Precision farming

Precision farming is a method used by farmers to optimize inputs such as water and fertilizers to improve plant productivity. The method also includes minimizing pests and diseases in order to apply a particularly targeted and precise amount of pesticides. This means that you will deal with parts of your agricultural field in different ways and in appropriate ways because these different parts of the fields are different. The soil may be slightly different from the sun received by a particular part of the field. Perhaps they come from different slopes, so, large farmland or various farm across the region has many factors to take into account in specific plots in order to maximize ecological factors.

So what exactly is precision agriculture and what is the difference between it and traditional agriculture.

Everything about traditional agriculture actually comes from experience. Technology has also been improved. They made machines, they realized that if I planted, harvested, and fertilized more accurately, they could actually get more benefits from my fields and seconds. The poor location will affect the efficiency of farm productivity, while the desperate location is actually because it is actually just a driving force or another measure of productivity in agriculture.

Precision agriculture is an agricultural management concept based on observing and responding to entropy changes. It relies on new technologies such as satellite images. Global positioning system (GPS), Information technology (IT), and other geospatial tools. Let's try to understand this better. Suppose you have 20 hectares of land with a yield of 100 tons per hectare. Select the difference between the years of different parts of the same ground for the remote sensing image in your field. The area marked in red indicates the output of 20 mu, and the area marked in blue indicates the output of 100000 per hectare. The difference is 100 tons. In other words, not optimizing the output of 100 tons will lead to a loss of productivity.