Yazar "Smith, S. E." seçeneğine göre listele

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    Assessment of the effect of salinity on the early growth stage of the common sunflower (Sanay cultivar) using spectral discrimination techniques
    (Academic Journals, 2008) Turhan, H.; Genc, L.; Smith, S. E.; Bostanci, Y. B.; Turkmen, O. S.
    Salinity is one of the main limiting factors for agricultural production. This is especially true in arid and semi-arid regions of the world like Turkey. The objective of this study was to determine if the effect of salt concentration on the physiological and physiological features of the sunflower (Helianthus annuus L) could be measured using remote sensing techniques. Sunflower seedlings were grown under controlled conditions and irrigated with Hoagland Solution containing three different concentrations of NaCl (salt) (0.0, 0.5, 1.0 and 1.5%). The results showed that plant growth decreased proportionally with increasing levels of NaCl. Chlorophyll concentration and a Normalized Difference Vegetation Index (NDVI) were derived for the plants using a spectroradiometer. There was found to be a significant (r(2) = 0.76) correlation between chlorophyll and NDVI values. Therefore, factors that can be derived through remote sensing such as NDVI and chlorophyll can be used to indirectly demonstrate the impact salinity has on sunflower plants. Therefore, agriculturalists can assess growth rate changes caused by salinity using remote sensing techniques.
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    Öğe
    Vegetation indices as indicators of damage by the sunn pest (Hemiptera: Scutelleridae) to field grown wheat
    (Academic Journals, 2008) Genc, H.; Genc, L.; Turhan, H.; Smith, S. E.; Nation, J. L.
    The sunn pest, Eurygaster integriceps Put. ( Hemiptera: Scutelleridae), also known as sting or cereal pest, is one of the most economically important pests of wheat in the world. In this study, a collapsible nylon cloth cage experiments were conducted to determine the feasibility of using remote sensing techniques to detect stress in wheat caused by the density of sunn pests. The results show we can detect the amount of stress in wheat caused by different life stages of sunn pest with a hand-held radiometer. Normalized difference vegetation index (NDVI) based indices; NDVIsg, NDVId, NDVIr, and structure insensitive pigment index ( SIPI) were chosen out of 19 indices initially tested. The NDVI based vegetation indices derived from hyperspectral data, recorded by a hand held spectroradiometer, were used to determine the predicted indices using the initial number of Sunn Pest (NOSP). Overall, r(2) values of all predicted indices calculated for 3(rd) instars were lower than those of 4(th) and adult stage. When r(2) was considered separately, predicted NDVIr index value (87.4) was the highest and predicted SIPI index value is lowest (80.7) in 3(rd) instars. The highest r(2) value was obtained in adult stage of sunn pest is NDVIsg (96.9) compare with NDVId (95.5), NDVIr (92.4) and SIPI (94.2). It was also concluded that remote sensing could detect not only the different stages pest damage on wheat, but also the number of sunn pest stages density affect in controlled experiments.