Measuring the energy consumption and energy efficiency in two-harvest-a-year grape cultivation

Journal Pre-proof Measuring the energy consumption and energy efficiency in two-harvest-a-year grape cultivation

Dong Tian, Min Zhang, Chuqiao Xiong, Weisong Mu, Jianying Feng PII:

S0360-5442(19)31953-X

DOI:

https://doi.org/10.1016/j.energy.2019.116258

Reference:

EGY 116258

To appear in:

Energy

Received Date:

09 July 2019

Accepted Date:

30 September 2019

Please cite this article as: Dong Tian, Min Zhang, Chuqiao Xiong, Weisong Mu, Jianying Feng, Measuring the energy consumption and energy efficiency in two-harvest-a-year grape cultivation, Energy (2019), https://doi.org/10.1016/j.energy.2019.116258

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Journal Pre-proof Measuring the energy consumption and energy efficiency in two-harvest-a-year grape cultivation Dong Tiana, Min Zhanga, Chuqiao Xionga, Weisong Mua, b, Jianying Fenga,* a China b

Agricultural University, Beijing 100083, China

The key laboratory of Viticulture and Enology, Ministry of Agriculture, Beijing 100083, China

Abstract: This paper aims to assess two-harvest-a-year grape production system from the perspective of energy consumption and energy utilization. The primary data was collected through field investigation in Guangxi, China, and the raw data was converted to energy data by the energy equivalent to account the energy consumption. Furthermore, the energy data were processed based on Data Envelopment Analysis model to measure the energy efficiency in two-harvest-a-year grape cultivation. The results reveal that the total energy input and output in annual are 67630MJ/ha and 50462 MJ/ha, and the energy input and output amounts in the first season are generally larger than that in the second season. However, energy input structures in two production seasons are quite similar for they both consume large proportions energy of chemical fertilizer and pesticide, which respectively are 41.65% and 25.20% in the first season and 39.29% and 25.66% in the second season. The average energy efficiency in the first season, the second season and annual is 0.805, 0.573 and 0.687, which reveals the firstly season is more efficient in energy utilization. Finally, some suggestions are proposed to optimize energy input structure and promote energy utilization efficiency of the production system. Keywords: two-harvest-a-year; grape cultivation; energy consumption; energy efficiency; Data Envelopment Analysis 1. Introduction Two-harvest-a-year grape cultivation is a kind of innovative grape production modes, which can effectively improve the utilization of agricultural resources and expand the growing area of grape cultivation. In the past, the southern China was considered to be an unsuitable area for grape cultivation due to the high temperature, heavy rain, and the small temperature difference between day and night in summer, as well as the climate in winter which is unable to meet the requirements of low temperature dormancy of fruit trees [1]. However, with the emergence of two-harvest-a-year technology in the protected grape cultivation, the summer fruit makes full use of the original waste of sunshine and heat resources. On the other hand, during the growing period of winter grape, the temperature difference between day and night is large and the illumination is adequate which is beneficial to the accumulation of photosynthesis and the improvement of grape quality. Thus, the grape production greatly improves the utilization rate of light, heat and land resources [2]. In recent years, the two-harvest-a-year technology has been developed rapidly in the southern region, especially in Guangxi, Yunnan, Hunan, and other southern provinces and regions. The key technical points of two-harvest-a-year cultivation are making full use of the physiological characteristics of the multiple differentiation of grape flower in one year, adopting

*

Corresponding author. No.17 Qinghuadonglu, Haidian District, Beijing 100083, China E-mail addresses: [email protected]; [email protected]; Tel./fax: +86 1062736717

Journal Pre-proof the pregermination treatment to break grape dormancy, and supplying good light, temperature, soil, fertilizer and water resources conditions (for example, some recent-advanced methods for water management[3])to enable grape trees to sprout, bloom and fruit two times a year. It is obviously that the production system requires a large number of manual operations for environmental control and plant physiological regulation, so it typically has the characters of high inputs of capital, manpower, energy and resources, and also is highly interfered and regulated by human beings. Therefore, the coupling relationship between production system and ecological environment is more complex. The abundant consumption and application for production goods including fertilizer, pesticide, insecticide and others might bring the pollution of the soil, water, air and food, they also lead to the rise of economic cost and environmental pressure [4]. Consequently, the energy management research of two-harvest-a-year viticulture from the perspective of efficiency improvement and sustainable development has a strong and typical significance. The efficient use of energy is one of the core contents of sustainable agricultural production [5], so the energy issue has become a research focus, and extensive research has been carried out related to the energy consumption of agricultural production systems. Basically, authors conducted agricultural energy consumption research from two scales, one is energy accounting at the macro scale using statistical data, usually the research scale is the whole agricultural industry or a specific agricultural sector. Xu [6] accounted for the energy consumption of wheat and corn in China, Blancard and Martin [7] and Vlontzons et al.[5] respectively calculated the energy use of agricultural production in France, Sweden and other EU countries, and Xu[8] analyzed the energy consumption and carbon emissions of China's agriculture from 1985 to 2012. This kind of study can reveal the overall energy consumption of agricultural production in a region or nation, while it’s difficult to reflect the key nodes affecting energy consumption, neither to assess the energy flow in some special production system. The other is energy accounting from micro-agricultural production system, commonly from the perspective of sampled or experimental farms. The raw energy data were obtained through field experiment or investigation, so the data is accurate and can be adopted to conduct in-depth modeling and optimization study. The input and output indicators that were used in micro-scale energy consumption accounting of related researches were summarized in Table 1. Table 1 Energy consumption accounting indicators for fruits production systems. Crop grape orange apple almond plum prune

Input Index Labor, machinery, diesel, pesticides, chemical fertilizer, compost, electricity Labor, machinery, diesel, chemical fertilizer, compost, pesticides, irrigation water, electricity Irrigation water, chemical fertilizer, machinery, diesel, electricity, labor

Output Index

References

grape yield

[9, 10]

orange

[11]

apple yield

[12]

Electricity, chemical fertilizer, Labor, pesticides, compost, diesel,

almond residues

machinery

and nut

Chemical fertilizer, diesel, machinery, pesticides, irrigation water, labor Labor, gasoline, chemical fertilizer, pesticides, electricity, irrigation water

[13]

yield

[14]

prune

[15]

Journal Pre-proof The effectiveness of energy use is an important index to evaluate the production efficiency and environmental impact of production system. Cerutti et al.[16] pointed out that energy balance and energy efficiency were critical methods to assess the environmental impacts and sustainability in fruit production system. By increasing energy efficiency, energy consumption of production system was reduced, and then economic input, ecological pressure and environmental impact were reduced and weakened, and finally the system sustainability was improved. Therefore, energy efficiency evaluation and improvement are always a focus in energy management. Considering the scarcity of resources, as well as the positive economic and environmental effects brought by energy conservation and emission reduction, adjusting and optimizing energy input is a more effective energy management method. In terms of energy efficiency assessment methods, more emphasis is placed on the proportion of actual output to the maximum desired output under a given energy input, or the proportion of the ideal minimum energy input to the actual energy input cost under a given output. The two formulations both emphasize the comparison between the actual energy utilization and the optimal situation. Parametric method and non-parametric method are commonly adopted to evaluate the energy efficiency. The typical representative of parametric methods is the stochastic frontier analysis (SFA) method, which calculates the energy efficiency by introducing the concept of production frontier and constructing different types of production functions. Moreover, it can analyzes the contribution degree of different energy input to output and the main factors affecting efficiency, so many researchers carried out the empirical energy efficiency evaluation studies based on SFA [17-20]. With regards to the non-parametric methods about energy efficiency research, data envelopment analysis (DEA) is the typical one. It treats each sampled farm as a DMU (decision-making unit), then the energy input and output data of all DMUs are used to envelop the best production frontier, and the efficiency of each DMU is the distance from the DMU point to the frontier. Many authors applied DEA to assess the energy efficiency of agricultural production system, Nassiri and Singh [21], Khoshnevisan et al.[22] and Khoshroo et al.[9] respectively constructed energy efficiency evaluation models for rice, cucumber and grape production systems based on DEA. Both SFA and DEA methods have their own advantages and disadvantages, which lead to errors in the evaluation results, so the researcher needs to adopt the suitable method in the specific empirical studies. Consequently, the goals of the present research are to account the energy consumption of two-harvest-a-year grape cultivation and evaluate the energy efficiency of the system, then explore its features in energy utilization and compare the energy utilization level of the production system with other agricultural systems, finally propose some advices for the improvement of the production system sustainability. The rest of the paper is organized as follows: Section 2 outlines production process of two-harvest-a-year grape cultivation, recognizes energy inputs/outputs index, establishes energy consumption calculation and energy efficiency assessment method, and introduces the sampling and data acquisition and processing. Then, energy input-output analysis, energy consumption accounting, and energy efficiency measurement results are presented and discussed in section 3. Conclusions are provided in the last section. 2 Materials and Methods 2.1 Production system analysis of two-harvest-a-year grape cultivation

Journal Pre-proof 2.1.1 Production process analysis The two-harvest-a-year grape cultivation system is put forward based on traditional one-harvest-a-year grape production, whose life cycle is more complex and abundant. This study focused on the energy consumption characters in two-harvest-a-year grape cultivation and the comparisons of energy use differences between two-harvests and one-harvest cultivations, so the production processes of construction the vineyard, seedling planting and agricultural operations before full bearing period are not taken into account for they are similar or even the same in the two grape production modes. Thus, a typical production processes and key links of two-harvest-a-year grape cultivation system are sorted out in Fig.1 on the basis of field research and literature analysis. Firstly, when the temperature is stably above 10° C from late-January to mid-February, the dormancy of vine tree is broken by bio-regulators and the tree begins to germinate. Through a series of operations such as nutrient management, fertilization and pesticide application, and pruning, the first season fruits are mature from mid-June to early-July (usually called summer grape)[23]. After harvesting summer fruit, it is necessary to clean up the vineyard, irrigate and fertilize, and restore the tree potential, this period will last about one month. Then, in the mid- and late-August, the grape tree germinates again under germination stimulator and starts the second growth cycle (usually called winter grape). The cultivation management and growth process of winter fruit are basically the similar to that of summer fruit. The winter grapes are harvested in the mid- and late-December. Likewise, the vineyard needs to be cleaned and prepared and the tree requires to recover the potential for production in the next year [24]. Summer fruit growth period

Grape growth stage

Gernimation

Flowering

Fruit

After harvesting summer grape , before winter fruit sprouting

Maturity

Fertilizing & Irrigation & Pet controlling Bud dormancy & Breaking

Key agricultural operations

Jan.

Feb.

Bud picking & Pinching Mar.

Flower and fruit thinning & Bagging & Topdressing

Apr.

May

Jun.

Jan.

Key agricultural operations

Cleaning garden, topdressing, irrigation and restoring tree

Jul.

Dec.

Grape harvest

Cleaning garden, topdressing, irrigation and restoring tree

Grape harvest

Nov.

Oct.

Flower and fruit thinning & Bagging & Topdressing

Bud picking & Pinching

Sep.

Aug.

Bud dormancy & Breaking

Fertilizing & Irrigation & Pet controlling

Grape growth stage

After harvesting winter grape, before summer fruit sprouting

Maturity

Fruit

Flowering

Germination

Winter fruit growth period

Fig. 1 Two-harvests-a-year grape production process with two production seasons

2.1.2 Energy input/output items analysis Along with the construction of vineyard, grape growth period and key agricultural operations, a variety of energy consumptions are generated. According to the field investigation, the vineyards for two-harvest-a-year grape cultivation are not quite different from ordinary vineyards, so the energy consumption for the two kinds of vineyards construction and maintenance are similar.

Journal Pre-proof Considering the purpose of this study, we didn’t account the energy use for vineyards construction and seedling planting, and only counted the energy consumption in the grape growing season, including the summer grape growth period and winter grape growth period. The types of energy inputs in the two production seasons are similar, but the amount of energy consumption varies greatly and needs to be accounted for separately. The energy items should be comprehensive and operable, and can be calculated as energy quantity. According, the energy input items were extracted which included the plastic films (shed film and mulching film), irrigation water, electricity, chemical fertilizer, organic fertilizer, pesticide and manpower (labor). In terms of energy output, the immature grape and pruned branches can’t be measured correctly and converted as energy index, so their energy are ignored, and the y energy output indicator is only grape yield, which consists of summer grape and winter grape. 2.2 Methods for energy consumption accounting and energy efficiency 2.2.1 Energy consumption calculation method The raw data of production goods, manpower and grape yield were converted and calculated into the energy data through energy equivalent according to the equation as follows[25, 26]: E=

∑𝑀 × 𝑘

(1)

𝑖

Where the total energy consumption E is the sum of each kind of specific energy consumption in the production season, 𝑀𝑖 is the raw quantity of 𝑖th energy indicator, specifically it is the input production resource or output yield, and 𝑘 is the energy equivalent of each energy indicator, its unit is KJ/unit. The value of 𝑀𝑖 is investigated in the field survey, most of the items can be obtained and directly calculated in the energy accounting, yet some items should be obverted and converted, including pesticide and chemical fertilizer. The value of 𝑀𝑝𝑒𝑠𝑡𝑖𝑐𝑖𝑑𝑒 is the purification dosage of pesticides, the value of 𝑀𝑁𝑖𝑡𝑟𝑜𝑔𝑒𝑛 𝑓𝑒𝑟𝑡𝑖𝑙𝑖𝑧𝑒𝑟 is the amount of N which converted from the Nitrogen fertilizer, and 𝑀𝑃ℎ𝑜𝑠𝑝ℎ𝑎𝑡𝑒 𝑓𝑒𝑟𝑡𝑖𝑙𝑖𝑧𝑒𝑟 and 𝑀𝑃𝑜𝑡𝑎𝑠𝑠𝑖𝑢𝑚 𝑓𝑒𝑟𝑡𝑖𝑙𝑖𝑧𝑒𝑟 are respectively the purification amount of P2O5 and K2O which converted from the Phosphate fertilizer and Potassium fertilizer. Table 2 summarizes the energy equivalents (k) which were selected from previous literature. Table 2 Energy equivalent of energy input and output index of two-harvest-a-year grape cultivation. Energy Items

Energy Equivalent

Reference

Plastic Film

51931.81kJ/kg

[27]

Manpower

12600kJ/d

[28]

Nitrogen fertilizer (N)

92048.00kJ/kg

[27]

13388.80kJ/kg

[27]

9204.80kJ/kg

[27]

Pesticide

1020896.90 kJ/kg

[27]

Organic fertilizer

300 kJ/kg

[28]

Phosphate fertilizer (P2O5） Potassium fertilizer (K2O)

Irrigation Water

1020

kJ/m3

[27]

Electricity

3598.24 kJ/kWh

[27]

Grape

2205.80 kJ/kg

[27]

Journal Pre-proof For the comparison of energy consumption in different grape production mode, we put forward two energy indices to evaluate the energy use status directly, which are energy input-output ratio and energy productivity. Among which, energy input-output ratio is the ratio of energy output and total energy input, and energy productivity is the results of grape yield divided by total energy input per unit area of vineyard. 2.2.2 Measurement model for energy efficiency The measurement models for energy efficiency are usually based on SFA or DEA. The premise of the SFA method is to assume the existence of a certain production function, if there is no obvious production function or a wrong production function is adopted, there will be a large deviation to the efficiency results. However, DEA measures the efficiencies of DMUs directly based on the input and output data without assumption a production function [29]. Therefore, this study measured the energy efficiency based on the DEA model. The principle of DEA model is to determine the relatively effective production frontier by keeping the input of decision-making units (DMU), using mathematical planning and statistical data. Then project each decision-making unit onto the production frontier, and evaluate their relative effectiveness by comparing the degree of departure of decision-making units from the DEA frontier. The original DEA model is a CCR model with constant returns to scale, measuring the technical efficiency (TE) of the decision unit. On this basis, a BCC model with variable scale returns is proposed, which decomposes the technical efficiency (TE) into pure technical efficiency (PTE) and scale efficiency (SE). Due to the grape production is not constant return to scale, this paper use DEA model with variable returns to scale. The DEA model also can be divided into two types: the input-oriented type of “output constant, minimum input” and the output-oriented type of “input constant, maximizing output”. In this study, there is only one kind of energy output, and there are many kinds of energy inputs. In actual production, managers usually obtain corresponding outputs by controlling inputs. Therefore, the input-oriented DEA model is more compatible with this research. The CCR model is defined as follows [30]:

(∑ 𝑚

min𝜃0 ― 𝜀 ∙

𝑠

𝑆𝑖

―

+

𝑖=1

∑𝑠

𝑟

+

𝑟=1

)

s. t. n

∑𝑥

𝑖𝑗

∙ 𝜆𝑗 + 𝑠𝑖 ― = 𝜃0 ∙ 𝑥𝑖0 , i ∈ 1,⋯,m

𝑟𝑗

∙ 𝜆𝑗 ― 𝑠𝑟 + = 𝑦𝑟0 , → 𝑟 ∈ 1,⋯,𝑚

j=1 n

∑𝑦 j=1

𝜆𝑗,𝑠𝑖 ― ,𝑠𝑟 + ≥ 0,

∀𝑖,𝑟,𝑗

（2）

Where n denotes the number of decision units(DMUs), each decision unit has m inputs 𝑥𝑖𝑗 (i=1, …,m) and s outputs 𝑦𝑟𝑗 (r=1, …,s), 𝜃0 represents efficiency indicators（𝜃0≤1），𝜀 is the infinitesimal amount of Archimedes, 𝜆𝑗 is the weight coefficient of input and output, 𝑠𝑟 + and

Journal Pre-proof 𝑠𝑖 ― are the slack variable and the residual variable, respectively. Adding the following constraints to formula (2), the model is transformed into a BCC model [31] based on input-oriented: 𝑛

∑𝑗 = 1𝜆𝑗 = 1

（3）

The expression of scale efficiency (SE) is as follows: ∗ 𝜃𝐶𝐶𝑅

∗ 𝜃𝑠𝑐𝑎𝑙𝑒 = 𝜃∗

（4）

𝐵𝐶𝐶

∗ ∗ Where 𝜃𝐶𝐶𝑅 and 𝜃𝐵𝐶𝐶 represent the calculated value of 𝜃 under the CCR model and BBC

model, respectively, that is, the technical efficiency value (TE) and the pure technical efficiency value (PTE), and the value range of them both are from 0 to 1. Similarly, the scale efficiency (SE) also ranges from 0 to 1, when SE=1 indicates that the current scale is efficient, and SE<1 indicates that the current scale is inefficient. 2.3 Sampling and data 2.3.1 Sampling and data collection Guangxi Zhuang Autonomous Region is the birthplace, and the most developed region for two-harvest-a-year grape cultivation in China, so it is selected as our research site. Then, on the basis of consulting relevant experts of Guangxi Academy of Agricultural Sciences (GXAAS) and combining with the actual cultivation situation of local farmers, the detailed sampling was carried out as follows: Firstly, we selected the representative cities with high developed two-harvest-a-year grape production, including Guilin City, Liuzhou City, Chongzuo City and Baise City. Then, several typical production counties were recognized as the survey sites, which are Lingchuan County, Xingan County, Ziyuan County and Quanzhou County in Guilin City, Liujiang County of Liuzhou City, Pingguo County of Baise City, and Daxin County of Chongzuo City. Finally, we investigated several vineyards in these counties under the assist of local staff in Grape and Wine Research Institute, GXAAS in 2017. The sample distribution is shown in Fig. 2. Most two-harvest-a-year grape vineyards were cultivated by individual farmers, and we took the form of field investigation to obtain data, that is, the researcher conducted face-to-face interviews with local farmers and recorded their production data. A questionnaire was employed in the field survey to collect production and energy information. The questionnaire was designed by the research team based on the literature research and expert consultation, and it covers the detailed information concerning material and manpower inputs in grape cultivation, including chemical fertilizer, pesticide, organic fertilizer, plastic film, irrigation water, electricity and manpower in the first and second seasons, as well as the grape yield. 26 samples were obtained in the central and southern regions of Guangxi (Liujiang City, Baise City and Chongzuo City), and 54 samples were collected in the northwestern region of Guangxi (Guilin City). After checking the collected questionnaires, the information in one vineyard was found to be logic errors and it was deleted. A total of 79 valid samples were finally obtained and used for next analysis.

Journal Pre-proof Study sites: Ziyuan County, Quanzhou County, Xingan County and Lingchuan County in Guilin City Number of vineyards: 54

Study sites: Liujiang County in Liujiang City Number of vineyards: 9

Study sites: Pingguo County in Baise City Number of vineyards: 13

Study sites: Daxin County in Chongzuo City Number of vineyards: 3

Fig. 2 Sample distribution of two-harvest-a-year grape vineyards

2.3.2 Data processing The raw production data was converted to the energy data by energy equivalent to calculate the energy consumption in the vineyard. The energy equivalents for three kinds of chemical fertilizer correspond to the purification dosage of the fertilizers (N, P2O5 and K2O), so in the energy accounting of chemical fertilizer, the raw data should be obverted and converted. Specially, the amount of raw consumption for different kinds of chemical fertilizers were acquired in the field survey firstly, and then was converted into the purification amount of N, P2O5 and K2O according to the effective percentage of N, P2O5 and K2O in the fertilizer compositions which were indicated on the package. After the conversion, the purification dosages of three chemical fertilizers were obtained, then the energy of each chemical fertilizer was calculated by the multiplication of purification dosage and energy equivalent, and finally the total energy of chemical fertilizer was the sum of the energy amount of each chemical fertilizer. Similarly, the amount of pesticide is purified according to the content of active components, and then multiplied by the energy equivalent to get the energy input of pesticide. The decision-making unit in this study was designed as each vineyard, while the scale of vineyards was different, so all the energy input and output were amounted to energy consumption and output per hectare vineyard in order to make the data comparable. The data of energy input and output in the first/second season was used to measure the energy efficiency of the first/second season respectively, then the energy data of two seasons was summed to represent the annual energy consumption and output, which was employed to measure the energy efficiency of the whole production year. The data were processed in Microsoft Excel 2016, and the energy efficiency measurement was implemented by DEAP 2.1 software. 3. Results and Discussion 3.1 Basic production status

Journal Pre-proof Through field investigation, some basic production information was acquired which helpful to understand the production status of two-harvest-a-year grape cultivation. The main varieties of two-harvest-a-year grape in Guangxi are Summer Black and kyoho grape, and a small number of vineyards plant Manicure Finger, Wink, Victoria, Shine Muscat and Red Globe grape. Most vineyards are small-scale with planting area less than 0.5 ha. Due to the small-scale vineyard, the family labor can manage the vineyards and seldom hire other staff. The farmers pump water to irrigate the vineyards, the irrigation water consumption is small for it is humid in Guangxi. Electricity power consumption is for water pump and lighting. Application quantity of fertilizer is large for grape trees requirement more nutrients to achieve two-harvest-a-year. Urea, potash fertilizer, phosphatic fertilizer, compound fertilizer and foliar fertilizer were usually applied to according to the local soil condition. Organic manure covers pig manure, chicken manure, tea bran, commercial organic fertilizer and biological microbial fertilizer, and they are usually applied as base fertilizer in vineyards and topdressing in some special period of grape growth, such as berry ripening stage. Pesticides applied in the vineyards are mainly lime-sulfur, pyrimidine, thiophonate-methyl, imidacloprid, and so on. The raw input data are presented in Table 3. Table 3 Average material and manpower inputs in production seasons of vineyards. Plastic

Irrigation

Electric

Chemical

Organic

film

water

power

fertilizer

fertilizer

(kg/ha)

(m3/ha.)

(kwh/ha.)

(kg/ha.)

(kg/ha.)

First season

248.69

292.16

355.45

1503.86

Second season

214.67

274.51

327.66

Annual

463.36

566.67

683.11

Pesticide

Manpower

(kg/ha.)

(day/ha.)

6100.00

41.47

484.07

1058.55

4583.33

31.51

293.97

2562.41

10683.33

72.98

778.04

Note: the amounts of chemical fertilizer and pesticide are the raw input quantities in grape production before purification and conversion.

Table 3 showed that all the inputs in the first season are higher than that in the second season, which means that summer grape production consumes more agricultural resources than winter grape, it also implies that summer fruit will consumes more energy. The reasons may be as follows: firstly, the summer climate in Guangxi is high temperature, high humidity and heavy rains, resulting in some pets and diseases (such as thrips, botrytis cinerea, Powdery Mildew, rust disease). But the summer grape gradually begins to mature at this time. In order to protect the berries, relatively more pesticides will be applied, which leads to high application frequency of pesticides during the first season, and thus the quantity of pesticide and manpower which consumed in pesticide application are large. But in the second season, most of the fruit growth period is during the dry season, so the demand for pesticides is relatively small. Secondly, it was learned from the investigation that most farmers paid more attention to the first season than the second season, for the second fruit was regard as the additional value-add part. Therefore, vine growers will input more production materials such as chemical and organic fertilizers in the first production season, they are also apt to manage the summer grape more sophisticated than the winter fruit, which causes more manpower consumption. The grape yield in two production seasons is also discrepant. It can be seen from Table 4 that the average yield in the first season is about 20403.94 kg/ha, whereas in the second season it is averagely 10677.31 kg/ha. The value of T-test is 0.00, which proves that there is a significant

Journal Pre-proof difference in grape yield between the two seasons from a statistical point of view. The total grape production can reach 31081.25 kg/ha. It can calculate that the average grape yield in Guangxi is 14590 kg/ha in 2016 based on the statistical data in China Agricultural Statistical Report (Ministry of Agriculture, PRC, 2016), which is obvious lower than two-harvest-a-year grape production. Table 4 Grape yield statistical results in two-harvest-a-year grape cultivation. Average (Kg/ha.)

Min (Kg/ha.)

Max (Kg/ha.)

Standard Deviation（SD）

First season

20403.94

8571.49

31500.14

11138

Second season

10677.31

1500.14

21664.25

11122

Annual

31081.25

14625.08

51383.62

17863

T-test

0.00 --

3.2 Energy consumption analysis 3.2.1 Energy accounting As shown in Table 5, there are differences in energy inputs between two production seasons of two-harvest-a-year cultivation. It can be found that every energy input item in the first season is higher than that in the second season, however, the inputs of plastic film, irrigation water and electricity are somewhat close in two production seasons, but the difference in the items of chemical fertilizer, organic fertilizer, pesticide and manpower is much big, and the results of T test also support this finding. Table 5 Statistic results of energy accounting of two-harvest-a-year grape cultivation Period Energy item

Plastic film

Irrigation water

Electric

Chemical fertilizer

Organic fertilizer

Unit：MJ/ha.

Statistic Index

First season

Second season

Annual

Average Min Max Standard Deviation T-test Average Min Max Standard Deviation T-test Average Min Max Standard Deviation T-test Average Min Max Standard Deviation T-test Average Min

12915 5491 45928 7267

11148 4469 35309 6230

24063 10276 81236 13430 -578 143 2637 494 -2458 540 5479 1152 -47996 8429 128686 29821 -3205 675

0.103 298 77 1341 247

280 66 1319 251 0.635

1279 305 3098 616

1179 195 3408 578 0.290

28168 4504 79091 17989

19828 3901 65372 15206 0.002

1830 500

1375 169

Journal Pre-proof

Pesticide

Manpower

Max Standard Deviation T-test Average Min Max Standard Deviation T-test Average Min Max Standard Deviation T-test

6750 1199

2972 828 0.006

17041 31314 46227 11495

12948 2428 46227 9751 0.017

6099 945 16464 3709

3704 945 13402 2376 0.000

8135 1803 -29989 6369 92455 20025 -9803 1890 29696 5819 --

The largest two energy input items are chemical fertilizer and pesticide, and they are respectively 28168 MJ/ha and 17041 MJ/ha in the first season, and 19828 MJ/ha and 12948 MJ/ha in the second season, followed by plastic film, manpower, organic fertilizer, electricity and irrigation water. For the phenomenon of large energy inputs of chemical fertilizer and pesticide, it can be explained from three points. Firstly, under the production mode of two-harvest-a-year, the burden of vines is heavy and trees require more resources and materials, especially the fertilizer; and the frequent occurrence of pets and diseases in Guangxi will add the pesticides application. Secondly, the energy conversion coefficients (energy equivalents) of pesticide and chemical fertilizer are obviously larger than others, which also led to the big amount of the energy inputs. Thirdly, some growers lacked the correct knowledge and concept of scientific cultivation, and they thought the grape grew better if more fertilizer were applied, that caused some overuse of chemical fertilizer. It is found in Table 5 that the standard deviation (SD) of each energy input is big, indicating the distribution of energy consumption data is much scattered, which means that the energy consumption and utilization of different sampled vineyards varies greatly. The T-test value of chemical fertilizer, organic fertilizer, pesticide and manpower is 0.002, 0.006, 0.017 and 0.000, respectively, which are all less than 0.05 and suggest significant differences in these energy input items between the first and second seasons, so it is necessary to explore their differences in energy efficiency. 3.2.2 Energy inputs structure Based on the detailed consumption data in Table 5, the structural proportion of various energy inputs in two production seasons were calculated and presented in Fig.3. The comparison indicates that the structure of energy inputs in the first season and the second season was quite similar, although Table 5 shows the quantity of energy input varies greatly in two production seasons. The biggest proportion of energy input is fertilizer which accounts for about 40%, and the second is pesticide which makes up approximately 25% in whole energy inputs. The proportions of chemical fertilizer and pesticide are greatly larger than other items, and they are nearly 2/3 in total energy consumption. Plastic film is the third and accounts for about 20%, and other items are not more than 10%. Ozkan et al. [32] reported that the top three energy input item in Turkish greenhouse grape production were electricity, chemical fertilizer and machinery, which was some different with this research. For their vineyard operations are more mechanized, while the two-harvest-a-year grape production are heavily relying on manpower. It could conclude that the

Journal Pre-proof energy input structure of two-harvest-a-year grape in Guangxi had a large dependence on chemical fertilizer and pesticide, and the similar input structure is found in the first and second seasons. Chemical fertilizer and pesticide are indirect and non-renewable energy sources, and excessive investment will inevitably lead to a large amount of waste of resources and environmental pollution, so the energy input structure needs adjusting and optimizing. 9.02% Plastic film 19.10% 25.20%

0.44% 1.89%

Irrigation water Electric Cheimcal fertilizer Organic fertilizer

41.65%

2.71%

Pesticide Manpower

(a) The first season

7.34% Plastic film 22.09%

Irrigation water 0.55% Electric 2.34% Cheimcal fertilizer

25.66%

Organic fertilizer Pesticide 2.72%

39.29%

Manpower

(b) The second season Fig. 3. Structural proportion of energy inputs in two-harvest-a-year vine growing

3.2.3 Energy utilization index Table 6 indicated the energy utilization in the first season, the second season and the full year for two-harvest-a-year grape cultivation. It can be seen that the energy input and output in the first season were generally higher than that in the second season. The first season consumed a total of 67630 MJ/ha energy, which accounted for 57.27% in the year-round energy use, and it output 45007 MJ/ha energy and made up about 65.65% of total annual energy output. The second season consumed 42.37% of annual energy input and produced 34.35% of total output. Overall, the first season was nearly 20 percentage points higher than the second season in energy input-output ratio, and 0.09 higher in the index of energy productivity, so the summer grape cultivation is proved to be more energy-intensive. Comparing the energy utilization index with related research, some important findings could

Journal Pre-proof be concluded. According to previous study [33], the total energy input in the protected grape cultivation was 210534.3 MJ/ha and the energy output was 48894.7 MJ/ha in China, it can be found that the energy input was much more but output was less than our results, so two-harvest-a-year grape cultivation had a higher energy input-output ratio and energy productivity. In Wang’s research [34], it indicated that the traditional one-harvest-a-year grape cultivation in Guangxi consumed about 203294 MJ/ha yearly and output about 51092 MJ/ha, with 25.13% of input-output ratio and 0.11 of energy productivity. It also finds that two-harvest-a-year production can obtained a higher commercial grape yield by comparing with public findings [9, 32]. Consequently, we can make a conclusion that two-harvest-a-year grape production is both economic and ecologic beneficial than traditional vine growing. Table 6 Energy utilization index in two-harvest-a-year grape cultivation. Total energy

Production

Proportion in

season

input（MJ/ha.）

First season

the annual

Total energy output

Proportion in the annual

Energy

Input-output

productivity

ratio

input

（MJ/ha.）

output

67630

57.27%

45007

65.65%

66.55%

0.302

Second season

50462

42.37%

23552

34.35%

46.67%

0.212

Annual sum

118092

100%

68559

100%

58.06%

0.263

(kg/MJ)

3.3 Energy efficiency analysis 3.3.1 Energy efficiency measurement results The energy efficiency was measured based on DEA method and presented in Table 7 (only some DMU’s results were showed due to the limitation of the paper length). The average of technical efficiency in the first season, the second season and the whole year are 0.805, 0.573 and 0.687, respectively. It is obvious that the energy efficiency in the first season is higher than that in the second season averagely, and there are significant differences in energy efficiency and ranking of each DMU between the two seasons. In terms of standard deviation (SD), the value of TE in the first season is the smallest, although its average is the largest, meaning that the technical efficiency difference of each sampled vineyard in the first season is small, and the energy efficiency value is relatively concentrated. Table 7 Energy efficiency and ranking of two-harvest-a-year grape based on the DEA model. In the first season

DMU

In the second season

Annual

number

TE

PTE

SE

Ranking

TE

PTE

SE

Ranking

TE

PTE

SE

Ranking

1

0.605

0.607

0.997

68

0.202

0.469

0.430

72

0.404

0.492

0.820

75

2

1.000

1.000

1.000

1

0.309

1.000

0.309

59

0.674

1.860

0.784

42

3

1.000

1.000

1.000

1

1.000

1.000

1.000

1

1.000

1.000

1.000

1

4

0.788

0.983

0.801

47

0.484

0.982

0.493

42

0.638

0.657

0.972

44

5

0.876

0.949

0.923

34

0.933

0.996

0.937

16

0.877

0.922

0.952

17

···

···

···

···

···

···

···

···

···

···

···

···

···

75

0.498

0.682

0.731

74

0.297

0.776

0.383

61

0.405

0.432

0.937

74

76

0.605

0.747

0.810

68

0.290

0.813

0.356

62

0.458

0.475

0.964

67

Journal Pre-proof 77

0.692

0.782

0.885

58

0.260

0.797

0.327

65

0.491

0.493

0.996

65

78

0.606

0.698

0.869

67

0.212

0.722

0.293

71

0.423

0.430

0.982

71

79

0.620

0.667

0.929

55

0.222

0.651

0.341

69

0.434

0.444

0.979

70

Average

0.805

0.880

0.904

--

0.573

0.919

0.613

--

0.687

0.755

0.915

--

0.187

0.125

0.121

--

0.298

0.127

0.285

--

0.192

0.212

0.075

--

Deviation

3.3.2 Distribution intervals of energy efficiency Fig. 4 shows the comparison of the distribution intervals of energy efficiency in two-harvest-a-year grape production. It could be seen that the distribution of energy efficiency is quite different in the first season, the second season and the whole year. In the first season, the energy efficiency of 22 DMUs is 1, which achieves the high level of effective energy utilization, and other DMUs mainly distribute in the range of [0.6, 0.9). While in the second season, DMUs with energy efficiency value of 1 are 12, which is significantly less than the first season, and DMUs that locate in the lowest interval [0, 0.5) are much more than the first season. The distribution of annual energy efficiency is the combination of the first and second season, and it has the largest proportion in the range of [0, 0.5) and [0.7, 0.8). Number of decision-making units

Standard

40 35

First

Second

30 25 20 15 10 5 0 [0,0.5) [0.5,0.6) [0.6,0.7) [0.7,0.8) [0.8,0.9) [0.9,1)

1

Interval distribution Fig. 4 Energy efficiency distribution of two-harvest-a-year grape based on the DEA model

Comprehensively analysis in Table 7 and Fig. 4, it is found that there are more DMUs fulfill efficient energy utilization in the first season, and the distribution of energy efficiency in the first season tends to be in the high intervals, while the situation in the second season is a little worse, for it has the largest proportion in the range of [0, 0.5). It is concluded that the energy utilization level in the first season of two-harvest-a-year grape cultivation mode in Guangxi is obviously higher than that in the second season. Therefore, it is necessary to adjust and optimize the energy consumption in the second season to increase its energy efficiency, and finally improve the energy efficiency and performance of the whole production system. The higher energy efficiency in the first season can be explained that the energy consumption was 67630 MJ/ha in the first season, which was slightly higher than that in the second season, while its output was much higher than the second season, resulting in higher energy efficiency in the first season. One of the reasons is the climate difference between the first and second seasons, and the more important reason may be the limitation of fruiting potential of vines. In the growth

Journal Pre-proof and fruiting of the first season, the vine tree has consumed most of the accumulated nutrition and exerted most of fruiting potential, leading to a lower output in the second season even though there was nutrition supplement. 3.3.3 Comparison of energy efficiency between two-harvest-a-year grape cultivation mode and other modes In order to clarify the energy efficiency level of two-harvest-a-year grape mode in Guangxi, we reviewed some related research results on the energy efficiency of grape and other agricultural crops, and the results are listed in Table 8. Table 8 Comparison of energy efficiency between two-harvest-a-year grape cultivation mode and other modes. Catalog

Grape

Object

Research region

Energy efficiency

References

Two-harvest-a-year grape

Guangxi, China

0.687

This study

One-harvest-a-year grape

Guangxi, China

0.506

[34]

Protected grape

China

0.707

[33]

Greenhouse grape

Iran

0.723

[9]

Citrus

Spain

0.711

[35]

Apple

Iran

0.786

[12]

Kiwifruit

Iran

0.942

[36]

Paddy

India

0.620

[20]

Rose

Iran

0.680

[37]

Cucumber

Iran

0.680

[22]

Other fruits

Other crops

Comparing the energy efficiency among different agricultural crops, we can find some conclusions. The two-harvest-a-year cultivation in Guangxi is at the high level of energy utilization in grape production, its energy efficiency is 0.687, which is obviously higher than that of one-harvest-a-year grape. Compared with the other fruits and crops production, the energy efficiency of two-harvest-a-year grape is much lower than that of kiwifruit, a little lower than energy efficiency of citrus and apple production, but higher than paddy, rose and cucumber in greenhouse. The energy consumption and output in an agricultural production system are really a complex problem and may be affected by multiple factors, such as crop varieties, agricultural operations, production concepts, climate change, energy price, technical progress, policy and others. Furthermore, the methods for assessing energy efficiency will cause some errors, and the energy equivalent should be adjusted according to temporal and spatial changes, all these may reduce the comparability of different studies in China and abroad. Nevertheless, the findings in this study still prove that two-harvest-a-year grape cultivation really improve the system performance through taking full advantages of natural resources and climatic factors, it is an innovative production mode that suitable for local grape industry. 4. Conclusions

Journal Pre-proof The cultivation pattern of two-harvest-a-year grape production changes Guangxi from an unsuitable area for vine growing to a characteristic good area in China, and this technique has achieved great success in increasing the local grape yield and enriching the market supply. This study assessed the production system from the perspective of energy consumption and utilization, and concluded some findings about its energy utilization features. The energy input structure two production season is basically similar, and the main input items are chemical fertilizer and pesticide, but amounts of energy input and output in the first season are generally much larger than that in the second season, and the energy utilization index and energy efficiency in the first season are all higher, where are more DMUs fulfill efficient energy utilization in the first season. Consequently, it is more efficient in the first season than the second season from the perspective of energy use. By compared with other research results, the energy utilization of two-harvest-a-year grape cultivation is superior to the one-harvest-a-year grape cultivation, which proves this technique is both more economic and ecologic beneficial than traditional vine growing. However, its energy efficiency is lower than some other farms, so the production mode still needs improving and optimizing. To promote the sustainable development of two-harvest-a-year grape cultivation system, some ecologically-friendly operations should be employed to adjust the energy consumption and utilization. For example, the timing and amount of chemical fertilizer and pesticide application should be rationally and scientifically planned and implemented, more organic fertilizer should be used to replace the chemical fertilizer, agricultural and physical measures should be adopted to control diseases and pests instead of using chemical and biological pesticide, the appropriate thickness of plastic film are chosen to reduce the frequency of updates, and so on. Acknowledgments This research was supported by the Natural Science Foundation of China under Grant No.41501585, China Agriculture Research System (CARS-29). The authors also show thankfulness to Mr. Cao Xiongjun from Grape and Wine Research Institute, GXAAS for his help in field investigation. References [1] Huang J, Wei L, Qin Z, et al. The climatic suitability of Kyoho grape cultivation in central Guangxi and key of two-harvest-a-year techniques[J]. Journal of Southern Agriculture, 2011,42(7):774-778. [2] Bai X, Li Y, Huang J, et al. A study on the cultivation mode of two-harvest-a-year Kyoho grape in southern Guangxi[J]. Southwest China Journal of Agricultural Sciences, 2008,21(4):953-955. [3] Sepehri A, Sarrafzadeh M. Activity enhancement of ammonia-oxidizing bacteria and nitrite-oxidizing bacteria in activated sludge process: metabolite reduction and CO2 mitigation intensification process[J]. Applied Water Science, 2019,9(5).DOI:10.1007/s13201-019-1017-6. [4] Mi S, Huang Z. Screening the applicability of agricultural greenhouse gas emission reduction technologies and management measures[J]. Scientia agricultura sinica, 2012,45(21):4517-4527. [5] Vlontzos G, Niavis S, Manos B. A DEA approach for estimating the agricultural energy and environmental efficiency of EU countries[J]. Renewable & Sustainable Energy Reviews, 2014,40:91-96. [6] Xu J. A study on the energy consumption and energy efficiency of grain production[D]. Hanghzhou: Zhejinag University, 2011.

Journal Pre-proof [7] Blancard S, Martin E. Energy efficiency measurement in agriculture with imprecise energy content information[J]. Energy Policy, 2014,66(66):198-208. [8] Xu J. Agricultural energy consumption and CO2 emissions in China: trends and emission reduction paths: based on Holt-Winter seasonal-free model and prediction of the 13th five-year plan [J]. Ecological Economy, 2016(2):122-126. [9] Khoshroo A, Mulwa R, Emrouznejad A, et al. A non-parametric Data Envelopment Analysis approach for improving energy efficiency of grape production[J]. Energy, 2013, 63:189-194. DOI:10.1016/j.energy.2013.09.021. [10] Mardani A, Taghavifar H. An overview on energy inputs and environmental emissions of grape production in West Azerbayjan of Iran[J]. Renewable & Sustainable Energy Reviews, 2016,54:918-924. [11] Nabavi-Pelesaraei A, Abdi R, Rafiee S, et al. Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach[J]. Journal of Cleaner Production, 2014,65(4):311-317. [12] Mousavi-Avval S H, Rafiee S, Mohammadi A. Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis[J]. Energy, 2011, 36(2): 909-916. [13] Torki-Harchegani M, Ebrahimi R, Mahmoodi-Eshkaftaki M. Almond production in Iran: An analysis of energy use efficiency (2008–2011) [J]. Renewable and Sustainable Energy Reviews, 2015,41:217-224.DOI:10.1016/j.rser.2014.08.037. [14] Baran M F, Oguz H I, Gokdogan O. Determination of Energy Input-Output Analysis in Plum (Prunus domestica L.) Production[J]. Erwerbs-Obstbau, 2017(7). [15] Tabatabaie S M H, Rafiee S, Keyhani A, et al. Energy and economic assessment of prune production in Tehran province of Iran[J]. Journal of Cleaner Production, 2013,39(1):280-284. [16] Cerutti A K, Sander B, Beccaro G L, et al. A review of studies applying environmental impact assessment methods on fruit production systems[J]. Journal of Environmental Management, 2011,92(10):2277-2286. [17] Xu S, Fan D, Wang S. Re-estimation of regional total factor energy use efficiency in China under environmental constraints[J]. East China Economic Management, 2013(3):60-64. [18] Jiang C, Zhu Q, Ma L. A study on changes and influencing factors of energy efficiency in China's industry[J]. Forum on science and technology in China, 2015(4):51-56. [19] Wu Y, Li Y. A study on industrial energy efficiency and influencing factors in Shandong Province[J]. China Population Resources and Environment, 2015,25(6):114-120. [20] Lin B, Long H. A stochastic frontier analysis of energy efficiency of China's chemical industry[J]. Journal of Cleaner Production, 2015,87(1):235-244. [21] Nassiri S M, Singh S. Study on energy use efficiency for paddy crop using data envelopment analysis

(DEA)

technique[J].

Applied

Energy,

2009,

86(7):1320-1325.

DOI:10.1016/j.apenergy.2008.10.007. [22] Khoshnevisan B, Rafiee S, Omid M, et al. Reduction of CO2 emission by improving energy use efficiency ofgreenhouse cucumber production using DEA approach[J]. Energy, 2013, 55(1): 676-682. [23] Bai X, Li Y, Xie T, et al. Climatic basis of two-harvest-a-year grape cultivation in Guangxi[J]. Journal of Guangxi Agriculture, 2008,23(1):1-4. [24] Liu J, Bai X, Huang J, et al. Cultivation technique two-harvest-a-year Kyoho grape[J]. Journal of

Journal Pre-proof southern agriculture, 2007,38(4):446-448. [25] Khoshnevisan B, Rafiee S, Omid M, et al. Applying data envelopment analysis approach to improve energy efficiency and reduce GHG (greenhouse gas) emission of wheat production[J]. Energy, 2013,58(3):588-593. [26] Bolandnazar E, Keyhani A, Omid M. Determination of efficient and inefficient greenhouse cucumber producers using Data Envelopment Analysis approach, a case study: Jiroft city in Iran[J]. Journal of Cleaner Production, 2014,79(18):108-115. [27] Luo S. Agricultural ecology[M]. Beijing: China Agriculture Press, 2009. [28] Koctürk O M, Engi̇Ndeni̇Z S. Energy and cost analysis of sultana grape growing: a case study of Manisa, west Turkey.[J]. African Journal of Agricultural Research, 2009,4(10):938-943. [29] Cooper W W, Seiford L M, Zhu J. Handbook on Data Envelopment Analysis[J]. International, 2011,71:592. [30] Charnes A, Cooper W, Rhodes E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978,2(6):429-444. [31] Banker R D, Charnes A, Cooper W W. Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis[J]. Mangement Science, 1984,30(9):1078-1092. [32] Ozkan B, Fert C, Karadeniz C F. Energy and cost analysis for greenhouse and open-field grape production[J]. Energy, 2007,32(8):1500-1504. [33] Tian D, Zhang M, Wei X, et al. GIS-Based Energy Consumption and Spatial Variation of Protected Grape Cultivation in China[J]. Sustainability, 2018. [34] Wang J. Evaluation on the energy efficiency and spatial layout characterizations of the protected grape in China[D]. Beijing: China agricultural university, 2015. [35] Reig-MartıNez E, Picazo-Tadeo A J. Analysing farming systems with Data Envelopment Analysis: citrus farming in Spain[J]. Agricultural Systems, 2004,82(1):17-30. [36] Mohammadi A, Rafiee S, Mohtasebi S S, et al. Energy efficiency improvement and input cost saving in kiwifruit production using Data Envelopment Analysis approach[J]. Renewable Energy, 2011,36(9):2573-2579. [37] Pahlavan R, Omid M, Rafiee S, et al. Optimization of energy consumption for rose production in Iran[J]. Energy for Sustainable Development, 2012, 16(2):236-241.

Journal Pre-proof

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Journal Pre-proof Highlights: 1. Assessing energy consumption and utilization of two-harvest-a-year grape cultivation 2. Sorting out production process and key links of two-harvest-a-year grape 3. Comparing energy consumption and output in two production seasons 4. Exploring the level of energy efficiency of two grape production seasons