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作物学报 ›› 2023, Vol. 49 ›› Issue (1): 177-187.doi: 10.3724/SP.J.1006.2023.24026

• 耕作栽培·生理生化 • 上一篇    下一篇

1991—2019年美国大豆区试品种(系)农艺和品质性状时空变化特征

白智媛, 陈向阳, 郑阿香, 张力, 邹军, 张大同, 陈阜, 尹小刚()   

  1. 中国农业大学农学院 / 农业农村部农作制度重点实验室, 北京 100193
  • 收稿日期:2022-01-21 接受日期:2022-05-05 出版日期:2023-01-12 网络出版日期:2022-05-19
  • 通讯作者: 尹小刚
  • 基金资助:
    中国科协青年人才托举工程项目(2019QNRC001);国家自然科学基金项目(32071979)

Spatial-temporal variations for agronomic and quality characters of soybeans varieties (strains) tested in America from 1991 to 2019

BAI Zhi-Yuan, CHEN Xiang-Yang, ZHENG A-Xiang, ZHANG Li, ZOU Jun, ZHANG Da-Tong, CHEN Fu, YIN Xiao-Gang()   

  1. College of Agronomy and Biotechnology, China Agricultural University / Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
  • Received:2022-01-21 Accepted:2022-05-05 Published:2023-01-12 Published online:2022-05-19
  • Contact: YIN Xiao-Gang
  • Supported by:
    Young Talent Promotion Project of China Association for Science and Technology(2019QNRC001);National Natural Science Foundation of China(32071979)

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摘要：

美国是全球重要的大豆生产国, 中美大豆生产水平差距大, 探讨美国大豆品种主要性状的时空演变规律对中国大豆生产具有重要借鉴意义。本研究基于1991—2019年美国213个大豆品种区试站点共计102,244个年点观测数据, 综合运用线性回归模型、空间分析和结构方程模型等方法, 研究了近30年来美国大豆区试品种(系)农艺和品质性状的时空变化特征。结果表明: (1) 1991—2019年美国大豆区试品种(系)数量和大豆单产均呈上升趋势, 1991—2003年大豆单产稳定在3000 kg hm-2左右, 2004年以来大豆单产以年均46.4 kg hm-2的速度显著增加, 近15年大豆平均单产为3525 kg hm-2; 西部和东部玉米带是美国大豆高产区, 2004—2019年美国有22.6%的区试站点大豆单产超过4000 kg hm-2, 且主要分布于西部玉米带和东部玉米带。(2) 近30年美国大豆区试品种(系)的百粒重呈下降趋势, 而株高和生育期无显著变化; 1991—2003年间百粒重年均下降0.12 g, 2004年以来百粒重无明显变化。(3) 近30年美国大豆区试品种(系)的蛋白质含量呈下降趋势, 平均蛋白质含量从1991—2003年间的41.3%下降到2004—2019年间的40.0%, 美国南部地区的蛋白质含量比北部地区高1.4%; 油脂呈先下降后增加趋势, 平均油脂含量从1991—2003年间的20.3%上升到2004—2019年间的21.3%; 2004—2019年美国有59.2%的区试站点大豆油脂含量超过21%。(4) 2004—2019年美国大豆区试品种(系)单产水平和油脂含量协同提高, 大豆自身农艺性状对单产的制约作用降低。本研究揭示了美国近30年来大豆品种(系)农艺和品质性状的时空变化特征, 阐明了不同时期大豆区试品种(系)单产与主要性状之间的关系, 可为中国大豆品种高产优质协同发展提供参考。

关键词: 大豆, 单产, 蛋白质, 油脂, 时空变化

Abstract:

America is an important soybean producer in the world, and there is a large gap in terms of soybean production level between China and America. It is of great significance to explore the spatial-temporal evolution patterns of the main characters of American soybean varieties in China’s soybean production. This study was based on the observation data of 102,244 variety-site-year observations from 213 soybean regional test sites in America from 1991 to 2019, which explored the spatial-temporal variations of agronomic and quality traits of American soybean regional trial varieties (strains) during the recent 30 years by using linear regression model, spatial analysis and structural equation model. The results showed that: (1) The number of soybean regional test varieties (strains) and soybean yield in America had an upward trend from 1991 to 2019, soybean yield was stable with the mean value of 3000 kg hm-2 from 1991 to 2003, which increased significantly with an average annual rate of 46.4 kg hm-2 since 2004, and the average soybean yield was 3525 kg hm-2 during the recent 15 years; the western-corn belt and eastern-corn belt were the high soybean yield regions in America, the yield level higher than 4000 kg hm-2 accounting for 22.6% of the regional test sites from 2004 to 2019, which was mainly distributed in the western-corn belt and eastern-corn belt. (2) The 100-grain weight of American soybean varieties (strains) had a downward trend during the recent 30 years, but there were no significant changes in plant height and growth period; specifically, the 100-grain weight decreased by 0.12 g per year from 1991 to 2003, while it kept stable since 2004. (3) In the recent 30 years, the protein content of American soybean regional test varieties (strains) experienced decreasing trend, and the average protein content decreased from 41.3% in 1991-2003 to 40.0% in 2004-2019, the protein content in the southern America was 1.4% higher than the northern parts; the oil content indicated decreasing trend while showed increasing trend afterwards, the average oil content increased from 20.3% in the 1991-2003 period to 21.3% in the 2004-2019 period; 59.2% of the regional test sites in America had soybean oil content higher than 21% from 2004 to 2019. (4) The yield level and oil content of American soybean regional test varieties (strains) increased synergistically from 2004 to 2019, while the restrictive effects of soybean agronomic traits on yield decreased. This study revealed the spatial-temporal variations of agronomic and quality traits of soybean varieties (strains) during the recent 30 years, and determined the constraint relationship between yield and various traits of regional trial varieties (strains) of American soybean in different periods, which could provide references for the coordinated development of high-yield and high-quality of soybean in China.

Key words: soybean, yield, protein, oil, spatial-temporal variations

图1

近30年美国大豆主产区和大豆品种区域试验点的空间分布 WCB: 西部玉米带; ECB: 东部玉米带; EC: 东海岸地区; MDS: 中南部地区; SE: 东南部地区。"

图2

1991-2019年美国大豆区试品种(系)数量及其在各地区的百分比 缩写同图1。"

图3

1991-2019年美国大豆区试品种(系)单产、百粒重、株高和生育期的时间演变"

表1

1991-2003和2004-2019年美国各主产区大豆区试相关指标的变化"

指标
Item		 1991-2003 2004-2019
WCB ECB EC MDS SE WCB ECB EC MDS SE
单产
Yield (kg hm-2)		 斜率 Slope -25.4 11 22.6 25.1 -4.59 54.5*** 29.7* 57.6* 72** 20.4***
均值 Mean 3119 3376 3041 3012 2794 3650 3809 3185 3470 3134
百粒重
100-grain weight (g)		 斜率 Slope -0.14* -0.16* -0.15 -0.05 -0.01 0.01 0.1* -0.06 -0.01 -0.00
均值 Mean 15.6 15.2 15.1 14 14.7 15.2 15.1 14.2 14.2 15
株高
Plant height (cm)		 斜率 Slope -0.68 -0.34 0.05 -0.37 -0.38 0.32 -0.15 0.63 0.3 -0.04
均值 Mean 83 81 76 78 83 83 84 78 75 86
生育期
Growth period (d)		 斜率 Slope -0.27 0.36 -0.26 — — 0.11 -0.32 0.48 0.82* -0.46
均值 Mean 126 127 119 — — 127 125 134 138 139
蛋白质含量
Protein content (%)		 斜率 Slope -0.01 0.02 0.13 -0.04 -0.08 0.03 -0.08 -0.05 0.02 0.02
均值 Mean 40.8 41.1 40.8 41.9 41.7 39.5 39.4 40.1 40.8 40.8
油脂含量
Oil content (%)		 斜率 Slope -0.01 -0.05 -0.17** -0.04 -0.08** 0.15*** 0.23*** 0.22*** 0.21*** 0.2***
均值 Mean 20.1 20.4 19.9 20.4 20.3 21.1 21.5 20.7 21.5 21.3
蛋白质+油脂含量
P+O content (%)		 斜率 Slope -0.03 -0.03 -0.04 -0.09 -0.16 0.19*** 0.15** 0.17** 0.23** 0.22***
均值 Mean 60.8 61.6 60.7 62.4 62 60.7 60.9 60.7 62.3 62.1

图4

1991-2003和2004-2019年美国大豆区试品种(系)单产、百粒重、株高和生育期的空间分布"

图5

1991-2019年美国大豆区试品种(系)蛋白质、油脂和蛋脂含量的时间演变"

图6

1991-2003和2004-2019年美国大豆区试品种(系)蛋白质、油脂和蛋脂含量的空间分布"

图7

1991-2003和2004-2019年单产的结构方程模型 实线: 变量之间存在显著相关性; 虚线: 变量之间无显著相关性; 红线: 负相关; 黑线: 正相关。Y: 单产; P: 蛋白质含量; O: 油脂含量; G: 生育期; H: 株高; W: 百粒重。"

[1] 盖钧镒. 中国大豆产业、科技、种业和转基因育种的思考(I). 大豆科技, 2011, (3): 1-2.
Gai J Y. Thoughts on soybean industry, science and technology, seed industry and transgenic breeding in China (I). Soybean Sci Technol, 2011, (3): 1-2. (in Chinese)
[2] 杨皓森, 王禹. 中国大豆供需形势中长期展望研究. 农业经济, 2020, (12): 114-117.
Yang H S, Wang Y. Study on medium- and long-term prospect of soybean supply and demand in China. Agric Econ, 2020, (12): 114-117. (in Chinese)
[3] 胡忆雨, 邹军, 吴尧, 王小慧, 杨雨豪, 陈阜, 尹小刚. 全球禾-豆生产系统作物多样性变化特征及其影响. 中国农业大学学报, 2021, 26(8): 9-22.
Hu Y Y, Zou J, Wu Y, Wang X H, Yang Y H, Chen F, Yin X G. Changes and impacts of crop diversity in global cereal-legume production systems. J China Agric Univ, 2021, 26(8): 9-22. (in Chinese with English abstract)
[4] 曹宝明, 赵霞. 基于局部均衡理论的中国大豆及其制品供需变化预测. 中国农村经济, 2011, (9): 23-36.
Cao B M, Zhao X. Prediction of supply and demand changes of soybean and its products in China based on local equilibrium theory. Chin Rural Econ, 2011, (9): 23-36. (in Chinese)
[5] 陈伟, 朱俊峰, 田国强. 中美贸易摩擦对中国大豆的影响及对策分析. 大豆科学, 2019, 38: 118-123.
Chen W, Zhu J F, Tian G Q. The impact and countermeasures analysis of Sino-US trade friction on China’s soybean. Soybean Sci, 2019, 38: 118-123. (in Chinese with English abstract)
[6] USDA. Uniform Soybean Test Sites. https://www.nass.usda.gov/.
[7] 尹小刚, 陈阜. 1961-2017年全球大豆生产时空变化. 世界农业, 2019, 487(11): 65-71.
Yin X G, Chen F. Spatial-temporal changes of global soybean production during 1961 and 2017. World Agric, 2019, 487(11): 65-71. (in Chinese with English abstract)
[8] Hurburgh C R, Brumm T J, Guinn J M, Hartwig R A. Protein and oil patterns in U.S. and world soybean markets. J Am Oil Chem Soc, 1990, 67: 966-973.
doi: 10.1007/BF02541859
[9] 胡忆雨, 朱颖璇, 杨雨豪, 邹军, 陈阜, 尹小刚. 1951-2015年中国主要粮食与油料作物种植结构变化分析. 中国农业大学学报, 2019, 24(11): 183-196.
Hu Y Y, Zhu Y X, Yang Y H, Zou J, Chen F, Yin X G. Changes of planting structure of major food and oil crops in China from 1951 to 2015. J China Agric Univ, 2019, 24(11): 183-196. (in Chinese with English abstract)
[10] Li C, Wang X S, Guo Z K, Huang N, Hou S B, He G, Batchelor W D, Siddique K H M, Wang Z H, Zhang D. Optimizing nitrogen fertilizer inputs and plant populations for greener wheat production with high yields and high efficiency in dryland areas. Field Crops Res, 2022, 276: 108374.
doi: 10.1016/j.fcr.2021.108374
[11] 敖荣军, 常亮. 基于结构方程模型的中国县域人口老龄化影响机制. 地理学报, 2020, 75: 1572-1584.
doi: 10.11821/dlxb202008002
Ao R J, Chang L. Influencing mechanism of regional ageing in China based on the structural equation model. Acta Geograph Sin, 2020, 75: 1572-1584. (in Chinese with English abstract)
[12] Board J E. Yield components related to seed yield in determinate soybean. Crop Sci, 1987, 27: 1296-1297.
doi: 10.2135/cropsci1987.0011183X002700060041x
[13] Wei M C F, Molin J P. Soybean yield estimation and its components: a linear regression approach. Agriculture, 2020, 10: 348.
doi: 10.3390/agriculture10080348
[14] Suhre J J, Weidenbenner N H, Rowntree S C, Wilson E W, Naeve S L, Conley S P, Casteel S N, Diers B W, Esker P D, Specht J E, Davis V M. Soybean yield partitioning changes revealed by genetic gain and seeding rate interactions. Agron J, 2014, 106: 1631-1642.
doi: 10.2134/agronj14.0003
[15] 尹阳阳, 徐彩龙, 宋雯雯, 胡水秀, 吴存祥. 密植是挖掘大豆产量潜力的重要栽培途径. 土壤与作物, 2019, 8: 361-367.
Yin Y Y, Xu C L, Song W W, Hu S X, Wu C X. Increasing planting density is an important approach to achieve the potential of soybean yield. Soils Crops, 2019, 8: 361-367. (in Chinese with English abstract)
[16] 赵团结, 盖钧镒, 李海旺, 邢邯, 邱家驯. 超高产大豆育种研究的进展与讨论. 中国农业科学, 2006, 39: 29-37.
Zhao T J, Gai J Y, Li H W, Xing H, Qiu J X. Advances in breeding for super high-yielding soybean cultivars. Sci Agric Sin, 2006, 39: 29-37. (in Chinese with English abstract)
[17] 杜维广, 张桂茹, 满为群, 陈怡, 栾晓燕, 郝乃斌, 戈巧英, 谷秀芝. 大豆高光效品种(种质)选育及高光效育种再探讨. 大豆科学, 2001, 20: 110-115.
Du W G, Zhang G R, Man W Q, Chen Y, Luan X Y, Hao N B, Ge Q Y, Gu X Z. Development of soybean cultivars (germplasm) with high photosynthetic efficiency (HPE) and rediscussion of breeding for HPE. Soybean Sci, 2001, 20: 110-115. (in Chinese with English abstract)
[18] 刘章雄, 邱丽娟, 关荣霞, 常汝镇. 美国大豆育种研究进展. 大豆科学, 2004, 23: 123-129.
Liu Z X, Qiu L J, Guan R X, Chang R Z. New advances in the study soybean breeding of U.S.A. Soybean Sci, 2004, 23: 123-129. (in Chinese with English abstract)
[19] Cooper R L. A delayed flowering barrier to higher soybean yields. Field Crops Res, 2003, 82: 27-35.
doi: 10.1016/S0378-4290(03)00003-0
[20] Carciochi W D, Schwalbert R, Andrade F H, Corassa G M, Carter P, Gaspar A P, Schmidt J, Ciampitti I A. Soybean seed yield response to plant density by yield environment in north America. Agron J, 2019, 111: 1923-1932.
doi: 10.2134/agronj2018.10.0635
[21] Pedersen P, Lauer J G. Corn and soybean response to rotation sequence, row spacing, and tillage system. Agron J, 2003, 95: 965-971.
doi: 10.2134/agronj2003.9650
[22] 张伟, 张惠君, 王海英, 谢甫绨, 陈振武. 株行距和种植密度对高油大豆农艺性状及产量的影响. 大豆科学, 2006, 25: 283-287.
Zhang W, Zhang H J, Wang H Y, Xie F T, Chen Z W. Effects of spacings and planting densities on agronomic traits and yield in high-oil soybean. Soybean Sci, 2006, 25: 283-287. (in Chinese with English abstract)
[23] USDA. https://www.usda.gov/topics/trade, 2021.
[24] Rotundo J L, Westgate M E. Meta-analysis of environmental effects on soybean seed composition. Field Crops Res, 2009, 110: 147-156.
doi: 10.1016/j.fcr.2008.07.012
[25] Yaklich R W, Vinyard B, Camp M, Douglass S. Analysis of seed protein and oil from soybean Northern and Southern Region uniform tests. Crop Sci, 2002, 42: 1504-1515.
doi: 10.2135/cropsci2002.1504
[26] Wu D, Qu J J, Hao X. Agricultural drought monitoring using MODIS-based drought indices over the America Corn Belt. Int J Remote Sens, 2015, 36: 5403-5425.
doi: 10.1080/01431161.2015.1093190
[27] Ren C, Bilyeu K D, Beuselinck P R. Composition, vigor, and proteome of mature soybean seeds developed under high temperature. Crop Sci, 2009, 49: 1010-1022.
doi: 10.2135/cropsci2008.05.0247
[28] Liu Y, Dai L. Modelling the impacts of climate change and crop management measures on soybean phenology in China. J Clean Prod, 2020, 262.
[29] 肖琴, 李建平, 刘冬梅. 转基因大豆冲击下的中国大豆产业发展对策. 中国科技论坛, 2015, (6): 137-141.
Xiao Q, Li J P, Liu D M. Development countermeasures of China’s soybean industry under the impact of genetically modified soybean. Forum Sci Technol China, 2015, (6): 137-141. (in Chinese with English abstract)
[30] 杨树果, 何秀荣. 中国大豆产业状况和观点思考. 中国农村经济, 2014, (4): 32-41.
Yang S G, He X R. Situation and viewpoint of China’s soybean industry. Chin Rural Econ, 2014, (4): 32-41. (in Chinese)
[31] 宋启建, 盖钧镒, 马育华. 长江中游夏大豆地方品种品质及产量等性状的典型相关与通径分析. 大豆科学, 1996, 15: 11-16.
Song Q J, Gai J Y, Ma Y H. Canonical correlation and path analysis of quality and yield of summer soybean landraces in the middle reaches of the Yangtze River. Soybean Sci, 1996, 15: 11-16. (in Chinese with English abstract)
[32] 何鑫, 马文娅, 付汝洪, 张琪, 闫向前. 2006-2017年国家黄淮海夏大豆品种区域试验参试品种(系)分析. 中国油料作物学报, 2019, 41: 537-549.
He X, Ma W Y, Fu R H, Zhang Q, Yan X Q. Analysis of national summer soybean regional trials in Huang-Huai-Hai region during 2006-2017. Chin Oil Crop Sci, 2019, 41: 537-549. (in Chinese with English abstract)
[33] 刘军, 徐瑞新, 石垒, 王孟, 徐印印, 姜汉峰, 姜硕琛, 邢丹英. 中国国审大豆品种(2003-2016年)主要性状变化趋势分析. 安徽农学通报, 2017, 23(11): 60-66.
Liu J, Xu R X, Shi L, Wang M, Xu Y Y, Jiang H F, Jiang S C, Xing D Y. Variation trend of major traits of national authorized soybean cultivars from 2003 to 2016. Anhui Agric Sci Bull, 2017, 23(11): 60-66. (in Chinese with English abstract)
[34] 刘绪贻. 罗斯福“新政”的农业政策. 史学月刊, 2001, (3): 103-109.
Liu X Y. Roosevelt’s agricultural policy in his “New Deal”. J Historic Sci, 2001, (3): 103-109. (in Chinese with English abstract)
[35] 王玉飞. 美国大豆补贴政策对我国的借鉴和启示. 农业经济问题, 2011, 32(1): 100-105.
Wang Y F. Reference and enlightenment of American soybean subsidy policy to China. Issues Agric Econ, 2011, 32(1): 100-105. (in Chinese)
[36] 苗水清, 程国强. 美国大豆补贴政策及其影响. 中国农村经济, 2006, (5): 72-80.
Miao S Q, Cheng G Q. American soybean subsidy policy and its impact. Chin Rural Econ, 2006, (5): 72-80. (in Chinese)
[37] Glauber J, Smith V. Trends in US agricultural policy since 2000 and implications for the next twenty years. Euro Choices, 2021, 20: 58-63.
[38] 程敏. 从粮食视角分析中美农产品贸易互利互赢——依据美国农业部数据. 黑龙江粮食, 2021, (6): 33-35.
Cheng M. Analysis on the mutual benefit and win-win of Sino US agricultural trade from the perspective of grain—according to the data of the U.S. Department of Agriculture. Heilongjiang Grain, 2021, (6): 33-35. (in Chinese with English abstract)
[39] 徐雪高, 吴比, 张振. 大豆目标价格补贴的政策演进与效果评价. 经济纵横, 2016, (10): 81-87.
Xu X G, Wu B, Zhang Z. Policy evolution and effect evaluation of soybean target price subsidy. Econ Rev J, 2016, (10): 81-87. (in Chinese)
[40] 王新刚, 司伟. 大豆补贴政策改革实现大豆扩种了吗?——基于大豆主产区124个地级市的实证. 中国农村经济, 2021, (12): 44-65.
Wang X G, Si W. Does the reform of subsidy policy realize the expansion of soybean production? An empirical analysis based on 124 prefecture-level cites in soybean main producing areas. Chin Rural Econ, 2021, (12): 44-65. (in Chinese with English abstract)
[41] 知谷客. 农业农村部、财政部发布2018年财政重点强农惠农政策. 农业机械, 2018, (4): 45-48.
Zhi G K. Ministry of Agriculture and Rural Affairs, Ministry of Finance issued the policy of strengthening agriculture and benefiting agriculture in 2018. Farm Machin, 2018, (4): 45-48. (in Chinese)
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