Firmness is one of the most important characteristics to estimate fruit maturity and quality.The potential of near-infrared(NIR)diffuse reflectance spectroscopy as a nondestructive way for pear firmness evaluation of ...Firmness is one of the most important characteristics to estimate fruit maturity and quality.The potential of near-infrared(NIR)diffuse reflectance spectroscopy as a nondestructive way for pear firmness evaluation of three varieties(‘Cuiguan’,‘Xueqing’and‘Xizilv’)was studied,both quantitatively and qualitatively.NIR models were established using partial least square(PLS)methods in the spectral range of 800 to 2500 nm.For quantitative analysis,the correlation coefficient r increased with more varieties involved in the model.Best results were obtained in the model for all three varieties:rcalwas 0.934,root mean square error of calibration(RMSEC)and root mean square error of prediction(RMSEP)were 2.06 N and 3.14 N,respectively.For qualitative analysis,the overall accuracies of discriminant PLS models for classifying pears into three firmness levels:low,medium and high firmness level were not so good,percentage of samples correctly classified ranged from 70.63%to 81.25%for calibration and from 56.25%to 74.38%for validation.The results indicate that NIR spectroscopy together with PLS chemometrics method is feasible for quantitative analysis of pear firmness,however,the classification accuracy is too low to put into practical application.展开更多
This paper presents a new idea, named as modeling multisensor-heterogeneous information, to incorporate the fuzzy logic methodologies with mulitsensor-multitarget system under the framework of random set theory. First...This paper presents a new idea, named as modeling multisensor-heterogeneous information, to incorporate the fuzzy logic methodologies with mulitsensor-multitarget system under the framework of random set theory. Firstly, based on strong random set and weak random set, the unified form to describe both data (unambiguous information) and fuzzy evidence (uncertain information) is introduced. Secondly, according to signatures of fuzzy evidence, two Bayesian-markov nonlinear measurement models are proposed to fuse effectively data and fuzzy evidence. Thirdly, by use of "the models-based signature-matching scheme", the operation of the statistics of fuzzy evidence defined as random set can be translated into that of the membership functions of relative point state variables. These works are the basis to construct qualitative measurement models and to fuse data and fuzzy evidence.展开更多
基金The authors gratefully acknowledge the financial support provided by National Natural Science Foundation of China(No.30671197)the Program for New Century Excellent Talents in University(No.NCET-04-0524).
文摘Firmness is one of the most important characteristics to estimate fruit maturity and quality.The potential of near-infrared(NIR)diffuse reflectance spectroscopy as a nondestructive way for pear firmness evaluation of three varieties(‘Cuiguan’,‘Xueqing’and‘Xizilv’)was studied,both quantitatively and qualitatively.NIR models were established using partial least square(PLS)methods in the spectral range of 800 to 2500 nm.For quantitative analysis,the correlation coefficient r increased with more varieties involved in the model.Best results were obtained in the model for all three varieties:rcalwas 0.934,root mean square error of calibration(RMSEC)and root mean square error of prediction(RMSEP)were 2.06 N and 3.14 N,respectively.For qualitative analysis,the overall accuracies of discriminant PLS models for classifying pears into three firmness levels:low,medium and high firmness level were not so good,percentage of samples correctly classified ranged from 70.63%to 81.25%for calibration and from 56.25%to 74.38%for validation.The results indicate that NIR spectroscopy together with PLS chemometrics method is feasible for quantitative analysis of pear firmness,however,the classification accuracy is too low to put into practical application.
基金Supported by the NSFC(No.60434020,60572051)Science and Technology Key Item of Ministry of Education of the PRC( No.205-092)the ZJNSF(No. R106745)
文摘This paper presents a new idea, named as modeling multisensor-heterogeneous information, to incorporate the fuzzy logic methodologies with mulitsensor-multitarget system under the framework of random set theory. Firstly, based on strong random set and weak random set, the unified form to describe both data (unambiguous information) and fuzzy evidence (uncertain information) is introduced. Secondly, according to signatures of fuzzy evidence, two Bayesian-markov nonlinear measurement models are proposed to fuse effectively data and fuzzy evidence. Thirdly, by use of "the models-based signature-matching scheme", the operation of the statistics of fuzzy evidence defined as random set can be translated into that of the membership functions of relative point state variables. These works are the basis to construct qualitative measurement models and to fuse data and fuzzy evidence.
