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Full-Text Articles in Physical Sciences and Mathematics
Leaf Traits Can Be Used To Predict Rates Of Litter Decomposition, Marc Rosenfield, Jennifer L. Funk, Jason K. Keller, Catrina Clausen, Kimberlee Cyphers
Leaf Traits Can Be Used To Predict Rates Of Litter Decomposition, Marc Rosenfield, Jennifer L. Funk, Jason K. Keller, Catrina Clausen, Kimberlee Cyphers
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Strong relationships exist between litter chemistry traits and rates of litter decomposition. However, leaf traits are more commonly found in online trait databases than litter traits and fewer studies have examined how well leaf traits predict litter decomposition rates. Furthermore, while bulk leaf nitrogen (N) content is known to regulate litter decomposition, few studies have explored the importance of N biochemistry fractions, such as protein and amino acid concentration. Here, we decomposed green leaves and naturally senesced leaf litter of nine species representing a wide range of leaf functional traits. We evaluated the ability of traits associated with leaf and …
De Novo Sequencing And Analysis Of Salvia Hispanica Tissue-Specific Transcriptome And Identification Of Genes Involved In Terpenoid Biosynthesis, James Wimberley, Joseph Cahill, Hagop S. Atamian
De Novo Sequencing And Analysis Of Salvia Hispanica Tissue-Specific Transcriptome And Identification Of Genes Involved In Terpenoid Biosynthesis, James Wimberley, Joseph Cahill, Hagop S. Atamian
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Salvia hispanica (commonly known as chia) is gaining popularity worldwide as a healthy food supplement due to its low saturated fatty acid and high polyunsaturated fatty acid content, in addition to being rich in protein, fiber, and antioxidants. Chia leaves contain plethora of secondary metabolites with medicinal properties. In this study, we sequenced chia leaf and root transcriptomes using the Illumina platform. The short reads were assembled into contigs using the Trinity software and annotated against the Uniprot database. The reads were de novo assembled into 103,367 contigs, which represented 92.8% transcriptome completeness and a diverse set of Gene Ontology …