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Application of a Spectroscopic Analysis-Based Portable Sensor for Phosphate Quantitation in Hydroponic Solutions
- Source :
- Journal of Sensors, Vol 2020 (2020)
- Publication Year :
- 2020
- Publisher :
- Hindawi Limited, 2020.
-
Abstract
- Hydroponic plant culturing requires the concentration of nutrients in the supplied solution to be maintained at a constant level. For example, phosphate ion concentration directly affects crop growth, which necessitates the development of convenient and rapid techniques for on-site phosphate quantitation. Herein, we developed a new low-cost colorimetric method of quick on-site phosphate quantitation based on a modification of the conventional molybdenum colorimetric method. Specifically, the nutrient solution treated with ascorbic acid and molybdate was analyzed by colorimetric method after 10 min incubation, and a phosphate quantitation protocol was proposed. To verify this protocol, 50 nutrient solution samples with concentrations of 0–200 ppm were used to develop a model and perform a validation experiment, and the PLSR (Partial Least Squares Regression) and PCR (Principal Component Regression) models were developed and validated using a crossvalidation method and sample transmission spectra. The PLSR model, employing smoothing preprocessing at a 5 nm wavelength spacing, exhibited the best prediction performance and showed an error of ~10% within the measurement range during verification. In addition, an artificial neural network-based model achieved R2=0.93 for the training set and R2=0.86 for the validation set. Finally, we developed convenient-to-use software for phosphate ion quantitation by the presented method and performed a demonstration test.
- Subjects :
- Chromatography
Training set
Article Subject
010401 analytical chemistry
Phosphate ion
02 engineering and technology
Molybdate
021001 nanoscience & nanotechnology
Ascorbic acid
Phosphate
01 natural sciences
0104 chemical sciences
chemistry.chemical_compound
chemistry
Control and Systems Engineering
Partial least squares regression
Principal component regression
T1-995
Electrical and Electronic Engineering
0210 nano-technology
Instrumentation
Smoothing
Technology (General)
Subjects
Details
- Language :
- English
- ISSN :
- 16877268
- Volume :
- 2020
- Database :
- OpenAIRE
- Journal :
- Journal of Sensors
- Accession number :
- edsair.doi.dedup.....6e83d9fcc1b2c5888e4a3f5e9fadc097