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Variable selection in near infrared spectra for the biological characterization of soil and earthworm casts.

机译:近红外光谱中的变量选择,用于土壤和earth的生物表征。

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Near infrared reflectance spectroscopy (NIRS) was used to predict six biological properties of soil and earthworm casts including extracellular soil enzymes, microbial carbon, potential nitrification and denitrification. Partial least squares regression (PLSR) models were developed with a selection of the most important near infrared wavelengths. They reached coefficients of determination ranging from 0.81 to 0.91 and ratios of performance-to-deviation above 2.3. Variable selection with the variable importance in the projection (VIP) method increased dramatically the prediction performance of all models with an important contribution from the 1750-2500 nm region. We discuss whether selected wavelengths can be attributed to macronutrient availability or to microbial biomass. Wavelength selection in NIR spectra is recommended for improving PLSR models in soil research.
机译:近红外反射光谱法(NIRS)用于预测土壤和earth的六种生物学特性,包括细胞外土壤酶,微生物碳,潜在的硝化作用和反硝化作用。通过选择最重要的近红外波长,开发了偏最小二乘回归(PLSR)模型。他们得出的确定系数在0.81至0.91范围内,性能偏差比在2.3以上。在投影(VIP)方法中具有重要重要性的变量选择极大地提高了所有模型的预测性能,这些模型的主要贡献来自1750-2500 nm区域。我们讨论选择的波长是否可以归因于大量营养素的利用或微生物的生物量。建议在NIR光谱中选择波长,以改善土壤研究中的PLSR模型。

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