Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artifici...Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.展开更多
This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enab...This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.展开更多
Numerical study was performed to evaluate the characteristics of combined heat transfer of radiation, conduction and convection in indirect near infrared ray （N/R） heating chamber. The effects of important design pa...Numerical study was performed to evaluate the characteristics of combined heat transfer of radiation, conduction and convection in indirect near infrared ray （N/R） heating chamber. The effects of important design parameters such as the shape of heat absorbing cylinder and heat releasing fin on the pressure drop and heat transfer coefficient were analyzed with different Reynolds numbers. The Reynolds numbers were varied from 103 to 3x106, which was defined based on the hydraulic diameter of the heat absorbing cylinder. Analyses were performed to obtain the inner and outer flow and the temperature distributions in the heat absorbing cylinder and the rates of radiation heat transfer and convection heat transfer. As the Reynolds number increases, the convection heat transfer rate is increased while the radiation heat transfer rate is decreased. The average convection heat transfer rate follows a power rule of the Reynolds number. Addition of three-dimensional heat releasing fin to the outside of the heat absorbing cylinder enhances the convection heat transfer.展开更多
In the paper, a method of building mathematic model employing genetic multilayer feed forward neural network is presented, and the quantitative relationship of chemical measured values and near-infrared spectral data ...In the paper, a method of building mathematic model employing genetic multilayer feed forward neural network is presented, and the quantitative relationship of chemical measured values and near-infrared spectral data is established. In the paper, quantitative mathematic model related chemical assayed values and near-infrared spectral data is established by means of genetic multilayer feed forward neural network, acquired near-infrared spectral data are taken as input of network with the content of five kinds of fat acids tested from chemical method as output, weight values of multilayer feed forward neural network are trained by genetic algorithms and detection model of neural network of soybean is built. A kind of multilayer feed forward neural network trained by genetic algorithms is designed in the paper. Through experiments, all the related coefficients of five fat acids can approach 0.9 which satisfies the preliminary test of soybean breeding.展开更多
Background Fiber maturity is a key cotton quality property,and its variability in a sample impacts fiber processing and dyeing performance.Currently,the maturity is determined by using established protocols in laborat...Background Fiber maturity is a key cotton quality property,and its variability in a sample impacts fiber processing and dyeing performance.Currently,the maturity is determined by using established protocols in laboratories under a controlled environment.There is an increasing need to measure fiber maturity using low-cost(in general less than $20000)and small portable systems.In this study,a laboratory feasibility was performed to assess the ability of the shortwave infrared hyperspectral imaging(SWIR HSI)technique for determining the conditioned fiber maturity,and as a comparison,a bench-top commercial and expensive(in general greater than $60000)near infrared(NIR)instrument was used.Results Although SWIR HSI and NIR represent different measurement technologies,consistent spectral characteristics were observed between the two instruments when they were used to measure the maturity of the locule fiber samples in seed cotton and of the well-defined fiber samples,respectively.Partial least squares(PLS)models were established using different spectral preprocessing parameters to predict fiber maturity.The high prediction precision was observed by a lower root mean square error of prediction(RMSEP)(<0.046),higher R_(p)^(2)(>0.518),and greater percentage(97.0%)of samples within the 95% agreement range in the entire NIR region(1000-2500 nm)without the moisture band at 1940 nm.Conclusion SWIR HSI has a good potential for assessing cotton fiber maturity in a laboratory environment.展开更多
Visible and near-infrared(VNIR)spectroscopy is an eco-friendly method used for estimating plant nutrient deficiencies.The aim of this study was to investigate the possibility of using VNIR method for estimating Zn con...Visible and near-infrared(VNIR)spectroscopy is an eco-friendly method used for estimating plant nutrient deficiencies.The aim of this study was to investigate the possibility of using VNIR method for estimating Zn content in cherry orchard leaves under field conditions.The study was conducted in 3different locations in Isparta region of Turkey.Fifteen cherry orchards containing normal and Zn deficient plants were chosen,and 60 leaf samples were collected from each location.The reflectance spectra of the leaves were measured with an ASD FieldSpec HandHeld spectroradiometer and a plant probe.The Zn contents of leaf samples were predicted through laboratory analysis.The spectral reflectance measurements were used to estimate the Zn levels using stepwise multiple linear regression analysis method.Prediction models were created using the highest coefficient of determination value.The results show that Zn content of cherry trees can be estimated using the VNIR spectroscopic method(87.5<r2<96.79).Moreover,plant nutrient contents can be estimated without using chemicals.However,further research is necessary to develop a standard method for field conditions.Because spectral reflectance is affected by ecological conditions,agricultural applications and nutrient interactions,more effective models must be developed depending on the geographical location,period and plant type.展开更多
基金Supported by the National 12th Five-year Plan for Science&Technology Support Fund(2012BAK08B04-02)the Heilongjiang Science and Technology Plan(GC12B404)
文摘Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.
文摘This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.
基金supported by the Second Stage of Brain Korea 21 Projects
文摘Numerical study was performed to evaluate the characteristics of combined heat transfer of radiation, conduction and convection in indirect near infrared ray （N/R） heating chamber. The effects of important design parameters such as the shape of heat absorbing cylinder and heat releasing fin on the pressure drop and heat transfer coefficient were analyzed with different Reynolds numbers. The Reynolds numbers were varied from 103 to 3x106, which was defined based on the hydraulic diameter of the heat absorbing cylinder. Analyses were performed to obtain the inner and outer flow and the temperature distributions in the heat absorbing cylinder and the rates of radiation heat transfer and convection heat transfer. As the Reynolds number increases, the convection heat transfer rate is increased while the radiation heat transfer rate is decreased. The average convection heat transfer rate follows a power rule of the Reynolds number. Addition of three-dimensional heat releasing fin to the outside of the heat absorbing cylinder enhances the convection heat transfer.
基金Heilongjiang Natural Science Foundation (F0318).
文摘In the paper, a method of building mathematic model employing genetic multilayer feed forward neural network is presented, and the quantitative relationship of chemical measured values and near-infrared spectral data is established. In the paper, quantitative mathematic model related chemical assayed values and near-infrared spectral data is established by means of genetic multilayer feed forward neural network, acquired near-infrared spectral data are taken as input of network with the content of five kinds of fat acids tested from chemical method as output, weight values of multilayer feed forward neural network are trained by genetic algorithms and detection model of neural network of soybean is built. A kind of multilayer feed forward neural network trained by genetic algorithms is designed in the paper. Through experiments, all the related coefficients of five fat acids can approach 0.9 which satisfies the preliminary test of soybean breeding.
基金supported partially by the USDA-ARS Research Project#6054-44000-080-00D.
文摘Background Fiber maturity is a key cotton quality property,and its variability in a sample impacts fiber processing and dyeing performance.Currently,the maturity is determined by using established protocols in laboratories under a controlled environment.There is an increasing need to measure fiber maturity using low-cost(in general less than $20000)and small portable systems.In this study,a laboratory feasibility was performed to assess the ability of the shortwave infrared hyperspectral imaging(SWIR HSI)technique for determining the conditioned fiber maturity,and as a comparison,a bench-top commercial and expensive(in general greater than $60000)near infrared(NIR)instrument was used.Results Although SWIR HSI and NIR represent different measurement technologies,consistent spectral characteristics were observed between the two instruments when they were used to measure the maturity of the locule fiber samples in seed cotton and of the well-defined fiber samples,respectively.Partial least squares(PLS)models were established using different spectral preprocessing parameters to predict fiber maturity.The high prediction precision was observed by a lower root mean square error of prediction(RMSEP)(<0.046),higher R_(p)^(2)(>0.518),and greater percentage(97.0%)of samples within the 95% agreement range in the entire NIR region(1000-2500 nm)without the moisture band at 1940 nm.Conclusion SWIR HSI has a good potential for assessing cotton fiber maturity in a laboratory environment.
文摘Visible and near-infrared(VNIR)spectroscopy is an eco-friendly method used for estimating plant nutrient deficiencies.The aim of this study was to investigate the possibility of using VNIR method for estimating Zn content in cherry orchard leaves under field conditions.The study was conducted in 3different locations in Isparta region of Turkey.Fifteen cherry orchards containing normal and Zn deficient plants were chosen,and 60 leaf samples were collected from each location.The reflectance spectra of the leaves were measured with an ASD FieldSpec HandHeld spectroradiometer and a plant probe.The Zn contents of leaf samples were predicted through laboratory analysis.The spectral reflectance measurements were used to estimate the Zn levels using stepwise multiple linear regression analysis method.Prediction models were created using the highest coefficient of determination value.The results show that Zn content of cherry trees can be estimated using the VNIR spectroscopic method(87.5<r2<96.79).Moreover,plant nutrient contents can be estimated without using chemicals.However,further research is necessary to develop a standard method for field conditions.Because spectral reflectance is affected by ecological conditions,agricultural applications and nutrient interactions,more effective models must be developed depending on the geographical location,period and plant type.
