BLT Stages

Abstract Bachelor Project 1 FBT 2020-2021: Validation of the updated calibration line of the Infratec device by using cotyledons and full soybeans

Alpro utilizes two methods in order to determine the moisture content, protein concentration and protein factor of soybeans and cotyledons. The fast method uses the Infratec NOVA, this is a device that determines these parameters using near infrared transmitter technology. It uses a software that constantly updates the device calibration curve. The purpose of my research is to validate the updated calibration curve so that it can be used for analysis. Alpro has two Infratec devices: one is LAB 286, the other is LAB 198. Six cotyledon samples and six bean samples were selected for these experiments. Validation is done by using validation parameters. Because the Infratec NOVA is an assay test, linearity, accuracy, precision and bias are determined. Because some validation parameters require nominal values, these must also be established. This is done by using the official method for determining the moisture content, protein concentration and protein factor with the drying oven and the Kjeltec device. The validation parameters have been given acceptance limits and beyond these limits the parameters will not be accepted. Linearity is acceptable when at least 75 % of the values deviate maximum 2 % from the back calculated values. The validation for linearity was completed successfully for the protein concentration and the protein factor of both soy beans and cotyledons. This was not the case for the moisture content when measuring the beans on both devices. With the Lab 286 device, only 56 % of the measurements remained below 2 %, with the Lab 198 device, only 61 % of the measurements. The accuracy was determined as acceptable when all the measurements of the cotyledons have a maximum deviation from the nominal values of 2 %. For the beans the maximum acceptable value was 3 %. Once again the accuracy of the protein concentration and the protein factor Was accepted, while the moisture determination of both the beans and the cotyledons was problematic. The precision is acceptable when all measurements vary less than 2 % from each other. This was accepted for the protein concentration, the protein factor and the moisture determination, for the beans and the cotyledons, and this applies to both devices. Bias is acceptable when the result is below 5 %. This was accepted for the protein concentration, the protein factor and the moisture determination, for the beans and cotyledons, and this applies to both devices. After careful consideration, it was concluded that the calibration curve has been validated, provided that there is a follow-up experiment for the moisture content of the beans and cotyledons. This postscript should be focused on the significance of different storage temperatures and its relative effects on the moisture content measurements.

Abstract Bachelor Project 1 FBT 2020-2021: Validation of the rapid thermogravimetric method to determine dry matter content against the official method with relevant matrices

The dry matter content of a food matrix is determined by two thermogravimetric methods, on the one hand, the Sartorius dry unit moisture analyzer 35 and on the other, the drying oven. Thermogravimetry heats the mass of a sample until constant weight is obtained. It is therefore important that these values are within the acceptance limits before the food matrix is sent to the store.

Now the food matrix is dried at x°C in the Sartorius MA 35, but is this the correct temperature for the food matrices compared to the official method? This research will try to find the optimal temperature to accurately determine the dry matter content of samples on the MA 35 by making 100 measurements at five different temperatures. The MA 35 appliance is a fast and small thermogravimetric method for infrared drying. It uses infrared radiation to heat the matter and evaporates the moisture. The official method is a large and slow thermogravimetric drying oven that uses forced convection. The dry matter is determined by a continuous warm air flow. Furthermore, quality parameters such as Grubbs-test, normal probability plots, standard deviations, means, range, accuracy and precision are applied.

The examined food matrices are divided into four groups: W, X, Y and Z. The group W has the following formulas W1, W2 and W3. Based on the obtained standard deviations, means and the range of the values of the MA 35 compared to the drying oven, the following optimal temperatures are obtained W1 (105°C), W2 (125°C) and W3 (125°C) after taking the quality parameters into account. The group X has the following formulas X1, X2, X3 and X4. The following optimal temperatures were found here are: X1 (125°C), X2 (105°C), X3 (125°C) and X4 (125°C). The Y group has the following formulas Y1 and Y2. The following optimal temperatures were found Y1 (125°C) and Y2 (145°C). The last group Z has the following formulas Z1 and Z2. The following optimal temperatures were found Z1 (105°C) and Z2 (125°C).

Based on the above results, it can be concluded that 125°C seems to be the most optimal temperature since seven of the eleven matrixes examined suggest this as the ideal temperature. However, further research will be required as four matrices do not obtain ideal quality of measurement with this temperature.

Abstract Bachelor Project FBT 2019-2020: Validation of the fast determination of the moisture content using the thermogravimetric method versus the official method

BACKGROUND: This project is about the validation of a thermogravimetric device to analyze the dry matter of different samples. Since the previous project, in 2018, was not finished and there was no conclusion formed, the project will be continued. This within a period of 13 to 15 weeks. The project is necessary to become a most ideal temperature for the device to test the different samples. There will not be a perfect fitting temperature for all the different samples but there can only be one temperature chosen for an easy way of working.

AIM: The main goal of this project is to validate and optimize the thermogravimetric device. There are different methods, samples, temperatures, … that are going to be measured. After all the necessarily data is collected the results will be graphically displayed and will be put in clearly arranged tables. Thereafter everything will be compared and a conclusion will be formed.

METHODS: There are eight samples of which three of them will be ½ diluted. This is because some specific products need to be diluted. Also, the diluted and undiluted products will be compared to each other to see if a dilution is still necessary. The samples are each of the fully completed product and an earlier phase from the process of production.

The first method is to put the samples in the drying oven for a specific time at a certain temperature and their weight will be measured before and after drying. The percentage of dry mass will be calculated by an integrated formula in an Excel file. In the thermogravimetric device, the second method, the drying percentage will be measured by five different temperatures and each of them with and without a glass fiber filter. All the samples will be measured in triple for a more trustworthy result. Thereafter the average will be taken of all the results and the results of both methods will be compared. The temperature that is the best for most of the samples will be chosen.

RESULTS AND CONCLUSION: The samples need to be evenly spread in the middle of the aluminium plate for the best results. Make sure that the sample does not go to the edge of the aluminium plate. Also, the thermogravimetric device needs to be preheated. The first sample is not reliable because the device only heats up when the sample has started testing. The highest temperature that is used to analyze the samples with a filter is too high. The samples get a burned smell and there is crust formation. A lower temperature is recommended, but a lower temperature will result in a longer during analyze. The filter makes the duration of the analyse shorter so this will be compensated. This has a positive effect on the results: it takes less time to analyze the samples and the values are more equal. With the use of a filter a lower temperature is recommended. Without using a filter a higher temperature is better. And the last fact is that dilution makes the duration of the analyze shorter, so this can be continued.