Analyzing architectural diversity in maize plants using the skeleton-image-based method
Shoot architecture in maize is critical since it determines resource use, impacts wind and rain damage tolerance, and affects yield stability. Quantifying the diversity among inbred lines in heterosis breeding is essential, especially when describing germplasm resources. However, traditional geometr...
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Published in | Journal of Integrative Agriculture Vol. 22; no. 12; pp. 3804 - 3809 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.12.2023
College of Biological Sciences,China Agricultural University,Beijing 100193,P.R.China Center for Crop Functional Genomics and Molecular Breeding,China Agricultural University,Beijing 100193,P.R.China%Department of Biology,Northeastern Illinois University,Chicago 60625,USA Frontier Technology Research Institute of China Agricultural University in Shenzhen,Shenzhen 518000,P.R.China KeAi Communications Co., Ltd |
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Abstract | Shoot architecture in maize is critical since it determines resource use, impacts wind and rain damage tolerance, and affects yield stability. Quantifying the diversity among inbred lines in heterosis breeding is essential, especially when describing germplasm resources. However, traditional geometric description methods oversimplify shoot architecture and ignore the plant’s overall architecture, making it difficult to reflect and illustrate diversity. This study presents a new method to describe maize shoot architecture and quantifies its diversity by combining computer vision algorithms and persistent homology. Our results reveal that persistent homology can capture key characteristics of shoot architecture in maize and other details often overlooked by traditional geometric analysis. Based on this method, the morphological diversity of shoot architecture can be mined (quantified), and the main shoot architecture types can be obtained. Consequently, this method can easily describe the diversity of shoot architecture in many maize materials. |
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AbstractList | Shoot architecture in maize is critical since it determines resource use, impacts wind and rain damage tolerance, and affects yield stability. Quantifying the diversity among inbred lines in heterosis breeding is essential, especially when describing germplasm resources. However, traditional geometric description methods oversimplify shoot architecture and ignore the plant’s overall architecture, making it difficult to reflect and illustrate diversity. This study presents a new method to describe maize shoot architecture and quantifies its diversity by combining computer vision algorithms and persistent homology. Our results reveal that persistent homology can capture key characteristics of shoot architecture in maize and other details often overlooked by traditional geometric analysis. Based on this method, the morphological diversity of shoot architecture can be mined (quantified), and the main shoot architecture types can be obtained. Consequently, this method can easily describe the diversity of shoot architecture in many maize materials. |
Author | LIU, Min-guo CAMPBELL, Thomas LI, Wei WANG, Xi-qing |
AuthorAffiliation | College of Biological Sciences,China Agricultural University,Beijing 100193,P.R.China;Frontier Technology Research Institute of China Agricultural University in Shenzhen,Shenzhen 518000,P.R.China;Center for Crop Functional Genomics and Molecular Breeding,China Agricultural University,Beijing 100193,P.R.China%Department of Biology,Northeastern Illinois University,Chicago 60625,USA |
AuthorAffiliation_xml | – name: College of Biological Sciences,China Agricultural University,Beijing 100193,P.R.China;Frontier Technology Research Institute of China Agricultural University in Shenzhen,Shenzhen 518000,P.R.China;Center for Crop Functional Genomics and Molecular Breeding,China Agricultural University,Beijing 100193,P.R.China%Department of Biology,Northeastern Illinois University,Chicago 60625,USA |
Author_xml | – sequence: 1 givenname: Min-guo surname: LIU fullname: LIU, Min-guo email: liumg@cau.edu.cn organization: College of Biological Sciences, China Agricultural University, Beijing 100193, P.R.China – sequence: 2 givenname: Thomas surname: CAMPBELL fullname: CAMPBELL, Thomas organization: Department of Biology, Northeastern Illinois University, Chicago 60625, USA – sequence: 3 givenname: Wei surname: LI fullname: LI, Wei organization: College of Biological Sciences, China Agricultural University, Beijing 100193, P.R.China – sequence: 4 givenname: Xi-qing surname: WANG fullname: WANG, Xi-qing email: wangxq21@cau.edu.cn organization: College of Biological Sciences, China Agricultural University, Beijing 100193, P.R.China |
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Cites_doi | 10.1104/pp.16.01516 10.1111/1467-9868.00293 10.1007/s00122-010-1320-y 10.1093/jxb/erz394 10.2134/agronj2003.1465 10.4238/2013.April.17.3 10.12688/f1000research.13541.1 10.3732/ajb.1700046 10.1126/science.aax5482 10.1016/S2095-3119(17)61785-4 10.2135/cropsci1971.0011183X001100040006x 10.2135/cropsci1978.0011183X001800030037x 10.1016/j.eswa.2008.01.039 10.3390/genes10090664 10.1016/j.pbi.2006.01.013 10.1007/s11032-010-9500-7 10.1038/hdy.2016.88 10.3389/fpls.2021.614926 10.3126/jnarc.v2i0.16119 10.7717/peerj.4088 10.1016/j.jia.2022.08.006 10.1105/tpc.16.00477 10.1186/s12870-022-03470-7 |
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Keywords | maize shoot architecture phenotyping technology morphological diversity persistent homology |
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SubjectTerms | agriculture computer vision corn germplasm heterosis maize morphological diversity persistent homology phenotyping technology rain damage shoot architecture wind |
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Title | Analyzing architectural diversity in maize plants using the skeleton-image-based method |
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