[Objectives]This study was conducted to clarify the difference of millet from different producing areas in near-infrared spectroscopy(NIRS)modeling.[Methods]Millet samples from six different regions were collected for...[Objectives]This study was conducted to clarify the difference of millet from different producing areas in near-infrared spectroscopy(NIRS)modeling.[Methods]Millet samples from six different regions were collected for NIRS analysis,and an origin identification model based on BP neural network was established.The competitive adaptive reweighted sampling(CARS)algorithm was used to extract characteristic wavelength variables,and a CARS-BP model was established on this basis.Finally,the CARS-BP model was compared with support vector machine(SVM),partial least squares discriminant analysis(PLS)and KNN models.[Results]The characteristic wavelengths were extracted by CARS,and the number of variables was reduced from 1845 to 130.The discrimination accuracy of the CARS-BP model for the samples from six producing areas reached 98.1%,which was better than SVM,PSL and KNN models.[Conclusions]NIRS can quickly and accurately identify the origin of millet,providing a new method and way for the origin identification and quality evaluation of millet.展开更多
Accurate identification of natural gas origin is fundamental to the theoretical research on natural gas geosciences and the exploration deployment and resource potential assessment of oil and gas.Since the 1970s,Acade...Accurate identification of natural gas origin is fundamental to the theoretical research on natural gas geosciences and the exploration deployment and resource potential assessment of oil and gas.Since the 1970s,Academician Dai Jinxing has developed a comprehensive system for natural gas origin determination,grounded in geochemical theory and practice,and based on the integrated analysis of stable isotopic compositions,molecular composition,light hydrocarbon fingerprints,and geological context.This paper systematically reviews the core framework established by him and his team according to related references and application results,focusing on the conceptual design and technical pathways of key diagnostic diagrams such asδ^(13)C_(1)-C_(1)/(C_(2)+C_(3)),δ^(13)C_(1)-δ^(13)C_(2)-δ^(13)C_(3),δ^(13)CCO_(2)versus CO_(2)content,and the C7light hydrocarbon ternary plot.We evaluate the applicability and innovation of these tools in distinguishing between oil-type gas,coal-derived gas,microbial gas,and abiogenic gas,as well as in identifying mixed-source gases and multi-stage charging systems.The findings suggest that this identification system has significantly advanced natural gas geochemical interpretation in China,shifting from single-indicator analyses to multi-parameter integration and from qualitative assessments to systematic graphical identification,and has also exerted considerable influence on international research in natural gas geochemistry.The structured overview of the development trajectory of natural gas origin discrimination methodologies provides a technical support for natural gas geological theory and practice and offers a scientific foundation for the academic evaluation and application of related achievements.展开更多
Objective:Citri Reticulatae Pericarpium(Chenpi,CRP)is one of the most used traditional Chinese medicines with great medicinal,dietary and collection values,among which the Citrus reticulata cv.'Chachi'(Citrus ...Objective:Citri Reticulatae Pericarpium(Chenpi,CRP)is one of the most used traditional Chinese medicines with great medicinal,dietary and collection values,among which the Citrus reticulata cv.'Chachi'(Citrus reticulata cv.Chachiensis)from Guangdong Xinhui is the geoherb of CRP.Xinhui CRP in the market was often counterfeited with other varieties or origins,molecular identification method can effectively distinguish different CRP varieties,but it's still a difficult problem to identify the same CRP variety from different origin.It is necessary to discover a new molecular marker to ensure the safe and effective application of Xinhui CRP.Methods:We selected one of the most studied transcription factor families in Citrus genus,MYB,to design the specific candidate primers on the conserved region.The primers with good band repeatability and high polymorphism were screened for PCR amplification of the test materials,and the genetic similarity coefficient among different families,genera,species,and origins were calculated.The cluster analysis was performed by unweighted pair group method using arithmetic average(UPGMA).Results:A total of ten MYB primers were screened out to identify Xinhui CRP from plants from different family(Panax ginseng and Morus alba),genus(Clausena lansium and Zanthoxylum schinifolium),and species(Citrus reticulata,C.sinensis and C.maxima).Furthermore,two from the ten primers,M1 and M10,were found to distinguish Xinhui CRP from other origins.There were 169,113,133 and 134 polymorphic bands in the identification of different families,genera,species,and origins respectively,and the accordingly polymorphism ration were 79.88%,76.87%,79.20%and 82.84%.Moreover,M1 was discovered to be the best primer to identify Xinhui CRP from other seven origins,the cluster analysis results based on the genetic similarity coefficients were consistent with the geographical distribution.Conclusion:This study established a novel molecular identification method according to MYB transcription factor,which can analyze the potential parental relationship of CRP germplasm,as well as identify the quality and origins of Xinhui CPR.展开更多
[Objectives]This study was conducted to realize the rapid and nondestructive identification of blueberry producing areas and protect benefits of high-quality blueberry brands.[Methods]Five types of blueberries from di...[Objectives]This study was conducted to realize the rapid and nondestructive identification of blueberry producing areas and protect benefits of high-quality blueberry brands.[Methods]Five types of blueberries from different regions were selected as experimental subjects,and spectral analysis techniques were combined with deep learning.Firstly,standard normal variable transform(SNV)and convolutional smoothing(SG)were used to deal with scattering noise and other issues in original spectral data.Secondly,due to a large amount of redundant information and high correlation between adjacent wavelengths in the collected spectra,continuous projection algorithm(SPA)and partial least squares regression(PLS)were combined for screening of features with RMSE as the indicator,and 40 feature variables were obtained.Finally,a convolutional network model CNN-SE integrating a Squeeze and Excitation(SE)attention mechanism module was constructed and compared with convolutional neural network(CNN),support vector machine(SVM),and BP neural network.[Results]The CNN-SE model had the best effect,with the accuracy and precision of the test set reaching 95%and 94.56%,respectively,and the recall and F 1 score reaching 93.94%and 94.24%,respectively.[Conclusions]The CNN-SE convolution network model can realize rapid,nondestructive and high-throughout identification of blueberry producing areas.展开更多
We estimated the proportion of hatchery and natural fall spawning chum salmon returning to the Amur River using chemical markers specific to hatchery-origin fry.We used otolith microchemistry technique to identify fis...We estimated the proportion of hatchery and natural fall spawning chum salmon returning to the Amur River using chemical markers specific to hatchery-origin fry.We used otolith microchemistry technique to identify fish with artificial origin among returning spawners.First,we found that juveniles of artificial origin had higher values of the Sr:Ca molar ratio of the otoliths’edge zone compared with juveniles of natural origin,what can be related to the use of rearing feed produced from raw materials of marine origin rich in strontium.Then we observed that most of the spawners from Anyuisky Hatchery and from the Amur River mouth at the start of the spawning migration has also the higher value of Sr:Ca molar ratio of the juvenile zone of otoliths.Also,adults with higher values of the Sr:Ca molar ratio are characterized by a skewed right in the peak of the age distribution.Both,the age structure and phenological shift in the time of spawning migration of individuals with higher value of the used chemical marker corresponds to results of studies on hatchery-produced chum salmon completed at different parts on Northern Pacific.The results of this study will be used in the management of Amur fall chum salmon fisheries,and also demonstrates the necessity of the development of specific measures for increasing the survival of juvenile anadromous salmonids released at large rivers and exposed to prolonged freshwater migration to the ocean.As a further application of the methodology,we plan to identify the markers specific to each of the hatcheries and main spawning tributaries belonging to Amur River catchments.This will be an important step in the evaluation of the contribution of different stocks in mixed fisheries and also in the estimation of the effect of hatchery releases on naturally spawning stocks of Amur fall chum.Following to,our results may indicate the applicability of this approach for the determination of artificial-origin fish in a mixed sample of the Amur fall chum salmon.展开更多
文摘[Objectives]This study was conducted to clarify the difference of millet from different producing areas in near-infrared spectroscopy(NIRS)modeling.[Methods]Millet samples from six different regions were collected for NIRS analysis,and an origin identification model based on BP neural network was established.The competitive adaptive reweighted sampling(CARS)algorithm was used to extract characteristic wavelength variables,and a CARS-BP model was established on this basis.Finally,the CARS-BP model was compared with support vector machine(SVM),partial least squares discriminant analysis(PLS)and KNN models.[Results]The characteristic wavelengths were extracted by CARS,and the number of variables was reduced from 1845 to 130.The discrimination accuracy of the CARS-BP model for the samples from six producing areas reached 98.1%,which was better than SVM,PSL and KNN models.[Conclusions]NIRS can quickly and accurately identify the origin of millet,providing a new method and way for the origin identification and quality evaluation of millet.
基金Supported by the“14th Five-Year Plan”Prospective and Basic Research Project of CNP)(2021DJ0502)Open Project of Key Laboratory of Shale Gas Resource Exploration(Chongqing Institute of Geology and Mineral Resources),Ministry of Natural Resources(KLSGE-2023)National Natural Science Foundation of China(42172149,U2244209)。
文摘Accurate identification of natural gas origin is fundamental to the theoretical research on natural gas geosciences and the exploration deployment and resource potential assessment of oil and gas.Since the 1970s,Academician Dai Jinxing has developed a comprehensive system for natural gas origin determination,grounded in geochemical theory and practice,and based on the integrated analysis of stable isotopic compositions,molecular composition,light hydrocarbon fingerprints,and geological context.This paper systematically reviews the core framework established by him and his team according to related references and application results,focusing on the conceptual design and technical pathways of key diagnostic diagrams such asδ^(13)C_(1)-C_(1)/(C_(2)+C_(3)),δ^(13)C_(1)-δ^(13)C_(2)-δ^(13)C_(3),δ^(13)CCO_(2)versus CO_(2)content,and the C7light hydrocarbon ternary plot.We evaluate the applicability and innovation of these tools in distinguishing between oil-type gas,coal-derived gas,microbial gas,and abiogenic gas,as well as in identifying mixed-source gases and multi-stage charging systems.The findings suggest that this identification system has significantly advanced natural gas geochemical interpretation in China,shifting from single-indicator analyses to multi-parameter integration and from qualitative assessments to systematic graphical identification,and has also exerted considerable influence on international research in natural gas geochemistry.The structured overview of the development trajectory of natural gas origin discrimination methodologies provides a technical support for natural gas geological theory and practice and offers a scientific foundation for the academic evaluation and application of related achievements.
基金supported by the Scientific Research Project Fund of Guangdong Provincial Administration of Traditional Chinese Medicine(No.20241220)the Open Research Project of State Key Laboratory of Dampness Syndrome of Chinese Medicine(No.SZ2022KF09)+6 种基金the Research Fund of Chinese Medicine Guangdong Laboratory(No.HQL2024PZ010,No.HQCML-C-2024005)the Research Fund of State Key Laboratory of Traditional Chinese Medicine Syndrome(No.QZ2023ZZ42)the Sanming Project of Medicine in Shenzhen,Guangdong Province,China(No.SZZYSM202111002)the Shenzhen Science and Technology Innovation Commission Shenzhen Basic Research Special Project(Natural Science Foundation)Basic Research Key Project(No.JCYJ20220818103402006)the Natural Science Foundation of Hubei Province,China(No.2024AFB502)Ph.D.Start-up Funding(No.BK202413)Medical Fund(No.2023YKY04)of Hubei University of Science and Technology。
文摘Objective:Citri Reticulatae Pericarpium(Chenpi,CRP)is one of the most used traditional Chinese medicines with great medicinal,dietary and collection values,among which the Citrus reticulata cv.'Chachi'(Citrus reticulata cv.Chachiensis)from Guangdong Xinhui is the geoherb of CRP.Xinhui CRP in the market was often counterfeited with other varieties or origins,molecular identification method can effectively distinguish different CRP varieties,but it's still a difficult problem to identify the same CRP variety from different origin.It is necessary to discover a new molecular marker to ensure the safe and effective application of Xinhui CRP.Methods:We selected one of the most studied transcription factor families in Citrus genus,MYB,to design the specific candidate primers on the conserved region.The primers with good band repeatability and high polymorphism were screened for PCR amplification of the test materials,and the genetic similarity coefficient among different families,genera,species,and origins were calculated.The cluster analysis was performed by unweighted pair group method using arithmetic average(UPGMA).Results:A total of ten MYB primers were screened out to identify Xinhui CRP from plants from different family(Panax ginseng and Morus alba),genus(Clausena lansium and Zanthoxylum schinifolium),and species(Citrus reticulata,C.sinensis and C.maxima).Furthermore,two from the ten primers,M1 and M10,were found to distinguish Xinhui CRP from other origins.There were 169,113,133 and 134 polymorphic bands in the identification of different families,genera,species,and origins respectively,and the accordingly polymorphism ration were 79.88%,76.87%,79.20%and 82.84%.Moreover,M1 was discovered to be the best primer to identify Xinhui CRP from other seven origins,the cluster analysis results based on the genetic similarity coefficients were consistent with the geographical distribution.Conclusion:This study established a novel molecular identification method according to MYB transcription factor,which can analyze the potential parental relationship of CRP germplasm,as well as identify the quality and origins of Xinhui CPR.
基金Supported by Natural Science Foundation of Heilongjiang Province(LH2022E099)Daqing Guidance Fund for Science and Technology Planning Project(zd-2023-63)San Heng San Zong Support Program of Heilongjiang Bayi Agricultural University(ZRCPY202216).
文摘[Objectives]This study was conducted to realize the rapid and nondestructive identification of blueberry producing areas and protect benefits of high-quality blueberry brands.[Methods]Five types of blueberries from different regions were selected as experimental subjects,and spectral analysis techniques were combined with deep learning.Firstly,standard normal variable transform(SNV)and convolutional smoothing(SG)were used to deal with scattering noise and other issues in original spectral data.Secondly,due to a large amount of redundant information and high correlation between adjacent wavelengths in the collected spectra,continuous projection algorithm(SPA)and partial least squares regression(PLS)were combined for screening of features with RMSE as the indicator,and 40 feature variables were obtained.Finally,a convolutional network model CNN-SE integrating a Squeeze and Excitation(SE)attention mechanism module was constructed and compared with convolutional neural network(CNN),support vector machine(SVM),and BP neural network.[Results]The CNN-SE model had the best effect,with the accuracy and precision of the test set reaching 95%and 94.56%,respectively,and the recall and F 1 score reaching 93.94%and 94.24%,respectively.[Conclusions]The CNN-SE convolution network model can realize rapid,nondestructive and high-throughout identification of blueberry producing areas.
基金support of the grant of the Ministry of Science and Higher Education of the Russian Federation project No.2019-0858"Biogeochemical and geochemical studies of landscapes in the conditions of the development of mineral deposits,the search for new methods of monitoring and forecasting the State of the environment".
文摘We estimated the proportion of hatchery and natural fall spawning chum salmon returning to the Amur River using chemical markers specific to hatchery-origin fry.We used otolith microchemistry technique to identify fish with artificial origin among returning spawners.First,we found that juveniles of artificial origin had higher values of the Sr:Ca molar ratio of the otoliths’edge zone compared with juveniles of natural origin,what can be related to the use of rearing feed produced from raw materials of marine origin rich in strontium.Then we observed that most of the spawners from Anyuisky Hatchery and from the Amur River mouth at the start of the spawning migration has also the higher value of Sr:Ca molar ratio of the juvenile zone of otoliths.Also,adults with higher values of the Sr:Ca molar ratio are characterized by a skewed right in the peak of the age distribution.Both,the age structure and phenological shift in the time of spawning migration of individuals with higher value of the used chemical marker corresponds to results of studies on hatchery-produced chum salmon completed at different parts on Northern Pacific.The results of this study will be used in the management of Amur fall chum salmon fisheries,and also demonstrates the necessity of the development of specific measures for increasing the survival of juvenile anadromous salmonids released at large rivers and exposed to prolonged freshwater migration to the ocean.As a further application of the methodology,we plan to identify the markers specific to each of the hatcheries and main spawning tributaries belonging to Amur River catchments.This will be an important step in the evaluation of the contribution of different stocks in mixed fisheries and also in the estimation of the effect of hatchery releases on naturally spawning stocks of Amur fall chum.Following to,our results may indicate the applicability of this approach for the determination of artificial-origin fish in a mixed sample of the Amur fall chum salmon.
