The rising population that is supposed to be almost 10 billion by 2050, the subsequent increased food demand, and the vulnerability of agriculture in the face of global climate changes pose new challenges to the agriculture industry. They prompt the agriculture industry to advance, moving forward and beyond the current horizons in the name of food security. Answering this call, researchers and scientists involved in the agriculture industry and related fields have achieved remarkable success in terms of technology and innovation, shaping the future of the agriculture industry into Agriculture 4.0 or digital agriculture. The terms were coined in parallel with Industry 4.0 and refer to the newest trends of the agriculture industry. With agriculture 4.0, the industry is rapidly becoming automated, and new technology and AI are slowly but gradually being introduced to the field. And new trends from all around the world related to digital agriculture promise to rewrite the agricultural landscape of the future.
Precision agriculture is at the nexus of digital agriculture. According to The International Society of Precision Agriculture, precision agriculture or exactness farming is “a management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” (1) It encompasses almost all facets of technology used in agriculture and highlights the need to use advanced technology to achieve the said ends. Precision agriculture helps to optimise available resources and augment yield, thereby addressing the sky-rocketing food demand. Leading research facilities in the world are exploring new avenues related to precision agriculture and it is safe to say that the future of agriculture and food safety is intrinsically linked with precision agriculture.
Sensors play a significant role in the IoT (Internet of Things) concept and have been used extensively in the field of agriculture. Research shows that wired and wireless sensors have been crucial to the agriculture industry in recent years. They are used to obtain plant, animal, and environmental data and they are vital to implementing IoT in agriculture. Some of the most important technologies include remote sensors and wireless sensor networks (2). In addition, soil and water sensors also have made their way into the agriculture industry and even family cultivators tend to think it reasonable to have sensors installed as they bring various advantages. For example, they gather data on the dampness of the soil, allowing users to make informed decisions based on precise and time-sensitive data rather than resorting to a foreordained timetable (3).
The agriculture industry is being rapidly automated and robots are used to increase efficiency and to decrease the time and resources spent. Developments in robotics and automation have proven to be versatile in the agriculture industry and serve a wide array of purposes, involved in multiple industry-related practises such as planting and harvesting, water supply, target spraying, weed and pest control, disease detection, pruning, etc (2). Some innovations are widely used by small farms and ranches while certain devices are used only in large-scale commercial farms. Some of the innovations most generally used by ranches include gathering mechanisation, independent farm haulers, and drones (2). Fixed robots are the most common in terms of industrial application; however, in the field of agriculture, mobile robots bring a larger benefit (2).
Artificial Intelligence (AI) and Machine Learning (ML), coupled with cloud computing and IoT, have been at the forefront of the implementation of agriculture 4.0. Particularly, ML has been extensively explored in this regard, with applications in manifold areas instrumental to the agriculture industry. For instance, ML algorithms can identify complex patterns, relationships, and trends in heterogeneous and multi-dimensional agricultural data, and thereby make predictions that enable informed and accurate agricultural decision making. Some commonly used ML algorithms in agriculture 4.0. are “random forest, SVMs, ANNs and various DL variants, including CNN’s for computer-vision applications. (2)”
A trend gaining popularity at the moment, indoor vertical farming is growing produce in a closed and controlled environment in a vertical setting. It is an ideal solution to the lack of space as it mounts growing shelves one above another vertically; in comparison to traditional farming, it does not require a lot of land area and flourishes in a restricted space. As a result, indoor vertical farming is most commonly associated with the city and urban farming. Further, most indoor vertical farms are aquatic or aerologic, meaning that plants are either grown in hydroponic environments or showered with water and supplements. Provided that they are closed farms, developed light is used instead of natural sunlight. Since it requires minimum natural conditions, indoor vertical farming is becoming more and more desirable in relatively hostile areas that are unfavourable for agriculture (2, 4).
“A minichromosome is an extremely small version of a chromosome, the thread-like linear or circular DNA and associated proteins that carry genes and functions in the transfer of genetic information (5).” Agricultural geneticists can add multiple traits to a plant through minichromosomes. The speciality of minichromosome technology is that it does not alter the genes of the plant in any manner, therefore attaining faster regulatory approval and acceptance by both farmers and consumers. In other words, it can add certain traits like drought resilience and nitrogen use to a plant without primarily altering its fundamental gene structure. This technology is poised to become a central aspect of the future of agriculture as the present temperature levels, soil conditions, unpredictable rainfall, resistant pests, etc that seem to be hostile to crop cultivation require modified crop varieties that can withstand them. Minichromosome technology emerges as the solution here, enabling scientists to conjure advanced crop varieties with multiple traits that address the said challenges.
It is staggering how much the agricultural industry has changed over the past decades. From traditional farms that relied on human labour and natural resources to digital farming that amalgamate various facets of technology, the agricultural industry has witnessed a drastic yet pivotal change. The newest trends in the industry are indeed promising and seem propitious in the face of perils entailed by accelerating climate change. What is noteworthy here is that these new trends do not occur in isolation; instead, they are often linked with each other and complement and benefit one another. Aided by these novel developments, it is evident that the agriculture industry will reach new heights soon.
Due to the country’s diverse climatic regions, Sri Lanka produces a wide variety of fruits, nuts, and vegetables. The manufacturing and exporting of more than 9000 tonnes of produce annually solidify Sri Lanka as a major exporter of fruits, nuts, and vegetables.