Metabolomics reveals the within-plant spatial effects of shading on tea plants

Abstract

It is well known that green tea made from fully developed leaves located at the base of young shoots is of lower quality than that made from the still developing leaves located on the top of the shoot. It has additionally been shown that plant shading can significantly improve green tea quality. Here, we aimed to get more insight into the effects of shading on the overall metabolome in different parts of the tea shoots. To do this, field-grown tea plants were shaded by coverage with either a straw layer or a black net, both blocking the daylight intensity for more than 90%. Both the first (i.e. still developing) leaf and the fourth (i.e. fully developed) leaf, as well as the stem of young shoots were harvested and subjected to complementary untargeted metabolomics approaches, using accurate mass LC-Orbitrap-Fourier transform mass spectrometry (FTMS) for profiling both semi-polar and lipid-soluble compounds and GC-TOF-MS for profiling polar compounds. In total, 1419 metabolites were detected. Shading resulted in a decreased ratio of polyphenols to amino acids (which improves the quality of green tea) and lower levels of galloylated catechins in the shoots. The positive effect of shading on the amino acid/catechin ratio was more pronounced in the fully developed (fourth) than in the developing (first) leaves. Furthermore, many metabolites, especially organic acids, carbohydrates and amino acids, showed differential or opposite responses to the shading treatments between the three shoot tissues investigated, suggesting a within-plant spatial regulation or transport/redistribution of carbon and nitrogen resources between the tissues of the growing young shoots. This work provides new insight into the spatial effects of shading on tea plants, which could further help to increase tea quality by improving cultivation measures for plant shading.

Keywords: flavonoid and amino acid metabolism; leaf position; shading; tea quality; untargeted metabolomics.