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Near Infrared Spectroscopy (NIRS) Model-Based Prediction for Protein Content in Cowpea
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作者 Kavera Biradar Waltram Ravelombola +1 位作者 Aurora Manley Caroline Ruhl 《American Journal of Plant Sciences》 CAS 2024年第3期145-160,共16页
Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models... Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content. 展开更多
关键词 COWPEA GERMPLASM PROTEIN Near-Infrared spectroscopy (nirS) Partial Least Squares (PLS)
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“赤霞珠”葡萄叶片缺磷胁迫的VIS/NIR光谱快速无损诊断方法
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作者 白雪冰 宋昌泽 +4 位作者 张倩玮 代斌秀 靳国杰 刘文政 陶永胜 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2023年第12期3719-3725,共7页
研究旨在明确“赤霞珠(Cabernet Sauvignon, Vitis Vinifera L.)”葡萄健康叶片和缺磷胁迫不同时期下的光谱信号特征变化,构建基于光谱技术的“赤霞珠”葡萄叶片缺磷胁迫快速无损诊断模型,为葡萄园病害防治与管理提供理论参考和技术支... 研究旨在明确“赤霞珠(Cabernet Sauvignon, Vitis Vinifera L.)”葡萄健康叶片和缺磷胁迫不同时期下的光谱信号特征变化,构建基于光谱技术的“赤霞珠”葡萄叶片缺磷胁迫快速无损诊断模型,为葡萄园病害防治与管理提供理论参考和技术支持。以酿酒葡萄“赤霞珠”葡萄叶片为研究对象,分别采集了正常、缺磷胁迫初期和末期葡萄叶的VIS/NIR反射率信息。对比Savitzky-Golay卷积平滑(S-G Smoothing)、移动平均平滑(MAS)、标准正态变换(SNV)和多元散射校正(MSC)4种预处理及组合方法对于去除葡萄叶光谱信号中随机噪声的能力,确定最佳预处理方法。采用连续投影法(SPA)筛选与“赤霞珠”葡萄叶缺磷胁迫相关的光谱特征变量,分别构建基于线性核函数(Linear)、多项式核函数(Poly)、径向基核函数(RBF)和二层神经网络核函数(Sigmoid)的支持向量机(SVM)模型,以灵敏度(SEN)和准确率(CCR)为依据评估模型诊断性能,形成基于VIS/NIR光谱的“赤霞珠”葡萄叶片缺磷胁迫快速无损诊断方法。S-G Smoothing预处理后的光谱信号的信噪比为110.58,以其为校正集构建的缺磷胁迫诊断模型最佳,因此确定其为最佳的预处理方法。采用主成分分析(PCA)计算样本光谱贡献率,以95%置信空间为依据检测数据集中的异常样本,最终发现并剔除了22的离群点。通过SPA筛选出402.6、 404.6、 409、 411.5、 539.4、 691.9、 729.9、 838.7、 1 011.9、 1 017.5和1 020.5 nm等11个反映“赤霞珠”葡萄叶缺磷胁迫的光谱特征波段,作为缺磷胁迫快速无损诊断模型的输入变量。通过对比分析上述4种核函数SVM的诊断结果,以Linear为核函数构建的“赤霞珠”葡萄叶缺磷胁迫诊断模型能力最佳,对正常叶片诊断的SEN为81.08%, CCR为100%;对缺磷胁迫早期叶片诊断的SEN为100%, CCR为84.78%;对缺磷胁迫末期叶片诊断的SEN为100%, CCR为100%。该研究建立了基于VIS/NIR光谱的“赤霞珠”葡萄叶片缺磷胁迫快速无损诊断方法,能够满足葡萄园病害防治与智能化管理的生产需求,为酿酒葡萄智慧农业发展提供了技术参考。 展开更多
关键词 酿酒葡萄 缺磷胁迫 可见光/近红外光谱 无损诊断 支持向量机
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Study on the secondary structure and hydration effect of human serum albumin under acidic pH and ethanol perturbation with IR/NIR spectroscopy
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作者 Hui Zhang Mengying Liang +6 位作者 Shuangshuang Li Mengyin Tian Xiaoying Wei Bing Zhao Haowei Wang Qin Dong Hengchang Zang 《Journal of Innovative Optical Health Sciences》 SCIE EI CSCD 2023年第4期90-104,共15页
Human serum albumin(HSA)is the most abundant protein in plasma and plays an essential physiological role in the human body.Ethanol precipitation is the most widely used way to obtain HSA,and pH and ethanol are crucial... Human serum albumin(HSA)is the most abundant protein in plasma and plays an essential physiological role in the human body.Ethanol precipitation is the most widely used way to obtain HSA,and pH and ethanol are crucial factors affecting the process.In this study,infrared(IR)spectroscopy and near-infrared(NIR)spectroscopy in combination with chemometrics were used to investigate the changes in the secondary structure and hydration of HSA at acidic pH(5.6-3.2)and isoelectric pH when ethanol concentration was varied from 0%to 40%as a perturbation.IR spectroscopy combined with the two-dimensional correlation spectroscopy(2DCOS)analysis for acid pH system proved that the secondary structure of HSA changed significantly when pH was around 4.5.What's more,the IR spectroscopy and 2DCOS analysis showed different secondary structure forms under different ethanol concentrations at the isoelectric pH.For the hydration effect analysis,NIR spectroscopy combined with the McCabe-Fisher method and aquaphotomics showed that the free hydrogen-bonded water fluctuates dynamically,with ethanol at 0-20%enhancing the hydrogen-bonded water clusters,while weak hydrogen-bonded water clusters were formed when the ethanol concentration increased continuously from 20%to 30%.These measurements provide new insights into the structural changes and changes in the hydration behavior of HSA,revealing the dynamic process of protein purification,and providing a theoretical basis for the selection of HSA alcoholic precipitation process parameters,as well as for further studies of complex biological systems. 展开更多
关键词 Human serum albumin HYDRATION FORMATION secondary structure IR spectroscopy nir spectroscopy
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Analytical Study of Two Differently Ranked Coals Using UV-VIS-NIR Spectroscopy
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作者 B. Manoj A.G. Kunjomana 《Journal of Minerals and Materials Characterization and Engineering》 2011年第10期905-911,共7页
The characterization of Indian bituminous and subbituminous coal was performed by UVVisible– NIR spectroscopy. Chemical leaching with varying concentration of hydrofluoric acid was conducted on both the samples. Elec... The characterization of Indian bituminous and subbituminous coal was performed by UVVisible– NIR spectroscopy. Chemical leaching with varying concentration of hydrofluoric acid was conducted on both the samples. Electronic absorption at this region was higher for higher ranked coals. Chemical leaching increased electronic transitions in subbituminous coal with maximum transitions for HF (10%) leached samples. The absorption maximum of benzeneoxygen system was found between 235-270 nm and was showing a red shift with leaching. The characteristic naphthalene ring systems (220 & 280 nm) were masked by the absorption regions of monoaromatic rings;indicating the content of napthalenoid hydrocarbon was very low. The bands observed in the visible region (450nm) were attributed to SO2 in the sample and was showing a red shift. The weak band at the 680 nm was attributed to the Ⅱ-Ⅱ* electronic transitions of the polynuclear aromatic hydrocarbons which also showed red shift with leaching. It was found that the ash content is reduced by 87.5% & 76.2% in bituminous and subbituminous coal respectively with HF (30%) leaching. 展开更多
关键词 UV-vis-nir spectroscopy COAL characterization CHEMICAL LEACHING proximateanalysis.
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Vis-NIR光谱模式识别结合SG平滑用于转基因甘蔗育种筛查 被引量:17
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作者 刘桂松 郭昊淞 +2 位作者 潘涛 王继华 曹干 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2014年第10期2701-2706,共6页
以Savitzky-Golay(SG)平滑筛选,主成分分析(PCA)分别结合有监督的线性判别分析(LDA)、无监督的系统聚类分析(HCA),应用于转基因甘蔗育种筛查的可见-近红外(Vis-NIR)无损检测。提出兼顾随机性、稳定性的定标、预测、检验框架;取田间种植... 以Savitzky-Golay(SG)平滑筛选,主成分分析(PCA)分别结合有监督的线性判别分析(LDA)、无监督的系统聚类分析(HCA),应用于转基因甘蔗育种筛查的可见-近红外(Vis-NIR)无损检测。提出兼顾随机性、稳定性的定标、预测、检验框架;取田间种植处于伸长期甘蔗叶样品456个,具有Bt基因和Bar基因的转基因样品(阳)306个,非转基因样品(阴)150个;随机选取156个为检验集(阴性50、阳性106),余下为建模集(阴性100、阳性200,共300),建模集再随机划分为定标集(阴性50、阳性100,共150)、预测集(阴性50、阳性100,共150)共50次;扩充SG平滑点数,同时删除绝对值偏小的高阶导数模式,共264个平滑模式用于模型筛选;采用前3个主成分两两组合,再根据模型效果选出最优主成分组合;基于所有定标、预测集划分和SG平滑模式,建立SG-PCA-LDA和SG-PCA-HCA模型,根据平均预测效果优选参数,使模型具有稳定性;最后用检验集进行模型检验。经SG平滑后,PCA-LDA和PCA-HCA的建模精度、稳定性均显著改善;最优SG-PCA-LDA模型阳性、阴性样品检验识别率分别达到94.3%和96.0%;最优SG-PCA-HCA模型阳性、阴性样品检验识别率分别达到92.5%和98.0%。结果表明:Vis-NIR光谱模式识别结合SG平滑可用于转基因甘蔗叶的准确识别,提供了一种简便的转基因甘蔗育种筛查方法。 展开更多
关键词 转基因甘蔗育种筛查 vis-nir光谱 SG平滑 PCA-LDA PCA-HCA
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土壤全氮田间Vis/NIR光谱测定方法研究 被引量:2
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作者 汪善勤 舒宁 张海涛 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2008年第4期808-812,共5页
应用Vis/NIR光谱直接测定原始土壤属性具有重要的研究和应用价值。选取我国中部水稻土和潮土共103个土样,对比分析了两种土壤在田间环境下的湿态(Rw)和干态(Rd)光谱特征。采用相对变换光谱方法对湿态光谱进行了处理,结果表明该方法能够... 应用Vis/NIR光谱直接测定原始土壤属性具有重要的研究和应用价值。选取我国中部水稻土和潮土共103个土样,对比分析了两种土壤在田间环境下的湿态(Rw)和干态(Rd)光谱特征。采用相对变换光谱方法对湿态光谱进行了处理,结果表明该方法能够有效降低土壤水分的干扰和消除部分噪声,得到的变换光谱(Rn)与干态光谱在信息量和特征方面具有很高的相似度。以此建立了土壤TN的PLS回归估计模型,检验结果表明,Rn对水稻土和潮土TN的估计模型精度均高于Rw,修正判定系数分别从0.26和0.46提高到0.53和0.62。因此,相对光谱变换方法能够有效提高应用田间土壤光谱估计土壤参数的能力,建立的PLS模型可以用于测定TN含量,研究结果可作为实现田间实时分析土壤属性的工作基础。 展开更多
关键词 全氮 vis/nir光谱 相对变换方法
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冷却肉微生物污染和肉色变化的Vis/NIR光谱无损检测 被引量:8
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作者 张雷蕾 彭彦昆 +2 位作者 刘媛媛 赵娟 郭辉 《农业机械学报》 EI CAS CSCD 北大核心 2013年第S1期159-164,共6页
利用可见/近红外光谱技术对冷却肉菌落总数和颜色进行快速、无损检测。采用400~1 100 nm可见/近红外光谱成像系统,获取54个冷却肉样本表面的光谱图像,采用主成分分析结合马氏距离方法对异常光谱进行判别及剔除。通过Gompertz分布函数对... 利用可见/近红外光谱技术对冷却肉菌落总数和颜色进行快速、无损检测。采用400~1 100 nm可见/近红外光谱成像系统,获取54个冷却肉样本表面的光谱图像,采用主成分分析结合马氏距离方法对异常光谱进行判别及剔除。通过Gompertz分布函数对散射特征曲线进行拟合,得到表征光谱信息的Gompertz参数,结合支持向量机算法建立冷却肉菌落总数和肉色L*的预测模型。α、β、θ、δ组合和α、β、δ组合建模对细菌总数预测效果最好,预测相关系数分别为0.937和0.935,预测标准差为0.600 lg CFU/g和0.702 lg CFU/g。β、δ组合建模对肉色L*预测效果较好,预测相关系数达到0.930,预测标准差为1.515。研究结果表明利用Vis/NIR光谱散射特征结合支持向量机可以实现冷却肉品质的快速、高效、无损伤检测。 展开更多
关键词 冷却肉 菌落总数 可见/近红外光谱 支持向量机 无损检测
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土壤含水量对采用Vis-NIR光谱分析土壤质地的影响 被引量:4
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作者 王德彩 张俊辉 韩光中 《地理与地理信息科学》 CSCD 北大核心 2015年第6期52-55,共4页
Vis-NIR光谱应用于野外土壤质地分析时,其分析精度将受到土壤含水量的影响。该文旨在定量研究基于Vis-NIR光谱对土壤质地分析时,土壤含水量对精度的影响。在实验室条件下分别测定8种不同含水量状态下土壤样品(78个)的Vis-NIR光谱反射... Vis-NIR光谱应用于野外土壤质地分析时,其分析精度将受到土壤含水量的影响。该文旨在定量研究基于Vis-NIR光谱对土壤质地分析时,土壤含水量对精度的影响。在实验室条件下分别测定8种不同含水量状态下土壤样品(78个)的Vis-NIR光谱反射率,运用偏最小二乘回归(PLSR)分别建立不同含水量状态下土壤质地分析模型,每一模型分别分析8种不同含水量状态下验证集的土壤质地。结果表明,当土壤处于同一湿度状态时,各含水量状态下均可获得较好的结果,粘粒含量和砂粒含量最佳分析模型对应的含水量分别为150-200g/kg和200-250g/kg。当土壤含水量差异较大时,分析精度随着验证样本与建模样本水分含量的差异增大而急剧降低。研究认为,当土壤处于同一湿度状态时,可直接应用Vis-NIR光谱分析湿土的土壤质地,在土壤水分状态差异较大时,宜根据含水量建立分组分析模型。 展开更多
关键词 土壤质地 vis-nir光谱 土壤含水量 PLSR
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基于正交信号校正的Vis-NIR光谱土壤质地预测 被引量:6
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作者 王德彩 蔚霖 +3 位作者 张俊辉 杨红震 黄家荣 孙孝林 《河南农业大学学报》 CSCD 北大核心 2017年第3期408-413,共6页
为提高基于VIS-NIR光谱的土壤质地预测精度,引入了正交信号校正(OSC)光谱预处理算法。分别用原始光谱、微分处理、OSC处理光谱,建立偏最小二乘回归(PLSR)模型。结果表明,OSC-PLSR模型验证精度高于其他两种方法所建模型,砂粒含量OSC-PLS... 为提高基于VIS-NIR光谱的土壤质地预测精度,引入了正交信号校正(OSC)光谱预处理算法。分别用原始光谱、微分处理、OSC处理光谱,建立偏最小二乘回归(PLSR)模型。结果表明,OSC-PLSR模型验证精度高于其他两种方法所建模型,砂粒含量OSC-PLSR模型的RMSEp为5.94,粘粒含量OSC-PLSR模型RMSEp为1.25,相比PLSR模型,分别降低22.22%和9.42%。OSC算法在土壤质地的VIS-NIR反演中能有效消除不相关因素的影响,提高模型预测精度。 展开更多
关键词 vis-nir光谱 土壤质地 正交信号校正 偏最小二乘回归
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基于Vis-NIR光谱的柑橘叶片黄龙病检测及其光谱特性研究 被引量:13
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作者 马淏 吉海彦 Won Suk Lee 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2014年第10期2713-2718,共6页
黄龙病作为柑橘类水果最具毁灭性的疾病之一,目前尚无有效的治愈手段,因此疾病预防成为已知的唯一有效方法。基于四种柑橘叶片(健康叶片、黄龙病叶片、铁缺乏叶片及氮缺乏叶片)VIS-NIR的反射光谱详细讨论了黄龙病的辨别方法以及在判别... 黄龙病作为柑橘类水果最具毁灭性的疾病之一,目前尚无有效的治愈手段,因此疾病预防成为已知的唯一有效方法。基于四种柑橘叶片(健康叶片、黄龙病叶片、铁缺乏叶片及氮缺乏叶片)VIS-NIR的反射光谱详细讨论了黄龙病的辨别方法以及在判别模型中光谱特征值的提取方法。在两类判别分析的特征值提取方法中,判别值(discriminability)运算的引入,为特征值提取提供了一个可靠依据,判别值越大表明光谱差异性越大。以被选特征值建立的Fisher线性判别分析模型,黄龙病与健康、铁缺乏、氮缺乏叶片的分类判别预测准确率分别都超过了90%,分类效果符合预期。最后,又讨论了分类树(classificationTree)在多类判别中的应用。通过对柑橘叶片原始反射谱,一阶导数谱及被选特征值分别建立分类模型,四种柑橘叶片平均预测准确度都超过88%,尤其是基于特征值的分类结果更是超过94%,验证了在多类判别中检测柑橘黄龙病的可行性及特征值提取的重要性。结合传统分类方法(k-NN,Bayesian)的结果分析,特征值作为输入变量的分类结果明显要优于原始光谱,证实了特征值选取的正确性,并为将来基于光谱特征值开发多光谱成像技术检测黄龙病打下坚实的基础。 展开更多
关键词 黄龙病 判别值 FISHER线性判别 分类树 近红外光谱
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基于野外Vis-NIR光谱的土壤有机质预测与制图 被引量:20
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作者 郭燕 纪文君 +1 位作者 吴宏海 史舟 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2013年第4期1135-1140,共6页
利用野外实时快速获取的土壤光谱进行土壤有机质(SOM)预测与制图是精确农业与土壤遥感制图的必然需要,利用ASD FieldSpec Pro FR野外型光谱仪实时快速获取的光谱数据,去除噪声较大的边缘波段后,进行倒数的对数转换(Log(1/R))为吸收光谱... 利用野外实时快速获取的土壤光谱进行土壤有机质(SOM)预测与制图是精确农业与土壤遥感制图的必然需要,利用ASD FieldSpec Pro FR野外型光谱仪实时快速获取的光谱数据,去除噪声较大的边缘波段后,进行倒数的对数转换(Log(1/R))为吸收光谱。在分析吸收光谱和光谱指数与SOM关系的基础上,采用偏最小二乘回归法进行SOM的建模预测并借助地统计学方法进行SOM空间变异制图研究。结果表明,建模效果好的指标分别为特征波段(R2=0.91,RPD=3.28),归一化光谱指数(R2=0.90,RPD=3.08),特征波段与3个光谱指数组合(R2=0.87,RPD=2.67),全波段(R2=0.95,RPD=4.36)。光谱指标的克里格制图与实测SOM制图表现出相同的空间变异趋势,不同的指标均达到了较好的预测效果。 展开更多
关键词 vis-nir光谱 野外型光谱仪 土壤有机质 预测与制图 偏最小二乘回归法(PLSR) 地统计
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基于Vis-NIR光谱的土壤质地BP神经网络预测 被引量:7
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作者 王德彩 张俊辉 《天津农业科学》 CAS 2015年第8期6-9,共4页
为快速、准确地获取土壤质地信息,提出了应用Vis-NIR光谱结合BP神经网络的建模方法。以河南封丘县的86个土壤样本为研究对象,以原始光谱和微分光谱主成分为输入变量,建立土壤粘粒和砂粒的BP神经网络预测模型,并将其预测结果与多元线性... 为快速、准确地获取土壤质地信息,提出了应用Vis-NIR光谱结合BP神经网络的建模方法。以河南封丘县的86个土壤样本为研究对象,以原始光谱和微分光谱主成分为输入变量,建立土壤粘粒和砂粒的BP神经网络预测模型,并将其预测结果与多元线性逐步回归模型进行比较。结果表明:基于原始光谱主成分的BP人工神经网络预测结果最好,优于多元逐步回归模型,预测粘粒和砂粒的RMSE分别为1.62和6.52。BP神经网络所建模型训练时间短、准确度也较高,能实现对土壤质地的高效预测。 展开更多
关键词 vis-nir光谱 BP神经网络 主成分分析 土壤质地
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基于Vis-NIR光谱的不同水分状态下土壤有机质预测
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作者 王德彩 张俊辉 黄家荣 《河南农业大学学报》 CAS CSCD 北大核心 2015年第3期331-334,342,共5页
以河南省封丘县的86个土壤样本为研究对象,测定9种不同含水量状态下的土壤光谱反射率,运用偏最小二乘回归(PLSR)建立不同含水量状态下的土壤有机质预测模型;运用0-50 g·kg^-1,200-250 g·kg^-1,400-450 g·kg^-1水分状态... 以河南省封丘县的86个土壤样本为研究对象,测定9种不同含水量状态下的土壤光谱反射率,运用偏最小二乘回归(PLSR)建立不同含水量状态下的土壤有机质预测模型;运用0-50 g·kg^-1,200-250 g·kg^-1,400-450 g·kg^-1水分状态下3组模型进行交互预测,以研究含水量状态差异较大情况下,土壤含水量对有机质预测精度的影响。结果显示,建模样本与预测样本处于同一含水量状态下,土壤含水量对土壤有机质含量预测精度的影响不显著;当验证集样本与建模集样本间水分状态差异较大时,预测结果会出现较大误差。当土壤处于同一湿度状态时,可直接应用Vis-NIR光谱预测湿土的有机质;当土壤样本间水分差异较大时,可依据含水量状态建立分组模型,以提高Vis-NIR光谱预测有机质的精度。 展开更多
关键词 土壤有机质 vis-nir光谱 土壤含水量 PLSR
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MIV波长优选改善VIS/NIR光谱TVB-N模型性能研究 被引量:3
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作者 陈亦凡 李芸婧 +3 位作者 彭苗苗 杨春勇 侯金 陈少平 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2020年第5期1413-1419,共7页
挥发性盐基氮(TVB-N)是衡量肉品新鲜的重要理化指标,利用可见/近红外(VIS/NIR)光谱对TVB-N含量进行定量检测具有重要意义。预测模型是VIS/NIR光谱检测TVB-N含量性能的关键要素,使其兼顾准确性与稳健性可有效改善TVB-N的定量分析结果。... 挥发性盐基氮(TVB-N)是衡量肉品新鲜的重要理化指标,利用可见/近红外(VIS/NIR)光谱对TVB-N含量进行定量检测具有重要意义。预测模型是VIS/NIR光谱检测TVB-N含量性能的关键要素,使其兼顾准确性与稳健性可有效改善TVB-N的定量分析结果。以猪肉为例,采集51组不同新鲜度样本的VIS/NIR光谱数据,去除低信噪比区间200~450和900~1000 nm,选取有效波段450~900 nm的光谱数据用于建模。随后利用主成分分析(PCA)对光谱信息降维,构建一个反向传播神经网络(BPNN)模型。在此基础上,提出用平均影响值(MIV)方法从有效波段中优选与肉质TVB-N含量强相关的特征波长,最终基于221个优选波长,构建一个MIV-PCA-BPNN预测模型。实验表明,初步构建的PCA-BPNN非线性预测模型,校正相关系数(R_C)和校正均方根误差(RMSEC)分别为0.96和1.47 mg/100 g,预测相关系数(R_P)和预测均方根误差(RMSEP)分别为0.93和1.74 mg/100 g,模型稳健性指标为1.18,优于经典的线性预测模型主成分分析回归和偏最小二乘回归,证明TVB-N具有较强的非线性效应。最终构建的MIV-PCA-BPNN预测模型的R_C和RMSEC分别为0.98和1.21 mg/100 g,R_P和RMSEP分别为0.96和1.12 mg/100 g,模型稳健性指标为1.08,在所构建的预测模型中,RMSEC和RMSEP最小,RC和RP最大,模型的准确性和稳健性最佳。另外,MIV方法筛选出的特征波长集中在7个波峰附近,皆分布于肉品中化学成分的吸收区内,且与TVB-N中的含氢基团的特征吸收峰表现出高度一致性,为利用MIV方法筛选波长变量提供了理论依据。研究结果显示,MIV波长优选可有效改善预测模型的性能,为利用神经网络剔除无关波长变量提供了新思路,所构建的MIV-PCA-BPNN预测模型满足了肉质中TVB-N定量分析的需求。 展开更多
关键词 vis/nir光谱检测 反向传播神经网络 波长优选 挥发性盐基氮
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Nondestructive Quantitative Analysis of Cofrel Medicines by Double ANN-NIR Spectroscopy 被引量:4
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作者 Ming Yang LIU Yu MENG +2 位作者 Jun Feng LI Hai Tao ZHANG Hong Yan WANG 《Chinese Chemical Letters》 SCIE CAS CSCD 2006年第9期1209-1212,共4页
In this paper, a double artificial neural network (DANN) algorithm was used to parse near infrared (NIR) reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ing... In this paper, a double artificial neural network (DANN) algorithm was used to parse near infrared (NIR) reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ingredient in Cofrel medicines, were accurately nondestructive quantitatively predicted. Compared the results with those of HPLC, the relative errors (RE %) were less than 0.18%. The analytical results could be applied to qualitative control of Cofrel medicines. 展开更多
关键词 Double ANN nir spectroscopy nondestructive quantitative analysis Cofrel.
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Sensing of Moisture Content of In-Shell Peanuts by NIR Reflectance Spectroscopy 被引量:10
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作者 Jaya Sundaram Chari V. Kandala +1 位作者 Konda Naganathan Govindarajan Jeyam Subbiah 《Journal of Sensor Technology》 2012年第1期1-7,共7页
It was found earlier that moisture content (MC) of intact kernels of grain and nuts could be determined by Near Infra Red (NIR) reflectance spectrometry. However, if the MC values can be determined while the nuts are ... It was found earlier that moisture content (MC) of intact kernels of grain and nuts could be determined by Near Infra Red (NIR) reflectance spectrometry. However, if the MC values can be determined while the nuts are in their shells, it would save lot of labor and money spent in shelling and cleaning the nuts. Grain and nuts absorb low levels of NIR, and when NIR radiation is incident on them, a substantial portion of the radiation is reflected back. Thus, studying the NIR reflectance spectra emanating from in-shell peanuts, an attempt is made for the first time to determine the MC of in-shell peanuts. In-shell peanuts of two different market types, Virginia and Valencia, were conditioned to different moisture levels between 6% and 26% (wet basis), and separated into calibration and validation groups. NIR absorption spectral data from 1000 nm to 2500 nm in 1 nm intervals were collected from both groups. Measurements were obtained on 30 replicates within each moisture level. Reference MC values for each moisture level in these groups were obtained using standard air-oven method. Partial Least Square (PLS) analysis was performed on the calibration data, and prediction models were developed. The Standard Error of Calibration (SEC), and R2 of the calibration models were computed to select the best calibration model. The selected models were used to predict the moisture content of peanuts in the validation sets. Predicted MC values of the validation samples were compared with their standard air-oven moisture values. Goodness of fit was determined based on the lowest Standard Error of Prediction (SEP) and highest R2 value obtained for the prediction models. The model, with reflectance plus normalization spectral data with an SEP of 0.74 for Valencia and 1.57 for Virginia type in-shell peanuts was selected as the best model. The corresponding R2 values were 0.98 for both peanut types. This work establishes the possibility of sensing MC of intact in-shell peanuts by NIR reflectance method, and would be useful for the peanut and allied industries. 展开更多
关键词 In-Shell Peanuts nir spectroscopy PRETREATMENTS Partial Least Square Standard Error of Prediction Relative PERCENT Deviation
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NIRS-XRF联用的煤炭发热量高稳定检测 被引量:5
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作者 宋健超 张雷 +2 位作者 马维光 尹王保 贾锁堂 《光学精密工程》 EI CAS CSCD 北大核心 2023年第13期1880-1889,共10页
实时获知煤炭发热量对于及时调整电站锅炉风粉配比和提高煤炭燃烧效率具有重要意义,为了实现电力生产中发热量的稳定快速检测,提出了一种近红外光谱(Near Infrared Spectroscopy, NIRS)与X射线荧光光谱(X-ray Fluorescence, XRF)联用的... 实时获知煤炭发热量对于及时调整电站锅炉风粉配比和提高煤炭燃烧效率具有重要意义,为了实现电力生产中发热量的稳定快速检测,提出了一种近红外光谱(Near Infrared Spectroscopy, NIRS)与X射线荧光光谱(X-ray Fluorescence, XRF)联用的煤炭发热量高稳定检测方法,它结合了NIRS能高稳定检测煤中与发热量正相关的有机基团的优势与XRF能高稳定检测与发热量负相关的成灰元素的特点,大大提高了对煤炭发热量的测量重复性。在光谱预处理中,先将两套光谱融合作为偏最小二乘回归的输入变量进行全谱初步建模,依据回归系数选择NIRS光谱中的有效波段,再将它与XRF光谱中的成灰元素谱线一并融合进行归一化处理。建模时将预处理后的融合光谱数据作为输入变量,利用偏最小二乘回归对煤炭发热量进行建模。实验结果表明,NIRS-XRF联用方法对定标集煤样发热量预测的线性相关度系数(R^(2))为0.995,对验证集煤样发热量预测的最小均方根误差、平均相对误差和标准偏差分别为0.24 MJ/kg,0.61%和0.05 MJ/kg,测量重复性满足小于0.12 MJ/kg的国家标准。NIRS-XRF联用的煤炭发热量高稳定检测方法有望推广应用于火力发电、煤化工、冶金、水泥和焦化等“高碳”行业,助力我国按期实现碳中和目标。 展开更多
关键词 近红外光谱 X射线荧光光谱 光谱融合 煤炭发热量 高稳定检测
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Application of NIR Reflectance Spectroscopy on Rapid Determination of Moisture Content of Wood Pellets 被引量:1
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作者 Jaya Sundaram Sudhagar Mani +1 位作者 Chari V. K. Kandala Ronald A. Holser 《American Journal of Analytical Chemistry》 2015年第12期923-932,共10页
NIR spectroscopy was used to measure the moisture concentration of wood pellets. Pellets were conditioned to various moisture levels between 0.63% and 14.16% (wet basis) and the moisture concentration was verified usi... NIR spectroscopy was used to measure the moisture concentration of wood pellets. Pellets were conditioned to various moisture levels between 0.63% and 14.16% (wet basis) and the moisture concentration was verified using a standard oven method. Samples from various moisture levels were separated into two groups, as calibration and validation sets. NIR absorption spectral data from 400 nm to 2500 nm with 0.5 nm intervals were collected using pellets within the calibration and validation sample sets. Spectral wavelength ranges were taken as independent variables and the MC of the pellets as the dependent variable for the analysis. Measurements were obtained on 30 replicates within each moisture level. Partial Least Square (PLS) analysis was performed on both raw and preprocessed spectral data of calibration set to determine the best calibration model based on Standard Error of Calibration (SEC) and coefficient of multiple determinations (R2). The PLS model that yielded the best fit was used to predict the moisture concentration of validation group pellets. Relative Percent Deviation (RPD) and Standard Error of Prediction (SEP) were calculated to validate goodness of fit of the prediction model. Baseline and Multiple Scatter Corrected (MSC) reflectance spectra with 1st derivative model gave the highest RPD value of 4.46 and R2 of 0.95. Also it’s SEP (0.670) and RMSEP (0.782) were less than the other models those had RPD value more than 3.0 with less number of factors. Therefore, this model was selected as the best model for moisture content prediction of wood pellets. 展开更多
关键词 Wood PELLETS nir Reflectance spectroscopy MOISTURE Content Partial Least SQUARE RELATIVE PERCENT Deviation
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利用VIS/NIR反射光谱快速检测柿饼加工中水分含量 被引量:1
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作者 赵鹏瑶 彭月梅 吴建虎 《农产品加工》 2021年第17期49-52,56,共5页
水分是柿饼的重要组成成分,也是影响柿饼制作过程的重要因素。利用可见/近红外反射光谱对柿饼制作过程中的水分含量进行检测。首先,获取柿饼在不同加工阶段的可见/近红外反射光谱(400~1000 nm),采用烘干法测定柿饼水分含量。然后,对光... 水分是柿饼的重要组成成分,也是影响柿饼制作过程的重要因素。利用可见/近红外反射光谱对柿饼制作过程中的水分含量进行检测。首先,获取柿饼在不同加工阶段的可见/近红外反射光谱(400~1000 nm),采用烘干法测定柿饼水分含量。然后,对光谱进行Mean smoothing(MS)平滑、多元散射校正(MSC)和一阶导数(1-D)预处理。最后,对不同预处理光谱,结合样本水分含量,使用Samples set partitioning based on joint x-y distance(SPXY)方法划分校正集和验证集,基于SPA方法选择特征波长,建立多元线性回归(MLR)预测模型。结果表明,反射光谱经过MS处理后,确定的9个最优波长组合建立水分检测模型的预测结果最好:预测相关系数(Rp)为0.9690,预测标准残差(SEP)为3.4729%,可见/近红外反射光谱技术可以较好地预测柿饼制作过程中的的水分含量。研究可为柿饼加工过程中的品质快速检测提供一定的技术支撑。 展开更多
关键词 柿饼 水分含量 vis/nir光谱反射 SPXY算法 SPA算法
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Visual Perception of Incomplete Human-Like Body Postures: A Near-Infrared Spectroscopy Study
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作者 Hiroshi Ito Hirofumi Saito +3 位作者 Misato Oi Tomoko Shiraishi Shuang Meng Victor Alberto Palacios 《Journal of Behavioral and Brain Science》 2014年第12期544-558,共15页
Previous studies have reported that the mirror neuron system plays a crucial role in social cognition. We examined whether the higher-order cognitive functions are involved in the activations in the mirror neuron area... Previous studies have reported that the mirror neuron system plays a crucial role in social cognition. We examined whether the higher-order cognitive functions are involved in the activations in the mirror neuron area when we perceive simplified pseudo-postures. We measured 14 participants’ brain activation during the posture-recognition task using near-infrared spectroscopy. The participants’ task was to observe five sequentially presented target pseudo-postures and judge whether a test pseudo-posture was identical to one of the preceding five target pseudo-postures. The results in the majority of participants (n = 10/14) revealed that the activity in the inferior frontal mirror neuron area is modulated by perception of human-likeness, but not in the remaining four participants (n = 4/14). These results suggest that the degree of the activation of higher-order cognitive functions, which may be engaged in the inhibitory and/or facilitative processing of human body or bodily movement, leads to the distinctive activities in the inferior frontal mirror neuron area. 展开更多
关键词 NEAR-INFRARED spectroscopy (nirS) MIRROR NEURON System Object PERCEPTION HUMAN Body
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