Plant diseases pose significant challenges to agricultural productivity and farmers' income, particularly in regions where agriculture is a primary livelihood. This study presents the development of an artificial intelligence-based plant disease diagnosis system for economic crops in Phetchaburi Province, Thailand, using citrus canker in lime as a case study. A Convolutional Neural Network (CNN) was employed to classify images of lime leaves and fruits into diseased and healthy categories. A total of $\mathbf{1, 6 0 0}$ images were collected, preprocessed, and augmented before being divided into training, validation, and testing datasets. The CNN model was implemented using the TensorFlow framework and optimized through parameter tuning. Experimental results showed that the proposed model achieved an accuracy of 93.75 % on the testing dataset, with balanced Precision, Recall, and F1-Score values. The trained model was further integrated into a web-based application to enable practical usage. User evaluation results indicated that the system was easy to use and suitable for supporting preliminary disease diagnosis, demonstrating its potential to enhance disease management and promote smart agriculture practices at the local level.
Lactic Acid Bacteria (LAB)-derived antimicrobial compounds are recognized as a promising source of novel antimicrobial agents, particularly for the treatment of Methicillin-Resistant Staphylococcus aureus (MRSA), where the mode of action and associated cellular effects remain largely unexplored. This study aims to evaluate antibacterial activity of Limosilactobacillus fermentum YTPP05 isolated from pickled radish against MRSA. Upon the initial antibacterial evaluations, it was found that strain YTPP05 inhibited the growth of MRSA isolates. Multiplex PCR identified multiple resistance genes in our MRSA strains, including mecA, blaZ, and aacA genes, aligning with antibacterial susceptibility profiles determined by the disc diffusion assay. An agar overlay assay showed that YTPP05 possessed antibacterial potential, with the largest inhibition zone diameters of 40.83 ± 8.43 mm, while the inhibition zones of the Cell Free Supernatant (CFS) of YTPP05 by an agar well diffusion were 27.16 ± 2.93 mm against the MRSA isolates. The minimum inhibitory concentration and minimum bactericidal concentration of YTPP05-derived CFS were 125 mg/mL. Scanning Electron Microscopy (SEM) demonstrated YTPP05 extracts caused cell membrane disruption, bubble-like protrusion, and cell lysis. Collectively, this study highlights the anti-MRSA potential of YTPP05 as an alternative antimicrobial agent for combating MRSA infections.
In this paper, we present a geometric framework designed to determine both the strong coupling strength and the QCD scale from a unified mass–charge structure. We introduce a simple, dimensionless mass–charge identity linking the effective strong charge to the neutral–charged pion mass ratio, ( e / g s ) 2 + ( M π 0 / M π ± ) 2 = 1, which defines a strong-sector mixing angle θ S . Based on a discrete hierarchy of effective charges, the framework predicts a geometric angle of θ S ≈ −14.5° (for g s = 4 e ). This prediction accurately reproduces the observed neutral–charged pion mass ratio and geometrically characterizes the strong interaction as a binding-dominated regime. Building on the hierarchy 1 e →2 e →4 e , the strong fine-structure constant is obtained from a universal geometric relation, α = ( q / q pl ) 2 , in agreement with experimental determinations at the percent level without adjustable parameters. Moreover, the confinement mass scale is derived directly from the proton charge radius as m Λ = ℏ/( r p c ) ≈ m p /4, yielding a value consistent with the phenomenological QCD scale Λ QCD . Taken together, these results indicate that the electromagnetic, weak, and strong interactions can be consistently described within a unified geometric framework at the level of coupling strengths and characteristic mass scales.
A 5-hydroxy methyl furfural (5-HMF) is contemplated a key bio-based principles chemical that presents potential in important substrate of various bio-base polymer materials. A novel system of corn cob dehydrogenated with methanoic acid (HCOOH): sodium hydroxide base (NaOH) has been studied. The dehydrogenation process is suggested with HCOOH:NaOH utilizing of method 1 at 120 ⸰ C for 180 min obtained a maximum 5-Hydroxy Methyl Furfural yield (5-HMF yield) of 80.17 ± 0.11% when compared with 18.23 ± 0.05 % 5-HMF yield of method 2 and 8.92 ± 0.07 % of method 3, significantly. Interestingly, the% 5-HMF yield of humin can be enhanced by corn cob dehydrogenated with HCOOH:NaOH at 120 ⸰ C for 180 min all of methods. By considering the fourier transform infrared spectrometer analysis (FTIR analysis) of humin structure, the 5-HMF structure of corn cob dehydrogenated with HCOOH:NaOH at 120 ⸰ C for 180 min of method 1 can be appeared while the humin structure method 2 and 3 of HCOOH:NaOH dehydrogenation at 120⸰C for 180 min cannot be appeared, indicating that the high performance 5-HMF product can be activated with novel technique of green chemistry reaction through method 1 reaction. Furthermore, These green chemistry reaction technique is first reported, demonstrating that 5-HMF of corn con dehydrogenated with HCOOH:NaOH mixture solution.
This study investigated the effectiveness of two nanoemulsion-based plant hexane extract formulations, S4L0 and S3L1, for managing sweet potato weevils (SPW) under field conditions. The formulations, derived from star anise and long pepper hexane extracts, were tested alongside a synthetic insecticide (imidacloprid) and an untreated control using a randomized complete block design (RCBD) on farmer plots in Sa Kaeo Province, Thailand. Key determination parameters included SPW infestation levels, crop yield, pesticide residue levels, diversity of nontarget soil arthropods, and soil physicochemical properties. Field applications of S4L0 and S3L1 reduced SPW infestations to 3.6 +/- 4.3 and 11.1 +/- 5.0 insects per plant, respectively, significantly lower than in untreated plots (33.9 +/- 11.8 insects/plant). No detectable imidacloprid residues were found in tubers treated with S4L0 or S3L1, whereas imidacloprid-treated tubers retained residues of 0.335 and 0.144 ppm at 5 and 7 days after application. Sweet potato yields ranged from 310 to 440 g/plant, with no significant differences among treatments. The untreated plots supported greater diversity and abundance of non-target soil arthropods, while the imidaclopridtreated plots showed the lowest diversity. Soil properties, including bulk density, pH, electrical conductivity, and organic matter content, remained stable across treatments. Overall, S4L0 and S3L1 demonstrated effective pest suppression and minimal environmental impact, highlighting their potential as sustainable alternatives to synthetic insecticides for integrated pest management in sweet potato production.
