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Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management

机译：使用时间序列UAV图像评估水稻发展阶段进行可变灌溉管理

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Rice is one of the three major crops in the world and is the major crop in Asia. Climate change and water resource shortages may result in decreases in rice yields and possible food shortage crises. In this study, water-saving farming management was tested, and IOT field water level monitoring was used to regulate water inflow automatically. Plant height (PH) is an important phenotype to be used to determine difference in rice growth periods and yields using water-saving irrigation. An unmanned aerial vehicle (UAV) with an RGB camera captured sequential images of rice fields to estimate rice PH compared with PH measured on site for estimating rice growth stages. The test results, with two crop harvests in 2019, revealed that with adequate image calibration, the correlation coefficient between UAV-PH and field-PH was higher than 0.98, indicating that UAV images can accurately determine rice PH in the field and rice growth phase. The study demonstrated that water-saving farming is effective, decreasing water usage for the first and second crops of 2019 by 53.5% and 21.7%, respectively, without influencing the growth period and final yield. Coupled with an automated irrigation system, rice farming can be adaptive to water shortage situations.
机译：大米是世界上三大作物之一，是亚洲的主要作物。气候变化和水资源短缺可能导致水稻产量和可能的粮食短缺危机减少。在这项研究中，测试了节水养殖管理，而IOT现场水位监测用于自动调节水流量。植物高度（pH）是用于测量水稻生长期差异的重要表型，使用节水灌溉。无人驾驶飞行器（UAV）具有RGB摄像机的RGB相机捕获稻田的顺序图像，以估计水稻pH与在现场测量的pH值，以估计水稻生长阶段。测试结果，2019年有两种作物收获，揭示了通过足够的图像校准，无人pH-pH与田间-PH之间的相关系数高于0.98，表明UAV图像可以准确地确定现场和水稻生长阶段的水稻pH值。该研究表明，节水养殖是有效的，2019年第一和第二作物的水资料减少53.5％和21.7％，而不会影响生长期和最终产量。再加上自动灌溉系统，水稻农业可以自适应水资源短缺情况。

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