PREDICTION OF LEAF WATER STATUS USING SPECTRAL INDICES FOR YOUNG OLIVE TREES


ÇAMOĞLU G., KAYA U., AKKUZU E., GENÇ L., GURBUZ M., Mengu G. P., ...More

FRESENIUS ENVIRONMENTAL BULLETIN, vol.22, pp.2713-2720, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22
  • Publication Date: 2013
  • Journal Name: FRESENIUS ENVIRONMENTAL BULLETIN
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2713-2720
  • Keywords: Olive, water stress, leaf water status, spectral indices, spectral reflectance
  • Çanakkale Onsekiz Mart University Affiliated: Yes

Abstract

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. 'Ayvalik', '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 Ayvalik 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.