The SMRI-NIRS technology Part 2: Improving factory performance

Shaun Madho; Bryan Barker

The Sugar Milling Research Institute NPC (SMRI) has developed a Near Infrared Spectroscopy (NIRS) analytical method for use in sugarcane factories, initially for use in South Africa, in place of conventional analytical methods. Details on the development, validation and benefit of the SMRI-NIRS analytical method are reported in Part 1 of this paper (Walford 2019). By 2019 all South African sugarcane processing factories had discontinued conventional analyses in favour of the SMRI-NIRS method for factory control purposes. The SMRI-NIRS method predicts analytical results of dry solids, polarimetric sugar, sucrose (HPLC), glucose, fructose, conductivity ash contents as well as ICUMSA colour and pH value from a single NIRS scan of any suitably diluted sugarcane process stream sample. Final molasses dry solids can also be predicted. In addition to improved laboratory output, the additional analytical data can be used to improve factory performance. This paper gives examples of where the SMRI-NIRS technology, the analytical method and the associated decision-support toolkits, have been used in South African factories to improve factory sucrose recoveries and the reporting of factory performance figures, such as: – Use of direct sucrose-based stocktakes and performance reporting. This is instead of performing polarimetric sugar analyses and then using a pol:sucrose ratio to convert to a “sucrose-based” recovery. The application of reporting of “gravity” purity instead of “apparent” purity is also discussed. – Inversion loss determinations across unit operations, including an account of a factory that, in one week, performed 34 tests across the evaporator station, with each test comprising measurements across all evaporator effects. – Use of factory-determined final molasses target purity differences (TPD) from each centrifuge to identify poorly operating centrifuges and to perform screen evaluations. – Determination of reducing sugar profiles on all process streams to identify possible inversion losses and Maillard-type reactions. – Use of daily SMRI-NIRS reports to identify areas of poor performance in addition to specialised SMRI-NIRS decision-support toolkits to aid further investigations.

2021 (146) 406–413
Language: ENG

The beet sugar factory of the future

Jan Maarten de Bruijn

The beet sugar industry is facing several challenges for the future. The climate change is requiring a transition from the traditional fossil fuel to a greenhouse gas neutral energy source. The available possibilities for this purpose will be outlined in this paper. The recent EU sugar market reform has markedly increased the competition between sugar companies and the resulting lower sugar price has a significant impact on the profit margin of sugar production. In order to keep up with these challenges it is key to make an appropriate use of the available opportunities to improve the cost-efficiency of sugar beet processing. The different means to advance the sugar business are better asset utilization, continuous process improvement, introducing innovative process technologies and further developing a sugar factory into a biorefinery with a further valorisation of (co-)products and wherein synergy is obtained between different on-site process operations. Why and how these different available tools can improve the competitiveness of sugar factories will be discussed in detail. A proper combination and choice of the suggested changes and opportunities will enable sugar factories to get prepared for the future.

2021 (146) 391–405
Language: ENG

The SMRI-NIRS technology: development, validation and benefit

Stephen N. Walford

The Sugar Milling Research Institute NPC (SMRI) has developed a simple to use near-infrared spectroscopy (NIRS) transmission-based analysis method as an alternative to conventional methods for analysis of sugarcane factory stream samples. The technology provides rapid, simultaneous analysis of refractometric dry substance (rds), polarimetric sugar, sucrose, glucose, fructose, conductivity ash contents as well as colour and pH for all streams and additionally, dry solids for final molasses and eliminates the need for sample clarification chemicals. The analyte prediction equations were developed using conventional results of samples from 14 South African factories, analysed at SMRI using SANAS/ISO17025 accredited test methods, and NIRS scans of the same samples using up to 16 different NIRS instruments. The NIRS analyte prediction equations were validated against more than 1,500 independent factory samples that had been analysed by conventional methods of analysis, including samples from factories outside South Africa. The reproducibility of the NIRS results were equivalent to existing conventional analysis reproducibility values (juice and final molasses) and previously undocumented values determined for this study for conventional raw house analysis methods. Correlation coefficients of greater than 0.97 were recorded for all major analytes and greater than 0.9 for minor analytes when predicted results were compared against conventional results. A maintenance protocol was also developed to ensure that the prediction equations remain robust and can account for sample matrix variations that can occur from season to season. The SMRI-NIRS technology was installed at all 14 South African factories and found to be robust and give equivalent results to conventional methods of analysis.

2021 (146) 354–359
Language: ENG

Identification of the microbiota in sugar extraction juices by sequencing-based techniques

Cordula K. Moser; Christina Ukowitz; Florian Emerstorfer; Walter Hein; Konrad J. Domig

The importance of microorganisms in the beet sugar industry came up in 1930. Since then, several approaches have been made to describe these bacteria. For this purpose, mainly cultivation-based methods were applied. However, the majority of the microorganisms cannot be cultivated or are in the viable-but-non-culturable state. In addition, these methods are time-consuming and costly. Progress in molecular biology allows a cheaper, faster and more precise identification of the microbiota. This study evaluates the application of an 16SrDNA-based metagenomic sequencing approach based on Illumina MiSeq technology to identify the microbiota in raw juice and juice of mid-tower in a beet sugar production plant and compares the results with those obtained by cultivation-based techniques. All bacteria orders detected with cultivation-based methods could be also found with the applied metagenomic approach. In raw juice, mainly mesophilic bacteria such as Lactobacillus spp. and Leuconostoc spp. species were identified. Additionally, a partly large proportion of gram-negative bacteria belonging to the order Enterobacterales were detected by the metagenomic approach. The diversity in juice of mid-tower was much lower and predominated by mainly thermophilic genera such as Geobacillus, Caldanaerobius and Thermoanaerobacter. The last two mentioned genera belong to the class of Clostridia. Surprisingly, in the juice of mid-tower Lactobacillus species could be verified by cultivation-based methods as well as by the metagenomic approach. As a consequence, it can be presumed that lactobacilli can survive in this very specific environment at 70°C occurring in the central part of the extraction tower.

2021 (146) 346–353
Language: ENG

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