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The bread, which is consumed in small or large quantities in all countries, is the most essential food for people, and it is the most consumed floury products. Being one of the largest cities of Turkey, Adana province is used to determine the major socio-economic characteristics of households, bread consumption, and amount of bread waste and their reasons in urban areas. According to the survey results, the number of the daily purchased bread loaves is 4.65 per household, whereas the consumed amount is 4.45 loaves on average. As income level of household increases, the amount of bread consumption decreases as it is expected. This proves that bread consumption is higher in households with low-income level compared to in those with high-income level. The rate of daily bread waste in the analyzed households is averagely 9.63%. It is determined that this rate is maximum in the highest group of income and minimum in the lowest group of income.
In the past 100 years, the annual global temperature has increased by almost 0.5ºC and is expected to increase further with time. This increase in temperature negatively affects the management of water resources globally as well as locally. Rain is an important phenomenon for agriculture, particularly in hilly areas where there is no feasible irrigation system. The present study is concerned with the analysis and modeling of the rain pattern, its variability, and prediction of monthly number of rainy days for the Abbottabad District, which is considered to be one of the greenest and most beautiful areas of Khyber Pakhtunkhwa, Pakistan, by incorporating both parametric and nonparametric techniques. Non-parametric statistical techniques are used for movement detection and significance testing; in this context, statistical tests were incorporated for inspection of homogeneity of rainy days among successive periods. A time series data for the period 1971-2013 was analyzed. Box Jenkins methodology and time series decomposition were applied for fitting the selected model, which was assessed for forecasting the monthly number of rainy days for 2015-2020. In this study several time series parametric and non-parametric approaches were applied to model rainfall data. The results showed that SARIMA (1, 0, 1) (0, 1, 1) was a better choice in predicting the monthly number of rainy days. Further analysis of the data suggests that January, March, May, July, and December have a considerable declining tendency in the number of rainy days.
The purpose of the present study was to scrutinize the effect of glyphosate and atrazine (herbicide) on blood biochemical and hematological parameters of common carp, (Cyprinus carpio), including plasma glucose (RBS), cholesterol (CH), serum protein (SP), creatinine phosphates (CPK), lactate dehydrogenase (LDH), WBC, hemoglobin (Hb), platelets (PT), lymphocytes (LP), monocytes (MT), esinophils (EN), and neutrophils (NT), and on behavioral aspects for (24, 48, 72, 96) hours under doses of (0.1, 0.07, 0.05, 0.02) and (0.2, 0.15, 0.1, 0.05)mlL-1 respectively of glyphosate and atrazine. For analysis of biochemical and hematological parameters, the protocol of biochemical analyzer set (Merck Micro Lab 300 biochemistry analyzer) and hematological analyzer (Mindray BC-2300 Hematology Analyzer) was followed in the laboratory. An upturn in RBS, CH, and WBC concentration was observed while SP, LDH, LT, MT, and EP concentrations were decreased against both herbicides. CPK and Hb concentrations were increased against atrazine, while against glyphosate the concentrations were decreased. PT and NT showed momentous upturn in concentrations against glyphosate, while showing a decline against atrazine. Both herbicides affected the blood biochemical and hematological parameters of the selected fish. Behaviorally, changes were observed against both herbicides, including loss of equilibrium, increase in the frequency of opercular movements, fast swimming and jumping, losing balance, becoming exhausted and lethargic, vertical swimming, and bleeding at the base of the eyeballs.
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