Accumulation Pattern of Amygdalin and Prunasin and Its Correlation with Fruit and Kernel Agronomic Characteristics during Apricot (Prunus armeniaca L.) Kernel Development

Abstract

To reveal the accumulation pattern of cyanogenic glycosides (amygdalin and prunasin) in bitter apricot kernels to further understand the metabolic mechanisms underlying differential accumulation during kernel development and ripening and explore the association between cyanogenic glycoside accumulation and the physical, chemical and biochemical indexes of fruits and kernels during fruit and kernel development, dynamic changes in physical characteristics (weight, moisture content, linear dimensions, derived parameters) and chemical and biochemical parameters (oil, amygdalin and prunasin contents, β-glucosidase activity) of fruits and kernels from ten apricot (Prunus armeniaca L.) cultivars were systematically studied at 10 day intervals, from 20 days after flowering (DAF) until maturity. High variability in most of physical, chemical and biochemical parameters was found among the evaluated apricot cultivars and at different ripening stages. Kernel oil accumulation showed similar sigmoid patterns. Amygdalin and prunasin levels were undetectable in the sweet kernel cultivars throughout kernel development. During the early stages of apricot fruit development (before 50 DAF), the prunasin level in bitter kernels first increased, then decreased markedly; while the amygdalin level was present in quite small amounts and significantly lower than the prunasin level. From 50 to 70 DAF, prunasin further declined to zero; while amygdalin increased linearly and was significantly higher than the prunasin level, then decreased or increased slowly until full maturity. The cyanogenic glycoside accumulation pattern indicated a shift from a prunasin-dominated to an amygdalin-dominated state during bitter apricot kernel development and ripening. β-glucosidase catabolic enzyme activity was high during kernel development and ripening in all tested apricot cultivars, indicating that β-glucosidase was not important for amygdalin accumulation. Correlation analysis showed a positive correlation of kernel amygdalin content with fruit dimension parameters, kernel oil content and β-glucosidase activity, but no or a weak positive correlation with kernel dimension parameters. Principal component analysis (PCA) showed that the variance accumulation contribution rate of the first three principal components totaled 84.56%, and not only revealed differences in amygdalin and prunasin contents and β-glucosidase activity among cultivars, but also distinguished different developmental stages. The results can help us understand the metabolic mechanisms underlying differential cyanogenic glycoside accumulation in apricot kernels and provide a useful reference for breeding high- or low-amygdalin-content apricot cultivars and the agronomic management, intensive processing and exploitation of bitter apricot kernels.

Keywords: accumulation pattern; amygdalin; apricot (Prunus armeniaca L.) kernel; cyanogenic glycoside; fruit quality.

Figure 1

Changes in fresh weight during the development of fruits and kernels in ten apricot cultivars. “Days after flowering” means days after 50% of flowers on the tree were open. Values are means ± standard error (n = 3). FW, fresh weight; cultivars: CZH, “Chuanzhihong”; DG, “Daguo”; JD, “Jidan”; JG, “Jiguang”; QH, “Qiuhong”; SK−1, “Shankuyihao”; ST−1, “Shantianyihao”; WX−1, “Weixuanyihao”; YS, “Yangshao”; ZK, “Zhengkui”.

Figure 2

Changes in water and oil contents (%) during kernel development in ten apricot cultivars. Kernel water content of the kernels (%) was determined as a percentage of fresh kernel weight by weighing the kernels before and after drying to constant weight. Oil content was expressed as a percentage of dry kernel weight. Values are means ± standard error (n = 3). cultivars: CZH, “Chuanzhihong”; DG, “Daguo”; JD, “Jidan”; JG, “Jiguang”; QH, “Qiuhong”; SK−1, “Shankuyihao”; ST−1, “Shantianyihao”; WX−1, “Weixuanyihao”; YS, “Yangshao”; ZK, “Zhengkui”.

Figure 3

Changes in cyanogenic glycosides (mg/g DW) and β-glucosidase activity (nmol/min/g FW) during kernel development in ten apricot cultivars. Values are means ± standard error (n = 3). FW, fresh weight; DW, dry weight; cultivars: CZH, “Chuanzhihong”; DG, “Daguo”; JD, “Jidan”; JG, “Jiguang”; QH, “Qiuhong”; SK−1, “Shankuyihao”; ST−1, “Shantianyihao”; WX−1, “Weixuanyihao”; YS, “Yangshao”; ZK, “Zhengkui”.

Figure 4

Correlation among physical, chemical and biochemical indexes and cyanogenic glycoside accumulation in ten apricot cultivars during fruit and kernel development. Days after flowering, DAF; fresh fruit weight, FWt; fruit length, FL; fruit width, FW; fruit thickness, FT; fruit geometric mean diameter, FGMD; fruit surface area, FSA; fruit sphericity, FSPH; fruit shape index, FSI; fresh kernel weight, KWt; kernel length, KL; kernel width, KW; kernel thickness, KT; kernel geometric mean diameter, KGMD; kernel surface area, KSA; kernel sphericity, KSPH; kernel shape index, KSI.

Figure 5

Principal component analysis (PCA) score plot (A) and loading plot (B) of ten apricot cultivars at different developmental stages. Numbers (30~90) after the cultivars in score plot (A) represent the days after flowering (DAF). Different color solid spheres in score plot (A) represent different cultivars: CZH, “Chuanzhihong”; DG, “Daguo”; JD, “Jidan”; JG, “Jiguang”; QH, “Qiuhong”; SK-1, “Shankuyihao”; ST-1, “Shantianyihao”; WX-1, “Weixuanyihao”; YS, “Yangshao”; ZK, “Zhengkui”. Blue and red arrows represent the tested physical, chemical and biochemical indexes: days after flowering, DAF; fresh fruit weight, FWt; fruit length, FL; fruit width, FW; fruit thickness, FT; fruit geometric mean diameter, FGMD; fruit surface area, FSA; fruit sphericity, FSPH; fruit shape index, FSI; fresh kernel weight (KWt); kernel length (KL); kernel width (KW); kernel thickness, KT; kernel geometric mean diameter, KGMD; kernel surface area, KSA; kernel sphericity, KSPH; kernel shape index, KSI.

Figure 5

Principal component analysis (PCA) score plot (A) and loading plot (B) of ten apricot cultivars at different developmental stages. Numbers (30~90) after the cultivars in score plot (A) represent the days after flowering (DAF). Different color solid spheres in score plot (A) represent different cultivars: CZH, “Chuanzhihong”; DG, “Daguo”; JD, “Jidan”; JG, “Jiguang”; QH, “Qiuhong”; SK-1, “Shankuyihao”; ST-1, “Shantianyihao”; WX-1, “Weixuanyihao”; YS, “Yangshao”; ZK, “Zhengkui”. Blue and red arrows represent the tested physical, chemical and biochemical indexes: days after flowering, DAF; fresh fruit weight, FWt; fruit length, FL; fruit width, FW; fruit thickness, FT; fruit geometric mean diameter, FGMD; fruit surface area, FSA; fruit sphericity, FSPH; fruit shape index, FSI; fresh kernel weight (KWt); kernel length (KL); kernel width (KW); kernel thickness, KT; kernel geometric mean diameter, KGMD; kernel surface area, KSA; kernel sphericity, KSPH; kernel shape index, KSI.