Stability Studies on the Aqueous Extract of the Fresh Leaves of Combretum Micranthum G. Don Used as Antibacterial Agent

The fresh leaves of Combretum micranthum were harvested during the rainy season in Akwa Ibom State, washed and subjected to extraction by maceration in distilled water. Concentration was done with a rotary evaporator. The extracts were tested for content of the following phytochemicals using standard methods： alkaloids, saponins, tannins, anthraquinones, cardiac glycosides, flavonoids and steroids. Antibacterial sensitivity test of the extract was carried out on S. aureus, B. subtilis and E. coli using agar well diffusion method and Ampiclox as control. The effect of storage time of the extract on its antibacterial activity was determined after the extract was kept at room temperature for 1 h, 24 h, 48 h and 72 h, respectively. Preparations of 200 mg/mL of the aqueous extract were made with additives as follows： （a） no additive; （b） methyl paraben （0.3%）; （c） propyl paraben （0.3%）; （d） sodium metabisulfite （0.01%）; （e） A combination of methyl paraben （0.3%） and propyl paraben （0.3%）; （f） A combination of methyl paraben （0.3%）, propyl paraben （0.3%） and sodium metabisulfite （0.01%）. A visual observation of the stabilized preparations was employed on daily basis for 30 days. Phytochemical analyses on the aqueous extract of the fresh leaves showed the absence of alkaloids, anthraquinones and flavonoids. Saponins, cardiac glycosides and steroids were present in moderate amounts and there was abundance of tannins. The extract had similar effect on both S. aureus and E. coli cultures but activity was very low with B. subtilis. When S. aureus activity increased with time of storage up to 48 hours, thereafter the activity started reducing. However, the activity of E. coli continued to increase with time （within the study period）. Thus, it appears reasonable to store the extract for at least 48 hours before the use for enhanced activity.

Development and validation of an analytical method for detecting chlorantraniliprole residues in fresh tea leaves

An efficient method using multiwalled carbon nanotubes(MWCNTs)as dispersive solid-phase extraction sorbent was established for determining chlorantraniliprole residues in fresh tea leaves,which are known to be a troublesome matrix containing abundant pigments,via gas chromatography with an electron capture detector.Acetonitrile was used as the extraction solvent,with sodium chloride enhancing the analyte partition in the organic phase.The optimal mixture of MWCNTs and primary secondary amine(PSA)was based on the distribution of the target analyte recovery and on the clean-up efficiency;while matrix-matched calibration was recommended to combat the matrix effect.Mean recoveries of 95.2%–108.8%were obtained with intraday and interday precisions of less than 7.9%and 10.3%,respectively.Good linearity was observed for concentrations of 0.02–1.0 mg/kg with a correlation coefficient of 0.9984.The limits of detection and quantification were 0.005 mg/kg and 0.02 mg/kg,respectively.The method was employed to investigate the dissipation dynamics of chlorantraniliprole in fresh tea leaves with real field samples.Consequently,the dissipation rates of chlorantraniliprole in fresh tea leaves followed pseudo-first-order kinetics with a half-life of 1.9 d,and the average chlorantraniliprole residue content was below 0.02 mg/kg with a harvest withholding period of 14 d.

Determination of 18 Kinds of Amino Acids in Fresh Tea Leaves by HPLC Coupled with Pre-column Derivatization

A rapid and accurate quantitative method of high performance liquid chromatography( HPLC) with fluorescence detector has been developed for the analysis of 18 kinds of amino acids in fresh tea leaves. The samples were minced and mixed,and extracted with ultra pure water at 90℃ for 20 min. The 6-aminoquinolyl N-hydroxy-succinimidyl carbamate( AQC) was used as pre-column derivatization reagent. Gradient HPLC separation was performed on a C_(18) column( Symmetry C_(18),3. 9 mm × 15 cm,4 μm). Good linearity between concentrations and peak areas was achieved in the concentration range of 5. 0-250 μmol/L for 18 kinds of amino acids. The method was validated by the analysis of five replicates. The 18 kinds of amino acid standards were spiked in fresh tea leaf samples and the average recovery rate was 86. 25%-109. 05% with relative standard deviations( n = 5) ranging from 6. 03% to 10. 56%. The limit of detection( LOD) for the analytes was0. 05-1. 27 μmol/L. The method was successfully applied to the analysis of the 18 kinds of amino acids in fresh tea leaves from east Dongting and west Dongting mountains in Suzhou. The results indicate that the method is simple,rapid,precise and reliable.

Seasonal changes of bioelements in litter and their potential return to green leaves in five species of tropical dry deciduous forest, western India

The Litter nutrient concentrations of N, P, Ca, Mg, K and Na in mature leaves, twigs and reproductive parts and their relationship between senescent and young leaves were investigated in five forest species： Acacia nilotica, Acacia leucophloea. Tectona grandis, Miliusa tomentosa and Butea monosperma in Indian tropical dry deciduous forest in Western India.. Total dry matter of plant species was recorded and analyzed for N, P, Ca, Mg, K and Na. A. nilotica had the highest concentrations of N in leaf, while ,4. leucophloea had the highest concentrations of Ca and Mg in leaf. The highest concentrations of P in leaf were found in A. nilotica, A. leucophloea and B. monosperma where as lowest in T. grandis and M. tomentosa. No significant differences in K and Na were registered among the species. A marked seasonal variability was ob- served in the concentrations of N, P and K, except for Ca and Mg. Potas- sium is the single element that undergoes leaching and mobilization in all species. Resorped N and P can be used for the production of fresh leaf in the following annual cycle. Nutrient resorption and retranslocation from senescent leaves and litter supports the production of new foliage and increase the fertility of soil.

Real-time monitoring of optimum timing for harvesting fresh tea leaves based on machine vision

The harvesting time of fresh tea leaves has a significant impact on product yield and quality.The aim of this study was to propose a method for real-time monitoring of the optimum harvesting time for picking fresh tea leaves based on machine vision.Firstly,the shapes of fresh tea leaves were distinguished from RGB images of the tea-tree canopy after graying with the improved B-G algorithm,filtering with a median filter algorithm,binary processing with the Otsu algorithm,and noise reduction and edge smoothing using open and close operations.Then the leaf characteristics,such as leaf area index,average length,and leaf identification index,were calculated.Based on these,the Bayesian discriminant principle and method were used to construct a discriminant model for fresh tea-leaf collection status.When this method was applied to a RGB tea-tree canopy image acquired at 45°shooting angle,the fresh tea-leaf recognition rate was 90.3%,and the accuracy for fresh tea-leaf harvesting status was 98%by cross validation.Hence,this method provides the basic conditions for future tea-plantation operation and management using information technology,automation,and intelligent systems.