Intelligent Monitoring and Precision Management of Tea Gardens Based on Sun-Induced Chlorophyll Fluorescence (SIF)

日光誘導葉綠素熒光（SIF）作為一種新興技術，在茶葉的葉綠素含量、氮監測和脅迫監測等方面具有潛在的應用價值。通過監測這些關鍵指標，可以更好地了解茶葉的生長狀況、品質和對環境脅迫的響應，從而為茶葉的精準管理提供支持。

Sun-induced chlorophyll fluorescence (SIF) is an emerging technology with potential applications in monitoring chlorophyll content, nitrogen status, and stress responses in tea plants. By tracking these key indicators, it is possible to gain deeper insights into the growth status, quality, and environmental adaptability of tea plants, thereby supporting precision management in tea production.

「茶葉葉綠素含量 / Chlorophyll Content in Tea Leaves」

日光誘導葉綠素熒光技術，可實現對葉綠素含量的快速無損監測，這對茶樹生長管理具有重要意義。

葉綠素是茶葉光合作用的關鍵色素，其含量直接影響光合效率，是其健康生長的基礎，與并茶樹長勢密切相關。

研究表明，適宜的遮陰處理可通過提高葉綠素含量改善茶葉品質，而SIF技術能精準量化這種品質關聯——通過追蹤熒光信號變化，可確定適合的遮陰時長與強度，確保葉綠素含量維持在利于氨基酸、可溶性糖積累的合理范圍。

SIF technology enables rapid, non-destructive monitoring of chlorophyll content, which is highly significant for the growth management of tea plants.

Chlorophyll is a key pigment in photosynthesis, and its content directly affects photosynthetic efficiency—fundamental to healthy growth—and is closely related to the vigor of tea plants.

Studies have shown that appropriate shading can improve tea quality by increasing chlorophyll content. SIF technology can accurately quantify this relationship: by tracking changes in fluorescence signals, the optimal shading duration and intensity can be determined to ensure chlorophyll levels remain within a range conducive to the accumulation of amino acids and soluble sugars.

不同種植條件影響茶葉的葉綠素含量，并影響其顏色、風味和香氣。

Different planting conditions affect the chlorophyll content in tea leaves, thereby influencing their color, flavor, and aroma.

「氮監測 / Nitrogen Monitoring 」

氮是茶葉生長必需的營養元素，對葉綠素合成和光合作用至關重要。傳統的氮肥管理依賴于經驗和土壤測試，難以實現精準施肥。SIF技術為茶葉的氮監測提供了一種新的途徑。

研究表明，SIF信號與植物的氮營養狀況密切相關。氮素充足時，植物光合作用旺盛，SIF信號較強；氮素不足時，光合作用受限，SIF信號減弱。SIF技術也有望于應用在茶葉種植上，通過分析SIF信號，判斷茶葉的氮營養狀況，從而指導施肥管理，提高茶葉產量和品質。

通過SIF信號反映的氮營養狀況，能夠精準調整氮肥用量，避免過量施肥造成的環境污染和資源浪費；同時，基于氮素需求的精準施肥可充分滿足茶樹生長所需，有效促進光合作用，進而提高茶葉產量；此外，適宜的氮營養還有助于提升葉綠素和氨基酸含量，顯著改善茶葉的整體品質。

Nitrogen is an essential nutrient for tea growth, playing a critical role in chlorophyll synthesis and photosynthesis. Traditional nitrogen management relies on experience and soil testing, making precise fertilization challenging. SIF technology offers a new approach to nitrogen monitoring in tea  farming.

Research indicates that SIF signals are closely correlated with the nitrogen status of plants. Under sufficient nitrogen supply, photosynthesis is vigorous, and SIF signals are strong; under nitrogen deficiency, photosynthesis is inhibited, and SIF signals weaken. SIF technology shows promise for application in tea production—by analyzing SIF signals, the nitrogen status of tea plants can be assessed, guiding fertilization management to improve yield and quality.

Using SIF-reflected nitrogen status, fertilizer application can be precisely adjusted to avoid environmental pollution and resource waste caused by over-fertilization. Meanwhile, precision fertilization based on nitrogen demand fully supports tea plant growth, effectively enhances photosynthesis, and thereby increases yield. Furthermore, optimal nitrogen nutrition helps elevate chlorophyll and amino acid content, significantly improving overall tea quality.

「茶葉脅迫監測 / Stress Monitoring in Tea Plants 」

茶葉在生長過程中會受到多種脅迫，如干旱、病蟲害等。這些脅迫會影響茶葉的光合作用和生長，降低產量和品質。SIF技術可以用于茶葉的脅迫監測。

研究表明，SIF對植物的生理變化敏感，可用于檢測棉花黃萎病等病害。因此，SIF也有望應用于茶葉病蟲害的早期診斷。

水分脅迫也會影響茶葉的生長。通過分析SIF對不同程度水分脅迫的響應，可以實現對茶葉水分狀況的監測。

Tea plants are subject to various stresses during growth, such as drought, pests, and diseases. These stressors can negatively impact photosynthesis and growth, reducing yield and quality. SIF technology can be applied to monitor stress in tea plants.

Studies demonstrate that SIF is sensitive to physiological changes in plants and can be used to detect diseases such as cotton Verticillium wilt. Therefore, SIF also holds potential for early diagnosis of pests and diseases in tea plants.

Water stress similarly affects tea plant growth. By analyzing the response of SIF to varying degrees of water stress, it is possible to monitor the water status of tea plants.

茶芽出現枯焦 / Tea buds appear scorched.

在實際應用中，SIF監測系統正變得越來越智能。

以愛博能開發的日光誘導葉綠素熒光(SIF)監測系統為例，該系統內置先進算法，能夠直接輸出葉綠素熒光產額和光合作用速率等關鍵參數，用戶無需再進行復雜的數據分析處理。系統提供塔臺在線式長期監測與無人機載機動巡測兩種型號，既可滿足茶園固定點的連續觀測需求，也能適應大范圍、多茶區的快速評估場景，為不同規模的茶園提供定制化解決方案。

日光誘導葉綠素熒光技術為茶葉生產提供了實時、無損且高效的監測新方式，覆蓋生長、營養與脅迫等多維度管理需求。隨著該技術不斷成熟與應用深化，它將在推動茶葉精準種植、提升茶葉品質與產業可持續發展方面發揮越來越重要的作用。

In practical applications, SIF monitoring systems are becoming increasingly intelligent.

For example, the SIF monitoring system developed by ExponentSci contains advanced algorithms that directly output key parameters such as chlorophyll fluorescence yield and photosynthetic rate, eliminating the need for users to perform complex data processing. The system offers two models: a tower-based online version for long-term monitoring and a drone-mounted mobile version for rapid large-scale assessments across multiple tea regions. This provides customized solutions for tea gardens of different scales.

SIF technology offers a real-time, non-destructive, and efficient monitoring method for tea production, addressing multidimensional management needs including growth, nutrition, and stress. As the technology continues to mature and find broader applications, it will play an increasingly important role in promoting precision tea  farming, improving tea quality, and supporting sustainable industry development.

案例來源 / Sources：

1. Ma, X., Liu, J., Li, H., Wang, W., Liu, L., Wang, P., Hu, J., Zhang, X., & Qu, F. (2024). Greenhouse covering **** promotes chlorophyll accumulation of tea plant (Camellia sinensis) by activating relevant gene expression and enzyme activity. BMC Plant Biology, 24(1).

2. XIANG, F., LI, W., LIU, H., ZHOU, L., & JIANG, C. (2018). Characteristics of Photosynthetic and Chlorophyll Fluorescence of Tea Varieties under Different Nitrogen Application Levels. In Acta Botanica Boreali-Occidentalia Sinica.

3. Wang, C., Wang, Z., Chen, L., Liu, W., Wang, X., Cao, Z., Zhao, J., Zou, M., Li, H., Yuan, W., & Wang, B. (2025). Intelligent Identification of Tea Plant Seedlings Under High-Temperature Conditions via YOLOv11-MEIP Model Based on Chlorophyll Fluorescence Imaging. Plants, 14(13), 1965.