Changes in Amino Acid Profile in Roots of Glyphosate Resistant and Susceptible Soybean (Glycine max) Induced by Foliar Glyphosate Application.

Amino acid profiles are useful to analyze the responses to glyphosate in susceptible and resistant soybean lines. Comparisons of profiles for 10 amino acids (Asp, Asn, Glu, Gln, Ser, His, Gly, Thr, Tyr, Leu) by HPLC in soybean roots were performed in two near isogenic pairs (four varieties). Foliar application of glyphosate was made to soybean plants after 5 weeks of seeding. Roots of four varieties were collected at 0 and 72 h after glyphosate application (AGA) for amino acid analysis by HPLC. Univariate analysis showed a significant increase of several amino acids in susceptible as well as resistant soybean lines; however, amino acids from the major pathways of carbon (C) and nitrogen (N) metabolism, such as Asp, Asn, Glu and Gln, and Ser, increased significantly in susceptible varieties at 72 h AGA. Multivariate analysis using principal component analysis (2D PCA and 3D PCA) allowed different groups to be identified and discriminated based on the soybean genetic origin, showing the amino acid responses on susceptible and resistant varieties. Based on the results, it is possible to infer that the increase of Asn, Asp, Glu, Gln, and Ser in susceptible varieties would be related to the deregulation of C and N metabolism, as well as changes in the growth mechanisms regulated by Ser.

Classification of Argentinean Sauvignon blanc wines by UV spectroscopy and chemometric methods.

UNLABELLED: Argentina is an important worldwide wine producer. In this country, there are several recognizable provinces that produce Sauvignon blanc wines: Neuquén, Río Negro, Mendoza, and San Juan. The analysis of the provenance of these white wines is complex and requires the use of expensive and time-consuming techniques. For this reason, this work discusses the determination of the provenance of Argentinean Sauvignon blanc wines by the use of UV spectroscopy and chemometric methods, such as principal component analysis (PCA), cluster analysis (CA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA). The proposed method requires low-cost equipment and short-time analysis in comparison with other techniques. The results are in very good agreement with results based on the geographical origin of Sauvignon blanc wines. PRACTICAL APPLICATION: This manuscript describes a method to determine the geographical origin of Sauvignon wines from Argentina. The main advantage of this method is the use of nonexpensive techniques, such as UV-Vis spectroscopy.

Chemometric characterization of sunflower seeds.

The spectroscopic characterization of different varieties of sunflower seeds based on their oleic acid content is proposed. One hundred fifty samples of sunflower seeds from different places of Argentina were analyzed by near-infrared diffuse reflectance spectroscopy (NIRDRS). Seed samples were grounded and sieved without chemical treatment previous to the analysis. For the characterization, the used multivariate methods were: principal component analysis (PCA), cluster analysis (CA), linear discriminant analysis (LDA), and partial least square discriminant analysis (PLS-DA). By using PCA, CA, and LDA, and from the point of view of varieties of sunflower seeds, 2 groups were differentiated, based on the concentration of oleic acid: a low oleic group, which ranged from 15% to 25% w/w oleic acid; and the other one (mid-high oleic varieties) which ranged from 26% to 90% w/w oleic acid. However, by using the PLS-DA, 3 groups were correctly differentiated based on the concentration of oleic acid: low oleic (from 15% to 25% w/w oleic acid); mid oleic (26% to 76% w/w oleic acid); and high oleic (≥ than 77% w/w oleic acid), demonstrating the high classification ability of this method. This multivariate characterization of sunflower seed varieties did not require chromatographic analysis to generate the matrix of concentrations, and only direct measures of NIRDRS spectra were required. This characterization can be useful to quickly know the variety of sunflower seed in the grain market. Practical Applications: This manuscript describes a method to determine 3 varieties of sunflower seeds (high, mid, and low oleic) The advantage of this method is to avoid the use of techniques that require long-time analysis.