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微信公众号：大豆科学

[1]王惠贞,唐红艳,牛冬,等.大豆关键品质成分的气象预报方法研究[J].大豆科学,2021,40(01):112-121.[doi:10.11861/j.issn.1000-9841.2021.01.0112]
　WANG Hui-zhen,TANG Hong-yan,NIU Dong,et al.Study on Meteorological Forecasting Method of Key Quality Components in Soybean[J].Soybean Science,2021,40(01):112-121.[doi:10.11861/j.issn.1000-9841.2021.01.0112]

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大豆关键品质成分的气象预报方法研究

《大豆科学》[ISSN:1000-9841/CN:23-1227/S] 卷: 第40卷期数: 2021年01 页码: 112-121 栏目: 出版日期: 2021-01-20

Title:: Study on Meteorological Forecasting Method of Key Quality Components in Soybean

文章编号:: 2021,40(1)：112-121

作者:: 王惠贞; 唐红艳; 牛冬; 吕淼; (1.内蒙古自治区生态与农业气象中心，内蒙古呼和浩特 010051;2.内蒙古自治区气象服务中心，内蒙古呼和浩特 010051;3.扎兰屯市气象局，内蒙古呼伦贝尔 162650)

Author(s):: WANG Hui-zhen; TANG Hong-yan; NIU Dong; LYU Miao; （1.Inner Mongolia Ecological and Agricultural Meteorological Center, Hohhot 010051, China; 2.Inner Mongolia Service Center of Meteorology, Hohhot 010051, China; 3.Zhalantun Meteorological Bureau, Hulun Buir 162650, China）

关键词:: 大豆; 关键品质; 气象因子; 相关分析; 预报模型

Keywords:: Soybean; Key quality; Meteorological factor; Correlation analysis; Prediction model

DOI:: 10.11861/j.issn.1000-9841.2021.01.0112

文献标志码:: A

摘要:: 为评价大豆气候品质，优化布局优质大豆产区、提升大豆产品附加值和市场竞争力，利用2005—2018年内蒙古东北部大豆主产区主栽品种内豆4号的品质分析、发育期和同期气象观测等数据，采用相关分析、典型年分析和回归分析等方法，确定影响大豆蛋白质、脂肪含量的关键气象因子和关键期，并构建大豆蛋白质含量、脂肪含量等品质成分与关键气象因子的定量关系模型。结果表明：温度和降水是影响大豆蛋白质含量的主导气象因子，而影响大豆脂肪含量的主导气象因子是温度; 8月上旬至9月上旬（结荚期~鼓粒期）是影响蛋白质和脂肪含量的共同关键期，也是影响大豆品质形成的最关键阶段。大豆进入开花期后，气温高、降水多有利于蛋白质的积累，而开花初期和结荚鼓粒期气温较低、成熟期气温较高，利于大豆脂肪含量的提高。在分析生物学意义基础上优选因子，构建大豆蛋白质含量、脂肪含量与关键影响因子定量关系模型，拟合率均较高。通过对2019年大豆蛋白质含量、脂肪含量的模拟检验，预报效果较好。

Abstract:: In order to evaluate the climate quality of soybean, optimize the layout of high-quality soybean production areas, and increase the added value and market competitiveness of soybean products, this study used the quality test data, development period data and meteorological observation data for the same period of Neidou 4 in the major soybean producing areas of the northeast Inner Mongolia from 2005 to 2018 as the materials. We used methods such as correlation analysis, typical year analysis, and regression analysis, to determine the key meteorological factors and critical periods that affect soybean protein and fat content, and construct quantitative relationship model between key meteorological factors and the quality components such as soybean protein content and fat content. The results showed that temperature and precipitation were the dominant meteorological factors affecting soybean protein content, while the dominant meteorological factor affecting soybean fat content was temperature. From early August to early September, soybean pod-granulation period was a common critical period affecting protein and fat content, and also the most critical stage affecting soybean quality formation. After the flowering stage, high temperature and heavy precipitation were conducive to protein accumulation. While lower temperature in the early flowering stage and pod bearing and granulation stage and higher temperature in the mature stage were conducive to the increasing of soybean fat content. Basing on the analysis of biological significance, factor selection was carried out to establish a quantitative relationship model between soybean protein content, fat content and key influencing factors with a high fitting rate. The prediction effect of the simulation test of 2019 soybean protein content and fat content was good.

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备注/Memo

中国气象局气候变化专项（CCSF202025）; 内蒙古自治区气象局科技创新项目（nmqxkjcx201915）; 内蒙古自治区地方标准制修订项目; 内蒙古自治区自然科学基金（2017MS0411）; 公益性行业（气象）科研专项 (GYHY201506001-3); 内蒙古科技重大专项（2020ZD0005）; 内蒙古科技计划项目（2019GG016）。

更新日期/Last Update: 2021-02-09