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基于腐蝕生長(zhǎng)算法的不同活力玉米種子根系表型研究
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國(guó)家自然科學(xué)基金項(xiàng)目(11604154)、江蘇省自然科學(xué)基金面上項(xiàng)目(BK20181315,、BK20170727),、江蘇省農(nóng)機(jī)三新工程項(xiàng)目(SZ120170036)、Asia Hub南京農(nóng)業(yè)大學(xué)-密歇根州立大學(xué)聯(lián)合研究項(xiàng)目(2017-AH-11)和揚(yáng)州市重點(diǎn)研發(fā)計(jì)劃(現(xiàn)代農(nóng)業(yè))項(xiàng)目(YZ2018038)


Root Phenotypic Detection of Different Vigorous Maize Seeds Based on Corrosion Growth Algorithm of Image
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    摘要:

    針對(duì)圖像法根系表型檢測(cè)中因土壤遮擋而導(dǎo)致根系圖像斷裂的問(wèn)題,,提出一種基于腐蝕生長(zhǎng)算法的玉米根系修復(fù)方法,,并進(jìn)行了不同活力玉米種子早期根系表型研究。首先,,采用長(zhǎng)方形扁平結(jié)構(gòu)透明培養(yǎng)容器種植玉米,,迫使其根系貼壁生長(zhǎng),可得到清晰的玉米根系圖,;通過(guò)偏振鏡和單反相機(jī)采集圖像,,并采用灰度化、二值化,、水漫算法等對(duì)圖像進(jìn)行預(yù)處理,,可有效去除因設(shè)備反光和土壤色差造成的各類噪聲,。其次,,基于玉米根系的向水性、向地性,、連續(xù)性等生理特性,,提出5條圖像修補(bǔ)規(guī)則,即端點(diǎn)判定規(guī)則,、分叉點(diǎn)判定規(guī)則,、內(nèi)部連續(xù)性規(guī)則、片段生長(zhǎng)規(guī)則,、近鄰生長(zhǎng)規(guī)則,,在以上規(guī)則約束下,通過(guò)細(xì)化圖像得到單像素連接的根系骨干,,以各個(gè)根段的末端點(diǎn)為起點(diǎn)向中心腐蝕,,并為屬于不同根段的點(diǎn)集標(biāo)記不同編號(hào),根據(jù)不同根段間的端點(diǎn)導(dǎo)數(shù)值和平均導(dǎo)數(shù)值等參數(shù),,連接根段,,實(shí)現(xiàn)根系的修補(bǔ),從而得到完整根系圖像。最后,,基于所提圖像修復(fù)算法對(duì)不同活力的玉米種子根系圖像進(jìn)行表型研究,,發(fā)現(xiàn)在相同時(shí)間,根系數(shù)目,、根系寬度,、根系長(zhǎng)度、根系延展長(zhǎng)度與玉米種子活力均呈現(xiàn)明顯負(fù)相關(guān),;以上4個(gè)生理參數(shù)的增速與種子活力呈現(xiàn)明顯正相關(guān),。研究表明,本文所提的根系修復(fù)算法可用于作物根系高通量表型無(wú)損檢測(cè),。

    Abstract:

    The root phenotypes of different vigorous maize seeds vary a lot, and imaging roots of growing maize is a noninvasive, affordable and high throughput way to detect it. However, due to the block of soil, acquiring a complete image is difficult. An algorithm was proposed to repair incomplete root images and based on it, root fast noninvasive phenotyping detection can be realized. Firstly, a cuboid transparent container without cover was developed as mesocosms and the maize seeds were planted in it. The maize roots grew in soil against two acrylic plastic surfaces due to the press of the small growing area to acquire more root details during roots visualization and imaging. Even though, parts of the roots were occluded by the soil which meant that it was tough to extract the information of root general physical construction. For recovering gaps from disconnected root segments, corrosion growth algorithm was proposed based on the physiological characteristics of hydrotropism, geostrophic and continuity with three steps which were root image thinning, corrosion and growing processing, respectively. The experiments indicated that maize phenotyping parameters were negatively correlated with seed aging days. And specifically, root number, root length, root width and root extension length of unaged and 14dayaged maize seeds were decreased from 14.80, 83.50mm, 1.53mm and 82.70mm to 4.38, 36.90mm, 1.38mm and 54.6mm, and the growing speed of them were changed from 1.68 per day, 8.80mm/d, 0.06mm/d, 9.0mm/d to 0.70 per day, 4.3mm/d, 0.05mm/d and 5.70mm/d, respectively. Whereas root extension angle is basically irrelevant with the level of maize seed aging. The developed cuboid transparent container without cover can push each root growing along the wall of the container which helped to acquire more root information. The presented novel corrosion growth algorithm can recover the missing parts, even for big gaps, of maize roots effectively according to root morphological properties. The experiments showed that the proposed method can be applied to evaluate the vigor of maize seeds which had vast application prospect in high throughput root phenotyping area.

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盧偉,李也,王玲,羅慧,孫國(guó)祥,汪小旵.基于腐蝕生長(zhǎng)算法的不同活力玉米種子根系表型研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2020,51(4):224-231. LU Wei, LI Ye, WANG Ling, LUO Hui, SUN Guoxiang, WANG Xiaochan. Root Phenotypic Detection of Different Vigorous Maize Seeds Based on Corrosion Growth Algorithm of Image[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(4):224-231.

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  • 收稿日期:2019-08-25
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  • 在線發(fā)布日期: 2020-04-10
  • 出版日期: 2020-04-10
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