首页> 外文学位 >Changes in response indices as a function of time in winter wheat (Triticum aestivum L.) and use of optical sensors for detecting yield differences at different resolutions in corn (Zea mays L.).
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Changes in response indices as a function of time in winter wheat (Triticum aestivum L.) and use of optical sensors for detecting yield differences at different resolutions in corn (Zea mays L.).

机译:冬小麦(Triticum aestivum L.)的响应指数随时间的变化,以及使用光学传感器检测玉米(Zea mays L.)不同分辨率下的产量差异。

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摘要

Scope and method of study. For chapter one, a study on hard red winter wheat was conducted to determine the nitrogen (N) responsiveness using a response index (RI) as a function of time at 5-locations over a 3-year period. Response index was plotted against days where growing degree days (GDD) were more than zero to determine the ideal stage for predicting RI. Sensor NDVI (normalized difference vegetation index) readings from a non-N limiting strip divided by the farmer practice was used to estimate RI NDVI. Subplots (2 m2) were established within five existing long-term trials employing a randomized complete block design. From each plot, Greenseeker(TM) NDVI sensor readings were collected at various growth stages where RINDVI was subsequently determined. For chapter two, experiments were conducted to determine the optimum resolution for prediction of corn grain yield. Four corn rows, 30 m in length, were randomly selected at three locations in 2004, and 15 m length with 8 rows at two locations in 2005 and 2006. A GreenSeeker optical sensor was used to determine average NDVI across number of plants and over 12 fixed distances. Individual corn plants were harvested and grain yield was determined. Correlation of corn grain yield versus NDVI was evaluated over increasing distances and increasing number of corn plants.; Findings and conclusions. For chapter one, RINDVI increased with advancing stage of growth. Excluding Stillwater 2006 and Perkins 2005, the relationship between RINDVI and GDD>0 was positive and highly correlated. The relationship between RINDVI and RIHarvest was best described using exponential equations. Averaged over years and sites for all growth stages, the correlation of RINDVI and RIHarvest was positive and increased up to Feekes 8. For chapter two, the linear-plateau model coefficient of determination (R 2) was maximized when averaged over every 4-plants in 2004 and 2006, and over 11-plants in 2005. Likewise, R2 was maximized at a fixed distance of 95, 141, and 87 cm in 2004, 2005, and 2006, respectively. Based on the results collected, we recommend 95 cm or alternately, 4-plants as the optimum resolution for detecting early-season differences in yield potential and making management decisions.
机译:研究范围和方法。在第一章中,进行了一项关于硬红冬小麦的研究,使用3年内5个位置的响应指数(RI)作为时间的函数来确定氮(N)响应度。针对生长度天数(GDD)大于零的天数绘制响应指数,以确定预测RI的理想阶段。来自非氮限制带的传感器NDVI(归一化植被指数)读数除以农民的做法被用于估算RI NDVI。在采用随机完整模块设计的五个现有长期试验中建立了子图(2 m2)。从每个样区中,在各个生长阶段收集Greenseeker TM NDVI传感器读数,随后确定RINDVI。对于第二章,进行了实验以确定预测玉米籽粒产量的最佳分辨率。 2004年在三个位置随机选择了四个玉米行,长30 m,在2005年和2006年在三个位置随机选择了15 m长,两个行中有8行。GreenSeeker光学传感器用于确定植物总数和12个以上植物的平均NDVI固定距离。收获单个玉米植物并确定谷物产量。在距离增加和玉米植株数量增加的情况下,评估了玉米籽粒产量与NDVI的相关性。结论和结论。对于第一章,RINDVI随着增长阶段的增加而增加。除了Stillwater 2006和Perkins 2005,RINDVI与GDD> 0之间的关系是正相关的。 RINDVI和RIHarvest之间的关系最好使用指数方程式来描述。在所有生长阶段的多年和站点上进行平均,RINDVI和RIHarvest的相关性为正,并增加到Feekes8。对于第二章,当每4个植物取平均值时,线性高原模型的测定系数(R 2)最大化。在2004年和2006年,以及在2005年超过11个植物。同样,在2004年,2005年和2006年,R2分别以95、141和87 cm的固定距离最大化。根据收集的结果,我们建议使用95厘米或另外的4株植物作为最佳分辨率,以检测产量潜力的早期季节差异并做出管理决策。

著录项

  • 作者

    Chung, Byungkyun.;

  • 作者单位

    Oklahoma State University.;

  • 授予单位 Oklahoma State University.;
  • 学科 Agriculture Agronomy.; Agriculture Soil Science.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 80 p.
  • 总页数 80
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农学(农艺学);土壤学;
  • 关键词

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