## 4 Discussion  
Here, we demonstrated an implementation of SS-OCT to confirm its applicability as an inspection tool in agriculture for the diagnosis of morphological mutations of rice leaf specimens. The competency of imaging the leaf morphology and the correlative quantifications suggest that the proposed method has various agricultural benefits that could be used to improve the pre-diagnosis process for rice leaf diseases. In fact, rice leaf morphology and quantifications related to small-vein and mid-vein have been studied previously by histological methods; however, these methods are destructive and time-consuming. The non-destructive SS-OCT imaging modality was used here for the first time and was found to have considerable merits over conventional methods. To the best of our knowledge, morphological identification, leaf rolling assessment and small-vein cellular enumeration analysis were performed destructively in agriculture and have not been studied descriptively using OCT technology [52; 53; 54]. Rice leaf consists of multiple tissue layers, while these tissues constitute the photosynthesis system and nutrient transport pipeline of rice. However, the destruction that occurs in leaf layers can lead to weakened photosynthesis, degrading the internal nutrient delivery system [55]. Moreover, when plants are infected, bacteria does not affect yield but results in poor quality grains and a high proportion of broken kernels. Since OCT is capable of providing vital morphological information non-destructively, the precision of the technique was further assessed through a comparison between healthy and abnormal leaf specimens. Therefore, to examine feasible applicability, rice leaf specimens were compared before (Figure 7a) and after (Figure 7b) the inoculation of Xan-grading bacterial leaf blight, which causes large-scale necrosis leading to thickness reduction and atrophy of leaf specimens. Figure 6: (**a**) Graphical description of the measurement procedure of small vein numbers. (**b**) The flipped 2D-OCT visualization acquired from the rear surface of the leaf specimen illustrating external bi-directional angles between lower epidermis layer and lower mid-vein (A1 and A3), and internal angle of lower mid-vein (A2). (**c**) Quantitative graphical representation of enumerated small vein information. (**d**) The thickness between lower epidermis layer and lower mid-vein (\(\Delta t\)). (**e**) Quantitative graphical representation of angular information. (The error bars are the standard deviation). The averaged reduction of thickness of leaf layers were examined and compared as shown in Figure 7. Here, the green and red color horizontal dotted lines in figures were considered the standard levels, where the upper range was fixed on lower mid-vein and the lower range was fixed on lower epidermis layer. All the standards were drawn and confirmed using imagej software. Figure 7a,b, along with thickness measurements, provide a clearly identifiable thickness difference between healthy (before inoculation) and abnormal stages (after inoculation), verifying the potential merits of SS-OCT system as an inspection tool. Besides thickness assessments, the angular measurements, such as A1-A3 were examined to further confirm the precision, and the representative numerical results indicated on Figure 7d revealed a significant angular expansion at the infected stage compared to the healthy stage, as shown in Figure 7c. Figure 7 depicts representative graphical illustrations with numerical assessments corresponding to thickness and angular analysis. To further confirm the demonstrated assessments, small vein enumerations, thickness assessments, and angular measurements of five leaf specimens were obtained at healthy and infected stages. To analyze each inspection parameter more precisely, a total of five measurements of each parameter were taken and averaged. The statistical values are emphasized in Tables 1-3. Table 1 provides a comparison of enumerated (average, minimum, maximum, and standard deviation) small vein information.