Development of calibration models for rapid determination of moisture content in rubber sheets using portable near-infrared spectrometers

Amorndej Puttipipatkajorn; Amornrit Puttipipatkajorn

doi:10.1142/s1793545820500091

[1] C. Pasquini, "Near infrared spectroscopy: A mature analytical technique with new perspectives," J. Anal. Chim. 1026, 8–36 (2018).

[2] K. H. Norris, "Design and development of a new moisture meter," J. Agric. Eng. 45(7), 370–372 (1964).

[3] A. M. Davies, A. Grant, "Review: Near-infra-red analysis of food," J. Food Sci. Technol. 22, 191–207 (1987).

[4] R. Rittiron, W. Seehalak, "Moisture content in rubber sheet analyzed by transflectance near infrared spectroscopy," J. Innov. Opt. Health Sci. 7, 1350068 (2014).

[5] P. Sirisomboon, A. Kaewkuptong, P. Williams, "Feasibility study on the evaluation of the dry rubber content of field and concentrated latex of Para rubber by diffuse reflectance near infrared spectroscopy," J. Near Infrared Spec. 21, 81–88 (2013).

[6] S. Suchata, P. Theanjumpolb, S. Karrila, "Rapid moisture determination for cup lump natural rubber by near infrared spectroscopy," J. Ind Crop Prod. 76, 772–780 (2015).

[7] V. R. Sharabiani, A. S. Naza, "Prediction of protein content of winter wheat by canopy of near infrared spectroscopy (NIRS) using partial least squares regression (PLSR) and artificial neural network (ANN) models," J. Agric. Sci. 29(1), 43–51 (2019).

[8] M. J. Martelo-Vidal, M. Vazquez, "Application of artificial neural networks coupled to UV-VIS-NIR spectroscopy for the rapid quantification of wine compounds in aqueous mixtures," J. Food Eng. 13 (1), 32–39 (2015).

[9] A. Savitzky, M. J. Golay, "Smoothing and differentiation of data by simplified least squares procedures," J. Anal. Chem. 36(8), 1627–1639 (1964).

[10] N. M. Nawi, T. Jensen, G. Chen, "The application of spectroscopic methods to predict sugarcane quality based on stalk cross-sectional scanning," J. Am. Soc. Sugar Cane Technol. 32, 16–27 (2012).

[11] S. Wold, J. Trygg, A. Berglund, H. Antti, "Some recent development in PLS modeling," J. Chemometr. Intell. Lab Syst. 58, 131–150 (2001).

[12] X. Yu, H. Lu, D. Wu, "Development of deep learning method for predicting firmness and soluble solid content of postharvest Korla fragrant pear using Vis/NIR hyperspectral reflectance imaging," J. Postharvest Biol. Technol. 141, 39–49 (2018).

[13] R. Redaellia, M. Alfieria, G. Cabassi, "Development of a NIRS calibration for total antioxidant capacity in maize germplasm," Talanta 154, 164–168 (2016).

[14] J. Li, W. Huang, C. Zhao, B. Zhang, "A comparative study for the quantitative determination of soluble solids content, pH and firmness of pears by Vis/NIR spectroscopy," J. Food Eng. 116(2), 324–332 (2013).

[15] V. N. Vapnik, Statistical Learning Theory, Springer, New York (1998).

[16] H. Y. Yua, X. Y. Niua, H. J. Lina, Y. B. Yinga, B. B. Lib, X. X. Panc, "A feasibility study on on-line determination of rice wine composition by Vis-NIR spectroscopy and least-squares support vector machines," J. Food Chem. 113(1), 291–296 (2009).

[17] A. Morellosa, X. E. Pantazia, D. Moshoua, T. Alexandridisc, R. Whettonb, G. Tziotziosa, J. Wiebensohnd, R. Billd, A. M. Mouazen, "Machine learning based prediction of soil total nitrogen, organic carbon and moisture content by using VISNIR spectroscopy," J. Biosyst. Eng. 152, 104–116 (2016).

[18] Z. Han, S. Cai, X. Zhang, Q. Qian, Y. Huang, F. Dai, G. Zhang, "Development of predictive models for total phenolics and free p-coumaric acid contents in barley grain by near-infrared spectroscopy," J. Food Chem. 227, 342–348 (2017).

[19] J. A. Suykens, J. Vandewalle, "Least squares support vector machine classifiers," Neural Process. Lett. 9(3), 293–300 (1999).

[20] F. Chauchard, R. Cogdillb, S. Rousselc, J. M. Rogera, V. Bellon-Maurela, "Application of LSSVM to non-linear phenomena in NIR spectroscopy: Development of a robust and portable sensor for acidity prediction in grapes," J. Chemometr Intell Lab Syst. 71(2), 141–150 (2004).

[21] K. De Brabanter, P. Karsmakers, F. Ojeda, C. Alzate, J. De Brabanter, K. Pelckmans, "LSSVM toolbox user's guide," ESAT-SISTA Technical Report, 10-146, (2011).

[22] D. Kruzlicova, J. Mock, B. Balla, J. Petka, M. Farkova, J. Havel, "Classification of Slovak white wines using artificial neural networks and discriminant techniques," J. Food Chem. 112, 1046–1052 (2009).

[23] S. Minaei, H. Bagherpour, M. A. Noghabi, M. E. Khorasani Fardvani, F. Forughimanesh, "A comparative study concerning linear and nonlinear models to determine sugar content in sugar beet by near infrared spectroscopy," J. Food Biosci. Technol. 6(1), 13–22 (2016).

[24] Y. Zhai, J. A. Thomasson, J. E. Boggess, R. Sui, "Soil texture classification with artificial neural networks operating on remote sensing data," J. Comput Electron Agr. 54, 53–68 (2006).

[25] M. T. Hagan, M. Menhaj, "Training feed forward networks with the Marquardt algorithm," IEEE Trans. Neural Netw. 5, 989–993 (1994).

[26] D. Perez-Marín, A. Garrido-Varo, J. E. Guerrero, J. C. Gutierrez-Estrada, "Use of artificial neural networks in near-infrared reflectance spectroscopy calibrations for predicting the inclusion percentages of wheat and sunflower meal in compound feeding stuffs," J. Appl Spectrosc. 60(9), 1062–1069 (2006).

[27] R. Stone, "Improved statistical procedure for the evaluation of solar radiation estimation models," Solar Energy 51(4), 289–291 (1993).

[28] AOAC, O±cial Methods of Analysis of AOAC International, 21st edition, https://www.aoac.org/o±-cial-methods-of-analysis-21st-edition-2019/ (2019).

[29] G. Hans, B. Leblon, P. Cooper, A. L. Rocque, J. Nader, "Determination of moisture content and basic specific gravity of Populus tremuloides (Michx.) and Populus balsamifera (L.) logs using a portable near-infrared spectrometer," J. Wood Mater Sci Eng. 10, 3–16 (2015).

[30] B. G. Osborne, T. Fearn, P. H. Hindle, Practical NIR Spectroscopy with Applications in Food and Beverage Analysis, Longman Group UK Limited, UK (1993).

[31] W. Saeys, A. M. Mouazen, H. Ramon, "Potential for onsite and online analysis of pig manure using visible and near infrared reflectance spectroscopy," J. Biosyst. Eng. 91(4), 393–402 (2005).

[32] M. Taurines, L. Brancheriau, S. Palu, D. Pioch, E. Tardan, N. Boutahar, P. Sartre, F. Meunier, "Determination of natural rubber and resin content of guayule fresh biomass by near infrared spectroscopy," J. Ind Crops Prod. 134, 177–184 (2019).