Foliar Application of Selenium Associated with a Multi-Nutrient Fertilizer in Soybean: Yield, Grain Quality, and Critical Se Threshold

Selenium uptake and its content in soybean grains are affected by Se application methods. This study evaluated the impact of Se foliar application combined with a multi-nutrient fertilizer (MNF) on soybean, establishing a Se threshold to better understand the relationship between Se content in grains and yield of two genotypes (58I60 Lança and M5917). Two trials were conducted in a 4 × 2 factorial design: four Se rates (0, 10, 40, 80 g Se ha-1) and two methods of foliar Se application (Se combined or not with MNF). Foliar fertilizers were applied twice, at phenological stages of beginning of pod development and grain filling. Grain yield increased with the application of MNF, yet Se rates increased Se contents linearly up to 80 g Se ha-1, regardless of the use of MNF. Lança and M5917 genotypes had grain Se critical thresholds of 1.0 and 3.0 mg kg-1, respectively. The application of Se favored higher contents of K, P, and S in grains of genotype Lança and higher contents of Mn and Fe in grains of genotype M5917. Our findings highlight the importance of addressing different Se fertilization strategies as well as genotypic variations when assessing the effects of Se on soybean yield and grain quality.

Discrimination of Brazilian arabica green coffee samples by chlorogenic acid composition

Coffee is basically consumed for the pleasure given by its taste and aroma, that is, the quality and acceptance of the coffee beverage are directly related to its sensorial characteristics. Thus, nowadays coffee quality is basically evaluated by sensorial analysis. However, together with this kind of analysis, it should be important to have available more objective chemical methods to assess coffee quality. One possible approach could be based on the analysis of chlorogenic acids (CGA), since they are considered precursors of coffee flavour and pigments during roasting. In the present work, high performance liquid chromatography (HPLC) analysis of chlorogenic acids was applied to six different Brazilian arabica green coffee samples which were previously characterised by sensorial analysis. The results showed the potential to correlate the chemical data, evaluated by the Principal Components Analysis (PCA) statistical method, with sensorial analysis in order to discriminate the quality of the samples. It was observed that the 3,4-dicaffeoylquinic (3,4-diCQA) and 3,5-dicaffeoylquinic (3,5-diCQA) isomers are very important for grouping the coffees into good and bad samples.