Agritech - Precision Farming

Quiz

Precision farming refers to using resources such as water, fertilizers, and pesticides precisely at the right time at the right location. Precision farming helps farmers increase their productivity, minimizing environmental damage, and improving crop quality.

Precision Farming vs Traditional Farming

Traditional farming is based on farmer's observation, experience, intuition, and manual labor. In traditional farming, decisions like when to plant, irrigate, and harvest depend on the understanding and observation of farmers.

Precision farming makes use of modern technologies and a data-driven decision-making approach. In precision farming, data collected from various technologies like IoT, drones, satellites, and big data is used to predict weather patterns and monitor crop and soil health. Here is a detailed difference between precision farming and traditional farming mentioned below in tabulated form.

	Precision Farming	Traditional Farming
Field Management	Precision farming uses technology and data to treat only the required area of the field.	In the traditional farming method, the entire field is uniformly treated. For example, the pesticide is sprayed over the entire field rather than spraying only the required area of the field.
Resource Usage	Input resources like water, fertilizers, and pesticides are applied precisely using Variable Rate Technology (VRT).	Resources are used uniformly on the entire field. This leads to wastage and overuse of resources.
Human Intervention	Precision farming makes use of robotics and automation to reduce the need for manual labor eliminating labor shortage.	Traditional farming is completely dependent on manual labor. Manual labors are needed from planting to harvesting, leading to labor shortage and decreasing the efficiency.
Technology & Tools	Precision farming is heavily dependent on various advanced technologies like IoT, GPS, drones, sensors, and many more.	In traditional farming, there is a very limited use of technology as it mostly relies on manual methods.
Data Collection	Technologies like sensors, cameras, drones, and satellites are used for real-time data collection.	Farmers use their observation and experience.
Impact on Environment	It precisely uses resources, reducing resource wastage and optimal use of chemicals.	There is higher usage of resources and chemicals having high impact on environment.

Technologies Used in Precision Farming

IoT Sensors: IoT sensors are used to monitor soil health, moisture content, and nutrient levels.
Drones: Drones are equipped with cameras and sensors to capture high-resolution images of crops for early detection of any disease. It is also used for applying fertilizers and spraying insecticides and pesticides.
AI and Machine Learning: It is used to analyze datasets to give predictive insights on pest outbreaks, planting time of crops, and many more.
Robotics: Robotics eliminates the shortage of manual labor. Robotic harvesters and weeders can be used for harvesting and weeding.
Autonomous Machines: Autonomous machines using GPS and sensors can be used to automate agricultural tasks without human intervention. For example, autonomous tractors can be used for plowing, planting, harvesting, and fertilizing.
Blockchain: Blockchain is used to track each step from planting till it reaches the store. It helps consumers to verify the authenticity of the product.
Cloud Computing: Cloud platforms store data gathered from various technologies like IoT sensors, drones, and satellite images. This stored data can be analyzed and accessed by farmers in real-time.
Variable Rate Technology: Variable Rate Technology (VRT) allows farmers to apply input resources such as water, fertilizers, and pesticides according to the need in different sections of the farm rather than uniformly applying across the entire field.

Data Collection Methods

Big Data: Big data are the data, which is generated by various technologies such as sensors, drones and satellites. These data are helps in crop Management, predicting weather patterns, and about market conditions.
Satellite Remote Monitoring: Satellite collects images of entire field which helps in getting information of soil moisture, and weather conditions. It helps in tracking growth pattern of the crops, and provide accurate climate data.
IoT Sensors: It collects real time data on soil moisture content, temperature, humidity, and nutrient levels. Sensors are placed in the entire field which helps farmers in real-time soil monitoring and adjusting irrigation and fertilization schedules.
Weather Stations: Weather stations collect weather data like temperature, humidity, and precipitation, in real-time. It helps farmers in planning schedules of planting, irrigation, and harvesting crops.

Applications of Precision Farming

Soil Health Management: IoT sensors placed in the fields can give data on soil nutritional value. Using this data farmers can precisely apply fertilizers to improve the fertility of soil without using excess chemicals.
Crop Monitoring: Precision farming makes use of technologies such as drones, satellites, and sensors to monitor crops for any signs of diseases. It can use a targeted approach if signs of stress, nutritional deficiency, or any disease are found.
Pest and Weed Control: Precision farming makes use of drones equipped with cameras and sensors to identify pests and weeds and use herbicides and pesticides to only the required area of the farm.
Yield Prediction: The tools and technologies used in precision farming help in predicting crop yield by analyzing past crop data, soil conditions, and weather patterns.
Efficient Resource Usage: Precision farming technologies give insights into soil moisture content and soil nutritional value, which allows farmers to use the required amount of water or fertilizers precisely wherever needed. This helps in reducing chemical use and preventing wastage of resources saving input costs.

Limitations of Precision Farming

Higher Initial Cost: The cost of tools and technologies needed for precision farming can be high for small-scale farmers.
Lack of Technical Skills: Lack of technical Knowledge required for operating tools and utilizing the data generated by various technologies like satellites can be a barrier.
Connectivity Issues: Precision farming is completely dependent on internet connectivity for collecting real-time data which rural areas may lack.
Data Privacy Concerns: Farmers may not be ready to share their farm data with third parties due to the risk of data breaches.

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