In vivo fluorescence methods are efficient tools for studying the distribution of phytoplankton in nature.Different algae species usually have different pigments with different ratios,which results in different fluore...In vivo fluorescence methods are efficient tools for studying the distribution of phytoplankton in nature.Different algae species usually have different pigments with different ratios,which results in different fluorescence emission spectra.Based on multiple excitation wavelength fluorescence emission spectra,a discrimination technique is established in this study.The discrimination method,established by multivariate linear regression and weighted least-squares,was used to differentiate the samples cultured in the laboratory and collected from Jiaozhou Bay near Qingdao at the division level.The correctly discriminated samples were ≥ 86% for single algae samples,≥ 88% for simulatively mixed ones,≥ 91% for physically mixed ones and 100% for samples collected from Jiaozhou Bay.The result in this research is more definite for the physically mixed samples in the laboratory.The method described here can be employed to monitor the phytoplankton population in the marine environment.展开更多
It is well known that when the random errors are iid. with finite variance, the week and the strong consiStency of LS estimate of multiple regression coefficients are equivalent. This note, by constructing a counter-e...It is well known that when the random errors are iid. with finite variance, the week and the strong consiStency of LS estimate of multiple regression coefficients are equivalent. This note, by constructing a counter-example, shows that this equivalence no longer holds true in case that the random errors possess only the r-th moment with 1≤5 T ＜ 2.展开更多
基金supported by the National Natural Science Foundation of China (No.40706036)the National High-Tech Research and Development Program of China (863 Program) (No.2006AA09Z178)
文摘In vivo fluorescence methods are efficient tools for studying the distribution of phytoplankton in nature.Different algae species usually have different pigments with different ratios,which results in different fluorescence emission spectra.Based on multiple excitation wavelength fluorescence emission spectra,a discrimination technique is established in this study.The discrimination method,established by multivariate linear regression and weighted least-squares,was used to differentiate the samples cultured in the laboratory and collected from Jiaozhou Bay near Qingdao at the division level.The correctly discriminated samples were ≥ 86% for single algae samples,≥ 88% for simulatively mixed ones,≥ 91% for physically mixed ones and 100% for samples collected from Jiaozhou Bay.The result in this research is more definite for the physically mixed samples in the laboratory.The method described here can be employed to monitor the phytoplankton population in the marine environment.
基金the National Natural Science Foundation of China (No.19631040).
文摘It is well known that when the random errors are iid. with finite variance, the week and the strong consiStency of LS estimate of multiple regression coefficients are equivalent. This note, by constructing a counter-example, shows that this equivalence no longer holds true in case that the random errors possess only the r-th moment with 1≤5 T ＜ 2.
