Relação entre Dados Hiperespectrais e a Composição de Aminoácidos em Genótipos de Soja

Abstract

The spectral reflectance of plants can be readily correlated with physiological and biochemical parameters. Thus, relating spectral data to amino acid (AA) content in different genetic materials provides an innovative and efficient approach to understanding and managing genetic diversity. The objective of this work was: (I) to separate genetic materials according to amino acid content and spectral reflectance and (II) to establish a relationship between amino acids and spectral bands calculated from hyperspectral data. In the 2023/2024 growing season, 32 soybean genotypes were used in randomized blocks with four replications. Spectral analysis was performed 60 days after emergence (DAE). The samples were taken to the laboratory where reflectance was measured using a spectroradiometer, which has the capacity to measure the spectrum in the range of 350 to 2500 nm. The wavelengths were grouped into averages of representative intervals, organized into 28 bands. Initially, the genotypes were subjected to cluster analysis using the k-means algorithm. In the present study, the k value that best discriminated the groups according to the characteristics was set at 4. A correlation was performed to ascertain the relationship between the variables within each group. The averages of the results were grouped using the Scott-Knott test. Soybean leaf reflectance was efficient in separating soybean genotypes according to leaf amino acid content. The spectral bands show relationships with amino acids. Bands B21 to B28 show the strongest positive correlations with glutamic acid, arginine, cystine, isoleucine, leucine, methionine, proline, threonine, and valine. Bands B12 to B17 are positively correlated with glutamic acid, histidine, methionine, proline, and threonine. Bands B23 and B26 show positive correlations with arginine, cystine, proline, tyrosine, and valine. Vitamins B12 to B17 are positively correlated with glutamic acid, histidine, methionine, proline, and threonine. Vitamins B23 and B26 show positive correlations with arginine, cystine, proline, tyrosine, and valine. Negatively correlated: Vitamins B2 to B10 are correlated with aspartic acid, alanine, arginine, methionine, proline, serine, tyrosine, and valine; Vitamins B15 to B18 are correlated with aspartic acid, alanine, cystine, methionine, proline, and serine; and Vitamin B27 is correlated with glycine, histidine, lysine, methionine, proline, tyrosine, and valine.

KEYWORDS: Remote sensing. High-precision phenotyping. Protein.