Jin Eon-Ju, Choi Myung-Suk, Lee Hyeok, Bae Eun-Ji, Kim Do-Hyun, Yoon Jun-Hyuck
Forest Biomaterials Research Center, National Institute of Forest Science, Jinju 52817, Republic of Korea.
Division of Forest Environmental Resources, Institute of Agriculture and Life Science, Gyeongsang National University, Jinju 52828, Republic of Korea.
Plants (Basel). 2024 Nov 21;13(23):3270. doi: 10.3390/plants13233270.
This study conducted a comparative analysis on the effects of smart automatic and semi-automatic irrigation methods on the physiological characteristics and growth of × Matsum. seedlings. The smart automatic irrigation system, which activates irrigation when the soil moisture drops below 15%, demonstrated superior characteristics in sap-wood area and bark ratio, as well as excellent water management efficiency, compared to the semi-automatic irrigation method, which involves watering (2.0 L) for 10 min at 60 min intervals starting at 8 AM every day. The analysis of soil moisture content changes under varying weather conditions and irrigation methods showed that smart automatic irrigation effectively maintained optimal moisture levels. Moreover, sap flow in the smart automatic irrigation treatment was more efficiently regulated in response to seasonal variations, showing a strong correlation with climatic factors such as temperature and solar radiation. In contrast, the semi-automatic irrigation treatment led to excessive sap flow during the summer due to a fixed watering schedule, resulting in unnecessary water supply. Analysis of photosynthesis parameters and chlorophyll fluorescence also revealed that smart automatic irrigation achieved higher values in light compensation and saturation points, maximizing photosynthetic efficiency. These findings suggest that the smart automatic irrigation system can enhance plant growth and water use efficiency, contributing to sustainable water management strategies. This research provides critical foundational data for developing efficient agricultural and horticultural irrigation management strategies in response to future climate change.
本研究对智能自动灌溉和半自动灌溉方法对×松苗生理特性和生长的影响进行了比较分析。智能自动灌溉系统在土壤湿度降至15%以下时启动灌溉，与半自动灌溉方法相比，在边材面积和树皮比率方面表现出优越特性，且水分管理效率极佳。半自动灌溉方法是每天上午8点开始，每隔60分钟浇水（2.0升）10分钟。对不同天气条件和灌溉方法下土壤水分含量变化的分析表明，智能自动灌溉有效地维持了最佳湿度水平。此外，智能自动灌溉处理中的液流在响应季节变化时得到更有效调节，与温度和太阳辐射等气候因素密切相关。相比之下，由于固定的浇水时间表，半自动灌溉处理在夏季导致液流过剩，造成不必要的供水。光合作用参数和叶绿素荧光分析还表明，智能自动灌溉在光补偿点和饱和点达到更高值，使光合效率最大化。这些发现表明，智能自动灌溉系统可促进植物生长和水分利用效率，有助于可持续的水分管理策略。本研究为制定应对未来气候变化的高效农业和园艺灌溉管理策略提供了关键基础数据。
