Effects of cyanogenesis on morphology and estimated leaf flavonoid content in 51 white clover accessions

Abstract

Context Plant secondary metabolites are of increasing interest for agriculture due to their diverse beneficial ecological functions. The forage crop white clover (Trifolim repens L.) has been intensively studied for its heritable polymorphism in the production of hydrogen cyanide (HCN), a toxic defense phytochemical. In fodder production, white clover accessions are selected for biomass production, whereby HCN production is an unwanted trait. Aim Although white clover is a legume crop species of global importance, little is known about the linkage between cyanogenesis and growth traits, in particular in combination with resistance-related phytochemicals, such as flavonoids. We aimed to identify differences in biomass production, estimated leaf flavonoid content, and trait correlations in cyanogenic (HCN-producing) and acyanogenic (not HCN-producing) individuals and accessions of white clover. Methods We analysed 51 white clover accessions from a German germplasm collection for variability in selected traits: cyanogenesis as equivalent electrode potential, estimated leaf flavonoid content, root and shoot production, leaf area, specific leaf area, and number of leaves produced. Key results Most accessions considered as cyanogenic were heterogeneous for HCN production. Chemical–morphological trait correlations differed between cyanogenic and acyanogenic plants. Acyanogenic individuals and accessions produced more and larger leaves compared to cyanogenic ones. Within cyanogenic accessions, the higher the HCN level of a plant, the fewer but larger leaves were produced. Conclusions Our results highlight the variation in HCN production within the selected accessions, which calls for a consistent approach for cyanogenesis-based categorisation. Implication This study demonstrates the potential of combining phytochemical traits with biomass production in white clover when selecting material in a breeding program.