Effects of nitrogen fertilizers on the aluminium contents of mature tea leaf and extractable aluminium in the soil

Plant and Soil (Impact Factor: 2.95). 09/1989; 119(2):342-345. DOI: 10.1007/BF02370429


Increasing rates of nitrogenous fertilizer decreased the aluminium contents in mature leaf of tea but increased the extractable
soil aluminium in the 0–30 cm soil depth. Use of NPKS 25:5:5:5 or NPK 20:10:10 did not affect the order of responses. Different
rates of potash had no effect on leaf aluminium levels. The concentrations of aluminium in the mature leaf were well above
the minimum required for tea nutrition. The increase in extractable soil aluminium due to higher nitrogen rates in part explains
the generally low potassium and calcium contents in the leaf and soil.

Download full-text


Available from: Philip Owuor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Numerous studies indicated that aluminum, the most abundant metallic element within the lithosphere, was considered to be related to some human diseases especially the Alzheimer’s disease. Tea, economically an important beverage in the world, has been found to contain higher concentration of aluminum than many other drinks and foods. Therefore, tea would be a potentially important source of dietary aluminum. In order to understand the sources of aluminum in tea leaves and factors related with aluminum content of tea leaves, an experiment was designed to investigate the relationships of aluminum in tea leaves with leaf age, soil properties and forms of aluminum in soils. The results showed that there were great distinctions in the concentration of aluminum in tea leaves with different leaf age (Alold leaf> Almature leaf> Alyoung leaf). Moreover, soil pH was the major factor controlling the uptake of aluminum from soil into tea leaves. Furthermore, the content of aluminum in tea leaves was better predicated by the soluble aluminum extracted by 0.02mol/L CaCl2.
    No preview · Article · Mar 2001 · Chinese Geographical Science
  • [Show abstract] [Hide abstract]
    ABSTRACT: The high-field 27Al NMR spectrum of aqueous tea extract contained two narrow resonances at 9.85 and 16.15 ppm. The spectra of aluminium chelates with a number of model ligands (catechol, pyrogallol, catechin, kojic acid, protocatechuic acid, ascorbic acid and salicylic acid) containing chelating moieties present in the constituents of tea showed broad resonances in the range 8–36 ppm. Potentiometric and NMR studies indicate the formation of a monohydroxo 1:1 Al-catechin chelate (δ 8.3 ppm) with highly distorted symmetry. From a comparison of the NMR spectra of tea infusions at different pH values with those of aluminium chelates with malic acid and oxalic acid (minor constituents in tea), the resonance at 16.15 ppm was assigned to the highly symmetric octahedral anionic chelate trisoxalatoaluminium, [Al(C2O4)3]3−. This was confirmed by anion-exchange separation of the chelate and its identification by 27Al NMR spectroscopy. The signal at 9.8 ppm could be due to a mixed ligand chelate containing oxalate. In the case of the aluminium-malate system, the resonance at 20 ppm was assigned to a 1:2 chelate in which malate functions as a tridentate resulting in five- and six-membered chelate rings.
    No preview · Article · Feb 1993 · Magnetic Resonance in Chemistry
  • [Show abstract] [Hide abstract]
    ABSTRACT: Medical images are noisy and complex. Segmentation and labeling of X-ray images represent many difficulties. Active contours have become an attractive subject in computer vision. Connectivity and closure properties of these contours help to overcome some important difficulties in computer vision, as edge organization and region merging. Consequently, using deformable contours reduces dramatically the search space dimension. In this paper, we present a model-based approach of multiple dynamic non-parametric curves matching with X-ray images. The model is formed of three parts: (i) image formation, (ii) high-level interaction, and (iii) contours smoothing constraints. The first and second part measure consistency of the reconstructed object with the given image and the relational a priori information of the object, respectively. The scene model represents a hierarchical structure of three processes: lines, regions and relational graphs. An object is modeled as a set of linked subobjects according to a 3-D relational graph which can be projected from a known viewpoint in a 2-D region relational graph. The resultant function is optimized using a descending search method with randomized sampling. Finally, successful results are presented for object matching in semitransparent noisy synthetic scenes
    No preview · Article · Jan 1995
Show more