Solar-Induced Chlorophyll Fluorescence (SIF) Applications in Agriculture, Forestry, and Ecological Monitoring

上一期文章中，我們介紹了日光誘導(dǎo)葉綠素?zé)晒猓?span>SIF）是什么，本篇將介紹SIF的主要應(yīng)用。SIF不僅僅是一個(gè)科研概念，它正在成為植物健康的“監(jiān)測(cè)儀"，為精準(zhǔn)農(nóng)業(yè)、生態(tài)監(jiān)測(cè)等領(lǐng)域帶來(lái)新的機(jī)遇。

This article will introduce the main applications of Solar-Induced Chlorophyll Fluorescence (SIF). SIF is not merely a scientific concept; it is becoming a "plant health monitor," bringing new opportunities to fields such as precision agriculture and ecological monitoring.

SIF：植物光合作用的“晴雨表"

SIF: A Barometer of Plant Photosynthetic Activity

簡(jiǎn)單來(lái)說(shuō)，日光誘導(dǎo)葉綠素?zé)晒猓?span>SIF）是植物在進(jìn)行光合作用時(shí)發(fā)射出的一種微弱光信號(hào)。SIF直接反映植物實(shí)時(shí)進(jìn)行光合作用的強(qiáng)度。當(dāng)植物感到“壓力"（如缺水、高溫、病蟲(chóng)害）時(shí)，它們的光合作用會(huì)減弱，SIF信號(hào)也會(huì)隨之變化。因此，SIF就像是植物光合作用的“晴雨表"，能夠靈敏地捕捉植物的生理狀態(tài)變化。

Simply put, Solar-Induced Chlorophyll Fluorescence (SIF) is a weak light signal emitted by plants during photosynthesis. SIF directly indicates the real-time intensity of plant photosynthesis. When plants experience "stress" (such as water deficiency, high temperature, pests, or diseases), their photosynthetic activity weakens, and the SIF signal changes accordingly. Therefore, SIF acts like a "barometer" of plant photosynthetic activity, capable of sensitively capturing changes in plant physiological status.

SIF的主要應(yīng)用介紹 / Introduction to Key SIF Applications

1. 農(nóng)業(yè)領(lǐng)域 / Agriculture

• 監(jiān)測(cè)作物生長(zhǎng)：SIF能夠?qū)崟r(shí)反映作物的生長(zhǎng)活力和光合效率，為作物生長(zhǎng)監(jiān)測(cè)提供更直接的生理信息，幫助種植者了解作物的生長(zhǎng)狀態(tài)，及時(shí)調(diào)整管理措施。

• 診斷病蟲(chóng)害和脅迫： 在作物表現(xiàn)出肉眼可見(jiàn)的病蟲(chóng)害或水分脅迫癥狀之前，SIF信號(hào)可能已經(jīng)發(fā)生變化，為早期預(yù)警和精準(zhǔn)施策提供依據(jù)。

• 化施肥灌溉： 通過(guò)監(jiān)測(cè)SIF數(shù)據(jù)評(píng)估作物對(duì)養(yǎng)分和水分的需求，可以指導(dǎo)精準(zhǔn)施肥和灌溉，提高資源利用效率，降低生產(chǎn)成本。

• 產(chǎn)量預(yù)估： SIF與作物最終產(chǎn)量之間存在良好的相關(guān)性，利用SIF數(shù)據(jù)可以更準(zhǔn)確地預(yù)估作物產(chǎn)量。

? Monitoring Crop Growth: SIF can real-time reflect crop vitality and photosynthetic efficiency, providing more direct physiological information for crop growth monitoring. This helps growers understand crop growth status and adjust management practices promptly.

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

? Optimizing Fertilization and Irrigation: By monitoring SIF data to assess crop nutrient and water requirements, precision fertilization and irrigation can be guided, improving resource utilization efficiency and reducing production costs.

? Yield Estimation: There is a good correlation between SIF and final crop yield. Utilizing SIF data can lead to more accurate crop yield estimations.

例如，2012年，美國(guó)大平原經(jīng)歷了一次嚴(yán)重的干旱事件。研究人員通過(guò)對(duì)SIF與干旱指數(shù)（如SPI和PDSI）的比較分析，發(fā)現(xiàn)SIF比傳統(tǒng)的NDVI能更早、更敏感地反映作物因干旱造成的脅迫。在干旱高峰期，SIF的變化幅度明顯大于NDVI，這意味著SIF可以更早地檢測(cè)到農(nóng)業(yè)干旱對(duì)作物造成的生理影響。

For example, in 2012, the Great Plains of the United States experienced an extreme drought event. Researchers compared SIF with drought indices (such as SPI and PDSI) and found that SIF reflected crop stress caused by drought earlier and more sensitively than traditional NDVI. During the peak of the drought, the magnitude of SIF change was significantly greater than that of NDVI, indicating that SIF can detect the physiological impact of agricultural drought on crops sooner.

2012年5月至10月期間，日光誘導(dǎo)葉綠素?zé)晒猓⊿IF）的下降

The reduction of solar-induced chlorophyll fluorescence (SIF) from May to October in 2012.

2012年5月至10月期間，歸一化植被指數(shù)（NDVI）的下降

The reduction of the normalized difference vegetation index (NDVI) from May to October in 2012.

2. 林業(yè)領(lǐng)域 / Forestry

• 干旱脅迫和監(jiān)測(cè)森林火災(zāi)風(fēng)險(xiǎn)：SIF對(duì)植物水分脅迫非常敏感。干旱會(huì)導(dǎo)致植物光合作用下降，SIF信號(hào)隨之變化。利用SIF數(shù)據(jù)可以評(píng)估森林的干旱程度，輔助進(jìn)行森林火險(xiǎn)預(yù)警。

• 評(píng)估森林健康：通過(guò)監(jiān)測(cè)森林冠層的SIF，可以評(píng)估森林的光合能力和健康狀況，及時(shí)發(fā)現(xiàn)森林退化或病蟲(chóng)害侵襲的區(qū)域。

? Drought Stress Monitoring and Forest Fire Risk Assessment: SIF is highly sensitive to plant water stress. Drought causes a decrease in plant photosynthesis, and the SIF signal changes accordingly. SIF data can be used to assess forest drought levels and assist in forest fire risk early warning.

? Assessing Forest Health: By monitoring forest canopy SIF, the photosynthetic capacity and health status of forests can be assessed, allowing for timely identification of areas experiencing forest degradation or pest and disease infestation.

在一項(xiàng)研究中，科研人員通過(guò)對(duì)香港地區(qū)森林進(jìn)行SIF信號(hào)分析，成功捕獲了因季節(jié)變化而產(chǎn)生的植被光合作用動(dòng)態(tài)。在不同季節(jié)中，SIF信號(hào)明顯呈現(xiàn)出冬季低、春夏增高的趨勢(shì)，與植被綠度（NDVI）的變化形成互補(bǔ)關(guān)系。研究中利用FLD方法，從690nm和740nm波段準(zhǔn)確提取SIF信號(hào)，并對(duì)比各季節(jié)NDVI值，證明了SIF在生態(tài)健康和脅迫診斷中的好的表現(xiàn)。

In one study, researchers analyzed SIF signals from forests in Hong Kong and successfully captured the dynamics of vegetation photosynthesis driven by seasonal changes. Across different seasons, the SIF signal clearly showed a trend of low values in winter and increasing values in spring and summer, complementing the changes in vegetation greenness (NDVI). The study used the FLD method to accurately extract SIF signals from the 690nm and 740nm bands and compared them with NDVI values across seasons, demonstrating the excellent performance of SIF in ecological health and stress diagnosis.

利用氧氣A吸收帶數(shù)據(jù)，反演得到不同季節(jié)的葉綠素?zé)晒鈴?qiáng)度。（DJI：冬天，MAM：春天，JJA：夏天，SON：秋天）

Inverted chlorophyll fluorescence intensity for different seasons using oxygen-A absorption band data. (DJF: Winter, MAM: Spring, JJA: Summer, SON: Autumn)

3. 生態(tài)研究 / Ecological Research

• 研究生態(tài)系統(tǒng)對(duì)環(huán)境變化的響應(yīng)：利用SIF監(jiān)測(cè)氣候事件（如干旱、熱浪）或人為干擾對(duì)不同生態(tài)系統(tǒng)的影響，深入了解生態(tài)系統(tǒng)的脆弱性和恢復(fù)能力。

• 研究生態(tài)系統(tǒng)碳循環(huán)：通過(guò)長(zhǎng)時(shí)間序列的SIF觀(guān)測(cè)，可以更好地理解生態(tài)系統(tǒng)在不同時(shí)間尺度上的碳吸收動(dòng)態(tài)，為氣候變化模型提供更準(zhǔn)確的參數(shù)，同時(shí)對(duì)評(píng)估陸地生態(tài)系統(tǒng)的碳匯功能具有重要意義。

• 監(jiān)測(cè)植被生產(chǎn)力：SIF是估算生態(tài)系統(tǒng)總初級(jí)生產(chǎn)力（GPP）的有力工具，比傳統(tǒng)的基于反射率的植被指數(shù)更直接地反映植被的光合固碳能力。

? Studying Ecosystem Response to Environmental Change: Using SIF to monitor the impact of extreme climate events (such as drought, heatwaves) or anthropogenic disturbances on different ecosystems provides a deeper understanding of ecosystem vulnerability and resilience.

? Studying Ecosystem Carbon Cycle: Long-term SIF observations allow for a better understanding of ecosystem carbon uptake dynamics across different time scales, providing more accurate parameters for climate change models, and is also of significant importance for evaluating terrestrial ecosystem carbon sink function.

? Monitoring Vegetation Productivity: SIF is a powerful tool for estimating ecosystem Gross Primary Production (GPP), reflecting the photosynthetic carbon fixation capacity of vegetation more directly than traditional reflectance-based vegetation indices.

一項(xiàng)研究利用全球不同區(qū)域的SIF數(shù)據(jù)，經(jīng)過(guò)處理和校準(zhǔn)后，將其與對(duì)應(yīng)區(qū)域和時(shí)間的實(shí)際農(nóng)作物產(chǎn)量統(tǒng)計(jì)數(shù)據(jù)進(jìn)行對(duì)比分析。研究發(fā)現(xiàn)，SIF數(shù)據(jù)能夠有效地反映農(nóng)作物光合作用的強(qiáng)度，并與農(nóng)作物產(chǎn)量呈現(xiàn)出高度的相關(guān)性。引入直接反映光合過(guò)程的SIF數(shù)據(jù)，不僅大幅提高了GPP估算精度，還為全球碳循環(huán)模型中環(huán)境變量的敏感性問(wèn)題提供了修正依據(jù)。

下圖是該研究中美國(guó)玉米帶農(nóng)田通量塔站點(diǎn)和西歐草原站點(diǎn)的數(shù)據(jù)圖表。基于通量塔的GPP、SIF（A, B）和植被增強(qiáng)指數(shù) EVI（C, D）的時(shí)間序列以及時(shí)空平均值，SIF和EVI都以相同的垂直比例繪制。改圖直觀(guān)地體現(xiàn)SIF和GPP的相關(guān)性及較高的相關(guān)系數(shù)。

One study utilized SIF data from different regions globally, and after processing and calibration, compared it with actual crop yield statistics for corresponding regions and times. The study found that SIF data could effectively reflect the intensity of crop photosynthesis and showed a high correlation with crop yield. The introduction of SIF data, which directly reflects the photosynthetic process, not only significantly improved GPP estimation accuracy but also provided a basis for correcting the sensitivity issues of environmental variables in global carbon cycle models.

The figure below shows data charts from a cropland flux tower site in the US Corn Belt and a grassland site in Western Europe from this study. Time series and spatiotemporally averaged values of flux tower based GPP, SIF (A, B), and Enhanced Vegetation Index (EVI) (C, D) are presented, with SIF and EVI plotted to the same vertical scale. This figure intuitively demonstrates the correlation between SIF and GPP and their high correlation coefficients.

結(jié)語(yǔ) / Conclusion

日光誘導(dǎo)葉綠素?zé)晒猓?span>SIF）技術(shù)正以更直接更深入的角度，為我們揭示植物光合作用的奧秘，其在精準(zhǔn)農(nóng)業(yè)、林業(yè)、生態(tài)研究等領(lǐng)域的應(yīng)用前景廣闊。

要充分發(fā)揮SIF技術(shù)的價(jià)值，高精度、高可靠性的觀(guān)測(cè)系統(tǒng)是關(guān)鍵。從塔基到無(wú)人機(jī)遙感，我們提供多尺度的專(zhuān)業(yè)日光誘導(dǎo)葉綠素?zé)晒猓?span>SIF）監(jiān)測(cè)解決方案，能夠?yàn)榭蒲小⑥r(nóng)林、環(huán)保等領(lǐng)域的客戶(hù)提供精準(zhǔn)、穩(wěn)定的SIF數(shù)據(jù)，助您深入了解植物健康狀況，做出科學(xué)決策。

Solar-Induced Chlorophyll Fluorescence (SIF) technology is revealing the mysteries of plant photosynthesis with unprecedented precision, and its application prospects in precision agriculture, forestry, and ecological research are vast.

To fully leverage the value of SIF technology, high-precision and high-reliability observation systems are key. From ground-based towers to drone remote sensing, we offer multi-scale professional Solar-Induced Chlorophyll Fluorescence (SIF) monitoring solutions, providing accurate and stable SIF data to clients in scientific research, agriculture and forestry, environmental protection, and other fields, helping you gain a deeper understanding of plant health and make scientific decisions.

案例來(lái)源 / Source

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

2. Joiner, J et al., First observations of global and seasonal terrestrial chlorophyll fluorescence from space, Biogeosciences, 8, 637–651, 2011.

3. Wang, S. et al., Monitoring and Assessing the 2012 Drought in the Great Plains: Analyzing Satellite-Retrieved Solar-Induced Chlorophyll Fluorescence, Drought Indices, and Gross Primary Production. Remote Sens. 2016, 8, 61

4. Irteza, S. M. and Nichol, J. E.: MEASUREMENT OF SUN INDUCED CHLOROPHYLL FLUORESCENCE USING HYPERSPECTRAL SATELLITE IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 911–913.

5. Y. Sun et al., OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence. Science358, eaam5747(2017).