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
Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts...Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce online predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of online COD measurements in wastewater using NIR spectroscopy.展开更多
The composition of cement raw materials was detected by near-infrared spectroscopy.It was found that the BiPLS-SiPLS method selected the NIR spectral band of cement raw materials,and the partial least squares regressi...The composition of cement raw materials was detected by near-infrared spectroscopy.It was found that the BiPLS-SiPLS method selected the NIR spectral band of cement raw materials,and the partial least squares regression algorithm was adopted to establish a quantitative correction model of cement raw materials with good prediction effect.The root-mean-square errors of SiO_(2),Al_(2)O_(3),Fe_(2)O_(3) and CaO calibration were 0.142,0.072,0.034 and 0.188 correspondingly.The results show that the NIR spectroscopy method can detect the composition of cement raw meal rapidly and accurately,which provides a new perspective for the composition detection of cement raw meal.展开更多
To clarify the quality characters,understand the genetic diversity and screen elite lines among different oilseed sunflowers,the contents of crude fat,oleic acid,linoleic acid,palmitic acid and stearic acid of 525 oil...To clarify the quality characters,understand the genetic diversity and screen elite lines among different oilseed sunflowers,the contents of crude fat,oleic acid,linoleic acid,palmitic acid and stearic acid of 525 oil sunflowers(including 375 germplasm accessions and 150 inbred lines)were detected by near-infrared spectroscopy(NIRS);the genetic variation and correlation analysis of quality traits were also performed.The results showed that oleic acid and linoleic acid had rich diversities with large variation ranges for each material type.Similar to the relation between crude fat content and palmitic acid content,significantly negative relation with high estimated value existed between oleic acid and linoleic acid content,while stearic acid content positively associated with oleic acid and palmitic acid content.Principal component analysis indicated that 5 quality traits were integrated into 2principal component factors(linoleic acid negative factor and palmitic acid factor)with the contribution rate of 88.191%,which could be used for evaluating sunflower quality.525 oilseed sunflowers were clustered into 3groups with obvious differences of quality characters,materials in Group I had high contents of oleic acid and low crude fat,but the opposite was found in GroupⅢ.59 superior quality accessions were obtained using large-scale and rapid near-infrared spectroscopy,and these excellent materials were verified by the traditional national chemical standard method.This research provided materials and significant reference for sunflower genetic research and quality breeding.展开更多
A portable near infrared spectroscopy system was developed for assessing the quality of Nanfeng mandarin fruit.One hundred and fifty-three Nanfeng mandarin samples were used to measure the performance of the system.Se...A portable near infrared spectroscopy system was developed for assessing the quality of Nanfeng mandarin fruit.One hundred and fifty-three Nanfeng mandarin samples were used to measure the performance of the system.Several pretreatment methods were adopted to process the spectra.Then Support Vector Machine(SVM),Back Propagation Neural Network(BPNN)and Partial Least Square(PLS)were used to build models for soluble solids content(SSC),titratable acidity(TA),vitamin C and surface color.The best results were obtained by SVM.The correlation coefficient(R)and root mean square error of prediction(RMSEP)were(0.93,0.65°Brix),(0.66,0.09%),(0.81,2.7mg/100g)and(0.57,0.81)for SSC,TA,vitamin C and color,respectively.The results demonstrated that the portable near infrared spectroscopy was feasible for determining the Nanfeng mandarin quality nondestructively.展开更多
A rapid identification method for aflatoxin B_(1) in paddy rice samples was developed by using near infrared spectroscopy under a wavelength range of 1000-2500 nm.Eighty paddy rice samples were collected from both nat...A rapid identification method for aflatoxin B_(1) in paddy rice samples was developed by using near infrared spectroscopy under a wavelength range of 1000-2500 nm.Eighty paddy rice samples were collected from both natural and artificial infection with aflatoxin B_(1) to build the calibration models based on the partial least square regression method.The best predictive model to detect aflatoxin B_(1) in paddy rice was obtained using standard normal variate detrending spectra,with a correlation of 0.850,and a standard error of prediction of 3.211%.Therefore,the result showed that near infrared spectroscopy could be a useful instrumental method for determining aflatoxin B_(1) in paddy rice.The near infrared spectroscopy methodology can be applied to the monitoring of aflatoxin fungal contamination in postharvest paddy rice during storage and may become a powerful tool for the safety of grain and grain products.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
The aim of this study was to develop near infrared spectroscopy(NIRS)calibrations to predict quality parameters,dry matter(DM,g kg1)and crude protein(CP,g kg1 DM),in fresh un-dried grass.Knowledge of these parameters ...The aim of this study was to develop near infrared spectroscopy(NIRS)calibrations to predict quality parameters,dry matter(DM,g kg1)and crude protein(CP,g kg1 DM),in fresh un-dried grass.Knowledge of these parameters would enable more precise allocation of quality herbage to grazing livestock.Perennial ryegrass samples(n=1615)were collected over the 2017 and 2018 grazing seasons at Teagasc Moorepark to develop a NIRS calibration dataset.Additional samples were collected for an independent validation dataset(n=197)during the 2019 grazing season.Samples were scanned using a FOSS 6500 spectrometer at 2 nm intervals in the range of 1100~2500 nm and absorption was recorded as log 1/Reflectance.Reference wet chemistry analysis was carried out for both parameters and the resultant data were calibrated against spectral data by means of modified partial least squares regression.A range of mathematical spectral treatments were examined for each calibration,which were ranked in order of standard error of prediction(SEP)and ratio of percent deviation(RPD).Best performing calibrations achieved high predictive precision for DM(R2=0.86 SEP=9.46 g kg1,RPD=2.60)and moderate precision for CP(R2=0.84 SEP=20.38 g kg1 DM,RPD=2.37).These calibrations will aid the optimisation of grassland management and the development of precision agricultural technologies.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Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce online predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of online COD measurements in wastewater using NIR spectroscopy.
基金Funded by the National Natural Science Foundation of China (No. 62073153)The Major Scientific and Technological Innovation Projects in Shandong Province (No.2019JZZY010448)The Key Research and Development Plan of Shandong Province of China (No.2019GSF109018)。
文摘The composition of cement raw materials was detected by near-infrared spectroscopy.It was found that the BiPLS-SiPLS method selected the NIR spectral band of cement raw materials,and the partial least squares regression algorithm was adopted to establish a quantitative correction model of cement raw materials with good prediction effect.The root-mean-square errors of SiO_(2),Al_(2)O_(3),Fe_(2)O_(3) and CaO calibration were 0.142,0.072,0.034 and 0.188 correspondingly.The results show that the NIR spectroscopy method can detect the composition of cement raw meal rapidly and accurately,which provides a new perspective for the composition detection of cement raw meal.
基金the Project of“Accurate Identification of Sunflower Germplasm Resources(19221985)”the earmarked fund of“CARS—Specific Oilseed Crops(CARS-14)”+2 种基金the Project of“Exploration,Identification and Innovative Utilization of Excellent Germplasm Resources of Oil Crops(CAAS-OCRI-ZDRW-202101)”the Project of“Oil Crop Germplasm Resource Protection(19221888-4)”the Project of“National Science and Technology Resource Sharing Service Platform(NCGRC-2022-Special Oil Crop)”。
文摘To clarify the quality characters,understand the genetic diversity and screen elite lines among different oilseed sunflowers,the contents of crude fat,oleic acid,linoleic acid,palmitic acid and stearic acid of 525 oil sunflowers(including 375 germplasm accessions and 150 inbred lines)were detected by near-infrared spectroscopy(NIRS);the genetic variation and correlation analysis of quality traits were also performed.The results showed that oleic acid and linoleic acid had rich diversities with large variation ranges for each material type.Similar to the relation between crude fat content and palmitic acid content,significantly negative relation with high estimated value existed between oleic acid and linoleic acid content,while stearic acid content positively associated with oleic acid and palmitic acid content.Principal component analysis indicated that 5 quality traits were integrated into 2principal component factors(linoleic acid negative factor and palmitic acid factor)with the contribution rate of 88.191%,which could be used for evaluating sunflower quality.525 oilseed sunflowers were clustered into 3groups with obvious differences of quality characters,materials in Group I had high contents of oleic acid and low crude fat,but the opposite was found in GroupⅢ.59 superior quality accessions were obtained using large-scale and rapid near-infrared spectroscopy,and these excellent materials were verified by the traditional national chemical standard method.This research provided materials and significant reference for sunflower genetic research and quality breeding.
基金the National Natural Science Foundation of China(Grant No.60844007,60468002,30560064)New Century Excellent Talents in University(NCET-06-0575)+1 种基金National Science and Technology Support Plan(2008BAD96B04,2006BAD11A12-07)Natural Science Foundation of Jiangxi Provincial(2008GQN0029,2007GZN0266,2007-130).
文摘A portable near infrared spectroscopy system was developed for assessing the quality of Nanfeng mandarin fruit.One hundred and fifty-three Nanfeng mandarin samples were used to measure the performance of the system.Several pretreatment methods were adopted to process the spectra.Then Support Vector Machine(SVM),Back Propagation Neural Network(BPNN)and Partial Least Square(PLS)were used to build models for soluble solids content(SSC),titratable acidity(TA),vitamin C and surface color.The best results were obtained by SVM.The correlation coefficient(R)and root mean square error of prediction(RMSEP)were(0.93,0.65°Brix),(0.66,0.09%),(0.81,2.7mg/100g)and(0.57,0.81)for SSC,TA,vitamin C and color,respectively.The results demonstrated that the portable near infrared spectroscopy was feasible for determining the Nanfeng mandarin quality nondestructively.
基金the National 12th Five-Year Plan for Science&Technology Support Fund(NO.2012BAK08B04-02)for its financial support。
文摘A rapid identification method for aflatoxin B_(1) in paddy rice samples was developed by using near infrared spectroscopy under a wavelength range of 1000-2500 nm.Eighty paddy rice samples were collected from both natural and artificial infection with aflatoxin B_(1) to build the calibration models based on the partial least square regression method.The best predictive model to detect aflatoxin B_(1) in paddy rice was obtained using standard normal variate detrending spectra,with a correlation of 0.850,and a standard error of prediction of 3.211%.Therefore,the result showed that near infrared spectroscopy could be a useful instrumental method for determining aflatoxin B_(1) in paddy rice.The near infrared spectroscopy methodology can be applied to the monitoring of aflatoxin fungal contamination in postharvest paddy rice during storage and may become a powerful tool for the safety of grain and grain products.
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The aim of this study was to develop near infrared spectroscopy(NIRS)calibrations to predict quality parameters,dry matter(DM,g kg1)and crude protein(CP,g kg1 DM),in fresh un-dried grass.Knowledge of these parameters would enable more precise allocation of quality herbage to grazing livestock.Perennial ryegrass samples(n=1615)were collected over the 2017 and 2018 grazing seasons at Teagasc Moorepark to develop a NIRS calibration dataset.Additional samples were collected for an independent validation dataset(n=197)during the 2019 grazing season.Samples were scanned using a FOSS 6500 spectrometer at 2 nm intervals in the range of 1100~2500 nm and absorption was recorded as log 1/Reflectance.Reference wet chemistry analysis was carried out for both parameters and the resultant data were calibrated against spectral data by means of modified partial least squares regression.A range of mathematical spectral treatments were examined for each calibration,which were ranked in order of standard error of prediction(SEP)and ratio of percent deviation(RPD).Best performing calibrations achieved high predictive precision for DM(R2=0.86 SEP=9.46 g kg1,RPD=2.60)and moderate precision for CP(R2=0.84 SEP=20.38 g kg1 DM,RPD=2.37).These calibrations will aid the optimisation of grassland management and the development of precision agricultural technologies.
