| 小麦、玉米粒重动态共性特征及其最佳模型的筛选与应用 |
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| 引用本文： | 付雪丽,赵明,周宝元,崔国美,丁在松.小麦、玉米粒重动态共性特征及其最佳模型的筛选与应用[J].作物学报,2009,35(2):309-316. |
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| 作者姓名： | 付雪丽 赵明 周宝元 崔国美 丁在松 |
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| 作者单位： | 中国农业科学院作物科学研究所，北京100081 |
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| 基金项目： | 本研究由国家重点基础研究发展计划（973计划）项目（2009CB118605），国家粮食丰产科技工程项目（2006BAD02A13）资助。 |
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| 摘 要： | 为了定量描述小麦、玉米两作物粒重变化共性特征，选用3个冬小麦和4个夏玉米不同熟期型品种进行不同密度的田间试验，对其粒重(GW)动态进行测定，并对GW和灌浆天数进行“归一化”处理得到的3个主要模型进行比较，结果表明，Logistic曲线方程y= a/(1+be–cx) 具有广泛适应性和生物学意义，具体方程式为y=1.0624/(1+52.8653e–6.7609x)，r=0.9916 (P<0.01)。不同作物、品种、密度处理的方程参数a值基本为1；参数b在密度间变异很小，品种间变幅较大，为45.3379~66.9306；c值在品种和密度间变异均很小，在小麦和玉米间的变幅分别为6.2122~6.8025和7.0199~7.7325。应用本试验及河南焦作高产冬小麦和山东泰安高产夏玉米不同品种的GW试验资料对模型分别进行验证表明，冬小麦和夏玉米的归一化GW动态共性模型的模拟准确度(以k表示)，分别为0.9870、1.0057和0.9982、1.0131，精确度(以R2表示)分别为0.9854、0.9918和0.9772、0.9926。说明归一化方法建立的小麦、玉米GW动态共性模型能够准确地反映两作物GW动态共性变化特点。利用该模型，仅根据品种的灌浆期和最大GW，以及参数b值的品种特点，便可还原整个灌浆期的GW动态。计算不同地点、年份及不同品种、密度处理的冬小麦、夏玉米灌浆前、中、后期的GW模拟值与测量值均比较接近，误差小于0.2797。
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| 关 键 词： | 小麦 玉米 粒重动态 共性特征 模型筛选 |
| 收稿时间： | 2008-08-13 |
| 修稿时间： | 2008-10-26 |
Optimal Model for Dynamic Characteristics of Grain Weight Commonly Used in Wheat and Maize |
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| FU Xue-Li,ZHAO Ming,ZHOU Bao-Yuan,CUI Guo-Mei,DING Zai-Song.Optimal Model for Dynamic Characteristics of Grain Weight Commonly Used in Wheat and Maize[J].Acta Agronomica Sinica,2009,35(2):309-316. |
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| Authors: | FU Xue-Li ZHAO Ming ZHOU Bao-Yuan CUI Guo-Mei DING Zai-Song |
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| Institution: | Crop Science Institutes,Chinese Academy of Agricultural Sciences, Beijing 100081,China |
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| Abstract: | Grain weight (GW) is one of important components of yield in cereal crops. Currently, there are several models on GW of cereal crops, such as wheat (Triticum aestivum L.), maize (Zea mays L.), and rice (Oryza sativa L.). However, these models are mostly applicable on a single crop.To establish a common model of GW for at least two crops with wider application under different conditions, three cultivars of winter wheat and four cultivars of summer maize were used in field experiments in four environments in 2006–2008. Each cultivar had three treatments of density. A common GW model, y= a / (1+be-cx), was developed with normalized GWand grain filling duration for the two crops. The parameters of a, b, and c were 1.0624, 52.8653, and 6.7609 (r=0.9916, P<0.01) on the basis of the experimental data, respectively. In different crops, cultivars, and densities, the GW dynamic model kept a relative stable a value, which was around 1; however, the b and c values varied in different conditions. The b value changed slightly with density, and shift from 45.3379 to 66.9306 in different cultivars; whereas, the c value had small differences among different cultivars and densities, and varied from 6.2122 to 6.8025 in winter wheat and from 7.0199 to 7.7325 in maize. The accuracy and precision of the normalized model were tested with theGWdata of winter wheat from Jiaozuo, Henan province and summer maize from Tianan, Shandong province as well as data in this study. The normalized dynamic model could make a good estimation of GW dynamics with the accuracies of 0.9870, 1.0057, and 0.9982, 1.0131, and the precision (R2) of 0.9854, 0.9918 and 0.9772, 0.9926 for winter wheat and summer maize respectively. Compared with other GWmodels established by other researches, normalized GW dynamic model could eliminate the variance of the model parameters caused by location, year, cultivar, and density. Normalized GWdynamic model can predict the increase of GW reliably and easily, if the GWmax and grain filling duration are acquired, and the characteristics of parameter b are ascertained. This model is applicable to calculate the GW of winter wheat and summer maize at early, middle, and late stages of growth under different conditions (region, years, cultivar, and density), and the error is less than 0.2797 between the measured GW and the simulated GW. |
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| Keywords: | Wheat Maize Grain weight dynamic Common characters Model selection |
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