Identification of chestnut varieties based on digital analysis of nut morphology

Li Tongtong; Guo Sujuan; Li Yanhua; Jiang Xibing

doi:10.12171/j.1000-1522.20220284

Journal of Beijing Forestry University > 2023 > 45(11): 78-89. > DOI: 10.12171/j.1000-1522.20220284

Li Tongtong, Guo Sujuan, Li Yanhua, Jiang Xibing. Identification of chestnut varieties based on digital analysis of nut morphology[J]. Journal of Beijing Forestry University, 2023, 45(11): 78-89. DOI: 10.12171/j.1000-1522.20220284

Citation:

PDF (8545 KB)

Identification of chestnut varieties based on digital analysis of nut morphology

1.
State Key Laboratory of Efficient Production of Forest Resources, Beijing Forestry University, Beijing 100083, China
2.
Forestry and Grassland Bureau, Yuxi 51100, Yunnan, China
3.
Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, Zhejiang, China

More Information

Received Date: July 12, 2022
Revised Date: October 20, 2022
Accepted Date: October 01, 2023
Available Online: November 20, 2023

Graphical Abstract

Abstract

Abstract

Objective
In order to solve the problem of variety confusion and low utilization rate in Chinese chestnut, geometric morphometry was used to digitally analyze the nut morphology of different Chinese chestnut varieties, and the variety identification method was established.
Method
A total of 3200 nuts of 80 varieties from different chestnut producing areas in China were used as test materials, and the plane, side and bottom components were photographed with unified parameters. Using Image J software combined with the morphological characteristics of chestnut nuts, 17, 12, and 16 identification marks were selected in different components in a specific order so as to obtain nut morphological coordinate data. Morpho J software was used to perform generalized procruste analysis on the data to eliminate the interference of non-morphological factors such as size and location, and to classify the data by variety. Performing relative warp analysis based on principal components on the data was to obtain the contribution rates of identification marks in different components, so as to extract important identification marks and visualize the morphological differences of nuts. Canonical variate and discriminant analysis were used to illustrate the identification effect of identification marks on different chestnut varieties.
Result
(1) Relative distortion analysis showed that the cumulative contribution rate of the top 25 identification points was 87.7%, which had a greater identification effect and was an important identification marks. (2) Principal component analysis showed that the morphological differences of nuts were mainly reflected in the top and shoulder, the plane contour shape of nuts, the thickness of nuts, and the relative size of the hilum. (3) The analysis of typical variables showed that most varieties had overlap and low differentiation when different components were identified separately. When 34 identification points were used for comprehensive identification, there were significant differences among different varieties, and the identification effect was obvious. When 25 important identification marks were used, the effect was similar to that of the former. (4) The discriminant analysis of 80 varieties for different components showed that the accuracy of plane, side and bottom components were 72.5%−100.0%, 71.8%−100.0%, 70.0%−100.0%, respectively. Comprehensively discriminated with 45 identification marks, the correct rates were 95.0%−100.0%. 33 important identification marks were used for identification, and the correct rate was 92.5%−100.0%. The latter two had a higher identification rate and could realize the identification of 80 chestnut varieties.
Conclusion
The geometric morphometric analysis based on 25 identification marks could achieve accurate identification of different chestnut varieties, with a correct discrimination rate of 92.5%−100.0%. In this study, a method for chestnut variety identification based on digital analysis of nut morphology is established, which will provide a new basis for the correct application of varieties in production practice.
- Castanea mollissima,
- nut morphology,
- geometric morphology,
- variety identification; digital analysis

FullText(HTML)

References (44)

References

[1]	Leishman M R, Jurado W E. Correlates of seed size variation: a comparison among five temperate floras[J]. Journal of Ecology, 1995, 83(3): 517−529. doi: 10.2307/2261604
[2]	吴晓春, 罗传文, 田兴军. 卫矛科植物种子表皮细胞几何形态在数值分类上的应用[J]. 林业科技, 1991, 16(1): 12−14. Wu X C, Luo C W, Tian X J. Numerical classification of geometric shapes of seed epidermal cells of Euonymus[J]. Forestry Science & Technology, 1991, 16(1): 12−14.
[3]	马骥, 李新荣, 张景光, 等. 我国种子微形态结构研究进展[J]. 浙江师范大学学报(自然科学版), 2005, 28(2): 121−127. Ma J, Li X R, Zhang J G, et al. Progress in research on microstructure features of seeds (Dom estic Part)[J]. Journal of Zhejiang Normal University (Natural Sciences), 2005, 28(2): 121−127.
[4]	周连第. 板栗种质资源遗传多样性研究[D]. 北京: 中国农业大学, 2005. Zhou L D. Study on genetic diversity of germplasm resources of chestnut[D]. Beijing: China Agriculture University, 2005.
[5]	刘亚斌, 郭素娟, 孙传昊. 基于巢式分组设计的板栗刺苞与坚果形态多样性分析[J]. 中南林业科技大学学报, 2020, 40(10): 51−60. Liu Y B, Guo S J, Sun C H. Morphological diversity analysis of chestnut thorns bract and nuts based on nested grouping design[J]. Journal of Central South University of Forestry & Technology, 2020, 40(10): 51−60.
[6]	Stojanovic M, Magazin N. Variability of sweet chestnut ( Castanea sativa Mill.) in montenegro according to morphological traits of fruits and upov descriptors[J]. Genetika-Belgrade, 2020, 52(2): 571−548. doi: 10.2298/GENSR2002571S
[7]	韩彪, 张萍, 郭素娟, 等. 失水对板栗种子超微结构与生理变化及萌发的影响[J]. 基因组学与应用生物学, 2021, 40(增刊2): 2785−2792. Han B, Zhang P, Guo S J, et al. Effects of waters loss on ultrastructure and physiological changes and germination of Castanea mollissima seeds[J]. Genomics and Applied Biology, 2021, 40(Suppl. 2): 2785−2792.
[8]	许学, 马卉, 王钰, 等. 基于多光谱成像技术的小麦品种快速无损鉴定[J]. 中国农学通报, 2019, 35(15): 14−19. Xu X, Ma H, Wang Y, et al. Rapid and nondestructive identification of wheat varieties with multispectral imaging technology[J]. Chinese Agricultural Science Bulletin, 2019, 35(15): 14−19.
[9]	黄志伟, 郭拓, 黄文静, 等. 近红外光谱技术在名贵中药材质量评价中的研究进展[J]. 中草药, 2022, 53(20): 6328−6336. Huang Z W, Guo T, Huang W J, et al. Research progress of near-infrared spectroscopy in quality evaluation of valuable Chinese medicinal materials[J]. Chinese Traditional and Herbal Drugs, 2022, 53(20): 6328−6336.
[10]	杨雨图, 熊杰, 司万, 等. 基于可见/近红外光谱技术的板栗产地识别[J]. 中国农机化学报, 2021, 42(12): 189−194, 203. Yang Y T, Xiong J, Si W, et al. Detection of chestnut production place based on visible and near-infrared spectroscopy[J]. Journal of Chinese Agricultural Mechanization, 2021, 42(12): 189−194, 203.
[11]	曾卫东. 基于形态、分子和生态数据的星果草属物种界定研究[D]. 南昌: 江西农业大学, 2019. Zeng W D. Species delimitation of Asteropyrum Drumm. et Hutch. (Rannuculaceae) based on morphological, molecular and ecological variation[D]. Nanchang: Jiangxi Agriculture University, 2019.
[12]	白晓倩, 陈于, 张仕杰, 等. 基于表型性状和SSR标记的板栗品种遗传多样性分析及分子身份证构建[J]. 植物遗传资源学报, 2022, 23(4): 972−984. Bai X Q, Chen Y, Zhang S J, et al. Genetic diversity analysis and fingerprinting of chestnut varieties based on phenotypic traits and SSR markers[J]. Journal of Plant Genetic Resources, 2022, 23(4): 972−984.
[13]	张宇和, 柳鎏, 梁维坚, 等. 中国果树志: 板栗榛子卷[M]. 北京: 中国林业出版社, 2005. Zhang Y H. Liu L, Liang W J, et al. Chinese fruit trees: chestnut hazelnut roll[M]. Beijing: China Forestry Publishing House, 2005.
[14]	Li X P, Jiang H Z, Jiang X S, et al. Identification of geographical origin of Chinese chestnuts using hyperspectral imaging with 1D-CNN algorithm[J]. Agriculture, 2021, 11(12): 2575.
[15]	聂兴华, 郑瑞杰, 赵永廉, 等. 利用荧光SSR分子标记评估中国栗属植物遗传多样性[J]. 中国农业科学, 2021, 54(8): 1739−1753. Nie X H, Zheng R J, Zhao Y L, et al. Genetic diversity evaluation of Castanea in China based on fluorescently labeled SSR[J]. Scientia Agricultura Sinica, 2021, 54(8): 1739−1753.
[16]	闫宝荣, 花保祯. 几何形态测量学及其在昆虫分类学和系统发育中的应用[J]. 昆虫分类学报, 2010, 32(4): 313−320. Yan B R, Hua B Z. Geometric morphometrics and its application in the systematics and phylogenetics of insects[J]. Entomotaxonomia, 2010, 32(4): 313−320.
[17]	邱立飞, 魏朝明, 王俊杰, 等. 基于几何形态学方法的秦巴山区中华蜜蜂翅形态变异研究[J]. 应用昆虫学报, 2018, 55(3): 503−513. Qiu L F, Wei Z M, Wang J J, et al. Geometric analysis of morphological variation in the wing of Apis cerana from the Qinling-Daba Mountain areas[J]. Chinese Journal of Applied Entomology, 2018, 55(3): 503−513.
[18]	Chaiphongpachara T, Sriwichai P, Samung Y, et al. Geometric morphometrics approach towards discrimination of three member species of Maculatus group in Thailand[J]. Acta Tropica, 2019(192): 66−74.
[19]	Martín-Gómez J J, Rewicz A, Rodríguez-Lorenzo J L, et al. Seed morphology in Silene based on geometric models[J]. Plants (Basel, Switzerland), 2020, 9(12): 1787.
[20]	Márquez F, Lozada M, Idaszkin Y L, et al. Cannabis varieties can be distinguished by achene shape using geometric morphometrics[J]. Cannabis and Cannabinoid Research, 2021, 7(4): 1−6.
[21]	Binashikhbubkr K, Malik A A, Al-Misned F, et al. Geometric morphometric discrimination between seven populations of Kawakawa Euthynnus affinis (Cantor, 1849) from Peninsular Malaysia[J]. Journal of King Saud University-Science, 2022, 34(3): 1−8.
[22]	马智. 翅脉特征在3种毒蛾形态差异鉴定中的可行性研究[D]. 北京: 北京林业大学, 2019. Ma Z. Feasibility of identification of 3 lymantriid moths based on morphological characteristics of wing veins[D]. Beijing: Beijing Forestry University, 2019.
[23]	Song Y G, Deng M, Hipp A L, et al. Leaf morphological evidence of natural hybridization between two oak species ( Quercus austrocochinchinensis and Q. kerrii) and its implications for conservation management[J]. European Journal of Forest Research, 2015, 134(1): 139−151. doi: 10.1007/s10342-014-0839-x
[24]	Reyment R A, Bookstein F L. Morphometric tools for landmark data: geometry and biology[J]. Biometrics, 1992, 48(4): 1301. doi: 10.2307/2532725
[25]	刘庆忠. 板栗种质资源描述规范和数据标准[M]. 北京: 中国农业出版社, 2006. Liu Q Z. Description specification and data standard of chestnut germplasm resources[M]. Beijing: China Agricultural Press, 2006.
[26]	Klingenberg C P. Evolution and development of shape: integrating quantitative approaches[J]. Nature Reviews Genetics, 2010, 11(7): 623−635.
[27]	王长海, 张晓艳, 李金花. 小叶杨与欧洲黑杨杂交子代苗期叶形变异分析[J]. 林业科学研究, 2020, 33(3): 132−138. doi: 10.13275/j.cnki.lykxyj.2020.03.017 Wang C H, Zhang X Y, Li J H. Variation analysis of seedling stage characters of hybrid progeny of Populus simonii × P. nigra[J]. Forest Research, 2020, 33(3): 132−138. doi: 10.13275/j.cnki.lykxyj.2020.03.017
[28]	于秀林, 任雪松. 多元统计分析[M]. 北京: 中国统计出版社, 1999. Yu X L, Ren X S. Multivariate statistical analysis[M]. Beijing: China Statistics Press, 1999.
[29]	高捍东, 黄宝龙. 板栗主要栽培品种的分子鉴别[J]. 林业科学, 2001, 37(1): 64−71. doi: 10.3321/j.issn:1001-7488.2001.01.010 Gao H D, Huang B L. Genetic analysis and indentification of main cultivated varities of chestnut ( Castanea mollissima) by PARD molecular markers[J]. Scientia Silvae Sinicae, 2001, 37(1): 64−71. doi: 10.3321/j.issn:1001-7488.2001.01.010
[30]	丁健美, 刘之熙. 杂交水稻品种鉴定方法(综述)[J]. 南方农业, 2022, 16(13): 139−143. Ding J M, Liu Z X. Identification methods of hybrid rice variety (review)[J]. South China Agriculture, 2022, 16(13): 139−143.
[31]	刘国彬, 曹均, 兰彦平, 等. 板栗总苞与坚果表型多样性及其相关关系研究[J]. 经济林研究, 2014, 32(2): 28−33. Liu G B, Cao J, Lan Y P, et al. Phenotypic diversity of involucres and nut in Castanea mollissima and their relationship[J]. Non-wood Forest Research, 2014, 32(2): 28−33.
[32]	田雪邻, 史彦江, 宋锋惠, 等. 新疆不同立地环境下平欧杂种榛坚果品质比较[J]. 食品工业科技, 2017, 38(15): 45−49, 54. Tian X L, Shi Y J, Song F H, et al. Comparitive on the quality of Corylus heterophylla × Corylus avellana nut under different sites conditions in Xinjiang[J]. Science and Technology of Food Industry, 2017, 38(15): 45−49, 54.
[33]	黄瑞敏, 潘刚, 周晔, 等. 西藏核桃引种到内地后坚果品质变化研究[J]. 中国油脂, 2019, 44(5): 144−148. Huang R M, Pan G, Zhou Y, et al. Nut quality changes of Tibetan walnuts after introduced to inland China[J]. China Oils and Fats, 2019, 44(5): 144−148.
[34]	俞文君. 新疆核桃种质资源果实表型多样性及其与土壤、气象因子的关系研究[D]. 阿拉尔: 塔里木大学, 2020. Yu W J. Diversity and fruit phenotypes of walnut germplasm resources in Xinjiang study on the relationship with soil and meteorological factors[D]. Alar: Tarim University, 2020.
[35]	陆相宜, 边迅, 邓维安. 几何形态测量学及其在直翅目研究中的应用[J]. 广西师范大学学报(自然科学版), 2022, 40 (5): 342−353. Lu X Y, Bian X, Deng W A. Geometric morphometrics and its application in Orthoptera[J]. Journal of Guangxi Normal University (Natural Science Edition), 2022,40 (5): 342−353.
[36]	蔡小娜, 黄大庄, 沈佐锐, 等. 用于昆虫分类鉴定的几何形态计量学方法研究: 相对扭曲分析[J]. 生物数学学报, 2016, 31(2): 254−262. Cai X N, Huang D Z, Shen Z R, et al. A study of geometric morphometric methods for taxonomic identification of insects: relative warp analysis[J]. Journal of Biomathematics, 2016, 31(2): 254−262.
[37]	车星锦, 郭艺, 刀微, 等. 澜沧江多鳞荷马条鳅种群间形态差异的比较[J]. 水生态学杂志, 2021, 42(2): 64−71. Che X J, Guo Y, Dao W, et al. Morphological comparison of Homatula pycnolepis (Teleostei: Nemacheilidae) among different geographic populations of Lancang River, China[J]. Journal of Hydroecology, 2021, 42(2): 64−71.
[38]	赖俊声, 江锡兵, 龚榜初, 等. 板栗地方品种质量性状多样性分析[J]. 浙江农业科学, 2016, 57(8): 1196−1200. Lai J S, Jiang X B, Gong B C, et al. Diversity analysis of quality traits of chestnut landraces[J]. Journal of Zhejiang Agricultural Sciences, 2016, 57(8): 1196−1200.
[39]	曹杰. 燕山板栗种质资源表型性状研究与评价[D]. 秦皇岛: 河北科技师范学院, 2013. Cao J. Reaearch and evaluation on phenotypic traits of Yanshan chestnut germplasm resources[D]. Qinhuangdao: Hebei Normal University of Science & Technology, 2013.
[40]	苏筱雨. 基于数字化形态特征的金龟子分类识别研究[D]. 保定: 河北农业大学, 2017. Su X Y. Classification and recognition on Scaraeoidea based on digital morphological characteristics[D]. Baoding: Hebei Agriculture University, 2017.
[41]	Daly H V. Insect morphometrics[J]. Annual Review of Entomology, 1985, 30(1): 415−438. doi: 10.1146/annurev.en.30.010185.002215
[42]	姜晓东, 成永旭, 潘建林, 等. 基于地标点几何形态测量法区分不同水系野生中华绒螯蟹[J]. 中国水产科学, 2019, 26(6): 1116−1125. Jiang X D, Cheng Y X, Pan J L, et al. Landmark-based morphometric identification of wild Eriocheir sinensis with geographically different origins[J]. Journal of Fishery Sciences of China, 2019, 26(6): 1116−1125.
[43]	Proietti E, Filesi L, Marzio P D, et al. Morphology, geometric morphometrics, and taxonomy in relict deciduous oaks woods in northern Italy[J]. Rendiconti Lincei. Scienze Fisiche e Naturali, 2021(3): 549−564.
[44]	陈相洁, 毛礼米, 潘昱安, 等. 部分十字花科植物花粉形态特征比较[J]. 植物资源与环境学报, 2022, 31(1): 13−20. doi: 10.3969/j.issn.1674-7895.2022.01.03 Chen X J, Mao L M, Pan Y A, et al. Comparision on pollen morphological characteristics of some species of Brassicaceae[J]. Journal of Plant Resources and Environment, 2022, 31(1): 13−20. doi: 10.3969/j.issn.1674-7895.2022.01.03

[1]	Wei Yunqi, Wang Yang, Yin Hao. A low-density tree digital twin model for refined urban greening management: a case study of tree wind disaster risk management[J]. Journal of Beijing Forestry University, 2025, 47(3): 139-150. DOI: 10.12171/j.1000-1522.20240400
[2]	Guo Jian, Qiao Hongyong, Yuan Tao, Wang Shubiao, Mou Ningning, Jia Jianfei, Xi Fan, Xia Wei. Tree safety risk assessment in urban parks: taking Beijing Zoo as an example[J]. Journal of Beijing Forestry University, 2025, 47(3): 128-138. DOI: 10.12171/j.1000-1522.20210200
[3]	Li Weiwei, Yang Xueqing, Zhang Yiming, Feng Xin, Wang Bo, Du Jianhua, Chen Feng, Liu Xiaodong. Hazard assessment of forest fire in Miyun District of Beijing based on the subcompartment scale[J]. Journal of Beijing Forestry University, 2024, 46(2): 75-86. DOI: 10.12171/j.1000-1522.20230227
[4]	Zong Xuezheng, Tian Xiaorui, Ma Shuai, Liu Chang. Quantitative assessment for forest fire risk based on fire simulation: taking the Subtropical Forest Experimental Center of Chinese Academy of Forestry as an example[J]. Journal of Beijing Forestry University, 2022, 44(9): 83-90. DOI: 10.12171/j.1000-1522.20210328
[5]	ZHANG Qiang, MA Chao, YANG Hai-long, WANG Zhi-gang, TU Jian.. Characteristics of low frequency debris flow and risk analysis in Beijing mountainous region.[J]. Journal of Beijing Forestry University, 2015, 37(12): 92-99. DOI: 10.13332/j.1000-1522.20150177
[6]	GONG Jun-jie, YANG Hua, DENG Hua-feng. Assessment of ecological risks of landscape along the Ming Great Wall in Beijing[J]. Journal of Beijing Forestry University, 2015, 37(8): 60-68. DOI: 10.13332/j.1000-1522.20140303
[7]	LI Dan, DAI Wei, YAN Zhi-gang, WANG Ni-hong. Habitat evaluation system of larch plantation based on fuzzy analytic hierarchy[J]. Journal of Beijing Forestry University, 2014, 36(4): 75-81. DOI: 10.13332/j.cnki.jbfu.2014.04.015
[8]	ZHENG Ran, YUE Ye, WANG Xiao-hui, WEN Zhi-yong, GUAN Wen-bin. Method of risk assessment and management for ancient trees[J]. Journal of Beijing Forestry University, 2013, 35(6): 144-150.
[9]	XIAO Hua-shun, ZHANG Gui, LIU Da-peng, CAI Xue-li. Selecting forest fire spreading models based on the Fuzzy Data Mining technique[J]. Journal of Beijing Forestry University, 2006, 28(6): 93-97.
[10]	LIU Hai-jun, LUO You-qing, WEN Jun-bao, ZHANG Zhi-ming, FENG Ji-hua, TAO Wan-qiang. Pest risk assessment of Dendroctonus valens,Hyphantria cunea and Apriona swainsoni swainsoni in Beijing area[J]. Journal of Beijing Forestry University, 2005, 27(2): 81-87.

Cited By

Cited by

Periodical cited type(3)

1.	管奥，毋玉婷，陈宇，孙扬，祁鹏志，郭宝英. 曼氏无针乌贼转录组微卫星特征分析. 渔业科学进展. 2018(03): 144-151 .
2.	杜改改，孙鹏，索玉静，韩卫娟，刁松锋，傅建敏，李芳东. 基于柿雌雄花芽转录组测序的SSR和SNP多态性分析. 中国农业大学学报. 2017(10): 45-55 .
3.	梅利那，范付华，崔博文，文晓鹏. 基于马尾松转录组的SSR分子标记开发及种质鉴定. 农业生物技术学报. 2017(06): 991-1002 .

Other cited types(5)

Get Citation

PDF

XML

Article views (263) PDF downloads (32) Cited by(8)

Turn off MathJax

Article Contents

Abstract

References

Identification of chestnut varieties based on digital analysis of nut morphology