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

上一期(qī)文章中(zhōng)，我(wǒ)們(mén)介(jiè)紹(shào)了日光誘導(dǎo)葉綠(lǜ)素(sù)熒光(guāng)（SIF）是什(shí)麼，本(běn)篇將介紹(shào)SIF的(dí)主要(yào)應(yīng)用。SIF不(bù)僅僅是一(yī)個科研(yán)概念，它正在成為植物(wù)健康的“監(jiān)測儀"，為(wéi)精準(zhǔn)農業，生(shēng)態(tài)監(jiān)測(cè)等(děng)領域帶來新(xīn)的機遇(yù)。

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(hé)作用的(dí)“晴雨(yǔ)表"

SIF: A Barometer of Plant Photosynthetic Activity

簡單來說，日光(guāng)誘導葉綠(lǜ)素(sù)熒光(guāng)（SIF）是植物在(zài)進(jìn)行光(guāng)合(hé)作(zuò)用(yòng)時(shí)發射出(chū)的(dí)一(yī)種(zhǒng)微(wēi)弱(ruò)光(guāng)信(xìn)號(hào)。SIF直接反映(yìng)植物(wù)實(shí)時進行光合(hé)作(zuò)用(yòng)的強(qiáng)度。當(dāng)植物感到(dào)“壓力(lì)"（如(rú)缺水，高溫，病(bìng)蟲害(hài)）時(shí)，它們的(dí)光合(hé)作(zuò)用(yòng)會(huì)減(jiǎn)弱，SIF信(xìn)號也會隨之變化。因(yīn)此，SIF就(jiù)像是植物光(guāng)合作用的(dí)“晴雨(yǔ)表"，能夠靈(líng)敏地(dì)捕(bǔ)捉(zhuō)植(zhí)物的(dí)生理(lǐ)狀態(tài)變(biàn)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(yào)應用介紹 / Introduction to Key SIF Applications

1. 農業(yè)領域(yù) / Agriculture

• 監測作物生長(cháng)：SIF能(néng)夠實時反映(yìng)作物(wù)的(dí)生長(cháng)活力和光合效率(shuài)，為(wéi)作物(wù)生長監測提(tí)供(gōng)更直接(jiē)的生(shēng)理(lǐ)信息，幫助種(zhǒng)植者(zhě)了解(jiě)作(zuò)物的(dí)生長狀(zhuàng)態，及(jí)時調整管(guǎn)理(lǐ)措施(shī)。

• 診斷(duàn)病蟲害(hài)和(hé)脅迫： 在作物表現(xiàn)出肉(ròu)眼可見(jiàn)的病(bìng)蟲害或水(shuǐ)分(fēn)脅迫(pò)症狀之前，SIF信號可(kě)能(néng)已經發生變(biàn)化，為早(zǎo)期(qī)預警和(hé)精準施策提供依據(jù)。

• 化施(shī)肥灌溉： 通過監測SIF數(shù)據(jù)評(píng)估(gū)作(zuò)物對(duì)養分和水分(fēn)的(dí)需(xū)求，可以指導精(jīng)準(zhǔn)施(shī)肥和灌(guàn)溉(gài)，提高(gāo)資源利用(yòng)效率，降低(dī)生產成本。

• 產(chǎn)量(liáng)預(yù)估(gū)： SIF與(yǔ)作物最(zuì)終產量之間(jiān)存(cún)在(zài)良好的相關性，利用(yòng)SIF數據可以更準(zhǔn)確(què)地(dì)預(yù)估(gū)作(zuò)物(wù)產量。

▷ 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(lì)如(rú)，2012年(nián)，美國(guó)大(dà)平(píng)原經(jīng)歷了一次嚴重的(dí)幹(gān)旱(hàn)事件。研究(jiū)人員通過對(duì)SIF與(yǔ)幹旱指數(shù)（如(rú)SPI和PDSI）的比較分析，發現SIF比傳統的NDVI能更(gēng)早，更(gēng)敏感地反(fǎn)映(yìng)作(zuò)物(wù)因幹旱造成的(dí)脅(xié)迫。在幹(gān)旱(hàn)高峰期，SIF的變化(huà)幅度(dù)明(míng)顯大(dà)於NDVI，這意味(wèi)著SIF可以(yǐ)更(gēng)早(zǎo)地檢測(cè)到(dào)農(nóng)業幹旱對(duì)作(zuò)物(wù)造成(chéng)的(dí)生(shēng)理(lǐ)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(nián)5月(yuè)至10月期間(jiān)，日(rì)光(guāng)誘導葉綠(lǜ)素熒光(guāng)（SIF）的下(xià)降(jiàng)

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

2012年5月至(zhì)10月期(qī)間，歸一(yī)化植被(bèi)指數(shù)（NDVI）的下(xià)降

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

2. 林(lín)業(yè)領域 / Forestry

• 幹(gān)旱脅迫和監(jiān)測森林(lín)火(huǒ)災(zāi)風(fēng)險(xiǎn)：SIF對植物(wù)水(shuǐ)分脅迫(pò)非常敏(mǐn)感。幹(gān)旱會(huì)導致植物(wù)光(guāng)合(hé)作用(yòng)下(xià)降，SIF信號隨之(zhī)變(biàn)化。利(lì)用SIF數(shù)據可以(yǐ)評估(gū)森(sēn)林(lín)的(dí)幹旱(hàn)程度(dù)，輔助進(jìn)行(háng)森林火險預警。

• 評(píng)估森林(lín)健康(kāng)：通(tōng)過(guò)監(jiān)測森林冠層的(dí)SIF，可(kě)以(yǐ)評估(gū)森林的光(guāng)合(hé)能(néng)力(lì)和健康狀況，及時(shí)發現森(sēn)林退化(huà)或(huò)病蟲害(hài)侵襲的(dí)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(zài)一項研(yán)究中(zhōng)，科研人員通過對香港地(dì)區森林進行SIF信號分(fēn)析，成功捕獲(huò)了因季節(jié)變化而產生的(dí)植被光(guāng)合作用動(dòng)態。在(zài)不同(tóng)季節中，SIF信(xìn)號明顯(xiǎn)呈現(xiàn)出冬季低，春夏增(zēng)高的趨(qū)勢，與植被綠(lǜ)度（NDVI）的變(biàn)化(huà)形成互補關(guān)係(xì)。研究(jiū)中(zhōng)利用(yòng)FLD方法，從690nm和(hé)740nm波段(duàn)準確(què)提取SIF信號，並(bìng)對(duì)比(bǐ)各季節NDVI值，證(zhèng)明了(liǎo)SIF在生(shēng)態(tài)健康(kāng)和脅(xié)迫(pò)診(zhěn)斷(duàn)中的好的(dí)表(biǎo)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(yòng)氧氣A吸收帶數據，反(fǎn)演得(dé)到(dào)不(bù)同季節(jié)的葉綠素(sù)熒光(guāng)強(qiáng)度(dù)。（DJI：冬天，MAM：春天，JJA：夏(xià)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(shēng)態研究 / Ecological Research

• 研究(jiū)生(shēng)態係(xì)統對環(huán)境變(biàn)化的響應(yīng)：利用SIF監(jiān)測(cè)氣(qì)候事件（如幹旱，熱浪(làng)）或(huò)人為(wéi)幹(gān)擾對不同(tóng)生(shēng)態係統(tǒng)的影(yǐng)響，深入了解生(shēng)態(tài)係(xì)統(tǒng)的(dí)脆弱性(xìng)和恢(huī)復能力(lì)。

• 研究(jiū)生(shēng)態(tài)係(xì)統(tǒng)碳(tàn)循環：通過(guò)長(cháng)時間序列的(dí)SIF觀(guān)測，可以更(gēng)好地(dì)理解生態係(xì)統(tǒng)在不(bù)同時間(jiān)尺(chǐ)度(dù)上(shàng)的碳吸收動(dòng)態，為(wéi)氣候(hòu)變化模型提供(gōng)更準確(què)的參(cān)數，同(tóng)時(shí)對評(píng)估(gū)陸(lù)地生(shēng)態(tài)係(xì)統的碳(tàn)匯功能具有重(zhòng)要意義。

• 監測植(zhí)被生產力：SIF是估算生態(tài)係統總(zǒng)初級生(shēng)產力(lì)（GPP）的(dí)有力(lì)工具，比(bǐ)傳統(tǒng)的基(jī)於(yú)反(fǎn)射(shè)率(shuài)的(dí)植被指(zhǐ)數更直接(jiē)地(dì)反映(yìng)植被的(dí)光(guāng)合(hé)固(gù)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(yī)項研(yán)究利用全球(qiú)不同區域的SIF數據(jù)，經過處理(lǐ)和(hé)校準後(hòu)，將(jiāng)其(qí)與(yǔ)對應(yīng)區(qū)域(yù)和時間的(dí)實際(jì)農(nóng)作(zuò)物產量(liáng)統(tǒng)計(jì)數據進行(háng)對比分析。研(yán)究(jiū)發現，SIF數據能夠有(yǒu)效地(dì)反(fǎn)映農(nóng)作物(wù)光(guāng)合(hé)作(zuò)用的強度，並與(yǔ)農(nóng)作(zuò)物產(chǎn)量呈(chéng)現出高(gāo)度的相關性。引入直接反映光合過(guò)程(chéng)的SIF數據，不僅(jǐn)大(dà)幅提高了GPP估算精(jīng)度(dù)，還(huán)為全(quán)球碳循環模型中環境變量的敏(mǐn)感性(xìng)問題提(tí)供(gōng)了修(xiū)正(zhèng)依據(jù)。

下圖是該研(yán)究中美(měi)國玉米帶(dài)農(nóng)田通(tōng)量塔站點和(hé)西歐草原站(zhàn)點的(dí)數(shù)據(jù)圖表(biǎo)。基於通(tōng)量塔的GPP，SIF（A, B）和植被增(zēng)強指數(shù) EVI（C, D）的時(shí)間序(xù)列以及(jí)時(shí)空(kōng)平均(jūn)值(zhí)，SIF和EVI都以(yǐ)相同的(dí)垂直比例繪(huì)製。改圖直觀地(dì)體現(xiàn)SIF和GPP的(dí)相關性(xìng)及較高(gāo)的(dí)相關係(xì)數。

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.

結語 / Conclusion

日(rì)光(guāng)誘導葉(yè)綠(lǜ)素(sù)熒(yíng)光（SIF）技術正(zhèng)以更直接(jiē)更深(shēn)入的角度，為我(wǒ)們揭(jiē)示植物(wù)光(guāng)合作用的奧秘，其在(zài)精準農業(yè)，林業，生(shēng)態(tài)研究等領域的應用(yòng)前景(jǐng)廣闊。

要充分(fēn)發揮(huī)SIF技術(shù)的(dí)價值(zhí)，高(gāo)精(jīng)度(dù)，高可(kě)靠性的(dí)觀(guān)測係統是關鍵。從塔基到(dào)無人機(jī)遙感，我們提(tí)供多(duō)尺(chǐ)度的專業(yè)日光(guāng)誘(yòu)導(dǎo)葉綠(lǜ)素熒(yíng)光（SIF）監測(cè)解決方(fāng)案，能(néng)夠為科(kē)研，農林，環(huán)保(bǎo)等領域的(dí)客戶提(tí)供精準，穩(wěn)定的SIF數據，助(zhù)您(nín)深(shēn)入(rù)了解(jiě)植(zhí)物(wù)健康(kāng)狀(zhuàng)況，做(zuò)出(chū)科學決策。

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(àn)例(lì)來(lái)源(yuán) / 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).