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作物学报 ›› 2024, Vol. 50 ›› Issue (5): 1287-1299.doi: 10.3724/SP.J.1006.2024.32030

• 耕作栽培·生理生化 • 上一篇    下一篇

稻油系统周年产量差及形成因素探究: 以湖北省武穴市为例

曹馨元(), 杜明利, 王宇诚, 陈欣华, 陈佳欣, 凌霄霞, 黄见良, 彭少兵, 邓南燕*()   

  1. 作物遗传改良全国重点实验室 / 农业农村部长江中游作物生理生态与耕作重点实验室 / 湖北洪山实验室 / 华中农业大学植物科学技术学院, 湖北武汉 430070
  • 收稿日期:2023-08-01 接受日期:2024-01-12 出版日期:2024-05-12 网络出版日期:2024-01-26
  • 通讯作者: 邓南燕, E-mail: nydeng@mail.hzau.edu.cn
  • 作者简介:E-mail: caoxinyuan@webmail.hzau.edu.cn
  • 基金资助:
    国家自然科学基金项目(31901424);湖北省现代种业“揭榜挂帅”项目(Research and Development of Modernized Rice Breeding Technology and Translation of Certified Seed Selection)

Evaluation of annual yield gap and yield limiting facters in rice-rapeseed cropping system: an example from Wuxue city, Hubei province, China

CAO Xin-Yuan(), DU Ming-Li, WANG Yu-Cheng, CHEN Xin-Hua, CHEN Jia-Xin, LING Xiao-Xia, HUANG Jian-Liang, PENG Shao-Bing, DENG Nan-Yan*()   

  1. National Key Laboratory of Crop Genetic Improvement / MARA Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River / Hubei Hongshan Laboratory / College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
  • Received:2023-08-01 Accepted:2024-01-12 Published:2024-05-12 Published online:2024-01-26
  • Contact: E-mail: nydeng@mail.hzau.edu.cn
  • Supported by:
    National Natural Science Foundation of China(31901424);Seed Industry Modernization of “Open Bidding for Selecting the Best Candidates” Program of Hubei Province(Research and Development of Modernized Rice Breeding Technology and Translation of Certified Seed Selection)

摘要:

明确农户水平稻油系统的产量差及进一步增产的限制因素对保障我国粮油安全具有重要作用。本研究以我国典型稻油系统生产区湖北省武穴市为研究对象, 采用作物模型与田间调查相结合的方法评估了该地区稻油系统周年产量差, 并使用单因素方差分析和条件推断树综合比较了农户在土壤条件和管理措施上的差异, 以探究该地区限制稻油系统产量进一步增长的主要栽培因素及可行的增产途径, 为因地制宜地缩小产量差提供新思路。结果表明: (1) 武穴市水稻季和油菜季的潜在产量分别为11.79 t hm-2和4.43 t hm-2, 按照水稻和油菜籽粒的能量当量换算系统周年能量后, 稻油系统的最高周年潜在能量为284 GJ hm-2。水稻季和油菜季的平均实际产量分别为8.11 t hm-2和1.82 t hm-2, 系统平均实际周年能量为165 GJ hm-2。该地区稻油系统的平均周年相对产量差(产量差与潜在产量的比值)为42%, 其中油菜季(59%)比水稻季(31%)具有更大的产量提升空间。相较于湖北省和长江流域的平均水平, 武穴市稻油系统周年潜在能量相近, 而周年实际能量分别低13%和5%, 导致该地区的产量差相对较大, 其中分别有83%和61%的农户相对产量差大于湖北省和长江流域平均水平。(2) 该地区周年产量较低的农户具有以下主要特征: 土壤为沙壤土, 耕层较浅; 水稻季虫草害防治效果差, 水稻季肥料做底肥一次施用且轻施氮、钾肥; 油菜季重施肥料, 且油菜机收损失较大。(3) 武穴市89%的农户选择种植常规稻品种黄华占, 其实际产量已达到该品种潜在产量的90%左右; 种植油菜品种的种类较多且产量差异较大。综上, 武穴市稻油系统仍具有较大的增产空间; 缩小当地稻油系统产量差的技术措施包括: 适当深耕提高土壤生产力; 油菜季选择当地适宜的高产油菜品种; 水稻季加强推广高产优质杂交稻品种, 重点关注增加水稻用种量, 提高直播密度和播种时的封闭除草, 系统周年施肥管理上应降低油菜季而提高水稻季的肥料用量, 水稻季仅施底肥的农户适当增施追肥等。

关键词: 产量差, 田间调查, 稻油系统, 作物模型, 管理措施

Abstract:

To ensure national food and edible oil security, it is important to identify the yield gap and yield-limiting factors of rice-rapeseed cropping system at farmer level. In this study, Wuxue city, Hubei province, a typical rice-rapeseed cropping system production area in China was selected for the research. The annual system yield gap was evaluated by a mixed approach of crop modeling and field investigation. Comparisons were conducted among smallholders in terms of soil conditions and management practices by the methods of one-way ANOVA and conditional inference tree. The objective of this study is to identify the crucial yield-limiting factors for smallholders, to explore practical strategies to further increase system yield, and to provide innovative insight into how to adapt specific strategies to close the yield gap based on local conditions. The results showed as follows: (1) The potential yields of rice and rapeseed seasons in Wuxue were 11.79 t hm-2 and 4.43 t hm-2, respectively, and the maximum annual system potential energy was 284 GJ hm-2 based on the equivalent energy of rice and rapeseed. The actual yields for rice and rapeseed seasons were 8.11 t hm-2 and 1.82 t hm-2, respectively, and the average annual actual system energy was 165 GJ hm-2. The average annual relative yield gap (the ratio of yield gap to potential yield) was 42%, and rapeseed (59%) had a greater space for yield increase than rice (31%) within the system. Compared with the average yields of Hubei province and Yangtze River Valley (YRV), the annual potential yield in Wuxue was similar, while the annual actual yield was 13% and 5% lower, respectively, resulting in a relatively large system yield gap in Wuxue. Specifically, approximately 83% and 61% of smallholders in Wuxue had larger relative yield gaps than the average levels in Hubei and the YRV, respectively. (2) Smallholders with relative low system yields presented the following characteristics: sandy-loam soil and low plowing depths, severe weed and pest damage, all fertilizers were applied as basal fertilizer in rice season, low annual fertilization input in rice season and high input in rapeseed season, and high rapeseed mechanical harvesting damage. (3) Most (89%) of smallholders in Wuxue planted the conventional rice Huanghuazhan, which has reached approximately 90% of its potential yield. In addition, rapeseed yield varied among different varieties. In conclusion, the rice-rapeseed system in Wuxue still had a large space for increasing production. The technical measures to reduce the yield gap of the local rice-rapeseed system including: appropriate deep plowing to increase soil production capacity, choosing suitable rapeseed high-yielding varieties in the rapeseed season. For rice season promoting hybrid rice varieties with high potential yield and good quality, increasing planting density, and strengthening weed control at sowing stage in rice season, and emphasizing topdressing in which only basal fertilizer is applied in rice season. Moreover, for the whole seoson fertilizer management it is important for local smallholders to reduce the amount in rapeseed season and increase the amount in rice season.

Key words: yield gap, field investigation, rice-rapeseed cropping system, crop modeling, management practices

附表1

ORYZA和CROPGRO-Canola主要校正的模型参数及定义"

模型
Model
参数
Parameter
定义
Definition
ORYZA DVRJ 幼苗期生长发育速率(℃ d-1) Development rate in juvenile phase (℃ d-1)
DVRI 光合敏感期生长发育速率(℃ d-1) Development rate in photoperiod-sensitive phase (℃ d-1)
DVRP 穗分化期生长发育速率(℃ d-1) Development rate in panicle development (℃ d-1)
DVRR 生殖生长期生长发育速率(℃ d-1) Development rate in reproductive phase (℃ d-1)
CROPGRO-
Canlo
EM-FL 萌发到始花的光热时间(℃ d)
Photothermal days between plant emergence and flower appearance (℃ d)
FL-SH 始花到第一个荚形成的光热时间(℃ d) Photothermal days between first flower and first pod (℃ d)
FL-SD 始花到第一个籽粒形成的光热时间(℃ d) Photothermal days between first flower and first seed (℃ d)
SD-PM 第一个籽粒形成到生理成熟的光热时间(℃ d)
Photothermal days between first seed and physiological maturity (℃ d)
FL-LF 始花到叶片面积停止扩大的光热时间(℃ d)
Photothermal days first flower and end of leaf expansion (℃ d)
LFMAX 30℃、350 vpm CO2和高光照条件下的叶片最大光合速率(mg CO2 m-2 s-1)
Maximum leaf photosynthesis rate at 30℃, 350 vpm CO2, and high light (mg CO2 m-2 s-1)
SLAVR 标准生长条件下的特定品种比叶面积(cm2 g-1)
Specific leaf area of cultivar under standard growth conditions (cm2 g-1)
SIZIF 最大全叶面积(三片叶)(cm2) Maximum size of full leaf (cm2)
XFRT 每日光合产物分配给种子+荚的最大比例
Maximum fraction of daily growth that is partitioned to seed and shell
WTPSD 最大粒重(g) Maximum weight per seed (g)
SFDUR 标准生长条件下籽粒灌浆持续的光热时间(℃ d)
Seed filling duration for pod cohort at standard growth conditions (℃ d)
SDPDV 标准生长条件下每个荚的籽粒数(pod-1) Average seed per pod under standard growing conditions (pod-1)
PODUR 最佳生长条件下达到籽粒完成灌浆的光热时间(℃ d)
Photothermal days required to reach the final pod load under optimal (℃ d)
THRSH 成熟期时籽粒占籽粒+荚重量的最大比例 The maximum ratio of (seed/(seed+shell)) at maturity
FRSTMF 最后一片叶子伸展后分配给茎的养分比例
The increased partitioning weight which is allocated to stem when the maximum V-stage occurs
FRLFF 最后一片叶子伸展后分配给叶的养分比例
The increased partitioning weight which is allocated to leaf when the maximum V-stage occurs
FREEZ1 叶片生长的最低温度(℃) Temperature thresholds for leaf growth due to freezing (℃)
FREEZ2 叶片存活的最低温度(℃) Temperature thresholds for leaf survival due to freezing (℃)
YLEAF 在各XLEAF时期营养分配给叶的比例 Daily dry matter partitioning to leaf in each XLEAF
YSTEM 在各XLEAF时期营养分配给茎的比例 Daily dry matter partitioning to stem in each XLEAF

附表2

校正后的ORYZA模型参数"

参数
Parameter
隆两优华占
Longliangyouhuazhan
黄华占
Huanghuazhan
DVRJ 0.000,569,905 0.000,765,9
DVRI 0.000,757,60 0.000,807,6
DVRP 0.000,680,80 0.000,769,8
DVRR 0.001,442,43 0.001,684,2

附表3

校正后的CROPGRO-Canola模型参数"

参数
Parameter
华油杂62
Huayouza 62
参数
Parameter
华油杂62
Huayouza 62
CSDL 23.73 SIZLF 97.01
PPSEN -0.019 WTPSD 0.008
EM-FL 42.83 SFDUR 27.61
FL-SH 6.85 SDPDV 25.41
FL-SD 10.82 PODUR 5.17
SD-PM 31.44 THRSH 53.93
FL-LF 2.062 FRLFF 0.22
LFMAX 2.000 FRSTMF 0.70
SLAVR 256.3

附图1

模型校正和验证的结果 模型校正的模拟值与实测值在生物量(a)、生育期(b)和产量(c)上的比较, 验证的模拟值与实测值在生物量(d)、生育期(e)和产量(f)上的比较。决定系数(R2)越接近于1, RMSE (均方根误差)和nRMSE (归一化均方根误差)越小, 则表明模型的模拟表现越好。LLYHZ, 杂交稻品种隆两优华占; HHZ, 常规稻品种黄华占; HYZ62, 油菜品种华油杂62。"

图1

不同播期下的水稻季(a、e)、油菜季(b、f)及稻油系统(c、d、g、h)潜在产量及生育期 (a、e): LLYHZ和HHZ分别为杂交稻品种隆两优华占和常规稻品种黄华占; (b、f): Yp和Yw分别表示灌溉和雨养潜在产量; (c、d、g、h): LLYHZ-HYZ62为系统1、HHZ-HYZ62为系统2。误差线表示2011-2022年产量均值的标准差。"

图2

湖北省武穴市稻油系统生产现状调查地点分布 地图来源于湖北省地理信息公共服务平台(https://hubei.tianditu. gov.cn/standardMap), 审图号: 鄂S (2023)009号。"

图3

武穴市稻油系统的潜在产量、实际产量和相对产量差的分布情况 (a): 水稻品种隆两优华占(LLYHZ)和黄华占(HHZ)的潜在产量(Yp)和实际产量(Ya); (b): 系统1和2的油菜品种华油杂62 (HYZ62)的Yp和Ya; (c): 系统1 (system1, LLYHZ-HYZ62)和系统2 (system2, HHZ-HYZ62)的Yp和Ya; (d): 水稻、油菜及系统的相对产量差, 即产量差占Yp的比例。红色菱形和黄色三角形分别表示湖北和长江流域的平均产量水平[6]。箱线图的上下边缘值分别表示95%和5%分位数, 箱的上下边界分别表示75%和25%分位数, 箱内部的实线为中位数, 虚线为平均值, 黑色点表示离群值。"

图4

不同土壤条件和管理措施下的水稻季、油菜季和稻油系统的产量比较 水稻品种中Hybrid为杂交稻品种, Other为其他常规稻品种, HHZ为常规稻品种黄华占; 油菜品种中Other为其他品种, YG2009为阳光2009, ZY28为浙油28, H919为华919, ZS11为中双11。氮、磷、钾肥分别表示N、P2O5、K2O的施用量。不同的字母标注表示在0.05概率水平差异显著, 误差线表示均值的标准误。"

图5

水稻、油菜和稻油系统的生产决策树分析 氮、磷、钾肥用量分别表示表示纯N、P2O5、K2O施用量(kg hm-2)。每个节点内的P表示该变量二元分类出的两组数据之间置换检验的P值, n表示该变量包含的样本数。"

[1] 潘孝武, 何强, 张武汉, 舒服, 邢俊杰, 孙平勇, 邓华凤. 新形势下长江流域稻作发展的思考. 杂交水稻, 2015, 30(6): 1-5.
Pan X W, He Q, Zhang W H, Shu F, Xing J J, Sun P Y, Deng H F. Reflection of rice development in Yangtze Rice Basin under the new situation. Hybrid Rice, 2015, 30(6): 1-5 (in Chinese with English abstract).
[2] 赵正洪, 戴力, 黄见良, 潘晓华, 游艾青, 赵全志, 陈光辉, 周政, 胡文彬, 纪龙. 长江中游稻区水稻产业发展现状、问题与建议. 中国水稻科学, 2019, 33: 553-564.
Zhao Z H, Dai L, Huang J L, Pan X H, You A Q, Zhao Q Z, Chen G H, Zhou Z, Hu W B, Ji L. Status, problems and solutions in rice industry development in the middle reaches of the Yangtze River. Chin J Rice Sci, 2019, 33: 553-564 (in Chinese with English abstract).
doi: 10.16819/j.1001-7216.2019.9061
[3] van Ittersum M K, Cassman K G. Yield gap analysis-rationale, methods and applications-introduction to the special issue. Field Crops Res, 2013, 143: 1-3.
doi: 10.1016/j.fcr.2012.12.012
[4] Jeong H, Jang T, Seong C, Park S. Assessing nitrogen fertilizer rates and split applications using the DSSAT model for rice irrigated with urban wastewater. Agric Water Manag, 2014, 141: 1-9.
doi: 10.1016/j.agwat.2014.04.009
[5] Hoogenboom G, Porter C H, Boote K J, Shelia V, Wilkens P W, Singh U, White J W, Asseng S, Lizaso J I, Moreno L P, Pavan W, Ogoshi R, Hunt L A, Tsuji G Y, Jones J W. The DSSAT Crop Modeling Ecosystem:Advances in Crop Modelling for a Sustainable Agriculture. Cambridge: Burleigh Dodds Science Publishing, 2019. pp 173-216.
[6] Huang J D, Cao X Y, Kuai J, Cheng H, Du H, Peng S B, Huang J L, Deng N Y. Evaluation of production capacity for rice-rapeseed cropping system in China. Field Crops Res, 2023, 293: 108842.
doi: 10.1016/j.fcr.2023.108842
[7] 赵鹏飞, 黄文超, 高超男, 曹国鑫, 张宏彦, 李晓林. 小麦白穗病发生与主要栽培管理措施的关系研究初报. 华北农学报, 2012, 27(增刊1): 368-373.
Zhao P F, Huang W C, Gao C N, Cao G X, Zhang H Y, Li X L. Preliminary report on the relationship between occurrence of white ear symptom in winter wheat and the prominent agricultural management practices. Acta Agric Boreali-Sin, 2012, 27(S1): 368-373 (in Chinese with English abstract).
[8] 何贤芳, 赵莉, 刘泽, 汪建来. 安徽稻茬小麦产量差异性与生产限制因子构成解析. 北方农业学报, 2020, 48(1): 123-128.
doi: 10.12190/j.issn.2096-1197.2020.01.24
He X F, Zhao L, Liu Z, Wang J L. Analysis of yield difference and production restriction factors of rice stubble wheat in Anhui province. J North Agric, 2020, 48(1): 123-128 (in Chinese with English abstract).
[9] Shao J J, Zhao W Q, Zhou Z G, Du K, Kong L J, Wang Y H. A new feasible method for yield gap analysis in regions dominated by smallholder farmers, with a case study of Jiangsu province, China. J Integr Agric, 2021, 20: 460-469.
doi: 10.1016/S2095-3119(20)63384-6
[10] Agus F, Andrade J F, Edreira J I R, Deng N Y, Purwantomo D K G, Agustiani N, Aristya V E, Batubara S F, Herniwati, Hosang E Y, Krisnadi L Y, Makka A, Samijan, Cenacchi N, Wiebe K, Grassini P. Yield gaps in intensive rice-maize cropping sequences in the humid tropics of Indonesia. Field Crops Res, 2019, 237: 12-22.
doi: 10.1016/j.fcr.2019.04.006
[11] Rizzo G, Agus F, Batubara S F, Andrade J F, Edreira J I R, Purwantomo D K G, Anasiru R H, Maintang, Marbun O, Ningsih R D, Syahri, Ratna B S, Yulianti V, Istiqomah N, Aristya V E, Howard R, Cassman K G, Grassini P. A farmer data-driven approach for prioritization of agricultural research and development: A case study for intensive crop systems in the humid tropics. Field Crops Res, 2023, 297: 108942.
doi: 10.1016/j.fcr.2023.108942
[12] 杨娅, 田贵生, 吴海亚, 周雨亭, 周志华, 丛日环. 武穴市油菜种植现状调研与分析. 中国农技推广, 2019, 35(增刊1): 17-18.
Yang Y, Tian G S, Wu H Y, Zhou Y T, Zhou Z H, Cong R H. Rapeseed production status investigation and analysis in Wuhan. China Agric Technol Ext, 2019, 35(S1): 17-18 (in Chinese).
[13] 秦鹏程, 万素琴, 邓环, 刘敏. 湖北省水稻种植布局精细化气候区划. 湖北农业科学, 2016, 55: 4150-4153.
Qin P C, Wan S Q, Deng H, Liu M. Fine climatic regionalization of rice cultivated patterns in Hubei province. Hubei Agric Sci, 2016, 55: 4150-4153 (in Chinese with English abstract).
[14] Li T, Angeles O, Marcaida III M, Manalo E, Manalili M P, Radanielson A, Mohanty Sl. From ORYZA 2000 to ORYZA (v3): an improved simulation model for rice in drought and nitrogen-deficient environments. Agric Meteorol, 2017, 237: 246-256.
[15] Sayin C, Mencet M N, Ozkan B. Assessing of energy policies based on Turkish agriculture: current status and some implications. Energy Policy, 2005, 33: 2361-2373.
doi: 10.1016/j.enpol.2004.05.005
[16] Tabar I B, Keyhani A, Rafiee S. Energy balance in Iran’s agronomy (19902006). Renew Sust Energ Rev, 2010, 14: 849-855.
doi: 10.1016/j.rser.2009.10.024
[17] Setiyono T D, Quicho E D, Gatti L, Campos-Taberner M, Busetto L, Collivignarelli F, García-Haro F J. Boschetti M, Khan N I, Holecz F. Spatial rice yield estimation based on MODIS and Sentinel-1 SAR data and ORYZA crop growth model. Remote Sens, 2018, 10: 293.
doi: 10.3390/rs10020293
[18] Deng N Y, Grassini P, Yang H S, Huang J L, Cassman K G, Peng S B. Closing yield gaps for rice self-sufficiency in China. Nat Commun, 2019, 10: 1725.
doi: 10.1038/s41467-019-09447-9 pmid: 30979872
[19] Boote K J, Jones J W, Hoogenboom G, Pickering N. The CROPGRO Model for Grain Legumes: Understanding Options for Agricultural Production. Dordrecht: Kluwer Academic Publishers, 1998. pp 99-128.
[20] Deligios P A, Farci R, Sulas L, Hoogenboom G, Ledda L. Predicting growth and yield of winter rapeseed in a Mediterranean environment: Model adaptation at a field scale. Field Crops Res, 2013, 144: 100-112.
doi: 10.1016/j.fcr.2013.01.017
[21] Xu M C, Wang C M, Ling L, Batchelor W D, Zhang J, Jie K. Sensitivity analysis of the CROPGRO-Canola model in China: a case study for rapeseed. PLoS One, 2021, 16: e0259929.
doi: 10.1371/journal.pone.0259929
[22] 李万君, 李艳军. 基于企业视角的湖北省油菜良种补贴效果评析: 以统一供种为例. 华中农业大学学报(社会科学版), 2016, 2: 47-52.
Li W J, Li Y J. Effect analysis on improved canola seed subsidy in Hubei province from perspective of enterprises-taking unified seed supply program for example. J Huazhong Agric Univ (Soc Sci Edn), 2016, 2: 47-52 (in Chinese with English abstract).
[23] 熊伟, 林而达, 杨婕, 李迎春. 作物模型区域应用两种参数校准方法的比较. 生态学报, 2008, 28: 2140-2147.
Xiong W, Lin E D, Yang J, Li Y C. Comparison of two calibration approaches for regional simulation of crop model. Acta Ecol Sin, 2008, 28: 2140-2147 (in Chinese with English abstract).
[24] Yang H S, Dobermann A, Lindquist J L, Walters D T, Cassman K G. Hybrid maize: a maize simulation model that combines two crop modeling approaches. Field Crops Res, 2004, 87: 131-154.
doi: 10.1016/j.fcr.2003.10.003
[25] Grassini P, van Bussel L G J, Van Wart J, Wolf J, Claessens L, Yang H S, Boogaard H, de Groot H, van Ittersum M K, Cassman K G. How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Res, 2015, 177: 49-63.
doi: 10.1016/j.fcr.2015.03.004
[26] Schils R, Olesen J E, Kersebaum K C, Rijk B, Oberforster M, Kalyada V, Khitrykau M, Gobin A, Kirchev H, Manolova V, Manolov I, Trnka M, Hlavinka P, Palosuo T, Peltonen-Sainio P, Lorgeou J, Marrou H, Danalatos N, Archontoulis S, van Ittersum M K. Cereal yield gaps across Europe. Eur J Agron, 2018, 101: 109-120.
doi: 10.1016/j.eja.2018.09.003
[27] Yuan S, Stuart A M, Laborte A G, Edreira J I R, Dobermann A, Kien L V N, Thúy L T, Paothong K, Traesang P, Tint K M, San S S, Villafuerte II M Q, Quicho E D, Pame A R P, Then R, Flor R J, Thon N, Agus F, Agustiani N, Deng N, Li T, Grassini P. Southeast Asia must narrow down the yield gap to continue to be a major rice bowl. Nat Food, 2022, 3: 217-226.
doi: 10.1038/s43016-022-00477-z pmid: 37117641
[28] Grassini P, Eskridge K M, Cassman K G. Distinguishing between yield advances and yield plateaus in historical crop production trends. Nat Commun, 2013, 4: 2918.
doi: 10.1038/ncomms3918 pmid: 24346131
[29] van Wart J, Grassini P, Cassman K G. Impact of derived global weather data on simulated crop yields. Glob Change Biol, 2013, 19: 3822-3834.
doi: 10.1111/gcb.2013.19.issue-12
[30] Han E, Ines A, Koo J. Global high-resolution soil profile database for crop modeling applications. Harv Data, 2015, 1: 1-37.
[31] Hothorn T, Hornik K, Zeileis A. Unbiased recursive partitioning: a conditional inference framework. J Comput Graph Statist, 2006, 15: 651-674.
doi: 10.1198/106186006X133933
[32] Guelman L, Guillén M, Pérez-Marín A M. A decision support framework to implement optimal personalized marketing interventions. Decis Support Syst, 2015, 72: 24-32.
doi: 10.1016/j.dss.2015.01.010
[33] Mourtzinis S, Kaur G, Orlowski J M, Shapiro C A, Lee C D, Wortmann C, Holshouser D, Nafziger E D, Kandel H, Niekamp J, Ross W J, Lofton J, Vonk J, Roozeboom K L, Thelen K D, Lindsey L E, Staton M, Naeve S L, Casteel S N, Wiebold W J, Conley S P. Soybean response to nitrogen application across the United States: a synthesis-analysis. Field Crops Res, 2018, 215: 74-82.
doi: 10.1016/j.fcr.2017.09.035
[34] Corassa G M, Amado T J C, Strieder M L, Strieder M L, Schwalbert R, Pires J L F, Carter P R, Ciampitti I A. Optimum soybean seeding rates by yield environment in southern Brazil. Agron J, 2018, 110: 2430-2438.
doi: 10.2134/agronj2018.04.0239
[35] Hothorn T, Hornik K, Zeileis A. ctree: conditional inference trees. Compr R Archiv Netw, 2015, 8: 1-32.
[36] 陆佳岚, 王净, 马成, 陶明煊, 赵春芳, 张亚东, 李霞, 方先文, 张俊, 陈长青, 张巫军, 夏加发, 江学海, 柳开楼, 乔中英, 张彬. 长江流域中稻产量和品质性状差异与其生育期气象因子的相关性. 江苏农业学报, 2020, 36: 1361-1372.
Lu J L, Wang J, Ma C, Tao M X, Zhao C F, Zhang Y D, Li X, Fang X W, Zhang J, Chen C Q, Zhang W J, Xia J F, Jiang X H, Liu K L, Qiao Z Y, Zhang L. Correlation between the differences in yield and quality traits among various types of middle rice and meteorological factors during growth period in the Yangtze River basin. Jiangsu J Agric Sci, 2020, 36: 1361-1372 (in Chinese with English abstract).
[37] Linh T B, Sleutel S, Thi G V, Khoa L V, Cornelis W M. Deeper tillage and root growth in annual rice-upland cropping systems result in improved rice yield and economic profit relative to rice monoculture. Soil Tillage Res, 2015, 154: 44-52.
doi: 10.1016/j.still.2015.06.011
[38] 姜宝龙, 代贵金, 宫殿凯, 赵福财, 于广星, 徐博, 刘宪平, 陈盈. 稻田旋耕深度对盐丰47的生长发育及产量性状的影响. 粮食科技与经济, 2020, 45(6): 107-109.
Jiang B L, Dai G J, Gong D K, Zhao F C, Yu G X, Xu B, Liu X P, Chen Y. Effect of rotary tillage depth on the growth and yield characters of Yanfeng 47. Food Sci Technol Econ, 2020, 45(6): 107-109 (in Chinese with English abstract).
[39] 刘智炫, 刘勇军, 彭曙光, 单雪华, 谢鹏飞, 李宏光, 李强, 穰中文, 周清明, 黎娟. 基于长期浅耕模式的烟稻轮作区土壤速效养分垂直分布特征. 中国烟草科学, 2020, 41(3): 28-35.
Liu Z X, Liu Y J, Peng S G, Shan X H, Xie P F, Li H G, Li Q, Rang Z W, Zhou Q M, Li J. Vertical distribution characteristics of soil available nutrients in tobacco rice rotation area based on long-term shallow tillage. Chin Tob Sci, 2020, 41(3): 28-35 (in Chinese with English abstract).
[40] Xing X, Zhang P, Ma X. Rapeseed dreg additive reducing soil infiltration and improving water retention. Trans CSAE, 2017, 33(2): 102-108.
[41] 袁金展, 马霓, 张春雷, 李俊. 移栽与直播对油菜根系建成及籽粒产量的影响. 中国油料作物学报, 2014, 36: 189-197.
doi: 10.7505/j.issn.1007-9084.2014.02.008
Yuan J Z, Ma N, Zhang C L, Li J. Effects of direct drilling and transplanting on root system and rapeseed yield. Chin J Oil Crop Sci, 2014, 36: 189-197 (in Chinese with English abstract).
[42] 王秋菊, 高中超, 张劲松, 常本超, 姜辉, 孙兵, 郭中原, 贾会彬, 焦峰, 刘峰. 黑土稻田连续深耕改善土壤理化性质提高水稻产量大田试验. 农业工程学报, 2017, 33(9): 126-132.
Wang Q J, Gao Z C, Zhang J S, Chang B C, Jiang H, Sun B, Guo Z Y, Jia H L, Jiao F, Liu F. Black-soil paddy field experiment on improving soil physical and chemical properties and increasing rice yield by continuous deep ploughing. Trans CSAE, 2017, 33(9): 126-132 (in Chinese with English abstract).
[43] Arora V K, Joshi R, Singh C B. Irrigation and deep tillage effects on productivity of dry-seeded rice in a subtropical environment. Agric Res, 2018, 7: 416-423.
doi: 10.1007/s40003-018-0323-9
[44] Shen X L, Wang L L, Yang Q C, Xiu W M, Li G, Zhao H N, Zhang G L. Dynamics of soil organic carbon and labile carbon fractions in soil aggregates affected by different tillage managements. Sustain, 2021, 13: 1541.
[45] 梁玉刚, 李静怡, 周晶, 吴涛, 方宝华, 余政军. 中国水稻栽培技术的演变与展望. 作物研究, 2022, 36: 180-188.
Liang Y G, Li J L, Zhou J, Wu T, Fang B H, Yu Z J. Evolution and prospect of rice cultivation technology in China. Crop Res, 2022, 36: 180-188 (in Chinese with English abstract).
[46] 杨永杰, 张慧泉, 金文涌, 糜学江, 张建萍, 于晓玥, 唐伟, 陆永良. 几种封闭除草剂两个时期用药效果对比及其交互作用分析. 植物保护, 2022, 48(5): 341-347.
Yang Y J, Zhang H Q, Jin W Y, Mi X J, Zhang J P, Yu X Y, Tang W, Lu Y L. Comparison of weed management with several pre-emergence herbicides under two application periods and analysis their interactions in weed control. Plant Prot, 2022, 48(5): 341-347 (in Chinese with English abstract).
[47] 金红梅. 长江中下游籼型常规稻与杂交稻主要性状的比较分析. 中国稻米, 2011, 17(3): 14-16.
doi: 10.3969/j.issn.1006-8082.2011.03.005
Jin H M. Comparison of major traits between Indica conventional rice and hybrid rice in the middle and lower reaches of Yangtze River Valley. China Rice, 2011, 17(3): 14-16 (in Chinese).
[48] 郑华斌, 唐启源, 陈风波. 绿色超级稻品种黄华占在湖南推广的启示. 作物研究, 2019, 33: 44-46.
Zheng H B, Tang Q Y, Chen F B. Enlightenment for promotion of Green Super Rice variety Huanghuazhan in Hunan. Crop Res, 2019, 33: 44-46 (in Chinese).
[49] 王亚梁, 朱德峰, 向镜, 陈惠哲, 张玉屏, 徐一成, 张义凯. 杂交水稻机插定位定量播种技术. 杂交水稻, 2020, 35(3): 42-45.
Wang Y L, Zhu D F, Xiang J, Chen H Z, Zhang Y P, Xu Y C, Zhang Y K. Sowing techniques of seed location and quantitation for machine transplanting of hybrid rice. Hybrid Rice, 2020, 35(3): 42-45 (in Chinese with English abstract).
[50] 季红娟, 张小祥, 赵步洪, 郑青松, 陈刚, 李育红, 肖宁, 潘存红, 吴云雨, 蔡跃, 李爱宏. 不同播期和密度对直播粳稻扬粳3012产量及品质的影响. 扬州大学学报(农业与生命科学版), 2020, 41(1): 85-90.
Ji H J, Zhang X X, Zhao B H, Zheng Q S, Chen G, Li Y H, Xiao N, Pan C H, Wu Y Y, Cai Y, Li A H. Effects of different sowing date and density on yield and quality of Yangjing 3012 indirect-seeding rice. J Yangzhou University (Agric Life Sci Edn), 2020, 41(1): 85-90 (in Chinese with English abstract).
[51] 吴培, 陈天晔, 袁嘉琦, 黄恒, 邢志鹏. 施氮量和直播密度互作对水稻产量形成特征的影响. 中国水稻科学, 2019, 33: 269-281.
doi: 10.16819/j.1001-7216.2019.8112
Wu P, Chen T H, Yuan J Q, Huang H, Xing Z P. Effects of interaction between nitrogen application rate and direct-sowing density on yield formation characteristics of rice. Chin J Rice Sci, 2019, 33: 269-281 (in Chinese with English abstract).
doi: 10.16819/j.1001-7216.2019.8112
[52] 安宁, 范明生, 张福锁. 水稻最佳作物管理技术的增产增效作用. 植物营养与肥料学报, 2015, 21: 846-852.
An N, Fan M S, Zhang F S. Best crop management practices increase rice yield and nitrogen use efficiency. J Plant Nutr Fert, 2015, 21: 846-852 (in Chinese with English abstract).
[53] 刘助生, 钟丽, 廖云云, 张宗急, 明日, 李云娟, 方鹏, 韦永忠. 桂北地区不同油菜品种对氮磷钾肥的响应研究. 作物研究, 2022, 36: 320-326.
Liu Z S, Zhong L, Liao Y Y, Zhang Z J, Ming R, Li Y J, Wan P, Wei Y Z. Responses of the different rapeseed cultivars to nitrogen, phosphorus and potassium fertilizers in northern Guangxi. Crop Res, 2022, 36: 320-326 (in Chinese with English abstract).
[54] Kuai J, Sun Y Y, Zuo Q S, Huang H D, Liao Q X, Wu C Y, Lu J W, Wu J S, Zhou G S. The yield of mechanically harvested rapeseed (Brassica napus L.) can be increased by optimum plant density and row spacing. Sci Rep, 2015, 5: 18835.
doi: 10.1038/srep18835 pmid: 26686007
[55] Kuai J, Sun Y Y, Zuo Q S, Liao Q X, Leng S H, Cheng Y G, Cao S, Wu J S, Zhou G S. Optimization of plant density and row spacing for mechanical harvest in winter rapeseed (Brassica napus L.). Acta Agron Sin, 2016, 42: 898-908.
doi: 10.3724/SP.J.1006.2016.00898
[56] 梁苏宁, 沐森林, 汤庆, 张敏, 吴崇友. 收获方式对油菜收获损失构成特征的影响. 农机化研究, 2018, 40(3): 134-140.
Liang S N, Ru S L, Tang Q, Zhang M, Wu C Y. The Effect of different harvest methods on formation of rape harvest loss. J Agric Mech Res, 2018, 40(3): 134-140 (in Chinese with English abstract).
[57] 王竹云, 张耀文, 赵小光, 侯君利, 关周博, 李殿荣, 史文青. 限制油菜高产水平提高的因素解析及解决途径. 江西农业学报, 2019, 31(6): 45-51.
Wang Z Y, Zhang Y W, Zhao X G, Hou L J, Guan Z B, Li D R, Shi W Q. Analysis and solution of factors restricting high yield of rapeseed. Acta Agric Jiangxi, 2019, 31(6): 45-51 (in Chinese with English abstract).
[58] 张立伟. 2021年菜籽菜油菜粕市场分析与2022年展望. 粮油与饲料科技, 2022, (3): 43-48.
Zhang L W. The market analysis of rapeseed seeds, oil, and meal of 2021 and the outlook of 2022. Grain Oil Feed Technol, 2022, (3): 43-48 (in Chinese).
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