文献类型： 外文期刊

第一作者： Zhang Xiao-yan

作者： Zhang Xiao-yan;Yang Bing-nan;Cao You-fu;Li Shao-ping;Zhao Qing-liang;Xing Li

作者机构：

关键词： Potato; Near infrared spectroscopy; SIMCA; Principal component analysis

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2018 年 38 卷 8 期

页码：

收录情况： SCI

摘要： China is one of the world's largest countries in potato production and consumption. In 2015, the Chinese government put forward a staple-potato development strategy aimed to change the Chinese traditional diet habit of vegetable-potato and promote potato's status in safeguarding food security. Potato ring rot is a common disease which has restricted the development of potato industry. With the ring rot potato as the seed, it would cause unhealthy plants; with the ring rot potato as the raw materials for processing, it would cause lower efficiency and worse product quality. Visual inspection, machinevisiontechnology and hyperspectral imaging are the traditional methodsto detect potato diseases. However, it is destructive testing when visual inspection and machinevisiontechnology are used to detect ring rot potatoes; and hyperspectral imaging is at a significant cost. There are some limitations of application on these traditional methods. Internal quality changes of potatoes is caused by ring rot diseases. Near infrared spectroscopy (NIRS) could be used to reflect the quality change of the whole potato. Therefore, NIRS can be used to distinguishring rot potatoes from healthy potatoes. It's feasible and practical to detect potato ring rot nondestructively with near infrared spectroscopy. Combined with NIRS and soft independent modeling of class analogy (SIMCA) , this experiment was aimed to identify ring rot potatoes from healthy potatoes. The results showed that, SIMCA mode based on principal component analysis (PCA) was effective to identify ring rot potatoes. In calibration set, the recognition rate and rejection rate of ring rot potatoes and healthy potatoes were both 100%. In validation set, the recognition rate and rejection rate of ring rot potatoes were 99. 00% and 100%. The recognition rate and rejection rate of healthy potatoes were 94. 12% and 100%. For external validation, the recognition rate of ring rot potatoes and healthy potatoes were 87. 50% and 80. 00% respectively without misjudge. The SIMCA model was accurate in prediction and suitable to practical application, but the precision would be improved in further research. The pathogenic site of ring rot potatoes was close to epidermis for about 0. 5 cm; and there was transmission and diffuse reflection when NIRS Penetrating potatoes. So that it is possible to collect the NIRS information of potato tuber flesh near to potato epidermis. Combined with pathogenic mechanism of potato ring rot disease and characteristics of near-infrared diffuse reflectance spectra, it is innovative and practical to use NIRS to distinguish ring rot potatoes from healthy potatoes.

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