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首页> 外文期刊>Fresenius Environmental Bulletin >PREDICTION OF LEAF WATER STATUS USING SPECTRAL INDICES FOR YOUNG OLIVE TREES
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PREDICTION OF LEAF WATER STATUS USING SPECTRAL INDICES FOR YOUNG OLIVE TREES

机译:利用光谱指数预测年轻橄榄树的叶片水分状况

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摘要

It is important to determine the plant water stress before it can reduce the yield or becomes visible. The aim of this study was to investigate the relationship between remotely sensed hyperspectral reflectance indices and leaf water status (LWS) of olive seedlings (Olea europaea L. cv. 'Ayvahik', 'D9', 'D36', 'Erdek Yaglik', 'Frantoio' and 'Gemlik') at different irrigation regime. A pot experiment was conducted in field conditions with 2-years old olive seedlings for the seasons 2011 and 2012. Four levels of water treatment were applied to the pots to bring about different stress conditions; no stress (I-100), mild stress (I-66), severe stress (I-33) and full stress (I-0). Leaf water potential (LWP) and relative water content (RWC) were determined to assess the LWS of the plants. In addition, canopy spectral reflectance was measured with a handheld spectroradiometer and several spectral vegetation indices were calculated using canopy reflectance data. Analysis showed that the irrigation requirement of Frantoio cultivar was the highest when compared to that of other cultivars, while the lowest amount of water was required by Ayvahk cultivar. According to the stepwise multiple linear regression (SMLR) analysis between spectral indices and LWS of olive seedlings, the coefficient of determination (R~2) of model between RWC and Photochemical Reflectance Index (PRI) was 0.70, while it was 0.81 between LWP and PRI, Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI) and Normalized Pigment Chlorophyll Index (NPCI). Accordingly, it appeared that LWP could be detected more accurately than RWC using spectral indices. Results of this study indicated that the olive plant was very susceptible to water stress and the remotely sensed spectral data could be used to determine RWC and LWP as an indicator of water stress.
机译:重要的是要确定植物水分胁迫,以免降低产量或变得可见。这项研究的目的是调查遥感遥感的高光谱反射指数与橄榄幼苗(Olea europaea L. cv。'Ayvahik','D9','D36','Erdek Yaglik', “ Frantoio”和“ Gemlik”)在不同的灌溉制度下。在田间条件下,对2岁的橄榄苗在2011年和2012年的田间条件下进行了盆栽试验。对盆栽进行了4级水处理,以产生不同的胁迫条件。无压力(I-100),轻微压力(I-66),严重压力(I-33)和完全压力(I-0)。确定叶的水势(LWP)和相对水含量(RWC)以评估植物的LWS。此外,用手持式光谱辐射仪测量了冠层光谱反射率,并使用冠层反射率数据计算了一些光谱植被指数。分析表明,与其他品种相比,Frantoio品种的灌溉需求最高,而Ayvahk品种的灌溉需求最低。根据橄榄幼苗光谱指数和LWS之间的逐步多元线性回归(SMLR)分析,RWC和光化学反射指数(PRI)之间模型的确定系数(R〜2)为0.70,而LWP与光化学反射指数之间的模型确定系数为0.81。 PRI,土壤调整植被指数(SAVI),归一化差异植被指数(NDVI)和归一化色素叶绿素指数(NPCI)。因此,看来使用光谱指数可以比RWC更准确地检测LWP。这项研究的结果表明,橄榄植物很容易受到水分胁迫,遥感光谱数据可用于确定RWC和LWP作为水分胁迫的指标。

著录项

  • 来源
    《Fresenius Environmental Bulletin 》 |2013年第9a期| 2713-2720| 共8页
  • 作者单位

    Laboratory of Agricultural Sensor and Remote Sensing, Department of Agricultural Structures and Irrigation, Faculty of Agriculture, Canakkale Onsekiz Mart University, Turkey;

    Bornova Olive Research Station, Izmir, Turkey;

    Department of Agricultural Structures and Irrigation, Faculty of Agriculture, Ege University, Izmir, Turkey;

    Laboratory of Agricultural Sensor and Remote Sensing, Department of Agricultural Structures and Irrigation, Faculty of Agriculture, Canakkale Onsekiz Mart University, Turkey;

    Bornova Olive Research Station, Izmir, Turkey;

    Department of Agricultural Structures and Irrigation, Faculty of Agriculture, Ege University, Izmir, Turkey;

    Laboratory of Agricultural Sensor and Remote Sensing, Department of Agricultural Structures and Irrigation, Faculty of Agriculture, Canakkale Onsekiz Mart University, Turkey;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Olive; water stress; leaf water status; spectral indices; spectral reflectance;

    机译:橄榄;水分压力叶水状况;光谱指数光谱反射率;

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