Abstract: Smart farming has an increasingly urgent demand for high-precision and real-time monitoring in smart agriculture. Among them, micro-nano sensing can also provide advanced technical support to the information acquisition in smart planting, due to its high specificity, high precision, and rapid response. However, it is relatively scarce in nano-sensing under intelligent agricultural scenarios. This study aims to systematically review the research progress and application of the nano sensors in smart planting. The practical application scenarios were also given on the cutting-edge progress of the nano-sensors in intelligent planting. Existing problems and challenges were then proposed to determine future research directions. Three major aspects are included as follows. Firstly, the advanced nanomaterials were applied to the nano sensors, including the carbon nanomaterials, metal oxide semiconductor nanomaterials, quantum dots, and biological nanomaterials. A comparison was then made of their advantages. Secondly, there were the sensing principles, working mechanisms, and performances of the key nano-sensing technologies, such as the electrochemical sensing, fluorescence resonance energy transfer (FRET), and surface-enhanced Raman scattering (SERS). Thirdly, the cutting-edge applications of the nano sensors were also focused on the key smart planting areas, such as soil quality monitoring, crop nutrient detection, plant hormone analysis, and disease monitoring. Agricultural nano sensors also served as the data acquisition tool in the various fields of smart agriculture, thus facilitating the real-time collection of agricultural data in the intelligent management of production resources. The high-precision data was required for new opportunities in the nano sensor technology, with the rapid development of smart agriculture. These sensors shared the broad prospects in the large-scale agricultural applications, due to their high precision, low cost, low power consumption, and ease of integration. Some challenges of the micro-nano sensors were also given on the robustness, stability, and safety for the large-scale practical applications, such as the complex environment of farmland. Four aspects should be emphasized to promote the nano sensors in smart agriculture: (1) To improve the selectivity, long-term stability, and reliability of the sensors, such as four solutions: advanced nano-selective coatings to block the penetration of interfering ions; novel wearable sensing with biomimetic adhesion; ultra-stable nanomaterials with excellent anti-interference; as well as the material and device encapsulation protection. (2) Multi-modal sensor arrays were integrated into the multi-parameter synchronous monitoring in agricultural environments. The decoupling strategies were required, including time-resolved stimulus-response mechanisms and spatially isolated sensor unit designs, in order to effectively mitigate the cross-interference between heterogeneous biological signals; (3) Artificial intelligence was empowered the advanced sensors in two aspects: Specifically, the highly sensitive sensing materials were utilized for the perception target, in order to automatically predict, screen, and optimize advanced sensing materials, thereby accelerating the research and development of new sensing materials; Artificial intelligence chips were integrated with the micro-nano sensors. The precise data was combined to obtain by sensors with artificial intelligence-driven, real-time cleaning, processing, analysis, and decision-making of the massive sensing data at the sensing end, thus promoting the transformation of the smart planting from passive response to active prediction and early warning; (4) To construct a universal and standardized sensor interface protocol and efficient communication standards in precise and stable integration of the nano-sensors with various agricultural equipment, thereby achieving the rapid and accurate data interaction in agricultural systems. Looking ahead, cutting-edge technologies can be expected to be integrated into the nano-technology-driven sensors, such as quantum computing, 5G communication, cloud computing, big data, and artificial intelligence, with the micro-nano sensing in smart agriculture. There was a driving variation in the various aspects of agricultural production and operation. The finding can also provide useful references to promote the nano-sensors in smart agriculture.