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Author: search.filters.author.Sirisomboon, PanmanasSubject: search.filters.subject.Sugarcane

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    Evaluation of informative spectral wavelengths for estimating soluble solids content in sugarcane billets
    (2022-02-22)
    Udompetaikul, Vasu
    ;
    Phetpan, Kittisak
    ;
    Sirisomboon, Panmanas
    This study proposed individual spectral wavelengths significant to estimate soluble solids content (SSC) in sugarcane billets moving on the conveyor. At the same time, an all-in-one quality and yield monitor using those wavelengths for a sugarcane harvester was also proposed. Seven wavelengths, 475, 560, 668, 717, 755, 840, and 890 nm, were arranged into three groups for modeling. Group 1, consisting of 475, 560, 668, 717, and 840 nm, was based on the spectral responses of a commercial multispectral camera, while group 2 (717 and 840 nm) was based on the invisible (RedEdge and near-infrared or NIR) responses of the camera. For group 3, two sugar-related wavelengths at 755 and 890 nm were selected as the candidates for modeling. Partial least squares regression (PLSR) was employed to model those three groups with corresponding soluble solids content (SSC). The results showed that the developed models based on two sugar-related wavelengths at 755 and 890 nm provided the best performance, explaining 80.2 % of the variance in the SSC and displaying a root mean square error of calibration (RMSEC) of 0.32 ºBrix. The predictive performance had the root mean square error of prediction (RMSEP) of 0.33 ºBrix. This finding confirmed the effectiveness of the sugar wavelengths and conveyed the possibility to develop the sugarcane quality and yield monitor.
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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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    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.