光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2014年
11期
2984-2988
,共5页
贾仕强%郭婷婷%刘哲%严衍禄%安冬%顾建成%李绍明%张晓东%朱德海
賈仕彊%郭婷婷%劉哲%嚴衍祿%安鼕%顧建成%李紹明%張曉東%硃德海
가사강%곽정정%류철%엄연록%안동%고건성%리소명%장효동%주덕해
玉米种子%种衣剂%品种真实性%近红外光谱
玉米種子%種衣劑%品種真實性%近紅外光譜
옥미충자%충의제%품충진실성%근홍외광보
Maize%Seed-coating agents%Variety identification%Near-infrared spectroscopy
应用近红外光谱鉴定玉米种子品种真实性已有深入的研究。在实际应用中,商品玉米种子均涂有种衣剂,给光谱的采集和分析带来了许多困难。提出了基于近红外光谱的带种衣剂玉米种子品种真实性快速鉴定方法。首先讨论了种衣剂对种子近红外光谱的影响,然后将种子沿着胚面凹陷方向切开,使用漫反射方式和专用配件测量种子切面的光谱,以消除种衣剂的影响。使用支持向量机、软独立模式识别和仿生模式识别三种方法建立四个玉米品种的真实性鉴定模型,正确识别率分别达到93%,95.8%和98%。品种鉴定模型具有很好的稳健性,对来自不同产地的同一品种的种子均能够正确识别。
應用近紅外光譜鑒定玉米種子品種真實性已有深入的研究。在實際應用中,商品玉米種子均塗有種衣劑,給光譜的採集和分析帶來瞭許多睏難。提齣瞭基于近紅外光譜的帶種衣劑玉米種子品種真實性快速鑒定方法。首先討論瞭種衣劑對種子近紅外光譜的影響,然後將種子沿著胚麵凹陷方嚮切開,使用漫反射方式和專用配件測量種子切麵的光譜,以消除種衣劑的影響。使用支持嚮量機、軟獨立模式識彆和倣生模式識彆三種方法建立四箇玉米品種的真實性鑒定模型,正確識彆率分彆達到93%,95.8%和98%。品種鑒定模型具有很好的穩健性,對來自不同產地的同一品種的種子均能夠正確識彆。
응용근홍외광보감정옥미충자품충진실성이유심입적연구。재실제응용중,상품옥미충자균도유충의제,급광보적채집화분석대래료허다곤난。제출료기우근홍외광보적대충의제옥미충자품충진실성쾌속감정방법。수선토론료충의제대충자근홍외광보적영향,연후장충자연착배면요함방향절개,사용만반사방식화전용배건측량충자절면적광보,이소제충의제적영향。사용지지향량궤、연독립모식식별화방생모식식별삼충방법건립사개옥미품충적진실성감정모형,정학식별솔분별체도93%,95.8%화98%。품충감정모형구유흔호적은건성,대래자불동산지적동일품충적충자균능구정학식별。
It is generally accepted that near infrared reflectance spectroscopy (NIRS) can be used to identify variety authenticity of bare maize seeds .In practical ,maize seeds are covered with seed coating agents .Therefore it’s of huge significance to investi-gate the feasibility of identifying coated maize seeds by NIRS .This study employed NIRS to quickly determine the variety of coa-ted maize seeds .Influence of seed coating agent on NIR spectra was discussed .The NIR spectra of coated maize seeds were ob-tained using an innovative method to avoid the impact of the seed coating agent .Coated seeds were cut open ,and the sections were scanned by the spectrometer ,so as to acquire the information of the seed itself .Then ,support vector machine (SVM ) , soft independent modeling of class analogy (SIMCA) ,and biomimetic pattern recognition (BPR) was employed to establish the identification model for four maize varieties ,and yield 93% ,95.8% ,98% average correct rate respectively .BPR model showed better performance than SVM and SIMCA models .The robustness of identification model was tested by seeds harvested from four regions and model showed good performance .