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Near infrared spectroscopy for cost effective screening of foliar oil characteristics in a Melaleuca cajuputi breeding population

机译:近红外光谱法用于经济有效地筛选白千层繁殖种群中的叶油特性

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摘要

The identification of Melaleuca cajuputi leaf samples (trees) that demonstrate enhanced oil characteristics using near infrared (NIR) spectroscopy is described. Leaf samples from an unthinned M. cajuputi seedling seed orchard in Indonesia were collected and air-dried, and their 1,8-cineole content and oil concentrations were determined. NIR spectra of the leaves were obtained, and calibrations for 1,8-cineole content and oil concentration were developed using spectra that had been selected using spectral features; that is, no knowledge of 1,8-cineole content or oil concentration was used to select the calibration samples. The calibrations were used to predict the 1,8-cineole content and oil concentration of the remaining samples. It was demonstrated that NIR spectroscopy could be used to identify leaf samples that had high 1,8-cineole contents and oil concentrations. The technique has the potential to greatly reduce the time involved in ranking large numbers of samples for these attributes, as is a requirement in tree breeding programs to enhance oil production. [References: 10]
机译:描述了使用近红外(NIR)光谱鉴定具有增强的油特性的千层叶样品(树)。收集印度尼西亚未稀释的M. cajuputi幼苗种子园的叶样品并风干,测定其1,8-桉树脑含量和油含量。获得了叶片的近红外光谱,并使用通过光谱特征选择的光谱进行了1,8-桉树脑含量和油浓度的校准。也就是说,不使用1,8-桉树脑含量或油浓度的知识来选择校准样品。校准用于预测剩余样品的1,8-桉树脑含量和油浓度。结果表明,近红外光谱可用于鉴定具有较高1,8-桉树脑含量和油浓度的叶片样品。该技术有可能极大地减少为这些属性对大量样本进行排名所需的时间,这是树木育种计划中提高石油产量的要求。 [参考:10]

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