A comparative study of remote sensing classification methods for monitoring and assessing desert vegetation using a UAV-based multispectral sensor.

Restoration programs require long-term monitoring and assessment of vegetation growth and productivity. Remote sensing technology is considered to be one of the most powerful technologies for assessing vegetation. However, several limitations have been observed with regard to the use of satellite imagery, especially in drylands, due to the special structure of desert plants. Therefore, this study was conducted in Kuwait's Al Abdali protected area, which is dominated by a Rhanterium epapposum community. This work aimed to determine whether Unmanned Aerial Vehicle (UAV) multispectral imagery could eliminate the challenges associated with satellite imagery by examining the vegetation indices and classification methods for very high multispectral resolution imagery using UAVs. The results showed that the transformed difference vegetation index (TDVI) performed better with arid shrubs and grasses than did the normalized difference vegetation index (NDVI). It was found that the NDVI underestimated the vegetation coverage, especially in locations with high vegetation coverage. It was also found that Support Vector Machine (SVM) and Maximum Likelihood (ML) classifiers demonstrated a higher accuracy, with a significant overall accuracy of 93% and a kappa coefficient of 0.89. Therefore, we concluded that SVM and ML are the best classifiers for assessing desert vegetation and the use of UAVs with multispectral sensors can eliminate some of the major limitations associated with satellite imagery, particularly when dealing with tiny plants such as native desert vegetation. We also believe that these methods are suitable for the purpose of assessing vegetation coverage to support revegetation and restoration programs.

Ice test in diagnosis of ocular myasthenia.

This observational, non-control, non equivalent pretest and post test descriptive study was carried out at Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh from June 2009 to December 2009 to compare the efficacy of ice test and repetitive nerve stimulation (RNS) in diagnosis of ocular myasthenia gravis. Ten patients with fluctuating ptosis (4 male and 6 female) who were suspected of having ocular myasthenia were included in the study. Male and female ratio in the study was 2:3. The mean age of the patients was 28.1 years. Positive response to pyridostigmine was taken as confirmation of ocular myasthenia. A piece of ice (2cm × 1cm) was placed over the upper eyelid for 2 minutes and the vertical eye lid fissure height was noted before and after the application of ice. Repetitive nerve stimulation was performed in the same subjects subsequently. Results of two tests were compared. Eight patients shows good (>2mm) elevation of eyelid with ice and three patients had abnormal RNS. In conclusion, ice test appears as more sensitive clinical test to detect ocular myasthenia than RNS test.

beta-Galactosidase and its significance in ripening mango fruit.

The fruit extracts of ripening cv. Harumanis mango contained a number of glycosidases and glycanases. Among the glycosidases, beta-D-galactosidase (EC 3.2.1.23) appeared to be the most significant. The enzyme activity increased in parallel with increase in tissue softness during ripening. Mango beta-galactosidase was fractionated into three isoforms, viz. beta-galactosidase I, II and III by a combination of chromatographic procedures on DEAE-Sepharose CL-6B, CM-Sepharose and Sephacryl S-200 columns. Apparent Km values for the respective beta-galactosidase isoforms for p-nitrophenyl beta-D-galactoside were 3.7, 3.3 and 2.7 mM, and their Vmax values were 209, 1024 and 62 nkat mg-1 protein. Optimum activity occurred at ca pH 3.2 for beta-galactosidase I and II, and pH 3.6 for beta-galactosidase III. Mango beta-galactosidase and its isoforms have galactanase activity, and the activity of the latter in the crude extracts generally increased during ripening. The close correlation between changes in beta-galactosidase activity, tissue softness, and increased pectin solubility and degradation suggests that beta-galactosidase might play an important role in cell wall pectin modification and softening of mango fruit during ripening.