近红外光谱结合化学计量学测定甘蔗中ADF和IVOMD含量

Ozcan Cataltas, K. Tutuncu
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引用次数: 0

摘要

甘蔗是一种既作为制糖原料,又作为动物饲料,都需要确定质量参数的植物。近红外光谱技术是近年来广泛应用于植物参数预测的一种技术。本研究提出了一种基于近红外光谱的模型,用于快速、轻松地分析甘蔗植株酸性洗涤纤维组分和体外有机物消化率参数。将偏最小二乘回归与常用的预处理方法相结合进行建模。该模型对酸性洗涤纤维组分和体外有机物消化率参数的R2CV值分别为0.935和0.953。然后,利用所提出的组合方法对三台手持光谱仪的光谱进行组合,生成更高光谱分辨率的新光谱。利用这些生成的光谱建立了新的模型,并与之前的结果进行了比较。结果表明,不同光谱仪的光谱组合可以提高模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determination of the ADF and IVOMD Content of Sugarcane Using Near Infrared Spectroscopy Coupled with Chemometrics
Sugarcane is a plant whose quality parameters are required to be determined both for being one of the substances used in sugar production and for being used as animal feed. Near-infrared spectroscopy is a technique that has already been used for predicting the parameters of various plants and has gained popularity in recent years. This study proposes a near-infrared spectroscopy-based model for the rapid and effortless analysis of acid detergent fiber fraction and vitro organic matter digestibility parameters of the sugarcane plant. Partial least squares regression was combined with common preprocessing methods for modeling. This model yielded an R2CV value of 0.935 and 0.953 for the acid detergent fiber fraction and vitro organic matter digestibility parameters, respectively. Then, the spectra from three handheld spectrometers were combined using a proposed combination method to generate new spectra with higher spectral resolution. New models were built using these generated spectra and compared to the previous result. Obtained results showed that combining spectra from different spectrometers can improve model performance.
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