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Technical Note: Measuring Grain and Insect Characteristics Using NIR Laser Array Technology

机译:技术说明:使用NIR激光阵列技术测量谷物和昆虫特征

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摘要

The potential of using a compact eight-wavelength near-infrared (NIR) laser array spectrometer for measuring wheat characteristics (hardness index, moisture content, and waxy character) and determining tsetse fly pupae sex was investigated and compared to a commercial single kernel near infrared (SKNIR) system. Wheat hardness was predicted accurately by both NIR systems and results were in close agreement with reference values. The accuracy of predicting moisture content by either system was similar with predicted values within 0.5% moisture content of the reference values. Waxy character was predicted by the laser system with less accuracy than the SKNIR system, but tsetse fly pupae sex was predicted with similar accuracies for both systems. Prediction equations derived from the laser spectra show that wavelengths influencing classification models generally agree with published literature. Thus, this research shows that a NIR laser array system can be used to predict some grain and insect traits with accuracy similar to a commercial NIR system and some predictions may be improved if other wavelengths are used in the laser array system
机译:研究了使用紧凑型八波长近红外(NIR)激光阵列光谱仪测量小麦特性(硬度指数,水分含量和蜡质特性)并确定采采蝇蝇p性的潜力,并将其与商用单核近红外进行了比较(SKNIR)系统。两种NIR系统均可准确预测小麦硬度,其结果与参考值非常吻合。通过这两个系统预测水分含量的准确性与参考值的0.5%水分含量内的预测值相似。激光系统预测蜡质特征的准确性要低于SKNIR系统,但两种系统预测的采采蝇p性具有相似的准确度。从激光光谱得出的预测方程式表明,影响分类模型的波长通常与已发表的文献一致。因此,这项研究表明,NIR激光阵列系统可用于预测某些谷物和昆虫的性状,其准确性与商用NIR系统相似,并且如果在激光阵列系统中使用其他波长,则可以改善某些预测

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  • 来源
    《Applied Engineering in Agriculture》 |2010年第1期|p.165-169|共5页
  • 作者单位

    Floyd E. Dowell, ASABE Member Engineer, Research Leader, Elizabeth B. Maghirang, ASABE Member Engineer, Agricultural Engineer, Engineering and Wind Erosion Research Unit, USDA ARS Center for Grain and Animal Health Research, Manhattan, Kansas;

    and Venkatramanan Jayaraman, Founder, Praevium Research, Inc., Santa Barbara, California. Corresponding author: Floyd E. Dowell, Engineering and Wind Erosion Research Unit, USDA ARS Grain Marketing and Production Research Center, 1515 College Avenue, Manhattan KS 66502;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    NIR; Spectroscopy; Wheat; Insects; Near-infrared; Laser; Grading; Quality;

    机译:近红外;光谱学小麦;昆虫;近红外;激光;等级;质量;

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