Classification of alfalfa hay based on infrared spectroscopy

نویسندگان

چکیده

Alfalfa hay plays a decisive role in the quality and safety of livestock products. Chemical analytical methods for alfalfa hays are laborious, time-consuming, costly. Therefore, suitable required rapid accurate detection hay. This study evaluated feasibility infrared spectroscopy (IR) identifying different hays. 105 samples under three drying were analysed. Results indicated that full spectra model constructed through standard normal variable transformation (SNV), first-derivative (FD), second-derivative (SD) preprocessing by BP SVM had best performance. The accuracies all up to 100%. Under same method, accuracy neural networks was better than support vector machine models most cases. characteristic wavelength-based SNV-SD-SPA exhibited performance other pretreatment methods, such as: SNV-SPA, SNV-FD-SPA, SNV-GA, etc. classification moldy-dried alfalfa, sun-dried shade-dried training set 100%, 99.5%, respectively, prediction reached 97.6%, 97.4%, respectively. Thus, theoretical basis obtained grading online monitoring

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ژورنال

عنوان ژورنال: Bioresources

سال: 2023

ISSN: ['1930-2126']

DOI: https://doi.org/10.15376/biores.18.3.5399-5416