Magnetic resonance imaging, water relation, gene expression and biochemical data for analysis of the effects of water stress on potato plant functioning and tuber development and quality.

The data presented in this paper include the original and processed MRI images acquired with a 1.5 T whole-body MRI scanner, describing the growth kinetics, spatialization and appearance of internal defaults of individual tubers of potato plants (Rosanna cultivar of Solanum tuberosum) grown in pots in a semi-controlled environment and exposed to two water regimes. The 2 conditions were a well-watered regime, in which soil moisture was maintained at 70 % of field capacity, and a variable water deficit regime, in which soil moisture was reduced to 20 % of field capacity several times during tuber growth, followed each time by a few-day period of rehydration to 70 % of field capacity. These data are supplemented by physiological, biochemical and gene expression data obtained from the leaves and tubers of additional potato plants grown under the same conditions. All these data contribute to highlight the long-term effects of water stress on plant functioning with a particular focus on the growth kinetics, spatialization and quality of potato tubers. The dataset presented here is related to the research article entitled "Growth kinetics, spatialization and quality of potato tubers monitored in situ by MRI - long-term effects of water stress". It is made publicly available to enable extended analyzes. It is a useful resource for biologists, agronomists and breeders interested in the potato crop, as well as for researchers interested in developing new imaging methods. All data can be used to improve databases on development and quality of tubers and to feed and validate mathematical models.

Growth kinetics, spatialization and quality of potato tubers monitored in situ by MRI - long-term effects of water stress.

Understanding the potato tuber development and effects of drought at key stages of sensitivity on yield is crucial, particularly when considering the increasing incidence of drought due to climate change. So far, few studies addressed the time course of tuber growth in soil, mainly due to difficulties in accessing underground plant organs in a non-destructive manner. This study aims to understand the tuber growth and quality and the complex long-term effects of realistic water stress on potato tuber yield. MRI was used to monitor the growth kinetics and spatialization of individual tubers in situ and the evolution of internal defects throughout the development period. The intermittent drought applied to plants reduced tuber yield by reducing tuber growth and increasing the number of aborted tubers. The reduction in the size of tubers depended on the vertical position of the tubers in the soil, indicating water exchanges between tubers and the mother plant during leaf dehydration events. The final size of tubers was linked with the growth rate at specific developmental periods. For plants experiencing stress, this corresponded to the days following rewatering, suggesting tuber growth plasticity. All internal defects occurred in large tubers and within a short time span immediately following a period of rapid growth of perimedullary tissues, probably due to high nutrient requirements. To conclude, the non-destructive 3D imaging by MRI allowed us to quantify and better understand the kinetics and spatialization of tuber growth and the appearance of internal defects under different soil water conditions.

Characterization of Potato Tuber Tissues Using Spatialized MRI T2 Relaxometry.

Magnetic Resonance Imaging is a powerful non-destructive tool in the study of plant tissues. For potato tubers, it greatly assists the study of tissue defects and tissue evolution during storage. This paper describes the MRI analysis of potato tubers with internal defects in their flesh tissue at eight sampling dates from 14 to 33 weeks after harvest. Spatialized multi-exponential T2 relaxometry was used to generate bi-exponential T2 maps, coupled with a classification scheme to identify the different T2 homogeneous zones within the tubers. Six classes with statistically different relaxation parameters were identified at each sampling date, allowing the defects and the pith and cortex tissues to be detected. A further distinction could be made between three constitutive elements within the flesh, revealing the heterogeneity of this particular tissue. Relaxation parameters for each class and their evolution during storage were successfully analyzed. The work demonstrated the value of MRI for detailed non-invasive plant tissue characterization.

Characterization of the Water Shortage Effects on Potato Tuber Tissues during Growth Using MRI Relaxometry and Biochemical Parameters.

The potato is one of the most cultivated crops worldwide, providing an important source of food. The quality of potato tubers relates to their size and dry matter composition and to the absence of physiological defects. It depends on the spatial and temporal coordination of growth and metabolic processes in the major tuber tissues: the cortex, flesh and pith. In the present study, variations in the biochemical traits of each of these tissues were investigated during tuber growth under optimal and water-deficit conditions. MRI relaxometry was used as a non-invasive and quantitative method to access information on cellular water status. The presence of slight but significant variations in organic compound contents quantified in the cortex and flesh revealed a tissue-dependent metabolic pattern. The T2 and relative I0 of the bi-exponential relaxation signal allowed a distinction to be made between the pith and the cortex, whereas the flesh could be differentiated from these tissues only through its relative I0. T2 values did not vary significantly during tuber development, in accordance with the typical growth pattern of tubers, but were shown to be sensitive to water stress. The interpretation of the multi-exponential transverse relaxation times is discussed and could be further developed via microscopic analysis.

High-resolution 1H NMR profiling of triacylglycerols as a tool for authentication of food from animal origin: Application to hen egg matrix.

Metabolomics of complex biological matrices conducted by means of 1H NMR leads to spectra suffering from severe signal overlapping. Previously, we have developed a high-resolution spectral treatment method to help solving this issue in 1H NMR of triacylglycerols. In this work, we tested the potential of the developed method in the characterization and authentication of food products from animal origin using egg yolk as a model matrix. The approach consisted in a spectral deconvolution guided by the precision obtained on the deconvoluted peaks after reference lineshape adjustment of spectra. Thus, 135 peaks were quantitated and successfully used as biomarkers of origin, of hens breed, and of farming system. This required multivariate statistical analyses for classification. The same pool of variables allowed construction of multivariate quantitation models for individual fatty acids. Furthermore, minute amounts of conjugated fatty acids were quantitated and used as fingerprints of samples from backyard and free-range farming.

Metabisotopomics of triacylglycerols from animal origin: A simultaneous metabolomic and isotopic profiling using 13C INEPT.

In previous works, we developed a 13C NMR method for analyzing triacylglycerols in olive oil using an adiabatic refocused INEPT sequence. This allowed spectral acquisition to be done in only 8 min with sufficient precision for isotopic measurements. In the present study, we made use of the same methodology to investigate the potential of triacylglycerols as source of biomarkers in animal origin matrices. To this end, egg yolk was taken as a model matrix. We called our profiling approach metabisotopomics since it was simultaneously metabolomic and isotopic profiling. Beside its ability to quantitate several fatty acids, metabisotopomics of triacylglycerols in egg yolk allowed the multivariate classification of samples according to the hen breed, to the farming system and origin. Achieved results confirmed our presumption that 13C metabisotopomics of triacylglycerols from animal sources is a powerful tool for metabolic studies as well as for food authentication processes.

Improved lipid mixtures profiling by 1H NMR using reference lineshape adjustment and deconvolution techniques.

ANALYSIS: of one-dimensional 1H NMR spectra of complex mixtures, such as lipids from natural extracts, is hampered by the small spectral width leading to a great number of overlapped signals. Additional complications including lineshape broadening and distortion may occur due to magnetic field inhomogeneity. Quantitation of such spectra is therefore challenging. We present in this work a quantitation approach based on deconvolution after correction of spectra by means of reference lineshape adjustment (RLA), also known as reference deconvolution. Spectral fit and precision obtained on deconvoluted peaks were used as indicators to iteratively improve the deconvolution process. This approach was tested on 1H NMR spectra of olive oil samples and allowed extraction of 77 peaks (available as peak intensities or areas), whereas spectral integration afforded 5 variables when only well-resolved signals were considered and 29 variables when a bucket around each discernible peak was integrated. Deconvoluted peak intensities and areas were obtained with improved precision after RLA of raw spectra. The use of these spectral variables as predictors in multivariate statistical analysis enhanced the classification of olive oil samples according to the altitude of the olive field or to the color of the olive drupes. The same variables allowed quantitation of oleic, palmitoleic, and vaccenic acids within triacylglycerols, which was not possible by 1H NMR, and improved quantitation of linoleic and linolenic acids. These results proved the high potential of the presented approach in the characterization and authentication of complex mixtures by 1H NMR spectroscopy.

Cholesterol, a powerful 13C isotopic biomarker.

Cholesterol is related to many health diseases and is considered as a metabolic disorder biomarker. This compound, present in all food products of animal origin, can also be used as food authentication biomarker. In this work and for the first time, positional 13C isotope contents were determined for such a high molecular weight compound. This was possible by means of NMR using adiabatic refocused INEPT. In order to test the potential of this approach for discrimination, hen eggs from different origins were collected. Quantitative extraction of egg yolk cholesterol was optimized, and partial reduced molar fractions of its different 13C isotopomers were used as predictors in discriminant analysis. Compared with the global 13C isotopic composition determined using isotope ratio monitoring by Mass Spectrometry, the relative content of cholesterol 13C isotopomers added valuable power to sample classifications according to their origins. This study paves the way to isotopomics of other steroids and similar molecular weight compounds.

Robust 1D NMR lineshape fitting using real and imaginary data in the frequency domain.

Quantitative NMR is intrinsically dependent on precise, accurate, and robust peak area calculation. In this work, we demonstrate how the use of complex-valued peak descriptions can improve peak fitting in the frequency domain - incorporating phase and baseline correction as well as apodization while working with commonly used Fourier-transformed data. The method has been implemented in an open source R package called rnmrfit that is available for download on GitHub (https://github.com/ssokolen/rnmrfit). Application to real data suggests that this approach can also result in dramatically higher precision than can be achieved with existing software. Simulation data indicates that coefficients of variation below 0.1% can be readily achieved at signal to noise (SNR) ratios of approximately 100. The use of complex-valued data in the frequency domain is demonstrated as a relatively simple and effective means of improving peak fitting for quantitative NMR analysis.