Variation in Amygdalin Content in Kernels of Six Almond Species (Prunus spp. L.) Distributed in China

Abstract

Amygdalin, a naturally occurring compound, is one of the main active ingredients of the Chinese raw bitter almond. The variation in amygdalin composition of seed kernels among the six almond species was determined, and relationships with geoenvironmental factors were analyzed. The amygdalin content exhibited great diversity, ranging from 0.0004 to 9.73 g/100 g. The highest level of amygdalin was detected in Tangut almond, with 5.45-9.73 g/100 g. The other kernels showed a range from 3.14 to 6.80 g/100 g in wild almond and from 3.00 to 4.22 g/100 g in longstalk almond. Amygdalin in common almond was almost undetectable. Factor analysis showed that amygdalin content in Prunus spp. kernels increased with altitude and decreased with the degree of aspect. Many environmental factors were closely related to amygdalin content, including annual precipitation (Bio12), UV intensity, and topsoil base saturation (T_BS), which all had a significant effect on amygdalin content. The amygdalin content is closely related to rainfall indicators, especially annual precipitation (Bio12), with the highest factor analysis value (3.63). Water regulates amygdalin in diverse ways. Since amygdalin is water-soluble, water can reduce the inhibitory effect of amygdalin on germination and regulate the synthesis of amygdalin at the late stage of germination by activating the amygdalin synthesis genes CYP79D16 and CYP71AN24. This study expands the understanding of amygdalin in almond resources and provides the direction for the regulation of amygdalin.

Keywords: almond kernel; almond species; amygdalin; amygdalin diversity; amygdalin synthesis; environmental factor.

FIGURE 1

Geographic distribution of different sampled positions of Prunus spp. L.

FIGURE 2

Range of amygdalin contents in six almond species in China. Medium dashed lines show each mean value, and solid lines show each median.

FIGURE 3

Factor analysis scores of amygdalin content in five topographic datasets (longitude, latitude, altitude, slope, and aspect) of six almond species (A); amygdalin content in different longitudes, latitudes (B), and altitudes (C); scatter plot of amygdalin content in different aspects (D) and slopes (E).

FIGURE 4

Factor analysis scores of amygdalin content in 19 climate factor datasets (Bio1–Bio19) of six almond varieties (A). Correlation analysis between amygdalin content and precipitation from January to December (B). The correlation coefficients ranged from 1 (blue, positive) to -1 (red, negative).

FIGURE 5

Correlation coefficient between amygdalin content and 3 annual climate factor datasets (A_Srad, annual mean solar radiation; A_Vapr, annual mean water vapor pressure; A_Wind, annual mean wind speed). (A) Correlation coefficient between amygdalin content and six UV-B radiation datasets. (B) Correlation coefficient between 15 soil variables and amygdalin content. (C) The correlation coefficients ranged from 1 (blue, positive) to -1 (red, negative).

FIGURE 6

Changes in the water content (A), amygdalin content (B), and expression of key regulatory genes (C) in kernels of longstalk almond during the process of seed germination promoted by water treatment.