ISIS Neutron and Muon Source Data Journal

The potential for leaf pruning to improve water use efficiency of maize under abiotic stress

Abstract: Climate change will likely increase the frequency of extreme events, such as drought, and there is a need to increase the resilience of food crops, particularly in arid regions. It has been observed in China that pruning a maize crop in its early stage of growth improved its resilience to abiotic (non-living) stress, which we suspect is due to interactions between roots and soil that improve water use efficiency. Our aim is to assess, in a controlled environment, the effect of leaf pruning on the water use efficiency of maize under drought and salinity abiotic stresses by monitoring important soil and plant properties. Neutron tomography offers the exciting prospect of mapping root architecture and soil water distribution at the fine scale to study the underlying mechanisms. The data generated will validate field measurements in China and will assist the development of models.

Principal Investigator: Dr Andrew Gregory
Experimenter: Mr Di Wang
Experimenter: Dr Xiaoxian Zhang
Local Contact: Dr Winfried Kockelmann
Experimenter: Dr Yang Gao

DOI: 10.5286/ISIS.E.RB1820415

ISIS Experiment Number: RB1820415

Publisher: STFC ISIS Neutron and Muon Source

Data format: RAW/Nexus
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Data Citation

The recommended format for citing this dataset in a research publication is as:
[author], [date], [title], [publisher], [doi]

For Example:
Dr Andrew Gregory et al; (2018): The potential for leaf pruning to improve water use efficiency of maize under abiotic stress, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB1820415

Data is released under the CC-BY-4.0 license.