Morphological variation among the four<i>Megalobrama</i>species inferred by X‐ray photography

Chen, Jing; Guo, Jing; Wang, Zhiqiang; Wang, Weimin

doi:10.1111/are.14743

Cited by 9 publications

(7 citation statements)

References 22 publications

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“…In the detection of agricultural products, Zou, Sun, and Zhang (2015) performed quick detection of the volume and mass of watermelons using X‐rays. J. Chen, Guo, and Wang (2020) used X‐ray technology for morphological studies of fish. The results showed that X‐ray photography was a suitable method for nondestructive and accurate detection of morphological parameters in the genus Megalobrama.…”

Section: Introductionmentioning

confidence: 99%

Mass detection of walnut based on X‐ray imaging technology

Gao

Zhang

Sun

et al. 2022

J Food Process Engineering

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In view of the problem of low accuracy in walnut mass detection caused by relatively inconstant density, this study suggested the integration of X‐ray imaging technology and image processing technology with machine learning for walnut mass detection. Using image processing technology to remove the background of walnut X‐ray image and to segment the kernels, the mass prediction models could be constructed after extracting the shape and texture of walnut characteristic parameters and the kernel shape characteristic parameters. The results revealed that when mass prediction models were built based on walnut shape characteristic parameters or constructed with the application of texture characteristic parameters, the determination coefficient (R2) were rather low, even the residual predictive deviation (RPD) less than 1.4, proving that these models were not reliable. However, when mass prediction models were built based on walnut and kernel shape characteristic parameters, the R2 for both partial least squares (PLS) and radial basis function (RBF) models were higher than 0.84. And the RPD values were 1.8133 and 1.7474, respectively. On this basis, when competitive adaptive reweighed sampling (CARS) optimized parameters were adopted, the R2 for both PLS and RBF models were higher than 0.86 and the RPD were 1.8759 and 1.8850, respectively. The result proved that the application of walnut and kernel shape characteristics can improve the accuracy of model prediction. Therefore, using X‐ray imaging technology to detect walnut mass was feasible, which could realized the prompt, accurate and nondestructive detection of walnut mass. This technology provided a novel thought for the accurate grading of walnuts. Practical Applications At present, there is a problem of similar size but large mass difference after walnut size classification, which directly affects the commodity value of walnuts. It is necessary to combine multiple characteristics to select and classify walnuts. Mass is an important grading index. With the development of machine vision technology, online detection of fruit mass has been realized. However, due to the relatively inconstant density of walnuts and the limitation of the technology, the machine vision technique cannot obtain internal information. This study used X‐ray transmission to obtain the internal information of walnuts without destroying the walnuts. At the same time, the mass detection models were established by combining the internal and external characteristics of the walnuts to achieve fast, accurate, and nondestructive testing of walnut mass. Automatic mass detection provides technical support for intelligent grading, which has important production significance and economic value for the development of the walnut industry.

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Section: Introductionmentioning

confidence: 99%

Mass detection of walnut based on X‐ray imaging technology

Gao

Zhang

Sun

et al. 2022

J Food Process Engineering

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“…For instance, M . amblycephala is distinguished by the morphology of the upper orbital bone and oral fissure, and also the caudal peduncle depth/length ratio [ 2 ]. It is mainly distributed in large- and medium-sized lakes in the middle and lower branches of the Yangtze River [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…It is mainly distributed in large- and medium-sized lakes in the middle and lower branches of the Yangtze River [ 3 ]. M. skolkovii differs from the other three species in the longer length of the first swim bladder [ 2 ]. It inhabits the Amur, Yangtze, Yellow, and Minjiang rivers [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…Megalobrama germplasm resources have been rapidly depleting in recent years as a result of many factors, including environmental degradation factors. There are a few reports on Megalobrama genetic resource conservation and population genetics [ 1 , 2 , 4 ]. By using population genomics, the genetic information of species diversity can be established with the advent of high-throughput sequencing [ 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

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Population Genomics of Megalobrama Provides Insights into Evolutionary History and Dietary Adaptation

Chen

Liu

Gooneratne

et al. 2022

Biology

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Megalobrama, a genus of cyprinid fish, is an economically important freshwater fish widely distributed in major waters of China. Here, we report the genome resequencing of 180 Megalobrama fish including M. amblycephala, M. skolkovii, M. hoffmanni, and M. pellegrini. Population structure indicated that geographically divergent Megalobrama populations were separated into six subgroups. A phylogenetic tree showed that M. skolkovii was more closely related to M. pellegrini than other species and M. hoffmanni was clustered apart from other Megalobrama species, showing a high nucleotide diversity in geographic groups. Treemix validated gene flow from M. amblycephala to M. skolkovii, suggesting that introgression may provide an important source of genetic variation in the M. skolkovii populations. According to the demographic history analysis, it is speculated that Megalobrama might have been originally distributed in the Pearl River with some spread to Hainan Island and northern China due to lower sea levels during the glacial period. Whole-genome selective sweeps analysis demonstrated that M. amblycephala likely developed an enhanced energy metabolism mostly through fatty acid degradation pathways whereas M. hoffmanni possibly regulate lipid absorption via the cholesterol metabolism pathway. Taken together, this study provides a valuable genomic resource for future genetic investigations aiming to improve genome-assisted breeding of Megalobrama species.

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“…Previous studies categorized the four species mainly based on morphologic traits and geographic distribution. For instance, M. amblycephala is distinguished by the morphology of the upper orbital bone and oral fissure, and also the caudal peduncle depth/length ratio [2]. It is mainly distributed in large-and medium-sized lakes in the middle and lower branches of the Yangtze River [3].…”

Section: Introductionmentioning

confidence: 99%

Population genomics of Megalobrama provides insights into evolutionary history and dietary adaptation

Chen

Liu

Gooneratne

et al. 2022

Preprint

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Megalobrama, a genus of cyprinid fish, is an important freshwater economic fish widely distributed in major waters of China. Here, we report the genome resequencing of 180 Megalobrama fish including M. amblycephala, M. skolkovii, M. hoffmanni and M. pellegrini. The results indicated that different geographical Megalobrama populations were separated into six subgroups and M. skolkovii was more closely related to M. pellegrini than other species. Megalobrama was originally distributed in the Pearl River, some spread to Hainan Island due to sea-level fall during the glacial period and others spread to northern China. The introgression provided an important genetic variation source of M. skolkovii populations. M. amblycephala enhanced energy metabolism mainly through fatty acid degradation pathways, while M. skolkovii used cholesterol metabolism pathway to regulate lipid absorption. Taken together, our results provide a valuable genomic resource for future genetic studies to improve genome-assisted breeding of Megalobrama species.

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Morphological variation among the fourMegalobramaspecies inferred by X‐ray photography

Cited by 9 publications

References 22 publications

Mass detection of walnut based on X‐ray imaging technology

Mass detection of walnut based on X‐ray imaging technology

Population Genomics of Megalobrama Provides Insights into Evolutionary History and Dietary Adaptation

Population genomics of Megalobrama provides insights into evolutionary history and dietary adaptation

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