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作物学报 ›› 2026, Vol. 52 ›› Issue (4): 1153-1165.doi: 10.3724/SP.J.1006.2026.55056

• 耕作栽培·生理生化 • 上一篇    下一篇

长江下游冬油菜区应对气候变化的育种和栽培策略研究

杨锐1(), 陈敬东1, 黄郢1, 张学昆1,2, 周登文3, 刘清云4, 徐劲松1, 谢伶俐1, 许本波1,*()   

  1. 1长江大学农学院 / 农业农村部长江中游作物绿色高效生产重点实验室(部省共建) / 湿地生态与农业利用教育部工程研究中心, 湖北荆州434025
    2岳麓山实验室 / 湖南省农业科学院作物所, 湖南长沙 410128
    3湖北省荆州市农业技术推广中心, 湖北荆州 434020
    4湖北省黄冈市浠水县农业技术推广中心, 湖北黄冈 438021
  • 收稿日期:2025-08-20 接受日期:2026-01-22 出版日期:2026-04-12 网络出版日期:2026-02-05
  • 通讯作者: *许本波, E-mail: benboxu@yangtzeu.edu.cn
  • 作者简介:E-mail: ruiyang.stu@yangtzeu.edu.cn
  • 基金资助:
    农业生物育种重大项目(2023ZD04042);农业农村部长江中游油菜单产提升技术集成示范项目(152304045)

Study on breeding and cultivation strategies for winter rapeseed to cope with climate change in the lower reaches of the Yangtze River

Yang Rui1(), Chen Jing-Dong1, Huang Ying1, Zhang Xue-Kun1,2, Zhou Deng-Wen3, Liu Qing-Yun4, Xu Jin-Song1, Xie Ling-Li1, Xu Ben-Bo1,*()   

  1. 1College of Agronomy, Yangtze University / Key Laboratory of Green and Efficient Crop Production in the Middle Reaches of Yangtze River, Ministry of Agriculture and Rural Affairs / Engineering Research Center of Wetland Ecology and Agricultural Use, Ministry of Education, Jingzhou 434025, Hubei, China
    2Yuelu Mountain Laboratory / Institute of Crops, Hunan Academy of Agricultural Sciences, Changsha 410128, Hunan, China
    3Agricultural Technology Extension Center of Jingzhou, Jingzhou 434020, Hubei, China
    4Agricultural Technology Extension Center of Xishui County, Huanggang 438021, Hubei, China
  • Received:2025-08-20 Accepted:2026-01-22 Published:2026-04-12 Published online:2026-02-05
  • Contact: *E-mail: benboxu@yangtzeu.edu.cn
  • Supported by:
    Major Projects of Agricultural Biology Breeding of China(2023ZD04042);Improving Rapeseed Yield Potential Ability in the Middle Reaches of the Yangtze River(152304045)

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摘要：

气候变化对油菜生产具有重要影响, 阐明气候变化条件下品种改良与栽培策略优化对保障油菜生产安全具有重要意义, 本研究基于2009—2023年长江下游油菜主产区多年多点国家区试数据, 采用混合线性模型(MLM)、线性回归与典型相关分析, 系统揭示气象因子与产量、产油量及抗性指标之间的关系。研究表明, 长江下游地区油菜生育期平均气温显著上升, 气温波动和降水不稳定性增强。平均气温上升整体有利于提升籽粒产量和产油量, 但极端天气显著削弱其正效应, 11月低温对产量具有显著负面影响。典型相关分析识别出2类主要气象性状耦合模式: (1) 秋末偏湿、春季温和、春末适度升温的气候条件有利于安全越冬、稳健返青和病害防控, 可显著提升产量, 但油分可能下降; (2) 冷春条件下产量与结构性状受抑, 病害风险增加。建议加强11月低温监测预警, 针对不同气候型采取差异化管理: 在温湿适宜年份优化密度与养分供应以提高含油量; 在冷春年份强化菌核病防控及花期到成熟期的养分补偿。育种上应同步选育稳产抗病型与高油高粒重型, 提升复杂气象条件下的适应力。建立气象-性状-产量多维预警体系, 结合历史气象型与未来预测, 实现品种选育与栽培管理的动态优化。

关键词: 油菜, 气象因子, 典型相关分析, 混合线性模型, 产量, 含油量, 菌核病

Abstract:

Climate change has a significant impact on rapeseed production, making it essential to clarify breeding and management strategies under evolving climatic conditions to ensure production stability. To systematically investigate the relationships between meteorological factors and yield, oil yield, and resistance-related traits, multi-year and multi-location national trial data from major production areas in the lower reaches of the Yangtze River during 2009-2023 were analyzed using a mixed linear model (MLM), linear regression, and canonical correlation analysis. Results showed a significant increase in mean temperature during the rapeseed growing season in this region, accompanied by greater temperature fluctuations and increased precipitation variability. Overall, the rise in mean temperature was beneficial for improving yield and oil production; however, extreme weather events substantially weakened this positive effect, and low temperatures in November had a particularly negative impact on yield. Canonical correlation analysis revealed two dominant meteorology-trait coupling patterns: Type 1 (humid late autumn-moderately cool early spring-moderately warm late spring), which supported safe overwintering, strong regrowth, and effective disease control, thereby significantly boosting yield but potentially reducing oil content; and Type 2 (cold spring), which was associated with suppressed yield and structural traits, as well as increased disease risk. It is recommended to enhance monitoring and early warning systems for extreme weather, especially low temperatures in November, and to adopt targeted management strategies. Under different climatic scenarios, differentiated field practices and a “dual-target” breeding strategy should be implemented: in warm and moist favorable years, optimize planting density and nutrient management to enhance oil content and thousand-seed weight; in cold spring years, apply timely control measures for Sclerotinia sclerotiorum rot and reinforce nutrient supply during the flowering to maturity stages. Breeding efforts should focus simultaneously on developing high-yield, disease-resistant genotypes and high-oil, high-thousand-seed-weight genotypes to enhance adaptability under complex climate conditions. A multidimensional meteorology-trait-yield early warning system should be established, integrating historical climate patterns with future projections to enable dynamic optimization of cultivar selection and field management.

Key words: rapeseed, climatic factors, canonical correlation analysis, mixed linear model, yield, oil content, Sclerotinia disease

表1

各对照品系BLUP换算值"

品系
Line		 产量
Yield		 株高
Plant height		 单株角果数
Silique number
per plant		 每角粒数
Seed number per silique		 千粒重
Thousand seeds weight		 全生育期
Whole growth period
沣油737
Fengyou 737		 224.18 -11.74 12.99 -1.04 0.106 -3.91
秦优10号
Qinyou 10		 15.22 11.66 -34.88 0.28 0.005 -1.53
秦优7号
Qinyou 7		 -104.12 8.04 -51.42 1.79 0.036 0.13
越优1203
Yueyou 1203		 508.78 1.67 8.52 0.10 0.284 -0.11
品系
Line		 含油量
Oil content		 菌核病指数
Sclerotium index		 选育单位
Breeding institution		 作为对照品系年度
Years served as a
control line
沣油737
Fengyou 737		 1.02 1.41 湖南省作物研究所
Crop Research Institute of Hunan province		 2018, 2020-2022
秦优10号
Qinyou 10		 1.76 1.07 咸阳市农业科学研究所
Xianyang Institute of Agricultural Sciences		 2011-2019
秦优7号
Qinyou 7		 1.93 -2.63 陕西杂交油菜研究中心
Hybrid Rapeseed Research Center of Shaanxi province		 2009-2011
越优1203
Yueyou 1203		 -0.02 -0.98 浙江省农业科学院
Zhejiang Academy of Agricultural Sciences		 2022-2023

表2

冬油菜生育时期内各月份气象因子与油菜产量、品质等重要农艺性状的相关性分析"

月份与气象因子
Month and climatic factors		 菌核病病指
Sclerotium index		 单株角果数
Silique number per plant		 株高
Plant height		 每角粒数
Seed number per silique
11月最高气温Max. temp. in Nov. -0.22 0.10 -0.42 0.02
11月最低气温Min. temp. in Nov. 0.16 0.30 0.29 -0.12
11月平均气温日较差DTD in Nov. -0.30 -0.07 0.03 0.22
11月降水量Precipitation in Nov. 0.19 0.03 -0.07 -0.20
11月日照时数Sunshine duration in Nov. -0.38 -0.17 0.04 0.28
12月降水量Precipitation in Dec. 0.55* 0.15 0.29 -0.01
12月日照时数Sunshine duration in Dec. -0.55* -0.34 -0.03 0.10
1月平均气温Mean temp. in Jan. 0.30 0.59* -0.19 -0.70**
1月最低气温Min. temp. in Jan. 0.21 0.29 0.23 -0.36
2月平均气温Mean temp. in Feb. -0.21 0.34 -0.20 -0.26
2月最高气温Max. temp. in Feb. -0.28 0.25 -0.31 -0.27
2月最低气温Min. temp. in Feb. 0.07 0.46 -0.33 -0.45
3月平均气温Mean temp. in Mar. 0.26 0.66** -0.33 -0.44
3月最低气温Min. temp. in Mar. 0.15 0.60* -0.29 -0.48
4月平均气温Mean temp. in Apr. 0.31 0.11 -0.10 -0.12
月份与气象因子
Month and climatic factors		 千粒重
Thousand seeds weight		 全生育期
Whole growth period		 含油量
Oil content		 产量
Yield		 产油量
Oil yield
11月最高气温Max. temp. in Nov. 0.53* -0.20 -0.20 -0.20 -0.39
11月最低气温Min. temp. in Nov. -0.05 -0.14 0.02 0.52* 0.41
11月平均气温日较差DTD in Nov. 0.23 -0.43 -0.56* 0.47 0.23
11月降水量Precipitation in Nov. -0.13 0.52* 0.43 -0.45 -0.26
11月日照时数Sunshine duration in Nov. 0.16 -0.31 -0.53* 0.43 0.26
12月降水量Precipitation in Dec. -0.30 0.31 0.31 -0.03 -0.05
12月日照时数Sunshine duration in Dec. 0.08 -0.12 -0.40 0.05 0.14
1月平均气温Mean temp. in Jan. 0.54* -0.17 0.04 0.38 0.23
1月最低气温Min. temp. in Jan. 0.14 0.28 -0.22 0.53* 0.48
2月平均气温Mean temp. in Feb. 0.48 -0.10 0.53* 0.01 0.08
2月最高气温Max. temp. in Feb. 0.59* -0.30 0.13 0.09 0.05
2月最低气温Min. temp. in Feb. 0.57* -0.03 -0.11 0.39 0.19
3月平均气温Mean temp. in Mar. 0.51 -0.76** 0.09 0.52* 0.16
3月最低气温Min. temp. in Mar. 0.39 -0.59* 0.08 0.45 0.21
4月平均气温Mean temp. in Apr. 0.02 -0.58* -0.13 0.09 -0.12

图1

2009-2023年温度变化趋势 R2上星号表示F检验显著性。*表示P < 0.05, ***表示P < 0.001。"

图2

2009-2023年降水量和日照时数变化趋势"

图3

2009-2023年产量、产油量变化"

图4

2009-2023年油菜生育期内各气象要素逐月变化趋势 A: 平均气温逐月变化趋势; B: 气温日较差逐月变化趋势; C: 最高气温逐月变化趋势; D: 最低气温逐月变化趋势; E: 降水量逐月变化趋势; F: 日照时数逐月变化趋势。每个箱体的上下界分别表示25%和75%分位, 箱体外的上下短线分别表示10%和90%分位, 箱体内部的实线和虚线分别表示中值和平均值; F检验检测是否存在显著线性趋势, 箱体上方*表示各月份年际间变化趋势的显著性, 以***、*分别表示P < 0.001、P < 0.05; 图中百分数表示变异系数。"

表3

偏高或偏低气象因子所在年份和月份分布"

气象因子
Factor		 偏高或偏低
Above or below		 年份
Year		 月份
Month		 气象因子
Factor		 偏高或偏低
Above or below		 年份
Year		 月份
Month
最低气温
Min. temp.		 偏高Above 2010 11 平均气温Mean temp. 偏高Above 2020 2
偏高Above 2011 11 偏高Above 2010 1
偏高Above 2012 11 最高气温Max. temp. 偏高Above 2010 1
偏高Above 2014 11 降水量Precipitation 偏高Above 2013 10
偏高Above 2017 11 偏高Above 2016 10
偏高Above 2018 11 偏高Above 2009 11
偏高Above 2019 11 偏高Above 2015 11
偏高Above 2020 11 偏高Above 2012 12
偏高Above 2021 11 偏高Above 2018 12
偏高Above 2018 1 偏高Above 2015 1
偏高Above 2019 1 偏高Above 2017 1
偏高Above 2019 2 偏高Above 2019 1
偏高Above 2016 3 偏高Above 2013 2
偏高Above 2018 3 偏高Above 2018 2
偏高Above 2019 3 偏高Above 2023 2
偏高Above 2020 3 偏高Above 2009 3
最低气温
Min. temp.		 偏高Above 2021 3 降水量Precipitation 偏高Above 2021 3
偏高Above 2022 3 偏高Above 2015 4
偏高Above 2011 4 偏高Above 2023 4
偏高Above 2015 4 偏低Below 2009 10
偏低Below 2009 11 偏低Below 2018 10
偏低Below 2013 11 偏低Below 2019 10
偏低Below 2015 11 偏低Below 2023 10
偏低Below 2016 11 偏低Below 2010 11
偏低Below 2022 11 偏低Below 2013 11
偏低Below 2023 11 偏低Below 2011 12
偏低Below 2023 12 偏低Below 2014 12
偏低Below 2017 1 偏低Below 2020 12
偏低Below 2017 2 偏低Below 2021 12
偏低Below 2009 3 偏低Below 2010 1
偏低Below 2011 3 偏低Below 2013 1
偏低Below 2012 3 偏低Below 2010 2
偏低Below 2015 3 偏低Below 2015 2
偏低Below 2017 3 偏低Below 2016 2
偏低Below 2023 3 偏低Below 2010 3
偏低Below 2010 4 偏低Below 2010 4
偏低Below 2012 4 偏低Below 2019 4
偏低Below 2014 4

图5

重要性状和气象条件间典型相关结构图 图中展示了2对典型变量对: U1-V1与U2-V2。箭头表示变量之间的相关作用; 蓝色为正相关, 红色为负相关。U表示由气象因子组合构成的典型变量, V表示由性状组合构成的典型变量。箭头上的数字为典型载荷(权重), 越大表示变量对U/V贡献越显著。|系数| < 0.2时: 不绘制箭头、认为它对典型变量的贡献可忽略。"

[1] 王汉中. 以新需求为导向的油菜产业发展战略. 中国油料作物学报, 2018, 40: 613-617.
doi: 10.7505/j.issn.1007-9084.2018.05.001
Wang H Z. New-demand oriented oilseed rape industry developing strategy. Chin J Oil Crop Sci, 2018, 40: 613-617 (in Chinese with English abstract).
[2] 周香玉, 徐劲松, 谢伶俐, 等. 甘蓝型油菜苗期响应渍害胁迫的生理调控机制. 作物学报, 2024, 50: 1015-1029.
doi: 10.3724/SP.J.1006.2024.34116
Zhou X Y, Xu J S, Xie L L, et al. Physiological mechanisms in response to waterlogging during seedling stage of Brassica napus L. Acta Agron Sin, 2024, 50: 1015-1029 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2024.34116
[3] 宁宁, 莫娇, 胡冰, 等. 长江流域不同生态区油菜籽关键品质比较研究. 作物学报, 2023, 49: 3315-3327.
doi: 10.3724/SP.J.1006.2023.34017
Ning N, Mo J, Hu B, et al. Comparative study on the processing quality of winter rape in different ecological zones of the Yangtze River valley. Acta Agron Sin, 2023, 49: 3315-3327 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2023.34017
[4] Jannat A, Ishikawa-Ishiwata Y, Furuya J. Does climate change affect rapeseed production in exporting and importing countries? evidence from market dynamics syntheses. Sustainability, 2022, 14: 6051.
doi: 10.3390/su14106051
[5] 李谷成, 牛秋纯, 冷博峰, 等. 新时代十年: 我国油菜产业发展与路径选择. 中国油料作物学报, 2024, 46: 228-235.
doi: 10.19802/j.issn.1007-9084.2023248
Li G C, Niu Q C, Leng B F, et al. The decade of rapeseed industry in the new era: development and its path choice. Chin J Oil Crop Sci, 2024, 46: 228-235 (in Chinese with English abstract).
[6] Mohamed I A A, Shalby N, El-Badri A M, et al. Multipurpose uses of rapeseed (Brassica napus L.) crop (food, feed, industrial, medicinal, and environmental conservation uses) and improvement strategies in China. J Agric Food Res, 2025, 20: 101794.
[7] 王瑞元. 我国粮油产销情况喜人. 中国油脂, 2025, 50(5): 1-4.
Wang R Y. Production and consumption of China’s grain and oil. China Oils Fats, 2025, 50(5): 1-4 (in Chinese).
[8] 殷艳, 廖星, 余波, 等. 我国油菜生产区域布局演变和成因分析. 中国油料作物学报, 2010, 32: 147-151.
Yin Y, Liao X, Yu B, et al. Regional distribution evolvement and development tendency of Chinese rapeseed production. Chin J Oil Crop Sci, 2010, 32: 147-151 (in Chinese with English abstract)
[9] 谢雄泽, 谢捷, 褚乾梅, 等. 长江流域冬油菜需水量及水分盈亏特征分析. 作物学报, 2024, 50: 1829-1840.
doi: 10.3724/SP.J.1006.2024.34190
Xie X Z, Xie J, Chu Q M, et al. Analysis of water requirement and water surplus/deficit characteristics of winter rapeseed in Yangtze River Basin. Acta Agron Sin, 2024, 50: 1829-1840 (in Chinese with English abstract)
doi: 10.3724/SP.J.1006.2024.34190
[10] 张智. 长江流域冬油菜产量差与养分效率差特征解析. 华中农业大学博士学位论文, 湖北武汉, 2018.
Zhang Z. Characteristic Analysis of Yield Gap and Nutrient Use Efficiency Gap of Winter Oilseed Rape in Yangtze River Basin. PhD Dissertation of Huazhong Agricultural University, Wuhan, Hubei, China, 2018 (in Chinese with English abstract).
[11] Pithan F, Schatt L. Diurnal temperature range trends differ below and above the melting point. Geophys Res Lett, 2024, 51: e2024GL109751.
[12] Pineda M, Barón M. Health status of oilseed rape plants grown under potential future climatic conditions assessed by invasive and non-invasive techniques. Agronomy, 2022, 12: 1845.
doi: 10.3390/agronomy12081845
[13] Zhang S Q, Ren G Y, Zheng X, et al. Changes in the mean and extreme temperature in the Yangtze River Basin over the past 120 years. Weather Clim Extrem, 2023, 40: 100557.
[14] Huang H J, Zhu Z W, Li J. Disentangling the unprecedented Yangtze River Basin extreme high temperatures in summer 2022: combined impacts of the reintensified La Niña and strong positive NAO. J Clim, 2024, 37: 927-942.
doi: 10.1175/JCLI-D-23-0466.1
[15] 张学昆, 张春雷, 廖星, 等. 2008年长江流域油菜低温冻害调查分析. 中国油料作物学报, 2008, 30: 122-126.
Zhang X K, Zhang C L, Liao X, et al. Investigation on 2008'low temperature and freeze injure on winter rape along Yangtze River. Chin J Oil Crop Sci, 2008, 30: 122-126 (in Chinese with English abstract).
[16] Zohner C M, Mo L D, Renner S S, et al. Late-spring frost risk between 1959 and 2017 decreased in North America but increased in Europe and Asia. Proc Natl Acad Sci USA, 2020, 117: 12192-12200.
doi: 10.1073/pnas.1920816117
[17] Sun B, Xue R F, Li W L, et al. How does Mei-yu precipitation respond to climate change? Natl Sci Rev, 2023, 10: nwad246.
[18] Wei S Z, Hsu P C, Xie J H. Effects of intraseasonal oscillation on timing and subseasonal predictability of Mei-yu onset over the Yangtze River Basin. J Clim, 2024, 37: 2277-2295.
doi: 10.1175/JCLI-D-23-0504.1
[19] Ding Y H, Liu Y Y, Hu Z Z. The record-breaking Mei-yu in 2020 and associated atmospheric circulation and tropical SST anomalies. Adv Atmos Sci, 2021, 38: 1980-1993.
doi: 10.1007/s00376-021-0361-2
[20] Shi H R, Zhang J Q, Zhao B, et al. Surface brightening in eastern and central China since the implementation of the clean air action in 2013: causes and implications. Geophys Res Lett, 2021, 48: e2020GL091105.
[21] Song Z Y, Chen L T, Wang Y J, et al. Effects of urbanization on the decrease in sunshine duration over Eastern China. Urban Clim, 2019, 28: 100471.
doi: 10.1016/j.uclim.2019.100471
[22] Raza A. Eco-physiological and biochemical responses of rapeseed (Brassica napus L.) to abiotic stresses: consequences and mitigation strategies. J Plant Growth Regul, 2021, 40: 1368-1388.
doi: 10.1007/s00344-020-10231-z
[23] Fahim A M, Cao L R, Ma L, et al. Integrated transcriptome and metabolome analysis revealed hub genes and metabolites associated with subzero temperature tolerance following cold acclimation in rapeseed (Brassica rapa L.). Plant Physiol Biochem, 2025, 221: 109647.
doi: 10.1016/j.plaphy.2025.109647
[24] Ghafoor A, Karim H, Asghar M A, et al. Effect of high-temperature, drought and nutrients availability on morpho-physiological and molecular mechanisms of rapeseed; an overview. Pak J Bot, 2021, 53: 2321-2320.
[25] Secchi M A, Fernandez J A, Stamm M J, et al. Effects of heat and drought on canola (Brassica napus L.) yield, oil, and protein: a meta-analysis. Field Crops Res, 2023, 293: 108848.
doi: 10.1016/j.fcr.2023.108848
[26] 谢伶俐, 李永铃, 许本波, 等. 油菜耐渍机理解析及遗传改良研究进展. 作物学报, 2025, 51: 287-300.
doi: 10.3724/SP.J.1006.2025.44121
Xie L L, Li Y L, Xu B B, et al. Progress on waterlogging tolerance mechanism and genetic improvement in rapeseed. Acta Agron Sin, 2025, 51: 287-300 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2025.44121
[27] Piepho H P, Möhring J, Melchinger A E, et al. BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 2008, 161: 209-228.
doi: 10.1007/s10681-007-9449-8
[28] Pathy T L, Mohanraj K. Estimating best linear unbiased predictions (BLUP) for yield and quality traits in sugarcane. Sugar Technol, 2021, 23: 1295-1305.
doi: 10.1007/s12355-021-01011-4
[29] Zorić M, Gunjača J, Galić V, et al. Best linear unbiased predictions of environmental effects on grain yield in maize variety trials of different maturity groups. Agronomy, 2022, 12: 922.
doi: 10.3390/agronomy12040922
[30] 常世豪, 耿臻, 杨青春, 等. 基于BLUP值的夏大豆产量与农艺性状的相关分析. 作物杂志, 2023(5): 10-15.
Chang S H, Geng Z, Yang Q C, et al. Correlation analysis of yield and agronomic traits of summer soybean based on BLUP value. Crops, 2023(5): 10-15 (in Chinese with English abstract).
[31] Marjanović-Jeromela A, Terzić S, Jankulovska M, et al. Dissection of year related climatic variables and their effect on winter rapeseed (Brassica napus L.) development and yield. Agronomy, 2019, 9: 517.
doi: 10.3390/agronomy9090517
[32] Pullens J W M, Kersebaum K C, Böttcher U, et al. Model sensitivity of simulated yield of winter oilseed rape to climate change scenarios in Europe. Eur J Agron, 2021, 129: 126341.
doi: 10.1016/j.eja.2021.126341
[33] Brown J K M, Beeby R, Penfield S. Yield instability of winter oilseed rape modulated by early winter temperature. Sci Rep, 2019, 9: 6953.
doi: 10.1038/s41598-019-43461-7 pmid: 31061437
[34] Li X H, Chen C, Yang X, et al. The optimisation of rapeseed yield and growth duration through adaptive crop management in climate change: evidence from China. Ital J Agron, 2022, 17: 2104.
[35] Han X, Tang Q Q, Xu L P, et al. Genome-wide detection of genotype environment interactions for flowering time in Brassica napus. Front Plant Sci, 2022, 13: 1065766.
doi: 10.3389/fpls.2022.1065766
[36] Li L L, Qiao J W, Yao J, et al. Automatic freezing-tolerant rapeseed material recognition using UAV images and deep learning. Plant Methods, 2022, 18: 5.
doi: 10.1186/s13007-022-00838-6 pmid: 35027060
[37] 陈于婷, 丁晓雨, 许本波, 等. 气候变暖对冬油菜产量、品质及重要农艺性状的影响. 作物学报, 2025, 51: 516-525.
doi: 10.3724/SP.J.1006.2025.44074
Chen Y T, Ding X Y, Xu B B, et al. Effects of climate warming on yield, quality-related and agronomic traits of winter rapeseed (Brassica napus L.). Acta Agron Sin, 2025, 51: 516-525 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2025.44074
[38] O'Sullivan C A, Belt K, Thatcher L F. Tackling control of a cosmopolitan phytopathogen: Sclerotinia. Front Plant Sci, 2021, 12: 707509.
doi: 10.3389/fpls.2021.707509
[39] Verdejo J F, Calderini D F. Resilience of rapeseed to temperature increase during early grain filling in a high yielding environment. Field Crops Res, 2025, 330: 109950.
doi: 10.1016/j.fcr.2025.109950
[40] Alberio C, Aguirrezábal L A N. Meta-analysis unravels common responses of seed oil fatty acids to temperature for a wide set of genotypes of different plant species. Front Plant Sci, 2024, 15: 1476311.
doi: 10.3389/fpls.2024.1476311
[41] Wang R S, Zhao C, Asseng S, et al. Winter dormant wheat will benefit from mean temperature increase of 2℃ when well-watered and fertilized in the main producing regions of China. Glob Change Biol, 2025, 31: e70324.
[42] Zheng C Y, Zhang J, Chen J, et al. Nighttime warming increases winter-sown wheat yield across major Chinese cropping regions. Field Crops Res, 2017, 214: 202-210.
doi: 10.1016/j.fcr.2017.09.014
[43] Zhou Y J, Xu L, Xu Y Z, et al. A meta-analysis of the effects of global warming on rice and wheat yields in a rice-wheat rotation system. Food Energy Secur, 2021, 10: e316.
[44] 丛日环, 张智, 鲁剑巍. 长江流域不同种植区气候因子对冬油菜产量的影响. 中国油料作物学报, 2019, 41: 894-903.
doi: 10.19802/j.issn.1007-9084.2019046
Cong R H, Zhang Z, Lu J W. Climate impacts on yield of winter oilseed rape in different growth regions of the Yangtze River Basin. Chin J Oil Crop Sci, 2019, 41: 894-903 (in Chinese with English abstract).
doi: 10.19802/j.issn.1007-9084.2019046
[45] Canales J, Verdejo J F, Calderini D F. Transcriptome and physiological analysis of rapeseed tolerance to post-flowering temperature increase. Int J Mol Sci, 2023, 24: 15593.
doi: 10.3390/ijms242115593
[46] Rivelli G M, Calderini D F, Abeledo L G, et al. Yield and quality traits of wheat and rapeseed in response to source-sink ratio and heat stress in post-flowering. Eur J Agron, 2024, 152: 127028.
doi: 10.1016/j.eja.2023.127028
[47] Liu S S, Xiong L X, Fang W, et al. Effects of nitrogen, phosphorous, and potassium fertilization on rapeseed yield under freeze stress. Crop Environ, 2025, 4: 143-153.
doi: 10.1016/j.crope.2025.04.002
[48] Liang J P, Li H, Li N, et al. Analysis and prediction of the impact of socio-economic and meteorological factors on rapeseed yield based on machine learning. Agronomy, 2023, 13: 1867.
doi: 10.3390/agronomy13071867
[49] Soni S, Kumar S, Sood A K, et al. Modeling of aphid complex and its associated natural enemies in rapeseed-mustard in relation to climatic factors. J Agrometeorol, 2021, 23: 207-212.
doi: 10.54386/jam.v23i2
[50] He Y Q, Revell B J, Leng B F, et al. The effects of weather on oilseed rape (OSR) yield in China: future implications of climate change. Sustainability, 2017, 9: 418.
doi: 10.3390/su9030418
[51] Tian Z, Ji Y H, Sun L X, et al. Changes in production potentials of rapeseed in the Yangtze River Basin of China under climate change: a multi-model ensemble approach. J Geogr Sci, 2018, 28: 1700-1714.
doi: 10.1007/s11442-018-1538-1
[52] Han J C, Zhang Z, Luo Y C, et al. The RapeseedMap10 database:annual maps of rapeseed at a spatial resolution of 10 m based on multi-source data. Earth Syst Sci Data, 2021, 13: 2857-2874.
[53] Rajković D, Marjanović Jeromela A, Pezo L, et al. Yield and quality prediction of winter rapeseed: artificial neural network and random forest models. Agronomy, 2022, 12: 58.
doi: 10.3390/agronomy12010058
[54] Abebaw S E. A global review of the impacts of climate change and variability on agricultural productivity and farmers' adaptation strategies. Food Sci Nutr, 2025, 13: e70260.
[55] Butkevičienė L M, Kriaučiūnienė Z, Pupalienė R, et al. Influence of sowing time on yield and yield components of spring rapeseed in Lithuania. Agronomy, 2021, 11: 2170.
doi: 10.3390/agronomy11112170
[56] Wu W, Shah F, Ma B L. Understanding of crop lodging and agronomic strategies to improve the resilience of rapeseed production to climate change. Crop Environ, 2022, 1: 133-144.
doi: 10.1016/j.crope.2022.05.005
[57] Guo C Y, Bai Z H, Wang X Z, et al. Spatio-temporal assessment of greenhouse gas emission from rapeseed production in China by coupling nutrient flows model with LCA approach. Food Energy Secur, 2022, 11: e398.
[58] HabibTabar Shiadeh S S, Feizabadi Y, Kosari-Moghaddam A. To what extent cultivar selection can affect the environmental impact of rapeseed production? Environ Sustain Indic, 2025, 26: 100619.
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