用近红外光谱法预测豆荚的化学化学成分

Antônio Marcos Ferreira Fernandes, M. A. Bomfim, S. F. Santos, J. D. L. Gonçalves, C. M. Mota
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引用次数: 0

摘要

采集于巴西东北部的豆科植物豆荚样本在自然环境中进行读取,在NIR Perten®DA 7250 (PerkinElmer, Inc, USA)中进行预处理,并在NIR FOSS 5000 Nirsystem II中使用ISIScan®软件进行预处理。参考分析采用动物营养实验室的常规方法。参考结果显示化学成分差异较大。在模型的性能方面,采用样本预处理建立的模型比采用自然样本建立的模型更有效。在这些仪器中,Perten的表现与FOSS仪器相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Previsão da composição químico-bromatológica de vagem de algaroba usando a espectroscopia no infravermelho próximo
Mesquite pod samples collected in Northeast Brazil were read in natura and pre-processed in NIR Perten® DA 7250 (PerkinElmer, Inc., USA), and pre-processed in NIR FOSS 5000 Nirsystem II using ISIScan® software. Reference analyzes were obtained by conventional methodologies in an animal nutrition laboratory. The reference results showed good variation in chemical composition. In the performance of the models, those developed with sample pre-processing were more efficient than those built with in natura samples. And among the instruments, Perten performed similarly to the FOSS instrument.
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