# The Impact of 6G-IoT Technologies on the Development of Agriculture 5.0: A Review
## 4 The Future of Farming: 6G-IoT Applications in Agriculture 5.0
### Enhancing Sensing Accuracy and Reliability  
A plethora of smart agricultural applications are currently presented in the relevant scientific literature, including smart irrigation systems [99], crop and weather monitoring [100; 101], livestock management [102], UAV-based field monitoring, and greenhouse automation [103; 104]. Nevertheless, the effectiveness of these applications is limited, as they typically employ a relatively small number of wireless sensors to collect environmental data such as air temperature, relative humidity, and soil moisture. With the advent of 6G-IoT wireless communications, however, there is the potential for significant improvements in the effectiveness and efficiency of these applications. 6G-IoT will allow for the connection of a vast number of sensors to a single cell tower (i.e., umMTC), enabling farmers to install more sensors and receive more accurate and detailed information even on a plant-by-plant basis [105; 106].  
Additionally, the utilization of quantum sensing technology can contribute significantly to this objective. Quantum sensors, relying on highly sensitive quantum systems, offer greater sensitivity compared to conventional sensors. Thus, two recent research studies [107; 108] propose the use of quantum sensors for the precise measurement of photosynthetically active radiation (PAR), which is regarded as one of the most important environmental metrics required to evaluate plant photosynthesis. Furthermore, in [109], the authors employed devices equipped with multiple quantum sensors in order to precisely measure PAR as part of a cost-effective UAV-based thermal system to generate predicted maps of leaf water potential (LWP). Moreover, quantum sensors can be employed  
Figure 5: Applications of 6G-IoT in Agriculture 5.0.  
to accurately measure pH levels and ions, enabling the precise assessment of essential nutrients such as nitrogen, phosphorus, and potassium, which facilitates the implementation of precise fertilization strategies. Additionally, the deployment of multiple quantum sensors in a network allows for the utilization of inter-sensor correlations, further enhancing the overall sensing capabilities of the system [110]. Moreover, [111] investigates the use of quantum dots, which are typically nanoscale semiconductor particles or structures with unique quantum mechanical properties due to their size, for the production of nanobiosensors that are able to detect distinct targets in plants, such as pathogens, nutrients, and pesticides.  
Using blockchain technology, all sensor measurements can be recorded on a tamper-resistant, decentralized ledger, enabling secure, transparent, and reliable record-keeping [112]. The collected data can then be analyzed using AI-based technologies such as machine learning algorithms, which can efficiently process and analyze the data to extract valuable insights, patterns, and trends. By employing quantum sensing and computing, blockchain, and AI, farmers will be able to acquire more precise and comprehensive data, thereby enhancing the effectiveness and productivity of smart agriculture.