本研究開發 UV/Vis的輔助方法，以數位相機取代傳統光學偵測器，配合LabVIEW內建機器視覺功能，依據紅綠藍三原色顏色變化的軌跡，作為檢測反應程度的依據。實驗中使用藍染溶液作為反應範例，即時監測顏色變化，並且對反應過程中物質的相對含量變化進行分析。為了還原靛藍，使用連二亞硫酸（Na2S2O4）進行化學還原，以及採用酵母粉（釀酒酵母）進行生物發酵過程。實驗結果顯示：靛藍溶液在化學還原法中可以透過 R 與 G 像素的曲線變化直接瞭解反應進程；G像素曲線開始增加表示產物靛白的形成，R曲線的急遽增加則顯示靛白量已超過靛藍，且反應逐漸達到平衡。在化學還原法中，由於Na2S2O4及其氧化產物皆為無色，因此溶液顏色直接由反應物靛藍與產物靛白的含量來決定。在生物發酵條件下觀察到較複雜的RGB追跡圖，從RGB曲線可觀察到反應初始的發酵活化期，且當R與G像素達到最大值時，表明在發酵作用下靛藍還原產生的靛白濃度最高，而後曲線變為平緩即反應已達到平衡。
RGB-tracking檢測法也應用在追跡靛藍還原溶液具有染布效力的時間點。從RGB即時追跡圖譜及染布塊的HSV數值可確定染色的優化時間。兩種靛藍還原法的染液都是在G像素開始增加時即具有染布效力，且隨著反應時間，染布塊的飽和度逐漸增加。化學還原法的染液可提供更高的色調 (H) 與飽和度 (S)，染色效能優於生物發酵法。
本研究運用RGB色彩空間與CIE xyY色度圖解釋靛藍還原過程的顏色變化。追蹤的RGB曲線變化可反映出溶液組成成分的消長，CIE xyY色度圖則可更直觀表述溶液顏色的色相與飽和度的變化趨勢。由主成分分析統計可以發現：CIE xy色度數值對於靛藍反應的顏色變化較具指標性，且從各項主成分變異的特徵可對反應進行監控，或是進行實驗條件的優化與探討。
這個RGB-tracking檢測法就像是微觀系統的放大鏡，例如常見的光敏電阻只能檢測光線的明亮度，而本研究開發的方法是以相機擷取溶液顏色，同步透過機器視覺程式，解讀即時的反應程度。靛藍還原反應不論是採用化學還原法，或是過程牽涉較多機制的生物發酵法，對於溶液顏色進行RGB三色的即時追跡，更能有效評估還原進行的程度，提高實驗的精確度。此方法具有即時且連續追跡的優點，且運用機器視覺編程具有彈性，可依需要進行客製化設計，未來將有可能取代UV/Vis光譜法，或做為UV/Vis光譜法的互補方式。

A novel RGB-tracking technique using detecting the color of the reaction solution is described. Using indigo solution as a model reaction, this approach allows real-time monitoring and analysis of the relative changes in substance concentrations during the reaction process. The RGB-tracking system consists of a digital camera, light source, data acquisition equipment, LabVIEW program, and integrated machine vision functions. For the reduction of indigo, sodium dithionite ( Na2S2O4 ) is applied for chemical reduction, while yeast powder (brewer's yeast) is utilized for the biological fermentation process. Experimental results reveal that in the chemical reduction method, the progression of the indigo solution can be directly understood through the curves of the R and G pixels. The initial increase in the G pixel curve indicates the formation of the product, leuco-indigo, while a sharp rise in the R curve signifies that the amount of leuco-indigo has exceeded that of indigo, indicating a gradual approach to equilibrium in the reaction. In the chemical reduction method, as both Na2S2O4 and its oxidation products are colorless, the color of the reaction solution is directly determined by the content of the reactant indigo and the product leuco-indigo. Under the conditions of biological fermentation, more intricate RGB tracking patterns were observed. Since a blank fermentation solution serves as the background, the color changes during the fermentation process are also taken into consideration. The RGB curves reveal the initial fermentation activation state, and when both the R and G pixels reach their maximum values, it indicates the highest concentration of leuco-indigo resulting from indigo reduction through fermentation. Subsequently, the curves become smooth, signifying that the reaction has reached equilibrium.
The RGB-tracking detection method is also applied to track the optimal moment when the indigo reduction solution becomes effective for dyeing fabric. By analyzing the real-time RGB curves and the HSV values of the dyed fabric samples, the ideal dyeing time can be determined. In both reduction methods for indigo dye, the dyeing effectiveness is evident as soon as the G pixel begins to increase, and with increasing reaction time, the fabric samples gradually achieve higher levels of saturation. The chemical reduced dyeing solution offers higher hue (H) and saturation (S), and demonstrates significantly better dyeing performance compared to the bio-fermentation method.
This study utilizes the RGB color space and the CIE xyY chromaticity diagram to explain the color changes during the indigo reduction process. The tracked changes in the RGB curves reflect the variations in the composition of the solution, while the CIE xyY chromaticity diagram provides a more intuitive representation of the changes in hue and saturation of the solution's color. Principal Component Analysis (PCA) reveals that the CIE xy chromaticity values are more indicative of the color changes in the indigo reaction. Additionally, the characteristics of the variations in the principal components can be used to monitor the reaction and optimize experimental conditions.
The RGB-tracking detection device acts like a magnifying glass for microsystems. For instance, common photosensitive resistors can only measure the brightness of light. In contrast, the approach developed in this study involves using a camera to capture color variations and simultaneously employs machine vision algorithms to interpret the immediate level of response. This is especially true for the process of indigo reaction, which involves multiple mechanisms. By instantly tracking the real-time changes in the RGB tri-color of the solution, it becomes even more effective in evaluating the extent of reduction processes, consequently elevating the precision of the experiments.
This method offers the advantages of real-time and continuous tracking. Moreover, the utilization of machine vision programming provides flexibility, allowing for customized designs as required. In the future, there is potential for this method to replace UV/Vis spectroscopy or serve as a complementary approach to UV/Vis spectroscopy.

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