LIU Ya,GUO Junxian,Muhetaer?MIJITI,et al.Effect of Spectral Data Pretreatment on Visible/Near Infrared Spectroscopy Model of Soluble Solids Content of Apples[J].Northern Horticulture,2016,40(20):1-4.[doi:10.11937/bfyy.201620001]
光谱预处理对苹果可溶性固形物含量VIS/NIR预测模型的影响
- Title:
- Effect of Spectral Data Pretreatment on Visible/Near Infrared Spectroscopy Model of Soluble Solids Content of Apples
- Keywords:
- spectral pretreatment; apple maturity; soluble solids content; visible/near spectroscopy; partial least squares
- 文献标志码:
- A
- 摘要:
- 可溶性固形物含量是苹果内部品质的重要指标,以“红富士”苹果为试材,测定了从果实膨大定型期到采收期整个成熟阶段,不同生长天数苹果的可见近红外反射光谱;对光谱进行了预处理,包括导数处理、标准正态变换、多元散射校正等方法;利用偏最小二乘法(PLS)建立了苹果可溶性固形物含量的预测模型。结果表明:使用一阶导数和二阶导数处理后的光谱进行预测的准确度高于原始光谱,相关系数分别为0.915 9、0.934 4。
- Abstract:
- The soluble solids content is an important index for apple internal quality.‘Fuji’ apple was used as test material,visible near infrared reflectance spectra of different growth days of apple was measured,during the apple′s ripening stage from enlargement period to harvest period.The original spectrum had pretreated by derivation,standard normal variation transformation and multiplicative scatter correction.Partial least square method was applied to construct the model between soluble solids content and spectrums.The results indicated that the forecast accuracy of the first order derivation and the second order derivation spectrums was higher than that of the original spectrums,the results of the correlation coefficient were 0.915 9,0.934 4.
参考文献/References:
? [1]PEIRS A,LAMMERTYN J,OOMS K,et al.Prediction of the optimal date of different apple cultivars by means of VIS/NIR-spectroscopy[J].Postharvest Biology and Technology,2001,21(2):189-194. [2]FAN G Q,ZHA J W,DU R,et al.Determination of soluble solids and firmness of apples by VIS/NIR transmittance[J].J Food Eng,2009,93(4):416-420. [3]GEYER M,GUESALAGA A R,AGOSIN E.Non-Destructive evaluation 〖JP3〗of apple fruit maturity on the tree[J].Vegetable Crops Research Bulletin,2007,66(1):161-169. [4]赵杰文,张海东,刘木华.利用近红外漫反射光谱技术进行苹果糖度无损检测的研究[J].农业工程学报,2005,21(3):162-165. [5]王加华,汤智辉,韩东海.多年份苹果糖度近红外预测模型建立[J].食品安全质量检测学报,2014,5(3):742-747. [6]袁雷明,高海宁,吕松等.可见/近红外光谱半透射法测苹果中可溶性固形物含量[J].食品安全质量检测学报,2012,3(5):448-452. [7]董一威,籍保平,史波林,等.苹果中糖酸度的CCD近红外光谱分析[J].食品科学,2007,28(8):376-380. [8]王铭海,郭文川,谷静思,等.成熟期梨可溶性固形物含量的近红外漫反射光谱无损检测[J].西北农林科技大学学报(自然科学版),2013,41(12):114-119. [9]刘辉军.田间黄花梨糖度的可见/近红外光谱检测方法[J].光谱学与光谱分析,2015,35(11):3078-3081. [10]宫元娟,周铁,屈亚堃,等.寒富苹果品质无损检测光谱信息在线分析[J].沈阳农业大学学报,2014,45(6):708-713. [11]周扬,戴曙光,吕进,等.光谱预处理对近红外光谱快速检测黄酒酒精度的影响[J].光电工程,2011,38(4):54-58. [12]褚小立,陆婉珍.近红外分析中光谱预处理及波长选择方法进展与应用[J].化学进展,2004,16(4):528-542. [13]王伟明,董大明,郑文刚,等.梨果糖浓度近红外漫反射光谱检测的预处理方法研究[J].光谱学与光谱分析,2013,33(2):359-360. [14]保罗·戈培林.化学计量学使用指南[M].北京:科学技术出版社,2012. [15]李民赞.光谱分析技术及其应用[M].北京:科学技术出版社,2006. [16]吴静姝,李慧.光谱预处理在农产品近红外模型优化中的应用研究[J].农机化研究,2011,33(3):178-181. [17]周丽萍,胡耀华,陈达,等.苹果可溶性固形物含量的检测方法-基于可见近红外光谱技术[J].农机化研究,2009,31(4):104-106. [18]尼珍,胡昌勤.近红外光谱分析中光谱预处理方法的作用及其发展[J].药物分析杂志,2008,28(5):824-829. [19]唐启义,冯明光.DPS处理系统[M].北京:科学技术出版社,2007. [20]王学民.应用多元分析[M].2版.上海:上海财经大学出版社,2004.〖JP3〗 [21]刘秀英,常庆瑞.基于可见/近红外光谱的牡丹花青素含量预测[J].农业机械学报,2015,46(9):320-323. [22]牛晓颖,贡东军,王艳伟,等.基于近红外光谱和化学计量学的李果实成熟度鉴别方法研究[J].现代食品科技,2014,30(12):230-234. [23]肖冰,潘存德,王世伟,等.新温185号核桃叶片光谱特征及其对施肥的响应[J],新疆农业科学,2015,51(7):1205-1212.
备注/Memo
第一作者简介:刘亚(1989-),男,硕士研究生,研究方向为农产品品质无损快速检测。E-mail:zztyly@163.com.责任作者:郭俊先(1975-),男,博士,副教授,研究方向为农产品品质无损快速检测。E-mail:junxianguo@163.com.基金项目:国家自然科学基金资助项目(61367001)。