Development of a potassium-selective optode for hydroponic nutrient solution monitoring

Comparative analysis of a bulk optode based on a valinomycin ionophore and a nano-optode in micelles with pluronic F-127 for the quantification of potassium in aqueous solutions

In this work, two types of optical sensors were prepared for the quantification of potassium: the bulk optode (BO) and nano-optode (NO). The BO was prepared using three main components: the ionophore valinomycin, the ion exchanger tetrakis(4-chlorophenyl) potassium borate (K-TCPB), and the chromoionophore ETH 5294 (CHI). The optimal composition was found to be in a ratio of [1 : 1 : 1]. The NO was prepared by miniaturizing the BO through sonication in surfactant Pluronic F-127. The working range for the linear calibration model of BO was from 10-6 to 1.0 M K+ with a LODBO = 0.31 μM, meanwhile for NO was from 10-4 to 1.0 M K+ with a LODNO = 30.3 μM. Both optodes were tested for selectivity towards K+ in the presence of alkaline and alkaline earth ions, with a selectivity coefficient > 1.0. Furthermore, precision and stability studies of BO and NO were performed for three levels of K+ concentrations, 10-6, 10-3, 1.0 M for BO and 10-4, 10-2, 1.0 M for NO, showing a good homogeneity of the NO in the whole concentration range. However, an excessive variability was obtained for BO at 1.0 M K+. Therefore, the NO represents a potential tool for quantification of K+.

A low-cost spectroscopic nutrient management system for Microscale Smart Hydroponic system

Hydroponics offers a promising approach to help alleviate pressure on food security for urban residents. It requires minimal space and uses less resources, but management can be complex. Microscale Smart Hydroponics (MSH) systems leverage IoT systems to simplify hydroponics management for home users. Previous work in nutrient management has produced systems that use expensive sensing methods or utilized lower cost methods at the expense of accuracy. This study presents a novel inexpensive nutrient management system for MSH applications that utilises a novel waterproofed, IoT spectroscopy sensor (AS7265x) in a transflective application. The sensor is submerged in a hydroponic solution to monitor the nutrients and MSH system predicts the of nutrients in the hydroponic solution and recommends an adjustment quantity in mL. A three-phase model building process was carried out resulting in significant MLR models for predicting the mL, with an R2 of 0.997. An experiment evaluated the system's performance using the trained models with a 30-day grow of lettuce in a real-world setting, comparing the results of the management system to a control group. The sensor system successfully adjusted and maintained nutrient levels, resulting in plant growth that outperformed the control group. The results of the models in actual deployment showed a strong, significant correlation of 0.77 with the traditional method of measuring the electrical conductivity of nutrients. This novel nutrient management system has the potential to transform the way nutrients are monitored in hydroponics. By simplifying nutrient management, this system can encourage the adoption of hydroponics, contributing to food security and environmental sustainability.

Recycling nutrients from organic waste for growing higher plants in the Micro Ecological Life Support System Alternative (MELiSSA) loop during long-term space missions

Space agencies are developing Bioregenerative Life Support Systems (BLSS) in view of upcoming long-term crewed space missions. Most of these BLSS plan to include various crops to produce different types of foods, clean water, and O2 while capturing CO2 from the atmosphere. However, growing these plants will require the appropriate addition of nutrients in forms that are available. As shipping fertilizers from Earth would be too costly, it will be necessary to use waste-derived nutrients. Using the example of the MELiSSA (Micro-Ecological Life Support System Alternative) loop of the European Space Agency, this paper reviews what should be considered so that nutrients recycled from waste streams could be used by plants grown in a hydroponic system. Whereas substantial research has been conducted on nitrogen and phosphorus recovery from human urine, much work remains to be done on recovering nutrients from other liquid and solid organic waste. It is essential to continue to study ways to efficiently remove sodium and chloride from urine and other organic waste to prevent the spread of these elements to the rest of the MELiSSA loop. A full nitrogen balance at habitat level will have to be achieved; on one hand, sufficient N2 will be needed to maintain atmospheric pressure at a proper level and on the other, enough mineral nitrogen will have to be provided to the plants to ensure biomass production. From a plant nutrition point of view, we will need to evaluate whether the flux of nutrients reaching the hydroponic system will enable the production of nutrient solutions able to sustain a wide variety of crops. We will also have to assess the nutrient use efficiency of these crops and how that efficiency might be increased. Techniques and sensors will have to be developed to grow the plants, considering low levels or the total absence of gravity, the limited volume available to plant growth systems, variations in plant needs, the recycling of nutrient solutions, and eventually the ultimate disposal of waste that can no longer be used.

HUM: A review of hydrochemical analysis using ultraviolet-visible absorption spectroscopy and machine learning

There is a need to develop improved methods for water quality analysis. Traditionally, water quality analysis is performed in a laboratory on discrete samples or in the field with simple sensors, but these methods have inherent limitations. Ultraviolet-visible absorption spectroscopy (UVAS) is a commonly used laboratory technique for water quality analysis and is being applied more broadly in combination with machine learning (ML) to allow for the detection of multiple analytes without sample pretreatments. This methodology (referred to here as Hydrochemical analysis using Ultraviolet-visible absorption spectroscopy and Machine learning; 'HUM') can be applied in the laboratory or in situ while requiring less time, labor, and materials compared to traditional laboratory analysis. HUM has been used for the quantification of a variety of chemicals in a variety of settings, but information is lacking related to instrumental setup, sample requirements, and data analysis procedures. For instance, there is a need to investigate the influence of spectral parameters (e.g., sensitivity, signal-to-noise ratio, and spectral resolution) on measurement error. There is also a lack of research aimed at developing ML algorithms specifically for HUM. Finally, there are emerging concepts such as sensor fusion and model-sensor fusion which have been applied to similar fields but are not common in studies involving HUM. This review suggests the need for further studies to better understand the factors that influence HUM measurement accuracy along with the need for hardware and software developments so that the methodology can ultimately become more robust and standardized. This, in turn, could increase its adoption in both academic and non-academic settings. Once the HUM methodology has matured, it could help to reduce the environmental impacts of society by improving our understanding and management of environmental systems through high-frequency data collection and automated control of water quality in environmentally relevant systems.

Optical Sensors for Bacterial Detection

Analytical devices for bacterial detection are an integral part of modern laboratory medicine, as they permit the early diagnosis of diseases and their timely treatment. Therefore, special attention is directed to the development of and improvements in monitoring and diagnostic methods, including biosensor-based ones. A promising direction in the development of bacterial detection methods is optical sensor systems based on colorimetric and fluorescence techniques, the surface plasmon resonance, and the measurement of orientational effects. This review shows the detecting capabilities of these systems and the promise of electro-optical analysis for bacterial detection. It also discusses the advantages and disadvantages of optical sensor systems and the prospects for their further improvement.

Paper-based cation-selective optode sensor containing benzothiazole calix[4]arene for dual colorimetric Ag+ and Hg2+ detection

A new paper-based analytical device based on bulk ion-selective optodes (ISOs) for dual Ag⁺ and Hg²⁺ detection has been developed. A plasticized PVC hydrophobic phase composed of 25,27-di(benzothiazolyl)-26,28-hydroxycalix[4]arene (CU1) as an ion-selective ionophore, potassium tetrakis(4-chlorophenyl)borate as an ion-exchanger and chromoionophore XIV as a lipophilic pH indicator was entrapped in the pores of cellulose paper. This paper strip showed higher selectivity for Ag⁺ and Hg²⁺ over common alkali, alkaline earth and some transition metal ions with a color change from blue to yellow. With the proposed sensor, Ag⁺ and Hg²⁺ can be measured with the range of 1.92 × 10^-6 to 5.00 × 10^-3 M for Ag⁺ and 5.74 × 10^-7 to 5.00 × 10^-5 M for Hg²⁺ with a limit of detection of 1.92 × 10^-6 M for Ag⁺ and 5.74 × 10^-7 M for Hg²⁺. The proposed sensor was successfully applied to determine the amount of mercury in various water sources and the amount of silver in cleaning product samples containing silver nanoparticles (AgNPs). The results were in good agreement with inductively couple plasma-optical emission spectrometric measurements (ICP-OES).

Impedance-based sensor for potassium ions

A conductometric sensor for potassium ions in solution is presented. Interdigitated, planar gold electrodes were coated with a potassium-selective polymer membrane composed of a poly(vinyl chloride) matrix with about 65 wt% of plasticiser and 2-5 wt% of a potassium-selective ionophore. The impedance of the membrane was measured, using the electrodes as a transducer, and related to the concentration of potassium in a sample solution in contact with the membrane. Sensitivity was optimised by varying the sensor components, and selectivity for potassium over sodium was also shown. The resulting devices are compact, miniature, robust sensors which, by means of impedance measurements, eliminate the need for a reference electrode. The sensor was tested for potassium concentration changes of 2 mM across the clinically relevant range of 2.7-18.7 mM.

Ion-specific nutrient management in closed systems: the necessity for ion-selective sensors in terrestrial and space-based agriculture and water management systems

The ability to monitor and control plant nutrient ions in fertigation solutions, on an ion-specific basis, is critical to the future of controlled environment agriculture crop production, be it in traditional terrestrial settings (e.g., greenhouse crop production) or as a component of bioregenerative life support systems for long duration space exploration. Several technologies are currently available that can provide the required measurement of ion-specific activities in solution. The greenhouse sector has invested in research examining the potential of a number of these technologies to meet the industry's demanding requirements, and although no ideal solution yet exists for on-line measurement, growers do utilize technologies such as high-performance liquid chromatography to provide off-line measurements. An analogous situation exists on the International Space Station where, technological solutions are sought, but currently on-orbit water quality monitoring is considerably restricted. This paper examines the specific advantages that on-line ion-selective sensors could provide to plant production systems both terrestrially and when utilized in space-based biological life support systems and how similar technologies could be applied to nominal on-orbit water quality monitoring. A historical development and technical review of the various ion-selective monitoring technologies is provided.