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Nondestructive detection of lead content in oilseed rape leaves based on MRF‐HHO‐SVR and hyperspectral technology
Author(s) -
Cao Yan,
Sun Jun,
Yao Kunshan,
Xu Min,
Tang Ningqiu,
Zhou Xin
Publication year - 2021
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.13793
Subject(s) - hyperspectral imaging , mean squared error , environmental science , feature selection , pollution , environmental pollution , mathematics , computer science , artificial intelligence , statistics , biology , ecology , environmental protection
Lead (Pb) pollution poses a huge threat to environmental quality and food safety. Eating products made by excessive Pb contaminated oilseed rape can seriously harm human health. To detect Pb content in rape leaves more accurately, a method based on visible‐near infrared (400.68–1000.61 nm) hyperspectral technology was studied. First, the first derivative was used to pretreat the original spectral data. To reduce the number of iterations and the randomness of variable selection, the random frog (RF) algorithm was improved and named modified random frog (MRF). Then, the characteristic wavelengths were selected by MRF and competitive adaptive reweighted sampling (CARS), respectively, and support vector regression (SVR) model was established to predict the Pb content in rape. MRF was determined as the best feature selection algorithm. Finally, Harris Hawks Optimizer (HHO) was used to optimize SVR and the coefficient of determination ( R 2 ) and root mean square error (RMSE) of the prediction set were 0.9431 and 0.1645 mg/kg, respectively. Therefore, the combination of hyperspectral technology and the optimal model (MRF‐HHO‐SVR) is feasible for nondestructive detection of Pb content in rape leaves. Practical applications In recent years, the development of mineral resources has caused more and more serious pollution of heavy metals in the soil. The problem of lead pollution is particularly prominent, and various crops have been polluted to varying degrees. The physiological indicators and nutrient content of Pb contaminated oilseed rape have obvious changes. Excessive consumption of lead contaminated rape products can be hazardous to human health. A method for detecting lead content in rape leaves based on hyperspectral technology was studied in this article. The results show that the hyperspectral technology could be used for the accurate and nondestructive determination of lead content in rape leaves, which provides a new method and idea for the detection of lead content in crops.