The radish is a delicious, healthy vegetable and an important ingredient to many side dishes and main recipes. However, climate change, pollinator decline, and especially Fusarium wilt cause a significant reduction in the cultivation area and the quality of the radish yield. Previous studies on plant disease identification have relied heavily on extracting features manually from images, which is time-consuming and inefficient. In addition to Red-Green-Blue (RGB) images, the development of near-infrared (NIR) sensors has enabled a more effective way to monitor the diseases and evaluate plant health based on multispectral imagery. Thus, this study compares two distinct approaches in detecting radish wilt using RGB images and NIR images taken by unmanned aerial vehicles (UAV). The main research contributions include (1) a high-resolution RGB and NIR radish field dataset captured by drone from low to high altitudes, which can serve several research purposes; (2) implementation of a superpixel segmentation method to segment captured radish field images into separated segments; (3) a customized deep learning-based radish identification framework for the extracted segmented images, which achieved remarkable performance in terms of accuracy and robustness with the highest accuracy of 96%; (4) the proposal for a disease severity analysis that can detect different stages of the wilt disease; (5) showing that the approach based on NIR images is more straightforward and effective in detecting wilt disease than the learning approach based on the RGB dataset.

This study aimed to investigate the impact of plant growth regulators, sucrose concentration, and the number of subcultures on axillary shoot multiplication, in vitro flowering, and somaclonal variation and to assess the phytochemical composition, antioxidant capacity, and enzyme inhibitory potential of in vitro-established callus, somaclonal variant, and normal green shoots of Catharanthus roseus. The highest shoot induction rate (95.8%) and highest number of shoots (23.6), with a mean length of 4.5 cm, were attained when the C. roseus nodal explants (0.6–1 cm in length) were cultivated in Murashige and Skoog (MS) medium with 2 µM thidiazuron, 1 µM 2-(1-naphthyl) acetic acid (NAA), and 4% sucrose. The in vitro flowering of C. roseus was affected by sucrose, and the number of subcultures had a significant effect on shoot multiplication and somaclonal variation. The highest levels of phenolics and flavonoids were found in normal green shoots, followed by those in somaclonal variant shoots and callus. The phytochemicals in C. roseus extracts were qualified using liquid chromatography–tandem mass spectrometry. A total of 39, 55, and 59 compounds were identified in the callus, somaclonal variant shoot, and normal green shoot tissues, respectively. The normal green shoot extracts exhibited the best free radical scavenging ability and reducing power activity. The strongest acetylcholinesterase inhibitory effects were found in the callus, with an IC50 of 0.65 mg/mL.