Phosphorylation of thylakoid proteins during chloroplast biogenesis in greening etiolated and light-grown wheat leaves

1987 ◽  
Vol 12 (3) ◽  
pp. 243-254 ◽  
Author(s):  
Patrick S. Covello ◽  
Andrew N. Webber ◽  
Stephen J. Danko ◽  
John P. Markwell ◽  
Neil R. Baker
Keyword(s):  
Chloroplast Biogenesis ◽  
Thylakoid Proteins ◽  
Wheat Leaves

Development of Photorespiration during Chloroplast Biogenesis in Wheat Leaves

1988 ◽  
Vol 39 (7) ◽  
pp. 833-843 ◽  
Author(s):  
A.K. TOBIN ◽  
N. SUMAR ◽  
M. PATEL ◽  
A. L. MOORE ◽  
G. R. STEWART
Keyword(s):  
Chloroplast Biogenesis ◽  
Wheat Leaves

Rate of Photosynthesis and Transpiration of Winter Wheat Leaves and Ears Under Water Deficit Conditions

2008 ◽  
Vol 23 (2) ◽  
pp. 326-335
Author(s):  
Jacek Olszewski ◽  
Agnieszka Pszczółkowska ◽  
Tomasz Kulik ◽  
Gabriel Fordoński ◽  
Krystyna Płodzień ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Water Deficit ◽  
Rate Of Photosynthesis ◽  
Wheat Leaves

Effects of Nitrogen Nutrition on Photosynthetic Functions of Wheat Leaves under Elevated Atmospheric CO2 Concentration

2010 ◽  
Vol 36 (8) ◽  
pp. 1362-1370 ◽  
Author(s):  
Xu-Cheng ZHANG ◽  
Fu-Suo ZHANG ◽  
Xian-Feng YU ◽  
Xin-Ping CHEN
Keyword(s):  
Nitrogen Nutrition ◽  
Wheat Leaves

GATL12 is Essential for Chloroplast Biogenesis in Arabidopsis

2011 ◽  
Vol 46 (4) ◽  
pp. 379-385 ◽  
Author(s):  
Su Yanping ◽  
Lu Xiaoduo ◽  
Shen Songdong ◽  
Zhang Chunyi
Keyword(s):  
Chloroplast Biogenesis

scholarly journals The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4550
Author(s):  
Huajian Liu ◽  
Brooke Bruning ◽  
Trevor Garnett ◽  
Bettina Berger
Keyword(s):  
Hyperspectral Imaging ◽  
High Throughput ◽  
Management Practices ◽  
Leaf Tissue ◽  
Plant Phenotyping ◽  
Proximal Sensing ◽  
N Content ◽  
Hyperspectral Sensors ◽  
Wheat Leaves ◽  
Non Destructive

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

scholarly journals The relative abundance of wheat Rubisco activase isoforms is post-transcriptionally regulated

2021 ◽  
Author(s):  
Juan Alejandro Perdomo ◽  
Peter Buchner ◽  
Elizabete Carmo-Silva
Keyword(s):  
Relative Abundance ◽  
Light Availability ◽  
Transcript Level ◽  
Rubisco Activase ◽  
Small Subunit ◽  
Diel Cycle ◽  
Diurnal Rhythms ◽  
Crop Species ◽  
Β Protein ◽  
Wheat Leaves

AbstractDiurnal rhythms and light availability affect transcription–translation feedback loops that regulate the synthesis of photosynthetic proteins. The CO2-fixing enzyme Rubisco is the most abundant protein in the leaves of major crop species and its activity depends on interaction with the molecular chaperone Rubisco activase (Rca). In Triticum aestivum L. (wheat), three Rca isoforms are present that differ in their regulatory properties. Here, we tested the hypothesis that the relative abundance of the redox-sensitive and redox-insensitive Rca isoforms could be differentially regulated throughout light–dark diel cycle in wheat. While TaRca1-β expression was consistently negligible throughout the day, transcript levels of both TaRca2-β and TaRca2-α were higher and increased at the start of the day, with peak levels occurring at the middle of the photoperiod. Abundance of TaRca-β protein was maximal 1.5 h after the peak in TaRca2-β expression, but the abundance of TaRca-α remained constant during the entire photoperiod. The redox-sensitive TaRca-α isoform was less abundant, representing 85% of the redox-insensitive TaRca-β at the transcript level and 12.5% at the protein level. Expression of Rubisco large and small subunit genes did not show a consistent pattern throughout the diel cycle, but the abundance of Rubisco decreased by up to 20% during the dark period in fully expanded wheat leaves. These results, combined with a lack of correlation between transcript and protein abundance for both Rca isoforms and Rubisco throughout the entire diel cycle, suggest that the abundance of these photosynthetic enzymes is post-transcriptionally regulated.

Sign in / Sign up

Export Citation Format

Share Document