棉纤维按长度分类的便携式振动光谱仪器和化学计量学

IF 10.3 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Computers and Electronics in Agriculture Pub Date : 2025-05-01 Epub Date: 2025-02-18 DOI:10.1016/j.compag.2025.110100
Darlei Gutierrez Dantas Bernardo Oliveria , Maria Fernanda Pimentel , Everaldo Paulo de Medeiros , Simone da Silva Simões
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引用次数: 0

摘要

本研究利用便携式近红外和拉曼光谱仪器结合多元分类技术,根据棉纤维的长度对其进行分类。上半平均值(UHM)长度被棉纤维市场视为一个质量参数,传统上使用高容量系统(HVI)来确定,这需要高安装成本和劳动密集型分析。由于UHM与纤维素聚合有关,因此可以通过近红外(NIR)和拉曼光谱等振动光谱技术来测定UHM。这些技术具有成本低、易于操作和快速数据采集等优点,适合现场使用。本研究旨在开发一种方法,并证明使用便携式近红外和拉曼光谱仪结合模式识别(PR)方法对棉纤维进行常规分析的可行性,为工业实际应用提供概念证明。采用巴西农业研究公司(EMBRAPA)棉花改良试验中的142份棉纤维样品。采用两种基于棉絮长度和相关经济价值的分类方法。第一个目标是区分短(SM)和长(LF)纤维,而第二个目标是进一步将长纤维分为内部类别(L, VL和EL)。总体而言,无论使用何种PR技术,使用便携式拉曼光谱仪的方法都具有100%的准确性。同时,基于近红外光谱仪的方法根据PR方法和变量选择的不同,精度达到100%。GLSW的使用减少了一个潜在变量。综上所述,使用便携式近红外和拉曼光谱仪与PR方法相结合,是一种基于棉纤维长度分类的创新和可行的技术。
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Portable vibrational spectroscopy instruments and chemometrics for the classification of cotton fibers according the length (UHM)
In this study, novel methods using portable NIR and Raman spectroscopy instruments associated with multivariate classification were developed to classify cotton fibers according to their length. The Upper Half Mean (UHM) length is considered a quality parameter by the cotton fiber market and is traditionally determined using a high-volume system (HVI), which entails high installation costs and labor-intensive analyses. As UHM correlates with cellulose polymerization, its determination can be achieved through vibrational spectroscopy techniques such as near-infrared (NIR) and Raman. These technologies offer advantages such as low cost, ease of handling, and rapid data acquisition, making them suitable for field use. This study aimed to develop a method and demonstrate the feasibility of using portable NIR and Raman spectrometers coupled with pattern recognition (PR) methods for routine analysis of cotton fibers, serving as a proof of concept for practical application in the industry. A total of 142 samples of cotton fibers from cotton improvement experiments conducted by the Brazilian Agricultural Research Corporation (EMBRAPA) were employed. Two classification approaches based on cotton lint length and the related economic value were employed. The first aimed to differentiate between short (SM) and long (LF) fibers, while the second aimed to further classify long fibers into internal classes (L, VL, and EL). Overall, methods using portable Raman spectrometer exhibited 100% accuracy performance regardless of the PR technique used. Meanwhile, methods based on NIR spectrometers achieved accuracies of 100% depending on the PR method and variable selection employed. The use of GLSW resulted in a reduction of a latent variable. In conclusion, the use of portable NIR and Raman spectrometers combined with PR methods emerges as an innovative and viable technology for the classification of cotton fibers based on their length.
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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