Smart Agriculture: How Precision Farming is Shaping Sustainable Practices
Climate change and a growing global population that demands more and more agricultural products are changing the rules of the game for the industry and forcing it to look for ways to adapt. This can be quite difficult at first glance because people cannot control the weather.
However, we have another superpower – technology. They transform the methods of conducting various human activities to which we are accustomed and change production, making it safer, more sustainable, and occasionally simplifying. Today, growers have access to remote crop monitoring, AI, GPS, and data analytics, opening up unprecedented opportunities to increase production and conserve nature.
Implementation of Technology for Efficient Farming
Precision farming involves the precise and rational allocation of resources, achieved through the use of technological innovations. For example, GPS technology provides accurate navigation and helps farmers better navigate their fields. Thanks to precise farm monitoring, crops receive the required amount of water, nutrients, and other resources, avoiding duplication in the same areas and reducing waste.
Soil sensors, drones, and satellites provide data in near real-time, providing comprehensive insights regarding plant health and the state of the environment. By implementing crop health monitoring, farmers can obtain reliable information conveniently to make effective decisions on managing agricultural land and resources.
Gel fertilizers are one such innovation that has shown promise in enhancing nutrient delivery to plants. These fertilizers provide a controlled release of nutrients, ensuring that plants receive what they need when they need it, thereby improving efficiency and reducing waste.
Data analytics is also a reliable tool for precision farming agriculture and is actively used by many agricultural enterprises to reduce costs and increase field productivity. Farm offices collect information about crop yields, livestock health, fertilizer application, soil mapping, and weather conditions. Big data analysis has many applications, one of which is determining the type of crop where and when to plant it.
Collecting and analyzing data from various sources is accessible and valuable for small farms. They also value making decisions based on reliable data. Water sensors, for example, can be used to plan future crops and operate this vital resource. It is instrumental in drought-prone areas.
Making Decisions Based on Data
A proactive approach to solving agricultural problems, including adaptation to climate change, not only improves field productivity but also brings us closer to a sustainable future. All this is possible thanks to using agricultural monitoring and its data to make decisions about various agricultural activities, management, and implemented practices.
As stated earlier, technology helps to get more yield and reduce waste. Data from various sources allows us to determine precisely what plants and soil need, when, and in what quantity. It is also crucial to improving supply chains. It can help to enhance logistics and help to reduce food waste.
Cloud computing technology, in combination with other innovations, can improve supply chain efficiency and reduce costs. Big agricultural data has already revolutionized the agri-food industry. Farmers can communicate information to other business participants and key stakeholders throughout the supply chain. Sharing vital information with all stakeholders has always been challenging. This way, everyone can prepare and respond on time to market activity changes.
Multispectral Satellite Imagery
Multispectral satellite imaging has been around for decades. However, the privilege of capturing, processing, and analyzing images from space in different wavelengths of light was available only to the military and aerospace industries.
In agriculture, this technology provides maps of information across the farmland. But that’s not all. It is applied to recognize issues with the crops and soil that are invisible to the naked eye.
The primary objective of multispectral imaging is to identify minor changes in crop or field health before they become visible so that farmers can take prompt action. Advanced technologies are required for in-depth analysis and active monitoring of farms to accomplish this. AI and machine learning technologies provide a range of valuable tools to develop algorithms for remote agriculture monitoring solutions for a specific area, crop, or issue.
Integrating Renewable Energy Sources
Integrating renewable energy technologies in farming presents a significant opportunity for determining mutually beneficial solutions and mechanisms for enhancing water supply, energy efficiency, food security, and sustainable agriculture in the face of climate change.
Due to fluctuating energy demand patterns, the energy sector must rapidly adopt renewable energy sources for agricultural irrigation. However, irrigation has water and energy security pressures, and the main technical barriers are access to affordable electricity and effective management of resources. Using renewable energy technologies with appropriate techniques can reduce the burden on the grid, lower energy and water demands, and cut irrigation costs.
Practicing Water Conservation
Irrigation uses a lot of water, and precision agriculture reduces costs. Smart irrigation systems, controlled by sensors, allow farmers to monitor soil moisture and deliver water to plants that need it, preventing excessive consumption. In dry regions, this technology is vital. Sensors and data analysis make it possible to manage such a valuable resource as water effectively.
Conclusion
Precision agriculture is a crucial component of smart agriculture, utilizing technology and renewable energy to make farming more productive and environmentally friendly. As the global population grows, adopting innovative agriculture practices is essential to feed the world without a threat to our planet.
