Grape cultivation method based on big data analysis

Abstract

The invention provides a grape cultivation method based on big data analysis. Grape planting information based on geographical positions is collected, and various grape planting schemes and managementscheme data are summarized and analyzed. The method specifically comprises the step that data such as planting time, maturity time, soil conditions, humidity, temperature, illumination and fertilizing time, and data such as finished product harvesting time, the grape sweetness and the taste are collected. The optimal management scheme is provided for planters through a large amount of data analysis; on the premise that the experience of the planters in grape cultivation is not mature, a grape cultivation suggestion scheme can be obtained by inputting geographical position data and the data such as soil, illumination, humidity and temperature, and suggestions in the aspects of grape variety selection and planting difficulty can be obtained.

Description

technical field

[0001] The invention relates to the field of fruit planting, in particular to a method for cultivating grapes based on big data analysis. Background technique

[0002] In recent years, the consumption level of consumers has been increasing, and the demand pattern for fruits has also gradually changed, especially for grapes. The growth cycle of grapes begins in spring when the temperature rises to about 10 degrees Celsius. New shoots germinate and the first leaves appear, and then branches begin to grow. In May and June, petal formation and flowering and fertilization are carried out at the end of this period, and berries are formed a few days after flowering; this is the first stage of fruit growth. During the growing period of the vines in July and August, the berries develop, followed by fruit ripening. The skins of the red grapes are colored, while the white grapes lose their green color; this is the beginning of the fruit ripening period. When the gra...

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