Measuring grain protein concentration with in-line near infrared reflectance spectroscopy

被引:40
|
作者
Long, D. S. [1 ]
Engel, R. E. [2 ]
Siemens, M. C. [1 ]
机构
[1] USDA ARS, Columbia Plateau Conservat Res Ctr, Pendleton, OR 97801 USA
[2] Montana State Univ, Bozeman, MT 59717 USA
关键词
D O I
10.2134/agronj2007.0052
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The advent of near infrared (NIR) on-combine sensors gives growers the opportunity to measure the grain protein concentration of wheat (Triticum aestivum L.) during harvest. A study consisting of three sequential experiments (laboratory bench, combine test stand, and field) was conducted to evaluate the performance of an in-line, NIR reflectance spectrometer, referred to as the ProSpectra Grain Analyzer, possessing a factory calibration model. In the laboratory bench experiment, the instrument was mounted to a circulating impeller apparatus designed to simulate a moving stream of grain. The ProSpectra performed well on a validation set of 231 grain samples of soft white winter wheat and explained a high level of protein variability (R-2 = 0.91, SEP = 3.1 g kg(-1)) with a slope near unity. In the second experiment, the sensor was installed on a combine test stand constructed from the cross and exit augers, and clean grain elevator of a combine, to create the grain flow conditions found on a combine. Predicted protein was highly correlated (R-2 = 0.93, SEP = 4.5 g kg(-1)) with reference protein of nine large (14-kg) wheat samples. During the third experiment, the instrument was placed on the exit auger of a Case IH 1470 combine for the harvest of a 17-ha winter wheat field. Prospectra protein predictions correlated well with reference protein measurements (R-2 = 0.94, SEP = 3.1 g kg(-1)). This study demonstrated the feasibility of using in-line NIR reflectance spectroscopy to rapidly (0.5 Hz measurement rate) and accurately (SEP < 5.0 g kg(-1)) measure wheat protein in a moving grain stream.
引用
收藏
页码:247 / 252
页数:6
相关论文
共 50 条
  • [1] Measuring Fatty Acid Concentration in Maize Grain by Near-Infrared Reflectance Spectroscopy
    Yang Xiao-hong
    Guo Yu-Qiu
    Fu Yang
    Hu Jie-yun
    Chai Yu-chao
    Zhang Yi-rong
    Li Jian-sheng
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29 (01) : 106 - 109
  • [2] Measuring fatty acid concentration in maize grain by near-infrared reflectance spectroscopy
    Yang, Xiao-Hong
    Guo, Yu-Qiu
    Fu, Yang
    Hu, Jie-Yun
    Chai, Yu-Chao
    Zhang, Yi-Rong
    Li, Jian-Sheng
    Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis, 2009, 29 (01): : 106 - 109
  • [3] Near infrared reflectance spectroscopy as a tool for the in-line determination of the moisture concentration in extruded semolina pasta
    De Temmerman, J.
    Saeys, W.
    Nicolai, B.
    Ramon, H.
    BIOSYSTEMS ENGINEERING, 2007, 97 (03) : 313 - 321
  • [4] Accuracy of in-line milk composition analysis with diffuse reflectance near-infrared spectroscopy
    Melfsen, A.
    Hartung, E.
    Haeussermann, A.
    JOURNAL OF DAIRY SCIENCE, 2012, 95 (11) : 6465 - 6476
  • [5] In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties
    Cortes, V.
    Cubero, S.
    Blasco, J.
    Aleixos, N.
    Talens, P.
    FOOD AND BIOPROCESS TECHNOLOGY, 2019, 12 (06) : 1021 - 1030
  • [6] In-line Application of Visible and Near-Infrared Diffuse Reflectance Spectroscopy to Identify Apple Varieties
    V. Cortés
    S. Cubero
    J. Blasco
    N. Aleixos
    P. Talens
    Food and Bioprocess Technology, 2019, 12 : 1021 - 1030
  • [7] In-stream measurement of canola (Brassica napus L.) seed oil concentration using in-line near infrared reflectance spectroscopy
    Long, Daniel S.
    McCallum, John D.
    Young, Francis L.
    Lenssen, Andrew W.
    JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2012, 20 (03) : 387 - 395
  • [8] Raman and near-infrared spectroscopy for in-line sensors
    Hattori, Yusuke
    ANALYTICAL SCIENCES, 2022, 38 (12) : 1455 - 1456
  • [9] Raman and near-infrared spectroscopy for in-line sensors
    Yusuke Hattori
    Analytical Sciences, 2022, 38 : 1455 - 1456
  • [10] In-line estimation of falling number using near-infrared diffuse reflectance spectroscopy on a combine harvester
    Risius, Hilke
    Hahn, Juergen
    Huth, Markus
    Toelle, Rainer
    Korte, Hubert
    PRECISION AGRICULTURE, 2015, 16 (03) : 261 - 274