کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6949355 1451265 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Combining leaf physiology, hyperspectral imaging and partial least squares-regression (PLS-R) for grapevine water status assessment
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
Combining leaf physiology, hyperspectral imaging and partial least squares-regression (PLS-R) for grapevine water status assessment
چکیده انگلیسی
Physiological measurements are considered to be the most accurate way of assessing plant water status, but they might also be time-consuming, costly and intrusive. Since visible (VIS)-to-shortwave infrared (SWIR) imaging spectrometers are able to monitor various bio-chemical alterations in the leaf, such narrow-band instruments may offer a faster, less expensive and non-destructive alternative. This requires an intelligent downsizing of broad and noisy hyperspectra into the few most physiologically-sensitive wavelengths. In the current study, hyperspectral signatures of water-stressed grapevine leaves (Vitis vinifera L. cv. Cabernet Sauvignon) were correlated to values of midday leaf water potential (Ψl), stomatal conductance (gs) and non-photochemical quenching (NPQ) under controlled conditions, using the partial least squares-regression (PLS-R) technique. It was found that opposite reflectance trends at 530-550 nm and around 1500 nm - associated with independent changes in photoprotective pigment contents and water availability, respectively - were indicative of stress-induced alterations in Ψl, gs and NPQ. Furthermore, combining the spectral responses at these VIS and SWIR regions yielded three normalized water balance indices (WABIs), which were superior to various widely-used reflectance models in predicting physiological values at both the leaf and canopy levels. The potential of the novel WABI formulations also under field conditions demonstrates their applicability for water status monitoring and irrigation scheduling.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 109, November 2015, Pages 88-97
نویسندگان
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