Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition

有害生物分析 光谱学 红外光谱学 农学 材料科学 化学 生物 植物 物理 天文 有机化学
作者
Zahra Basati,Bahareh Jamshidi,Mansour Rasekh,Yousef Abbaspour‐Gilandeh
出处
期刊:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy [Elsevier BV]
卷期号:203: 308-314 被引量:55
标识
DOI:10.1016/j.saa.2018.05.123
摘要

The presence of sunn pest-damaged grains in wheat mass reduces the quality of flour and bread produced from it. Therefore, it is essential to assess the quality of the samples in collecting and storage centers of wheat and flour mills. In this research, the capability of visible/near-infrared (Vis/NIR) spectroscopy combined with pattern recognition methods was investigated for discrimination of wheat samples with different percentages of sunn pest-damaged. To this end, various samples belonging to five classes (healthy and 5%, 10%, 15% and 20% unhealthy) were analyzed using Vis/NIR spectroscopy (wavelength range of 350-1000 nm) based on both supervised and unsupervised pattern recognition methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) as the unsupervised techniques and soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) as supervised methods were used. The results showed that Vis/NIR spectra of healthy samples were correctly clustered using both PCA and HCA. Due to the high overlapping between the four unhealthy classes (5%, 10%, 15% and 20%), it was not possible to discriminate all the unhealthy samples in individual classes. However, when considering only the two main categories of healthy and unhealthy, an acceptable degree of separation between the classes can be obtained after classification with supervised pattern recognition methods of SIMCA and PLS-DA. SIMCA based on PCA modeling correctly classified samples in two classes of healthy and unhealthy with classification accuracy of 100%. Moreover, the power of the wavelengths of 839 nm, 918 nm and 995 nm were more than other wavelengths to discriminate two classes of healthy and unhealthy. It was also concluded that PLS-DA provides excellent classification results of healthy and unhealthy samples (R2 = 0.973 and RMSECV = 0.057). Therefore, Vis/NIR spectroscopy based on pattern recognition techniques can be useful for rapid distinguishing the healthy wheat samples from those damaged by sunn pest in the maintenance and processing centers.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
yue完成签到,获得积分10
3秒前
淼队完成签到,获得积分10
4秒前
4秒前
落叶解三秋完成签到,获得积分10
5秒前
Crystal完成签到 ,获得积分10
8秒前
小小酥完成签到,获得积分10
8秒前
等待蚂蚁完成签到 ,获得积分10
9秒前
zgt01发布了新的文献求助10
9秒前
心心完成签到 ,获得积分10
10秒前
123完成签到,获得积分10
11秒前
温超完成签到,获得积分10
11秒前
量子星尘发布了新的文献求助10
11秒前
12秒前
13秒前
Menta1y完成签到,获得积分10
13秒前
czzlancer完成签到,获得积分10
14秒前
汶溢完成签到,获得积分10
14秒前
xsss完成签到,获得积分10
15秒前
TAN完成签到,获得积分10
15秒前
通通通发布了新的文献求助10
16秒前
liudw完成签到,获得积分10
16秒前
丹丹子完成签到 ,获得积分10
17秒前
时光完成签到,获得积分10
17秒前
18秒前
充电宝应助vsvsgo采纳,获得10
20秒前
123完成签到 ,获得积分10
22秒前
Ammr完成签到 ,获得积分10
22秒前
无限的依波完成签到,获得积分10
22秒前
姽婳wy发布了新的文献求助10
23秒前
lemon完成签到,获得积分10
23秒前
传奇3应助duckspy采纳,获得30
24秒前
陈木木完成签到,获得积分10
25秒前
可可西里完成签到,获得积分10
26秒前
奋斗蜗牛完成签到,获得积分10
26秒前
CipherSage应助眼睛大的擎苍采纳,获得10
26秒前
打打应助小小酥采纳,获得10
27秒前
fox完成签到 ,获得积分10
27秒前
僦是卜够完成签到 ,获得积分10
28秒前
小马甲应助嘉梦采纳,获得10
31秒前
qiqi完成签到,获得积分10
32秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038235
求助须知:如何正确求助?哪些是违规求助? 3575992
关于积分的说明 11374009
捐赠科研通 3305760
什么是DOI,文献DOI怎么找? 1819276
邀请新用户注册赠送积分活动 892662
科研通“疑难数据库(出版商)”最低求助积分说明 815022