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首页> 外文期刊>International journal of remote sensing >Using aerial imagery and digital photography to monitor growth and yield in winter wheat
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Using aerial imagery and digital photography to monitor growth and yield in winter wheat

机译:使用航空影像和数码摄影监测冬小麦的生长和单产

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摘要

Monitoring wheat (Triticum aestivum L.) performance throughout the growing season provides information on productivity and yield potential. Remote sensing tools have provided easy and quick measurements without destructive sampling. The objective of this study was to evaluate genetic variability in growth and performance of 20 wheat genotypes under two water regimes (rainfed and irrigated), using spectral vegetation indices (SVI) estimated from aerial imagery and percentage ground cover (%GC) estimated from digital photos. Field experiments were conducted at Bushland, Texas in two growing seasons (2014-2015 and 2015-2016). Digital photographs were taken using a digital camera in each plot, while a manned aircraft collected images of the entire field using a 12-band multiple camera array Tetracam system at three growth stages (tillering, jointing and heading). Results showed that a significant variation exists in SVI, %GC, aboveground biomass and yield among the wheat genotypes mostly at tillering and jointing. Significant relationships for %GC from digital photo at jointing was recorded with Normalized Difference Vegetation Index (NDVI) at tillering (coefficient of determination, R-2 = 0.84, p 0.0001) and with %GC estimated from Perpendicular Vegetation Index (PVI) at tillering (R-2 = 0.83, p 0.0001). Among the indices, Ratio Vegetation Index (RVI), Green-Red VI, Green Leaf Index (GLI), Generalized DVI (squared), DVI, Enhanced VI, Enhanced NDVI, and NDVI explained 37-99% of the variability in aboveground biomass and yield. Results indicate that these indices could be used as an indirect selection tool for screening a large number of early-generation and advanced wheat lines.
机译:在整个生长期监测小麦(Triticum aestivum L.)的表现可提供有关生产力和单产潜力的信息。遥感工具提供了简便而快速的测量,而没有破坏性的采样。这项研究的目的是使用航空影像估计的光谱植被指数(SVI)和数字影像估计的地表覆盖率(%GC),评估两种水情(干旱和灌溉)下20种小麦基因型生长和表现的遗传变异性。相片。在两个生长季节(2014-2015年和2015-2016年)在德克萨斯州布什兰市进行了田间试验。在每个小区中,使用数码相机拍摄数码照片,而有人驾驶飞机则使用12带多相机阵列Tetracam系统在三个生长阶段(分iller,拔节和航向)收集整个田地的图像。结果表明,在分er和拔节期,不同基因型小麦的SVI,%GC,地上生物量和产量存在显着差异。分digital时用归一化植被指数(NDVI)(测定系数,R-2 = 0.84,p <0.0001)记录了拔节时数码照片中%GC的显着关系,而垂直分枝指数(PVI)估计了%GC的显着关系。分((R-2 = 0.83,p <0.0001)。在这些指标中,比率植被指数(RVI),绿红VI,绿叶指数(GLI),广义DVI(平方),DVI,增强型VI,增强型NDVI和NDVI解释了地上生物量的37-99%的变异性和产量。结果表明,这些指数可以用作筛选大量早期和高级小麦品系的间接选择工具。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第18期|6905-6929|共25页
  • 作者单位

    Texas A&M Univ, Dept Soil & Crop Sci, College Stn, TX 77843 USA|Texas A&M AgriLife Res, Amarillo, TX 79119 USA;

    Texas A&M Univ, Dept Soil & Crop Sci, College Stn, TX 77843 USA;

    Texas A&M Univ, Dept Soil & Crop Sci, College Stn, TX 77843 USA;

    Texas A&M AgriLife Res, Amarillo, TX 79119 USA;

    Texas A&M AgriLife Res, Amarillo, TX 79119 USA;

    USDA ARS, Stoneville, MS 38776 USA;

    Texas A&M AgriLife Res, Amarillo, TX 79119 USA;

    Texas A&M AgriLife Res, Amarillo, TX 79119 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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