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| Home > Publications database > NMR Relaxometry for the Study of Water and Dry Matter in Living Plants: Faster, Simpler and Sensor-Like |
| Poster (After Call) | FZJ-2026-01206 |
;
2025
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Please use a persistent id in citations: doi:10.34734/FZJ-2026-01206
Abstract: The greates challenge for the routine characterisation of intact, growing plant organs by Time Domain (TD-) NMR relaxometry is dealing with the complexity of their NMR relaxometric signature. Plants consist of many types of tissues, with cells, cell walls, organelles and types of vasculature that vary in size and composition with species, organ, developmental stage and age. The physicochemical makeup of intact plants thus is characterized by a multitude of varying compartments and components. This complexity can be dealt with using multi-dimensional TD-NMR approaches, but these are time-consuming and require expert operators. To be useful for the plant sciences, a much faster and sensorlike approach is needed. Recently a simple T2 weighted, sensor-like approach, the Solid Liquid Content (SLC) method, was proposed that yielded linear correlations between total proton density (PDtot) and fresh weight (FW), and a T2 weighted measure (PDliq) that correlated surprisingly well with water weight (WW) [1]. The correlations however are not unique and vary with species, organ and developmental stage. This necessitates re-calibration of the method for such cases. Further, deviations from the linear correlation were observed for samples with especially high solid matter contents. In this contribution, we test a) how sensitive the results of this sensor like method are to changes in the makup of the plant material; b) if it is possible to classify plant material on basis of the TD-relaxometric signature and predict their calibration function; and c) we explore what happens with the correlation functions at especially low water contents.The SLC method utilizes an FID-Carr-Purcell-Meiboom-Gill (CPMG) measurement sequence. Based on this, PDtot is estimated by extrapolating the NMR signal to time zero using a mono-exponential fit applied to the first 75μs of the FID. PDliq is approximated by averaging the signal intensity of the data points in the 0-25ms time window of the CPMG. For our analysis, we applied the method to a range of plant organs stronlgy varying in their physicochemical properties (intact leaves of various species and wheat ears).Inline with previous observations, we obtained strong and linear correlations between the proton densities and the corresponding weight parameters for each species. Yet, our results indicate that both the estimation of PDtot and PDliq are (slightly) susceptible to the specific properties of the sample and sample water content (WC). Grouping samples of species with similar, but not identical behavior into calibration groups resulted in reduced predictive performance for both FW and WW (and their derivatives dry matter and water content). Additionally, in wheat ears the presence of a large fast decaying proton fraction (appearing for appr. WC<40%) resulted in an underestimation of PDtot and deviations from the linear correlation between PDliq/PDtot and WC. References[1] C.W. Windt, M. Nabel, J. Kochs, S. Jahnke, U.Schurr, A mobile NMR sensor and relaxometric method to non-destructively monitor water and dry matter content in plants, Frontiers in Plant Science,12 (2021).
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