Our entire risotto project with Lara was inspired by J. Kenji López-Alt’s blog on pressure cooker made risotto. The actual project idea came from Dr Matthew Foreman who sent me a copy of a paper on the gelatinisation of starch in rice. We decided to investigate the effect of toasting rice, cooking temperature, and time on the consistency of risotto. Lara has already reported on some aspects of the work in earlier posts and we are currently writing up the results for a scientific paper. So that we can celebrate a successful project we decided to cook a mushroom risotto also testing the conclusions of Lara’s work in practice.
100g of each type of rice was mixed with 200g of distilled water at room temperature. The slurries were vacuum packed using a Sammic Vacuum Sealer V410 and heated for 15h at 35ºC in a water bath. Together with the rice and water one magnetic stirring bar was placed inside each vacuum sealed bag to stir the samples during 3min at 1000rpm at room temperature. Then, the sealed bags were opened and sieved during 2min more. Each water-starch solution and sample of sieved rice was weighted separately. After that, the rice grains were washed with 50g of distilled water, stirred at 1000rpm during 2min and sieved.
100g of each type of rice was mixed with 200g of distilled water at room temperature. The slurries were vacuum packed using a Sammic Vacuum Sealer V410 and heated for 20 h at 35 ºC in a water bath. Together with the rice and water one magnetic stirring bar was placed inside each vacuum sealed bag to stir the samples during 3min at 1000rpm at room temperature. Then, the sealed bags were opened and sieved mixing manually during 2min more. Each water-starch solution and sieved rice was weighted separately. After that the rice grains were washed two times with 80g of distilled water and mixed manually during 2min.
We present a gelatinisation model for a rice grain in spherical coordinates at a given temperature that allow us to obtain reasonable cooking times that depend on the initial moisture content and the rice grain equivalent diameter.
The following link allows to read it:
Creaminess is the term used for the velvety coating sensation normally assessed in the tongue and palate. It is one of the most relevant textural properties of risotto. Understanding creaminess requieres a multidisciplinary effort: from physical and chemical techniques to sensory perception studies and human-food interaction knowledge. After a review of the literature, we can conclude that it is undoubtedly related to thickness and smoothness. Other factors such as flavour or surface properties may also contribute to the perceived creaminess. An attempt to quantify creaminess was proposed by Kokini and Cussler1:
Creaminess = (Thickness)a(Smoothness)b
where a = 0.54 ± 0.1, b = 0.84±0.1.
Amylose content (AC) in rice grains is a relevant parameter for predicting pasting properties of cooked rice as it is often used for a tenderness prediction. We will perform experiments to measure the AC in different types of rice grains commonly used in risottos, such as carnalori, arborio or vialone nano. For that purpose we will:
1. Isolate starch
A wide range of methods are available for isolation of starch from rice. They are grouped into three categories: alkali isolation, acid isolation and water isolation. The main objective of the alkali and acid methods is to separate proteins and lipids from starch.
The process of cooking risotto is sometimes confusing and several procedures have been proposed to be the key to cook the real risotto, which requires ‘al dente’ rice grains and the adequate creamy texture.
If we want to prepare the ultimate risotto recipe we will have to answer some questions: what type of rice should we use?, should we stir while cooking the rice? , what is the cooking time?
Starch plays a vital role in achieving the desired consistency. Starch is a polysaccharide mainly composed by amylose, fundamentally linear, and amylopectin, highly branched. It presents a semi-crystalline structure.
Two weeks ago I described the general trends we saw when analysing the force-displacement data from breaking Pringles that had been left unsealed for a varying number of days. I stated that the feature that showed most correlation with the age and hence the crispness was the amount of force peaks after the major force drop. We have since produced a graph showing this trend. The graph is displayed below, we used the standard error derived from the three sets of measurements at each age for the error bars.
To be absolutely sure that we found a trend we decided to redo the measurements under different conditions.
Last week we began measurements on McVitie’s Digestive biscuits and carrots. We steamed the samples for different periods of time in order to modify their moisture content. We chose these two foods because of their very different structures. We want to probe how the moisture dependencies of acoustic and mechanical parameters are influenced by structure.
We steamed biscuits for 30, 45 and 60 seconds and carrots for 1,2,3,4 and 5 minutes in a steam oven. The acoustic data was consistently limited for different steam-time samples in both foods and failed to give any useful information. However, the force-deformation curves were more successful for both foods and we were able to identify parameters in each that showed a dependency on steam time.