Nutritional Evaluation of Quinoa Genetic Resources Growing in the Climatic Conditions of Central Europe.

Quinoa displays huge genetic variability and adaptability to distinct climatic conditions. Quinoa seeds are a good source of nutrients; however, the overall nutritional composition and nutrient content is influenced by numerous factors. This study focused on the nutritional and morphologic evaluation of various quinoa genotypes grown in the Czech Republic. Significant differences between years were observed for morphological traits (plant height, inflorescence length, weight of thousand seeds). The weather conditions in the year 2018 were favorable for all the morphological traits. The protein content of quinoa accessions ranged between 13.44 and 20.01% and it was positively correlated to mauritianin. Total phenolic content varied greatly from year to year, while the antioxidant activity remained relatively stable. The most abundant phenolic compounds were the flavonoids miquelianin, rutin, and isoquercetin. Isoquercetin, quercetin, and N-feruoloyl octopamine showed the highest stability under variable weather conditions in the analyzed years. A total of six compounds were detected and quantified in quinoa for the first time. Most varieties performed well under Central European conditions and can be considered a good source of nutrients and bioactive compounds. These data can be used as a source of information for plant breeders aiming to improve the quality traits of quinoa.

Genetic and chemical diversity among yacon [Smallanthus sonchifolius (Poepp. et Endl.) H. Robinson] accessions based on iPBS markers and metabolomic fingerprinting.

The present study is focused on the characterization of yacon [Smallanthus sonchifolius (Poepp. et Endl.) H. Robinson] accessions from different geographic origins (Bolivia, Ecuador, and Peru) by iPBS markers and metabolomic fingerprinting. The results showed that the number of amplified polymorphic fragment levels ranged from 20 up to 27 with a level of polymorphism ranging from 80 to 100%. Five of the iPBS primers used in this study provided no specific banding pattern able to discriminate between the different yacon accessions. However, two iPBS primer pairs were able to separate Peru accessions from those of Ecuador and Bolivia. The UPLC-HRMS/MS-based metabolomic fingerprinting showed highly similar metabolomic fingerprints characterized by the accumulation of high quantities of sesquiterpene lactones and diterpenes, but no apparent geographic clustering. The present study demonstrates that yacon accessions from different geographical origins maintained ex situ (in the Czech Republic) present a rather low chemical and genetic diversity.

Dealing with AFLP genotyping errors to reveal genetic structure in Plukenetia volubilis (Euphorbiaceae) in the Peruvian Amazon.

An analysis of the population structure and genetic diversity for any organism often depends on one or more molecular marker techniques. Nonetheless, these techniques are not absolutely reliable because of various sources of errors arising during the genotyping process. Thus, a complex analysis of genotyping error was carried out with the AFLP method in 169 samples of the oil seed plant Plukenetia volubilis L. from small isolated subpopulations in the Peruvian Amazon. Samples were collected in nine localities from the region of San Martin. Analysis was done in eight datasets with a genotyping error from 0 to 5%. Using eleven primer combinations, 102 to 275 markers were obtained according to the dataset. It was found that it is only possible to obtain the most reliable and robust results through a multiple-level filtering process. Genotyping error and software set up influence both the estimation of population structure and genetic diversity, where in our case population number (K) varied between 2-9 depending on the dataset and statistical method used. Surprisingly, discrepancies in K number were caused more by statistical approaches than by genotyping errors themselves. However, for estimation of genetic diversity, the degree of genotyping error was critical because descriptive parameters (He, FST, PLP 5%) varied substantially (by at least 25%). Due to low gene flow, P. volubilis mostly consists of small isolated subpopulations (ΦPT = 0.252-0.323) with some degree of admixture given by socio-economic connectivity among the sites; a direct link between the genetic and geographic distances was not confirmed. The study illustrates the successful application of AFLP to infer genetic structure in non-model plants.