中国农业科学

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最新录用:山东省强筋小麦品质评价及与气象因子关系分析

余维宝1, 2,李楠3,寇一泓1, 2,曹新有1,司纪升1,韩守威1, 2,李豪圣1,张宾1,王法宏1,张海林2,赵鑫2,李华伟1* #br#   

  1. 1山东省农业科学院作物研究所/小麦玉米国家工程研究中心/农业农村部黄淮北部小麦生物学与遗传育种重点实验室/山东省小麦技术创新中心/济南市小麦遗传改良重点实验室,济南 2501002中国农业大学农学院,北京 100193;3山东省气象局,济南 250031
  • 出版日期:2022-07-27 发布日期:2022-07-27

Study on the Quality Parameters of Strong Gluten Wheat and Analysis of Its Relationship with Meteorological Factors in Shandong Province

YU WeiBao1, 2, LI Nan3, KOU YiHong1, 2, CAO XinYou1, SI JiSheng1, HAN ShouWei1, 2, LI HaoSheng1, ZHANG Bin1, WANG FaHong1, ZHANG HaiLin2, ZHAO Xin2, LI HuaWei1* #br#   

  1. 1 Crop Research Institute, Shandong Academy of Agricultural Sciences/National Engineering Research Center of Wheat and Maize/Key Laboratory of Wheat Biology and Genetics and Breeding in Northern Huang-hHuai River Plain, Ministry of Agriculture and Rural Affairs/Shandong Technology Innovation Center of Wheat/Jinan Key Laboratory of Wheat Genetic Improvement, Jinan 250100; 2College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China3Shandong Meteorological Bureau, Jinan 250031
  • Published:2022-07-27 Online:2022-07-27

摘要: 【目的】明确山东省强筋小麦品质分布特征,分析关键气象因子对小麦品质参数的影响。【方法】以优质强筋小麦济麦44为材料,20182020山东省44个县区获取296组籽粒样品评价了其品质参数在山东省的分布特征,采用逐步回归的方法分析了不同生育期光、温、水等气象因子与小麦品质参数之间的关系,利用地理信息系统(GIS)对品质参数及其影响因子进行了空间可视化分析,并探究了优质强筋小麦在山东省可能性优势分布区域。【结果】不同年份,不同区域间各品质参数存在差异,两年强筋达标率表现为最大拉阻力吸水率容重稳定时间蛋白质含量拉伸面积湿面筋含量,变异系数表现为稳定时间拉伸面积最大拉阻力湿面筋含量蛋白质含量吸水率容重。容重在鲁西和鲁西北地区整体高于其他地区,随经度升高而降低,主要受返青拔节期降雨量的影响;蛋白质含量受开花-乳熟期5℃积温正向影响,20182019年从西南向东北增加,20192020年从西北向东南增加;鲁东地区湿面筋含量较高,这与该地区小麦开花乳熟期降雨量多极显著相关;拔节开花期最高气温的负效应与播种越冬期降雨量的正效应综合影响了稳定时间高值的分布与区域变化;拉伸面积从鲁西向鲁东逐渐降低主要与返青拔节期5℃积温显著相关;最大拉阻力总体表现在东西方向上低而中部高主要与开花乳熟期5℃积温显著负相关。综合分析显示在鲁东和鲁南地区种植强筋小麦的优质可能性强于鲁中和鲁北地区,鲁西地区最低。【结论】鲁东和鲁南地区是山东省强筋小麦优势种植区域,优质可能性最大。返青拔节期、拔节开花期以及灌浆期高温都不利于小麦面团流变 学参数开花乳熟期积温蛋白质含量正相关;播种越冬期降雨有利于面团稳定时间的增加,当开花乳熟期降雨量低于14.5 mm时不利于湿面筋含量达到强筋标准,而返青拔节期降水不利于容重提高。所以在强筋小麦生产中建议视天气状况适当浇灌越冬水和灌浆水,推迟返青拔节期灌水时间。


关键词: 小麦, 品质评价, 气象因子, 空间分布

Abstract:

ObjectiveIn this paper, the dominant distribution areas of strong gluten wheat were clarified in Shandong province, and the influence of key meteorological factors on its quality parameters was analyzed. MethodThe high-quality strong-gluten wheat Jimai 44 was selected as the research material, and 296 samples were collected from 44 counties and districts in Shandong provincein the growing seasons of 2018 to 2020. The relationship of meteorological factors, such as light, temperature and water, in different growth periods with wheat quality parameters was analyzed byusing the method of stepwise regression. The geographic information system (GIS) was used for spatial visualization analysis, and the possible distribution of high-quality strong-gluten wheat advantageous areas was explored in Shandong province. ResultThere were differences in the performance of each quality parameter in the different regions in different years. The proportion of samples reaching the standard of strong gluten wasshown as maximum pull resistance> water absorption rate>bulk density>stabilize time>protein content>tensile area>wet gluten content in two years, and the coefficients of variation of quality parameters from large to small were stabilize time, tensile area, maximum pull resistance, wet gluten content, protein content, water absorption rate, and bulk density. The bulk density in western and northwestern Shandong was generally higher than that in other regions, and decreased with the increase of longitude, which was mainly related to the influence of rainfall during the rejuvenation-jointing period. The protein content was positively affected by the accumulated temperature ≥5℃ during the anthesis-milk maturity period, while increased from southwest to northeast in 2018-2019 and from northwest to southeast in 2019-2020. The wet gluten content was higher in the eastern Shandong region, which was significantly related to the high rainfall during the anthesis-milk maturity period in this region. The stabilize time was significantly negatively correlated with the maximum temperature during the jointing-anthesis period, and positively correlated with the rainfall during the sowing-overwintering period, and this affected its high value distribution and regional variation; the tensile area was significantly negatively correlated with the accumulated temperature ≥5℃ during the rejuvenation-jointing period, and gradually decreased from the west to the east of Shandong province. The maximum pull resistance was significantly negatively correlated with the accumulated temperature ≥5℃ during the anthesis-milk maturity period; it was low in the east-west direction and high in the middle area of Shandong province. Taking into account comprehensively, the high-quality probability of high-gluten wheat planting in eastern and southern Shandong province was stronger than that in central and northern, and the lowest in western. ConclusionEastern and southern regions were the optimal planting areas for strong-gluten wheat in Shandong province, with the greatest possibility of high quality. The high maximum temperature during rejuvenation-jointing period, jointing-anthesis period and grain-filling period was unfavorable to the rheological parameters of wheat dough, while the increase of effective accumulated temperature during anthesis-milk maturity period was beneficial to the increase of protein content. The rainfall during sowing-overwintering period was beneficial to the increase of dough stabilize time; when the rainfall was less than 14.5 mm during anthesis-milk maturity period, it was not beneficial for the wet gluten content to reach the strong gluten standard; thrainfall during the rejuvenation-jointing period is was not conducive to the increase of bulk density. Therefore, in the production of strong gluten wheat, it was suggested that irrigation should be carried out in the overwintering period and early grouting according to the weather conditions, and the irrigation time during rejuvenation-jointing period should be postponed as far as possible.

Key words: wheat quality parameters, meteorological factors, spatial distribution