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
This study aimed to investigate the capabilities of hyperspectral scattering imaging in tandem with Gaussian function,Exponential function and Lorentzian function for rapid and nondestructive determination of total vi...This study aimed to investigate the capabilities of hyperspectral scattering imaging in tandem with Gaussian function,Exponential function and Lorentzian function for rapid and nondestructive determination of total viable count(TVC)in pork meat.Two batches of fresh pork meat was purchased from a local market and stored at 10°C for 1-9 d.Totally 60 samples were used,and several samples were taken out randomly for hyperspectral scattering imaging and conventional microbiological tests on each day of the experiments.The functions of Gaussian,Exponential and Lorentzian were employed to model the hyperspectral scattering profiles of pork meat,and good fitting results were obtained by all three functions between 455 nm and 1000 nm.The Lorentzian function performed best for fitting the hyperspectral scattering profiles of pork meat compared with other functions.Both principal component regression(PCR)and partial least squares regression(PLSR)methods were performed to establish the prediction models.Among all the developed models,the models developed using parameters CE(scattering width parameter of Exponential function)and CL(scattering width parameter of Lorentzian function)by PLSR method gave superior results for predicting pork meat TVC,with RV and RMSEV of 0.92,0.59 log CFU/g,and 0.91,0.61 log CFU/g,respectively.In addition,based on the improved hyperspectral scattering system,parameter c which represented the scattering widths in all three functions gave more accurate prediction results,regardless of the modeling methods(PCR or PLSR).The obtained results demonstrated that hyperspectral scattering imaging combined with the presented data analysis algorithm can be a powerful tool for evaluating the microbial safety of meat in the future.展开更多
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.
基金The authors gratefully acknowledge the China Postdoctoral Science Foundation(Project No.2014M561096)the Special Fund for Agro-scientific Research in the Public Interest Program(Project No.201003008)the National Science and Technology Support Program(Project No.2012BAH04B00)for supporting this research.
文摘This study aimed to investigate the capabilities of hyperspectral scattering imaging in tandem with Gaussian function,Exponential function and Lorentzian function for rapid and nondestructive determination of total viable count(TVC)in pork meat.Two batches of fresh pork meat was purchased from a local market and stored at 10°C for 1-9 d.Totally 60 samples were used,and several samples were taken out randomly for hyperspectral scattering imaging and conventional microbiological tests on each day of the experiments.The functions of Gaussian,Exponential and Lorentzian were employed to model the hyperspectral scattering profiles of pork meat,and good fitting results were obtained by all three functions between 455 nm and 1000 nm.The Lorentzian function performed best for fitting the hyperspectral scattering profiles of pork meat compared with other functions.Both principal component regression(PCR)and partial least squares regression(PLSR)methods were performed to establish the prediction models.Among all the developed models,the models developed using parameters CE(scattering width parameter of Exponential function)and CL(scattering width parameter of Lorentzian function)by PLSR method gave superior results for predicting pork meat TVC,with RV and RMSEV of 0.92,0.59 log CFU/g,and 0.91,0.61 log CFU/g,respectively.In addition,based on the improved hyperspectral scattering system,parameter c which represented the scattering widths in all three functions gave more accurate prediction results,regardless of the modeling methods(PCR or PLSR).The obtained results demonstrated that hyperspectral scattering imaging combined with the presented data analysis algorithm can be a powerful tool for evaluating the microbial safety of meat in the future.
