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Five groundbreaking and exciting agritech trends to help global agriculture in 2021

Agriculture has changed drastically since the advent of human civilization. It has moved from a labor-intensive industry to one that makes smart and rational decisions. Many new technology trends prevail in agriculture in 2021.
 
 

1. IoT In Agriculture

- The use of IoT (Internet of Things) in smart agriculture is supported by various sensors inserted into the agricultural farm. The different sensors used are light, humidity, soil moisture, temperature, plant health monitoring, etc.

Some of the key use cases of IoT in agriculture are:

Collect data using farm sensors such as autonomous vehicles, wearables, cameras with buttons, robots, control systems, etc.

 Aerial and ground-based drones for irrigation, crop health assessment, spraying, monitoring and field analysis.

 Geolocation using wireless IoT sensors and livestock tracking to monitor livestock health care.

 Predictive analytics for precipitation, temperature, soil, humidity, etc.

 Innovative greenhouse with the support of IoT devices and displays, no human intervention required.

2. Geographic Information System (GIS) In Agriculture

- GIS is a technology that represents any geographical entity in spatial representation by hardware, software and data. Hardware is used in satellites, drones, GPS systems to locate data points and get information from them for analysis.

- In the agricultural field, farmers can use GIS to analyze complex spatial data such as rainfall, topography, soil elevation, slope, wind direction, flooding, erosion, etc.

Some great use cases of GIS in agriculture industry trends 2021 are:

 Mapping irrigated landscapes.

 Assess plant health.

 Analysis of irrigation modification.

 Land degradation assessment study.

 Repair erosion.

 Efficient drainage elevation pattern.

- GIS and its widespread usage have led to its other names - satellite farming or precision agriculture for all its wonders. Furthermore, with advances in GPS, robotics, and unnamed flying vehicles, various farming operations are now computerized.

3. AI / ML & Data Science in Agricultural Technology

- Artificial intelligence is the application of human intelligence through a machine body where instructions are fed into the machine. The entire life cycle of agriculture includes soil preparation, seeding, fertilizing, watering, weed protection, harvesting, and storage. - At every stage, growers or farmers need to rely on their own instincts, calculations, risks based on the right time and other factors. AI and ML can greatly contribute and benefit from their proven data analytics and predictions.

- All important agricultural data collected by IoT devices and ML algorithms are processed and streamed using data science. Farmers cannot use raw data, and thus data science is changing farmers' lives in making important decisions.

- Real-time use cases of AI/ML and data science in agriculture are:

 Productivity prediction and quality assessment.

 Predictive analysis of crop sustainability.

 Use ML to eliminate weeds by recognizing plant/crop species.

 Detect plant infections and diseases.

 Harvest and decide prices smart.

 Anti-waste and meet demand.

 Automatic robot for herding livestock.

4. Blockchain Technology

- Once the crops and products are ready, farmers dive into the hassle of fair trading, fair marketing and prove the authenticity of their products, helping farmers ensure the safety of their crops. products, prevent theft and fraud, effectively manage supply chains, and balance the food ecosystem.

The real-time use cases of agricultural blockchain technology are:

 Food traceability.

 Transparency in the food supply chain.

 Agricultural insurance for farmers.

 E-commerce for the agricultural industry.

 Agricultural subsidies.

5. Automation

- Robots have evolved tremendously and we are not surprised that machines do the agricultural work. It helps in farm automation, aka smart farming, by reducing the workload on human resources.

- Therefore, it is necessary to meet the needs of the growing population by producing agricultural products with less human intervention and faster. Drones, custom tractors, watering engines, harvesters and more modern technologies for agricultural automation.

- The use cases of automation in agricultural technology are:

 Agrobot is a real-time example of strawberry harvesting, accessible from a mobile platform, by meeting farmer standards.

 Harvest apples with Abundant Robotics' vacuum cleaner.

 The automatic tractor is pre-programmed to perform driverless control.

 Use computer vision to sow seeds and sprinkle pesticides as needed.

Origin: bacancytechnology