Single Droplet Drying Technology for the Optimization of the Dairy Ingredients with Best Quality and Functionality

As a result of their extended shelf-life, dried dairy ingredients constitute a significant category produced for global markets. During the development of dairy ingredients, several drying trials are typically conducted to determine optimum drying conditions. The results of these trials can be critical in determining optimum dryer design. However, these trials can be expensive and time-consuming. An alternative that has recently been developed using a new technique called single droplet drying (SDD). The SDD technique involves a single droplet suspended on the tip of a glass filament, where changes in droplet diameter, mass, and temperature are measured during drying. SDD makes it possible to create a pictorial view of the drying process. Once the drying process is complete, particle morphology can be determined using microscopy, or the rehydration behavior can be visually studied. A predictive model generated using SDD can then be used to optimize the drying conditions and dryer design. The modeling will help reduce costly plant trials and accelerate the development of new ingredients with novel functionalities. Hence, the Single Droplet Dryer (SDD) was installed at SDSU to conduct the bench-top trials. The aim of the first study was to study the effect of different solids concentration on the drying kinetics of whey protein concentrate by using SDD. There was a significant (P\u3c 0.01) change in the diameter, mass, and temperature change profiles during the drying run between 10%, 20%, and 30% total solids level for the WPC80. These activation curves are independent of the initial droplet sizes and constant drying conditions but dependent on the initial total solids’ concentration, hence calculated separately for each level of total solids. The viscosity of the WPC80 solution significantly (P \u3c 0.01) increases with an increase in the total solids level. There is a correlation between the particles obtained from the semi-commercial spray dryer and the particle generated on the SDD. Scanning electron microscopy, in conjunction with SDD, completely avoids commercial spray drying run to observe a particle and study the morphology of newer materials. The second study was conducted to compare the differences in the drying kinetics of Micellar Casein Concentrate (MCC) vs. Modified (CO2 induced) MCC, due to the difference in the composition of both the materials. Due to the differences in the pH and mineral balance between MCC (pH ~ 6.7) and Modified MCC (pH ~ 5.7); and the presence of the higher amount of de-aggregated casein micelle in the modified MCC, there was a significant difference (P\u3c 0.01) observed in the drying properties like change in moisture removal pattern, mass change of the particle, and temperature change pattern during the drying run. Materials with higher viscosities, higher total protein, and higher total solids, and minor differences in composition can be compared and studied on SDD. The objective of the third study was to understand the dissolution behavior of the dried particle of the infant formula at two different temperatures, viz: 70°C and 110°C. The outlet temperatures of the dryer have a significant effect (P\u3c 0.01) on the rehydration properties of dried powder. We have observed a significant difference (P\u3c 0.01) in the diameter change/ moisture removal pattern, mass change, and temperature change between 70°C and 110°C, two different temperatures of drying at all the solids level viz., 15%, 40%, and 50%. The change in total solids for each temperature had a significant (P\u3c 0.01) effect on the properties of the dried particle. We observed better rehydration/ higher solubility (P\u3c 0.01) of the powder particle of Infant Milk formula dried at 70°C temperature compared to those dried at 110°C. The dissolution times for each total solid at 70°C are significantly (P\u3c 0.01) different than those at 110°C for corresponding total solid values. Hence, the functionality of dairy powders is affected by the outlet temperatures of the dryer

What's the difference?: Textual analysis of variations in technical document structure

The aim of this project is to analyze text variations in technical documents, provided by John Deere, to better understand how the documents are structured. Example of variations include synonymous titles and differences in content structure. The goals are to report the amount of deviations by the document texts from the mean, describe the anatomy of the documents, and identify commonalities between documents. This supports more structured standards to be drafted, allowing the data inside the documents to be more manageable. Python is the languages of choice for this project.Ope

What's the difference?: Textual analysis of variations in technical document structure

The aim of this project is to analyze text variations in technical documents, provided by John Deere, to better understand how the documents are structured. Example of variations include synonymous titles and differences in content structure. The goals are to report the amount of deviations by the document texts from the mean, describe the anatomy of the documents, and identify commonalities between documents. This supports more structured standards to be drafted, allowing the data inside the documents to be more manageable. Python is the languages of choice for this project.Ope