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Author: search.filters.author.Sirisomboon, PanmanasSubject: search.filters.subject.Soluble solids content

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    Development of the partial least-squares model to determine the soluble solids content of sugarcane billets on an elevator conveyor
    (2021-01-01)
    Udompetaikul, Vasu
    ;
    Phetpan, Kittisak
    ;
    Sirisomboon, Panmanas
    This study aimed to determine the optimum multivariate model for monitoring the soluble solids content (SSC) of sugarcane billets being transferred on a conveyor. The study covered two main issues: the exploration of an appropriate spectral range (450–900 nm versus 700–900 nm) and the assessment of the influence of different levels of cane billets on an elevator via modelling to predict the SSC values. Partial least squares regression (PLSR) was used for model development. Modelling using the range of 450–900 nm employed 4 latent variables (LVs) and showed the coefficient of determination (R<sup>2</sup>) and root mean squares error of prediction (RMSEP) of 0.83 and 0.29 °Brix, respectively. This caused the model established using the range of 700–900 nm, employed 3 LVs and provided the R<sup>2</sup> and RMSEP values of 0.81 and 0.31 °Brix, respectively, seems more appropriate. In case of assessing the different cane levels on the conveyor, the outcomes presented model performance of the full and half cane levels in predicting half and full cane datasets with R<sup>2</sup> and RMSEP of 0.52 and 0.55 °Brix and 0.53 and 0.48 °Brix, respectively. This showed that the different levels affected the SSC predictive accuracy of the model. The combined model was developed to cover variations of this difference and was used to predict two external sets. The predictions of ninety and thirty samples that were collected from the same and different growing seasons as the samples for the modelling presented the R<sup>2</sup>, RMSEP and RPD of 0.70, 0.42 °Brix and 1.83 and 0.56, 0.42 °Brix and 2.00, respectively.
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    Two different portables visible-near infrared and shortwave infrared region for on-tree measurement of soluble solid content of marian plum fruit
    (2020-01-01)
    Posom, Jetsada
    ;
    Soonnamtiang, Navavit
    ;
    Kotethum, Patcharapong
    ;
    Konjun, Pakhpoom
    ;
    Sirisomboon, Panmanas
    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 2<sup>nd</sup> derivative, providing a coefficient of determination of calibration set (R<sup>2</sup>) of 0.81, a coefficient of determination of validation set (r<sup>2</sup>) 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.
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    An online visible and near-infrared spectroscopic technique for the real-time evaluation of the soluble solids content of sugarcane billets on an elevator conveyor
    (2018-11-01)
    Phetpan, Kittisak
    ;
    Udompetaikul, Vasu
    ;
    Sirisomboon, Panmanas
    The aim of this research study is to propose a prototype online detection system based on the visible and near-infrared spectroscopic (vis/SW-NIR) technique for the real-time evaluation of the soluble solids content (SSC) of sugarcane billets on an elevator conveyor. The system consisted of two main parts, a cane billet elevator and a spectral acquisition device. An elevator speed of 2 m/s was used for the transfer of sugarcane billets. Spectra acquisition was performed using four 50 W tungsten halogen lamps as a light source in conjunction with vis/SW-NIR spectrometer in reflectance mode. Partial least squares regression (PLSR) was subsequently used to correlate the spectra with the experimentally determined SSC values. The model performance was then assessed using an independent prediction set. The model was found to display a coefficient of determination of prediction (R<sup>2</sup>) of 0.785, a root mean square error of prediction (RMSEP) of 0.30 and a residual predictive deviation (RPD) of 2.16. The result on the prediction set confirm that the proposed system is suitable for the online SSC measurement of the sugarcane billets on an elevator conveyor.