Pro Tip: Five nondestructive assessment methods for evaluating the quality of baked products.
The demand for high-quality baked goods has driven significant advancements in nondestructive assessment techniques. Rising consumer awareness and advancements in sensor technology are pushing the food manufacturing industry to innovate.
There are several nondestructive methods for evaluating the quality of baked products; each with their specific applications, advantages and limitations.
Near-Infrared Spectroscopy (NIR) and Hyperspectral Imaging (HSI)
NIR and HSI are pivotal in assessing moisture content, texture and ingredient distribution in baked goods. NIR uses the interaction of materials with infrared light to determine moisture levels, crucial for shelf life and texture maintenance.
HSI, combining spectroscopy and image processing, provides detailed spectral and spatial information, useful for monitoring chemical component distribution, surface defects and quality control. For example, Nallan Chakravartula, et al. (2019) used NIR to predict moisture content in mini-burger buns, showing its potential in quick moisture determination during food drying processes.
Magnetic Resonance Imaging (MRI)
MRI is extensively used to visualize internal structures and monitor baking processes. It helps in studying dough properties during fermentation and baking, moisture and oil distribution, and structural changes during storage.
The technique offers non-invasive, real-time monitoring, which is crucial for optimizing baking parameters and ensuring product consistency. Studies by Bajd and Serša (2011) demonstrated the use of MRI in evaluating pore distribution and volume changes in dough during fermentation and baking.
Ultrasound Techniques
Ultrasound methods measure the velocity and attenuation of sound waves passing through the product, providing insights into density, porosity and air pockets. This technique is valuable for assessing texture and uniformity. Peressini, et al. (2017) found that ultrasonic parameters could predict rheological properties and bread quality attributes across different formulations, proving its reliability.
X-ray Microcomputed Tomography (X-ray μ-CT)
X-ray μ-CT creates high-resolution 3D images of the internal microstructure of baked products. It is beneficial for analyzing the spatial arrangement and quantifying microstructural characteristics.
This technique is non-destructive and allows for in situ scanning, making it a preferred choice for detailed internal analysis. X-rays from synchrotron sources, though less available, offer higher resolution and faster acquisition, suitable for dynamic studies.
Applications and Industry Integration
The integration of these techniques into the baking industry ensures consistent product quality, meeting consumer expectations for sensory traits such as texture, flavor and appearance.
Nondestructive methods provide real-time data, enabling timely production decisions and quality control. They facilitate defect detection, nutritional content prediction, texture evaluation, shelf life forecasting and process monitoring.
However, challenges such as cost, calibration, standardization and data management remain. The reliance on big data necessitates robust analytical methods to handle the large datasets generated by these techniques. Machine learning and artificial intelligence are increasingly employed to enhance data analysis, pattern recognition and decision-making processes.
The future of nondestructive assessment in the bakery industry looks promising with continuous technological advancements. Emphasis on Industry 4.0 and smart manufacturing will likely drive further innovation, improving efficiency and product quality. Researchers are encouraged to explore and refine these techniques, addressing current limitations and expanding their applications.
The adoption of nondestructive assessment methods marks a significant step towards advanced quality control in the baking industry. By preserving product integrity and providing rapid, accurate analyses, these innovations ensure the production of high-quality baked goods that meet consumer expectations and regulatory standards.
Reference:
Olakanmi, S.J., Bharathi, V.S.K., Jayas, D.S., & Paliwal, J. (2024). Innovations in nondestructive assessment of baked products: Current trends and future prospects. Comprehensive Reviews in Food Science and Food Safety.
Dr. Senay Simsek , serving as the department head, professor and dean’s chair in food science at Purdue University, possesses a background in cereal science, technology and wheat quality. Her goal is to foster collaboration between producers, scientists and food processors, optimizing research potential in this area.
