Luiza Mariano Leme

Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer

Rationale: The nematode Aphelenchoides besseyi is the causal agent of green stem and foliar retention, a soybean disease recently described in Brazil. This condition can reduce soybean yield by up to 100%. However, little is known about chemical interactions between the plant and pathogen. Therefore, this work aimed to investigate metabolites from healthy soybean roots and from soybean roots that were inoculated with A. besseyi . Methods: A. besseyi were multiplied in vitro with Fusarium sp. colonies in Petri dishes for 25 days, and were axenically inoculated into hydroponics healthy soybean plants. The metabolites were extracted from the roots of healthy and A. besseyi ‐infected plants 16 days post‐inoculation. These extracts were analyzed using an untargeted metabolomic method with an ultra‐high‐performance liquid chromatography/electrospray ionization /tandem mass spectrometry (UHPLC/ESI‐MS/MS) and molecular networking approach. Results: Roots from infected plants showed morphological alterations such as shrinkage, darkening, and arching. Similarly, they also showed an increased presence of flavonoids, compared with healthy roots. Compounds such as neobavaisoflavone, glycitin, genistin, and genistein were putatively identified and had greater intensity in inoculated roots. These compounds are linked to the defensive mechanisms in plants against nematodes. Moreover, coumaric acid, also exclusively putatively identified in inoculated roots, shows activity related to inhibition of root growth. Conclusions: Liquid chromatography, mass spectrometry, and molecular networking approaches proved to be a powerful tool for the metabolomic study of GSFR. This study showed metabolomics differences of protective substances in the roots, evidencing a quick response of the plant to the attack of A. besseyi .

Classical methods, as titration to evaluate acidity, bring disadvantage to waste generation and mainly time consumption. Therefore, is necessary to develop an alternative methodology for measuring total acidity of wine samples. The Ultraviolet and Visible spectrophotometric technique can be introduced in the industry to monitoring this parameter because it enables rapid and efficient analysis without waste generation. Thereby, in this study were developed multivariate calibration models using the Partial Least Squares (PLS) regression between the UV-Vis spectra of wines and total acidity values determined by the reference method. The figures of merit for the models were Root Mean Squared Error of Calibration (RMSEC), Root Mean Squared Error of Prediction (RMSEP) and correlation coefficient (R). To the white wines, the model obtained showed RMSEC and RMSEP of 5.87 meq L-1 and 6.58 meq L-1, respectively. To the red wines, the model presented RMSEC 0.71 meq L-1 and RMSEP 6.93 meq L-1. Both models presented correlation coefficient of 0.71. A paired t-test showed no significant difference between titration and spectrophotometric methods at a confidence level of 95%. Therefore, the advantages offered by the UV-Vis method are attractive to industrial requirements, suggesting that studies focused on optical methods and multivariate calibration can be interesting and deserve to be observed in further studies. DOI: 10.14685/rebrapa.v6i1.193