Near infrared spectroscopy (NIR) and chemometrics methods to identification of haploids in maize

Ribeiro, Mariana Rodrigues; Simeone, M. L. F.; Trindade, R. dos S.; Dias, Luíz Antônio dos Santos; Guimarães, L. J. M.; Tibola, Casiane Salete; Azevedo, Tácila Cristina de

doi:10.1016/j.microc.2023.108604

Cited by 2 publications

(1 citation statement)

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“…Another interesting tool that has been tested for rapid prediction of the physiological potential of seeds is nearinfrared spectroscopy (NIR), which has the advantages of being simple, non-destructive and non-subjective (Ribeiro et al, 2023). In general, this technique is based on the absorption of wavelengths of electromagnetic radiation with the range of 780-2,500 nm, enabling the formation of spectra that correlate with the functional groups of the molecules (C-H, N-H and O-H) present in the sample (Xia et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Near infrared spectroscopy and seedling image analysis to evaluate the physiological potential of Urochloa decumbens (Stapf) R.D. Webster seeds

Souza,

Limão,

Pinheiro

et al. 2023

J. Seed Sci.

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The demand for techniques that make it possible to assess the physiological potential of seeds quickly and assertively make near-infrared spectroscopy (FT-NIR) and seedling analysis using ILASTIK software promising tools. The aim of this study was to evaluate the physiological potential of Urochloa decumbens seeds using near-infrared spectroscopy (FT-NIR) and ILASTIK software. Seeds from 10 lots of U. decumbens were classified according to their physiological potential (germination and vigor) and then FT-NIR spectra were obtained from individual seed samples, the original spectra being pre-processed with different dispersion correction methods used for the construction of a classification model through partial least squares discriminant analysis (PSL-DA). For the ILASTIK evaluation, the seedlings were photographed at 7 and 14 days of germination and the trained classifier was applied to the images, generating data on the numbers of strong seedlings, weak seedlings and non-germinated seeds. With data from the FT-NIR technique pre-processed by the 2nd derivative of Savitzky-Golay, it was possible to obtain a classification model with high efficiency to discriminate the classes regarding the physiological potential of the seeds. ILASTIK was efficient to classify seeds according to their physiological potential after only 7 days of germination. FT-NIR and ILASTIK analyses are non-destructive and fast alternatives, with great potential for quality control of U. decumbens seed lots.

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Section: Introductionmentioning

confidence: 99%