Precision Monitoring of Wheat Stripe Rust: Unraveling Hyperspectral and Solar-Induced Chlorophyll Fluorescence Technologies

小(xiǎo)麥條(tiáo)鏽病(bìng)嚴(yán)重(zhòng)威脅糧食安(ān)全(quán)
，實(shí)現早(zǎo)期(qī)準確監測既(jì)需要高靈敏技術支(zhī)持(chí)
，也(yě)需切實可行的硬(yìng)件(jiàn)設備。高光譜成(chéng)像和(hé)日光誘(yòu)導(dǎo)葉(yè)綠素熒(yíng)光（SIF）技(jì)術(shù)因(yīn)其(qí)敏感(gǎn)捕捉植株(zhū)生理和光(guāng)譜(pǔ)變化的能(néng)力
，正成為(wéi)小(xiǎo)麥病(bìng)害監(jiān)測(cè)的有力工具。接(jiē)下(xià)來
，我們結合(hé)三項具體研究案例
，展示光(guāng)譜(pǔ)技(jì)術的(dí)應(yīng)用。

Wheat stripe rust, a serious threat to food security, requires highly sensitive technological support and practical hardware for early and accurate monitoring. Hyperspectral imaging and Sun/Solar-Induced Chlorophyll Fluorescence (SIF) technologies, known for their ability to sensitively capture physiological and spectral changes in plants, are becoming powerful tools for monitoring wheat diseases.

Here, we present three specific research case studies that demonstrate the application of these spectral technologies.

基於日(rì)光誘(yòu)導(dǎo)葉(yè)綠素熒光(guāng)（SIF）的(dí)冠層(céng)與葉(yè)片(piàn)尺(chǐ)度(dù)監測(cè)

某(mǒu)團隊(duì)以冬(dōng)小麥(mài)自然感(gǎn)染(rǎn)條(tiáo)鏽(xiù)病為研(yán)究對象
，在陝(shǎn)西田間采集冠(guān)層(céng)及葉片級別(bié)數據
，使用(yòng)日光(guāng)誘導(dǎo)葉綠素熒(yíng)光測(cè)量係統結合高光譜(pǔ)設備采集SIF信(xìn)號(hào)，熒(yíng)光產量(liáng)（ΦF），歸一化植(zhí)被(bèi)指數（NDVI）等數據。

研究發現
，冠層尺度(dù)上多(duō)個(gè)熒光相(xiāng)關指標與(yǔ)病情(qíng)嚴重度(dù)均顯著(zhù)相(xiāng)關(guān)
，其中ΦF-r（SIF/NIRvR
，NIRvR是植被(bèi)的(dí)近(jìn)紅外輻(fú)射(shè)度）在病(bìng)害(hài)早(zǎo)期對植株生理壓(yā)力的敏(mǐn)感性優(yōu)於傳(chuán)統光(guāng)譜(pǔ)指標；而傳(chuán)統(tǒng)光譜(pǔ)指(zhǐ)標(biāo)如(rú)NDVI在病害後(hòu)期的監測表(biǎo)現仍(réng)具優勢(shì)。

這意味著(zhuó)SIF信號與傳(chuán)統(tǒng)光譜(pǔ)指數具(jù)有互(hù)補(bǔ)優勢
，二者(zhě)結(jié)合(hé)可實現更全(quán)麵(miàn)，更(gēng)精(jīng)準的小麥(mài)條鏽(xiù)病監測(cè)。

Canopy and Leaf Scale Monitoring Based on Solar-Induced Chlorophyll Fluorescence (SIF)

A research team focused on naturally infected winter wheat with stripe rust in Shaanxi Province, collecting canopy and leaf-level data in the field. They employed a SIF measurement system integrated with hyperspectral equipment to capture SIF signals, fluorescence yield (ΦF), and normalized difference vegetation index (NDVI).

The study found that several fluorescence-related indicators at the canopy scale were significantly correlated with disease severity levels. Notably, ΦF-r (SIF/NIRvR, where NIRvR refers to near-infrared radiation of vegetation) exhibited superior sensitivity to physiological stress in plants during the early stages of the disease compared to traditional spectral indices. In contrast, traditional spectral indices like NDVI remained effective in monitoring during the later stages of the disease.

This indicates that SIF signals and traditional spectral indices possess complementary advantages. When combined, they can achieve a more comprehensive and precise monitoring of wheat stripe rust.

a.研究區(qū)
，b.冠層光(guāng)譜(pǔ)測(cè)量實(shí)驗裝(zhuāng)置
，c.研(yán)究區小麥的三(sān)種形(xíng)態(tài)

Study area (a), experimental set-up of canopy spectral measurements (b), and three morphological of wheat in study area (c).

輕病(bìng)條件(jiàn)下不(bù)同信號(hào)與 SL 的關係(xì) （SL<20%）。（a–f） 是冠層尺(chǐ)度(dù)數據(jù);（g
，h） 是葉尺度數(shù)據(jù)。紅帶內的紅綫(xiàn)表(biǎo)示回歸綫和95%置信(xìn)區(qū)間(jiān)。

Relationship between different signals and SL under comprehensive experimental conditions.  (a–f) are canopy-scale data; (g,h) are leaf-scale data. The red lines with band denote the regression line and 95% confidence interval.

利用小波能(néng)量(liáng)係數(shù)的協同冠(guān)層SIF監測(cè)冬(dōng)小麥條(tiáo)鏽(xiù)病

另(lìng)一(yī)研究團(tuán)隊結合小(xiǎo)波(bō)能量係數方法
，協同使用(yòng)冠層SIF信(xìn)號
，在河北廊坊對冬(dōng)小(xiǎo)麥條(tiáo)鏽病進行定量監測。采用高光譜成(chéng)像儀(yí)采集冠(guān)層光(guāng)譜(pǔ)及(jí)葉(yè)綠素(sù)熒(yíng)光(guāng)數據
，深入分析了光譜(pǔ)與熒光(guāng)信號(hào)對病害(hài)動態(tài)變化的響應。

研究(jiū)中(zhōng)建立了多因(yīn)子(zǐ)融合模型
，揭(jiē)示(shì)了(liǎo)病害(hài)影(yǐng)響下作(zuò)物光合(hé)生理的群體(tǐ)特(tè)征表現
，顯著(zhù)提升了(liǎo)病(bìng)害檢測的準確(què)性和時效性。該(gāi)方法為利用SIF進行小(xiǎo)麥條鏽病動態(tài)監(jiān)控提(tí)供(gōng)了理(lǐ)論和技術(shù)支(zhī)持(chí)。

Monitoring Winter Wheat Stripe Rust Using Collaborative Canopy SIF with Wavelet Energy Coefficients

Another research team employed a wavelet energy coefficient method, utilizing canopy SIF signals to quantitatively monitor winter wheat stripe rust in Langfang, Hebei Province. They collected canopy spectral and chlorophyll fluorescence data using hyperspectral imaging equipment for in-depth analysis of the response of spectral and fluorescence signals to dynamic changes in disease.

They established a multi-factor integration model that revealed the impacts of stripe rust on the photosynthetic physiology of the crops, significantly improving the accuracy and timeliness of disease detection. This method provides theoretical and technical support for employing SIF in the dynamic monitoring of wheat stripe rust.

冠層(céng)光譜。a.不(bù)同疾(jí)病(bìng)嚴重(zhòng)程度(dù)下(xià)的原始(shǐ)光(guāng)譜；b.DI 與反射(shè)率(shuài)之間(jiān)的相關係數(shù)曲(qū)綫(xiàn)

Analysis based on canopy spectra. (a) the original spectra under different disease severity; (b) the curve of correlation coefficient between DI and reflectance.

技(jì)術(shù)框架 / Methodological framework of the monitoring model for stripe rust

無人(rén)機(jī)高光譜成(chéng)像技(jì)術(shù)融(róng)合葉綠素熒(yíng)光指(zhǐ)標(biāo)實現條(tiáo)鏽(xiù)病早期(qī)檢(jiǎn)測(cè)

該(gāi)團(tuán)隊還進行了另外一(yī)組研究(jiū)：利用(yòng)無人機搭(dā)載(zǎi)高(gāo)光(guāng)譜成像儀(yí)
，結合多(duō)種色(sè)素(sù)及(jí)相關(guān)光譜(pǔ)指數
，檢測(cè)小麥條鏽病。該團隊通(tōng)過(guò)航拍獲取大(dà)範(fàn)圍田間(jiān)高光譜(pǔ)數(shù)據
，提取(qǔ)病(bìng)斑色(sè)素特(tè)征和光譜(pǔ)指標
，融合葉(yè)綠(lǜ)素(sù)熒光(guāng)相關(guān)參(cān)數(shù)進(jìn)行建(jiàn)模(mó)分析。

結(jié)果(guǒ)表明
，該(gāi)方(fāng)法可實現條鏽病(bìng)的(dí)高精(jīng)度早(zǎo)期檢測
，適(shì)用於大範(fàn)圍快(kuài)速(sù)監測(cè)與(yǔ)病害(hài)擴散風險評估(gū)
，為農(nóng)業精(jīng)準防控提(tí)供(gōng)可靠技(jì)術支撐(chēng)。

Early Detection of Stripe Rust Using UAV-Mounted Hyperspectral Imaging Technology and Chlorophyll Fluorescence Indicators

In a different research initiative, the team utilized UAVs equipped with hyperspectral imaging systems to detect wheat stripe rust, combining various pigments and related spectral indices. They obtained extensive hyperspectral data through aerial surveys, extracting pigment characteristics and spectral indices from the diseased patches, which were then modeled together with the chlorophyll fluorescence parameters.

The results demonstrated that this method could achieve high-precision early detection of stripe rust, suitable for large-scale rapid monitoring and disease spread risk assessment, thereby providing reliable technical support for precision agricultural management.

實(shí)驗(yàn)區(qū)位(wèi)置(zhì)和(hé)樣(yàng)地分布。A表示實(shí)驗(yàn)區(qū)域的位置；B表(biǎo)示無(wú)人機(jī)高光(guāng)譜數據(jù)采(cǎi)集(jí)活動(dòng)；C表(biǎo)示(shì)無(wú)人機(jī)高(gāo)光(guāng)譜圖像(xiàng)和(hé)樣(yàng)本(běn)位(wèi)置；D表示(shì)不同侵染期健(jiàn)康(kāng)和患病樣本的狀(zhuàng)態。D1-D3代(dài)表(biǎo)健康樣本
，D4-D6分(fēn)別代(dài)表接(jiē)種後(hòu)7天(tiān)，16天(tiān)和(hé)23天(tiān)（DPI）的患(huàn)病(bìng)樣本(běn)。

Experimental area location and plot distribution. A represents the location of the experimental area; B represents UAV hyperspectral data acquisition activity; C represents UAV hyperspectral image and sample location; D represents the status of healthy and diseased samples at different infestation periods. D1-D3 represent healthy samples, and D4-D6 represent diseased samples at 7, 16, and 23 days post-inoculation (DPI), respectively.

Exponent的產品(pǐn)優勢與解決(jué)方(fāng)案

為(wéi)支持廣(guǎng)泛應用(yòng)
，我司(sī)自主(zhǔ)研發日(rì)光誘導葉(yè)綠素(sù)熒光(SIF)監測(cè)係(xì)統(tǒng)
，具備*的(dí)實(shí)時采(cǎi)集能(néng)力；同時(shí)代理高性(xìng)能(néng)的國產高光譜(pǔ)成像儀(yí)
，滿足從(cóng)地麵(miàn)，塔(tǎ)基到無人機平(píng)台(tái)的多(duō)場景(jǐng)需(xū)求。

用(yòng)戶可(kě)利(lì)用這些(xiē)硬(yìng)件設備(bèi)
，自主(zhǔ)開發分(fēn)析模(mó)型
，實(shí)現小麥條鏽(xiù)病(bìng)的早期(qī)預警，動(dòng)態(tài)監(jiān)控與(yǔ)精準防控
，真正(zhèng)實(shí)現農(nóng)業生產的數(shù)字化(huà)和智能化轉(zhuǎn)型(xíng)。

此(cǐ)外
，我們的設備支持(chí)集成到(dào)農業機械中
，輔助(zhù)農(nóng)機實(shí)現精(jīng)準，智能的高效噴藥作(zuò)業
，有效提升除(chú)病效率
，降低(dī)農藥使(shǐ)用量
，推動(dòng)綠(lǜ)色(sè)農業(yè)發(fā)展。

歡(huān)迎(yíng)聯係了解(jiě)設備詳情(qíng)及定製(zhì)化(huà)技(jì)術(shù)服務
，讓(ràng)光(guāng)譜技術助力智(zhì)慧農業(yè)
，守(shǒu)護(hù)糧食安全！

Exponent's Product Advantages and Solutions

To support widespread application, our company has independently developed a Solar-Induced Chlorophyll Fluorescence (SIF) monitoring system with powerful real-time acquisition capabilities. We also represent high-performance domestic hyperspectral imaging systems, catering to various scenarios from ground, tower, to UAV platforms.

Users can utilize these hardware devices to develop their analytical models, enabling early warnings, dynamic monitoring, and precise prevention of wheat stripe rust, effectively realizing the digital and intelligent transformation of agricultural production.

Additionally, our devices can be integrated into agricultural machinery, assisting in precise and intelligent pesticide application, thus improving disease control efficiency and reducing pesticide usage, promoting the development of sustainable agriculture.

We welcome inquiries for more details about our equipment and customized technical services, empowering smart agriculture through spectral technology and safeguarding food security!

案(àn)例(lì)來源 / Source

1. Du, K., et al. "An Improved Approach to Monitoring Wheat Stripe Rust with Sun-Induced Chlorophyll Fluorescence." Remote Sensing, vol. 15, no. 3, 2023, p. 693.

2. Ren, Kehui, et al. "Monitoring of Winter Wheat Stripe Rust by Collaborating Canopy SIF with Wavelet Energy Coefficients." Computers and Electronics in Agriculture, vol. 215, 2023, p. 108366.

3. Guo, Anting, et al. "Improved Early Detection of Wheat Stripe Rust through Integration Pigments and Pigment-Related Spectral Indices Quantified from UAV Hyperspectral Imagery." International Journal of Applied Earth Observation and Geoinformation, vol. 135, 2024.