•  
  •  
 

Abstract

In order to forecast the content of fumonisin in corn using the infrared spectrum analysis technology, and reduce the differences caused by their yield region, the influence of experiment using 4 different origin of domestic corn were investigated. The method of using x-y co-occurrence distance could be divided into calibration sample and validation sets, using the classical and different regions based on the partial least squares, and then the prediction model of fumonisin maize hybrid origin, and USES the validation set samples to validate the prediction precision, respectively. In order to reduce the computational complexity of modeling and forecasting process, experiments using continuous projection algorithm (SPA) and competitive adaptive weighting algorithm (CARS) the characteristics of the infrared spectra of different origin corn wavelength filter, and 22 characteristics were filtered out. Then these 22 wavelengths were input as variables, and this greatly reduced the computational complexity of modeling and forecasting process, as well as improved the prediction accuracy, with the correlation coefficient at 0.954.

Publication Date

2-28-2017

First Page

56

Last Page

59

DOI

10.13652/j.issn.1003-5788.2017.02.012

References

[1] CAMPS Dachoupakan Sirisomboon, REDDY Putthang, PETTR Sirisomboon. Application of near infrared spectroscopy to detect aflatoxigenic fungal contamination in rice[J]. Food Control, 2013, 33(4): 207-214.
[2] SMITA T, MISHRA L. A rapid FT-NIR method for estimation of aflatoxin B1 in red chili powder[J]. Food Control, 2009, 20(11): 840-846.
[3] XIA Chu. Research progress in the technology for rapid detection of mycotoxins in grain and its products[J]. Science and Technology of Cereals, Oils and Foods, 2013, 21(3): 76-81.
[4] JAMES K. Deoxynivalenol: mechanisms of action, human exposure, and toxicological relevance[J]. Arch Toxicol, 2010, 84: 663-679.
[5] 袁景, 郭小玉, 杨天溪, 等. 基于光谱技术的食品中常见真菌霉素的快速检测研究进展[J]. 上海师范大学学报: 自然科学版, 2015, 44(5): 571-579.
[6] 刘秀英, 申健, 常庆瑞, 等. 基于可见/近红外光谱的牡丹叶片花青素含量预测[J]. 农业机械学报, 2015, 46(9): 319-327.
[7] SIMS D A, GAMON J A. Relationships between leaf pigmerit content and spectral reflectance across a wide range of species, leaf structures and development stages[J]. Remote Sensing of Envrionment, 2002, 81(2/3): 337-354.
[8] 邹小波, 陈正伟, 石吉勇, 等. 基于近红外高光谱图像的黄瓜叶片色素含量快速检测[J]. 农业机械学报, 2012, 43(5): 152-156.
[9] 刘秀英, 王力, 宋荣杰, 等. 黄绵土风干过程中土壤含水率的光谱预测[J]. 农业机械学报, 2015, 46(4): 266-272.
[10] 李栓民, 郭银巧, 王克如, 等. 小麦籽粒蛋白质光谱特征变量筛选方法研究[J]. 中国农业科学, 2015, 48(12): 2 317-2 326.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.