Determination of natural rubber and resin content of guayule fresh biomass by near infrared spectroscopy

Taurines, Manon; Brancheriau, Loïc; Palu, Serge; Pioch, Daniel; Tardan, Eric; Boutahar, Nabila; Sartre, Pascal; Meunier, Florence

doi:10.1016/j.indcrop.2019.03.073

Cited by 27 publications

(16 citation statements)

References 21 publications

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“…To illustrate, under both CV and EV, the R 2 and RPD values from the DRY dataset were higher than putting all the dry and irrigated samples together while R 2 and RPD values from the IRR dataset were lower than the ALL dataset, meaning that putting all the samples from different growing conditions together might mitigate or weaken the predictive power and accuracy of models. Undeniably, our NIR models seem not as powerful as the ones (R 2 > 0.95) established by previous researchers [2, 4, 6, 18, 38]; however, the previous studies on rubber-producing plants were all based on a limited number of accessions and large numbers of NIR scans, and this technical strategy might lead to overestimation of the stability and accuracy in the prediction of PLSR models. In contrast, our models were based on 56 different accessions representing a USDA guayule germplasm collection and included wild and improved genetic materials that were planted under different growth conditions [19].…”

Section: Resultscontrasting

confidence: 67%

“…Near-infrared (NIR) spectroscopy, based on vibration properties of organic molecule chemical bonds and their interactions with NIR radiation, is a technique used for rapid, reliable, and non-destructive prediction of chemical components in plants, animal products, food, and pharmaceuticals [12–16]. In the last several decades, NIR spectroscopy has been applied to determine resin and rubber content in guayule [2, 4, 6, 17, 18]; however, these studies were either too early to use advanced multivariate data analysis approaches or the sample size of varieties/accessions was small with a very limited range of rubber and resin contents. Moreover, no previous studies made comparisons between different NIR instruments with varying spectral ranges and resolution.…”

Section: Introductionmentioning

confidence: 99%

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A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

2019

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BackgroundGuayule (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. Near-infrared (NIR) spectroscopy is a promising technique that simplifies and speeds up the quantification procedure without 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 contribute to prominent absorbance peaks were identified.ResultsUsing 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 spectra (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.ConclusionsIn 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.

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Section: Resultscontrasting

confidence: 67%

Section: Introductionmentioning

confidence: 99%

A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

2019

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“…The wavebands at 1125 and 1389 nm had a high positive correlation, while at 1156 nm and 1430 nm, there was a high negative correlation with the model prediction of moisture content. The wavebands around 1125, 1156, and 1389 nm were related to the CH 3 functional groups 29 of the rubber polymer (poly-isoprene) that is the primary chemical constituent of natural rubber and the waveband at 1430 nm was related to the OH functional groups of water 32 in the rubber sheet. The above signi¯cant wavebands of the model were closely related to the moisture content and dry rubber content of the rubber sheet.…”

Section: Calibration Model Analysismentioning

confidence: 99%

Development of calibration models for rapid determination of moisture content in rubber sheets using portable near-infrared spectrometers

Puttipipatkajorn

2020

J. Innov. Opt. Health Sci.

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Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber industries. The quality of a rubber sheet can be visually examined by holding it against clear light to inspect for any specks and impurities inside, but its moisture content is difficult to evaluate based on a visual inspection and this might lead to unfair trading. Herein, we developed a rapid, robust and nondestructive near-infrared spectroscopy (NIRS)-based method for moisture content determination in rubber sheets. A set of 300 rubber sheets were divided into a calibration (200 samples) and prediction groups (100 samples). The calibration set was used to develop NIRS calibration equation using different calibration models, Partial Least Square Regression (PLSR), Least Square Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN). Among the models investigated, the ANN model with the first derivative of spectral preprocessing presented the best prediction with a coefficient of determination ([Formula: see text] of 0.993, root mean square error of calibration (RMSEC) of 0.126% and root mean square error of prediction (RMSEP) of 0.179%. The results indicated that the proposed NIRS-ANN model will be able to reduce human error and provide a highly accurate estimate of the moisture content in a rubber sheet compared to traditional wet chemistry estimation methods according to AOAC standards.

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“…Several procedures have been developed to extract the rubber and resin from guayule [63]. Relatively large bench-scale isolation of guayulin A (9 g) from defoliated guayule (30 kg), which also allowed the isolation of guayulin B albeit in relatively low yield, has been demonstrated [64].…”

Section: Guayulin Extraction Processesmentioning

confidence: 99%

Potential Applications of Guayulins to Improve Feasibility of Guayule Cultivation

2019

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Guayule (Parthenium argentatum Gray) is an interesting alternative and renewable source of rubber/latex which has been used in the past. Guayule rubber and latex products are not available in the market largely because the raw material cost is higher than the current sources produced in South-East Asia and other tropical countries (Hevea brasiliensis). Guayule contains many other compounds whose joint exploitation could make guayule cultivation profitable, especially in semi-desert areas where cultivation of other crops is difficult or impossible. Guayulins A–D, sesquiterpene esters, appear to have some commercial promise. Despite being accumulated in relatively high concentrations (its majority representative, guayulin A, can account for up to 13.7% of the resin content of this plant, which itself ranges from 6%–12%), guayulins have received little direct attention from scientists. This review presents the current knowledge about the activity of these compounds and, based on known activities of similar compounds from other species, potential uses as fungicides, miticides and insecticides are suggested.

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Determination of natural rubber and resin content of guayule fresh biomass by near infrared spectroscopy

Cited by 27 publications

References 21 publications

A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

A high-throughput quantification of resin and rubber contents in Parthenium argentatum using near-infrared (NIR) spectroscopy

Development of calibration models for rapid determination of moisture content in rubber sheets using portable near-infrared spectrometers

Potential Applications of Guayulins to Improve Feasibility of Guayule Cultivation

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