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Soil disinfestation with steam was evaluated as an alternative to fumigation. Following soil disinfestation, plant health has traditionally been measured using plant size and yield. Plant health can be measured in a timely manner more efficiently, more easily and non-destructively using image analysis. We hypothesized that plant health could be quantified and treatments can be differentiated using an RGB (Red, Green, Blue) image analysis program, particularly by observing the greenness of plant leaves. However, plant size or the proportion of green area could be unreliable due to plant loss and camera's position and angle. To this end, we decided to evaluate plant health by analyzing the RGB codes associated with the green color only, which detects the chlorophyll reflectance and nutrient status, noting that the degree of greenness within the green-leaf-area was not affected by the plant size. We identified five RGB codes that are commonly observed in the plant leaves and ordered them from dark green to light green. Among the five RGB codes, the relative percentage covered by the darkest green to the lightest green was significantly different between the steam and chloropicrin treatments and the control, and it was not significantly different between the steam and chloropicrin treatments. Furthermore, the result was correlated with the total yield, and the trend observed in the first year was replicated in the second year of this experiment. In this study, we demonstrate that the RGB image analysis can be used as an early marker of the treatment effect on the plant health and productivity.

Weeds are the major limitation to efficient crop production, and effective weed management is necessary to prevent yield losses due to crop-weed competition. Assessments of the relative efficacy of weed control treatments by traditional counting methods is labor intensive and expensive. More efficient methods are needed for weed control assessments. There is extensive literature on advanced techniques of image analysis for weed recognition, identification, classification, and leaf area, but there is limited information on statistical methods for hypothesis testing when data are obtained by image analysis (RGB decimal code). A traditional multiple comparison test, such as the Dunnett-Tukey-Kramer (DTK) test, is not an optimal statistical strategy for the image analysis because it does not fully utilize information contained in RGB decimal code. In this article, a bootstrap method and a Poisson model are considered to incorporate RGB decimal codes and pixels for comparing multiple treatments on weed control. These statistical methods can also estimate interpretable parameters such as the relative proportion of weed coverage and weed densities. The simulation studies showed that the bootstrap method and the Poisson model are more powerful than the DTK test for a fixed significance level. Using these statistical methods, three soil disinfestation treatments, steam, allyl-isothiocyanate (AITC), and control, were compared. Steam was found to be significantly more effective than AITC, a difference which could not be detected by the DTK test. Our study demonstrates that an appropriate statistical method can leverage statistical power even with a simple RGB index.

The birth prevalence of symptomatic congenital cytomegalovirus (cCMV) disease among live birth in Korea from a multicenter study was 0.06% during 2001–2015 with increasing frequency. The administrative prevalence of cCMV infection by big-data analysis from the national health insurance system was 0.01% and the average healthcare cost was US$2010 per person. [ABSTRACT FROM AUTHOR]

The aim of the present study is to explore the underlying hepatoprotective mechanism of PKC#963, consisting of Pinus koraiensis, Saururus chinensis, and Lycium barbarum in association with acute and chronic liver injury induced by alcohol or carbon tetrachloride (CCl4). Here, PKC#963 significantly suppressed aspartate aminotransferase (AST), alanine aminotransferase (ALT), phosphorylated signal transducer and activator of transcription 3 (p‐STAT3), inducible nitric oxide synthase (iNOS), and cyclooxygenase (COX‐2) in CCl4‐treated HepG2 cells. Also, PKC#963 significantly suppressed reactive oxygen species (ROS) production in HepG2 cells. Consistently, PKC#963 suppressed the expression of AST, ALT, p‐STAT3, iNOS, COX‐2, interleukin 6 (IL‐6), tumor necrosis factor alpha (TNF‐α) and α‐smooth muscle actin (α‐SMA) and increased procaspase 3 in the liver tissues of CCl4 treated rats. In addition, PKC#963 enhanced alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH) for alcohol metabolism, superoxide dismutase (SOD), and catalase as antioxidant enzymes and also suppressed AST and ALT in alcohol‐treated rats. Furthermore, PKC#963 reduced hepatic steatosis and necrosis in CCl4‐treated rats by H&E (Hematoxylin and Eosin) staining. Taken together, these findings highlight evidence that PKC#963 has hepatoprotective potential via inhibition of iNOS, COX‐2, and p‐STAT3 and enhancement of SOD and catalase. [ABSTRACT FROM AUTHOR]