Biology subjects

Herrmann, I.

Publications and source records attributed to Herrmann, I..

3 recordsLinked to original sources

bioRxiv2023

Optimization of chickpea irrigation in a semi-arid climate based on morpho-physiological parameters

While the world population is steadily growing, the demand for plant-based protein in general, and chickpea in particular, is rising. Heatwaves and terminal drought are the main environmental constraints on chickpea production worldwide. Thus, developing better irrigation management for the chickpea agro-system can promote higher and more sustainable yields. Supplemental irrigation at the right timing and dose can increase yield dramatically. Here, we studied the response of a modern Kabuli chickpea cultivar to supplemental irrigation during the critical pod-filling period over three growing seasons (2019-2021) in northern Negev, Israel, under semi-arid conditions. Six irrigation treatments were applied based on irrigation factors of 0, 0.5, 0.7, 1.0, 1.2, and 1.4 of crop evapotranspiration (ET0) as measured by an on-site meteorological station. Morpho-physiological parameters and above-ground biomass accumulation were monitored throughout the cropping seasons, and the final grain yield was determined at maturation. Irrigation onset was determined based on plants leaf water potential ({Psi}LWP > 15 bar) in the field. Our results indicate that optimal water status (as reflected by pressure chamber values) was 12-14 bar during the irrigation period. Irrigation according to evapotranspiration (ET0) with an irrigation factor of 1.2 resulted in the highest grain yields over the three years. To ensure optimal water supply during the reproductive phase compatible with the crop water requirements, maintaining a 25 mm node length above the last fully developed pod and a 90 mm distance between the last fully developed pod to the stem apex is recommended. In conclusion, irrigation onset when the crop is already at mild drought stress, followed by sufficient irrigation while following the indicated morphology and water potential values, may help farmers optimize irrigation and maximize chickpea crop production. HighlightsO_LIChickpea irrigation is optimized based on meteorological data (ETc) and morphological traits. C_LIO_LIMorphological- not only physiological- traits can capture the dynamics of crop water status. C_LIO_LIIrrigation onset should be at mild drought stress (>15 bar) during the reproductive stage. C_LIO_LIExtending the reproductive phase is essential for grain yield improvement under semi-arid conditions. C_LIO_LIIF=1.2 provides the most productive irrigation regime for chickpea in Mediterranean conditions. C_LI

plant biology↗

bioRxiv2021

Particle interactions and their effect on magnetic particle imaging and spectroscopy

Tracer and thus signal stability is crucial for an accurate diagnosis via magnetic particle imaging (MPI). However, MPI-tracer nanoparticles frequently agglomerate during their in vivo applications leading to particle interactions. Here, we investigate the influence of such magnetic coupling phenomena on the MPI signal. We prepared and characterized Zn0.4Fe2.6O4 nanoparticles and controlled their interparticle distance by variying SiO2 coating thickness. The silica shell affected the magnetic properties indicating stronger particle interactions for a smaller interparticle distance. The SiO2-coated Zn0.4Fe2.6O4 outperformed the bare sample in magnetic particle spectroscopy (MPS) in terms of signal/noise, however, the shell thickness itself only weakly influenced the MPS signal. To investigate the importance of magnetic coupling effects in more detail, we benchmarked the MPS signal of the bare and SiO2-coated Zn-ferrites against commercially available PVP-coated Fe3O4 nanoparticles in water and PBS. PBS is known to destabilize nanoparticles mimicking an agglomeration in vivo. The bare and coated Zn-ferrites showed excellent signal stability, despite their agglomeration in PBS. We attribute this to their aggregated morphology formed during their flame-synthesis. On the other hand, the MPS signal of commercial PVP-coated Fe3O4 strongly decreased in PBS compared to water, indicating strongly changed particle interactions. The relevance of this effect was further investigated in a mammalian cell model. For PVP-coated Fe3O4, we could detect a strong discrepancy between the particle concentration obtained from the MPS signal and the actual concentration determined via ICP-MS. The same trend was observed during their MPI analysis; while SiO2-coated Zn-ferrites could be precisely located in water and PBS, PVP-coated Fe3O4 could not be detected in PBS at all. This drastically limits the sensitivity and also general applicability of MPI using such standard commercial tracers and highlights the advantages of our flame-made Zn-ferrites concerning signal stability and ultimately diagnostic accuracy.

bioengineering↗

bioRxiv2021

Spectral estimation of in-vivo wheat chlorophyll a/b ratio under contrasting water availabilities

To meet the ever-growing global population necessities, it is needed to identify climate change-relevant plant traits to integrate into breeding programs. Developing new tools for fast and accurate estimation of chlorophyll parameters, chlorophyll a (Chl-a), chlorophyll b (Chl-b) content, and their ratio (Chl-a/b), can promote breeding programs of wheat with enhanced climate adaptively. Spectral reflectance of leaves is affected by changes in pigments concentration and can be used to estimate chlorophyll parameters. The current study identified and validated the top spectral indices known and developed new vegetation indices (VIs) for Chl-a and Chl-b content estimation and used them to non-destructively estimate Chl-a/b values and compare them to hyperspectral estimations. Three wild emmer introgression lines, with contrasting drought stress responsiveness dynamics, were selected. Well and limited irrigation irrigation regimes were applied. The wheat leaves were spectrally measured with a handheld spectrometer to acquire their reflectance at the 330 to 790 nm range. Regression models based on calculated VIs as well as all hyperspectral curves were calibrated and validated against chlorophyll extracted values. The developed VIs resulted in high accuracy of Chl-a and Chl-b estimation allowing indirect non-destructive estimation of Chl-a/b with root mean square error (RMSE) values that could fit 6 to 10 times in the range of the measured values. They also performed similarly to the hyperspectral models. Altogether, we present here a new tool for a non-destructive estimation of Chl-a/b which can serve as a basis for future breeding efforts of climate-resilience wheat as well as other crops.

physiology↗