scholarly journals Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

Sensors ◽  
2017 ◽  
Vol 17 (10) ◽  
pp. 2258 ◽  
Author(s):  
Jongguk Lim ◽  
Giyoung Kim ◽  
Changyeun Mo ◽  
Kyoungmin Oh ◽  
Hyeonchae Yoo ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Hulled Barley

scholarly journals Komparasi Metode Koreksi Spektrum NIRS (De-Trending dan Derivatif ke-2) untuk Penentuan Kadar Air Bubuk Biji kakao

2016 ◽  
Vol 1 (1) ◽  
pp. 1059-1068
Author(s):  
Masdar Masdar ◽  
Agus Arip Munawar ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Least Squares ◽  
Water Content ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Second Derivative ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Ft Ir

Rendahnya pengawasan mutu kakao menyebabkan harga jual di pasar dunia menurun akibat kurangnya pengawasan kadar air. Salah satu metode yang tepat dan cepat dalam penentuan kadar air adalah menggunakan atau Near Infrared Reflectance Spectroscopy (NIRS). Tujuan penelitian adalah melihat kemampuan NIRS dalam memprediksi kadar air bubuk biji kakao dengan menggunakan metode Partial Least Squares (PLS) serta membandingkan dua metode pretreatment De-trending dan Derivatif ke-2.Alat yang digunakan FT-IR IPTEK T-1516, dan pengolahan data dengan unscrambler software® X version 10. Hasil penelitian menunjukkan NIRS mampu menduga kadar air dalam jumlah 10 gram dengan selang kadar air 7.42 – 11.09 % menggunakan PLS secara non pretreatment maupun pretreatment. Panjang gelombang relevan dalam menduga kadar air bubuk biji kakao adalah  1400-1450 nm dan 1800-1950 nm. Peningkatkan kinerja PLS yang paling bagus menggunakan pretreatment derivative ke-2.Abstract The lowest quality of cocoa supervision cause the selling price descrease due to the lack of supervision on the water content. One of the exact method in determining the water content is Near Infrared Reflectance Spectroscopy (NIRS). The purpose of this study is to know the capability of NIRS in order to predict the water content of cocoa by using Partial Least Squares (PLS) method then compared the two pretreatment methods namely De-trending and second Derivative. The instrument used was FT-IR IPTEK T-1516, and the spectra data were analyzed by using unscrambler software® X version 10. The results showed that NIRS can be used to predict the water content in amount 10 grams in a range of water content 7:42 to 11:09% by using PLS non pretreatment and vice versa. The relevantwavelengthsused to predict water content of cocoa powder ware1400-1450 nm and 1800-1950 nm. The optimum best pretreatment method was found to be second Derivative.

Evaluation of the bony repair in rat cranial defect using near infrared reflectance spectroscopy and discriminant analysis

2017 ◽  
Vol 33 (4) ◽  
pp. 1160-1168 ◽  
Author(s):  
Leomir A. S. de Lima ◽  
Kássio M. G. Lima ◽  
Lana S. S. de Oliveira ◽  
Aurigena A. Araújo ◽  
Raimundo Fernandes de Araújo Junior
Keyword(s):  
Discriminant Analysis ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Cranial Defect

Classification of freshwater fish species by linear discriminant analysis based on near infrared reflectance spectroscopy

2017 ◽  
Vol 25 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Hao Lv ◽  
Wenjie Xu ◽  
Juan You ◽  
Shanbai Xiong
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Freshwater Fish ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Linear Discriminant ◽  
Infrared Reflectance Spectroscopy

Near infrared reflectance spectroscopy was used to discriminate different species of freshwater fish samples. Samples from seven freshwater fish species of the family Cyprinidae (black carp ( Mylopharyngodon piceus), grass carp ( Ctenopharyngodon idellus), silver carp ( Hypophthalmichthys molitrix), bighead carp ( Aristichthys nobilis), common carp ( Cyprinus carpio), crucian ( Carassius auratus), and bream ( Parabramis pekinensis)) were scanned by near infrared reflectance spectroscopy from 1000 nm to 1799 nm. Linear discriminant analysis models were built for the classification of species. We inspected the effect of partial least square, principal component analysis, competitive adaptive reweighted sampling, and fast Fourier transform on linear discriminant analysis. The results showed that the dimension reduction methods worked very well for this example. Linear discriminant analysis models which were combined with principal component analysis and fast Fourier transform could classify accurately all the samples under multiplicative scatter correction pre-processing. According to the loadings in principal component analysis, spectra wavelengths 1000, 1001, 1154, 1208, 1284, 1288, 1497, 1665, and 1770 nm were selected as effective wavelengths in linear discriminant analysis. The discriminant analysis was simplified by using effective wavelengths as independent variables in a linear discriminant analysis model. This study indicated that linear discriminant analysis combined with near infrared reflectance spectroscopy could be an effective strategy for the classification of freshwater fish species.

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