| 基于近红外光谱技术的小白菜农药残留鉴别分析 |
| 投稿时间：2020-07-15 修订日期：2020-07-24 点此下载全文 |
| 引用本文：李敏.基于近红外光谱技术的小白菜农药残留鉴别分析[J].红外,2020,41(10):44~47 |
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| 基金项目:四川省教育厅自然科学重点基金项目(18ZA0231) |
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| 中文摘要:针对市场上销售的蔬菜存在的农药残留问题，提出了一种高效无损的小白菜农药残留定性分类鉴别方法。将3组小白菜叶片和氯氟氰菊酯农药作为研究对象，并分别对其中的2组小白菜喷洒2种不同浓度（农药与水的配比分别为1∶500和1∶20）的农药，从而形成不含农药、含轻度农残和含重度农残的三类样本。然后分别采集三类样本的近红外光谱数据，并对其进行小波软阈值预处理，再利用主成分分析（Principal Component Analysis, PCA）对数据进行降维，最后采用Fisher判决和K近邻(K-Nearest Neighbor, KNN)分类方法进行鉴别。实验结果表明，此方法对无农药残留与含轻度农药残留两类样本的正确鉴别率为95%，且对含轻度农残与含重度农残两类样本的正确鉴别率为90%。因此，本文方法可用于对小白菜农残进行有效的定性分类鉴别，为蔬菜农残定性分类鉴别提供了一种新思路。 |
| 中文关键词:近红外光谱 农药残留鉴别 K-近邻分类 |
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| Identification and Analysis of Pesticide Residues in Chinese Cabbage Based on Near Infrared Spectroscopy Technology |
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| Abstract:Aiming at the problem of pesticide residues in vegetables sold in the market, an efficient and nondestructive method for the qualitative classification and identification of pesticide residues in Chinese cabbage is proposed. Three groups of Chinese cabbage leaves and cyhalothrin are used as the research objects. Two groups of Chinese cabbage are sprayed with two different concentrations of pesticides (the ratios of pesticide to water are 1∶500 and 1∶20 respectively), and three types of samples are formed, which contain no pesticides, mild pesticide residues and severe pesticide residues. Three kinds of samples are collected by near infrared spectroscopy, and the spectral data are preprocessed by wavelet soft threshold, then the dimension is reduced by principal component analysis. Fisher decision and K-nearest neighbor classification are performed as well. The experimental results show that the correct identification rate of the two kinds of samples without pesticide residues and with mild pesticide residues is 95%, and that of the samples with mild and severe pesticide residues is 90%, which proves that this method is effective for the qualitative classification and identification of pesticide residues in Chinese cabbage and provides a new way of thinking for the qualitative classification and identification of pesticide residues. |
| keywords:near infrared spectroscopy identification of pesticide residues K-nearest neighbor classification |
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