中国油料作物能源利用效率与CO<sub>2</sub>排放

陈丽; 刘娟; 王末; 李牧

doi:10.12357/cjea.20230283

中国油料作物能源利用效率与CO₂排放

doi: 10.12357/cjea.20230283

陈丽^{1, 2,},
刘娟^{1, 2},
王末^{1, 2},
李牧^3, ,

1.
中国农业科学院农业信息研究所　北京　100081
2.
农业农村部农业大数据重点实验室　北京　100081
3.
天津商业大学公共管理学院　天津　300134

基金项目: 中央级公益性科研院所基本科研业务费专项(Y2021XC17)、天津市哲学社会科学研究规划项目(TJGL21-030)和中国农业科学院创新工程项目(CAAS-ASTIP-2023-AII)资助

详细信息

作者简介:
陈丽, 主要从事土地资源利用与农业大数据技术应用研究。E-mail: chenli02@caas.cn

通讯作者:
李牧, 主要从事城乡人地关系和土地利用规划研究。E-mail: TJCUlm@tjcu.edu.cn

中图分类号: F323.2; S565
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出版历程
- 收稿日期: 2023-05-22
- 录用日期: 2023-10-24
- 修回日期: 2023-11-06
- 网络出版日期: 2023-11-09

Energy use efficiency and CO₂ emissions of oilseed crops in China

CHEN Li^{1, 2
,},
LIU Juan^{1, 2},
WANG Mo^{1, 2},
LI Mu^{3
, ,}

1.
Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
2.
Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Beijing 100081, China
3.
School of Public Management, Tianjin Commercial University, Tianjin 300134, China

Funds: This study was supported by the Central Public-interest Scientific Institution Basal Research Fund of China (Y2021XC17), Tianjin Philosophy and Social Science Research Program (TJGL21-030) and Chinese Academy of Agricultural Sciences innovation project (CAAS-ASTIP-2023-AII).

More Information

Corresponding author: E-mail: TJCUlm@tjcu.edu.cn

摘要

摘要: 作物生产中有效利用能源是可持续农业的一个重要目标。中国作为油料生产和消费大国, 在其生产过程中, 减少过度无效能源消耗, 优化能源利用结构, 提高能源利用效率, 对于农民节本增收、降低温室气体排放和环境影响具有重要意义。本文基于生命周期分析(LCA)视角, 采用生命周期评价和数据包络分析(DEA)方法, 对油菜、大豆、花生3种油料作物能源利用效率和温室气体排放进行了测算, 分析了不同省份能源高效和低效利用的原因, 探究了各省能源节约和温室气体减排的可能性与潜力。结果表明: 1) 3种油料作物生产系统单位能量消耗的产出能力相差不大, 但能源利用效率差异明显, 呈现花生>油菜>大豆的特点。2) 3种油料作物中, 花生温室气体排放量最高[874.96 kg(CO₂ eq)∙hm⁻²], 其次为油菜[660.16 kg(CO₂eq)∙hm⁻²]和大豆[507.07 kg(CO₂eq)∙hm⁻²]; 不同油料作物物质投入和农事操作温室气体排放贡献差异明显, 油菜与花生种植主要温室气体排放源为化肥, 而大豆种植过程中化肥、柴油、灌溉温室气体排放贡献相对均衡。3)油料作物能源利用优化和温室气体减排潜力较大, 油菜、大豆、花生低效省份能源利用优化后, 分别可节约11.97%、16.38%和15.89%的资源, 实现了20.60~616.32 kg(CO₂ eq)∙hm⁻²的减排。因此, 根据区域实际情况, 优化能源低效利用地区的能源利用结构, 探寻产量与碳排双优的生产模式, 对推动油料种植节本增收与绿色发展将发挥重要作用。
- 油料作物 /
- 能源利用效率 /
- 温室气体排放 /
- 生命周期评价模型 /
- 数据包络分析模型
Abstract: Energy is a major component in enhancing agricultural productivity. Accounting for energy efficiency at the production stage of crop is essential for achieving sustainable agriculture. Due to the high level of production and consumption of oil in China, it is of great importance to pay attention to energy consumption and its negatively environmental impacts in the oil production process. Measures of optimizing energy utilization structure, reducing excessive and ineffective energy consumption and improving energy utilization efficiency can be used, in order to increase income, save cost and reduce greenhouse gas emissions synthetically. Academically, a large number of previous studies have contributed to energy use and environmental impacts in the production of oilseed crops, fruits, vegetables, and food crops on various scales. However, there is a lack of studies related to energy use efficiency and greenhouse gas emissions in oil production which concentrate in major oilseed crops production areas nationally so far. Generally, in terms of models used in relevant study areas, methods including life cycle assessment (LCA), data envelopment analysis (DEA), process analysis, energy analysis have been used commonly, which provide valuable references to the present study. Given that oilseed crops production is inherently a life process, this paper combined LCA+DEA methods to estimate the energy utilization efficiency and greenhouse gas emissions of oilseed crops, which helped to rank efficient and inefficient provincial production units. In further, the underlying reasons which caused inefficient energy use were deeply identified in different provinces. Additionally, for purpose of practical application, this paper explored the possibility and potential of energy saving and CO₂ emission reduction in each province. The results showed as follows. 1) There was no significant difference in the output capacity per unit energy consumption among the three studied oilseed crop systems. However, the energy use efficiency of three oilseed crops displayed remarkably differently, which showed peanut > oilseed rape > soybean. 2) Among the three oilseed crops, peanut had the highest CO₂ emissions [874.96 kg(CO₂ eq)∙hm⁻²], followed by oilseed rape [660.16 kg(CO₂ eq)∙hm⁻²] and soybean [507.07 kg(CO₂ eq)∙hm⁻²]. In addition, the contributions of substantiality inputs and agricultural operations to CO₂ emissions varied greatly from different oilseed crops. Specifically, the significant CO₂ emission source of oilseed rape and peanut was fertilizer. Nevertheless, contribution of fertilizer, diesel fuel and irrigation to the CO₂ emissions of soybean showed less different. 3) There was great potential for energy utilization optimization and CO₂ emission reduction. Estimates resulted from this study displayed that about 11.97%, 16.38% and 15.89% of resources invested to oilseed rape, soybean and peanut in inefficient provinces could be saved respectively, which were capable of reducing 20.60−616.32 kg(CO₂ eq)∙hm⁻² emissions as well. Therefore, it is necessary to optimize the energy utilization structure of low efficiency areas according to the actual situation, and explore the production mode of double optimal yield and carbon emissions. This will play an important role in saving money and increasing income for regional oilseed cultivation, as well as green development.
- Oilseed crops /
- Energy use efficiency /
- GHG emissions /
- LCA model /
- DEA model

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图 1 研究边界

Figure 1. Research boundary

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图 2 不同省份油料作物生产系统能源输入贡献占比

Figure 2. Percentages of energy inputs of oilseed crop production system in different provinces

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图 3 中国油料作物生产系统能效指标区域差异

EP、EUE和NE分别表示能源生产率、能源利用效率和净能源。

Figure 3. Regional differences in energy efficiency indicators of oilseed crop production system in China

EP, EUE and NE refer to energy productivity, energy use efficiency and net energy, repectively.

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图 4 油料作物生产系统不同效率值的决策单元(DMU)频数

Figure 4. Frequency of decision making unit (DMU) with different efficiency values of oilseed crop production system

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表 1 研究对象与区域

Table 1. Research object and area

研究对象 Study object	研究区域 Research area
大豆 Soybean	河北、山西、内蒙古、辽宁、吉林、黑龙江、江苏、安徽、山东、河南、湖北、四川、陕西 Hebei, Shanxi, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Jiangsu, Anhui, Shandong, Henan, Hubei, Sichuan, Shaanxi
油菜 Oilseed rape	内蒙古、江苏、浙江、安徽、江西、河南、湖北、湖南、重庆、四川、贵州、云南、陕西、甘肃、青海 Inner Mongolia, Jiangsu, Zhejiang, Anhui, Jiangxi, Henan, Hubei, Hunan, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai
花生 Peanut	河北、辽宁、吉林、安徽、福建、江西、山东、河南、湖北、湖南、广东、广西、四川 Hebei, Liaoning, Jilin, Anhui, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong, Guangxi, Sichuan

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表 2 油料作物生产系统各项能源输入和输出计算公式及相关系数

Table 2. Calculation formula and correlation coefficient of energy input and output in oilseed crop production system

项目 Project	公式 Formula	描述 Description
能源输入 Energy input
种子 Seed	$ {e}_{i}^{\mathrm{s}}={q}_{i}^{\mathrm{s}}\times {\varepsilon }_{i}^{\mathrm{s}} $	$ {e}_{i}^{\mathrm{s}} $表示作物i (即油菜、大豆和花生)的种子能耗(MJ∙hm⁻²); $ {q}_{i}^{\mathrm{s}} $表示作物i的种子用量(kg∙hm⁻²); $ {\varepsilon }_{i}^{\mathrm{s}} $表示作物i的种子能量当量, 油菜、大豆和花生的取值分别为20.9 MJ∙kg⁻¹、16.31 MJ∙kg⁻¹和13.1 MJ∙kg^−1[22] $ {e}_{i}^{\mathrm{s}} $ refers to energy consumption of seed for crop i (MJ∙hm⁻²), which includes oilseed rape, soybean and peanut; $ {q}_{i}^{\mathrm{s}} $ refers to usage amount of seed for crop i (kg∙hm⁻²); $ {\varepsilon }_{i}^{\mathrm{s}} $ refers to seed energy equivalent for crop i, and the corresponding value of oilseed rape, soybean and peanut are 20.9, 16.31 and 13.1 MJ∙kg⁻¹, respectively^[22]
化肥 Chemical fertilizer	$ {e}_{ih}^{\mathrm{f}}={q}_{ih}^{\mathrm{f}}\times {\varepsilon }_{h}^{\mathrm{f}} $	$ {e}_{ih}^{\mathrm{f}} $表示化肥h (即氮肥、磷肥、钾肥和复混肥)的能耗(MJ∙hm⁻²); $ {q}_{ih}^{\mathrm{f}} $表示化肥h施用在作物i的用量(kg∙hm⁻²); $ {\varepsilon }_{h}^{\mathrm{f}} $表示化肥h的能量当量, 氮肥、磷肥、钾肥和复混肥的取值分别为24.0 MJ∙kg⁻¹、8.5 MJ∙kg⁻¹、9.0 MJ∙kg⁻¹和12.8 MJ∙kg^{−1 [23]} $ {e}_{ih}^{\mathrm{f}} $ refers to energy consumption of chemical fertilizer h (MJ∙hm⁻²), which includes nitrogen fertilizer, phosphate fertilizer, potassium fertilizer and compound fertilizer; $ {q}_{ih}^{\mathrm{f}} $ refers to the usage amount of fertilizer h for crop i (kg∙hm⁻²); $ {\varepsilon }_{h}^{\mathrm{f}} $ refers to energy equivalent for fertilizer h, and the corresponding value of nitrogen fertilizer, phosphate fertilizer, potassium fertilizer and compound fertilizer are 24.0, 8.5, 9.0 and 12.8 MJ∙kg⁻¹, respectively^[23]
柴油 Diesel fuel	$ {e}_{i}^{\mathrm{d}}={(q}_{i}^{\mathrm{d}}+{q}_{i}^{\mathrm{m}}\times \phi )/{p}^{\mathrm{d}}\times {\varepsilon }^{\mathrm{d}} $	$ {e}_{i}^{\mathrm{d}} $表示作物i的柴油能耗(MJ∙hm⁻²); $ {q}_{i}^{\mathrm{d}} $表示作物i的燃料动力费(¥∙hm⁻²); $ {q}_{i}^{\mathrm{m}} $表示作物i的机械作业费(¥∙hm⁻²); $ \mathrm{\phi } $表示机械作业费中购买燃料费用占比, 取值40%^[24]; $ {p}^{\mathrm{d}} $表示柴油价格(¥∙kg⁻¹); $ {\varepsilon }^{\mathrm{d}} $表示柴油能量当量, 取值为43.5 MJ∙kg^{−1 [23]} $ {e}_{i}^{\mathrm{d}} $ refers to consumption of diesel fuel for crop i (MJ∙hm⁻²); $ {q}_{i}^{\mathrm{d}} $ refers to fuel and power cost for crop i (¥∙hm⁻²); $ {q}_{i}^{\mathrm{m}} $ refers to machinery cost for crop i (¥∙hm⁻²); $ \mathrm{\phi } $ refers to the proportion of the cost of buying fuel in the total cost of mechanical operation, and the value of $ \mathrm{\phi } $ is 40%^[24]; $ {p}^{\mathrm{d}} $ refers to diesel price (¥∙kg⁻¹); $ {\varepsilon }^{\mathrm{d}} $ refers to diesel fuel energy equivalent, and the value of $ {\varepsilon }^{\mathrm{d}} $ is 43.5 MJ∙kg^{−1 [23]}
电力 Electricity	${e}_{i}^{\mathrm{e} }=\left({q}_{i}^{\mathrm{ir} }-{q}_{i}^{\mathrm{w} }\right)/{p}^{\mathrm{e} }\times {\varepsilon }^{\mathrm{e} }$	$ {e}_{i}^{\mathrm{e}} $表示作物i的电力能耗(MJ∙hm⁻²); ${q}_{i}^{\mathrm{ir} }$表示作物i的灌排费(¥∙hm⁻²); $ {q}_{i}^{\mathrm{w}} $表示作物i灌排费中的水费(¥∙hm⁻²); $ {p}^{\mathrm{e}} $表示农业灌溉电费(¥∙kWh⁻¹); $ {\varepsilon }^{\mathrm{e}} $表示电力能量当量, 取值为12.3 MJ∙kWh^−1[23] $ {e}_{i}^{\mathrm{e}} $ refers to energy consumption of electricity for crop i (MJ∙hm⁻²); ${q}_{i}^{\mathrm{ir} }$ refers to irrigation and drainage fee for crop i (¥∙hm⁻²); $ {q}_{i}^{\mathrm{w}} $ refers to water charges in irrigation and drainage fees for crop i (¥∙hm⁻²); $ {p}^{\mathrm{e}} $ refers to electricity costs for agricultural irrigation (¥∙kWh⁻¹); $ {\varepsilon }^{\mathrm{e}} $ refers to electricity energy equivalent, which is 12.3 MJ∙kWh^−1[23]
人工 Labor	$ {e}_{i}^{\mathrm{p}}={q}_{i}^{\mathrm{p}}\times {\varepsilon }^{\mathrm{p}}/24\times 8 $	$ {e}_{i}^{\mathrm{p}} $表示作物i人工能耗(MJ∙hm⁻²); $ {q}_{i}^{\mathrm{p}} $表示作物i家庭用工天数; $ {\varepsilon }^{\mathrm{p}} $表示男社员劳动力全日(24小时)能量消耗, 取值11.1 MJ∙d^−1[25]; 每天工作时长按8 h计 $ {e}_{i}^{\mathrm{p}} $ refers to energy consumption of human consumption for crop i (MJ∙hm⁻²); $ {q}_{i}^{\mathrm{p}} $ refers to househould employment days for crop i; $ {\varepsilon }^{\mathrm{p}} $ refers to full day (24 hours) energy consumption of male member labor force, which is 11.1 MJ∙d^−1[25]; the working time is assumed as 8 hours per day
能源输出 Energy output
主产品 Main product	$ {e}_{i}^{\mathrm{o}}={q}_{i}^{\mathrm{G}}\times {\varepsilon }_{i}^{\mathrm{o}} $	$ {e}_{i}^{\mathrm{o}} $表示作物i每公顷主产品能源输出量(MJ∙hm⁻²); $ {q}_{i}^{\mathrm{G}} $表示作物i每公顷主产品产量(kg∙hm⁻²); $ {\varepsilon }_{i}^{\mathrm{o}} $表示作物i主产品能量当量, 油菜、大豆和花生的取值分别为20.9 MJ∙kg⁻¹、16.31 MJ∙kg⁻¹和27.7 MJ∙kg^{−1 [22]}; $ {e}_{i}^{\mathrm{o}} $ refers to the energy output per hectare of the main product for crop i (MJ∙hm⁻²); $ {q}_{i}^{\mathrm{G}} $ refers to the yield of main product per hectare for crop i (kg∙hm⁻²); $ {\varepsilon }_{i}^{\mathrm{o}} $ refers to the energy equivalent of the main product for crop i, and the corresponding value for oilseed rape, soybean and peanut are 20.9, 16.31 and 27.7 MJ∙kg⁻¹, respectively^[22]
副产品 By-product	$ {e}_{i}^{\mathrm{b}}={q}_{i}^{\mathrm{G}}\times {\theta }_{i}\times {\varepsilon }_{i}^{\mathrm{b}} $	$ {e}_{i}^{\mathrm{b}} $表示作物i每公顷秸秆能源输出量(MJ∙hm⁻²); $ {\theta }_{i} $表示作物i的草谷比, 不同省份油菜的取值分别为2.05^{①⑩⑪⑬⑭㉓}、2.0^⑥㉑㉒㉔、2.67^{③⑧⑯⑰⑳}, 不同省份大豆的取值分别为1.57^{⑦⑧⑯⑱⑲}、1.7^⑨⑫⑮、1.68^①⑩⑬、1.07^⑳、1.05^㉑, 不同省份花生的取值分别为1.22^{⑦⑧⑫⑮⑱}、1.5^①⑩⑪⑭、1.65^②④⑤㉑ ^[26-27], 上标数字表示不同省份, 见表注; $ {\varepsilon }_{i}^{\mathrm{b}} $表示作物i的副产品能量当量, 油菜、大豆和花生的取值分别为14.14 MJ∙kg⁻¹、15.15 MJ∙kg⁻¹和27.7 MJ∙kg^{−1 [23,28]} $ {e}_{i}^{\mathrm{b}} $ refers to energy output per hectare of straw for crop i (MJ∙hm⁻²); $ {\theta }_{i} $ refers to ratio of grass to grain for crop i; $ {\theta }_{i} $ for oilseed rape in different provinces are 2.05^{①⑩⑪⑬⑭㉓}, 2.0^⑥㉑㉒㉔ and 2.67^{③⑧⑯⑰⑳}, $ {\theta }_{i} $ for soybean in different provinces are 1.57^{⑦⑧⑯⑱⑲}, 1.7^⑨⑫⑮, 1.68^①⑩⑬, 1.07^⑳ and 1.05^㉑, $ {\theta }_{i} $ for peanut in different provinces are 1.22^{⑦⑧⑫⑮⑱}, 1.5^①⑩⑪⑭ and 1.65^②④⑤㉑ ^[26-27], and the superscript refers to different provinces as shown in the notes of the table; $ {\varepsilon }_{i}^{\mathrm{b}} $ refers to by-product energy equivalent for crop i, and the corresponding values for oilseed rape, soybean and peanut are 14.14, 15.15 and 27.7 MJ∙kg⁻¹, respectively ^[23,28]
①: 安徽; ②: 福建; ③: 甘肃; ④: 广东; ⑤: 广西; ⑥: 贵州; ⑦: 河北; ⑧: 河南; ⑨: 黑龙江; ⑩: 湖北; ⑪: 湖南; ⑫: 吉林; ⑬: 江苏; ⑭: 江西; ⑮: 辽宁; ⑯: 内蒙古; ⑰: 青海; ⑱: 山东; ⑲: 山西; ⑳: 陕西; ㉑: 四川; ㉒: 云南; ㉓: 浙江; ㉔: 重庆。草谷比指农作物单位面积地上部秸秆产量与籽粒产量的比值。①: Anhui; ②: Fujian; ③: Gansu; ④: Guangdong; ⑤: Guangxi; ⑥: Guizhou; ⑦: Hebei; ⑧: Henan; ⑨: Heilongjiang; ⑩: Hubei; ⑪: Hunan; ⑫: Jilin; ⑬: Jiangsu; ⑭: Jiangxi; ⑮: Liaoning; ⑯: Inner Mongolia; ⑰: Qinghai; ⑱: Shandong; ⑲: Shanxi; ⑳: Shaanxi; ㉑: Sichuan; ㉒: Yunnan; ㉓: Zhejiang; ㉔: Chongqing. Grass-grain ratio refers to the ratio of straw yield to grain yield per unit area of the crop.

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表 3 油料作物生产系统平均能源输入与输出

Table 3. Average energy inputs and outputs of oilseed crop production system

项目 Project	油菜 Oilseed rape	大豆 Soybean	花生 Peanut
能源输入 Energy input (MJ∙hm⁻²)	8647.94	8125.84	13 931.01
种子 Seed	116.62	1279.71	2838.52
化学肥料 Chemical fertilizer	4170.71	1821.05	3997.82
氮肥 Nitrogen fertilizer	2098.56	472.43	870.65
磷肥 Phosphate fertilizer	72.17	48.84	196.06
钾肥 Potassium fertilizer	31.86	14.85	14.64
复合肥 Compound fertilizer	1968.13	1284.92	2916.48
柴油 Diesel fuel	2675.69	2594.70	3463.48
电力 Electricity	695.13	1846.61	2302.39
人工 Labor	989.79	583.77	1328.80
能源输出 Energy output (GJ∙hm⁻²)	112.87	132.21	188.79
主产品 Main-product	45.06	34.64	50.33
副产品 By-product	67.81	97.57	138.46
能源效率 Energy efficiency
净能源 Net energy (GJ∙hm⁻²)	104.22 36.41^*	76.84 26.51^*	222.10 83.64^*
能源生产力 Energy productivity (kg∙MJ⁻¹)	0.80 0.25^*	0.67 0.26^*	0.61 0.25^*
能源利用效率 Energy use efficiency	13.05 5.21^*	10.46 4.26^*	16.94 7.00^*
^表示仅考虑了主产品能源输出。^ refers to the data only involving the energy output of the main product.

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表 4 中国油料作物生产不同排放源的温室气体排放量

Table 4. GHG emissions from different sources of oilseed crop production in China

kg(CO₂ eq)∙hm⁻²
排放源 Emission source	油菜 Oilseed rape	大豆 Soybean	花生 Peanut
柴油 Diesel fuel	203.72	197.55	263.70
电力 Electricity	34.36	91.28	113.81
化肥 Chemical fertilizer	422.08	218.24	497.45
合计 Total	660.16	507.07	874.96

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表 5 油料作物种植低效省份的能源节约

Table 5. Energy saving in provinces where oilseed crops are planted inefficiently

MJ∙hm⁻²
类型 Types	决策单元 Decision making unit	柴油 Diesel fuel	电力 Electricity	化肥 Chemical fertilizer	人工 Labor	种子 Seed	总能源节约 Total energy saving
油菜 Oilseed rape	甘肃 Gansu	3116.82	763.21	2134.09	0.00	97.35	6111.46
	河南 Henan	157.10	174.84	0.00	0.00	12.07	344.02
	陕西 Shaanxi	1445.93	1181.50	2079.26	335.73	82.32	5124.73
	云南 Yunnan	1551.51	456.17	1775.77	0.34	164.33	3948.12
大豆 Soybean	湖北 Hubei	1071.47	0.00	422.83	0.00	66.22	1560.52
	山西 Shanxi	1588.06	3677.71	2126.48	416.89	114.18	7923.32
	陕西 Shaanxi	1789.28	3001.97	2643.75	224.05	165.51	7824.56
花生 Peanut	河北 Hebei	0.00	10 408.32	990.90	516.58	1241.41	13 157.21
	河南 Henan	0.00	5911.78	2685.82	3.60	1024.42	9625.63
	山东 Shandong	0.00	2020.61	2472.59	856.69	646.83	5996.73

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表 6 能源节约省份温室气体减排潜力

Table 6. GHG emission reduction potential in energy-saving provinces


类型 Types	决策单元 Decision making unit	柴油 Diesel fuel [kg(CO₂ eq)∙hm⁻²]	电力 Electricity [kg(CO₂ eq)∙hm⁻²]	化肥 Chemical fertilizer [kg(CO₂ eq)∙hm⁻²]	总计 Total [kg(CO₂ eq)∙hm⁻²]	减排潜力 Reduction potential (%)
油菜 Oilseed rape	甘肃 Gansu	237.31	37.73	219.30	494.34	51.15
	河南 Henan	11.96	8.64	0.00	20.60	3.20
	陕西 Shaanxi	110.09	58.40	213.67	382.16	53.00
	云南 Yunnan	118.13	22.55	182.48	323.16	51.25
大豆 Soybean	湖北 Hubei	81.58	0.00	43.45	125.03	26.42
	山西 Shanxi	120.91	181.79	218.52	521.23	67.92
	陕西 Shaanxi	136.23	148.39	271.68	556.30	92.69
花生 Peanut	河北 Hebei	0.00	514.49	101.83	616.32	48.54
	河南 Henan	0.00	292.22	276.00	568.23	47.09
	山东 Shandong	0.00	99.88	254.09	353.97	30.33

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