scholarly journals Two Different Portables Visible-Near Infrared and Shortwave Infrared Region for On-Tree Measurement of Soluble Solid Content of Marian Plum Fruit

2020 ◽  
Vol 24 (5) ◽  
pp. 227-236
Author(s):  
Jetsada Posom ◽  
Navavit Soonnamtiang ◽  
Patcharapong Kotethum ◽  
Pakhpoom Konjun ◽  
Panmanas Sirisomboon ◽  
...  
Keyword(s):  
Near Infrared ◽  
Solid Content ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Soluble Solid Content ◽  
Relative Standard ◽  
Soluble Solid ◽  
Shortwave Infrared ◽  
Mean Square Errors

The goal of this study was to predict the soluble solid content (SSC) of on-tree Marian plum fruit using two different wavelength range and algorithm. One of these was the commercial dispersion NIR spectrometer (MicroNIR 1700), providing shortwave infrared (SWIR), while the other was a making diode array spectrometer giving visible-near infrared (Vis-NIR). To search optimal model, the analytical ability of the two wavelength ranges spectrometers coupled with two algorithms: i.e. partial least squares regression (PLSR) and support vector machine regression (SVR), were investigated. Different spectral pre-processing methods were tested. The model providing the lowest root mean square errors of prediction (RMSEP) was selected. Overall, the proposed outcome was that the performance of SWIR was more accurate than Vis-NIR spectrometer, and that both SWIR and Vis-NIR coupled with PLSR algorithm had a higher accuracy than SVR algorithm. The best model for on-tree evaluation SSC was the SWIR constructed using the PLSR algorithm with the spectral pre-processing of the 2nd derivative, providing a coefficient of determination of calibration set (R2) of 0.81, a coefficient of determination of validation set (r2) of 0.76, RMSEP of 0.69 °Brix, and a relative standard error of prediction (RSEP) of 4.43%. The outcome showed that a portable SWIR spectrometer developed with PLSR could be used for monitoring the SSC of individual Marian plum fruit on-tree for quality assurance.

Hyperspectral Imaging for Predicting Soluble Solid Content of Starfruit

2015 ◽  
Vol 73 (1) ◽  
Author(s):  
Feri Candra ◽  
Syed Abd. Rahman Abu Bakar
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging System ◽  
Solid Content ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Soluble Solid Content ◽  
Calibration Model ◽  
Soluble Solid

Hyperspectral imaging technology is a powerful tool for non-destructive quality assessment of fruits. The objective of this research was to develop novel calibration model based on hyperspectral imaging to estimate soluble solid content (SSC) of starfruits. A hyperspectral imaging system, which consists of a near infrared  camera, a spectrograph V10, a halogen lighting and a conveyor belt system, was used in this study to acquire hyperspectral  images of the samples in visible and near infrared (500-1000 nm) regions. Partial least square (PLS) was used to build the model and to find the optimal wavelength. Two different masks were applied for obtaining the spectral data. The optimal wavelengths were evaluated using multi linear regression (MLR). The coefficient of determination (R2) for validation using the model with first mask (M1) and second mask (M2) were 0.82 and 0.80, respectively.

Determination of soluble solid content in market tomatoes using Near-infrared Spectroscopy

Food Control ◽  
2021 ◽  
pp. 108068
Author(s):  
Annelisa Arruda de Brito ◽  
Fernanda Campos ◽  
Abadia dos Reis Nascimento ◽  
Gilmarcos de Carvalho Corrêa ◽  
Flávio Alves da Silva ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Solid Content ◽  
Soluble Solid Content ◽  
Soluble Solid

Rheological Characteristics of Juniperus drupacea Fruit Juice (pekmez) Concentrated by Boiling

2008 ◽  
Vol 14 (4) ◽  
pp. 321-328 ◽  
Author(s):  
M. Akbulut ◽  
H. Çoklar ◽  
G. Özen
Keyword(s):  
Flow Characteristics ◽  
Shear Thickening ◽  
Solid Content ◽  
Soluble Solids ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Rheological Parameters ◽  
Soluble Solid Content ◽  
Rotational Viscometer ◽  
Soluble Solid

Rheological parameters of Juniperus drupacea fruit pekmez were evaluated using a rotational viscometer at 10, 20, 30, 40, and 50 °C and at concentrations of 62.8, 68.9, 72.0, and 75.2% total soluble solids. The flow characteristics of Juniperus drupacea fruit pekmez were described by the power law and Herschel—Bulkley models. The Herschel—Bulkley model was found to be the best to describe the rheological property with the coefficient of determination higher than 0.993. Juniperus drupacea pekmez exhibited a time-independent shear thickening behavior. The effect of temperature on viscosity can be described by means of an Arrhenius equation. Depending on the soluble solid contents, the activation energies for flow of diluted samples vary from 78.23 to 60.38 kJ/mol. The effect of soluble solids on viscosity can be described by an exponential equation. Experimental data were fitted to several models in order to describe the effect of temperature and soluble solid content. The combined effect of temperature and soluble solid content on viscosity was also formulated.

scholarly journals Improvement of NIR models for quality parameters of leech and earthworm medicines using outlier multiple diagnoses

2017 ◽  
Vol 11 (01) ◽  
pp. 1750009 ◽  
Author(s):  
Chunyan Wu ◽  
Jiashan Chen ◽  
Mengru Li ◽  
Yongjiang Wu ◽  
Xuesong Liu
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Solid Content ◽  
Detection Methods ◽  
Soluble Solid Content ◽  
Relative Standard Error ◽  
Diffuse Reflection Spectroscopy ◽  
Nondestructive Technique ◽  
Relative Standard

Leeches and earthworms are the main ingredients of Shuxuetong injection compositions, which are natural biomedicines. Near infrared (NIR) diffuse reflection spectroscopy has been used for quality assurance of Chinese medicines. In the present work, NIR spectroscopy was proposed as a rapid and nondestructive technique to assess the moisture content (MC), soluble solid content (SSC) and hypoxanthine content (HXC) of leeches and earthworms. This study goal was to improve NIR models for accurate quality control of leech and earthworm using outlier multiple diagnoses (OMD). OMD was composed of four outlier detection methods: spectrum outlier diagnostic (MD), leverage diagnostic (LD), principal component scores diagnostic (PCSD) and factor loading diagnostic (FLD). Conventional outlier diagnoses (MD, LD) and OMD were compared, and the best NIR models were those based on OMD. The correlation coefficients ([Formula: see text]) for leech were 0.9779, 0.9616 and 0.9406 for MC, SSC and HXC, respectively. The values of relative standard error of prediction (RSEP) for leech were 2.3%, 5.1% and 9.0% for MC, SSC and HXC, respectively. The values of [Formula: see text] for earthworm were 0.9478, 0.9991 and 0.9605 for MC, SSC and HXC, respectively. The values of RSEP for earthworm were 8.8%, 2.4% and 12% for MC, SSC and HXC, respectively. The performance of the NIR models was certainly improved by OMD.

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