Waterlogging and drought have become major challenges in many regions worldwide. Under water stress, plants exhibit a range of physiological and electrical responses, including changes measurable by electrical impedance spectroscopy (EIS). Monitoring these parameters can provide valuable insights into plant growth status under adverse conditions. This study investigated changes in relative chlorophyll content (SPAD), maximum photochemical efficiency (Fv/Fm), relative water content (RWC), non-structural carbohydrates (NSC), and EIS parameters in apple rootstocks subjected to different water stress treatments. Results indicated that all physiological indicators, except NSC, showed a declining trend under two water stress episodes. Critically, the initial water stress episode elicited significantly greater physiological disruption than its subsequent counterpart. This suggests that plants developed a degree of physiological adaptation—such as osmotic adjustment and enhanced antioxidant activity—reducing their sensitivity to subsequent stress. Correlation analysis revealed that high-frequency resistivity (r) and intracellular resistivity (r_i) were strongly associated with key physiological parameters. Thus, r and r_i may serve as effective indicators for assessing plant water stress status. Furthermore, classification algorithms—Fuzzy K-Nearest Neighbors (FKNN) and sparse Linear Discriminant Analysis (sLDA)—were applied to distinguish water status in apple rootstocks, achieving high classification accuracy. These findings provide a theoretical basis for improved water management in apple cultivation.

The microbiome in silage may vary substantially from the onset to the completion of fermentation. Improved additives and inoculants are being developed to accelerate the ensiling process, to enhance fermentation quality, and to delay spoilage during feed-out. However, current methods for preselecting and characterizing these amendments are time-consuming and costly. Here, we have developed a multi-sensor mini-bioreactor (MSMB) to track microbial fermentation in situ and additionally presented a mathematical model for the optimal assessment among candidate inoculants based on the Bolza equation, a fundamental formula in optimal control theory. Three sensors [pH, CO₂, and ethanol (EtOH)] provided data for assessment, with four additional sensors (O₂, gas pressure, temperature, and atmospheric pressure) to monitor/control the fermentation environment. This advanced MSMB is demonstrated with an experimental method for evaluating three typical species of lactic acid bacteria (LAB), Lentilactobacillus buchneri (LB) alone, and LB mixed with Lactiplantibacillus plantarum (LBLP) or with Enterococcus faecium (LBEF), all cultured in De Man, Rogosa, and Sharpe (MRS) broth. The fermentation process was monitored in situ over 48 h with these candidate microbial strains using the MSMB. The experimental results combine acidification characteristics with production of CO₂ and EtOH, optimal assessment of the microbes, analysis of the metabolic sensitivity to pH, and partitioning of the contribution of each species to fermentation. These new data demonstrate that the MSMB associated with the novel rapid data-processing method may expedite development of microbial amendments for silage additives.

HYDRUS-3D is a widely used software for modeling variably saturated water flow, but its performance under field conditions requires validation, particularly given the challenges of soil moisture detection. This study aimed to validate the accuracy of HYDRUS-3D in simulating soil water infiltration under drip irrigation using advanced horizontal mobile sensor systems (HMSSs). We designed a three-dimensional soil water infiltration experiment for drip-irrigated fields, employing two HMSSs which were orthogonally placed at 0.2 m and 0.4 m depths from the horizontal plane, and formed a trapezoidal configuration (height: 0.2 m, top edge width: 1 m) on the soil surface. These measurements provided three-dimensional data in the central area and two-dimensional data in the sloped sections. HYDRUS-3D simulations were compared to HMSS measurements, showing strong agreement in both the central area and sloped sections, with high R² values and low RMSE, indicating excellent model accuracy. These results confirm HYDRUS-3D’s reliability in simulating soil water movement under real-world conditions. In particular, the model effectively captured the horizontal fusion process of adjacent drip emitters, which advances its validation for field-scale applications and supports its use in precision agricultural water management.

Bulblet initiation in Lilium lancifolium is a critical yet understudied aspect of lily development. Prior research has predominantly focused on bulb production and tissue culture techniques, with limited exploration of regulatory mechanisms. This study investigates the initiation process through histological, biochemical, and molecular approaches. Scales from tissue-cultured bulblets were analyzed for sugar content and gene expression. Results revealed significant increases in sucrose levels at the scale base during culture, paralleled by transcriptomic enrichment in hormone signaling, cell cycle, DNA replication, and sugar metabolism pathways. These findings, validated by quantitative real-time polymerase chain reaction (qRT-PCR), offer valuable insights into the molecular basis of bulblet initiation in L. lancifolium, providing a foundation for future research into lily developmental mechanisms.