Soma Roy

Solubility of commercial milk protein concentrates and milk protein isolates

High-protein milk protein concentrate (MPC) and milk protein isolate (MPI) powders may have lower solubility than low-protein MPC powders, but information is limited on MPC solubility. Our objectives in this study were to (1) characterize the solubility of commercially available powder types with differing protein contents such as MPC40, MPC80, and MPI obtained from various manufacturers (sources), and (2) determine if such differences could be associated with differences in mineral, protein composition, and conformational changes of the powders. To examine possible predictors of solubility as measured by percent suspension stability (%SS), mineral analysis, Fourier transform infrared (FTIR) spectroscopy, and quantitative protein analysis by HPLC was performed. After accounting for overall differences between powder types, %SS was found to be strongly associated with the calcium, magnesium, phosphorus, and sodium content of the powders. The FTIR score plots were in agreement with %SS results. A principal component analysis of FTIR spectra clustered the highly soluble MPC40 separately from the rest of samples. Furthermore, 2 highly soluble MPI samples were clustered separately from the rest of the MPC80 and MPI samples. We found that the 900 to 1,200 cm⁻¹ region exhibited the highest discriminating power, with dominant bands at 1,173 and 968 cm⁻¹, associated with phosphate vibrations. The 2 highly soluble MPI powders were observed to have lower κ-casein and α-(S1)-casein contents and slightly higher whey protein contents than the other powders. The differences in the solubility of MPC and MPI were associated with a difference in mineral composition, which may be attributed to differences in processing conditions. Additional studies on the role of minerals composition on MPC80 solubility are warranted. Such a study would provide a greater understanding of factors associated with differences in solubility and can provide insight on methods to improve solubility of high-protein milk protein concentrates.

Combating Anti-Statistical Thinking Using Simulation-Based Methods Throughout the Undergraduate Curriculum

The use of simulation-based methods for introducing inferen-ce is growing in popularity for the Stat 101 course, due in part to increasing evidence of the methods ability to improve studen-ts’ statistical thinking. This impact comes from simulation-based methods (a) clearly presenting the overarching logic of inference, (b) strengthening ties between statistics and probability/mathematical concepts, (c) encouraging a focus on the entire research process, (d) facilitating student thinking about advanced statistical concepts, (e) allowing more time to explore, do, and talk about real research and messy data, and (f) acting as a firm-er foundation on which to build statistical intuition. Thus, we argue that simulation-based inference should be an entry point to an undergraduate statistics program for all students, and that simulation-based inference should be used throughout all under-graduate statistics courses. To achieve this goal and fully recognize the benefits of simulation-based inference on the undergraduate statistics program, we will need to break free of historical forces tying undergraduate statistics curricula to mathematics, consider radical and innovative new pedagogical approaches in our courses, fully implement assessment-driven content innovations, and embrace computation throughout the curriculum. [Received December 2014. Revised July 2015]

Physicochemical properties of skim milk powders prepared with the addition of mineral chelators.

The objective of this study was to determine the effect of mineral chelator addition during skim milk powder (SMP) manufacture on the solubility, turbidity, soluble protein, and heat stability (HS). Three chelators (sodium citrate dihydrate, sodium polyphosphate, and disodium EDTA) at 3 different concentrations (5, 15, and 25mM) were added to skim milk concentrate (30% total solids), and the pH was adjusted to 6.65 before spray drying to produce SMP. Spray-dried SMP samples were tested for solubility index (SI). Additionally, samples were reconstituted to contain 9% total solids, adjusted to pH 7.0, and tested for turbidity, protein content from supernatants of ultracentrifuged samples, and HS. Lower SI values were observed for samples treated with 5mM disodium EDTA and sodium polyphosphate than control samples or samples with 5mM sodium citrate dihydrate. Furthermore, lower SI values were observed with an increased level of chelating agents regardless of chelator type. A decreased turbidity value was found with increasing levels of mineral chelating salt treatment. Low turbidity with increasing levels of added chelators may be associated with the dissociation of caseins from micelles. Furthermore, higher protein content was observed in supernatants of ultracentrifuged samples treated with increased level of chelators as compared with the control sample. Higher HS was observed in samples treated with 5mM compared with samples treated with 25mM mineral chelator. The results suggest improved solubility and HS upon addition of mineral chelators to SMP during its manufacture.

Vigorous Physical Work and Obesity?-the Paradox of the Californian Farmworker Population.

A good understanding of underlying causes of obesity prevalence in the farmworker population is critical in finding effective strategies to fight obesity and related chronic diseases. There is growing evidence that the population of farmworkers fares poorly with regard to health status, but available data on obesity levels and related chronic diseases is scarce or missing. This study examined the prevalence of overweight and obesity among a sample of farmworker population in California. Results of the regression model indicate that along with demographic variables such as age and gender, several lifestyle and behavioral risk factors are associated with obesity of the farmworkers. Results from this study will inform the design of intervention efforts and policies to help improve the health status of the farmworker population at the community level and beyond.

Interview With Soma Roy

SR: Thanks, Allan! I am very honored and excited to have been chosen for the position of editor for JSE! And, also for having been chosen to do this interview! (You can tell how excited by the frequent use of exclamation marks!) The year I turned 18 was the year I started college. As you know, I was born and raised in India. In the Indian education system, students take what are called “board exams” at the end of the 12th year of school (called “12th standard”). After having taken said exams, and while waiting for my scores, I spent some time researching undergraduate programs and colleges. In India you are required to apply to a specific major, so I had to decide on one specific area of interest that I wanted to pursue. However, being only eighteen and having seen very little of the world, it was a difficult decision to arrive at, at the time. I knew I liked working with numbers, but I also liked writing—could I work with numbers and then write the story that the numbers told? Was that what statistics would help me do? Well, there was only one way to find out. Luckily for me, my college of choice, Lady Shri Ram College for Women, New Delhi, has an undergraduate program in statistics, and they were happy with my scores and my interview. So I traveled about 700 miles from home to go to college, and began my statistics journey.

Estimating Percentiles in Computer Experiments: A Comparison of Sequential-Adaptive Designs and Fixed Designs

Computer simulators are often used when it is impossible or infeasible to observe actual systems or processes. These simulators can be very complex, requiring many hours or days for a single simulation, and thus, the number of times we may run the code is small. Running such a simulator at a few chosen input settings comprises a computer experiment. Most of the work done in this area focuses on either estimating the unknown complex input-output relationship or optimizing the output. In this article, we consider the problem of percentile estimation in a computer experiments setting and propose the use of sequential-adaptive designs to estimate percentiles, as opposed to fixed designs. For estimating the value and location of the percentile, we present design criteria that can be used to adaptively select the design sites at which to run the simulator. A comparison of results from using sequential-adaptive designs and fixed designs is presented.