Cotton micronaire is an essential fiber quality attribute that characterizes both fiber maturity and fineness components. Micronaire and other attributes are measured on fiber lint routinely in laboratories under controlled environmental conditions following a well-established high-volume instrument protocol. In this study, the attenuated total reflection Fourier transform infrared spectroscopy, characterizing fundamental group vibrations in fiber cellulose from 4000 to 400 cm−1, and using an attenuated total reflection device, was explored for fiber micronaire assessment, especially for seed cotton locule fibers that were mingled with nonlint materials, and varied in fiber maturity within a naturally variable sample. Partial least squares multivariate regression models and the algorithmic infrared maturity approach were developed and then applied to predict micronaire values of validation samples and independent seed cotton samples for comparison. Unlike partial least squares models that showed worse in the coefficient of determination, bias, and percentage of samples within the 95% agreement range for independent samples than for validation samples, the algorithmic infrared maturity approach indicated a similarity in the coefficient of determination, bias, and percentage of samples within the 95% agreement range between the validation samples and independent samples. In particular, the algorithmic infrared maturity approach avoided the need to re-calibrate the model with new samples. Therefore, the development of a robust and effective Fourier transform infrared technique combined with the infrared maturity approach for rapid laboratory micronaire assessment and distribution demonstrated a great potential for its extension to the early micronaire testing in remote/breeding locations, and also to regular cotton fibers, processed cotton yarns and fabrics.

中文翻译：

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傅里叶变换红外光谱在棉纤维马克隆值测量和分布中的潜力研究

棉花马克隆值是重要的纤维质量属性，表征纤维成熟度和细度组成。马克隆值和其他属性是在实验室中按照完善的高容量仪器协议在受控环境条件下对纤维棉绒进行常规测量。在本研究中，衰减全反射傅里叶变换红外光谱表征了纤维纤维素中 4000 至 400 cm 的基本基团振动−1并使用衰减全反射装置，探索了纤维马克隆值评估，特别是对于与不起毛材料混合的籽棉小室纤维，并且在自然变化的样品中纤维成熟度不同。开发了偏最小二乘多元回归模型和算法红外成熟度方法，然后应用于预测验证样品和独立籽棉样品的马克隆值以进行比较。与验证样本相比，偏最小二乘模型在独立样本的决定系数、偏差和 95% 一致性范围内的样本百分比方面显示较差，算法红外成熟度方法表明在决定系数、偏差和样本百分比方面存在相似性。验证样本和独立样本之间 95% 一致性范围内的样本百分比。特别是，算法红外成熟度方法避免了使用新样本重新校准模型的需要。因此，开发稳健有效的傅里叶变换红外技术与红外成熟度方法相结合，用于快速实验室马克隆值评估和分布，证明了其扩展到偏远/育种地点的早期马克隆值测试以及常规棉纤维的巨大潜力，加工棉纱和织物。