Near-infrared spectroscopy and accelerated ageing in evaluating the vigour of lentil seeds

被引:0
|
作者
Limao, Marcelo Augusto Rocha [1 ]
Dias, Denise Cunha Fernandes dos Santos [1 ]
Nascimento, Warley Marcos [2 ]
de Noronha, Bruno Gomes [1 ]
Soares, Julia Martins [1 ]
da Silva, Laercio Junio [1 ]
机构
[1] Fed Univ Vicosa UFV, Vicosa Campus, Vicosa, MG, Brazil
[2] Embrapa Hortal, Caixa Postal 280, Brasilia, DF, Brazil
来源
关键词
Lens culinaris Medik. Physiological quality; Deterioration; Artificial intelligence; FT-NIR; VIABILITY; AGREEMENT;
D O I
10.5935/1806-6690.20250034
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The cultivation and consumption of lentils has been gaining importance in recent years due to the high nutritional value of the grain. Research related to seed technology is therefore important in providing high-quality seeds for the market. The aim of this study was to adapt the accelerated ageing test and evaluate the potential of FT-NIR spectroscopy for classifying lentil seeds based on physiological potential. Seven batches of lentil seeds were subjected to tests to characterise their physiological potential. The accelerated ageing test included the traditional method (100% RH) with an alternative method using saturated saline solution (76% RH) at 41 degrees C for 24, 36, 48 and 72 hours. NIR spectra were also obtained, taking 200 spectral readings from each batch that were individually processed for 30 seconds. Following the spectral analysis, the seeds were submitted to tests of germination and accelerated ageing to validate the technique. The PLS-DA technique was employed, using 70% of the data for training and 30% for validation. Different pre-processing methods were used, including the standard normal variate (SNV), multiplicative scatter correction (MSC), and the 1st and 2nd Savitzky-Golay (SG) derivatives. It was concluded that the accelerated ageing test at 41 degrees C for 48 hours using the traditional method (100% RH) was the most efficient way of evaluating the physiological potential of the lentil seeds. The models derived from the FT-NIR spectral data were 99% accurate in predicting the class of physiological potential of the batches.
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页数:11
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