الفهرس 
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Abstract
Objectives: The objectives of this study were to evaluate passive remote sensing technology as a tool to detect water and nitrogen stress levels for potato crop. Also to test and validate measurements of canopy temperature to detect changes in potato canopy water content and determine the optimal hyper spectral indices in the visible and near- infrared portions of the spectrum that best characterize potato crop characteristics. Methodology & Results: This study included the evaluation of the crop water stress and normalized relative canopy temperature indices by measuring potato leaf temperature. These indices were used to show water status of potato crop under fully irrigated and water stress conditions. Five normalized spectral reflectance indices were introduced besides seven old ones for detecting water and nitrogen status of potato crop. Then, optimal spectral indices were selected from contour maps to predict canopy water content (%), water productivity (WP), nitrogen concentration, nitrogen uptake and SPAD value. CWSI and NRCT indexes increased with increasing canopy temperature which accordingly cause the decrement of CWC (%) and water productivity. Apositive relationship between CWSI and water productivity was found in both in winter and summer seasons. The obtained results showed that average CWSI value under irrigated conditions was 0.19 and the low and high correlation were 0.73 and 0.90 between crop water stress index and water productivity (WP). While in early water stress treatments, average CWSI value was 0.65. Also, the low and high value of R2 between CWSI and WP were 0.65 and 0.95*, respectively. Whereas in late water stress treatments, the mean of CWSI values was 0.38 and the low and high R2 values between CWSI and WP were 0.63 and 0.91. The results indicated that canopy water content CWC % is affected with early and late water stress conditions. Both indices CWSI and NRCT gave higher correlation (0.85 and 0.80) with CWC in winter season than summer (0.77 and 0.78). On the other hand, the optimal index with CWC was (R760-R670/R760+R670) with high correlation 0.74** and 0.70** for the two seasons. These results showed that the best index for detecting potato nitrogen concentration (%) was (R780_R670)/( R780+R670) with high correlation of 0.72** and 0.83** for two seasons, respectively. These results also showed that the best index for detecting potato nitrogen uptake was (R978_R906)/( R978+R906) with high correlation of R2= 0.77**, 0.64**. As well as, the optimal index with SPAD value was (R774_R656)/(R774+R656) and the correlation value (R2) were 0.70** and 0.67**. Conclusion: Over all results under field conditions, potato canopy water content was the most suitable parameter to detect water stress by using passive spectral reflectance and thermal imaging camera. Therefore, time-consuming destructive methods could be replaced by rapid, non-destructive methods. The results observed from this work approved the passive spectral reflectance technique is reliable and has a high level of confidence.