DIGITALISATION IN FARMING
Introduction to digital farming:
Digital farming can be defined as the use of technology by farmers to integrate financial and field-level records for complete farm activity management.
“Digital Farming is the consistent application of the methods of precision agriculture and smart farming, internal and external networking of the farm and use of web-based data platforms together with Big Data”
Data from each plot can be analyzed to provide information on soil, weather, and crop growth patterns to give actionable geographically relevant timely insights to prevent losses and optimize the productivity of each plot on the farm.
Farmers can even get their queries solved and manage the supply chain directly through applications on their phones. Through pre-harvest and post-harvest management of farms, digital farming aims to take over all the aspects of farming from farm to fork.
Digitalization of farm data for actionable insights:
Digital farming gives farmers access to timely valuable insights so that they can adopt best practices and manage farms more efficiently thus reducing losses and maximizing profits. Technologies offer a variety of solutions for adapting to advanced farming. IoT in agriculture consists of sensors, drones, and computer imaging integrated with analytical tools for generating actionable insights. Placement of physical equipment on the farms, monitors and records data which is used to get insights. Due to advancements in satellite imagery, machine learning, and data storage in clouds, predictive analytics software has been pretty favorable as they are highly scalable and easy to use.
Technologies used in Digital Farming:
Digital Farming is the integration of precision farming and smart farming and is achieved through the implementation of intelligent software and hardware.
Precision farming is popularly defined as a technology-enabled approach to farming management that observes, measures, and analyzes the needs of individual fields and crops. Smart farming is more focused on the use of data acquired through various sources (historical, geographical, and instrumental) in the management of the activities of the farm.
Digital Farming can be done through the installation of network-connected ‘smart’ devices as part of IoT (Internet of Things) or they can be software as a service (SaaS) based agtech.
When hardware transfers data over a network, they become ‘smart devices’ and become part of the Internet of Things (IoT). IoT in agriculture comprises the use of sensors, drones, robots, and cameras. Sensors, cameras, and robots are installed on the farms and record the data.
Drones in agriculture can be used as pay per services or can be bought and stationed on farms. The IoT equipment needs to be connected to an analytical dashboard for the analysis of data. IoTs are used for field-related data only. They can’t help manage the overall farm activities and show the data in terms of financial gains or losses. They are just data.
Benefits of Digital Farming:
Benefits of a digital agriculture solution for a food processing industry
Incorporates end-to-end solutions from farm-to-fork
Higher yields as inputs are optimized and constantly monitored
Better quality due to compliance with food standards and nutrition tracking
Less waste due to customized practices accounting for the precise application of resources and thus reducing production costs
Supply chain management from farm to fork.
Challenges of Digital Farming
High cost of adoption
Many digital farming technologies can be expensive, which may be a barrier.
Limited access to technology
In some cases, access to digital farming technologies may be limited, particularly in developing countries or rural areas with limited infrastructure.
Training and knowledge
There may also be a learning curve associated with using digital farming technologies, and farmers may need to be trained in order to use them effectively.
DIGITALISING RURAL FARMS
Digital technologies have the potential to revolutionise agriculture by helping farmers work more precisely, efficiently and sustainably. Data-driven insights can improve decision-making and practices and help increase environmental performance while making the job more attractive to younger generations. Digital technologies also have the potential to offer consumers greater transparency as to how their food is produced. They offer opportunities to renew business models in value chains by connecting producers and consumers in innovative ways. Beyond farming, digital technologies are key to make rural communities more attractive, smart and sustainable, reducing problems related to remoteness and improving access to services.
Agriculture Digitalisation is hindered by resource allocation and technology decisions, these remain rather "at an average level" where management, consumer sales and risk management efficiencies are still limited by a lack of precise information. Climatic variables – sometimes a blessing, and other times a curse – mean that a good farm manager, even after making the best decisions, may run into the same problems as a bad one when both face climate adversities such as drought or excessive rain.
How then to reap the benefits of efficient management as we have with technological progress?
In this context, digital agriculture appears to be a promising alternative to meeting the need of gains in management efficiency, allowing the correct allocation of resources and ensuring the development of people working in the fields. As in other industries, digital transformation has made great strides in agriculture, sowing the seeds of what is now known as Agriculture 4.0, Digital Farming or Smart Agriculture.
In practical terms, this signifies an increase in data collection by way of the internet of things, i.e. sensors, machines and drones gathering real-time information that is then stored and processed in the cloud. Thanks to the detailed control of inputs, this allows efficiency gains like labour cost reductions, observing and preparing for climatic conditions that interfere with production processes, monitoring the spread of pests and diseases and so on. Additionally, predictive models supported by big data and artificial intelligence will enable forecasts of pest and disease outbreaks, recommendations for better seed placement in fields and selection of the best plant varieties as well as determining the best time to bring products to the market.
"Global Digitalisation is allowing customisable solutions and, in some cases, a spur in innovations otherwise not possible due to lack of data"
In this context, the digitalisation of agriculture has become a turning point for the world to develop its capabilities, even considering the existing scarcity of resources, and within areas of small-scale farming. This is an example of the “Farming as a Service” model that provides technological solutions designed for agriculture, converting fixed costs into variable costs when charging for the utilisation of services such as data collection by sensors and machinery rental.
There are three key issues to be considered when developing digital agriculture:
As the agribusiness production chain grows more complex, its users are becoming more specialised
Because of this increasing specialisation, farmers do not always have an integrated solution where all the technology and innovations are compatible with each other.
How to deal with technologies developed in “silos”?
There are other related issues as well.
How can we enhance the co-operation between the various agricultural players and solution providers?
How to reconcile the economic, technical and regulatory interests of start-ups, businesses and the government?
Agriculture Digitalisation is bringing new services through a better understanding of individual farmers’ circumstances
Digitalisation will allow customisable solutions and, in some cases, spur innovation otherwise not possible due to lack of data. For instance, agricultural insurance and/or a farmer financing business could use a digital agriculture database to find the best managers and, consequently, make offers to the most suitable candidates. Oddly enough, the risk management tools tend to look for those that achieve the best risk management; it will be no different from agriculture digitalisation. Are we ready to deal with such actions, seen as market segmentation on one hand but considered discriminatory on the other?
Get more facts and compare your country on the OECD Agriculture Data Portal
We have to deal with increasing global worries around data privacy and cybersecurity
However, the level of pressure brought about by digital agriculture is quite another story. In the worst-case scenario, it might become a state issue if the loss, misuse or theft of data could influence or jeopardise a government’s capacity to feed its population. It also involves the possible use of inside information in order to benefit from the agricultural commodities market, among others. The key issue here will be how to set control and governance levels on the use of this information.
FPI believes digital technologies have the potential to revolutionise agriculture by helping farmers work more precisely, efficiently and sustainably. Data-driven insights can improve decision-making and practices and help increase environmental performance while making the job more attractive to younger generations. Digital technologies also have the potential to offer consumers greater transparency as to how their food is produced. They offer opportunities to renew business models in value chains by connecting producers and consumers in innovative ways. Beyond farming, digital technologies are key in making rural communities more attractive, smart and sustainable, reducing problems related to remoteness and improving access to services.and a stunning pic to engage your audience and get them to click.
FPI takes research and innovation as vital and important tools to facilitate and accelerate digital transformation in agriculture and rural areas for the benefit of global citizens and businesses. FPI wants to be active in undertaking R&I activities laying the ground for digitalised and data-empowered agriculture, especially in rural areas. Strategic interventions support the uptake of digital technologies, and should increase R&I investments to develop new digital solutions and the crucial assessment of the socio-economic impacts of digitalisation.
For this project to have an impact, FPI shall carry out the following:
1. Research and innovation to develop new technologies and business models
2. Improving the uptake of new technologies in agriculture and rural areas
3. Analysing & managing the impact of digitisation in agriculture and rural areas