## 1 Introduction  
In the field of high-throughput acquisition of crop phenotype information, synchronous acquisition of multi-source information (including visible light imaging, laser imaging, multispectral imaging, hyperspectral imaging, thermal imaging, etc.) has become an important trend [1, 2, 3]. By integrating multiple sensors to realize the synchronous acquisition of crop phenotype information, it can provide not only rich data for subsequent intelligent decision-making algorithms but also hardware support for multi-parameter acquisition and data registration in the fast mobile crop phenotype platform, improving the accuracy of agricultural production decisions [4, 5, 6, 7]. Time synchronization of multi-sensor systems has always been a research hotspot in aerospace, environmental monitoring, ocean observation, industrial automation, energy and transportation, and other fields [8; 9; 10; 11; 12; 13; 14; 15], among which the synchronization problem between each sensor is a challenging key issue. To address these challenges, the current multi-sensor relative time synchronization protocols mainly include the Network Time Protocol (NTP) and the Precision Time Protocol (PTP). The NTP technology is a protocol based on the User Datagram Protocol (UDP) and built on the application layer, realizing time synchronization through message interaction between multiple devices, with a synchronization time error ranging from 50 to 200 ms. The PTP can be built not only on the application layer but also between the Medium Access Control (MAC) and physical layers, enabling message interaction between multiple devices. Because it is at the bottom of the entire system, it is less affected by various interferences and instabilities of the system, so it can achieve higher-precision time synchronization, and the synchronization time error between the MAC and physical layers can reach the nanosecond level [16]. [PERSON] et al. achieved time synchronization between the timing center and the time receiving module in the transportation field based on the GPS satellite navigation system for timing and the Pulse Per Second (PPS) signal, with an error of less than 200 ns [17]. [PERSON] et al. realized high-precision time synchronization between 5G network and industrial equipment through intelligent PTP gateway (s-PTP gateway) in industrial IoT environment, which meets the synchronization requirements of Industry 4.0 and 5.0 application scenarios [18], [PERSON] et al. effectively improved the clock synchronization performance of IEEE 1588 PTP in industrial network asymmetric delay scenarios by modeling unknown delays and optimizing filtering algorithms, providing a reliable clock parameter tracking solution for wired, wireless, and multi-hop networks [19]. Although multi-sensor time synchronization issues have been extensively studied across various industries, there are few reported cases of PTP applications in the agricultural sector. Furthermore, research reports on multi-sensor time synchronization in fast-moving crop phenology monitoring systems are even scarcer. Existing fast-moving crop phenology platforms (such as UAVs) typically only carry a single detection sensor, such as a multispectral camera or an infrared thermal imaging camera [20; 21; 22; 23]. Some UAVs can carry two detection sensors simultaneously, but due to their high flight speeds (approximately 25 m/s) [24], without time synchronization technology, the data collection times of the two sensors are not synchronized, leading to significant differences in the samples collected by different sensors. This makes subsequent data processing and application extremely challenging, failing to adequately support the needs of smart agriculture and hindering its widespread adoption in agricultural production.