AN-NIR-143
2026-09
Semola and semolina quality control using NIR spectroscopy
Nondestructive analysis of protein, moisture, gluten, and more in semolina-based products
Summary
Good pasta products start with good ingredients—including flour. Semola and semolina are special types of flour made from durum wheat, known for giving the resulting pasta a firm texture, bright yellow color, and superior cooking character. The difference is that semola is coarse (milled once) and semolina is exceptionally fine (milled twice). To make high-quality pasta, it is important to check key properties of these flours, like protein, moisture, ash content, gluten, and water absorption. This Application Note shows how monitoring these parameters with near-infrared spectroscopy (NIRS) can help pasta manufacturers quickly detect the best semola and semolina to keep their products consistent, tasty, and of high quality.
Experimental equipment
Samples of semola and semolina flours were analyzed using an OMNIS NIR Analyzer Solid (Figure 1). Measurements were carried out in reflection mode while using a large sample cup. To enhance representativeness, the samples were rotated during the measurement, allowing the device to capture spectral data from multiple regions of each flour. OMNIS Software was used for all data acquisition and prediction model development.
Result
The OMNIS NIR Analyzer was used to monitor the quality of semolina and semola flours, focusing on protein, moisture, ash, gluten content, and water absorption. Figure 2 shows an example of some semola spectra gathered by the OMNIS NIR Analyzer Solid.
For semolina, moisture showed the strongest performance (Figure 3), with low prediction errors and a high correlation between NIR predictions and laboratory reference values. Ash, protein, and gluten content (Figures 4–6) were also quantified with good accuracy.
For semola, protein content was predicted with excellent correlation to the reference data (Figure 7), while moisture, ash, gluten, and water absorption also showed reliable calibration performance (Table 1).
Result moisture content in semolina
| R2 | SEC (%) | SECV (%) |
|---|---|---|
| 0.949 | 0.29 | 0.31 |
Result protein content in semolina
| R2 | SEC (%) | SECV (%) |
|---|---|---|
| 0.907 | 0.60 | 0.63 |
Result ash content in semolina
| R2 | SEC (%) | SECV (%) |
|---|---|---|
| 0.734 | 0.14 | 0.14 |
Result gluten content in semolina
| R2 | SEC (%) | SECV (%) |
|---|---|---|
| 0.550 | 1.71 | 1.87 |
Result protein content in semola
| R2 | SEC (%) | SECV (%) |
|---|---|---|
| 0.933 | 0.14 | 0.14 |
FOM from other semola prediction models
| Parameter (range) | No. Spectra | SEC (%) | SECV (%) | R2 |
|---|---|---|---|---|
| Moisture (12.5–15.1%) | 146 | 0.20 | 0.20 | 0.834 |
| Ash (0.74–1.12%) | 99 | 0.04 | 0.04 | 0.787 |
| Gluten (23–32%) | 43 | 0.67 | 0.81 | 0.815 |
| Water absorption (53.7–58.8%) | 37 | 0.37 | 0.44 | 0.82 |
Conclusion
This Application Note demonstrates the feasibility of using NIR spectroscopy to determine multiple key parameters in semolina and semola flours. As shown in Table 2, various traditional analytical methods are typically used for these measurements. However, NIR spectroscopy has proven to be a faster, simpler, and highly accurate alternative, offering excellent precision while streamlining the analysis process.
| Parameter | Method |
|---|---|
| Protein | ISO 1871 – Kjeldahl method |
| Moisture | ISO 760 – Karl Fischer |
| Ash | ISO 2171 – Determination of ash content |
| Gluten | ISO 21415 – Methods for determining gluten |
| Water Absorption | ISO 5530-1 – Determination of water absorption using a farinograph |