A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectro
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Plant Methods Open Access
METHODOLOGY
A high‑throughput quantification of resin and rubber contents in Parthenium argentatum using near‑infrared (NIR) spectroscopy Zinan Luo, Kelly R. Thorp and Hussein Abdel‑Haleem*
Abstract Background: Guayule (Parthenium argentatum A. Gray), a plant native to semi-arid regions of northern Mexico and southern Texas in the United States, is an alternative source for natural rubber (NR). Rapid screening tools are needed to replace the current labor-intensive and cost-inefficient method for quantifying rubber and resin contents. Nearinfrared (NIR) spectroscopy is a promising technique that simplifies and speeds up the quantification procedure with‑ out losing precision. In this study, two spectral instruments were used to rapidly quantify resin and rubber contents in 315 ground samples harvested from a guayule germplasm collection grown under different irrigation conditions at Maricopa, AZ. The effects of eight different pretreatment approaches on improving prediction models using partial least squares regression (PLSR) were investigated and compared. Important characteristic wavelengths that contrib‑ ute to prominent absorbance peaks were identified. Results: Using two different NIR devices, ASD FieldSpec®3 performed better than Polychromix Phazir™ in improving R2 and residual predicative deviation (RPD) values of PLSR models. Compared to the models based on full-range spec‑ tra (750–2500 nm), using a subset of wavelengths (1100–2400 nm) with high sensitivity to guayule rubber and resin contents could lead to better prediction accuracy. The prediction power of the models for quantifying resin content was better than rubber content. Conclusions: In summary, the calibrated PLSR models for resin and rubber contents were successfully developed for a diverse guayule germplasm collection and were applied to roughly screen samples in a low-cost and efficient way. This improved efficiency could enable breeders to rapidly screen large guayule populations to identify cultivars that are high in rubber and resin contents. Keywords: Parthenium argentatum, Guayule, Resin, Rubber, Near-infrared (NIR) spectroscopy, Partial least squares regression (PLSR), Bioenergy crop Background Guayule (Parthenium argentatum A. Gray), commonly grown in semi-arid regions, is a promising crop to produce natural rubber (NR). NR cannot be replaced completely by synthetic rubber because NR possesses
*Correspondence: Hussein.Abdel‑[email protected] US Arid-Land Agricultural Research Center, USDA-ARS, Maricopa, AZ 85138, USA
high-performance properties in resilience, impact resistance, abrasion, and heat dispersion, among other desirable properties [1–3]. Almost all the current NR in the US is imported from countries in southeastern Asia, where Hevea brasiliensis is widely planted. To increase NR production to meet increasing demands, stabilize economics, and avoid disease threats to Hevea in Southeast Asian countries, guayule is considered to be a top alternative resource for domestic rubber production. Additi
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