Detecting bitter almonds in your nougat processing

Thursday, 17 October, 2019

Detecting bitter almonds in your nougat processing

Small percentages of bitter almonds can cause issues for producers of food products such as nougat and ice-cream that include almonds. Now a research group at the Alicante University (UA) in Spain has developed a new technology that can quickly identify whether an almond is sweet or bitter using non-destructive digital image processing.

In terms of world almond production, California holds 80% of the market share, followed by Australia, with 8%, and Spain, with 5%. The presence of a small percentage of bitter almonds in batches of sweet almonds leads to toxicity and economic repercussions for producers of almonds and derived products, such as nougat, drinks and vegetable pâtés or flours.

A bitter almond detection procedure has been developed by professors Juan Mora, Luis Gras, Guillermo Grindlay and Marta Navas, all of them from the Department of Analytical Chemistry, Nutrition and Food Science at the UA. The technology allows a quick classification of almonds based exclusively on the processing of different parameters of digital images, which can then differentiate bitter almonds from sweets almonds.

The almond tree has a great genetic variability. Although sweet taste is dominant in almonds, there is still a large presence of bitter almonds in Spanish crops. According to Juan Mora, this presence in manufactured products (nougats, chocolates, etc) is a serious handicap for the producing companies, which have lacked a quick and simple tool so far. However, in addition to the unpleasant taste, the greatest risk lies in the toxicity of these fruits. The bitter taste of almonds is due to the presence of amygdalin, which, upon contact with the enzyme amylase in saliva, is transformed into benzaldehyde (which confers the bitter taste) and hydrocyanic acid or cyanide, a highly toxic compound.

The simple method developed by the UA researcher consists of placing the almonds on an illuminated surface. There, the almonds can be dosed by the device automatically or manually, individually or in batches, by means of a hopper or conveyor belt adapted to the line that supplies the almonds. Once the sample batch has been distributed evenly on the surface by means of conveyor belts or vibrating tables, it is illuminated with an ultraviolet light source. This means that the bitterest almonds can be detected quickly. A simultaneous processing of the digital images retrieved together with a computer application that includes a discrimination model makes the detection of almonds with higher concentration of amygdalin possible.

The director of the research group points out that this is a non-destructive analytical method based on fluorescence and artificial vision to identify bitter almonds. Thus, the basis of the method lies in the fluorescence emitted by the compounds naturally present in bitter almonds. These can be detected specifically only by illuminating the sample with appropriate wavelength light and subsequent processing of the image generated. The method allows researchers to automate the classification of sweet and bitter almonds quickly, simply, objectively and in real time using an inexpensive, eco-friendly and non-destructive procedure.

The method doesn’t require the use of chemical reagents and doesn’t generate any type of waste, and the researchers said the method can be used safely by any operator without prior specific training. Additionally, the system allows for automated and online industrial deployment.

The procedure and device has been patented under the name “Procedimiento para la detección de almendras amargas basado en el procesamiento de imágenes digitales y el dispositivo asociado” (Procedure for the detection of bitter almonds based on digital image processing and the associated device) with patent number P201930561.

Image credit: © Winter

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