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Xia Yao Yan ZhuYongChao Tian Wei FengWeiXing Cao 《International Journal of Applied Earth Observation and Geoinformation》2010
Hyperspectral sensing can provide an effective means for fast and non-destructive estimation of leaf nitrogen (N) status in crop plants. The objectives of this study were to design a new method to extract hyperspectral spectrum information, to explore sensitive spectral bands, suitable bandwidth and best vegetation indices based on precise analysis of ground-based hyperspectral information, and to develop regression models for estimating leaf N accumulation per unit soil area (LNA, g N m−2) in winter wheat (Triticum aestivum L.). Three field experiments were conducted with different N rates and cultivar types in three consecutive growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance and LNA under the various treatments. Then, normalized difference spectral indices (NDSI) and ratio spectral indices (RSI) based on the original spectrum and the first derivative spectrum were constructed within the range of 350–2500 nm, and their relationships with LNA were quantified. The results showed that both LNA and canopy hyperspectral reflectance in wheat changed with varied N rates, with consistent patterns across different cultivars and seasons. The sensitive spectral bands for LNA existed mainly within visible and near infrared regions. The best spectral indices for estimating LNA in wheat were found to be NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516), and the regression models based on the above four spectral indices were formulated as Y = 26.34x1.887, Y = 5.095x − 6.040, Y = 0.609 e3.008x and Y = 0.388x1.260, respectively, with R2 greater than 0.81. Furthermore, expanding the bandwidth of NDSI (R860, R720) and RSI (R990, R720) from 1 nm to 100 nm at 1 nm interval produced the LNA monitoring models with similar performance within about 33 nm and 23 nm bandwidth, respectively, over which the statistical parameters of the models became less stable. From testing of the derived equations, the model for LNA estimation on NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) gave R2 over 0.79 with more satisfactory performance than previously reported models and physical models in wheat. It can be concluded that the present hyperspectral parameters of NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) can be reliably used for estimating LNA in winter wheat. 相似文献
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随机森林机器算法在江苏省小麦赤霉病病穗率预测中的应用 总被引：1，自引：0，他引：1
基于2002—2018年江苏省13个市的小麦赤霉病病穗率资料与生育期观测资料、相应时段内的逐日气象数据,应用随机森林机器学习算法,分生育期、分区域定量评估影响病穗率的主要气象因子特征变量和贡献率,按不同起报时间建立预测模型并进行验证。结果表明,各生育期重要特征变量贡献率的排序为:抽穗扬花期＞拔节期＞越冬期。抽穗扬花期湿度、连续≥3 d的雨日和日照对赤霉病起主导作用,拔节期日照、降雨量、湿度和雨日与越冬期气温和降雪对赤霉病均具有前期影响,甄别出的重要特征变量排序结果符合赤霉病菌发育、释放、侵染和流行规律;基于随机森林算法建立的病穗率预测模型的精度与重要特征变量个数、赤霉病发生区域、Mtry参数设定、生育期有关;最早可在3月初进行预测,预测时效近3个月,起报时间越接近乳熟期,输入的重要特征变量越多,则病穗率预测准确率越高,病穗率模拟值与实测值的波动趋势完全一致,对赤霉病“中等”和“偏重”等级模拟效果好,表明随机森林算法在赤霉病预测中有较高的可靠性和业务应用潜力。 相似文献
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主要对以色列野生二粒小麦赫尔蒙种群中分离获得的一个抗条锈病基因进行了分子定位研究 ,将源于赫尔蒙山具抗杀锈病的种系 T.dicoccides H52与普通的栽培种 Langdon进行杂交并创建了 F2 代遗传图。研究发现 H52种系抗条锈病的能力由一种显性基因控制 ,将其暂定名为 Yr H52。从 1 2 0个微卫星标记中 ,已经检测到来自亲本 91 %的多态性 ,而且从其中 56个微卫星分子标记中产生了 79个分离的位点 ,有 9个位点显示出了与 Yr H 52基因连锁 ,其重组率 0 .0 2～ 0 .3 5,遗传距离 2 .0 0～ 4 3 .3 7cm之间 ,L OD值 3 .56～ 54.2 2。由 1 0个微卫星位点和 Yr H52构建的染色体 1 B遗传图 ,其图距全长为 1 0 1 .5cm。Yr H52基因位于 Xgwm2 64 a和 Xgwm2 64 c之间 ,且与 Xgwm2 64 a、Xgwm1 8紧密连锁 ,两侧依次分别与 Xgwm1 3 1 a、Xgwm63 6b、Xgwm2 64 c、Xgwm4 0 3 a、Xgwm1 53、Xgwm550 a和 Xgwm1 2 4连锁。同时 ,Yr H52也与 REL P标记物 N or1紧密连锁 ,图距 1 .4 cm,L OD2 9.62。这显然与野生二粒小麦另一个抗条锈病基因 Yr1 5不同 ,研究证明 Yr1 5与 N or1图距是 1 1 .0 cm。 相似文献
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采用部门间影响模式比较计划（ISI-MIP）的气候模式,确定全球升温1.5℃和2.0℃出现的时间,并结合农业技术转移决策支持系统（DSSAT）模型模拟小麦的产量,最终选取4套数据对比研究中国小麦区温度和降水变化特征以及各区域小麦产量变化趋势,综合评价了不同升温情景对中国小麦产量的影响。结果表明：(1)在全球升温1.5℃和2.0℃背景下,我国小麦生育期内温度相对于工业革命前分别升高1.17℃和1.81℃。两种升温情景下我国春麦区升温幅度大于冬麦区升温幅度。春麦区中新疆春麦区升温幅度最大,西北春麦区升温幅度最小;冬麦区中温度变化最大和最小的麦区分别为西南冬麦区和黄淮冬麦区。(2)在全球升温1.5℃和2.0℃情景下,我国小麦生育期内降水相对于历史时段(1986—2005年)分别增加9.1%和11.3%。从各麦区来看,两种升温情景下春麦区降水增加幅度略大于冬麦区的增加幅度。所有麦区中只有新疆春麦区降水低于历史时段降水。春麦区降水增加幅度最大的麦区为北部春麦区。冬麦区中降水增加较大的麦区为北部冬麦区和黄淮冬麦区,降水增加较小的麦区为华南冬麦区和西南冬麦区。(3)两种升温情景下,我国小麦单产相对于历史时段(1986—2005年)平均减产分别为5.2%和4.6%,两种升温情景对中国小麦产量并没有显著的差异。在全球升温大背景下我国春小麦主要呈现增产趋势,冬小麦主要呈现减产趋势。减产幅度较大的麦区为华南冬麦区和青藏春麦区,增产幅度最大的麦区为西北春麦区。从各麦区产量减产面积比例上看,我国各麦区减产面积所占比例趋势为从北向南由多变少再变多,其中华南冬麦区减产面积所占比例最大,北部冬麦区最小。 相似文献
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利用新疆巴楚气象站1984—2013年逐日气象资料,运用线性回归、趋势系数、异常度、Mann-Kendall突变检验等方法,分析了巴楚县多时间尺度气温的变化特征对冬小麦生长发育和产量的影响。结果表明:近30 a巴楚县冬季、春季平均气温均呈上升趋势,其中春季平均气温上升趋势显著,并于1998年发生了增暖性突变;寒冷日和酷冷日数均呈减少趋势,其中寒冷日数在1996年发生了减少性突变;稳定通过0℃界限温度的初日表现为提前、终日表现为推迟,持续日数则相应表现为增加趋势;日最高气温≥30℃日数呈增加趋势;冬小麦生长季内前期气温偏低,后期气温偏高是影响小麦产量的主要气候因子,其中抽穗、开花期的平均气温与小麦产量显著相关。 相似文献
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Environmental variables related to wheat yields in the semiarid pampa region of Argentina 总被引：1，自引：0，他引：1
The current paper analyses various environmental parameters in relation to wheat yields in Bordenave, Province of Buenos Aires, Argentina. The variables used are: precipitation (ppt), maximum (Tx) and minimum temperature (Tmi) as well as those obtained by applying the Palmer model. Decadic and phenological scales are used for data corresponding to the period 1977–2000. The stepwise method is used to obtain a multi-variate equation to calculate yield taking into account environmental variables only. For a five variates model the coefficient of determination, R2 equals 95.79% and the standard error of estimation is 129.0 kg ha−1. In the sample yields, the incidence of total variability for thermal variables is 42.7% and for hydrological variables, 53%. The value and sign of the correlation coefficients were analysed throughout the cultivation cycle. The α coefficient is mainly responsible for yield variance during tillering and stem elongation. There is good correlation with the values of Palmer's Drought Severity Index (PDSI) for the flowering and grain filling stages. 相似文献
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内蒙古奈曼麦田生长期的微气象变化 总被引：2，自引：1，他引：2
采用波文比热量平衡法分析了内蒙古奈曼麦田生长不同阶段的微气象变化。结果表明：（１）麦田反射率随小麦生长趋于旺盛而减小；（２）随着小麦的生长，净辐射及其与太阳总辐射的比值增大；（３）白天净辐射主要用于潜热交换；夜里净辐射主要由潜热交换与土壤热交换补给；（４）波文比白天小，早晨和夜里大。 相似文献
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