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Plant hormone Abscisic Acid (ABA) plays an important role in regulating plant growth. However, the content of ABA in plant tissues is very low, and rapid and sensitive detection methods are urgently needed. In this study, a rapid and quantitative ABA detection method was established based on aptamer recognition and surface-enhanced Raman spectroscop (SERS). The gold nanoparticles modified by ABA aptamer had the characteristics of SERS signal enhancement and selective recognition, realizing the rapid and sensitive detection of trace ABA in complex plant sample matrix. When ABA molecules appeared in detect system, the aptamer would specifically bind with ABA molecules, and the aptamer folded into G-tetrad structure at same time, which wrapped ABA molecules in the tetrad structure, shortened the distance between ABA molecules and gold nanoparticles, and the enhanced and stable ABA molecules SERS signal were obtained. Under the condition of optimized aptamer concentration at 0.12 µmol/L, different concentrations of ABA solutions in the detection system were detected. Within the concentration range of 0.1－100 µmol/L, the SERS intensity of ABA presented a good linear relationship with the concentration. The detection limit of this method was 0.1 µmol/L and the linear correlation coefficient R2 was 0.9855. The repeatability test of 20 points randomly on SERS substrate showed that the relative standard deviation (RSD) was 6.71%, indicating the stability of SERS substrate was well. Furthermore, the substrate of gold nanoparticles modified by the ABA aptamer terminal with sulfhydryl group (SH-Apt) could be stored in the refrigerator for more than half a year, indicating that the substrate has good stability. Once the preparation of the synthesized SH-Apt modified gold nanoparticles was completed. It could be used on demand without the need to prepare SERS substrate for every detection. In this sense, the constructed aptamer SERS biosensor could realize the rapid and quantitative detection of ABA. The method was used for the determination of ABA in wheat leaves, and the result was in good agreement with the Enzyme Linked Immunosorbent Assay (ELISA) (The max relative error was 9.13%). This biosensor is an exploratory study on the detection of plant hormones by SERS, and the results of the study will have important reference value for the subsequent quantitative and on-site detection of ABA, as well as the detection of other plant hormones.

Plants have evolved intricate signaling pathways, which operate as networks governed by feedback to deal with stressors. Nevertheless, the sophisticated molecular mechanisms underlying these routes still need to be comprehended, and experimental validation poses significant challenges and expenses. Consequently, computational hypothesis evaluation gains prominence in understanding plant signaling dynamics. Biosensors are genetically modified to emit light when exposed to a particular hormone, such as abscisic acid (ABA), enabling quantification. We developed computational models to simulate the relationship between ABA concentrations and bioluminescent sensors utilizing the Hill equation and ordinary differential equations (ODEs), aiding better hypothesis development regarding plant signaling. Based on simulation results, the luminescence intensity was recorded for a concentration of 47.646 RLUs for 1.5 μmol, given the specified parameters and model assumptions. This method enhances our understanding of plant signaling pathways at the cellular level, offering significant benefits to the scientific community in a cost-effective manner. The alignment of these computational predictions with experimental results emphasizes the robustness of our approach, providing a cost-effective means to validate mathematical models empirically. The research intended to correlate the bioluminescence of biosensors with plant signaling and its mathematical models for quantified detection of specific plant hormone ABA. [ABSTRACT FROM AUTHOR]

Background: This study explores the role of leguminous crops like lima bean in enhancing soil quality and ecosystem stability. Despite existing studies on agronomic aspects, there is a significant research gap on its impact on soil organic matter level, microbial activity, soil health, and nutrient availability. Therefore, this study examines the capacity of lima bean to reactivate soil quality, focusing on its impact on soil organic matter level, microbial activity, soil health, and nutrient availability. Methods: The experimental area was set up in 2023 using three replicates and a randomized block design. Two treatments were used: lima bean-planted plots and control plots with various weeds and without lima bean. Post-harvest soil samples were collected from various agroecological zones and sterilely packed, and physical, chemical, and biological indices were examined. Results: lima bean significantly affected nutrients, enzymes, soil microbial respiration, and other markers. Amylase activity (0.41**) was positively correlated with urease activity (0.73**), while dehydrogenase activity positively correlated with both. Dehydrogenase activity was negatively correlated with total nitrogen (0.66**) and sulfur (0.60**). Lima bean significantly affected soil quality, with all locations showing higher ratings (55–77%) than wild land, except for location D (Ilora). A total of 70% of total nitrogen variation may be attributed to soil quality (r2 = 0.696). Lima bean enhanced soil quality, potentially enhancing productivity and reducing dependence on inorganic nitrogen inputs. Conclusions: The symbiotic relationship between lima bean and nitrogen-fixing bacteria improves nutrient cycling, enhancing agricultural productivity and environmental conservation. Future research should explore the economic viability of integrating lima bean into crop rotations or agroforestry systems for sustainable agricultural practices, providing valuable information for farmers. [ABSTRACT FROM AUTHOR]

Accurate estimation of soil water content (SWC) is crucial for effective irrigation management and maximizing crop yields. Although dielectric property-based SWC measurements are widely used, their accuracy is still affected by soil variability, soil–sensor contact, and other factors, making the development of convenient and accurate soil-specific calibration methods a major challenge. This study aims to propose a plate compression filling technique for soil-specific calibrations and to monitor the extent of soil biomass degradation using dielectric properties. Before and after biodegradation, dielectric measurements of quartz sand and silt loam were made at seven different water contents with three different filling techniques. A third-order polynomial fitting equation explaining the dependence of the dielectric constant on the volumetric water content was obtained using the least-squares method. The suggested plate compression filling method has a maximum mean bias error (MBE) of less than 0.5%, according to experimental results. Depending on the water content, silt loam's dielectric characteristics change significantly before and after biodegradation. The best water content, measured in gravimetric units, to encourage the decomposition of biomass was discovered to be 24%. It has been demonstrated that the plate compression filling method serves as a simple, convenient, and accurate alternative to the uniform compaction method, while the dielectric method is a reliable indicator for evaluating biomass degradation. This exploration provides valuable insights into the complex relationship between SWC, biomass degradation, and soil dielectric properties. [ABSTRACT FROM AUTHOR]

Biological contact oxidation coupled with biological activated carbon process is proposed to solve the difficulties in achieving stable and high energy consumption treatment high salt sewage in refining and chemical enterprises. Salt-tolerant bacteria are successfully acclimated by gradually increasing the influent salt content, and then the biological contact oxidation unit is activated. The biofilm in the pool is well attached, and the denitrification and carbon removal effect is remarkable. The effluent COD can be stably controlled below 90 mg/L, and total nitrogen is below 15 mg/L. The results of flora analysis reveals in the high-salt sewage environment, significant alterations in the number and diversity of flora in the contact oxidation unit biofilm compared to the inoculated sludge. The predominant functional bacteria identified are Thiovirga, Thauera, Flavobacterium, Gemnobacter, Hydrogenophaga, etc. In the biological activated carbon unit, the organic combination of salt resistant and efficient bacterial agents with activated carbon has improved the resistance to influent COD fluctuations. A biofilm is formed on the surface of the activated carbon. The system operates stably. The effluent COD can be stably controlled below 60 mg/L, ammonia nitrogen is below 2 mg/L, and total nitrogen is below 15 mg/L. The entire process is centered around biodegradation, with a short process flow and low operating costs. This study provides technical support for the standard treatment of high salt sewage in refining and chemical enterprises. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3 ) represents a perilous gas that poses a substantial hazard to both human well-being and the environment, particularly within agricultural regions. Agricultural activities constitute a primary source of ammonia emissions. Thus, effective monitoring and measurement of ammonia sources in agriculture are imperative for mitigating its adverse impact. However, not all existing ammonia detection methods are suitable for discerning the low concentrations typically encountered in agricultural ammonia volatilizing (ranging from 0.01 to 5 parts per million). Consequently, curtailing ammonia volatilization from farmland assumes paramount importance, with real-time monitoring serving as a crucial mechanism for assessing environmental contamination and minimizing agricultural ammonia losses. Deploying appropriate detection methodologies ensures that requisite measures are taken to safeguard human health and the environment from the deleterious repercussions of ammonia exposure. The present paper introduces a comprehensive approach to detecting and analyzing ammonia in agricultural settings. It elucidates the merits and demerits of conventional indoor and outdoor ammonia detection methods, juxtaposing them with the innovative technology of Electronic nose (E-nose). Within the paper, seven widely employed ammonia detection methods in farmland are scrutinized and compared against traditional techniques. Additionally, the constructional aspects and distinct components of E-nose are meticulously delineated and appraised. Ultimately, the paper culminates in a comprehensive comparative analysis encompassing all the aforementioned methodologies, elucidating the potential and limitations of E-nose in facilitating ammonia detection endeavors within agricultural contexts. [ABSTRACT FROM AUTHOR]