植物“荧光”：比肉眼更懂植物健康

Plant "Fluorescence": Understanding Plant Health Beyond the Naked Eye

在日常农业生产与生态环境监测中，农作物或植被的健康状况常常出现一些表面上难以察觉的变化。想象这样一个场景：肉眼观察并发现没有明显的病虫害或营养缺陷，但田间产量却出现了下滑。传统的植被指数（例如NDVI）在此类情况下有时难以及时捕捉到植物内部的光合作用变化，从而导致对产量乃至生态系统健康状态的错误判断。

正是在这种背景下，日光诱导叶绿素荧光（SIF）技术应运而生，并迅速成为科学界和产业界关注的焦点。这项技术直接反映了植物光合作用的真实动态，为检测植物压力、预测作物生产力以及评估生态系统功能提供了一种全新的、精确的监测手段。SIF技术作为一种“植物的心电图”，能够捕捉到植物在光合作用过程中释放出的微弱荧光信号。这种信号与传统通过反射获得的植被指数存在本质不同，其优势在于能直接反映植物内在生理活动，而非仅仅依赖叶面积、绿度等表面特征。

In daily agricultural production and ecological environment monitoring, crops and vegetation often exhibit subtle changes in their health status that are difficult to detect with the naked eye. Imagine a scenario: you observe a field with no obvious signs of pests, diseases, or nutrient deficiencies, yet the yield is declining. Traditional vegetation indices, such as NDVI, sometimes fail to capture the underlying photosynthetic changes in plants in such cases, leading to incorrect assessments of yield and even ecosystem health.

It is against this backdrop that Solar-Induced Chlorophyll Fluorescence (SIF) technology has emerged and rapidly become a focal point in the scientific and industrial communities. This technology directly reflects the true dynamics of plant photosynthesis, providing a novel and precise monitoring tool for detecting plant stress, predicting crop productivity, and evaluating ecosystem function. SIF technology, acting as a "plant electrocardiogram", captures the faint fluorescence signals emitted by plants during photosynthesis. This signal is fundamentally different from traditional vegetation indices derived from reflection, as its advantage lies in directly reflecting the plant's intrinsic physiological activity, rather than merely relying on surface characteristics like leaf area or greenness.

土壤-植被-大气连续统中植被尺度的生态过程和水势梯度

Ecological Processes and Water Potential Gradients at the Vegetation Scale within the Soil-Vegetation-Atmosphere Continuum

什么是日光诱导叶绿素荧光（SIF）？

What is Solar-Induced Chlorophyll Fluorescence (SIF)?

日光诱导叶绿素荧光（Solar-induced chlorophyll fluorescence, SIF），是一种直接反映植物光合作用效率的信号，其产生过程与光合作用密切相关。简而言之，植物在吸收太阳光能后，一部分能量用于光合作用，而另一部分能量则通过热散发或以叶绿素荧光形式辐射出来。SIF技术通过传感器对这些荧光信号进行捕捉和解析，从而直接衡量光合活动的强弱及其随时间和环境条件的动态变化。

Solar-Induced Chlorophyll Fluorescence (SIF) is a signal that directly reflects the efficiency of plant photosynthesis. Its generation process is closely linked to photosynthesis. Simply put, after plants absorb solar energy, a portion of this energy is used for photosynthesis, while another portion is dissipated as heat or re-emitted as chlorophyll fluorescence. SIF technology captures and analyzes these fluorescence signals using sensors, thereby directly measuring the intensity of photosynthetic activity and its dynamic changes over time and under varying environmental conditions.

(A) 农田面积上基于 SIF 的年度作物 GPP 估计的空间详细信息、(B) 每个网格框的农田面积比例

(A) Spatially explicit estimates of annual crop GPP based on SIF over agricultural areas, and (B) the proportion of agricultural area in each grid box

1.1 SIF信号的形成与检测机制

Formation and Detection Mechanism of SIF Signals

在光合作用过程中，植被吸收了大量太阳能后，为维持光合平衡并防止能量过剩引起的光损伤，叶绿素会释放出非常微弱的荧光信号。这一荧光信号主要集中在红光（约680nm）和远红光（约740nm）波段，正是这一特性使得SIF成为捕捉植物内部光合作用活动的重要手段。而且，不同类型的作物和自然植被，其SIF信号强度和动态响应存在区域性差异，如同植物体内生理状态的实时反馈。

During photosynthesis, after absorbing a large amount of solar energy, vegetation releases very faint fluorescence signals to maintain photosynthetic balance and prevent photoinhibition caused by excess energy. This fluorescence signal is primarily concentrated in the red light (around 680nm) and far-red light (around 740nm) spectral bands. This specific characteristic makes SIF a crucial means of capturing the internal photosynthetic activity of plants. Furthermore, different types of crops and natural vegetation exhibit regional variations in SIF signal intensity and dynamic response, serving as a real-time feedback of the plant's internal physiological state.

1.2 夫琅禾费暗线的“井”填充效应

The "Filling" Effect of Fraunhofer Lines

在自然光照条件下，植被反射的光谱实际上包含了两个部分：一部分是叶片对入射太阳光的反射，另一部分则是植被自身发射的日光诱导叶绿素荧光（SIF）。虽然SIF的信号非常微弱，通常不到太阳入射能量的1%，远弱于植被的反射光，但在特定的波段，我们可以巧妙地利用一个自然现象来提取SIF信号。这个自然现象就是“夫琅禾费暗线”。由于太阳和地球大气层的吸收作用，太阳光谱中存在一些非常狭窄且强度较低的“暗线”（宽度为0.1~10nm），这些就是夫琅禾费暗线。在这些暗线位置，太阳光的能量显著低于周围波段。

叶绿素荧光的光谱辐射恰好会填充这些暗线区域，使得在这些暗线位置，SIF的相对比例显著增大。因此，将太阳辐射和植被反射光谱中某个波段的夫琅禾费暗线与相邻的波谱之间的相对强度进行比较，二者之间的差异就可以用来反演出SIF的强度。这就像在太阳光谱的“凹陷处”找到了SIF留下的“填补”痕迹，通过测量这种填补的程度，我们就能估算出SIF的强度。

Under natural illumination, the spectrum reflected by vegetation actually comprises two components: one is the reflection of incident solar light by the leaves, and the other is the Solar-Induced Chlorophyll Fluorescence (SIF) emitted by the vegetation itself. Although the SIF signal is very weak, typically less than 1% of the incoming solar energy and much weaker than reflected light, we can cleverly utilize a natural phenomenon to extract the SIF signal at specific wavelengths. This phenomenon is known as "Fraunhofer Lines". Due to the absorption by the sun and the Earth's atmosphere, the solar spectrum contains very narrow and less intense "dark lines" (with widths ranging from 0.1 to 10nm). These are the Fraunhofer lines. At these dark line positions, the solar energy is significantly lower than in the surrounding spectral regions.

The spectral radiation of chlorophyll fluorescence happens to "fill in" these dark line regions, causing the relative proportion of SIF to significantly increase at these Fraunhofer line positions. Therefore, by comparing the relative intensity between a Fraunhofer line and its adjacent spectral region in both the incoming solar radiation and the vegetation's reflected radiance spectra, the difference can be used to retrieve the intensity of SIF. This is akin to finding the "filling" trace left by SIF in the "dips" of the solar spectrum. By measuring the extent of this filling, we can estimate the intensity of SIF.

叶绿素荧光（SIF）对夫琅和费暗线的“井”填充效应

The "In-filling" Effect of Chlorophyll Fluorescence (SIF) on Fraunhofer Lines

SIF：植物的心电图

SIF: The Plant's Electrocardiogram

从前面的介绍可知，SIF能够更直接、更敏感地反映植物光合作用的效率和健康状况。SIF可以看作是植物的“心电图”，用来监测植物生理活动的“脉搏”。凭借这个特性，SIF在众多领域展现出强大的应用潜力，以下是它的主要应用方向：

As discussed, SIF provides a more direct and sensitive reflection of plant photosynthetic efficiency and health status. SIF can be considered the plant's "electrocardiogram," used to monitor the "pulse" of its physiological activity. With this characteristic, SIF demonstrates powerful application potential in numerous fields. Here are its main application areas:

农业领域

• 监测作物生长：SIF能够实时反映作物的生长活力，帮助了解作物的生长状态，及时调整管理措施。

• 诊断病虫害和胁迫：在作物表现出肉眼可见的病虫害或水分胁迫症状之前，SIF信号可能已经发生变化，为早期预警和精准施策提供依据。

• 优化施肥灌溉：根据SIF数据评估作物对养分和水分的需求，实现精准施肥和灌溉，提高资源利用效率，降低生产成本。

• 产量预估： SIF与作物最终产量之间存在良好的相关性，利用SIF数据可以更准确地预估作物产量，为农业生产决策提供支持。

Agricultural

• Monitoring Crop Growth: SIF can reflect crop growth vitality in real-time, helping to understand the growth status of crops and adjust management measures promptly.

• Diagnosing Pests, Diseases, and Stress: Before crops exhibit visible symptoms of pests, diseases, or water stress, the SIF signal may have already changed, providing a basis for early warning and precise intervention strategies.

• Optimizing Fertilization and Irrigation: SIF data can be used to assess crop demand for nutrients and water, enabling precise fertilization and irrigation, improving resource utilization efficiency, and reducing production costs.

• Yield Prediction: There is a good correlation between SIF and final crop yield. Utilizing SIF data can lead to more accurate crop yield predictions, supporting agricultural production decisions.

林业领域

• 评估森林健康：通过监测SIF，可以评估森林的光合能力和健康状况，及时发现森林退化或病虫害侵袭的区域。

• 监测森林火灾风险：干旱和高温会导致森林植被水分含量降低，光合作用下降，SIF信号随之减弱。利用SIF数据可以评估森林的干旱程度，辅助进行森林火险预警。

Forestry

• Assessing Forest Health: By monitoring SIF, the photosynthetic capacity and health status of forests can be evaluated, allowing for the timely identification of areas experiencing degradation or pest and disease outbreaks.

• Monitoring Forest Fire Risk: Drought and high temperatures lead to reduced water content in forest vegetation and decreased photosynthesis, resulting in a weakening of the SIF signal. SIF data can be used to assess the severity of drought in forests and assist in forest fire risk warning.

生态研究

• 监测植被生产力：SIF数据可以用于估算区域和全球尺度的植被总初级生产力（GPP），帮助科学家理解陆地生态系统碳循环，评估气候变化对植被的影响。

• 研究生态系统对环境变化的响应： 利用SIF监测气候事件（如干旱、热浪）对不同生态系统的影响，深入了解生态系统的脆弱性和恢复能力。

Ecological

• Monitoring Vegetation Productivity: SIF data can be used to estimate Gross Primary Production (GPP) at regional and global scales, helping scientists understand terrestrial ecosystem carbon cycling and evaluate the impact of climate change on vegetation.

• Studying Ecosystem Responses to Environmental Changes: SIF can be used to monitor the impact of extreme climate events (such as drought and heatwaves) on different ecosystems, providing deeper insights into ecosystem vulnerability and resilience.

预告 Preview

我们了解了SIF是什么，它如何产生。SIF微弱却蕴含着巨大的信息量，它是植物与我们“对话”的一种特殊方式。这些数据能在实际中发挥哪些作用呢？在接下来的文章中，我们将通过具体的应用案例，展示SIF在农业、林业、生态研究等领域的巨大潜力。敬请期待！

We have learned what SIF is and how it is produced. Despite being weak, SIF carries a wealth of information. It is a special way for plants to "communicate" with us. How can this data be applied in practice? In the following articles, we will showcase the immense potential of SIF in agriculture, forestry, ecological research, and other fields through specific application examples. Stay tuned!

如果您对SIF设备或相关方面有兴趣，欢迎随时联系我们了解咨询相关产品信息。

If you are interested in SIF equipment or related aspects, please feel free to contact us for product information.

参考论文 / Articals

1. Ni. Zhuoya.L. et al., A Review of Retrieving in Sun-Induced Chlorophyll Fluorescence, Advances in Meteorological Science and Technology (2021).

2. L.Guanter,Y.et al., Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence, Proc. Natl. Acad. Sci. U.S.A. 111 (14) E1327-E1333.