A new automated plant pigment analysis system

Importance of the topic

Photosynthetic pigment concentration is a key measure of algal biomass and water productivity. Ratios of pigments offer insight into community composition and physiological status. Reliable pigment analysis underpins water quality management and early warning of algal blooms.

Goals and overview

This study aimed to accelerate pigment extraction and analysis by combining pre and post sonication freezing with automation. A second goal was to streamline spectrophotometric measurements of chlorophylls a b c and phaeopigments in acetone methanol and ethanol extracts to deliver same day results with improved precision.

Methodology

Water samples were collected with Ruttner bottles from various depths and filtered on 1.2 μm glass fiber filters within eight hours. Pigments were extracted in cold aqueous acetone methanol or ethanol using a novel freezing sonication protocol to maximize recovery and minimize degradation. Optical densities at 480 510 630 647 649 664 665 and 750 nm were measured before and after acidification.

Instrumentation

• Double beam scanning Cary 1 spectrophotometer
• SPS 5 autosampler
• Computer control system with custom software for automated scanning acidification and calculation

Main results and discussion

The automated system reduced analysis time from 8–12 minutes to about one minute per sample. Precision was high with coefficients of variation below 11% for chlorophyll variants and phaeopigments. Accuracy was validated against pure chlorophyll standards with errors under ±5%. Comparative tests across dam water urban runoff pure algal cultures and sea water showed consistent results with existing manual methods.

Benefits and practical applications

• High throughput enabling hundreds of results in a single day
• Early detection of algal blooms and taste odour events
• Cost effective operation and resource savings
• Enhanced quality assurance through automated data handling

Future trends and possibilities

Further integration with data analytics and remote monitoring could enable real time water quality assessment. Extension to a broader range of pigments chromatographic coupling and miniaturized in situ sensors represent emerging directions. Automated systems may support continuous field deployment and networked environmental monitoring.

Conclusion

The development of an automated pigment analysis system markedly improves speed precision and cost efficiency of chlorophyll and phaeopigment measurements. This advance supports timely water resource management and provides a scalable platform for future methodological enhancements.

References

1. Standard Methods for Examination of Water and Wastewater 17th ed APHA 1990
2. SCOR/UNESCO Determination of Photosynthetic Pigments in Sea Water Monograph on Ocean Method No 1 1991
3. Jeffrey SW Humphrey GF New spectrophotometric equations for determining chlorophylls a b c Biochemie und Physiologie der Pflanzen 167 1975
4. Marker AFH Crowther CA Gunn RJM Methanol and acetone as solvents for estimating chlorophyll a and phaeopigments by spectrophotometry Archiv fuer Hydrobiologie 1980
5. Wintermans IFGM de Mots A Spectrophotometric characteristics of chlorophylls a and b and their pheophytins in ethanol Biochimica et Biophysica Acta 109 1969
6. Lorenzen CJ Determination of chlorophyll and phaeopigments spectrophotometric equations Limnology and Oceanography 12 1967