Hirosaki University

Neighboring plants exchange adaptive information related to their genetic identity, stress experiences, and reproductive state. Here, we tested the possibility that Plantago asiatica plants utilize both above- and below-ground communication to differentially respond to stress cues perceived from neighbors with variable genetic identities. Stress response was observed by recording stomatal aperture in stressed plants and their neighbors while restricting interplant communication to either root or shoot cueing. Split-root plants were planted in triplets at equidistant intervals. Half of the roots of the central plant were subjected to salt stress, while the other half shared its rooting volume with the roots of an unstressed neighboring plant on one side, and its headspace with another unstressed neighbor on the other side. Sixty minutes after the onset of salt stress, soil-sharing neighbors had a larger proportion of closed stomata when the stressed plant was genetically closer (sibling [SB] or from a near population [NP]) than from a more remote population (FP). In contrast, aboveground stress cueing was equally effective regardless of the genetic relatedness of the neighboring plants. The findings demonstrate for the first time a concurrent utilization of both specific and nonspecific interplant stress cueing. The results call for further investigation into the adaptive implications of these communication modes on the survival and performance of P. asiatica under variable environmental scenarios.

To effectively utilize crop by-product resources, we developed a low-cost natural culture medium using rice straw as material, successfully synthesized a lactic acid bacteria (LAB) biofilm conducive to silage, and activated LAB activity to drive the silage fermentation process. Commercial freeze-dried LAB strains FG1 (Lactiplantibacillus plantarum) and TH14 (Lacticaseibacillus casei) and their corresponding culture medium, used for the preparation of silage from orchard grass and timothy grass. The crude protein and mineral content in fresh grass was higher than 14.4 % and 3.0 g/kg based on dry matter (DM), respectively, and formed a microbial biofilm structure and symbiotic network dominated by harmful microorganisms. Compared with the control and other treatments, silage prepared using the FG1 medium exhibited excellent fermentation quality, with pH and ammonia nitrogen content below 3.6 and 0.7 g/kg of fresh weight (FW) (P < 0.05), respectively, while lactic acid content exceeded 1.1 g/kg of FW (P < 0.05). The single LAB biofilm constructed using the FG1 medium developed in this study promoted a rapid shift in the silage biofilm community structure from Gram-negative to Gram-positive bacteria. Ultimately, a biofilm structure dominated by Lactiplantibacillus plantarum was formed. This structure effectively regulated the dynamic symbiotic network of silage fermentation microorganisms, increasing the relative abundance of Lactiplantibacillus plantarum to 35.4 %, significantly driving carbohydrate metabolism and global and overview map metabolic pathways while inhibiting amino acid metabolic pathways. This study achieved low-cost and high-quality silage fermentation by scientifically designing the biofilm structure of microorganisms related to silage fermentation.

Passive radon monitors with CR-39s are commonly used in major epidemiological studies. However, the conventional CR-39 track density analysis method makes it difficult to estimate the concentration accurately due to the heterogeneity of tracks on CR-39s and the small track reading area. Track heterogeneity in CR-39 detectors arises from exposure-related and detector-related factors. To improve the accuracy of track density analysis in passive radon monitors, this study implemented a new stochastic approach utilizing Latin Hypercube Sampling (LHS) to compare the performance to the conventional method. Consequently, the stochastic method reduces the root mean square deviation of mean track density by 15.6 % compared to the conventional method. The coefficient of determination of the stochastic method is significantly higher than that of the conventional method in the linear correlation of estimated track density and accumulated exposure. The stochastic method utilizing the LHS for track density analysis decreased the total counting area of CR-39 and performed congruently and effectively, as the large counting area using the conventional strategy. These findings suggest the stochastic approach is a promising method for improving track density determination in passive radon measurements with CR-39 detectors.