Direct Determination of Sugar Cane Quality Parameters by X-ray Spectrometry and Multivariate Analysis

Melquíades, Fábio Luiz; Bortoleto, Gisele Gonçalves; Marchiori, Luis Fernando Sanglade; Bueno, Maria Izabel M. S.

doi:10.1021/jf302471b

Cited by 27 publications

(15 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In alternative methodologies to estimate Pol, the accuracy of the model in the calibration phase is often high. However, it becomes little accurate and with high bias in the validation (Melquiades et al, 2012). This is because the samples do not have contrasting conditions and the model ends up generalizing the results.…”

Section: Resultsmentioning

confidence: 99%

Application of artificial neural networks in the prediction of sugarcane juice Pol

Coelho

Bettiol

Dalri

et al. 2019

Rev. bras. eng. agríc. ambient.

View full text Add to dashboard Cite

Innovative techniques that seek to minimize the costs of production and the laboriousness of certain operations are one of the great challenges in the sugar-energy sector nowadays. Thus, the objective of the present study was to estimate the Pol values of sugarcane juice as a function of °Brix and wet cake weight (WCW) using artificial neural network (ANN) modeling. A database was organized consisting of 204 technological analyses from a field experiment with 15 treatments and 2 years of evaluation. 75% of the data were used for the calibration of the model and 25% for its validation. Multilayer Perceptron ANNs were used for calibration and validation of the data. Before calibration, the variables were normalized. The training algorithm used was backpropagation and the activation function was the sigmoid. The ANNs were established with two hidden layers and the number of neurons ranging from 4 to 20 in each. The 15 ANNs with the lowest root mean square errors were randomly presented by the software, among which 6 were chosen to verify the accuracy. The ANNs had a high accuracy in the estimation of sugarcane juice Pol, both in the calibration phase (R2 = 0.948, RMSE = 0.36%) and in the validation (R2 = 0.878, RMSE = 0.41%), and can replace the standard method of analysis. Simpler networks can be trained to have the same accuracy as more complex networks.

show abstract

Section: Resultsmentioning

confidence: 99%

Application of artificial neural networks in the prediction of sugarcane juice Pol

Coelho

Bettiol

Dalri

et al. 2019

Rev. bras. eng. agríc. ambient.

View full text Add to dashboard Cite

show abstract

“…An attenuated total reflectance Fourier transform infrared spectrometry, with multivariate analysis [5], has been employed to measure sucrose content in cane juice using the characteristic absorption bands of sucrose at 800-1250 cm −1 . An X-ray spectrometry and multivariate analysis [6] has also been reported for direct determination of sugar can quality parameter, including sucrose and fiber contents. Thermometry has been reported by Thavarangkul based on the hydrolysis of sucrose by invertase enzyme immobilized on a sensing thermistor [7].…”

Section: Introductionmentioning

confidence: 99%

Sequential Injection System for Analysis of Degree Brix, Orthophosphate and pH in Raw Sugarcane Juice Applicable to Sugar Industry

2021

View full text Add to dashboard Cite

This work presents, for the first time, a new sequential injection analysis (SIA) method to simultaneously analyze degree Brix, orthophosphate and pH in raw cane juice. These key parameters relate to price of harvested sugarcane and quality of cane juice for sugar production. The SIA system employed two detectors: the first detector is a diode-array spectrophotometer, equipped with a regular flow cell, for measurements of degree Brix and orthophosphate. Quantitative of degree Brix (°Bx; ca. % (w/w) sucrose) was based on manipulation of the schlieren effect at the interface between plugs of sample and water. Orthophosphate analysis was carried out based on the molybdenum blue method with significant reduction in consumption of the reagents. Compensation of the schlieren effect from sucrose for determination of orthophosphate was achieved by using a dual-wavelength spectrometric detection. Second detector is a pH-sensing device, called ion-selective field-effect transistors (ISFET). The ISFET is based on the current through the ISFET arising according to the H+ concentration in solution. Our developed SIA system provides linear calibration graphs fitting for purpose in analysis of sugarcane juice (pH: 0–14, °Bx: 1.0–7.0 and P2O5: 20–200 mg L−1). Simultaneous analysis of sugarcane juice for pH, °Bx and P2O5 is carried out within 5 min (12 sample per h). Precision of SIA system is acceptable (RSD < 3%). Our SIA system gave quantitative results insignificantly different, as compared with conventional methods for analysis of pH, °Bx and P2O5 in sugarcane juice.

show abstract

“…LIBS and XRF have been employed for the determination of macronutrients and micronutrients in different plant leaves, for example, sugarcane, cannabis , black tea, tomato, medicinal plants, orange, lemon, wheat, soybean, cotton, maize, and grass . However, in all the above mentioned studies, prior to analysis, the leaves were either detached from the plants or pelletized after washing, drying, and grinding …”

Section: Introductionmentioning

confidence: 99%

Direct determination of mineral nutrients in soybean leaves under vivo conditions by portable X‐ray fluorescence spectroscopy

et al. 2019

View full text Add to dashboard Cite

A portable energy dispersive X‐ray fluorescence (XRF) spectrometer furnished with an Rh X‐ray tube was evaluated for the determination of macronutrients and micronutrients in soybean leaves (Glycine max L.). XRF instrumental parameters were optimized in a univariate way, and emission intensities were measured for 60 s and under vacuum for macronutrients, and during 180 s, under air, and 305 μm Al/25.4 μm Ti filter, for micronutrients. Fresh and dried leaves were irradiated, and it was possible to identify P, K, Ca, S, Mn, Fe, Cu, and Zn Kα emission lines. For comparative purpose, the samples were also microwave assisted, digested and analyzed by inductively coupled plasma optical emission spectrometry. In general, linear correlations between K, Ca, Mn, Fe, Cu, and Zn concentrations in the tested samples and the corresponding portable XRF (pXRF) intensities were obtained. The linear correlation coefficients (R2) ranged from 0.42 to 0.86. In addition, the detection limits were suitable for plant nutrient diagnosis. It is demonstrated that pXRF is a simple and powerful tool for analysis of plant materials.

show abstract

Direct Determination of Sugar Cane Quality Parameters by X-ray Spectrometry and Multivariate Analysis

Cited by 27 publications

References 42 publications

Application of artificial neural networks in the prediction of sugarcane juice Pol

Application of artificial neural networks in the prediction of sugarcane juice Pol

Sequential Injection System for Analysis of Degree Brix, Orthophosphate and pH in Raw Sugarcane Juice Applicable to Sugar Industry

Direct determination of mineral nutrients in soybean leaves under vivo conditions by portable X‐ray fluorescence spectroscopy

Contact Info

Product

Resources

About