Near infrared spectroscopy for the classification of vigor level of soybean seed

被引:1
|
作者
da Silva, Martha Freire [1 ]
Roque, Jussara Valente [2 ]
Soares, Julia Martins [3 ]
Moura, Lorena de Oliveira [3 ]
de Medeiros, Andre Dantas [3 ]
da Silva, Felipe Lopes [3 ]
da Silva, Laercio Junio [3 ]
机构
[1] State Univ Maringa UEM, Dept Agr Sci, Umuarama, PR, Brazil
[2] Univ Fed Goias, Inst Chem, Goiania, GO, Brazil
[3] Fed Univ Vicosa UFV, Dept Agron, Vicosa, MG, Brazil
来源
关键词
NIR; Seed Storage; Seed deterioration; Physiological quality of seeds; Biochemical composition of seeds; PARTIAL LEAST-SQUARES; QUALITY; PROTEIN; GERMINATION; VIABILITY;
D O I
10.5935/1806-6690.20240005
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
This work aimed at investigating the viability of near infrared spectrometry (NIR), associated with chemometric methods, in order to identify differences at the levels of vigor of naturally and artificially aged soybean seeds. Seeds of six soybean genotypes were analyzed when freshly harvested, after natural aging in storage for eight months, and after artificial aging at the temperature of 41 degrees C for 96 hours. The seed moisture content, germination potential and vigor were evaluated. Also, there were measured the content of protein, oil and of the fatty acids: palmitic, stearic, oleic, linoleic and linolenic. The NIR spectra were obtained from the freeze-dried and grinded seeds. The natural and artificial aging of the seeds promote deterioration at distinct levels, reflecting in differences in seed vigor. The regions of the electromagnetic spectrum between wavelengths of 1000-1200 nm, 1350-1450 nm, 1800-1900 nm and 2300-2400 nm are important to distinguish the levels of quality of the soybean seeds. The contents of oil and protein have a relationship with the physiological quality of the seeds. Also, the most relevant wavelengths for the classification of seed vigor present a relationship with these compounds. NIR spectroscopy, in combination with chemometric methods, presents potential to be used in the classification of soybean seeds regarding their physiological quality.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Soybean seed vigor discrimination by using infrared spectroscopy and machine learning algorithms
    Larios, Gustavo
    Nicolodelli, Gustavo
    Ribeiro, Matheus
    Canassa, Thalita
    Reis, Andre R.
    Oliveira, Samuel L.
    Alves, Charline Z.
    Marangoni, Bruno S.
    Cena, Cicero
    [J]. ANALYTICAL METHODS, 2020, 12 (35) : 4303 - 4309
  • [2] Effect of γ-irradiation on rice seed vigor assessed by near-infrared spectroscopy
    Song, Le
    Wang, Qi
    Wang, Chunyang
    Lin, Yanqing
    Yu, Ding
    Xu, Zhuopin
    Huang, Qing
    Wu, Yuejin
    [J]. JOURNAL OF STORED PRODUCTS RESEARCH, 2015, 62 : 46 - 51
  • [3] Classification of Damaged Soybean Seeds Using Near-Infrared Spectroscopy
    Wang, D.
    Ram, M.S.
    Dowell, F.E.
    [J]. Transactions of the American Society of Agricultural Engineers, 2002, 45 (06): : 1943 - 1948
  • [4] Classification of damaged soybean seeds using near-infrared spectroscopy
    Wang, D
    Ram, MS
    Dowell, FE
    [J]. TRANSACTIONS OF THE ASAE, 2002, 45 (06): : 1943 - 1948
  • [5] Study on the Vigour Testing of Soybean Seed Based on Near Infrared Spectroscopy Technology
    Qi, Xingwei
    Li, Weikai
    Li, Wei
    Li, He
    [J]. INFORMATION TECHNOLOGY FOR MANUFACTURING SYSTEMS II, PTS 1-3, 2011, 58-60 : 458 - +
  • [6] Near-infrared spectroscopy used to predict soybean seed germination and vigour
    Al-Amery, Maythem
    Geneve, Robert L.
    Sanches, Mauricio F.
    Armstrong, Paul R.
    Maghirang, Elizabeth B.
    Lee, Chad
    Vieira, Roberval D.
    Hildebrand, David F.
    [J]. SEED SCIENCE RESEARCH, 2018, 28 (03) : 245 - 252
  • [7] Evaluation of seed traits in alfalfa and soybean with near-infrared reflectance spectroscopy
    Sekharan, S
    Kephart, KD
    Turnipseed, EB
    [J]. AMERICAN FORAGE AND GRASSLAND COUNCIL, VOL 9, PROCEEDINGS, 2000, 9 : 328 - 328
  • [8] Identification of Soybean Seed Coat Crack Based on Near Infrared Spectroscopy and Machine Learning
    Wang, Liusan
    Huang, Ziliang
    Wang, Rujing
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2021, 52 (06): : 361 - 368
  • [9] Classification of the physiological potential of soybean seed lots using infrared spectroscopy and chemometric methods
    Soares, Julia Martins
    Batista, Thiago Barbosa
    da Silva, Martha Freire
    Rodrigues, Natalia Soares
    Dias, Denise Cunha Fernandes dos Santos
    da Silva, Laercio Junio
    [J]. JOURNAL OF SEED SCIENCE, 2024, 46
  • [10] Classification of fungal-damaged soybean seeds using near-infrared spectroscopy
    Wang, D
    Dowell, FE
    Ram, MS
    Schapaugh, WT
    [J]. INTERNATIONAL JOURNAL OF FOOD PROPERTIES, 2004, 7 (01) : 75 - 82