Effect of fermentation on nutrient composition, antinutrients, and mineral bioaccessibility of finger millet based Injera: A traditional Ethiopian food.

Finger millet, like other cereals, contains high amounts of antinutrients that bind minerals, making them unavailable for absorption. This study explores the effect of traditional fermentation on nutritional, antinutritional, and subsequent mineral bioaccessibility (specifically iron, zinc, and calcium) of finger millet based Injera. Samples of fermented dough and Injera prepared from light brown and white finger millet varieties were analyzed for nutritional composition, antinutritional content, and mineral bioaccessibility following standard procedures. With some exceptions, the proximate composition of fermented dough was significantly affected by fermentation time. Compared to unfermented flour, the phytate and condensed tannin content significantly (p < 0.05) decreased for fermented dough and Injera samples. A strong decline in phytate and condensed tannin content was observed in white finger millet Injera as fermentation time increased, compared to light brown finger millet based Injera. The mineral bioaccessibility of Injera prepared from finger millet and maize composite flour increased with fermentation time, leading to a significant increase in bioaccessible iron, zinc, and calcium, ranging from 15.4-40.0 %, 26.8-50.8 %, and 60.9-88.5 %, respectively. The results suggest that traditional fermentation can be an effective method to reduce phytate and condensed tannin content, simultaneously increasing the bioaccessibility of minerals in the preparation of finger millet based Injera.

In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model.

Computational tools that allow in silico analysis of the role of cell growth and division on photosynthesis are scarce. We present a freely available tool that combines a virtual leaf tissue generator and a two-dimensional microscale model of gas transport during C3 photosynthesis. A total of 270 mesophyll geometries were generated with varying degrees of growth anisotropy, growth extent, and extent of schizogenous airspace formation in the palisade mesophyll. The anatomical properties of the virtual leaf tissue and microscopic cross-sections of actual leaf tissue of tomato (Solanum lycopersicum L.) were statistically compared. Model equations for transport of CO2 in the liquid phase of the leaf tissue were discretized over the geometries. The virtual leaf tissue generator produced a leaf anatomy of tomato that was statistically similar to real tomato leaf tissue. The response of photosynthesis to intercellular CO2 predicted by a model that used the virtual leaf tissue geometry compared well with measured values. The results indicate that the light-saturated rate of photosynthesis was influenced by interactive effects of extent and directionality of cell growth and degree of airspace formation through the exposed surface of mesophyll per leaf area. The tool could be used further in investigations of improving photosynthesis and gas exchange in relation to cell growth and leaf anatomy.

Automatic analysis of the 3-D microstructure of fruit parenchyma tissue using X-ray micro-CT explains differences in aeration.

BACKGROUND: 3D high-resolution X-ray imaging methods have emerged over the last years for visualising the anatomy of tissue samples without substantial sample preparation. Quantitative analysis of cells and intercellular spaces in these images has, however, been difficult and was largely based on manual image processing. We present here an automated procedure for processing high-resolution X-ray images of parenchyma tissues of apple (Malus × domestica Borkh.) and pear (Pyrus communis L.) as a rapid objective method for characterizing 3D plant tissue anatomy at the level of single cells and intercellular spaces. RESULTS: We isolated neighboring cells in 3D images of apple and pear cortex tissues, and constructed a virtual sieve to discard incorrectly segmented cell particles or unseparated clumps of cells. Void networks were stripped down until their essential connectivity features remained. Statistical analysis of structural parameters showed significant differences between genotypes in the void and cell networks that relate to differences in aeration properties of the tissues. CONCLUSIONS: A new model for effective oxygen diffusivity of parenchyma tissue is proposed that not only accounts for the tortuosity of interconnected voids, but also for significant diffusion across cells where the void network is not connected. This will significantly aid interpretation and analysis of future tissue aeration studies. The automated image analysis methodology will also support pheno- and genotyping studies where the 3D tissue anatomy plays a role.

Synchrotron X-ray computed laminography of the three-dimensional anatomy of tomato leaves.

Synchrotron radiation computed laminography (SR-CL) is presented as an imaging method for analyzing the three-dimensional (3D) anatomy of leaves. The SR-CL method was used to provide 3D images of 1-mm² samples of intact leaves at a pixel resolution of 750 nm. The method allowed visualization and quantitative analysis of palisade and spongy mesophyll cells, and showed local venation patterns, aspects of xylem vascular structure and stomata. The method failed to image subcellular organelles such as chloroplasts. We constructed 3D computer models of leaves that can provide a basis for calculating gas exchange, light penetration and water and solute transport. The leaf anatomy of two different tomato genotypes grown in saturating light conditions was compared by 3D analysis. Differences were found in calculated values of tissue porosity, cell number density, cell area to volume ratio and cell volume and cell shape distributions of palisade and spongy cell layers. In contrast, the exposed cell area to leaf area ratio in mesophyll, a descriptor that correlates to the maximum rate of photosynthesis in saturated light conditions, was no different between spongy and palisade cells or between genotypes. The use of 3D image processing avoids many of the limitations of anatomical analysis with two-dimensional sections.

Prediction of water loss and viscoelastic deformation of apple tissue using a multiscale model.

A two-dimensional multiscale water transport and mechanical model was developed to predict the water loss and deformation of apple tissue (Malus × domestica Borkh. cv. 'Jonagold') during dehydration. At the macroscopic level, a continuum approach was used to construct a coupled water transport and mechanical model. Water transport in the tissue was simulated using a phenomenological approach using Fick's second law of diffusion. Mechanical deformation due to shrinkage was based on a structural mechanics model consisting of two parts: Yeoh strain energy functions to account for non-linearity and Maxwell's rheological model of visco-elasticity. Apparent parameters of the macroscale model were computed from a microscale model. The latter accounted for water exchange between different microscopic structures of the tissue (intercellular space, the cell wall network and cytoplasm) using transport laws with the water potential as the driving force for water exchange between different compartments of tissue. The microscale deformation mechanics were computed using a model where the cells were represented as a closed thin walled structure. The predicted apparent water transport properties of apple cortex tissue from the microscale model showed good agreement with the experimentally measured values. Deviations between calculated and measured mechanical properties of apple tissue were observed at strains larger than 3%, and were attributed to differences in water transport behavior between the experimental compression tests and the simulated dehydration-deformation behavior. Tissue dehydration and deformation in the high relative humidity range ( > 97% RH) could, however, be accurately predicted by the multiscale model. The multiscale model helped to understand the dynamics of the dehydration process and the importance of the different microstructural compartments (intercellular space, cell wall, membrane and cytoplasm) for water transport and mechanical deformation.

A plant cell division algorithm based on cell biomechanics and ellipse-fitting.

BACKGROUND AND AIMS: The importance of cell division models in cellular pattern studies has been acknowledged since the 19th century. Most of the available models developed to date are limited to symmetric cell division with isotropic growth. Often, the actual growth of the cell wall is either not considered or is updated intermittently on a separate time scale to the mechanics. This study presents a generic algorithm that accounts for both symmetrically and asymmetrically dividing cells with isotropic and anisotropic growth. Actual growth of the cell wall is simulated simultaneously with the mechanics. METHODS: The cell is considered as a closed, thin-walled structure, maintained in tension by turgor pressure. The cell walls are represented as linear elastic elements that obey Hooke's law. Cell expansion is induced by turgor pressure acting on the yielding cell-wall material. A system of differential equations for the positions and velocities of the cell vertices as well as for the actual growth of the cell wall is established. Readiness to divide is determined based on cell size. An ellipse-fitting algorithm is used to determine the position and orientation of the dividing wall. The cell vertices, walls and cell connectivity are then updated and cell expansion resumes. Comparisons are made with experimental data from the literature. KEY RESULTS: The generic plant cell division algorithm has been implemented successfully. It can handle both symmetrically and asymmetrically dividing cells coupled with isotropic and anisotropic growth modes. Development of the algorithm highlighted the importance of ellipse-fitting to produce randomness (biological variability) even in symmetrically dividing cells. Unlike previous models, a differential equation is formulated for the resting length of the cell wall to simulate actual biological growth and is solved simultaneously with the position and velocity of the vertices. CONCLUSIONS: The algorithm presented can produce different tissues varying in topological and geometrical properties. This flexibility to produce different tissue types gives the model great potential for use in investigations of plant cell division and growth in silico.