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首页> 外文期刊>Wood Science and Technology >Regional calibration models for predicting loblolly pine tracheid properties using near-infrared spectroscopy
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Regional calibration models for predicting loblolly pine tracheid properties using near-infrared spectroscopy

机译:使用近红外光谱法预测火炬松气管特性的区域校准模型

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摘要

This study developed regional calibration models for the prediction of loblolly pine (Pinus taeda) tracheid properties using near-infrared (NIR) spectroscopy. A total of 1842 pith-to-bark radial strips, aged 19-31 years, were acquired from 268 trees from 109 stands across the southeastern USA. Diffuse reflectance NIR spectra were collected at 10-mm increments from the radial face of pith-to-bark strips using a FOSS 5000 scanning spectrometer. A subset of the 10-mm samples was selected based on the NIR spectra uniqueness and placed in calibration (N = 1020) and validation (N = 998) test sets. The samples were macerated and the tracheid properties measured using an optical analyzer (Techpap MorFi Fiber and Shive Analyzer). Models were created using partial least squares (PLS) regression using the calibration samples, and their performance checked using the validation set. Prediction PLS models for tracheid length were strong when checked with the validation set [R (2)(p) = 0.87, standard error of prediction (SEP) = 0.23 mm, ratio of performance to deviation (RPD) = 2.8]. Prediction models for tracheid width had moderate fit statistics (R (2) = 0.61, SEP = 1.6 mu m, RPD = 1.6), but the SEP was similar to the measurement error of the camera (+/- 2 mu m). The NIR wavelengths of importance were largely attributed to cellulose. The 1542 nm wavelength explained 77% of the variation in tracheid length (RMSE = 0.31 mm). These results demonstrate that NIR spectroscopy models for tracheid length and width can be developed from a diverse set of samples and still maintain prediction accuracy.
机译:这项研究开发了区域标定模型,用于使用近红外(NIR)光谱预测火炬松(Pinus taeda)的气管特性。从美国东南部的109个林分中的268棵树中获得了总计1842个年龄在19-31岁之间的从树皮到树皮的放射状条带。使用FOSS 5000扫描光谱仪,从髓到树皮条的径向表面以10毫米的增量收集漫反射NIR光谱。根据NIR光谱的唯一性选择10毫米样品的一个子集,并将其放置在校准(N = 1020)和验证(N = 998)测试集中。将样品浸软并使用光学分析仪(Techpap MorFi Fiber和Shive Analyzer)测量气管特性。使用校正样本使用偏最小二乘(PLS)回归创建模型,并使用验证集检查其性能。当使用验证集[R(2)(p)= 0.87,预测标准误差(SEP)= 0.23 mm,性能与偏差之比(RPD)= 2.8]进行检查时,对气管长度的PLS预测模型很强。管胞宽度的预测模型具有适度的拟合统计量(R(2)= 0.61,SEP = 1.6微米,RPD = 1.6),但SEP类似于摄像机的测量误差(+/- 2微米)。重要的NIR波长主要归因于纤维素。 1542 nm波长解释了气管长度变化的77%(RMSE = 0.31 mm)。这些结果表明,可以从各种样品中开发出用于气管长度和宽度的近红外光谱模型,并且仍保持预测准确性。

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  • 来源
    《Wood Science and Technology》 |2018年第2期|445-463|共19页
  • 作者单位

    Univ Georgia, Warnell Sch Forestry & Nat Resource, 180 E Green St, Athens, GA 30602 USA;

    Univ Georgia, Warnell Sch Forestry & Nat Resource, 180 E Green St, Athens, GA 30602 USA;

    Oregon State Univ, Wood Sci & Engn, 119 Richardson Hall, Corvallis, OR 97331 USA;

    USDA, Forest Prod Lab, One Gifford Pinchot Dr, Madison, WI 53726 USA;

    Univ Georgia, Warnell Sch Forestry & Nat Resource, 180 E Green St, Athens, GA 30602 USA;

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