SPECTRAL CHARACTERISTICS FOR ESTIMATION HEAVY METALS ACCUMULATION IN WHEAT PLANTS AND GRAIN | ||||
| Journal of Productivity and Development | ||||
| Article 1, Volume 22, Issue 3, August 2017, Page 409-428 PDF (943.83 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/jpd.2019.41905 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Mai Amer  1; Ay Tyler2; Clare Wilson2; Mario Vallejo-Marin3; Bi Hunter2; Tarek Fouda1; Adel El Metwaly1
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| 1Agricultural Engineering Dept., Faculty of Agriculture, Tanta University, Egypt | ||||
| 2Biological and Environmental Sciences, School of Natural Sciences, University of Stirling , Stirling, Scotland, UK | ||||
| 3Agricultural Engineering Dept., Faculty of Agriculture, Tanta University, Egypt b Biological and Environmental Sciences, School of Natural Sciences, University of Stirling , Stirling, Scotland, UK | ||||
| Abstract | ||||
| Plants would the start with step of a metal's pathway starting with the dirt on heterotrophic creatures for example, such that animals and humans, thus the substance from claiming metallic follow components for eatable parts of a plant representable accessible load of these metals that might enter those natural way of life through plants. Around metal elements, Cu and Zn would micro nutrients as they are essential in trace concentrations for physiological processes in plants. Furthermore consequently would a critical part from the soil–plant–food continuum. Therefore this study aimed to analyzing the performance of multivariate hyperspectral vegetation indices of wheat (Triticum aestivum L.) in estimating the accumulation of these elements in plant dry mutter and the final product of Egyptian wheat crop irrigated with high concentrations of Zn and Cu. We applied five concentrations for each element (0.05, 20, 40, 100, and 150 ppm of Zn) and (0.02, 8, 10, 12, and 15 ppm of Cu) to a controlled greenhouse experiment to examine the effect of these concentrations on plant spectral characteristics and study the possibility of using spectroradiometry measurements for identifying the grain content of these metals. The results demonstrated that The hyperspectral vegetation indices had a potential for monitoring Zn concentration in the plant dry matter. NPCI and PSSR had a highest correlation with Cu phytoaccumulation into the grains with highest significant level (P-Value < 0.01) and (r) values (-0.39, -0.42). Conclusively, Results of present study demonstrate that hyperspectral reflectance data, as well as studied VIs appears to have potentials for monitoring the phytoaccumulation of Zn into above-ground parts of wheat. The hyperspectral vegetation indices had insignificant correlation with Zn accumulation in to the grains, but it had a significant negative relationship with Cu concentration in grains with low correlation coefficient values. | ||||
| Keywords | ||||
| Heavy metals; Remote Sensing; Vegetation Indices; detecting stress | ||||
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