Plant biomass has various compositions and structures at different scales (from the component organs to their constitutive tissues) to support its functional properties. Recovering each part of the plant without damaging its structure poses a challenge to preserving its original properties for differential dedicated end uses, and considerably increases its added value. In this work, an original combination of grinding based on shearing stress and separation based on particle size and density was successfully used to sort rind (65% w/w) and pith (35% w/w) from maize stem internodes. More than 97% of the rind was isolated. The pith alveolar structure was well preserved in coarse particles, making them suitable for insulation bio-based composite materials, a promising alternative to conventional nonbiodegradable insulation panels. Boards produced from the dry fractionated pith exhibited thermal conductivities like those produced from hand dissected pith, with values equal to 0.037 W·mK⁻¹ and 0.039 W·mK⁻¹, respectively. In the finest fraction (particle size <1 mm), the pith vascular bundles (around 300–400 µm in diameter) were dissociated from parenchyma cells and successfully isolated using a cutting-edge electrostatic separator. Their structures, which provide the plant structural support, make them potentially valuable for reinforcement in composite materials.

A quantitative histology of maize stems is needed to study the role of tissue and of their chemical composition in plant development and in their end-use quality. In the present work, a new methodology is proposed to show and quantify the spatial variability of tissue composition in plant organs and to statistically compare different samples accounting for biological variability. Multispectral UV/visible autofluorescence imaging was used to acquire a macroscale image series based on the fluorescence of phenolic compounds in the cell wall. A series of 40 multispectral large images of a whole internode section taken from four maize inbred lines were compared. The series consisted of more than 1 billion pixels and 11 autofluorescence channels. Principal Component Analysis was adapted and named large PCA and score image montages at different scales were built. Large PCA score distributions were proposed as quantitative features to compare the inbred lines. Variations in the tissue fluorescence were clearly displayed in the score images. General intensity variations were identified. Rind vascular bundles were differentiated from other tissues due to their lignin fluorescence after visible excitation, while variations within the pith parenchyma were shown via UV fluorescence. They depended on the inbred line, as revealed by the first four large PCA score distributions. Autofluorescence macroscopy combined with an adapted analysis of a series of large images is promising for the investigation of the spatial heterogeneity of tissue composition between and within organ sections. The method is easy to implement and can be easily extended to other multi–hyperspectral imaging techniques. The score distributions enable a global comparison of the images and an analysis of the inbred lines’ effect. The interpretation of the tissue autofluorescence needs to be further investigated by using complementary spatially resolved techniques.

Maize (Zea mays L.) is widely cultivated worldwide for food, feed, and fuel uses. Maize forage has become a valuable feed material, and there is much interest in characterizing its friability, as friability may shape feed value through its effect on ingestibility. The objective of this study was to characterize the friability of maize forage based on its milling behavior within a collection of inbred lines of maize. We proposed two friability indexes—Particle Size Reduction (PSR) and Energy Index—and evaluated their ability to discriminate 24 inbred maize lines differing in digestibility. Both the PSR Index and Energy Index effectively highlighted the variability in friability, which could vary by a factor of two regardless of index. These two friability indexes are based on two different milling technologies and therefore on different mechanical stresses inside the mills that could both inform on friability, but on different scales. In order to interpret the observed differences, we characterized the biomass at different scales, from phenotypic observation of the shoot to physical properties of the chopped maize, down to cell wall amount and composition. The friability assessed through these two indexes was mainly inter-correlated: the lower the milling energy, the more friable the fine particles produced. However, we also identified slight differences between the indexes that could be interpreted in relation to structural scale: while the Energy Index primarily informed friability at the cellular scale, the PSR Index also informed friability at the cell wall scale. This study provided key insight into the friability of maize forage and its relation to physical and fiber properties.