RESULTS: Numerical optimization showed that rice noodles prepared with SPI, 68.32 (g kg-1 of rice flour), MTG, 5.06 (g kg-1 of rice flour) and GDL, 5.0 (g kg-1 of rice flour) gave the best response variables; hardness (53.19 N), springiness (0.76), chewiness (20.28 J), tensile strength (60.35 kPa), and cooking time (5.15 min). The pH, sensory, and microstructure results showed that the optimized rice noodles had a more compact microstructure with fewer hollows, optimum pH for MTG action, and overall sensory panelists also showed the highest preference for the optimized formulation, compared to other samples selected from the numerical optimization and desirability tests.
CONCLUSION: Optimization of the levels of SPI, MTG, and GDL yielded quality noodles with improved textural, mechanical, sensory, and microstructural properties. This was partly due to the favourable pH value of the optimized noodles that provided the most suitable conditions for MTG crosslinking and balanced electrostatic interaction of proteins. © 2020 Society of Chemical Industry.
Materials and Methods: Institutional ethical clearance was obtained. A total of 206 patients who reported to the Department of Hematology for blood investigations were the participants in this study. Age, sex, place, weight, height, dental fluorosis, and skeletal complaints were noted down. Body mass index was calculated, and statistical analysis was performed.
Results: Dental fluorosis was present in 63.1% and absent in 36.9% of the samples reported. Skeletal fluorosis was present in 24.8% and was absent in 75.2%. A large number of the patients had knee pain and difficulty in bending. Chi-square test was used for statistical analysis. Skeletal fluorosis and age were compared and P value was 0.00 and was significant. Dental fluorosis and skeletal fluorosis were compared and P value was found to be 0.000 and significant.
Discussion and Conclusion: There is a need to take measures to prevent dental and skeletal fluorosis among the residents of Salem district. Calcium balance should be maintained, and fluoride intake should be minimized to reduce the symptoms. The government should provide water with low fluoride level for drinking and cooking. Once the symptoms develop, treatment largely remains symptomatic, using analgesics and physiotherapy.
Methods: Cross-sectional data from 62 developing countries were used to run several multivariate linear regressions. R2 was used to compare the powers of MPI with income-poverties (income poverty gaps [IPG] at 1.9 and 3.1 USD) in explaining LE.
Results: Adjusting for controls, both MPI (β =-0.245, P<0.001) and IPG at 3.1 USD (β=-0.135, P=0.044) significantly correlates with LE, but not IPG at 1.9 USD (β=-0.147, P=0.135). MPI explains 12.1% of the variation in LE compared to only 3.2% explained by IPG at 3.1 USD. The effect of MPI on LE is higher on female (β=-0.210, P<0.001) than male (β=-0.177, P<0.001). The relative influence of the deprivation indictors on LE ranks as follows (most to least): Asset ownership, drinking water, cooking fuel, flooring, child school attendance, years of schooling, nutrition, mortality, improved sanitation, and electricity.
Conclusion: Interventions to reduce poverty and improve LE should be guided by MPI, not income poverty indices. Such policies should be female-oriented and prioritized based on the relative influence of the various poverty deprivation indicators on LE.