- Global population is expected to reach 9.7 billion by 2050, leading to a surge in global food demand.
- Precision farming uses sensors and analytics tools for gathering data and information.
- With robotics technology, the future need for manpower in agriculture can be reduced to a great extent.
- Drones can now collect raw data from the field, which provides valuable information for plant science research.
According to the United Nations, the world’s population is expected to increase by 2 billion in next 30 years. It will be around 9.7 billion in 2050 and could peak at nearly 11 billion around 2100. The ever-increasing population will increase global food demand, increasing the need for better ways to maximise grain yield.
The agriculture industry faces enormous challenges, from global warming to surging costs of inputs and the labour crisis. There is increasing recognition from agriculture businesses that solutions are needed for these challenges.
Precision farming refers to growing crops with the precise utilisation of inputs. This technology uses sensors and analytics tools for precise measurement and exploits a large amount of data and information. It results in maximum profits due to the reduced cost of production and increased level of output.
Remote sensing, geographic information, and the global positioning system are often used in precision agriculture. This enables farmers to maximise their benefits and reduce costs as compared to the traditional farming system.
An agricultural robot is a specialised technology that assists farmers in various field operations. Labour scarcity is one of the significant crop production issues, resulting in reduced yields. With robotics technology, the future need for manpower can be reduced to a great extent. Agricultural robots automate dull, repetitive, and slow tasks for farmers, enabling them to focus more on enhancing overall production yields.
Artificial intelligence in agriculture
Artificial intelligence (AI) has brought revolutions in many industries and will transform the agriculture sector for good. AI will improve the quality and quantity of crops and further will improve farmers' efficiencies.
Some of the major applications of AI in agriculture are:
- Providing predictive insights for the right time of sowing and weather conditions
- Prediction of crop yield and forecasting prices to maximise profit
- Identification of infected areas in the field and the precise spraying of chemicals
- Crop and soil monitoring for the amount of irrigation and fertilisers
- Classification of plant diseases
Drones in agriculture
Image source: © Ekkasit919 | Megapixl.com
Drones, also known as unmanned aerial vehicles (UAVs), can now collect raw data from the field, which provides valuable information for plant science research. It also helps in farm surveillance and monitoring. Drones with a camera can provide aerial imaging and the surveying of difficult fields to access. Similarly, drones with GPS technology are used for livestock farming, mainly tracking and monitoring grazing.
Some of the critical information obtained from drone images are:
- Counting of plant stand and plot statistics
- Plant height and density
- Plant phenology, leaf area and treatment efficacy
- Water requirements
Advancements in robotic systems in UK’s agriculture industry || Expert talk with Atif Syed