Can NIR help profits in palm oil mills?
Chapter 22
📁 Case overview: After integrating NIR technology directly at the production lines of a palm oil mill a while ago, the detectives head over to Colombia to see how the NIR system is performing for their client. Will they find that he has given up on the real-time analytical technique or will he be grateful for adding NIR to his processes? There’s only one way to find out, join the food detectives on their trip!
Eggcule Poirot and Shallot Holmes enter the agency with barely contained smiles on their faces. Eggcule Poirot puts his fingers in his mouth and whistles loudly to catch the attention of his colleagues. The other three food detectives look up startled and narrow their eyes in disdain at having been whistled, but walk over nonetheless curious about the whole fuss.
Eggcule Poirot is jumping from one leg to another, barely holding in his excitement. One of his arm, hidden behind his back until now, suddenly shoots out as he waves five plane tickets in the air. They are going on a trip to Colombia to visit an old customer of theirs. They want to see how his project is going first-hand and to collect his feedback on the methods the detectives had proposed to him for solving his challenges.
On the long flight over, Eggcule Poirot has all the time in the world to remind his colleagues of the details on the previous case. They had initially been hired to help a palm oil producer improve his oil extraction from fruit by minimizing oil losses and improving the oil extraction rate (OER).
The oil extraction rate of palm oil mills, in fact, has a high financial impact, directly connected to performance indicators that are used to measure oil losses. On average, a total oil loss of 6.2% occurs from the field to the storage tanks of the palm oil mill.
Together with the client, the detectives back then analyzed the oil loss indicators and identified when losses occurred, at which stage or from what by-product of the process:
- Husks
- Fruit attached to the husks
- Fiber
- Nuts in fibres in wet and dry shells
- Sterilization condensate
- Centrifuge sludge
- Cake
- During the optional double-stage separating system
At the time being, the client was completely frustrated with using reference methods. He wanted better ways to generate data, support decision-making and speed up process monitoring. he stressed to the detectives that processes at palm oil mills involve high demands on time, labour and conventional methods to monitor quality parameters create unnecessary delays in the workflow.
For example, the reference method to determine oil losses in a standard palm oil mill in Colombia, is Soxhlet extraction with a solvent, such as hexane or benzene. The client was not a fan of this method, as it took around four to five hours to obtain a result, so data was usually available on the day after the fruit was processed. Lab staff at the mill had to collect more process samples to determine additional quality parameters, but again, receiving the results only on the following day.
After consulting amongst themselves, it was Nancy Beef who proposed to either use nuclear magnetic resonance (NMR) or Near-InfraRed (NIR), as both technologies offered immediate determination of physiochemical parameters. After consulting the 5-step guide to improving profitability in food and feed, the detectives settled on NIR. This method can be used to obtain multiple parameters from spectroscopic analysis and the visual responses from a liquid or solid sample with prior calibration and formation of mathematical prediction methods. The calibration process depends on the reliability of the reference procedures performed in the laboratory, just as with other types of rapid-response analytical techniques. Once the NIR prediction models are developed, results can be obtained in a matter of minutes for each sample analyzed. Simultaneous results can even be obtained for each sample, including solid or oily matrices.
When Nancy Beef introduced the client to NIR, he was happy to see that he could measure variations in indicators of losses, or quality parameters, at each stage of his workflow. He recognized right away that he could stop the process immediately to adjust parameters, such as pressure and temperature.
Making real-time adjustments throughout the process would save him considerable amounts of time and money, with a return of the investment on his equipment in a matter of months, as oil loss is one of the most significant factors affecting business profitability.
After agreeing to try out NIR, the food detectives wasted no time in setting up the lab and at-line NIR systems for him. They also integrated NIR-Online technology on his process line, as a real-time monitoring tool for the industrial oil potential (OP) of the fruits per provider.
After dedicating some time to the project, the team was able to generate new prediction models for variables from the numerous products obtained from cultivation of oil palm. This involved validating and calibrating reference parameters in the lab, improving the NIR model’s prediction efficiency by monitoring statistical indicators. Eggcule Poirot and his team also evaluated and adjusted the NIR equipment in the palm oil mills based on prediction models.
Nancy Beef and the team developed models for the analysis of crude palm oil, fiber, and pressed husk samples to measure:
- Free Fatty Acids (FFA)
- Moisture
- DOBI
- Oil loss
- Impurities
A few years later, the food detectives are back in Colombia to see how satisfied the client is with his NIR technology for quality control of palm oil.
They find him extremely enthusiastic and thankful for their ideas and help with integrating NIR into his processes. He chatters away happily about all the benefits and after spending the whole day touring the palm oil mill and various production lines, the detectives find a moment to jot down and summarize all his statements. Eggcule Poirot collects their notes and draws out a table of how, in this case, NIR technology compared to conventional technology with regards to several important process parameters:
Aspect | Conventional Technique | NIR Technology |
---|---|---|
Analysis time | 4-5 hours for oil content; 10-15 minutes for other parameters | About 1 minute irrespective of sample type |
Precision / accuracy | Very high, given that they are reference methods | High, thanks to reproducibility of the results |
Cost per analysis | High | Low |
Information for each analysis | Different procedures for each parameter measured | A single measurement simultaneously generates values for various parameters |
Sample treatment | Complex: quartering, weighing and use of chemical reagents | Simple: no need to weigh or use chemical reagents, as it depends on optical analysis of light on matrices |
Permits | Clearance certificate needed (anti-narcotics - Information System for the Control of Substances and Chemicals (SICOQ) Cost of processing and time availability | None required |
Involvement of an analyst | High | Low (enabling the analyst to perform more sampling and/or process controls and analysis of data obtained) |
Safety | Risk of fire or exposure to chemicals (such as hexane or acids) | No chemicals used |
Environmental considerations | Generates solid and liquid waste; hazardous gases | Does not generate any hazardous waste |
Operation | Requires multiple items of equipment and components in the laboratory | NIR ProxiMate: all-in-one solution: PC + sensor + Internet connection port for remote support |
Opportunity for decision-making | The most important results, such as oil losses, are available after a minimum of 4 hours of processing time | Once the sample has been analyzed, crucial decisions can be made immediately - such as stopping the process to adjust the equipment to reduce the loss indicator being monitored |
The detectives are fully satisfied they had achieved what they came for. They observed the process together with the implemented NIR systems, well after its introduction and they could compare how the workflow is running with NIR versus traditional methods. This would be useful information to share with future clients facing similar challenges and limitations.
The detectives bid their farewells and hop on the red eye back home. Everyone falls asleep, but Eggcule Poirot. He spends his time watching a webinar of his client discussing use of NIR in palm oil mills. He smiles to himself. Another great case in the palm of their hand.