By Aamarpali and Sneh Lata


Using Near Infrared Spectrophotometer of Elico (India) in the spectral range of 600-2500nm, online method of estimation of various impurities (polysaccharides, inorganic compounds and amino acids) in cane juice has been developed. Standard error of calibration and standard error of prediction was evaluated for each impurity using Partial Least Square Regression Analysis and Multi Linear Regression Analysis. Multi Linear Regression Analysis was also done and the wavelengths were identified at which the absorbance correlated well with the concentrations of particular impurity. Brookfield (HBDV-III) programmable Rheometer with small sample adapter that was double walled system of sample volume 8ml was used to study the effect of these impurities (polysaccharides, inorganic compounds and amino acids) at different temperatures (313, 318, 323, 328 and 333 K) on the rheology of final cane molasses.

Key words: near infrared spectrophotometer, rheometer, calibration, transmittance, molasses


The scientists are able to give their best research and that to in time is due to the usage of electronic equipment in their research laboratories. An electronic laboratory is always first choice of any researcher because the results are derived in shortest time span, there is no doubt about the result if instrument is properly calibrated, wastage of chemicals is less and apart from this the samples which can’t be kept for long time are analyzed best. Physical properties of substances are exactly measured by electronic equipment rather then glass made objects.

In the present manuscript the use of various electronic equipment is given for research work done in sugar technology. The research given here was impossible without electronic equipment In sugar industry the testing of sugarcane for pol, brix, sucrose content, invert and other common constituents have traditionally been done by a series of ICUMSA (International Commission for Uniform Methods of Sugar Analysis) and AOAC (Association of Official Agricultural Chemists) test methods. As many of these methods are time consuming, operator dependent and involve the use of hazardous reagents so Near-Infrared analysis has gained rapid acceptance as an alternative method. The various applications (Edye and Clarke, 1996) of NIR in sugar industry are analysis of raw sugar, refinery liquors, run-off syrups, remelt streams, molasses and low purity streams. Near Infrared analysis of shredded (Schaffler and Meyer, 1996) cane is being used as potential replacement for direct analysis of cane. The increased demand for quality sugar at low cost is the main objective behind doing research in this field. Sugar cane juice, which is main source of sugar, can’t be kept for long time. It gets decayed with time and temperature. It develops various microorganisms if preserved at high or low temperatures. To move forward and to get some important clues, the decision was taken to study sugarcane impurities (polysaccharides, inorganic compounds and amino acids). These impurities are natural constituent of cane juice. Starch gets gelatinized by heating during juice clarification and is removed to an extent of 30-35 % but the rest gets concentrated in the process stream due to evaporation of the clear juice. The resulting harmful effects of it are the increase in viscosity and poor juice filterability. Mechanical harvesting has resulted in an increase in the quantity of bacterial polysaccharides like soluble dextran in the juice (Cuddihy and Donal, 1999). Dextran that enters the juice remains with it until crystallization of the sugar. Dextran formation causes sugar loss (Donal, 1994), processing problems (James and Cameron, 1971) and increases the viscosity manifold (Sikdar and Ore, 1979). Presence of phosphate in optimum concentration in cane juice is essential for good clarification and has beneficial effect on sugar crystallization. The (Mathur, 1986a) optimum requirement of P2O5 is 300-500mg per liter of juice in the form of soluble phosphate. When the phosphate content in the clear juice is less, the deficiency should be made up by the addition of P2O5 the form of soluble phosphate before clarification. Silica, during crystallization creates problem by forming calcium silicate scales in the inner surface of the boilers, which are too hard to be removed. So the removal of these deposits by mechanical and chemical means is a time consuming and costly experience. The main amino acids found in cane juice are alanine and glycine. Cane juice (Mathur, 1986b) contains nitrogenous bodies such as albuminoids, ammonia, amino acids (alanine and glycine) and amides varying from 0.5 to 1.0%. Amino acids are of importance as they along with other nitrogenous bodies react with reducing sugars and form colored compounds. So therein lays the need to study these impurities in sugarcane individually. In present study impurities are estimated in cane juice with the help of Near-Infrared (NIR) spectrophotometer. NIR spectroscopic technique is environment friendly as it avoids the usage of lead sub-acetate for clarification of cane juice. The individual effect of these impurities on the rheology of final molasses is also studied. Equipment by equipment role in sugar research is given below.

Near Infrared Spectrophotmeter:

Near-Infrared spectrophotometer of Elico (India): Spectral range 600-2500 nm, bandwidth 10 nm, accuracy +0.5 nm, repeatability + 0.2 nm and with advanced state of the art MS Windows® based software for data acquisition was used. In NIR spectroscopy, a spectrum is run over the Near-Infrared wavelength range (800-2500 nm), in a manner analogous to the spectrum run in the visible range in UV- visible spectrophotometers. In this NIR spectrophotometer processing, storage, retrieval and interpretation of complex spectra can be done. This spectrophotometer helps in quantitative estimation of impurities in cane juice using regression analysis. The instrumental set up is shown in the Fig.1. It is PC based user friendly and menu driven. It is having high performance concave grating monochromator and two color detector.

The basic principle of this instrument is, that Near-Infrared radiation when incident on a sample gets transmitted. In transmission mode, the incident radiations get transmitted through the sample with diminished energy. The amount of transmitted energy from the sample is a measure of concentration of the constituent molecules in the sample. A series of standards of known concentration is used to develop concentration absorption correlation, using regression technique. The concentration of the constituent molecule in the sample is determined based on the correlation.

In contrast to conventional methods it require no hazardous chemicals. The striking features of the Near-Infrared technology are as follows:

-Designed for all cane and beet juice, syrups and molasses;

-It is environment friendly since no chemical reagents are used for the tests.

– Easy to use, thus permitting analysis of clear to turbid liquids without clarification or filtration;

-Frequency of response is online and continuous;

-Single and multiple-constituents analysis possible.

One more advantage of using NIR technology is that it has no consumables and operational costs are low, after purchasing the information technology equipment and the package there are no other costs involved. However, in case of conventional laboratories costly consumables are used and thus the operational costs are high. In this method firstly initial concentration of particular impurity is determined in cane juice. As the accuracy of NIR analysis is wholly dependent on the quality of calibration set so utmost care was taken in gathering, selecting and preparing samples to be used for calibration. While collecting samples it was taken into consideration that the samples should cover wide range of constituent’s concentration. The cane juice samples undergo chemical and biological (microbial) degradation with time. So the samples were analyzed on the same day without any delay. Calibration models were prepared for impurities. using PLSR. Separate prediction files were also prepared. In NIR estimation the prediction value is obtained from software, which gives required value by comparing with the calibration file chosen. The SEC is found to be negligible for all impurities thus indicating the correctness of models set up for them.

Brookfield Rheometer:

The rheology of final molasses was studied using Brookfield (HBDV-III) programmable Rheometer with small sample adapter, which was double walled system of sample volume 8ml. The spindle of spindle code SC4-21/13R was used. Brookfield refrigerated temperature bath model TC 500 was used to maintain uniform and constant temperature. The water at a given temperature was circulated in water jacket.

The final molasses samples of local mill were firstly defoamed. In the final molasses sample the initial concentration of different impurities were determined. The brix and purity of final molasses samples were also noted. For each sample rheological characteristics (shear stress, shear rate and apparent viscosity) were recorded directly from the instrument at the temperatures 313, 318, 323, 328 and 333 K. The measurement was carried out at these five temperatures in the increasing order of concentration of impurity for all samples. The rpm was so selected that the torque maintained within 10-90 %. The shear stress and shear rate data obtained during experimentation was fitted to the Power law model (Heldman and Singh, 1981). This revealed the flow behaviour of molasses in the presence of various impurities. The consistency of final molasses increased with the increase in phosphate concentration but decreased with increase in alanine and glycine concentrations. With the increase in concentration of silica in final molasses up to 20 ppm the consistency increased prominently but as the concentration of silica was further increased steep fall in the consistency of final molasses was observed. However with increase in temperature the consistency decreased with increase in concentration of phosphate, silica, alanine and glycine in final molasses. The final molasses behavior was found to be non-Newtonian at low temperature in all the five samples analyzed for phosphate however pure molasses sample at high temperature showed Newtonian behavior.

For final molasses samples containing added silica the behavior was non-Newtonian in sample having 0 and 10 ppm silica (at all the five temperatures), Newtonian in molasses sample having 20 ppm silica (at 328 and 333 K) and again non Newtonian in final molasses sample having 30 and 40 ppm silica (at 313, 328 and 333 K).

For final molasses samples having added alanine the molasses was found to be non-Newtonian at low temperatures but with increase in concentration of alanine in molasses samples, at higher temperature the flow behavior was shifted to Newtonian. Also for final molasses samples containing glycine the behavior was found to be non-Newtonian at low temperature but shifted to Newtonian with rise in glycine concentration in final molasses at higher temperatures.

The Arrhenius equation is used to describe the influence of temperature on consistency index (µ). The energy of activation was calculated for pure final molasses samples and for samples having added impurities. The energy of activation was found to decrease with increase in concentration of phosphate in final molasses and increase with increase in concentrations of silica, alanine and glycine in final molasses.

With this I limit my manuscript that relates electronics and sugar technology research.

ACKNOWLEDGEMENT: Author Dr. Aamarpali Ratna Puri is very thankful to Guru Nanak Dev University, Amritsar for providing necessary instruments and infrastructure for the present research.


Cuddihy, J. A. and Donal, F.D., 1999. Process and financial impact of Dextran on a sugar factory. Sugar Journal 3: 27-50.

Donal, F.D., 1994. Dextran induced sugar loss to molasses. J of ASSCT 1: 53-57.

Edye, L.A and Clarke, M.A. (1996). “Near Infrared Spectroscopy in sugar refining: Five years down the road”. Proc. Annual. Meeting. Sug. Ind. Tech., 55, 1-8.

Heldman, D.R and Singh, R.P. (1981). “ Food Process Engineering, the AVI Publishing Co

Inc, West Port.

James, G. P. and Cameron, J .M., 1971. The influence of deteriorated cane on raw sugar filterabilityProceedings of the Queensland Soc. Of Sugarcane Technologists 38th Conf Wattson Ferguson & Co., Bribane, Queensland, Australia 247-250.

Mathur, R.L. (1986a). “Handbook of cane sugar technology”. IInd Edition, Oxford and IBH Publishing Co., India, 98.

Mathur, R.L. (1986b). “Handbook of cane sugar technology IInd Edition”. Oxford and IBH Publishing Co., India, 26.

Schaffler, K.J and Meyer, J.H. (1996). “Near Infrared analysis of shredded cane: A potential replacement for direct analysis of cane”, Proc. Sth. Afr. Sug. Tech. Assoc., 70 (5), 131-139.

Sikdar, S. K., and Ore, F., 1979. Viscosity measurement of non-Newtonian slurry suspension using rotating viscometer, I and EC Process Design and Dev. 18, 772.


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