The Food Engineering Research Laboratory at the University of Kentucky is a multi-disciplinary science lab that integrates approaches from different sciences and technologies, designed in a way to meet the growing need for engineering application in food processing in the food industry. Our central goal is to train manpower for the food industry in the Kentucky and US, develop food engineering solutions that will strengthen and improve the food system in Kentucky, nationally, and internationally.

This we are accomplishing through an integrated research, instruction, and outreach program where engineering principles are applied to address the core issues related to the provision of adequate, safe, appealing, stable and nutritious food for all. At the heart of these are four important research areas that we specialize on, which include but not limited to:

1. Grain Value Addition

Underutilized grains valorization: There is need to source for alternatives to common grains like corn and wheat due to their competitive use and the attraction to the rich nutrient profile in some of the alternative grains. Our initial approach focused on understanding the physicochemical characteristics of different proso millet cultivars grown in the US. We have studied the rheological properties and baking quality of batter systems from proso millet and we have identified cultivars that have close characteristics to wheat in terms of viscoelasticity and bread quality. We also studied quality of starch modified with two techniques and compared them to those of native starch. We are currently assessing the quality of extracted protein fractions from different proso millet cultivars. We are also evaluating the properties of high fiber snack made with proso millet. Future work build on our knowledge of the qualities of proso millet carbohydrates and protein qualities. We identify processes for optimizing malting process for millet and other grains using unique lighting regimes.

Appropriate technologies to enhance postharvest processing of grains: Significant portion of the limited grains grown in developing countries are often contaminated with Aflatoxin produced by certain fungi that thrive under high humidity environment. This stems from the fact that drying processes are still most done in inefficient ways – sun drying or solar drying. We designed and

fabricated a system that allows harnessing of wind energy for mechanical forced air generation to allow for convective heat and mass transfer during drying. The preliminary results indicate an efficiency of about 10% and improved drying time. Future work will be directed towards improving the system for better efficiency and field study.



1. Singh, M., Adedeji, A.A., and Santra, D. (2018). Physico-chemical and functional properties of nine proso millet cultivars. Transaction of ASABE 61(3), 1165-1174.

2. Singh, M., and Adedeji, A.A. (2017). Characterization of hydrothermal and acid modified proso millet starch. LWT – Food Science and Technology 79, 21 – 26.

3. Adedeji, A. A., Joseph, M.V., Plattner, B and Alavi, S. (2017). Physicochemical and functional properties of extruded sorghum based bean analog. Journal of Food Process Engineering 40(2).

4. Adedeji, A. A., Zhou, Y, Fang, Y., Davis, A., Fahrenholz, A. and Alavi, S. (2017). Utilization of sorghum ingredients and its co-product in aquatic animal feed production. Aquaculture Research 48(3), 883–898. http://doi.or/10.1111/are.12932.1–16

2. Food Processing Waste Valorization

Kentucky (KY) produces 95% of the world bourbon (corn whisky), which fetches the state hundreds of millions of dollars in revenue yearly. Along with the process of bourbon production is a major byproduct, spent grain (SG) that constitutes significant disposal problem. Distilling companies have negative to zero return on SG presently because they either pay to send them to landfill or pay to have livestock Farmers come collect the by-product. SG from bourbon is very rich in protein, fiber, fat, phenolic compounds and other soluble nutrients that can be processed for human food applications. Our current effort is identifying processes for the inclusion of SG from distilling and brewing as a source of high fiber in extruded products for human use. We were able to achieve inclusion level that exceeded the dietary recommendation by FDA for daily intake of fiber per serving by about 10 percent. The impact this would have is directly on the bourbon industry that produces SG, which would see potential increased return on their SG instead of expense. Future work will focus on devising means to increase the utilization of SG in extruded snack that rival quality of non-SG extrudate and further increased the health benefit of high-

extruded products so derived; also we intend to develop approach to extract the rich protein constituent of the SG and use it for the production of nanoparticle for different food applications.


3. Extrusion of nutrient dense foods

Through a collaborative effort, a USDA-NIFA equipment grants was awarded to us in 2016 for the procurement of a Lab scale extruder with a capacity of 10 kg/h and 40 L/D ratio. This has accelerated our research effort on food processing waste and grain valorization. Since the equipment was installed in October 2016, we have completed six projects. There are several other projects currently going on with use of the extruder by my graduate students. I continue to explore applications of extrusion in food and feed development, and hands-on training of my students. The impact of this acquisition is extensive research on food, feed and fiber that would lead to many high quality extruded products that will add significant value to the economy of KY and US. We have presented five conference paper and four peer reviewed paper is under review for publication. Future work will explore other applications of extrusion in value-added food and feed.





Accomplishments – see above publications under “grain value-addition”.

4. Noninvasive Methods in Agricultural Product Safety and Food Quality Assessment

Our current effort in this regard is divided into two main technology applications. We are currently applying two noninvasive technologies, namely hyperspectral imaging (HSI) and acoustic emission (AE) methods to characterize food qualities and assess them for safety.

Codling moth (CM) infestation detection using HSI and AE: CM is a very devastating pest problem in the apple industry in the US. Infestation often occur in the field when eggs are laid by adult moth on apple fruits, which are very difficult to detect during handling. These eggs later turn to larvae, which burrow their way into the fruit, often during the supply chain, causing significant damage. Early detection of CM infested apple will save farmers and processors significant resources, hence the need to develop noninvasive methods to detect the eggs, neonate or the larvae infested apple before they get far into the supply chain. Approach: Through collection of acoustic data emitted by healthy and infested apples with a piezoelectric transducer and application of multivariate analysis and machine learning approach, we are able to delineate between infested apples and healthy apple signals, at short sampling time (0.5 s). So far, we succeeded in obtaining 100% and 87% classification rate for training and test data set. Based on proof of concept, a disclosure of invention was filed with UK Office of Technology Transfer. We also applied another noninvasive method, hyperspectral imaging (HSI) to detect and classify infested apples, and the classification results we got is above the scientific bench mark of 83 percent.

Future work: We just received a USDA-NIFA grant that will allow us to further explore new data analytic approach, determine the source of acoustic signals and improve on the accuracy of detection and classification. In future work, we will focus on increasing accuracy by adopting new machine learning techniques and combining two sensing methods in a sensor fusion approach to harness the strength of each for a better detection. We also seek to develop the fundamental understanding of the sound signal emission source that allows for differentiation between infested and whole apple.

Noninvasive Adulteration Detection in Premium Processed Meat: The meat industry in the US, especially the beef industry is a multi-billion dollar industry that sustains the economy of many states and communities. The problem of intentional adulteration for economic gain is becoming rampant, especially with the “horsegate” scandal in the EU in 2013. These scandals exposed inefficiencies in the safety assurance systems among which is the detection approach. Our group is focused on developing multispectral systems, based on hyperspectral imaging and NIR spectroscopy for detecting possible adulterants in processed meat (beef and pork). Impact: Our research has provided a strong knowledge base for artificial intelligence technology development

that can prevent billions of dollars in loses that can ensue when food adulteration scandals break. We have so far published one peer reviewed paper, submitted another for publication and two other papers are being prepared for publication in high impact factor journals. We have also presented the preliminary result from our work at international conferences. Our goal in the future is to increase the robustness of the model for more accurate predictive capacity by trying other powerful algorithm, and data analysis approach.



1. Rady, A., Sugiharto, S., and Adedeji, A.A. (2018). Evaluation of carrot quality using visible-near infrared spectroscopy and multivariate analysis. Journal of Food Research 7(4), 80-93.

2. Li, M, Ekramirad, N., Rady, A., and Adedeji, A.A. (2018). Application of acoustic emission and machine learning to detect codling moth infested apples. Transaction of ASABE, 61(3), 1157-1164. 3.

4. Rady, A., and Adedeji, A.A. (2018). Assessing different processed meat adulterants using visible/near-infrared spectroscopy. Meat Science 136, 59 - 67.

5. Ekramirad, N., Rady, A., Adedeji, A.A., and Alimardani, R. (2017). Application of hyperspectral imaging and acoustic emission techniques for apple quality prediction. Transactions of ASABE 60(4), 1391-1401.

6. Rady, A., Ekramirad, N., Adedeji, A.A., Li, M., and Alimardani, R. (2017). Hyperspectral Imaging for detection of codling moth infestation in GoldRush apples. Postharvest Biology and Technology 129, 37 - 44.

7. Ekramirad, N., Adedeji, A.A. and Alimardani, R. (2016). A review of non-destructive methods for detection of insect infestation in fruits and vegetables. Innovation in Food Research 2(1)