ALBERT

Description: Macroautophagy is a membrane-trafficking process that delivers cytoplasmic constituents to lysosomes for degradation. The process operates under basal conditions as a mechanism to turnover damaged or misfolded proteins and organelles. As a result, it has a major role in preserving cellular integrity and viability. In addition to this basal function, macroautophagy can also be modulated in response to various forms of cellular stress, and the rate and cargoes of macroautophagy can be tailored to facilitate appropriate cellular responses in particular situations. The macroautophagy machinery is regulated by a group of evolutionarily conserved autophagy-related (ATG) proteins and by several other autophagy regulators, which either have tissue-restricted expression or operate in specific contexts. We report here the characterization of a novel autophagy regulator that we have termed DRAM-3 due to its significant homology to damage-regulated autophagy modulator (DRAM-1). DRAM-3 is expressed in a broad spectrum of normal tissues and tumor cells, but different from DRAM-1, DRAM-3 is not induced by p53 or DNA-damaging agents. Immunofluorescence studies revealed that DRAM-3 localizes to lysosomes/autolysosomes, endosomes and the plasma membrane, but not the endoplasmic reticulum, phagophores, autophagosomes or Golgi, indicating significant overlap with DRAM-1 localization and with organelles associated with macroautophagy. In this regard, we further proceed to show that DRAM-3 expression causes accumulation of autophagosomes under basal conditions and enhances autophagic flux. Reciprocally, CRISPR/Cas9-mediated disruption of DRAM-3 impairs autophagic flux confirming that DRAM-3 is a modulator of macroautophagy. As macroautophagy can be cytoprotective under starvation conditions, we also tested whether DRAM-3 could promote survival on nutrient deprivation. This revealed that DRAM-3 can repress cell death and promote long-term clonogenic survival of cells grown in the absence of glucose. Interestingly, however, this effect is macroautophagy-independent. In summary, these findings constitute the primary characterization of DRAM-3 as a modulator of both macroautophagy and cell survival under starvation conditions.

Description: Variations in photosynthesis still cause substantial uncertainties in predicting photosynthetic CO 2 uptake rates and monitoring plant stress. Changes in actual photosynthesis that are not related to greenness of vegetation are difficult to measure by reflectance based optical remote sensing techniques. Several activities are underway to evaluate the sun-induced fluorescence signal on the ground and on a coarse spatial scale using space-borne imaging spectrometers. Intermediate-scale observations using airborne-based imaging spectroscopy, which are critical to bridge the existing gap between small-scale field studies and global observations, are still insufficient. Here we present the first validated maps of sun-induced fluorescence in that critical, intermediate spatial resolution, employing the novel airborne imaging spectrometer HyPlant . HyPlant has an unprecedented spectral resolution, which allows for the first time quantifying sun-induced fluorescence fluxes in physical units according to the Fraunhofer Line Depth Principle that exploits solar and atmospheric absorption bands. Maps of sun-induced fluorescence show a large spatial variability between different vegetation types, which complement classical remote sensing approaches. Different crop types largely differ in emitting fluorescence that additionally changes within the seasonal cycle and thus may be related to the seasonal activation and deactivation of the photosynthetic machinery. We argue that sun-induced fluorescence emission is related to two processes: (i) the total absorbed radiation by photosynthetically active chlorophyll and (ii) the functional status of actual photosynthesis and vegetation stress. This article is protected by copyright. All rights reserved.

Description: Fungicide intensity and sowing time influence the N use efficiency (NUE) of winter wheat but the underlying mechanisms, interactions of plant traits, and the temporal effects are not sufficiently understood. Therefore, organ-specific responses in NUE traits to fungicide intensity and earlier sowing were compared at two nitrogen (N) levels for six winter wheat cultivars in 2017. Plants were sampled at anthesis and at maturity and separated into chaff, grain, culms, and three leaf layers to assess their temporal contribution to aboveground dry matter (DM) and N uptake (Nup). Compared to the control treatment, across cultivars, the treatment without fungicide mostly exerted stronger and inverse effects than early sowing, on grain yield (GY, −12% without fungicide, +8% n.s. for early sowing), grain Nup (GNup, −9% n.s., +5% n.s.) as well as on grain N concentration (+4%, −2% n.s.). Grain yield in the treatment without fungicide was associated with similar total DM, as observed in the control treatment but with lower values in harvest index, thousand kernel weight, N use efficiency for GY (NUE) and N utilization efficiency. Lower GNup was associated with similar vegetative N uptake but lower values in N translocation efficiency and N harvest index. In contrast, early sowing tended to increase total DM at anthesis and maturity as well as post-anthesis assimilation, at similar harvest index and increased the number of grains per spike and total N use efficiency. Total N uptake increased after the winter season but was similar at anthesis. Although the relative N response in many traits was lower without fungicide, few fungicide x interactions were significant, and the sowing date did not interact either with N fertilization for any of the N and DM traits. The results demonstrate the positive effects of fungicides and earlier sowing on various traits related to yield formation and the efficient use of nitrogen and are discussed based on various concepts.

Description: Sensors, Vol. 18, Pages 2931: Evaluating RGB Imaging and Multispectral Active and Hyperspectral Passive Sensing for Assessing Early Plant Vigor in Winter Wheat Sensors doi: 10.3390/s18092931 Authors: Lukas Prey Malte von Bloh Urs Schmidhalter Plant vigor is an important trait of field crops at early growth stages, influencing weed suppression, nutrient and water use efficiency and plant growth. High-throughput techniques for its evaluation are required and are promising for nutrient management in early growth stages and for detecting promising breeding material in plant phenotyping. However, spectral sensing for assessing early plant vigor in crops is limited by the strong soil background reflection. Digital imaging may provide a low-cost, easy-to-use alternative. Therefore, image segmentation for retrieving canopy cover was applied in a trial with three cultivars of winter wheat (Triticum aestivum L.) grown under two nitrogen regimes and in three sowing densities during four early plant growth stages (Zadok’s stages 14–32) in 2017. Imaging-based canopy cover was tested in correlation analysis for estimating dry weight, nitrogen uptake and nitrogen content. An active Greenseeker sensor and various established and newly developed vegetation indices and spectral unmixing from a passive hyperspectral spectrometer were used as alternative approaches and additionally tested for retrieving canopy cover. Before tillering (until Zadok’s stage 20), correlation coefficients for dry weight and nitrogen uptake with canopy cover strongly exceeded all other methods and remained on higher levels (R² > 0.60***) than from the Greenseeker measurements until tillering. From early tillering on, red edge based indices such as the NDRE and a newly extracted normalized difference index (736 nm; ~794 nm) were identified as best spectral methods for both traits whereas the Greenseeker and spectral unmixing correlated best with canopy cover. RGB-segmentation could be used as simple low-cost approach for very early growth stages until early tillering whereas the application of multispectral sensors should consider red edge bands for subsequent stages.

Description: Precise sensor-based non-destructive estimation of crop nitrogen (N) status is essential for low-cost, objective optimization of N fertilization, as well as for early estimation of yield potential and N use efficiency. Several studies assessed the performance of spectral vegetation indices (SVI) for winter wheat (Triticum aestivum L.), often either for conditions of low N status or across a wide range of the target traits N uptake (Nup), N concentration (NC), dry matter biomass (DM), and N nutrition index (NNI). This study aimed at a critical assessment of the estimation ability depending on the level of the target traits. It included seven years’ data with nine measurement dates from early stem elongation until flowering in eight N regimes (0–420 kg N ha−1) for selected SVIs. Tested across years, a pronounced date-specific clustering was found particularly for DM and NC. While for DM, only the R900_970 gave moderate but saturated relationships (R2 = 0.47, p 〈 0.001) and no index was useful for NC across dates, NNI and Nup could be better estimated (REIP: R2 = 0.59, p 〈 0.001 for both traits). Tested within growth stages across N levels, the order of the estimation of the traits was mostly Nup ≈ NNI 〉 NC ≈ DM. Depending on the number (n = 1–3) and characteristic of cultivars included, the relationships improved when testing within instead of across cultivars, with the relatively lowest cultivar effect on the estimation of DM and the strongest on NC. For assessing the trait estimation under conditions of high–excessive N fertilization, the range of the target traits was divided into two intervals with NNI values 〈 0.8 (interval 1: low N status) and with NNI values 〉 0.8 (interval 2: high N status). Although better estimations were found in interval 1, useful relationships were also obtained in interval 2 from the best indices (DM: R780_740: average R2 = 0.35, RMSE = 567 kg ha−1; NC: REIP: average R2 = 0.40, RMSE = 0.25%; NNI: REIP: average R2 = 0.46, RMSE = 0.10; Nup: REIP: average R2 = 0.48, RMSE = 21 kg N ha−1). While in interval 1, all indices performed rather similarly, the three red edge-based indices were clearly better suited for the three N-related traits. The results are promising for applying SVIs also under conditions of high N status, aiming at detecting and avoiding excessive N use. While in canopies of lower N status, the use of simple NIR/VIS indices may be sufficient without losing much precision, the red edge information appears crucial for conditions of higher N status. These findings can be transferred to the configuration and use of simpler multispectral sensors under conditions of contrasting N status in precision farming.

Description: Grain nitrogen (N) uptake (GNup) in winter wheat (Triticum aestivum L.) is influenced by multiple components at the plant organ level and by pre- and post-flowering N uptake (Nup). Although spectral proximal high-throughput sensing is promising for field phenotyping, it was rarely evaluated for such N traits. Hence, 48 spectral vegetation indices (SVIs) were evaluated on 10 measurement days for the estimation of 34 N traits in four data subsets, representing the variation generated by six high-yielding cultivars, two N fertilization levels (N), two sowing dates (SD), and two fungicide (F) intensities. Close linear relationships (p 〈 0.001) were found for GNup both in response to cultivar differences (Cv; R2 = 0.52) and other agronomic treatments (R2 = 0.67 for Cv*F*N, R2 = 0.53 for Cv*SD*N and R2 = 0.57 for the combined treatments), notably during milk ripeness. Especially near-infrared (NIR)/red edge SVIs, such as the NDRE_770_750, outperformed NIR/visible light (VIS) indices. Index rankings and seasonal R2 values were similar for total Nup, while the N harvest index, which expresses the partitioning to the grain, was moderately estimated only during dough ripeness, primarily from indices detecting contrasting senescence between different fungicide intensities. Senescence-sensitive indices, including R787_R765 and TRCARI_OSAVI, performed best for N translocation efficiency and some organ-level N traits at maturity. Even though grain N concentration was best assessed by the red edge inflection point (REIP), the blue/green index (BGI) was more suited for leaf-level N traits at anthesis. When SVIs were quantitatively ranked by data subsets, a better agreement was found for GNup, total Nup, and grain N concentration than for several contributing N traits. The results suggest (i) a good general potential for estimating GNup and total Nup by (ii) red edge indices best used (iii) during milk and early dough ripeness. The estimation of contributing N traits differs according to the agronomic treatment.