Scientia Agricultura Sinica ›› 2025, Vol. 58 ›› Issue (11): 2118-2144.doi: 10.3864/j.issn.0578-1752.2025.11.005

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

The Possible Effects of Global Warming on Cropping Systems in China XV. Adjustment of China’s Oil Crop Patterns to Adapt to Future Climate Change

GUO ShiBo1,2,3(), ZHANG ZhenTao1, GUO ErJing1,4, ZHAO Jin1, LIU ZhiJuan1, ZHAO Chuang1, YANG XiaoGuang1()   

  1. 1 College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193
    2 Hebei Provincial Institute of Meteorological Sciences, Shijiazhuang 050021
    3 Key Laboratory of Meteorology and Ecological Environment of Hebei Province, Shijiazhuang 050021
    4 China Meteorological Administration Training Centre (CMATC), Beijing 100081
  • Received:2024-08-25 Accepted:2024-11-15 Online:2025-06-01 Published:2025-06-09
  • Contact: YANG XiaoGuang

Abstract:

【Objective】 Oil crops are important sources of edible vegetable oil and feed protein. Soybean, canola, and peanut are the three major oil crops of China. This study aimed to clarify the climate suitability, and high-stable yield of oil crops under future climate change, and to propose adjustment of crop patterns framework, provided a theoretical basis for improving the total oil production and ensuring the safety of grain and oil in China under the background of climate change. 【Method】 Based on the yield, climate factors and agricultural technological factors of three oil crops from 1981 to 2019, a random forest model was constructed to predict yield under SSP1-2.6 and SSP5-8.5 scenarios from 2021 to 2060. Based on the crops’ climate suitability and high-stable yield, a comprehensive suitable area was divided. Combined with the impact of climate change, a framework of crops’ patterns adjustment to adapt to future climate change was proposed. Finally, the crops production, environment benefits and economic benefits before and after adjustment were clarified. 【Result】 (1) From 1981 to 2019, the proportion of soybean, canola, and peanut planting areas in the region with suitable climate and high-stable yield was 11.6%, 38.3%, and 46.0%, respectively. Future, the proportion of soybean planting area in this region will decrease, the proportion of canola will increase, and the proportion of peanuts will not change significantly. (2) After future adjustment, the planting area of soybean, canola and peanut will increase by 1.8×106-2.6×106 hm2, 3.2×106-3.9×106 hm2 and 0.8×106-1.8×106 hm2, respectively. (3) The production of soybean, canola and peanut will increase by 140%, 150% and 150%, respectively, while the self-sufficiency rate of oil crop will increase by 7.9%-13.0%. The negative impact of climate change on production will decrease by 1.0×106-1.8 ×106 t. The total amount of nitrogen fertilizer application and greenhouse gas emissions will decrease by 1.1×106-1.5×106 t and 9.7×106-12.7×106 t CO2-eq, respectively. The total economic benefits will increase by 0.3×105-0.4×105 million yuan. 【Conclusion】 Under future climate change, the framework of adjustment of crop patterns for oil crops based on the climate suitability, high-stable yield and climate change impacts could expand the planting area of oil crops, increase crops production, reduce the negative impact of climate change, reduce total nitrogen fertilizer use and greenhouse gas emissions, and increase economic benefits.

Key words: climate change, oil crops, climate suitability, high and stable yield, adjustment of crop patterns

Fig. 1

Main planting regions and harvested area for three major oil crops of 2019"

Fig. 2

Specific scheme of adjustment of crop patterns"

Table 1

Specific scheme of adjustment of crop patterns for different oil and grain crops."

综合适宜区
Comprehensive suitability
产量变化
Yield change
种植布局调整
Adjustment of crop pattern
油料作物
Oil crop
主粮作物
Grain crop
油料作物
Oil crop
主粮作物
Grain crop
SH/UH SH/UH + + 不进行面积调整 No adjustment
SH/UH SH/UH + - 总面积的75%分配给油料作物 75% of the total area is adjusted to oil crops
SH/UH SH/UH - + 总面积的75%分配给主粮作物 75% of the total area is adjusted to grain crops
SL/UL SH/UH + + 将该区域内主粮占总种植面积的比例进行排序,将15%分位数为阈值,每个地级市多余的面积分配给油料作物
The proportion of grain crops in the total planting area in the region was ranked, the 15% quantile was used as the threshold, and the excess area of each prefecture-level city is adjusted to oil crops
SL/UL SH/UH + - 总面积的50%分配给油料作物 50% of the total area is adjusted to oil crops
SL/UL SH/UH - + 总面积的100%分配给主粮作物
100% of the total area is adjusted to grain crops
SH/UH SL/UL + + 将该区域内主粮作物占总面积的比例进行排序,将35%分位数为阈值,每个地级市多余的面积分配给油料作物
The proportion of grain crops in the total planting area in the region was ranked, the 35% quantile was used as the threshold, and the excess area of each prefecture-level city is adjusted to oil crops
SH/UH SL/UL + - 总面积的100%分配给油料作物 100% of the total area is adjusted to oil crops
SH/UH SL/UL - + 总面积的50%分配给主粮作物 50% of the total area is adjusted to grain crops
其余地级市 Other cities 将主粮作物单产由大到小进行排序,按顺序将总面积的75%分配给主粮作物,直至总产达到2019年的总产
Sort the yield of grain crops from high to low, and allocate 75% of the total area to grain crops in order until the total production reaches the total production of 2019

Table 2

Greenhouse gases emissions coefficients of agricultural inputs for different crops"

农业投入 Agricultural input 系数Coefficient 单位 Unit 文献来源Reference source
氮肥 N fertilizer 8.30 kg CO2-eq/kg N [22]
磷肥 P fertilizer 0.79 kg CO2-eq/kg P2O5
钾肥 K fertilizer 0.55 kg CO2-eq/kg K2O
农药 Pesticides 19.13 kg CO2-eq/kg Pesticides
柴油 Diesel 1.43 kg CO2-eq/L [40]
劳动力 Labor 0.86 kg CO2-eq/(person/day) [41]
灌溉用电量 Electricity for irrigation 0.92 kg CO2-eq/kWh [38]
大豆种子 Soybean seed 0.58 kg CO2-eq/kg [42]
花生种子 Peanut seed 0.92 kg CO2-eq/kg [43]
油菜种子 Canola seed 0.83 kg CO2-eq/kg [37]
玉米种子 Maize seed 1.22 kg CO2-eq/kg [38]
小麦种子 Wheat seed 0.40 kg CO2-eq/kg [39]

Fig. 3

Validation results of random forest for the yield of each crop"

Fig. 4

Changes of spatial distribution and planting area changes of crops’ comprehensive suitability regions under historical and future climate change"

Fig. 5

Changes of crops productions in different comprehensive suitability regions under historical and future climate change"

Fig. 6

Spatial distribution of city-level soybean, peanut and rapeseed planting area after crop substitution under future climate change"

Fig. 7

Spatial distribution of province-level soybean, peanut and maize planting area after crop substitution under future climate change"

Fig. 8

Spatial distribution of province-level canola and wheat planting area after crop substitution under future climate change"

Table 3

Changes of oil crops production after crop pattern adjustment under future climate change"

布局调整
Patterns adjustment
作物
Crop
影响
Impact
SSP1-2.6 SSP5-8.5
2030s 2050s 2030s 2050s
调整前
Before adjustment
大豆
Soybean
总产 Production (×106 t) 19.2 19.1 19.1 18.9
气候变化对总产的影响
Production change under climate change (×105 t)
-2.9 -4.5 -4.1 -5.7
油菜
Canola
总产 Production (×106 t) 13.4 13.1 13.2 13.0
气候变化对总产的影响
Production change under climate change (×105 t)
-4.2 -9.0 -6.2 -8.0
花生
Peanut
总产 Production (×106 t) 16.6 16.4 16.6 16.3
气候变化对总产的影响
Production change under climate change (×105 t)
-3.0 -5.2 -3.2 -6.3
调整后
After adjustment
大豆
Soybean
总产 Production (×106 t) 27.5 27.3 27.1 25.7
气候变化对总产的影响
Production change under climate change (×105 t)
1.4 0.6 1.0 -0.7
油菜
Canola
总产 Production (×106 t) 20.2 19.7 20.1 19.1
气候变化下总产的变化
Production change under climate change (×105 t)
-0.2 -0.5 0.1 -0.9
花生
Peanut
总产 Production (×106 t) 27.3 25.2 26.8 22.5
气候变化对总产的影响
Production change under climate change (×105 t)
-0.9 -1.3 -1.4 -1.7

Fig. 9

Spatial distribution of province-level canola and wheat planting area after crop substitution under future climate change"

Fig. 10

Spatial distribution of province-level canola and wheat planting area after crop substitution under future climate change"

[1]
LU K D, ARSHAD M, MA X Y, ULLAH I, WANG J J, SHAO W. Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6-GCMs. International Journal of Climatology, 2022, 42(15): 7703-7729.
[2]
LI W L, SUN B, WANG H J, ZHOU B T, LI H X, XUE R F, DUAN M K, LUO X C, AI W W. Anthropogenic impact on the severity of compound extreme high temperature and drought/rain events in China. NPJ Climate and Atmospheric Science, 2023, 6: 79.
[3]
吴欣宇, 朱秀芳. 中国不同植被区对极端气候的响应差异. 生态学报, 2023, 43 (24): 10202-10215.
WU X Y, ZHU X F. Differential analysis of vegetation response to extreme climate in different vegetation regions of China. Acta Ecologica Sinica, 2023, 43 (24): 10202-10215. (in Chinese)
[4]
LENG G Y, HUANG M Y. Crop yield response to climate change varies with crop spatial distribution pattern. Scientific Reports, 2017, 7: 1463.

doi: 10.1038/s41598-017-01599-2 pmid: 28469171
[5]
ZHU P, BURNEY J, CHANG J F, JIN Z N, MUELLER N D, XIN Q C, XU J L, YU L, MAKOWSKI D, CIAIS P. Warming reduces global agricultural production by decreasing cropping frequency and yields. Nature Climate Change, 2022, 12(11): 1016-1023.
[6]
LAM H M, REMAIS J, FUNG M C, XU L Q, SUN S S. Food supply and food safety issues in China. The Lancet, 2013, 381(9882): 2044-2053.
[7]
周振亚, 李建平, 张晴, 罗其友. 中国植物油产业发展现状、问题及对策研究. 中国农学通报, 2011, 27(32): 92-97.
ZHOU Z Y, LI J P, ZHANG Q, LUO Q Y. The developing status, problem and countermeasure investigation of the vegetable oil industry in China. Chinese Agricultural Science Bulletin, 2011, 27(32): 92-97. (in Chinese)

doi: 10.11924/j.issn.1000-6850.2011-1202
[8]
LESK C, ROWHANI P, RAMANKUTTY N. Influence of extreme weather disasters on global crop production. Nature, 2016, 529(7584): 84-87.
[9]
HEINO M, KINNUNEN P, ANDERSON W, RAY D K, PUMA M J, VARIS O, SIEBERT S, KUMMU M. Increased probability of hot and dry weather extremes during the growing season threatens global crop yields. Scientific Reports, 2023, 13: 3583.

doi: 10.1038/s41598-023-29378-2 pmid: 36869041
[10]
农业农村部市场预警专家委员会. 中国农业展望报告(2022-2031). 北京: 中国农业科学技术出版社, 2021.
Market Early Warning Expert Committee of the Ministry of Agriculture and Rural Affairs. China agricultural outlook report (2022-2031). Beijing: China Agricultural Science and Technology Press, 2021. (in Chinese)
[11]
农业农村部市场预警专家委员会. 中国农业展望报告(2023-2032). 北京: 中国农业科学技术出版社, 2023.
Market Early Warning Expert Committee of the Ministry of Agriculture and Rural Affairs. China Agricultural Outlook Report (2023-2032). Beijing: China Agricultural Science and Technology Press, 2023. (in Chinese)
[12]
SLOAT L L, DAVIS S J, GERBER J S, MOORE F C, RAY D K, WEST P C, MUELLER N D. Climate adaptation by crop migration. Nature Communications, 2020, 11: 1243.

doi: 10.1038/s41467-020-15076-4 pmid: 32144261
[13]
刘珍环, 杨鹏, 吴文斌, 李正国, 游良志. 近30年中国农作物种植结构时空变化分析. 地理学报, 2016, 71(5): 840-851.

doi: 10.11821/dlxb201605012
LIU Z H, YANG P, WU W B, LI Z G, YOU L Z. Spatio-temporal changes in Chinese crop patterns over the past three decades. Acta Geographica Sinica, 2016, 71(5): 840-851. (in Chinese)

doi: 10.11821/dlxb201605012
[14]
TAN Q H, LIU Y J, DAI L, PAN T. Shortened key growth periods of soybean observed in China under climate change. Scientific Reports, 2021, 11: 8197.

doi: 10.1038/s41598-021-87618-9 pmid: 33854171
[15]
HE L, JIN N, YU Q. Impacts of climate change and crop management practices on soybean phenology changes in China. Science of the Total Environment, 2020, 707: 135638.
[16]
ZHANG J, LIU Y J. Decoupling of impact factors reveals the response of cash crops phenology to climate change and adaptive management practice. Agricultural and Forest Meteorology, 2022, 322: 109010.
[17]
鲁韦坤, 李蒙, 胡雪琼, 李湘. 气候变化对云南橡胶潜在种植区的影响. 应用气象学报, 2023, 34(3): 379-384.
LU W K, LI M, HU X Q, LI X. Impact of climate change on potential planting areas of rubber trees in Yunnan. Journal of Applied Meteorological Science, 2023, 34(3): 379-384. (in Chinese)
[18]
GUO S B, ZHAO J, ZHAO C, GUO E J, LIU Z J, HARRISON M T, LIU K, ZHANG T Y, YANG X G. Adapting crop land-use in line with a changing climate improves productivity, prosperity and reduces greenhouse gas emissions. Agricultural Systems, 2024, 217: 103905.
[19]
ZHAO J C, WANG C, SHI X Y, BO X Z, LI S, SHANG M F, CHEN F, CHU Q Q. Modeling climatically suitable areas for soybean and their shifts across China. Agricultural Systems, 2021, 192: 103205.
[20]
RISING J, DEVINENI N.Crop switching reduces agricultural losses from climate change in the United States by half under RCP 8.5. Nature Communications, 2020, 11: 4991.
[21]
XIE W, ZHU A F, ALI T, ZHANG Z T, CHEN X G, WU F, HUANG J K, DAVIS K F. Crop switching can enhance environmental sustainability and farmer incomes in China. Nature, 2023, 616(7956): 300-305.
[22]
LIU Z T, YING H, CHEN M Y, BAI J, XUE Y F, YIN Y L, BATCHELOR W D, YANG Y, BAI Z H, DU M X, et al. Optimization of China’s maize and soy production can ensure feed sufficiency at lower nitrogen and carbon footprints. Nature Food, 2021, 2(6): 426-433.
[23]
JIANG Y L, WANG X H, HUO M Y, CHEN F, HE X K. Changes of cropping structure lead diversity decline in China during 1985-2015. Journal of Environmental Management, 2023, 346: 119051.
[24]
王斌, 张秀芳, 姜宁, 谢永刚, 朱伟峰, 宿宝江. 基于农业生产资料价格指数的灌区农业水价研究. 节水灌溉, 2021(1): 95-99.
WANG B, ZHANG X F, JIANG N, XTE Y G, ZHU W F, SU B J. Research on agricultural water price in irrigation district based on price indices of agricultural means of production. Water Saving Irrigation, 2021(1): 95-99 (in Chinese)
[25]
邵华英. 基于ARIMA模型的粮食价格波动分析——以玉米为例. 社会科学前沿, 2023, 12(5): 2470-2478.
SHAO H Y. Price fluctuation analysis of grain based on the ARIMA model—A case study of corn. Advances in Social Sciences. 2023, 12 (5): 2470-2478. (in Chinese)
[26]
GUO S B, GUO E J, ZHANG Z T, DONG M Q, WANG X, FU Z Z, GUAN K X, ZHANG W M, ZHANG W J, ZHAO J, LIU Z J, ZHAO C, YANG X G. Impacts of mean climate and extreme climate indices on soybean yield and yield components in NorthEast China. Science of the Total Environment, 2022, 838: 156284.
[27]
ZHANG Q, HAN J H, YANG X Y. Effects of direct heat stress on summer maize and risk assessment. Theoretical and Applied Climatology, 2021, 146(1): 755-765.
[28]
DUAN Y W, MA Z G, YANG Q. Characteristics of consecutive dry days variations in China. Theoretical and Applied Climatology, 2017, 130(1): 701-709.
[29]
ZHAO J, YANG X G. Distribution of high-yield and high-yield- stability zones for maize yield potential in the main growing regions in China. Agricultural and Forest Meteorology, 2018, 248: 511-517.
[30]
GOMES V H F, IJFF S D, RAES N, AMATAL I L, SALOMÃO R P, COELHO L D S, MATOS F D D A, CASTILHO C V, FILHO D D A L, LÓPEZ D C, et al. Species distribution modelling: Contrasting presence-only models with plot abundance data. Scientific Reports, 2018, 8: 1-12.
[31]
JIANG T C, WANG B, XU X J, CAO Y X, LIU D L, HE L, JIN N, MA H J, CHEN S, ZHAO K F, et al. Identifying sources of uncertainty in wheat production projections with consideration of crop climatic suitability under future climate. Agricultural and Forest Meteorology, 2022, 319: 108933.
[32]
ADALIBIEKE W, CUI X Q, CAI H W, YOU L Z, ZHOU F. Global crop-specific nitrogen fertilization dataset in 1961-2020. Scientific Data, 2023, 10: 617.

doi: 10.1038/s41597-023-02526-z pmid: 37696817
[33]
NEMECEK T, ROESCH A, BYSTRICKY M, JEANNERET P, LANSCHE J, STÜSSI M, GAILLARD G. Swiss agricultural life cycle assessment: A method to assess the emissions and environmental impacts of agricultural systems and products. The International Journal of Life Cycle Assessment, 2024, 29(3): 433-455.
[34]
国家发展和改革委员会. 全国农产品成本收益资料汇编. 北京: 中国统计出版社, 2020.
National Development and Reform Commission. National compilation of agricultural product cost and benefit data. Beijing: China Statistics Press, 2020. (in Chinese)
[35]
ZHANG X, XIAO G M, LI H, WANG L G, WU S X, WU W L, MENG F Q. Mitigation of greenhouse gas emissions through optimized irrigation and nitrogen fertilization in intensively managed wheat-maize production. Scientific Reports, 2020, 10: 5907.

doi: 10.1038/s41598-020-62434-9 pmid: 32245982
[36]
HE S N, CHEN Y, XIANG W, CHEN X W, WANG X L, CHEN Y. Carbon and nitrogen footprints accounting of peanut and peanut oil production in China. Journal of Cleaner Production, 2021, 291: 125964.
[37]
陈中督, 徐春春, 纪龙, 方福平. 2004—2015年长江中下游地区冬油菜生产碳足迹的时空变化. 中国生态农业学报(中英文), 2019, 27(7): 1105-1114.
CHEN Z D, XU C C, JI L, FANG F P. Spatial and temporal changes in carbon footprint for oilseed rape production in the middle and lower reaches of Yangtze River during 2004-2015 Chinese Journal of Eco-Agriculture, 2019, 27(7): 1105-1114. (in Chinese)
[38]
HUANG S H, DING W C, JIA L L, HOU Y P, ZHANG J J, XU X P, XU R, ULLAH S, LIU Y X, HE P. Cutting environmental footprints of maize systems in China through Nutrient Expert management. Journal of Environmental Management, 2021, 282: 111956.
[39]
朱永昶, 李玉娥, 姜德锋, 邹晓霞. 基于生命周期评估的冬小麦-夏玉米种植系统碳足迹核算: 以山东省高密地区为例. 农业资源与环境学报, 2017, 34(5): 473-482.
ZHU Y C, LI Y E, JIANG D F, ZOU X X. Life cycle assessment on carbon footprint of winter wheat-summer maize cropping system based on survey data of Gaomi in Shandong Province, China. Journal of Agricultural Resources and Environment, 2017, 34(5): 473-482. (in Chinese)
[40]
CLARK S, KHOSHNEVISAN B, SEFEEDPARI P. Energy efficiency and greenhouse gas emissions during transition to organic and reduced-input practices: Student farm case study. Ecological Engineering, 2016, 88: 186-194.
[41]
CHEN Z D, XU C C, JI L, FENG J F, LI F B, ZHOU X Y, FANG F P. Effects of multi-cropping system on temporal and spatial distribution of carbon and nitrogen footprint of major crops in China. Global Ecology and Conservation, 2020, 22: e00895.
[42]
黄晓敏, 陈长青, 陈铭洲, 宋振伟, 邓艾兴, 张俊, 郑成岩, 张卫建. 2004—2013年东北三省主要粮食作物生产碳足迹. 应用生态学报, 2016, 27(10): 3307-3315.

doi: 10.13287/j.1001-9332.201610.036
HUANG X M, CHEN C Q, CHEN M Z, SONG Z W, DENG A X, ZHANG J, ZHENG C Y, ZHANG W J. Carbon footprints of major staple grain crops production in three provinces of NorthEast China during 2004-2013. Chinese Journal of Applied Ecology, 2016, 27(10): 3307-3315. (in Chinese)
[43]
邹晓霞, 张晓军, 王月福, 王铭伦. 山东省小麦-夏直播花生种植体系碳足迹. 应用生态学报, 2018, 29(3): 850-856.

doi: 10.13287/j.1001-9332.201803.020
ZOU X X, ZHANG X J, WANG Y F, WANG M L. Carbon footprint of wheat-summer direct-seeding peanut planting system in Shandong Province, China. Chinese Journal of Applied Ecology, 2018, 29(3): 850-856. (in Chinese)
[44]
GUILPART N, IIZUMI T, MAKOWSKI D. Data-driven projections suggest large opportunities to improve Europe’s soybean self- sufficiency under climate change. Nature Food, 2022, 3(4): 255-265.
[45]
SMERALD A, KRAUS D, RAHIMI J, FUCHS K, KIESE R, BUTTERBACH-BAHL K, SCHEER C. A redistribution of nitrogen fertiliser across global croplands can help achieve food security within environmental boundaries. Communications Earth & Environment, 2023, 4: 315.
[46]
SANTACHIARA G, SALÜAGIOTTI F, ROTUNDO J L. Nutritional and environmental effects on biological nitrogen fixation in soybean: A meta-analysis. Field Crops Research, 2019, 240: 106-115.
[1] XUE Wei, XU LiJun, NIE YingYing, WU XinJia, YAN YiDan, YE LiMing, LIU XinWei. Study on Dominant Factors Affecting Spatial Variation of Soil Organic Carbon in Hulunbuir Grassland [J]. Scientia Agricultura Sinica, 2024, 57(12): 2378-2389.
[2] YANG WangHua, LIU ZhiJuan, GONG JingJin, FU ZhenZhen, ZHANG TaiLin, ZHANG XiaoLong, SHEN YanJun, YANG XiaoGuang. Drought Risk for Spring Maize in the Future and Response to Climate Change in the Northeast China [J]. Scientia Agricultura Sinica, 2024, 57(12): 2336-2349.
[3] ZHANG WeiJian, SHANG ZiYin, ZHANG Jun, YAN ShengJi, DENG AiXing, ZHANG Xin, ZHENG ChengYan, SONG ZhenWei. Standardized Establishment and Improvement of Accounting System of Agriculture Greenhouse Gas Emission [J]. Scientia Agricultura Sinica, 2023, 56(22): 4467-4477.
[4] SHI XinRui, HAN BaiShu, WANG ZiQian, ZHANG YuanLing, LI Ping, ZONG YuZheng, ZHANG DongSheng, GAO ZhiQiang, HAO XingYu. Investigation on the Effects of Climate Change on the Growth and Yield of Different Maturity Winter Wheat Varieties in Northern China Based on the APSIM Model [J]. Scientia Agricultura Sinica, 2023, 56(19): 3772-3787.
[5] ZHANG ZhiLiang, HE ZhiHao, RU XiaoYa, JIANG TengCong, HE YingBin, FENG Hao, YU Qiang, HE JianQiang. Influence of Future Climate Change on the Climate Suitability of Potato Cultivation in China [J]. Scientia Agricultura Sinica, 2023, 56(18): 3530-3542.
[6] ZHANG WenJing, ZHAO Jin, CUI WenQian, LI ManYao, LI E, GONG XiaoYa, YANG XiaoGuang. Effects of Changing Normal and Extreme Climate States on Maize Meteorological Yield in Northeast China [J]. Scientia Agricultura Sinica, 2023, 56(10): 1859-1870.
[7] ZHAO ZhengXin,WANG XiaoYun,TIAN YaJie,WANG Rui,PENG Qing,CAI HuanJie. Effects of Straw Returning and Nitrogen Fertilizer Types on Summer Maize Yield and Soil Ammonia Volatilization Under Future Climate Change [J]. Scientia Agricultura Sinica, 2023, 56(1): 104-117.
[8] GUO ShiBo, ZHANG FangLiang, ZHANG ZhenTao, ZHOU LiTao, ZHAO Jin, YANG XiaoGuang. The Possible Effects of Global Warming on Cropping Systems in China XIV. Distribution of High-Stable-Yield Zones and Agro-Meteorological Disasters of Soybean in Northeast China [J]. Scientia Agricultura Sinica, 2022, 55(9): 1763-1780.
[9] REN Yifang,YANG ZhangPing,LING Fenghua,XIAO LiangWen. Risk Zoning of Heat Stress Risk Zoning of Dairy Cows in Jiangsu Province and Its Characteristics Affected by Climate Change [J]. Scientia Agricultura Sinica, 2022, 55(22): 4513-4525.
[10] JianZhao TANG,Jing WANG,DengPan XIAO,XueBiao PAN. Research Progress and Development Prospect of Potato Growth Model [J]. Scientia Agricultura Sinica, 2021, 54(5): 921-932.
[11] ZHANG WeiJian, YAN ShengJi, ZHANG Jun, JIANG Yu, DENG Aixing. Win-Win Strategy for National Food Security and Agricultural Double-Carbon Goals [J]. Scientia Agricultura Sinica, 2021, 54(18): 3892-3902.
[12] FANG Rui,YU ZhenHua,LI YanSheng,XIE ZhiHuang,LIU JunJie,WANG GuangHua,LIU XiaoBing,CHEN Yuan,LIU JuDong,ZHANG ShaoQing,WU JunJiang,Stephen J HERBERT,JIN Jian. Effects of Elevated CO2 Concentration and Warming on Soil Carbon Pools and Microbial Community Composition in Farming Soil [J]. Scientia Agricultura Sinica, 2021, 54(17): 3666-3679.
[13] KaiYuan GONG, Liang HE, DingRong WU, ChangHe LÜ, Jun LI, WenBin ZHOU, Jun DU, Qiang YU. Spatial-Temporal Variations of Photo-Temperature Potential Productivity and Yield Gap of Highland Barley and Its Response to Climate Change in the Cold Regions of the Tibetan Plateau [J]. Scientia Agricultura Sinica, 2020, 53(4): 720-733.
[14] WANG MingLei,SHI WenJiao. Spatial-Temporal Changes of Newly Cultivated Land in Northern China and Its Zoning Based on Driving Factors [J]. Scientia Agricultura Sinica, 2020, 53(12): 2435-2449.
[15] SUN JianFei,ZHENG JuFeng,CHENG Kun,YE Yi,ZHUANG Yuan,PAN GenXing. Quantifying Carbon Sink by Biochar Compound Fertilizer Project for Domestic Voluntary Carbon Trading in Agriculture [J]. Scientia Agricultura Sinica, 2018, 51(23): 4470-4484.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!