The Study Of Climate Impact On Storage-preservation And Merchandise Sales

Storage of fresh agricultural products is highly sensitive to environmental factors. In suitable microclimate environment, preservation time of agricultural products can be extended to reduce the sales loss. Sales of drinks, sunscreen and other goods are affected by weather fluctuations. Development of warehousing and sales strategy according to the weather conditions has significance for improving the economic.The paper is based on analysis about the storage and preservation test data and the sales data of agricultural related goods in a supermarket, with the corresponding perennial ground observation data from meteorological offices and stations in Xuzhou, Hefei, Bengbu and Maanshan, apply the correlation analysis and significance test, study the effect of artificial microclimate factors on the supermarket storage and preservation method, and analysis about the correlation of climate factor and supermarket sales, to improve large supermarkets and logistics for goods quality and utilization rate of positions. This research mainly concluded the following results:(1) In this paper, storage and preservation experiment test were carried out for the rice and vegetable which are more sensitive for the climate factor. In bulk package and cooling storage methods, the rice storage experiment was carried out. Using the air conditioning, temperature low down to 15℃, relative humidity set to 75%, can significantly extend the storage time of rice. As for vegetable, fresh lettuce was apply in the experiment, the results showed that:lettuce storage time is three times under 0℃ as much as 5℃. Storage in appropriate low temperature and wrapped with plastic bag to reduce the transpiration, it is helpful to maintain the freshness and extension of shelf life.(2) Climate change has important impact on food sales. Correlation analysis was carried out about the climate factor on the food sales. There is a significant negative correlation between sales of frozen meat and monthly average temperature. The coefficient is -0.885, the fitting curve is:y=2669.2x2-34631x+113142, passed the significance test, α=0.01. Hot pot food sales showed a decline tendency from 2008 to 2012, presents by stores sales:Xuzhou> Hefei>Bengbu> Maanshan; by season, winter sales highest, fall second, minimum in summer, a negative correlation between the temperature and the sales trend of hot pot food. Hot pot food sales of up to 58970.58 RMB in January, sales slump to 1132.44 RMB in July.(3) Temperature changes and drinking water sales shows a positive correlation, Bengbu reach highest temperature in July, water also reached the highest sales of 135572.29 RMB, to study the monthly sales and monthly average temperature, the fitting curve is:y=-4266.42x2+57089x-83287, R=0.92, passed α=0.01. In terms of region, water sales in Hefei area is highest, Bengbu second, Maanshan lowest. For alcohol sales in 2012, the correlation coefficient in three cities monthly temperature all pass the significant test, Xuzhou -0.557, Bengbu -0.633, Hefei -0.878, showed that alcohol sales have significant negative correlation with the temperature. Bengbu and Hefei are through the significance test of 99%, Xuzhou through the test of significance of 95%. In the same year for beer, correlation coefficient of sales and monthly temperature in three cities are all through the significant test, Xuzhou 0.612, Bengbu 0.685 and Hefei 0.738, showed that beer sales have significant positive correlation with the temperature.(4) Sunscreen sales change and sunshine time shows the positive correlation tendency, coefficient of 0.877, reached to extremely significant level. There was no significant correlation between skin care goods sales and the relative humidity. Due to the commodity characteristic, sales of hands care goods is bigger than the lips care.(5) According to the correlation analysis for perennial average temperature and pesticide sales, the coefficient is 0.685, the significance test passed a=0.05, indicate that temperature has obvious positive correlation with pesticides sales, to study the monthly average temperature and the sales data, the fitting curve is y=-3883x2+49040x-61653, R=0.72, passed significance test of α=0.05. But no significant correlation between relative humidity and sales change. Sales which affected by temperature is greater than the relative humidity.