Analyzing protein concentration from intact wheat caryopsis using hyperspectral reflectance

Chemical and Biological Technologies in Agriculture

Research

Zhou Zhang¹  Xingxing Qiao²  Yiming Su²  XiaoBin Yan²  Wenjie Han²  Xiaomei Zhang²  Xiaoxiang Hou²  Wude Yang²  Guangxin Li²  Chao Wang²  Meichen Feng²  Fahad Shafiq³  Ping Chen⁴  Huihua Kong⁴ 

[1] Biological Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA;College of Agriculture, Shanxi Agricultural University, Taigu, Jinzhong, Shanxi, China;Department of Botany, Government College University Lahore, Lahore, Pakistan;Shanxi Key Laboratory of Signal Capturing & Processing, North University of China, Taiyuan, Shanxi, China;

关键词: Grain protein;    Hyperspectral technology;    Multivariate models;    Spectral preprocessing;    Wheat;   

DOI  :  10.1186/s40538-023-00456-x

 received in 2023-05-03, accepted in 2023-08-10,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundWinter wheat grain samples from 185 sites across southern Shanxi region were processed and analyzed using a non-destructive approach. For this purpose, spectral data and protein content of grain and grain powder were obtained. After combining six types of preprocessed spectra and four types of multivariate statistical models, a relationship between hyperspectral datasets and grain protein is presented.ResultsIt was found that the hyperspectral reflectance of winter wheat grain and powder was positively correlated with the protein contents, which provide the possibility for hyperspectral quantitative assessment. The spectral characteristic bands of protein content in winter wheat extracted based on the SPA algorithm were proved to be around 350–430 nm; 851–1154 nm; 1300–1476 nm; and 1990–2050 nm. In powder samples, SG-BPNN had the best monitoring effect, with the accuracy of Rv2 = 0.814, RMSEv = 0.024 g/g, and RPDv = 2.318. While in case of grain samples, the SG-SVM model exhibited the best monitoring effect, with the accuracy of Rv2 = 0.789, RMSEv = 0.026 g/g, and RPDv = 2.177.ConclusionsBased on the experimental findings, we propose that a combination of spectral pretreatment and multivariate statistical modeling is helpful for the non-destructive and rapid estimation of protein content in winter wheat.Graphical Abstract

【 授权许可】

CC BY   
© Springer Nature Switzerland AG 2023

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