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In his more recent work, Henri Chanzy explored the nature of cellulose microfibrils that were biosynthesized in vitro, in the absence of physical confinement, i.e. external constraints due to the presence of a solid cell wall against which the nanofibrils would be deposited. Henri Chanzy and his colleagues found out by electron diffraction that cellulose IVI could be generated in the native cell wall. At the macroscopic scale, cellulose IVI could hardly be distinguished from cellulose Iβ in powder patterns because of the superimposition of the various signals. In the present work, the use of strongly textured flax or wood specimens was explored in order to generate strong longitudinal (or meridional) 00l patterns in a very wide range of the reciprocal space and with a high resolution. In order to do so, a diffractometer was used with a parafocusing geometry and long scans permitted to document the 002 to 0010 diffraction bands with accuracy, including the odd reflections that are normally present when dealing with cellulose IVI or imperfect forms of cellulose I. An omega scan also demonstrated the extreme selectivity of this setup and the very narrow orientation distribution of the sample. Surprisingly, this study showed that both flax fibres and fir wood contained three characteristic reflections that could be readily distinguished from one another and corresponded to characteristic interplanar spacings. A lineshape analysis using the Williamson–Hall approach and the Hosemann theory was performed on the flax sample. The results provide a better insight as to the longitudinal arrangement of cellulose in terms of domain sizes, microstrains or paracrystallinity. The three forms of order, characterized by various interplanar spacings, were present in different amounts in flax and fir, but the exact match of their interplanar spacing reveals some kind of possible universality in the cellulose arrangement. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Longitudinal orders in the flax cell wall re-examined by lineshape analysis of the X-ray diffraction 00l profile up to l = 10." The correction addresses issues with the conventions used in crystallography in the original publication. Specifically, the correct notation for referring to specific planes and reflections is clarified. Additionally, a correction is made to Figure 5, where the decimal separator in the y-axis should be a dot, not a comma. The corrected version of the article has been provided. The publisher, Springer Nature, remains neutral and unbiased in relation to jurisdictional claims and institutional affiliations. [Extracted from the article]

In Morocco, wheat production shows a high inter-annual variability due to uncertain rainfall. In view of the importance of this resource to the country's economy, it is important to gain a better understanding of the natural large-scale climate oscillation governing this variability. In this study, we analyzed de-trended (1) time series of common wheat yields (1983-2008) from 11 agricultural provinces that account for 80 % of national wheat production; (2) monthly rainfall and 10-day temperature from ten meteorological stations; (3) 10-day normalized difference vegetation index (NDVI) from the AVHRR sensor; (4) monthly atmospheric climate indices [North Atlantic Oscillation (NAO) and Scandinavian Pattern (SCA)] and monthly 500 hPa geopotentials fields; and (5) monthly sea surface temperature (SST) fields and indices (NIÑO3, Tropical North Atlantic and Tropical South Atlantic). The relationship between rainfall and temperature during tillering in early winter and grain filling in early spring and wheat yields already observed at the plot scale was also found to be significant at the provincial scale. The linkages between wheat yields and large scale climate have been analyzed for the first time over Morocco. In agreement with previous studies, results show a complex and competing influence of different climate phenomena. The NAO is found to be significantly related to yields during the early stage of wheat growth in December, whereas the SCA correlates with yields later in the season, in January and February. Interesting lagged correlations with higher lead time are also highlighted, with the leading modes of SST variability in the equatorial Atlantic during October (the 'Atlantic Niño' mode) and in the North Atlantic (the 'Atlantic tripole' mode) in February. Our conclusion is that regional climate indices and variables represent valuable information with which to increase lead time and skill regarding wheat yield predictions in Morocco. [ABSTRACT FROM AUTHOR]