Development of Calibration Models to Predict Mean Fibre Diameter in Llama (Lama glama) Fleeces with Near Infrared Spectroscopy

被引:1
|
作者
Ignacio Amorena, Jose [1 ]
Eugenia Alvarez, Dolores Maria [2 ]
Fernandez-Ahumada, Elvira [3 ]
机构
[1] Inst Nacl Tecnol Agr INTA, Estn Expt Agr EEA Catamarca, RP 33,Km 4-5, RA-4705 Catamarca, Argentina
[2] Ctr Invest & Tecnol Quim CITeQ CONICET UTN, Ciudad Univ, RA-5016 Cordoba, Argentina
[3] Univ Cordoba UCO, Dept Matemat, Cordoba 14071, Spain
来源
ANIMALS | 2021年 / 11卷 / 07期
关键词
llama; textile fibres; near infrared spectroscopy; NIRS; REFLECTANCE SPECTROSCOPY; WOOL; ALPACA; CLASSIFICATION; FEASIBILITY; PARAMETERS; REGRESSION; QUALITY;
D O I
10.3390/ani11071998
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Simple Summary In the Puna region of Argentina, llama fibre production has enormous social, economic and environmental potential, but is still in its early stages of development. For this reason, classification and quality analysis systems used today are still deficient. Near infrared reflectance spectroscopy is a technological resource used in the agroindustry for quality analysis of organic compounds. In this work we studied the feasibility of this technology to evaluate the mean fibre diameter, which is one of the most important quality parameters in the textile industry. Despite some limitations, which are mainly related to fibre heterogeneity, the results obtained were encouraging as spectroscopy could be used in screening programmes as a sustainable, fast and low-cost method to improve fibre quality validation. Llama fibre has the potential to become the most valuable textile resource in the Puna region of Argentina. In this study near infrared reflectance spectroscopy was evaluated to predict the mean fibre diameter in llama fleeces. Analyses between sets of carded and non-carded samples in combination with spectral preprocessing techniques were carried out and a total of 169 spectral signatures of llama samples in Vis and NIR ranges (400-2500 nm) were obtained. Spectral preprocessing consisted in wavelength selection (Vis-NIR, NIR and discrete ranges) and multiplicative and derivative pretreatments; spectra without pretreatments were also included, while modified partial least squares (M-PLS) regression was used to develop prediction models. Predictability was evaluated through R-2: standard cross validation error (SECV), external validation error (SEV) and residual predictive value (RPD). A total of 54 calibration models were developed in which the best model (R-2 = 0.67; SECV = 1.965; SEV = 2.235 and RPD = 1.91) was obtained in the Vis-NIR range applying the first derivative pretreatment. ANOVA analysis showed differences between carded and non-carded sets and the models obtained could be used in screening programs and contribute to valorisation of llama fibre and sustainable development of textile industry in the Puna territory of Catamarca. The data presented in this paper are a contribution to enhance the scarce information on this subject.
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页数:11
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