Abstract: Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.
Abstract: The study was conducted to evaluate the efficiency of
Garlic and Chili combination solution on control of insect pests in
cabbage crop. The solution was sprayed at different intervals after
transplanting. The efficiency of Garlic and chili combination solution
on cabbage insect pests was measured. Results revealed that Garlic
and chili combination solution was the effectively reduced cabbage
insect pests. On other hand, the spray solution not only reduced the
number of days required for the cabbage growth but also greatly
enhanced the leaf number, head diameter, head weight, and quality of
cabbage. Garlic and chili combination solution have positive effects
on pests reduction and improve growth, yield and quality of cabbage
vegetable.
Abstract: The purpose of this research is to study of consumer
perception and understanding consumer buying behavior that related
between satisfied and factors affecting the purchasing. Methodology
can be classified between qualitative and quantitative approaches for
the qualitative research were interviews from middlemen who bought
organic vegetables, and middlemen related to production and
marketing system. A questionnaire was utilized as a tool to collect
data. Statistics utilized in this research included frequency,
percentage, mean, standard deviation, and multiple regression
analysis. The result show the reason to decision buying motives is
Fresh products of organic vegetables is the most significant factor on
individuals’ income, with a b of –.143, t = –2.470, the price of
organic vegetables is the most significant factor on individuals’
income, with a b of .176, t = 2.561, p value = .011. The results show
that most people with higher income think about the organic products
are expensive and have negative attitudes towards organic vegetable
as individuals with low and medium income level. Therefore,
household income had a significant influence on the purchasing
decision.
Abstract: Formaldehyde is the illegal chemical substance used
for food preservation in fish and vegetable. It can promote
carcinogenesis. Superoxide dismutases are the important
antioxidative enzymes that catalyze the dismutation of superoxide
anion into oxygen and hydrogen peroxide. The resultant level of
oxidative stress in formaldehyde-treated lymphocytes was
investigated. The formaldehyde concentrations of 0, 20, 40, 60, 80
and 120μmol/L were treated in human lymphocytes for 12 hours.
After 12 treated hours, the superoxide dismutase activity change was
measured in formaldehyde-treated lymphocytes. The results showed
that the formaldehyde concentrations of 60, 80 and 120μmol/L
significantly decreased superoxide dismutase activities in
lymphocytes (P < 0.05). The change of superoxide dismutase
activity in formaldehyde-treated lymphocytes may be the biomarker
for detect cellular injury, such as damage to DNA, due to
formaldehyde exposure.