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 establish a rapid in vitro plant regeneration method from rhizome buds of Kaempferia parviflora to obtain the valuable secondary metabolites with antioxidant and enzyme inhibition properties. The disinfection effect of silver oxide nanoparticles (AgO NPs) on rhizome and effects of plant growth regulators on shoot multiplication and subsequent rooting were investigated. Surface sterilization of rhizome buds with sodium hypochlorite was insufficient to control contamination. However, immersing rhizome buds in 100 mg L⁻¹ AgO NPs for 60 min eliminated contamination without affecting the survival of explants. The number of shoots (12.2) produced per rhizome bud was higher in Murashige and Skoog (MS) medium containing 8 µM of 6-Benzyladenine (6-BA) and 0.5 µM of Thidiazuron (TDZ) than other treatments. The highest number of roots (24), with a mean root length of 7.8 cm and the maximum shoot length (9.8 cm), were obtained on medium MS with 2 µM of Indole-3-butyric acid (IBA). A survival rate of 98% was attained when plantlets of K. parviflora were acclimatized in a growth room. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) was used to determine the chemical profile of K. parviflora leaf extracts. Results showed that several biologically active flavonoids reported in rhizomes were also present in leaf tissues of both in vitro cultured and ex vitro (greenhouse-grown) plantlets of K. parviflora. We found 40 and 36 compounds in in vitro cultured and ex vitro grown leaf samples, respectively. Greenhouse leaves exhibited more potent antioxidant activities than leaves from in vitro cultures. A higher acetylcholinesterase inhibitory ability was obtained for greenhouse leaves (1.07 mg/mL). However, leaves from in vitro cultures exhibited stronger butyrylcholinesterase inhibitory abilities. These results suggest that leaves of K. parviflora, as major byproducts of black ginger cultivation, could be used as valuable alternative sources for extracting bioactive compounds.

Traditional phenotyping relies on experts visually examining plants for physical traits like size, color, or disease presence. Measurements are taken manually using rulers, scales, or color charts, with all data recorded by hand. This labor-intensive and time-consuming process poses a significant obstacle to the efficient breeding of new cultivars. Recent innovations in computer vision and machine learning offer potential solutions for accelerating the development of robust and highly effective plant phenotyping. This study introduces an efficient plant recognition framework that leverages the power of the Segment Anything Model (SAM) guided by Explainable Contrastive Language–Image Pretraining (ECLIP). This approach can be applied to a variety of plant types, eliminating the need for labor-intensive manual phenotyping. To enhance the accuracy of plant phenotype measurements, a B-spline curve is incorporated during the plant component skeleton extraction process. The effectiveness of our approach is demonstrated through experimental results, which show that the proposed framework achieves a mean absolute error (MAE) of less than 0.05 for the majority of test samples. Remarkably, this performance is achieved without the need for model training or labeled data, highlighting the practicality and efficiency of the framework.

The goal of this study was to establish an efficient protocol for the large-scale propagation of Mertensia maritima (L.) Gray, and evaluate the carotenoid, fatty acid, and tocopherol contents in the leaves of in vitro regenerated shoots. Surface-disinfected node and shoot tip explants were placed on semisolid Murashige and Skoog (MS) medium with 0–16 µM N⁶-benzyladenine (BA), kinetin, (KN), and thidiazuron (TDZ) alone, or in combination with, 1 or 2 µM α-naphthaleneacetic acid (NAA). Of the three different cytokinins employed, TDZ elicited the best results for axillary shoot proliferation. A maximum frequency of shoot initiation above 84%, with a mean of 8.9 and 4.8 shoots per node and shoot tip, respectively, was achieved on the culture medium supplemented with 4 µM TDZ. A combination of TDZ + NAA significantly increased the percentage of multiple shoot formation and number of shoots per explant. The best shoot induction response occurred on MS medium with 4 µM TDZ and 1 µM NAA. On this medium, the node (93.8%) and shoot tip (95.9%) explants produced an average of 17.7 and 8.6 shoots, respectively. The highest root induction frequency (97.4%) and number of roots per shoot (25.4), as well as the greatest root length (4.2 cm), were obtained on half-strength MS medium supplemented with 4 µM indole-3-butyric acid (IBA). The presence of six carotenoids and α-tocopherol in the leaf tissues of M. maritima was confirmed by HPLC. Gas chromatography-mass spectrometry analysis confirmed the presence of 10 fatty acids, including γ-linolenic acid and stearidonic acid in the leaf tissues of M. maritima. All-E-lutein (18.49 μg g⁻¹ fresh weight, FW), α-tocopherol (3.82 μg g⁻¹ FW) and α-linolenic acid (30.37%) were found to be the significant compounds in M. maritima. For the first time, a successful protocol has been established for the mass propagation of M. maritima with promising prospects for harnessing its bioactive reserves.

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.

Kimchi made from small-type (Altari) radishes grown in late spring is more pungent than that made from autumn-grown Altari radishes, which poses a major challenge in the kimchi industry. The mechanism through which the pungency of Altari radish changes seasonally has not been intensively investigated. In this study, three small-type radish cultivars with different pungency levels were cultivated in spring and autumn to identify the factors affecting the seasonal-dependent pungency of small-type radishes. The contents of pungency-related metabolite glucoraphasatin and other polar metabolites were analyzed. Although a previous study reported that the glucoraphasatin concentration affects the pungency of radish, in the current study, the concentration of neither glucoraphasatin nor its hydrolysis product (raphasatin) could fully explain the change in the pungency associated with radish cultivars grown in the two seasons. The change in the pungency of radish by season may be explained by the ratio of raphasatin content to total sweetness of sugars. In addition, the polar metabolites that differ with season were analyzed to identify seasonal biomarkers and understand the seasonal changed physio-biochemistry.