July, average temperature of January, annual precipitation, and annual sunshine hours. Each variable was classified into four levels: most suitable, suitable, sub-suitable, and unsuitable, with corresponding scores of 5, 4, 3, and 2. The specific grade classification standards are detailed in

Table 1. Classification standards for the climate adaptability level of late-maturing citrus in Sichuan province.

Variable	The Most Suitable	Suitable	Sub-Suitable	Unsuitable
Average annual temperature/°C	(16.5,17.5]	(15.5,16.5] or (17.5,18.5]	(13,15.5] or (18.5,21]	(-∞,13] or (21,+∞)
Accumulated temperature ≥ 10 °C/°C	(5500,6000]	(5000,5500] or (6000,6500]	(4500,5000] or (6500,7000]	(-∞,4500] or (7000,+∞)
Average July temperature/°C	(25.5,27]	(24,25.5] or (27,28]	(21,24] or (28,30]	(-∞,21] or (30,+∞)
Average January temperature/°C	(5,7]	(3,5] or (7,9]	(−2,3] or (9,12]	(-∞,−2] or (12,+∞)
Annual precipitation/mm	(900,1100]	(800,900] or (1100,1300]	(700,800] or (1300,1500]	(-∞,700] or (1500,+∞)
Annual sunshine hours/h	(1000,1200]	(900,1000] or (1200,1500]	(800,900] or (1500,1800]	(-∞,800] or (1800,+∞)

.

Classification criteria: The temperature-based criteria were based on the literature [14,37,38], the water classification criteria were derived from the literature [39,40], and the light classification criteria were drawn from the literature [13,41] and the author’s relevant research.

In the production of late-maturing citrus, soil quality and pest prevalence exert a significant influence on fruit quality and can serve as indirect indicators of the climatic conditions in citrus-cultivating regions. However, after conducting an extensive literature review and years of field research, it has been observed that in various prefecture-level cities and autonomous prefectures in Sichuan Province, the soil conditions are often enhanced through the application of fertilizers. In order to improve the sweetness, smoothness, diameter, and resistance to citrus yellow shoot and other citrus diseases in late-maturing citrus fruits, some growers have been found to contravene government and industry regulations by employing substantial quantities of pesticides. This situation has rendered it challenging to accurately quantify fertilizer and pesticide usage for late-maturing citrus in Sichuan Province using scientific methods; hence, these parameters were not included in this study.

2.3.3. DEA–Malmquist

The DEA was introduced in 1978 by American operations research researchers A. Harris and W.W. Cooper [42]. Let there be n decision units, with each characterized by m input variables $x_{1j},x_{2j},\cdots ,x_{mj}$, and s output variables $y_{1j},y_{2j},\cdots ,y_{sj}$ (where $x_{ij}$ > 0, $y_{rj}$ > 0, $i=1,2,\cdots ,m$; $r=1,2,\cdots ,s;j=1,2,\cdots ,n$), with ${\lambda }_j$ representing the weight vector between the inputs and outputs of each decision-making unit. In the BCC model, every $DM{U}_j$ is assigned an efficiency evaluation index $\theta$. For $DM{U}_{j0}$, its optimal input–output efficiency model is presented in Formula (2).

$$\left\{\begin{array}{c}\begin{array}{c}\min \theta \\ s.t.\end{array}\\ {\displaystyle \sum _{j=1}^n{\lambda }_j{y}_j\le {\theta }_{x0},}\\ {\displaystyle \sum _{j=1}^n{\lambda }_j{y}_j\le y_0,}\\ {\displaystyle \sum _{j=1}^n{\lambda }_j=1,}\end{array}\right.$$

(2)

In Formula (2), ${\lambda }_j<0,j=1,2,\cdots n$. In the DEA model, the relative efficiency value is distributed within the interval of (0,1], and a DMU located on the boundary is considered as an effective combination with a value of 1.

The traditional DEA model captures the efficiency value of different decision-making units at a specific point in time, making it suitable for cross-sectional data and belonging to static analysis [43]. However, the Malmquist dynamic index analysis method can effectively address the limitations of the traditional DEA model by reflecting changes in production efficiency over different periods. Therefore, this study employed the DEA–Malmquist index method to investigate the variations in climate resource utilization efficiency in late-maturing citrus planting in Sichuan, as demonstrated by Formula (3).

$$\begin{array}{c}M=\frac{D_0^t(x^{t+1},y^{t+1})}{D_0^t(x^t,y^t)}{\left[\frac{D_0^t(x^{t+1},y^{t+1})}{D_0^{t+1}(x^{t+1},y^{t+1})}\times \frac{D_0^t(x^t,y^t)}{D_0^{t+1}(x^t,y^t)}\right]}^{\frac{1}{2}}=effch\times tech\\ tfpch=effch\times tech=pech\times \mathrm{sech}\times tech\end{array}$$

(3)

In Formula (3), M represents the input vector and output vector of the decision-making unit in period t. The Malmquist index (tfpch) measures the climate resource utilization efficiency of citrus planting from period t to period t + 1. When M > 1, it indicates an improvement in the climate resource utilization efficiency; when M < 1, it indicates a decline in the climate resource utilization efficiency [44]. tfpch can be decomposed into integrated technical efficiency (effch) and technical progress efficiency (tech). effch represents the degree of change in the technical efficiency of climate resource utilization in a certain period. When effch > 1, it indicates an improvement in the technical efficiency; when effch < 1, it indicates a decline in the technical efficiency. tech is used to measure the degree of technological innovation or progress. When tech > 1, it indicates technological progress; when tech < 1, it indicates a slowdown in the technological progress. effch can be further decomposed into scale efficiency change (sech) and pure technical efficiency change (pech). sech reflects the changes in the climate resource utilization efficiency with the scale of input, and pech reflects the changes in the management level [45,46].

In view of the DEA’s requirement that the number of DMUs should be at least twofold greater than the product of the number of input and output indicators or the threefold sum of the number of input and output indicators [47,48], one output index and six input indicators were selected and deflated through the corresponding price index, as shown in

Table 2. Climate adaptability assessment index system for late-maturing citrus industry in Sichuan Province.

Type of Indicator	Content of Indicator
Indicator of output	$E{F}_{it}$
Index of inputs	Grade score for annual average temperature suitability
	Suitable grade score of accumulated temperature ≥ 10 °C
	Rating score for July’s average temperature suitability
	Rating score for January’s average temperature suitability
	Requisite grade score for annual precipitation
	Appropriate grading criteria for annual sunshine hours

.

Among the selected evaluation metrics, the output indicator was the resource endowment coefficient. Its calculation method and all input indicators exhibited no correlation or duplication, aligning with the requirements of the DEA–Malmquist index method for indicator relationships [25,26]. The evaluation period spanned from 2010 to 2020, encompassing 18 DMUs with a sample size of 198, exceeding 100 and meeting the sample size criteria for performance assessment [27].

3. Results

3.1. The $E{F}_{it}$ in the Late-Maturing Citrus Industry in Sichuan Province

The $E{F}_{it}$ of late-maturing citrus production in the 18 prefecture-level cities and autonomous prefectures in Sichuan is shown in

Table 3. Late-maturing citrus production in various prefecture-level cities and autonomous prefectures in Sichuan Province.

	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	Index Fluctuations	Years with EFit > 1	Mean Value
Chengdu	1.16	1.18	1.15	1.22	1.22	1.22	1.12	1.37	1.18	1.16	1.24	↑	11	1.20
Zigong	1.56	1.55	1.57	1.57	1.60	1.61	1.61	1.73	1.66	1.49	1.56	=	11	1.59
Luzhou	0.39	0.38	0.41	0.44	0.47	0.49	0.50	0.50	0.50	0.51	0.52	↑	0	0.46
Deyang	0.31	0.31	0.28	0.32	0.31	0.31	0.30	0.25	0.24	0.27	0.26	↓	0	0.29
Mianyang	0.48	0.46	0.45	0.41	0.43	0.42	0.40	0.23	0.23	0.26	0.25	↓	0	0.37
Guangyuan	0.76	0.81	0.78	0.83	0.82	0.81	0.76	0.63	0.63	0.51	0.25	↓	0	0.69
Suining	0.27	0.25	0.25	0.29	0.28	0.30	0.28	0.28	0.31	0.30	0.28	↑	0	0.28
Neijiang	1.58	1.49	1.40	1.46	1.44	1.46	1.39	1.43	1.43	1.49	1.56	↓	11	1.47
Leshan	0.65	0.67	0.65	0.64	0.60	0.56	0.52	0.54	0.55	0.45	0.47	↓	0	0.57
Nanchong	1.47	1.44	1.36	1.33	1.30	1.25	1.20	1.06	1.06	1.15	1.16	↓	11	1.25
Meishan	3.52	3.51	3.38	3.40	3.56	3.56	3.66	4.07	4.05	4.32	4.44	↑	11	3.77
Yibin	1.51	1.45	1.48	1.47	1.43	1.43	1.37	1.18	1.29	1.29	1.24	↓	11	1.38
Guangan	1.01	1.04	1.02	1.00	1.00	0.96	0.93	0.82	0.81	0.78	0.76	↓	3	0.92
Dazhou	0.82	0.80	0.80	0.78	0.75	0.74	0.73	0.67	0.66	0.70	0.71	↓	0	0.74
Yaan	0.35	0.36	0.46	0.57	0.62	0.72	0.71	0.75	0.79	0.64	0.65	↑	0	0.60
Bazhong	0.22	0.25	0.25	0.31	0.30	0.29	0.28	0.28	0.27	0.24	0.25	↑	0	0.27
Ziyang	2.08	1.99	2.13	1.75	1.89	2.00	3.34	3.26	3.67	4.89	4.84	↑	11	2.89
Liangshan	0.09	0.09	0.10	0.10	0.11	0.10	0.10	0.11	0.12	0.12	0.13	↑	0	0.11

.

According to the analysis of Table 3, during the investigation period, significant issues of escalating homogenized competition and low-level duplication were observed in late-maturing citrus production across the 18 prefecture-level cities and autonomous prefectures in Sichuan province. These challenges primarily manifested as follows: First, more than 60% of the prefecture-level cities and autonomous prefectures did not have the resource endowment advantage of late-maturing citrus production. The observation of the average value found that the $E{F}_{it}$ of citrus production in Meishan (3.77) was above 3.0 in all years, and the $E{F}_{it}$ of late-maturing citrus production in Ziyang (2.89) was less than 2.0 for only three years, showing the strong resource endowment advantage of the above two cities; Zigong (1.59), Nejiang (1.47), Yibin (1.38), Nanchong (1.25), and Chengdu (1.20) had a certain resource endowment advantage, but the other 11 prefecture-level cities and autonomous prefectures lacked the resource endowment advantage of late-maturing citrus production, among which Liangshan (0.11) ranked the last in all years. Second, half of the prefecture-level cities and autonomous prefectures showed a declining trend of resource endowment to varying degrees. Among the eight prefecture-level cities and autonomous prefectures with increased $E{F}_{it}$, the value in Ziyang increased from 2.08 to 4.84 and has stayed above 2.0 since 2015, making it the only county with an increase in $E{F}_{it}$ greater than 1.0. Among the nine prefecture-level cities and autonomous prefectures with decreased $E{F}_{it}$, the value in Guangan decreased from 1.01 to 0.76 and has decreased year by year since 2015, making it the only county that changed from having resource endowment to losing resource endowment. The value in Guangyuan decreased from 0.76 to 0.25, which is the largest decrease. Third, the $E{F}_{it}$ of citrus production in the key and non-key prefecture-level cities and autonomous prefectures of Sichuan’s late-maturing citrus industry was quite different. In terms of the average (In 2016, Sichuan Province designated Chengdu, Zigong, Luzhou, Neijiang, Leshan, Nanchong, Meishan, Guang’an, Dazhou, Ziyang, and Liangshan as key prefecture-level cities and autonomous prefectures for the development (support) of the citrus industry in the province. This was outlined in the “Action Plan for Promoting Agricultural Supply-side Structural Reform and Accelerating Innovative and Green Development of Sichuan Agriculture” (Sichuan Provincial Party Committee Office Circular [No. 174] of 2016).), the average $E{F}_{it}$ of late-maturing citrus production in 11 key prefecture-level cities and autonomous prefectures of the late-maturing citrus industry was 1.36, and the average $E{F}_{it}$ of late-maturing citrus production in 7 non-key prefecture-level cities and autonomous prefectures was 0.45.

The resource endowment deficiency or decline resulting from the large-scale and rapid expansion of cultivation has been empirically confirmed in practical research. In 2020, the planting area of late-maturing citrus in Sichuan exceeded the provincial target by 5.17 thousand hectares. However, there remained a deficit of 110,000 tons in production compared to the standard. The primary contributing factor to this disparity was attributed to the expansion of late-maturing citrus cultivation in Nanchong, Leshan, Neijiang, Guangan, Suining, and other prefecture-level cities that have yet to yield fruit or reach peak production. Consequently, both the existing planted areas and potential yields have not been accounted for within the statistical data.

As such, whether considering current late-maturing citrus planting areas or future yields, the actual situation of Sichuan’s late-maturing citrus industry significantly surpassed the provincial targets. In 2020 alone, the three prefecture-level cities designated as “China’s late-maturing Citrus Hometown”—Meishan, Nanchong, and Leshan—boasted actual planting areas exceeding 66.70 thousand hectares each, significantly surpassing the official statistics and continuing to grow [49].

By the end of 2017, Nanchong had proposed plans to establish a “200 million mu (13.3 million hectares) late-maturing Citrus Base” and provided substantial subsidies for orchard establishment. In the period from 2017 to 2020, Nanchong expanded its late-maturing citrus planting area by over 46.49 thousand hectares. However, the low level of cultivation standards and inadequate supporting facilities have hindered Nanchong’s development within this sector [50].

The research findings also revealed price differentials between products originating from Nanchong when compared with similar items from Meishan: “Mandarine Orange” sold at a price lower by RMB 2–3 per kilogram, while “Shiranui mandarin” was priced lower by RMB 3–4 per kilogram than comparable products from Chengdu. Meishan holds a leading position across Sichuan regarding late-maturing orange plantation area, output, and value. However, the region’s land carrying capacity is limited. Continued rapid expansion will inevitably breach cultivated land redlines and exacerbate non-food land use risks.

3.2. The Climatic Suitability Levels for Late-Maturing Citrus Production in Various Prefecture-Level Cities and Autonomous Prefectures in Sichuan Province

The average climate suitability index for the late-maturing citrus fruit industry in the 18 prefecture-level cities and autonomous prefectures of Sichuan is shown in

Table 4. The average climate suitability index for late-maturing citrus fruits in various prefecture-level cities and autonomous prefectures in Sichuan from 2010 to 2020.

	Grade Score for Annual Average Temperature Suitability	Suitable Grade Score of Accumulated Temperature ≥ 10 °C	Rating Score for July’s Average Temperature Suitability	Rating Score for January’s Average Temperature Suitability	Requisite Grade Score for Annual Precipitation	Appropriate Grading Criteria for Annual Sunshine Hours	Optimum Grade Number	Suitable Grade Number	Sub-Suitable Grade Number	Unsuitable Grade Number
Chengdu	5	4	4	5	4	4	2	4	0	0
Zigong	3	4	4	4	4	4	0	5	1	0
Luzhou	4	4	4	4	4	4	0	6	0	0
Deyang	5	5	5	4	4	4	3	3	0	0
Mianyang	5	5	5	4	4	4	3	3	0	0
Guangyuan	4	4	5	5	4	4	2	4	0	0
Suining	4	4	4	5	4	4	1	5	0	0
Neijiang	4	5	4	4	4	4	1	5	0	0
Leshan	4	4	5	4	3	4	1	4	1	0
Nanchong	4	5	4	4	5	4	2	4	0	0
Meishan	4	5	5	4	4	4	2	4	0	0
Yibin	4	4	4	4	4	4	0	6	0	0
Guangan	4	5	4	5	4	4	2	4	0	0
Dazhou	4	5	3	5	4	5	3	2	1	0
Yaan	5	4	4	4	2	3	1	3	1	1
Bazhong	4	5	4	5	4	3	2	3	1	0
Ziyang	4	5	4	4	4	4	1	5	0	0
Liangshan	4	4	3	3	4	2	0	3	2	1

.

The suitability of the climate conditions for late-maturing citrus planting in two-thirds of the prefecture-level cities and autonomous prefectures is evident from Table 4. With the exception of Zigong, Leshan, Dazhou, Yaan, Bazhong, and Liangshan, all the other key climate factors in these areas were categorized as most suitable or suitable. Notably, half of the prefecture-level cities and autonomous prefectures fell into the most suitable category for accumulated temperature ≥ 10° C, while one-third were classified as most suitable based on the average temperature in January. Furthermore, no prefecture-level cities and autonomous prefectures were deemed unsuitable when considering the annual average temperature, accumulated temperature ≥10 °C, average temperature in July, and average temperature in January. Deyang and Mianyang exhibited superior climate conditions for late-maturing citrus planting, with three key climate factors falling within the most suitable grade, respectively. Conversely, Liangshan’s climate conditions are unsuitable for late-maturing citrus planting, as it ranked highest among all the provinces regarding sub-suitable and unsuitable grades.

3.3. The Average and Decomposition of the Climate Adaptability Index for the Late-Maturing Citrus Industry in Prefecture-Level Cities and Autonomous Prefectures in Sichuan Province

Using the DEAP2.1 software, the climate adaptability index (TFP) for the late-maturing citrus industry in various prefecture-level cities and autonomous prefectures in Sichuan from 2010 to 2020 was calculated, along with its average and composition, as shown in

Table 5. The average and decomposition of climate adaptability index of late-maturing citrus industry in various prefecture-level cities and autonomous prefectures of Sichuan from 2010 to 2020.

	Effch	Tech	Pech	Sech	TFP
Chengdu	0.930	0.995	0.969	0.960	0.925
Zigong	0.930	1.027	1.000	0.930	0.956
Luzhou	1.012	1.026	1.149	0.881	1.038
Deyang	0.933	0.987	0.859	1.086	0.920
Mianyang	0.907	1.015	0.906	1.002	0.921
Guangyuan	0.892	1.030	1.075	0.830	0.919
Suining	0.972	1.022	0.970	1.002	0.994
Neijiang	0.974	1.051	1.000	0.974	1.023
Leshan	0.963	1.020	1.080	0.892	0.983
Nanchong	0.919	1.039	0.954	0.963	0.955
Meishan	1.000	1.004	1.000	1.000	1.004
Yibin	0.998	1.020	1.003	0.994	1.018
Guangan	0.895	1.044	0.831	1.077	0.934
Dazhou	0.907	1.037	0.875	1.037	0.941
Yaan	1.017	1.054	1.000	1.017	1.071
Bazhong	1.052	0.985	1.196	0.879	1.036
Ziyang	1.054	1.097	1.054	1.000	1.156
Liangshan	1.028	1.025	1.000	1.028	1.054
mean	0.964	1.026	0.991	0.973	0.990

.

According to Table 5, the average climate adaptability index of the late-maturing citrus fruit industry in various prefecture-level cities and autonomous prefectures in Sichuan exhibited the following three characteristics.

(1) More than half of the prefecture-level cities and autonomous prefectures exhibited inefficient utilization of climate resources in late-maturing citrus cultivation. During the investigation period, the average TFP value of eight prefecture-level cities and autonomous prefectures, namely Ziyang, Yaan, Liangshan, Luzhou, Bazhong, Neijiang, Yibin, and Meishan, exceeded 1.0. Among these regions, five were identified as key areas with suitable scale, and the technical proficiency in the late-maturing citrus industry aligned with local climate conditions. However, there were 10 prefecture-level cities and autonomous prefectures, including 6 key ones, that displayed general weaknesses in enhancing the climate resource utilization efficiency. Notably, Guangyuan ranked last in terms of the average TFP value for late-maturing citrus cultivation within the province, primarily due to its focus on the kiwifruit industry rather than late-maturing citrus as a leading sector. Inadequate attention towards improving late-maturing citrus technology and management levels further contributed to this situation. Additionally, the devastating impact caused by fruit fly pests in 2008 inflicted long-lasting damage on Guangyuan’s late-maturing citrus industry, which remains challenging to fully recover from even after several years, thus emphasizing the utmost importance of ensuring quality and safety standards for late-maturing citrus products.

(2) The low efficiency of climate resource utilization in late-maturing citrus planting in Sichuan was primarily attributed to inadequate effch. During the investigation period, only 6 prefecture-level cities and autonomous prefectures demonstrated effective effch, while 15 prefecture-level cities and autonomous prefectures exhibited effective tech. This indicates that two-thirds of the prefecture-level cities and autonomous prefectures failed to effectively harness established climate resources for enhancing resource endowment or achieving significant technological progress based on climatic conditions. Moreover, the pace of technological advancement reliant on climate conditions was relatively sluggish, indicating a lack of high-level management.

(3) The lower pech and sech were the primary factors contributing to the overall low effch. Throughout the investigation period, the average values of pech and sech in all the prefecture-level cities and autonomous prefectures were below 1.0, with pech surpassing sech in eight prefecture-level cities and autonomous prefectures. Among these, there were five prefecture-level cities and autonomous prefectures where ineffective effch was solely caused by pech, with Guangan having the lowest value (0.831). This indicates that these prefecture-level cities and autonomous prefectures did not fully utilize their climate resource conditions. Additionally, there were five prefecture-level cities and autonomous prefectures where ineffective effch was solely caused by sech, with Guangyuan having the lowest value (0.830). This reflects a discrepancy between the increase in citrus output value proportionally compared to the suitable grade of all climate resources within these areas. Both pech and sech proved ineffective in Chengdu and Nanchong, highlighting a clear mismatch between climate resource conditions and actual citrus production output in these two prefecture-level cities and autonomous prefectures. Major issues related to technical level and industrial scale are evident.

3.4. The Temporal Variation in the Climate Adaptability Index for the Late-Maturing Citrus Industry in Prefecture-Level Cities and Autonomous Prefectures in Sichuan Province

During the observation period, the climate adaptability index (TFP) of the late-maturing citrus industry in the various prefecture-level cities and autonomous prefectures in Sichuan exhibited significant variations in different years, as shown in

Table 6. Changes in TFP time value of late-maturing citrus planting in prefecture-level cities and autonomous prefectures of Sichuan from 2010 to 2020.

	2010– 2011	2011– 2012	2012– 2013	2013– 2014	2014– 2015	2015– 2016	2016– 2017	2017– 2018	2018– 2019	2019– 2020
Chengdu	0.678	1.462	0.707	0.866	0.866	0.734	1.529	0.730	1.243	0.859
Zigong	0.962	0.697	1.118	1.019	1.006	1.000	0.961	0.960	0.803	1.114
Luzhou	1.125	1.114	1.073	1.068	0.834	1.068	1.056	0.930	0.814	1.419
Deyang	1.118	1.173	0.571	0.866	1.491	0.726	0.860	1.175	0.874	0.703
Mianyang	1.022	0.947	0.683	1.049	1.302	1.429	0.420	0.885	1.063	0.863
Guangyuan	1.137	0.807	1.190	0.988	0.988	1.171	0.734	1.000	0.810	0.580
Suining	0.926	1.067	1.297	0.836	0.928	1.165	1.038	1.031	0.649	1.167
Neijiang	1.461	0.647	1.166	0.854	0.878	0.891	1.626	0.775	1.087	1.249
Leshan	1.031	1.120	0.881	0.786	1.244	0.929	0.929	1.024	0.610	1.567
Nanchong	0.735	0.944	1.304	0.977	0.962	0.960	0.914	0.966	0.728	1.208
Meishan	1.287	0.746	1.006	1.209	0.866	1.028	1.344	0.828	1.264	0.713
Yibin	1.395	0.703	1.110	0.842	1.155	0.958	0.770	0.849	1.064	1.687
Guangan	0.772	0.981	1.307	1.500	0.429	1.352	0.947	0.920	0.646	1.037
Dazhou	0.845	0.866	1.300	1.442	0.493	1.232	0.881	1.376	0.530	1.014
Yaan	1.029	1.475	1.239	1.088	0.774	1.479	0.901	1.071	0.944	0.930
Bazhong	1.174	0.866	1.479	1.117	0.837	1.115	1.000	0.964	1.013	0.928
Ziyang	1.070	0.957	1.225	0.935	1.262	1.693	1.380	0.916	1.362	0.990
Liangshan	1.118	0.994	1.000	1.160	0.909	1.000	1.351	0.909	1.325	0.885
mean	1.028	0.951	1.061	1.017	0.918	1.081	0.991	0.952	0.901	1.013

.

The changes in the TFP time value of late-maturing citrus planting in the various prefecture-level cities and autonomous prefectures in Sichuan during the investigation period exhibited the following three characteristics, as illustrated in Table 6.

(1) Taking 2016, the year when the Action Plan was proposed and implemented, as the demarcation point, it was observed that instead of an increase, two-thirds of the prefecture-level cities and autonomous prefectures witnessed a decline in the average TFP for late-maturing citrus planting. Comparing the TFP averages before and after implementing the Action Plan revealed that apart from Chengdu, Neijiang, Leshan, Meishan, Yibin, and Liangshan, all the other 12 prefecture-level cities and autonomous prefectures experienced a decrease in their TFP averages. Among them, Guangyuan exhibited the most significant decline (−0.266). Prior to implementing the Action Plan, the TFP averages for these twelve prefecture-level cities and autonomous prefectures exceeded 1.0; however, post-implementation, only eight prefecture-level cities and autonomous prefectures demonstrated effective progress.

(2) The climate resource utilization efficiency of half of the prefecture-level cities and autonomous prefectures exhibited a declining trend. During the study period, there was an increase in the climate resource utilization efficiency of Chengdu, Zigong, Luzhou, Suining, Leshan, Nanchong, Yibin, Guangan, and Dazhou; notably, Leshan demonstrated the highest increase (0.536). Conversely, the remaining eight prefecture-level cities and autonomous prefectures experienced varying degrees of decrease in their climate resource utilization efficiency; in particular, Guangyuan showed a significant decline (−0.557).

(3) In Sichuan, there were no prefecture-level cities and autonomous prefectures where the efficiency of climate resource utilization in late-maturing citrus planting had been significantly improved to gain an absolute advantage.

Table 7. The climate adaptability index of late-maturing citrus industry in Sichuan from 2010 to 2020 in prefecture-level cities and autonomous prefectures below the mean value.

Year	TFP Mean	Prefectures and Autonomous Regions with TFP below the Mean	Frequency Statistics
2010–2011	1.028	Chengdu, Zigong, Mianyang, Suining, Nanchong, Guangan, Dazhou	7 times (Chengdu); 6 times (Mianyang, Nanchong, Meishan, Deyang); 5 times (Zigong, Guangan, Dazhou, Guangyuan, Neijiang, Leshan, Liangshan); 4 times (Suining, Yibin, Luzhou); 3 times (Bazhong, Ziyang, Yaan)
2011–2012	0.951	Zigong, Mianyang, Guangyuan, Neijiang, Nanchong, Meishan, Yibin, Suining, Dazhou, Bazhong
2012–2013	1.061	Chengdu, Deyang, Mianyang, Leshan, Meishan, Liangshan
2013–2014	1.017	Chengdu, Deyang, Guangyuan, Suining, Neijiang, Leshan, Nanchong, Yibin, Ziyang
2014–2015	0.918	Chengdu, Luzhou, Neijiang, Meishan, Guangan, Dazhou, Yaan, Bazhong, Liangshan
2015–2016	1.081	Chengdu, Zigong, Luzhou, Deyang, Neijiang, Leshan, Nanchong, Meishan, Yibin, Liangshan
2016–2017	0.991	Zigong, Deyang, Mianyang, Guangyuan, Leshan, Nanchong, Yibin, Guangan, Dazhou, Yaan
2017–2018	0.952	Chengdu, Luzhou, Mianyang, Neijiang, Meishan, Yibin, Guangan, Ziyang, Liangshan
2018–2019	0.901	Zigong, Luzhou, Deyang, Guangyuan, Suining, Leshan, Nanchong, Guangan, Dazhou
2019–2020	1.013	Chengdu, Deyang, Mianyang, Guangyuan, Meishan, Yaan, Bazhong, Ziyang, Liangshan

presents a comparison of the TFP and the average values among the prefecture-level cities and autonomous prefectures in Sichuan over the investigation period.

According to Table 7, it is evident that during the study period, the climate adaptability index of the late-maturing citrus industry in the various prefecture-level cities and autonomous prefectures in Sichuan was consistently lower than the annual average. This suggests that none of the 18 prefecture-level cities and autonomous prefectures showed a significant improvement in climate adaptability or demonstrated absolute dominance in this regard. Among them, Ziyang exhibited the best performance, having three years below the average but six effective years, and no year falling below 0.9.

4. Discussion and Conclusions

This study integrated traditional citrus regional division with resource endowment coefficients and evaluated the climate adaptability of the late-maturing citrus industry in 18 prefecture-level cities and autonomous prefectures of Sichuan Province from 2010 to 2020 using the DEA–Malmquist index model. The results indicate the following:

(1) The overall climate conditions in Sichuan are generally suitable for the growth of late-maturing citrus fruits. However, the extensive cultivation of similar late-maturing citrus varieties has led to a decline in resource endowment. Although two-thirds of the prefecture-level cities and autonomous prefectures have favorable climate conditions for late-maturing citrus cultivation, half of them showed a trend of declining resource endowment to varying degrees. During the study period, both the production and planting area of late-maturing citrus fruits in each prefecture-level city and autonomous prefecture increased annually, even during years with meteorological disasters. While this short-term increase may lead to a higher income from late-maturing citrus cultivation, from a long-term development perspective, blind expansion is likely to result in a decrease in comparative advantage. This is especially true when poor climate conditions lead to a decline in the quality of late-maturing citrus fruits, ultimately impacting the increase in industrial output value and hindering sustainable development within the industry.

(2) The rapid expansion of late-maturing citrus cultivation in Sichuan has led to a decline in climate adaptability. All 10 prefecture-level cities and autonomous prefectures with low climate adaptability indices have experienced the issue of rapid expansion of late-maturing citrus cultivation, despite overall favorable climate conditions. The additional planting area for late-maturing citrus cannot yield economic benefits in the short term. The field survey results also indicated that Chengdu, Nanchong, Leshan, and Suining have witnessed the phenomenon of citrus cultivation encroaching on arable land. However, the climate conditions are unable to meet the dual requirements of a sustained rapid increase in late-maturing citrus yields and an improvement in fruit quality. Furthermore, inadequate or absent daily management techniques by growers hinder fruit quality improvement, ultimately leading to a decrease in selling prices for late-maturing citrus. As a result of declining income from decreased sales prices, late-maturing citrus growers are unable to increase their investment in technical management. In cases of meteorological disasters, small-scale growers are completely unprepared to cope with such events.

(3) Policies that are not in line with climate adaptation are detrimental to the sustainable development of the late-maturing citrus industry in Sichuan. Policy intervention in agricultural production layout is a major hindrance to the development of agricultural industries, and policy support should not overlook the suitability of climate conditions. The climate conditions in Baizhong, Ya’an, and Liangshan are not conducive to the large-scale planting of citrus. Although they exhibited some degree of climate adaptability, this was primarily due to low input and low output being aligned with each other. In recent years, influenced by policies such as poverty alleviation and economic development, these prefecture-level cities and autonomous prefectures have pursued an increase in late-maturing citrus output without considering adequate technical support or mature cultivation techniques. This has led to a decline in citrus prices and demoralized fruit farmers and has had a counterproductive effect on the development of the late-maturing citrus industry.

Based on the research of other scholars, Deng Xinxin had already identified the phenomenon of using arable land to cultivate late-ripening citrus fruits in Sichuan as early as 2022 [51], which is consistent with the findings of this study. Some scholars have also focused on the experiences and deficiencies in dealing with meteorological disasters in major late-ripening citrus fruit production areas such as Meishan, Chengdu, and Nanchong in Sichuan [50,52,53]. Wang Xun [14] conducted an analysis of data spanning from 1981 to 2010 and reached the conclusion that certain regions, namely Meishan, Chengdu, Ziyang, Suining, Nanchong, and Guangan, exhibited optimal climatic conditions for late-maturing citrus cultivation. Additionally, some areas, including Leshan, Deyang, Mianyang, Guangyuan, Dazhou, Neijiang, Zigong, Luzhou, and Yibin, were also deemed suitable for late-maturing citrus planting. Conversely, the majority of the regions in Bazhong, Yaan, and Liangshan were found to be unsuitable for such cultivation; this finding aligns with the climate suitability aspect explored in this study. Lin Zhengyu [18], on the other hand, documented a rapid spatial expansion of citrus farming in Sichuan between 1980 and 2015. Building upon this perspective, the present study further determined that the trend towards an accelerated growth in the citrus plantation scale within Sichuan from 2016 to 2020 has continued to intensify while simultaneously revealing its lack of adaptability to prevailing climate resource conditions.

The focus of this study was to assess the climatic adaptability of late-maturing citrus cultivation in various prefecture-level cities and autonomous prefectures in Sichuan, aiming to determine whether these regions have fully utilized their inherent climatic resources for citrus production. Previous research on the suitability of citrus cultivation in specific county-level cities, counties, and autonomous counties has provided valuable insights for this study. However, due to the differing climate requirements between late-maturing citrus and other types of citrus, it is not feasible to directly compare the climatic adaptability of late-maturing citrus with previous research findings.

There is significant potential for improvement in data acquisition in this study. The frost-free period is a crucial climatic condition for the cultivation of late-maturing citrus, but data at the level of prefectural cities and autonomous prefectures and below were not available. Due to the strict requirements of the DEA model regarding the ratio of decision-making units (DMUs) to indicators, an inability to expand the number of DMUs means that selecting additional key meteorological factor indicators would render computational results invalid. Consequently, this study cannot make more precise assessments due to its inability to access data on late-maturing citrus production, revenue, and key meteorological factors at county-level cities, counties, and autonomous counties as well as villages and townships.