Irrigation management continues to be an important issue for tomato cultivation, especially in plant factories. Accurate and timely assessment of tomato leaf water status is a key factor in enabling appropriate irrigation, which can save nutrition solution and labor. In recent decades, hyperspectral imaging has been widely used as a nondestructive measurement method in agriculture to obtain plant biological information. The objective of this research was to establish an approach to obtain the tomato leaf water status—specifically, the relative water content (WC) and equivalent water thickness (MC)—for five different tomato cultivars in real time by using hyperspectral imaging. The normalized difference vegetation index (NDVI) and two-band vegetation index (TBI) analyses were performed on the tomato leaf raw relative reflection (RAW), the inversion-logarithm relative reflection (LOG), and the first derivative of relative reflection (DIFF) from wavelengths of 900 nm to 1700 nm. The best regression model for WC assessment was obtained by TBI regression using DIFF at wavelengths of 1410 nm and 1520 nm, and the best regression model for MC assessment was obtained by NDVI regression using RAW at wavelengths of 1300 nm and 1310 nm. Higher model performance was obtained with MC assessment than with WC assessment. The results will help improve our understanding of the relationship between hyperspectral reflectance and leaf water status.

Photoplethysmography is a widely used technique to noninvasively assess heart rate, blood pressure, and oxygen saturation. This technique has a large potential for further applications, for example in the field of physiological and mental health monitoring. However, advanced applications of photoplethysmography have been hampered by the lack of accurate and reliable methods to analyze the characteristics of the complex nonlinear dynamics of the photoplethysmogram. Methods of nonlinear time series analysis may be used to estimate the dynamical characteristics of the photoplethysmogram but they are highly influenced by the length of the time series, which is often limited in practical photoplethysmography applications. The aim of this study was to evaluate the error in the estimation of the dynamical characteristics of the photoplethysmogram associated to the limited length of the time series. The dynamical properties were evaluated using recurrence quantification analysis, and the estimation error was computed as a function of the length of the time series. Results demonstrated that properties such as de-terminism and entropy can be estimated with an error lower than 1% even for short photople-thysmogram recordings. Additionally, the lower limit for the time series length to estimate the average prediction time was computed.

Bifidobacteria capable of metabolizing human milk oligosaccharides (HMOs) regulate microbial balance and enhance immune defenses, yet their adhesive properties and pathogen-inhibitory capacity remain understudied. We examined auto-aggregation, surface hydrophobicity, adhesion, and pathogen antagonism in 12 HMO-metabolizing bifidobacterial strains isolated from infant feces, using Bifidobacterium longum subsp. infantis ATCC 15697 (BI_15697) and M63 (BI_M63) as reference strains. Bifidobacterium bifidum BB_Y10 and BB_Y22 exhibited the highest auto-aggregation, hydrophobicity, and adhesion. Adhesion assays using Caco-2 cells and mucin, combined with scanning electron microscopy (SEM) for qualitative morphological observation, revealed distinct surface characteristics among the strains. These morphological differences may be associated with, but do not directly establish, the observed variability in adhesion capacity. Surface-associated molecules, including surface layer proteins (SLPs), extracellular polysaccharides (EPS), and lipoteichoic acid (LTA), differentially contributed to adhesion across the strains. BB_Y10 and BB_Y22 demonstrated strong adhesive capacity and enhanced pathogen antagonism in competitive, exclusion, and displacement assays in vitro, suggesting their potential to inhibit pathogen colonization in future in vivo studies and identifying them as promising probiotic candidates for further development.