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.
引用
收藏
页数:11
相关论文
共 50 条
  • [21] NEAR-INFRARED SPECTROSCOPY
    KAWANO, S
    JOURNAL OF THE JAPANESE SOCIETY FOR FOOD SCIENCE AND TECHNOLOGY-NIPPON SHOKUHIN KAGAKU KOGAKU KAISHI, 1992, 39 (04): : 376 - 376
  • [22] NEAR-INFRARED SPECTROSCOPY
    GERMON, TJ
    YOUNG, AER
    NELSON, RJ
    JOURNAL OF NEUROSURGERY, 1995, 83 (06) : 1111 - 1111
  • [23] Classification of Fir Seeds Based on Feature Selection and Near-infrared Spectroscopy
    Lu, Jing
    Zhang, Yan
    Xie, Shanshan
    Liu, Jiang
    Lv, Danjv
    Huang, Biaosheng
    Yin, Yue
    2022 IEEE 5th International Conference on Artificial Intelligence and Big Data, ICAIBD 2022, 2022, : 274 - 280
  • [24] Near-Infrared Spectroscopy of the Bladder: New Parameters for Evaluating Voiding Dysfunction
    Macnab, Andrew
    Shadgan, Babak
    Afshar, Kourosh
    Stothers, Lynn
    INTERNATIONAL JOURNAL OF SPECTROSCOPY, 2011,
  • [25] Prediction of fatty acid composition of sunflower seeds by near-infrared reflectance spectroscopy
    Akkaya, Murat Reis
    JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE, 2018, 55 (06): : 2318 - 2325
  • [26] Classification of fungal-damaged soybean seeds using near-infrared spectroscopy
    Wang, D
    Dowell, FE
    Ram, MS
    Schapaugh, WT
    INTERNATIONAL JOURNAL OF FOOD PROPERTIES, 2004, 7 (01) : 75 - 82
  • [27] Use of Near-infrared Reflectance Spectroscopy for the Estimation of the Isoflavone Contents of Soybean Seeds
    Sato, Tetsuo
    Eguchi, Kentaro
    Hatano, Tetsuya
    Nishiba, Yoichi
    PLANT PRODUCTION SCIENCE, 2008, 11 (04) : 481 - 486
  • [28] Nondestructive classification of mung bean seeds by single kernel near-infrared spectroscopy
    Phuangsombut, Kaewkarn
    Suttiwijitpukdee, Nattaporn
    Terdwongworakul, Anupun
    JOURNAL OF INNOVATIVE OPTICAL HEALTH SCIENCES, 2017, 10 (03)
  • [29] Prediction of fatty acid composition of sunflower seeds by near-infrared reflectance spectroscopy
    Murat Reis Akkaya
    Journal of Food Science and Technology, 2018, 55 : 2318 - 2325
  • [30] NEAR-INFRARED SPECTROSCOPY - REPLY
    GOPINATH, SP
    ROBERTSON, CS
    GROSSMAN, RG
    CHANCE, B
    JOURNAL OF NEUROSURGERY, 1994, 80 (01) : 182 - 182