适合马铃薯块茎计算机断层扫描原位观察的栽培基质筛选

doi:10.16420/j.issn.0513-353x.2022-0218

摘要/Abstract

摘要：

土壤的不透明性阻碍了马铃薯块茎生长过程的直接可视化，而计算机断层扫描（Computed tomography，CT）技术可避免破坏性取样，实现植株地下生长过程实时连续观测。为了筛选马铃薯块茎CT成像效果好的栽培基质，对6种不同含水量基质的CT成像效果、数据提取效果和植株生长状态进行了对比分析。结果显示，过筛草炭的植株地上部分生长状况最佳，过筛草炭、蛭石与过筛草炭混合两种类型基质中块茎干、鲜质量最高。除蛭石基质以外，其他基质成像效果均随含水量降低而改善，但基质含水量过低导致植株无法正常生长。相同含水量条件下，过筛草炭的扫描背景杂质最少、成像效果最佳，可获得更清晰的CT图像。因此，在适宜植株正常生长的含水量条件下，即20%左右含水量条件下，过筛草炭是适合CT扫描观测马铃薯块茎生长发育的栽培基质。

关键词: 马铃薯, 块茎, CT, 基质, 生长发育

Abstract:

Soil hinders visualization in tuber growing and developing process，while Computed tomography（CT）technology can avoid destructive sampling and be applied on real-time observation for underground parts of plant. In order to select the cultivation substrate with good CT imaging of potato tubers，CT imaging effect，data extraction and plant growth parameters of six common cultivation substrates with different water content were compared and analyzed. The results showed that potato overground parts in sieved turf grew best，and furthermore，dry weight and fresh weight of tubers in sieved turf or vermiculite & sieved turf were the highest among all substrates. Except for vermiculite，the CT imaging can be improved with water content of substrates decreasing whereas potato plant can not grow normally under serious water shortage. In comparison to other substrates with same water content，there are less background impurities and better CT imaging sieved turf has. Therefore，sieved turf with 20% water content is a suitable cultivation substrate to observe tuber development using CT scanning.

Key words: potato, tuber, CT, cultivated substrate, growth and development

中图分类号:

S532

谭杰, 刘建刚, 刘菊, 简银巧, 李广存, 金黎平, 徐建飞. 适合马铃薯块茎计算机断层扫描原位观察的栽培基质筛选[J]. 园艺学报, 2023, 50(5): 1085-1094.

TAN Jie, LIU Jiangang, LIU Ju, JIAN Yinqiao, LI Guangcun, JIN Liping, XU Jianfei. Cultivated Substrates Evaluation for in-situ Observation of Potato Tubers Using Computed Tomography[J]. Acta Horticulturae Sinica, 2023, 50(5): 1085-1094.

图/表 9

表1 Volume Player Plus（VPP）软件默认参数

Table 1 Default parameters of VPP

特征 Property	默认值 Default value
评估阈值 Evaluation threshold	0.04
用于评估的核大小 Kernel size for evaluation	1
核大小腐蚀 Kernel size erosion	5
核大小中值 Kernel size median	4
最小管衰减值 Minimal tube attenuation value	0.14
最大管衰减值 Maximal tube attenuation value	0.20
最小直径 Minimal diameter	50
最小球面比 Minimal spherical ratio	0.3

表2 20%含水量条件下不同基质中块茎和基质灰度值

Table 2 Gray values of tubers and substrates in different substrates with 20% water content

基质类型 Substrate type	块茎灰度值 Gray values of tuber	基质灰度值 Gray values of substrate
ST	6 800 ~ 8 000	1 400 ~ 3 800
PL	6 800 ~ 8 400	1 000 ~ 4 500
PL & ST	6 700 ~ 7 600	1 700 ~ 4 500
GT	6 700 ~ 7 800	1 600 ~ 5 000
VM & ST	6 900 ~ 7 500	1 800 ~ 6 000
VM	7 200 ~ 8 300	4 300 ~ 9 800

图1 不同基质不同含水量条件下的CT成像效果 ST：过筛草炭；PL：珍珠岩；PL & ST：珍珠岩与过筛草炭混合；GT：普通草炭；VM & ST：蛭石与过筛草炭混合；VM：蛭石。下同。

Fig. 1 CT imaging in different substrates and empty basin with different water content ST：Sieved turf；PL：Perlite；PL & ST：Perlite mixed with sieved turf；GT：General turf；VM & ST：Vermiculite mixed with sievedturf；VM：Vermiculite. The same below.

表3 不同基质不同含水量条件下块茎数量机测值与实测值比较

Table 3 Comparison number of tubers between observed and measured with machine in different water content

基质类型 Substrate type	实测块茎数 Number of tubers observed	0含水量 0 water content		10%含水量10% water content		20%含水量20% water content
基质类型 Substrate type	实测块茎数 Number of tubers observed	机测块茎数 Number of tubers measured with machine	相对误差率/% Relative error rate	机测块茎数 Number of tubers measured with machine	相对误差率/% Relative error rate	机测块茎数 Number of tubers measured with machine	相对误差率/% Relative error rate
ST	10	10	0	10	0	7	-30.00
PL	18	17	-5.56	14	-22.22	12	-33.33
GT	20	19	-5.00	21	5.00	18	-10.00
VM	10	0	-100.00	1	-90.00	6	-40.00
PL & ST	13	12	-7.69	11	-15.38	11	-15.38
VM & ST	13	14	7.69	20	53.85	15	15.38

图2 6种基质不同含水量条件下块茎体积实测值与机测值

Fig. 2 Observed value and machine measured value of tuber volume in six substrates with different water content

图3 不同基质条件下植株地上部生长参数不同小写字母表示在0.05水平差异显著。下同。

Fig. 3 Growth parameters of aboveground plant in different substrate conditions Different lowercase letters indicate significant differences at 0.05 level. The same below.

图4 不同栽培基质条件下块茎干、鲜质量

Fig. 4 Dry weight and fresh weight of tubers in different substrate conditions

图5 不同含水量基质CT成像效果图中红色的横线、蓝色的竖线和伸向花盆背面的横线构成以花盆中心为原点的坐标轴。

Fig. 5 Effect on CT imaging in different substrates with different water content The coordinate axis with the center of the flowerpot as the origin is composed of red horizontal lines，blue vertical lines and horizontal lines extending to the back of the flowerpot.

图6 以过筛草炭为基质的块茎发育过程CT观测 A：出苗阶段；B：匍匐茎伸长阶段；C：匍匐茎膨大阶段；D：块茎形成阶段；E和F：块茎膨大阶段。

Fig. 6 CT observation of tuber development process in sieved turf A：Emergence stage；B：Stolon elongation stage；C：Stolon swelling stage；D：Tuber forming stage；E and F：Tuber bulking stage.

参考文献 14

[1]	Chapman H W. 1958. Tuberization in the potato plan. Physiologia Plantarum, 11 (2):215-224. doi: 10.1111/ppl.1958.11.issue-2 URL
[2]	Ferreira S J, Senning M, Sonnewald S, Kessling P M, Goldstein R, Sonnewald U. 2010. Comparative transcriptome analysis coupled to X-ray CT reveals sucrose supply and growth velocity as major determinants of potato tuber starch biosynthesis. BMC Genomics, 11:93. doi: 10.1186/1471-2164-11-93 pmid: 20137087
[3]	Gray D. 1973. The growth of individual tubers. Potato Research, 16 (1):80-84. doi: 10.1007/BF02360598 URL
[4]	Li Yao-long, Ji Yan-hai, Yu Ping-bin, Wu Zhan-hui, Liu Ming-chi. 2016. Screening test for mixed soilless culture matrix based on different physical and chemical properties. Northern Horticulture,(8):36-40. (in Chinese)
	李耀龙, 季延海, 于平彬, 武占会, 刘明池. 2016. 基于不同基质理化特性的无土栽培混合基质筛选. 北方园艺,(8):36-40.
[5]	Mairhofer S, Zappala S, Tracy S R, Sturrock C, Bennett M J, Mooney S J, Pridmore T. 2012. RooTrak:automated recovery of three-dimensional plant root architecture in soil from X-ray microcomputed tomography images using visual tracking. Plant Physiol, 158 (2):561-569. doi: 10.1104/pp.111.186221 pmid: 22190339
[6]	Metzner R, Eggert A, van Dusschoten D, Pflugfelder D, Gerth S, Schurr U, Uhlmann N, Jahnke S. 2015. Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil:potential and challenges for root trait quantification. Plant Methods, 11:17. doi: 10.1186/s13007-015-0060-z pmid: 25774207
[7]	Mooney S J, Pridmore T P, Helliwell J, Bennett M J. 2012. Developing X-ray computed tomography to non-invasively image 3-D root systems architecture in soil. Plant & Soil, 352 (1-2):1-22.
[8]	Nösberger J, Humphries E C. 1965. The influence of removing tubers on dry-matter production and net assimilation rate of potato plants. Annals of Botany, 29 (116):579-588. doi: 10.1093/oxfordjournals.aob.a083973 URL
[9]	Pérez-Torres E, Kirchgessner N, Pfeifer J, Walter A. 2015. Assessing potato tuber diel growth by means of X-ray computed tomography. Plant Cell & Environment, 38 (11):2318-2326.
[10]	Tracy S R, Roberts J A, Black C R, McNeill A, Davidson R, Mooney S J. 2010. The X-factor:Visualizing undisturbed root architecture in soils using X-ray computed tomography. Journal of Experimental Botany, 61 (2):311-313. doi: 10.1093/jxb/erp386 URL
[11]	Tu S J, Shaw C C, Chen L. 2006. Noise simulation in cone beam CT imaging with parallel computing. Physics in Medicine and Biology, 51 (5):1283-1297. doi: 10.1088/0031-9155/51/5/017 URL
[12]	van Dusschoten D, Metzner R, Kochs J, Postma J A, Pflugfelder D, Bühler J, Schurr U, Jahnke S. 2016. Quantitative 3D analysis of plant roots growing in soil using magnetic resonance imaging. Plant Physiol, 170 (3):1176-1788. doi: 10.1104/pp.15.01388 pmid: 26729797
[13]	van Harsselaar J K, Claußen J, Lübeck J, Wörlein N, Uhlmann N, Sonnewald U, Gerth S. 2021. X-Ray CT phenotyping reveals bi-phasic growth phases of potato tubers exposed to combined abiotic stress. Frontiers in Plant Science, 12:613108. doi: 10.3389/fpls.2021.613108 URL
[14]	Xu Jian-fei, Jin Li-ping. 2017. Advances and perspectives in research of potato genetics and breeding. Scientia Agricultura Sinica, 50 (6):990-1015. (in Chinese) doi: 10.3864/j.issn.0578-1752.2017.06.003
	徐建飞, 金黎平. 2017. 马铃薯遗传育种研究:现状与展望. 中国农业科学, 50 (6):990-1015. doi: 10.3864/j.issn.0578-1752.2017.06.003

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