Author

S. L. Anderson

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Plant Biology· 4

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Research Focus:development & morphogenesis· 2 Research Focus:differential expression· 2 Assay:imaging· 2 Organism:plant (other)· 2 Organism:C. elegans· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1

Frequent Co-Authors

B. J. Pearson· 2 shared S. C. Murray· 2 shared Z. Brym· 2 shared A. Adak· 1 shared A. Chang· 1 shared D. Cope· 1 shared J. Jung· 1 shared L. Malambo· 1 shared

Activity by Year

2019-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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2 shared papersPlant Biology

B. J. Pearson

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4 papers

Recent·Most cited

Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions

A. Adak, S. C. Murray, S. L. Anderson

This paper shows that temporal phenomic data from drones can predict plant fitness as well as genomic data in maize hybrids.

bioRxiv · Oct 6, 2021Plant Biology

Photoperiodic Flowering Response of Essential Oil, Grain, and Fiber Hemp (Cannabis sativa L.) Cultivars

M. Zhange, S. L. Anderson, Z. Brym, B. J. Pearson

This study identifies critical photoperiod thresholds for hemp cultivars, showing that photoperiod differences as small as 15 min can significantly affect flowering, with implications for tropical and subtropical cultivation.

bioRxiv · May 13, 2021Plant Biology

Evaluation of substrate composition and exogenous hormone application on vegetative propagule rooting success of essential oil hemp (Cannabis sativa L.)

S. M. Campbell, S. L. Anderson, Z. Brym, B. J. Pearson

This study evaluates how propagation media and hormones affect rooting success in essential oil hemp cultivars, finding that media has the greatest impact and rockwool performs best.

bioRxiv · Mar 15, 2021Plant Biology

Unoccupied aerial system enabled functional modeling of maize (Zea mays L.) height reveals dynamic expression of loci associated to temporal growth.

S. L. Anderson, S. C. Murray, Y. Chen, L. Malambo, A. Chang, S. Popescu, D. Cope, J. Jung

This paper uses UAS to model maize growth and identifies temporal QTL associated with plant height, showing dynamic expression patterns over time.

bioRxiv · Nov 19, 2019 · PreprintPlant Biology