范文一：[黄瓜的英文]黄瓜英文怎么说，黄瓜的英文例句

[黄瓜的英文]黄瓜英文怎么说，黄瓜的英文

例句

篇一 : 黄瓜英文怎么说，黄瓜的英文例句

英文翻译:Cucumber

例句:

这棵黄瓜爬蔓了。

This cucumber plant is climbing.

将已收获过的黄瓜、西红柿和其他作物的秧蔓割下，制成堆肥。

Cut down and compost spent cucumbers, tomatoes and other crops.

茄子啊，黄瓜啊，卷心菜啊，西红柿啊，各种蔬菜摆满了货架。

The shelves were filled with all sorts of vegetables& eggplants,

cucumbers, cabbages, tomatoes.

黄瓜可以生吃。

Cucumbers can be eaten raw.

在我们的菜园里，我们种了茄子、黄瓜和土豆。

In our garden we have egg-plants, cucumbers and potatoes.

黄瓜被切成了圆片。

A cucumber was sliced into rounds.

她温室内的黄瓜和番茄成熟了。

Cucumbers and tomatoes ripened in her hothouses.

他们和瓜类、黄瓜和南瓜有关。

They are related to melons, cucumbers and squashes.

研究了麦饭石对黄瓜种子萌发和细胞分裂的影响。

Studied the affection of medical stone on the seed germination and cell division of cucumber.

酸黄瓜、果酱、腌浆果、西红柿，凡是你说得出的，他们都有。

“Pickled cucumbers, jam, pickled berries, tomatoes

研究了PP333对黄瓜幼苗素质和抗冷能力的影响。

The effect of PP333 on seedling quality and chilling resistance of cucumber were investigated.

现在，是黄瓜，蚕豆和青椒的时刻了。

But spring is the time for cucumber, fava bean and capsicum.

他给了我一根黄瓜。

He gave me a huge cucumber.

这可能与黄瓜和番茄对水分的要求不同有关。

It may be caused by different demand of cucumber and tomato for water.

我要一些茄子，小黄瓜，红葡萄和豌豆。

I want some eggplant, cucumbers, carrots and peas.

有西瓜汁、橙汁和黄瓜汁。

We have watermelon juice, orange juice and cucumber juice.

所谓绿色沙拉指的是只有绿色的蔬菜，如莴苣和黄瓜等凉拌生

菜。

A green salad has only green vegetables, such as lettuce and cucumber.

由于我是新手，一开始，我只种了一些西红柿和黄瓜。

For the start, I only planted some tomatoes and cucumbers.

而且我也不喜欢小黄瓜和南瓜。

And I don’t like cucumbers and pumpkin.

小黄瓜、马铃薯和洋葱是蔬菜类。

Cucumbers, potatoes, and onions are vegetables.

用雨水和净化过的河水种植莴苣、番茄、黄瓜和胡椒。

Rainwater and purified river water are used to grow lettuce, tomatoes, cucumbers and peppers.

是的，我喜欢，尤其是腌黄瓜和红萝卜。

Yes, I like it, especially pickled cucumbers and carrots.

研究了单纯氙气对芦笋、黄瓜保鲜指标的影响。

The paper studied the effects of single xenon on the preservation of cucumber and asparagus.

通过室内盆栽和田间药效试验，研究了唑菌酯对黄瓜白粉病的

防治效果。

The control effects of pyraoxystrobin on cucumber powdery

mildew were tested in greenhouses and fields.

小萝卜、甘蓝、老玉米、黄瓜和茄子。

Radishes, broccoli, corn, cucumbers and egg plant.

我只要莴苣和酸黄瓜。

I just want lettuce and pickles.

回到弗拉特布什大道上，庞正忙着往货架上补充黄瓜和椰子。

Back on Flatbush Avenue, Pong is busy restocking his shelves with cucumbers and coconuts.

我把黄瓜和西红柿切成大块。

I cut the cucumber and tomato in large chunks.

芦荟和黄瓜提取物抚慰和凉爽干燥的皮肤。

Aloe Vera and Cucumber Extracts soothe and cool dry skin.

这种蔬菜汁主要由西红柿和黄瓜制成。

This vegetable juice is made up chiefly of tomatoes and cucumbers.

篇二 : 黄瓜的英文

黄瓜是我们日常生活中常见的蔬菜，那你知道黄瓜的英语怎么说,那么下面就随康网小编一起看看黄瓜的英语怎么说吧。,]

1、cucumber

2、Cucumis sativus

3、cuke

现代生活，黄瓜已经成为一种新型的时尚的健康食品。生吃黄瓜可以美容养颜，也可以用作减肥的食材。也许你还不知道，黄瓜浑身都是宝，黄瓜汁能降火气，排毒养颜，黄瓜沫用来敷在脸上能祛痘，作为无公害蔬菜，无公害黄瓜皮儿也不用去掉也可食用。最容易被忽略的黄瓜把儿比黄瓜的作用还要大。

所以建议大家吃黄瓜时，一定不要把黄瓜把儿扔掉，避免扔掉了好东西。这是因为，黄瓜把儿含有较多苦味素，苦味成分为葫芦素C。动物实验证实，这种物质具有明显的抗肿瘤作用。

吃黄瓜还需要注意的的是，吃黄瓜不宜过多食用，专家提醒:黄瓜偏寒，脾胃虚寒、久病体虚者宜少吃。有肝病、心血管病、肠胃病以及高血压的人，不要吃腌黄瓜。

黄瓜含有维生素C、维生素B族及许多微量矿物质。黄瓜的皮所含营养素丰富，我们在吃黄瓜时应当保留生吃。为了预防黄瓜上残留的药物对我们身体的危害，我们因先将黄瓜在盐水中浸泡一会再洗净生食。但我们要切记在浸泡黄瓜时不要切头去根，那样会黄瓜的营

养流失。我们建议在生活住中黄瓜最好要生吃，这样不会使维生素损

失。

范文二：基于GMM的黄瓜病害图像建模_英文_

Model for Cucumber Disease Images based on GMM 1 2* 2REN Xiao-dong，LU Me-qn，BA Hu-hu IiiIii

1, Institute for the Control of Agrochemicals，Ministry of Agriculture，Beijing 100125，China; 2, Institute of Information Science，Beijing Jiaotong University， Bejng 100044，Chna iii

Abstract Based on the accuratea nalysis of cucumber disease images，the low level feature of images was effectively extracted，and Gaussian Mixture Model( GMM) for 8 common cucumber diseases was built, The parameters of GMM were estimated by the algorithm of expectation maximum ( EM) to accurately charac- terze the featured strbuton of 8 cucumber dseases，thus ncreased the correctd entfcaton of cucumber dseases and accurate graspng of damage condtons，and iiiiiiiiiiiiiiprovided basis for achievement of real-time and accurate prediction of cucumber diseases, Key words Cucumber disease; Image processing; Mathematical modeling; Gaussian Mixture Model; China

Diseases，pests and weeds control of crops plays an extremelyorphology characteristics，and achieved the automatic recognitionm

mportant poston in crop producton and natona economc deve- and cassfcaton of 3 knds of nsects，the detecton accuracy rate iiiiililliiiiiiopment，the primary premise of control processesi s the correct of the systemr eached 90% , Re volving around rapid diagnosis of recognition of diseases，pests and weeds and the accuratea nalysis crop diseases，pests and weeds，WANG Ke-ru et a l, combined of damage condition during crop growth period，thus further grasp the expertk nowledge of crop diseases，pests and weeds recognition

the occurrenced ynamcs of dseases to acheve rea-tme and accu- wth dgta mage processng and neura network together，andiiiliiiiliil

comprehensively used artificial intelligence and network technolo- rate prediction and control, In recent years，along with the rapid

gy，to acheve the remote mage recognton and dagnoss of crop iiiiiidevelopment of computer and information technology，increasingly ,3,diseases，pests and weeds, ZHANG Hong-tao et al, used wave- wide application of computer vision and gradual maturity of various let analysis for image processing，put forward the opinion by using pattern recognition technology，the research and application of color and texture featureo f pestsf or species recognition，and input digital image processing technology has extended toa gricultural neural network classifier after features election for patternr ecogni- engineering field，especially has wide study and application in tion，but the aspects o f recognition speed，feature extraction， recognition diagnosis of crop diseases，pests and weeds，crop nu- hardware design still needed to be improved，so as to improve pest ,5,trent defcency dagnoss，seed quaty nspecton，quaty detec- iiiiiliiilirecognition rate, LIAN Fei-yu et al, used wavelet transformt o ton and cassfcaton of agrcutura products，showng great po- iliiiillicompress high dimensional image vector，the high frequency com- tential in application, The images of crop diseases，pests and ponent of image was matched with edge and contour of image， weeds are processed to extracth acracteristic parameters，and fur- which better compresseadn d characterized the featureo f pest im- ,7,age，putting forward a kind of SVM classification, The methods ther studya utomatic detection and recognition technology of crop

focus on dagnoss and recognton of crop dseases，pests and iiiiidiseases，pests and weedsi n fields and develop visual control sys- weeds，which ignore mining the featured istribution properties of tem，so as to acheve the purposeo f ntegent recognton，whch iilliiiicrop diseases，pests and weeds images，thus limiting the under- is the important research content of current machine vision standng and grasp of crop dseases，pests and weeds in iitechnology, essence,Th erefore，through characteristic analysis of 8 kinds of The methodsu sed during the processing processo f images of common diseases in cucumber crop，the author established Gauss crop diseases，pests and weeds mainly include multi-parametric mixture model ( GMM) ，and described the characteristic ,1,,2,analysis method，color space partition method，artificial in- dstrbuton of 8 knds of dseases，so as to provde referencef or iiiiii,3,,4,realizing real-time telligence analysis method，texture featurean alysis method， ,5,and accuratep rediction and prevention of cucumber disease, speca mage anayss method，morphoogca feature anayss ililililli,6, ,7,methodand wavelet analysis method, YU Xin-wen et al, de-

veloped a set of vision detection system for automatic recognition ,8,and classification of cotton bollworms, The system studied the 1Modeling of Cucumber Disease Imagesegmentation of insect image and edge detection algorithm，extrac- 1, 1 Feature extraction Generally speaking，the color changested plant leaf contour uotline and insect body profile using insect of pant ( stem，eaf) durng dfferent growth perods in the growth lliii of cucumber are the important information characterizing crop Received: September1 6，2011Accepted: November 29，2011 growth, Meanwhile，different nutritional status，groupss tructures， Supported by National Natural Science Foundation of China ( 60903066，damage conditions and other factorsa ll affect the growtha nd de- 0985244) , Natural Science Foundation of Beijing City ( 4102049 ) , Ne w velopment of cucumbe，rthese effectsm ake different parts of plant Teacher Fund of Ministry of Education ( 20090009120006) , Basic Scientific exhibit different colors, Therefore，the extraction of color informa- Research Expenses of Central College ( 20100008030) , tion in cucumber image and carrying the related transformation * Corresponding author, E-mail: mqliu@ bjtu, edu, cn

,10, calculation，is the key to realize modeling and identification of cu-one of the effective functions, The study used wavelet filteringcumber diseases by true color image analyzing and processing method to extract texture fea，tuarned composed3 9 dimensional technoogy, In addton，from the mage semantc comprehenson liiiiicombined vectorw ith the color featuresi n " 1, 1, 1" to describe the and anayss，the texture nformaton of cucumber damaged by df- liiiicharacterstc feature of each pece of cucumber dsease iiiiferent dseases in dfferent growth perods are dfferent，so the n- iiiiiimage,S pecifically，one level Haar wavelet transformwa s used to

decom- pose cucumber disease image with M ×N pixels，the formaton expresson of cucumber dseases mage beongs to the iiiil

calculation texture feature expresson, Based on the anayss of above two ili

points，the study extracted twloo w level features for cucumber for one of the hgh frequency band of texture featurewa s shown n iidsease mage，namey the coor feature and texture faeture，and iillformula ( 1) : 1 /2 m , 1n , 1 12 ( f( ，j) ) iT =( 1) combned the two features to compo6s ed mensona combned egiiilii- ,, i = 0 j = 0 mn?envector tod escrbe the combned feature dstrbuton propertes of iiiiii Where f( i，j) indicates the coefficient value in one channelcucumber dsease mage, iiafter waveet transform，T vaue of each frequency band s adopted lli1, 1, 1 Color feature extraction of cucumber disease image, Color as feature texture componeonft jont featureo f regona bock, Af- iillfeatureh as the following advantages: it has robustnessp roperties， ter extracton of 39 dmensona egenvector，each dmensona fea- iiiliiilwhich is most active in low level feature extraction of true color ture needs to be normalized，so that the cloor featuresa nd texture images，and is easy to extract, In addition，color feature spaceis featuresh ave the equal contribution in the description of image a linear space，which has obvious advantages in measurement，features for cucumber dsease, iand is more suitable for distance measurement betwee2n pieces of 1, 2 Gaussian mixture model To recognize every kind of dis- cucumber disease images, The researcho n color feature mustb e ease information of cucumber crop，the standard model which not set in color model，the common color models include RGB，HSV， only can accurately depict the combined feature of each disease YUV，YIQ，Luv，Lab，XYZ and Munsell model, HSV is a color image，but also can accurately describe various disease informa- space model reflecting human visual characteristics，which is suit- ton needs tob e expored, The study obtaned the combned egen- iliiiable for image processing，where H representshu e，S represents vector of cucumber disease image，and estimated GMM of each saturation，V represents brightness value，the model has beendsease of cucumber，so as to descrbe the dstrbuton characters- iiiiiiadopted by many algorithm, The study also used HSV color feature tics of combined feature of the disease, Specifically，39 dimen- mode, lsional eigenvector set extractedfr om each piece of cucumber dis-

The color featured escriptions commonly used are color histo- V Vgram，coor moment and coor set, The coor hstogram s the most lllii ease image was I，V = { ，…， } the definition of featured istri-xxcommonly used color feature description, Specifically，the color 1 Nbution probability of the semantic region described by GMM was as histogram is calculated through 3 steps: the first step，quantization follows: of color space，the stepi nvolves selection of quantization method M in color model ( uniform or non-uniform) ，color space is usually p( x)= N( x | ，)( 2)πμ i i i quantfed nto m knds of coor; the second ste，pthe appearance iiiil = 1i indicates Gaussian distribution In the formula，N( x | ，)frequency of each color in image is counted，thereby get cloor his- μ i i togram; the third step，normalization of histogram，this is mainly of i mixed components; and are mean and covariance matrixμ? i i for making the histogram apply to images of different sizes，which of i Gaussian component;indicates weight value of i Gaussianπ i M is convenient for similarity comparison among images, Based on component，and satisfies the condition ; M is the total = 1π i = 1 ithe above steps，the study extracte3d6 -dimensional color histo- number of mixed component, Each Gaussian component reflectsgram in HSV color space as color component part of combined one cluster in eigenvector space，indicating the characterization of eigenvector, combined feature distribution within rectangular segmentation re-

gion, For each Gaussian component，the conditional probability

density of combined eigenvector x within rectangular segmentation

regon s:ii 1, 1, 2Texture feature xteraction of cucumber disease image,

1 1T ,1 Texture features another mportant component of ow eve featureiilllexp, ( x , ) ( x , ) N( x; ; ) =μ μμ i ii i i , , d 2of infrared thermography, Generally speaking，texture feature ex- ( 2) ||π i槡

tracton s many from the reatonshp between thep xe and ts iiilliiili ( 3)neghborng pxes, The common comparson methods ncude spa- iiiliil Where d represents thed imension of eigenvector x,tial autocorrelation function method，FFT power law，joint proba- Particularly，the parameterso f GMM model are estimated bybty matrx method，and waveet fterng method currenty beng iliilililiEM algorithm, EM algorithm is a kind of maximum likelihood esti- ,9,studied more, In the above process，high frequency band of mation method to aclculate model distribution parametersfr om in- wavelet coefficients reflect the changes of pixels in the horizontal complete data，which achieves parameter calculation through itera- direction，vertical direction and oblique direction，so the functions tive processo f E step and M step overlapping calculation，and EM of these hgh frequency coeffcents can express texture featuroef iiialgorithm must be convergent aftesre veral times of iteration, As- image，the mean square value of different high frequency bands is sumng tota number of combned egenvectors wthn rectanguar iliiiil

segmentation region R is N，making = ( ，) i ndicate meanwhich is normally taken as:θμ w iii and covariance parameter of i Gaussian component, The processo fd( d + 1) m = ( M , 1)( 9)+ M?d + M? M 2parameter estimation is illustrated with n iteration as an

Analysis from semantic content of cucumber disease image，example,S tep E: giving possibility to each eigenvector ( x，i = i each image has relatively independent physical meaning and image 1，…， ( n)( n)feature，so GMM model not only focuses on the description of N) b eongng to Gaussan vector ( g，j = 1，…，M) , lii )p( x| πθ w j j i j ( 4)p( g| x，)= θ j i j Moverall featureo f image，but also can accurately describe distribu- ( n)( n) p( x| )πθ k k i k = 1tion properties of combined feature of disease image, ( n)Step M: updating model parameters = ( ，) ,θμ j j j M 1 ( n + 1)( n) ( 5)2ests and ssRulAnalyi = p( g| x，)πθ jj j i i = 1M 2, 1 e ees of seces of 8 common cceImagxamplpimnuumbr M ( n)p( g| x，) | xθ j jiidiseases To verify the validity of the proposed modeling algo- ( n + 1)i = 1 =( 6)μ j M rithm of plant disease image，the images of specimens of 8 com- ( n)p( g| x，)θ j j i i = 1mon cucumber diseases were collected，including cucumber pow- M ( n)( n + 1)( n + 1) T p( g| x，) (x , ( x, )θμμ dery mildew，cucumber downy mildew，cucumber gray mold，cu- j i j i j i j i = 1( n + 1) =( 7) jMcumber wilt，cucumber gummy stem blight，cucumber anthrac- ( n) )p( g| x，θ j i j = 1i nose，cucumber bactera anguar spots and cucumber ill Intuitively，due to different diversities of semantic featuresi nblight,Eac h disease was photographedf or 20 images，each image different semantic segmentation regions，the component number M has the resolution of 256 ×25 6，with a total of 160 images, Each of ts GMM s not consstent，so the combned egenvector set wth iiiiiiimage had different illumination and posture，with certain side different rectangular segmentation regions should adaptively decide ange,Th e mages of specmens of 8 common cucumber dseases liiithe value of M, The study used Minimum Description Length were shown in Fig, 1, ,11, ( MDL) criterionto select the optimal M value,is selectedM 2, 2 The features of cucumber dsease mage To ustrate iiill to make the formula ( 8) take them aximum value:feature extracton effect of the cucumber dsease mage，Tab, 1 iiiN Mw m Mshowed 39 dimensional eigenvector of powdery mildew and gray ( 8)logN( x; ; ) , logN?πμ i k i i w k = 1 i = 1 2mold, Where，mis the number of free parametersw ith M GMM， M

Note: A, Powdery mildew; B, Downy mildew; C, Gray mold; D, Wilt; E, Gummy stem blight; F, Anthracnose; G, Bacterial angular spots; H, Blight,

Fig, 1 Image examples of 8 cucumber diseases

2, 3 GMM of cucumber disease image Based on the extrac-iseases,of cucumber d

ted eigenvector and the description in formula ( 1) ,( 9) ，GMM Accordng to the crroespondng GMM dstrbuton feature of iiiiimodels were established for 8 common diseases of cucumber such dseases in Fg, 2，GMM modes of cucumber wt and cucumber iililas powdery mdew，so as to descrbe the dstrbuton property of iliiiibacterial angular spots was composed of a Gaussian component， each cucumber disease characteristics，improve the understanding GMM models of cucumber powderym ildew，cucumber anthracnose

of the essenceo f cucumber diseases，accurately and timely diag-and cucumber gummy stem blight were composed of 2 Gaussian nose the dseases in cucumber，whch coud avod yed reducton iiliilicomponents，GMM models of cucumber gray mold，cucumber of cucumber，and further provide data support for the control of blight and cucumber downy mildew were composedo f 3 Gaussian cucumber dseases, Fg, 2 sted GMM modes of 8 dseases，and iililicomponents,

described the corresponding characteristic distribution conditions

Tab, 1 Thirty-nine dimensional eigenvector extracted from images of powdery mildew and gray mold

Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Name of teristic 1 Fteristic 2 Fteristic 3 Fteristic 4 Fteristic 5 Fteristic 6 Fteristic 7 Fteristic 8 Fteristic 9 Fteristic 10 F dsease i1 2 3 4 5 6 7 8 9 10 Powdery mildew 0, 010 80, 000 20, 000 30, 000 40, 002 30, 006 40, 017 50, 000 00, 000 00, 000 0 Gray mold 0, 000 8 0, 001 1 0, 000 5 0, 000 3 0, 000 3 0, 000 8 0, 000 4 0, 110 1 0, 051 1 0, 028 2 Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Name of teristic 11 Fteristic 12 Fteristic 13 Fteristic 14 Fteristic 15 Fteristic 16 Fteristic 17 Fteristic 18 Fteristic 19 Fteristic 20 F disease 11 12 13 14 15 16 17 18 19 20 Powdery mildew 0, 009 90, 000 50, 001 20, 000 00, 032 90, 008 50, 00500, 000 80, 235 90, 234 5 Gray mod 0, 014 6 0, 124 6 0, 281 0 0, 017 2 0, 019 7 0, 308 6 0, 0234 0, 010 5 0, 005 6 0, 000 0 l Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac- Name of teristic 21 Fteristic 22 Fteristic 23 Fteristic 24 Fteristic 25 Fteristic 26 Fteristic 27 Fteristic 28 Fteristic 29 Fteristic 30 F dsease i21 22 23 24 25 26 27 28 29 30 Powdery mdew 0, 234 50, 283 70, 125 50, 000 30, 000 20, 000 00, 000 00, 000 00, 000 00, 000 0il Gray mold 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Charac-Name of teristic 31 Fteristic 32 Fteristic 33 Fteristic 34 Fteristic 35 Fteristic 36 Fteristic 37 Fteristic 38 Fteristic 39 F disease 31 32 33 34 35 36 37 38 39 Powdery mildew 0, 000 00, 000 00, 000 00, 000 00, 000 00, 000 00, 138 40, 364 70, 034 0 Gray mod 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 000 0 0, 412 5 0, 007 8 0, 178 9 l

Note: The first 36 dimensions are color features; the last 3 dimensions are texturef eatures,

Fig, 2 GMM of 8 common cucumber diseases

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GMM 基于 的黄瓜病害图像建模

1 2* 2 ，，刘美琴白慧慧任晓东( 1, ，100125; 2, ，100044) 农业部农药检定所北京 北京交通大学信息所北京

( Gaussian Mixture Model， ，，8 摘要 通过对黄瓜病害图像的准确分析有效提取了图像的底层特征建立了 种常见黄瓜病害的高斯混合模型 GMM) ，( Expectation-Maximization，EM) GMM ，8 ，并利用最大期望算法估计 的参数精确描述了 种黄瓜病害的特征分布从而提高了对黄瓜病害的 ，。正确识别和为害情况的准确把握为实现黄瓜病害的实时与准确的预测和防治提供了理论依据 ; ; ; 关键词 黄瓜病害图像处理数学建模高斯混合模型

( 60903066，0985244) ; ( 4102049) ; ( 20090009120006) ; 基金项目 国家自然科学基金项目北京市自然科学基金 项目教育部新教师基金项目中央高校基 ( 20100008030) 。本科研业务费项目 ( 1979 , ) ，，，，，。* ，，，。作者简介 任晓东男山东德州人工程师硕士从事农药信息技术研究通讯作者讲师硕士从事信号与信息处理研究2011-09-16 2011-11-29 收稿日期 修回日期

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lasm of Verticillium wilt resist,J,, Jiangxi Cottons，2006，28( 6) :germ p( Continued from page 5) 10 , 14, ( in Chinese) ,,41, LANG LM，LU YL，WANG ZX，et a, Seecton of new wt-resstant IIlliili ,43,WANG QL，LU YZ，ZHANG JB，et al, New species hybrid cottonB aimiangermplasms from G, Hirsutum × G , Sturtianum,J,, Acta Agriculturae No, 3,J,, China Cotton，2007，34( 8) : 18 , 22, ( in Chinese) ,Boreali-occidentalis Sinica，2002，11( 4) : 16 , 18, ( in Chinese) , ,42,XIAO SH，WU QJ，LIU JG，et al, Production of top quality cotton new

、 棉花抗黄萎病分子育种的现状问题与展望

1 1 2 ，，( 1, ，226019; 2, ，044000) 汪保华高灵路王长彪南通大学生命科学学院江苏南通 山西省农业科学院棉花研究所山西运城

。，，QTL 摘要 黄萎病是棉花生产上的重要病害极大地影响了棉花的生产概述了棉花黄萎病病菌的分类及其致病机理棉花黄萎病抗性的 定 ，，。位及分子育种进展探讨了黄萎病抗性育种存在的问题和发展方向为今后棉花黄萎病育种研究提供参考 ; ; QTL; 关键词 棉花黄萎病分子育种

( 31000729，30900911) ; ( 10KJB210004 ) ; ( 基金项目 国家自然科学基金江苏省普通高校自然科学基金南通市科技创新计划生物技术及新医药专项 AS2010018) 。 ( 1976 , ) ，，，，，。作者简介 汪保华男安徽潜山人博士讲师从事植物基因组与分子育种研究 2011-08-082011-11-27 收稿日期修回日期

范文三：刀拍黄瓜的英文做法

刀拍黄瓜

原料:

黄瓜、蒜末、盐、白糖、醋、生抽、辣椒、花椒。

做法:

1、黄瓜表面抹少许盐，搓洗干净，再用凉白开冲洗后晾干。

2、洗好的黄瓜平放在案板上，用刀背拍碎，再用手掰成小块。

3、装进大碗里，加盐，拌匀腌10分钟左右。

4、把腌出来的多余的黄瓜水倒净。

5、撒上白糖，蒜末，醋，生抽。

6、取油锅爆香干辣椒末和少许花椒，淋在蒜末上，吃的时侯拌匀即可。

A knife shoot cucumber

Raw material:

Cucumber, garlic, salt, sugar, vinegar, soy sauce, pepper, Chinese prickly ash.

Practice:

1, the surface of the cucumber and wipe a little salt, scrub clean, reoccupy cold water to dry after

washing.

2, a good wash Huang Guaping put on the chopping board, knife blade to smash, and then hand to break it into small pieces.

3, in a bowl, add salt, marinate for about 10 minutes.

4, the salt out of water down the net excess of cucumber.

5, sprinkle with sugar, garlic, vinegar, soy sauce.

6, take the pan saute dried chilli pepper and a little garlic, pour in, eat when mix.

范文四：国外也吃拍黄瓜？？？“拍黄瓜”的英文怎么说？

国外也吃拍黄瓜???”拍黄瓜“的英文怎么说?

拍黄瓜是中国的“传统大菜”,不仅遍布中国各地,在国外也有很好的反响。

美国《纽约时报》报道称,纽约餐馆都在学做拍黄瓜,从墨西哥餐厅到美式餐厅,拍黄 瓜变得随处可见。

如此受欢迎的“拍黄瓜”的英文一定要记住, smashed cucumbers.

你有没有想过,黄瓜为什么一定要拍呢,切不行么?

不行!人们人发现,切片黄瓜 (sliced cucumbers

) 表面光滑、不易入味,调料加在上 面往往会滑落。 拍黄瓜则不然, 它不规则的棱角 (craggy edges) , 和粗糙的表面 (rough surfaces ) , 极易吸收调料入味。

报道称,美国各餐厅拍黄瓜的方法各不相同,有的跟中国人学,用刀面直接拍;有的学 日本人,用木锤 (wooden mallet) ,或者用擀面杖 (rolling pin) 。

拍黄瓜的动作时,动词除了用 smash ,还可以用 smack 。

做这样一道“大菜”,除了需要菜名里的“拍” (smash ) 和“黄瓜” (cucumbers ) 这两 样,还需要什么材料呢?

范文五：国外也吃拍黄瓜？？？”拍黄瓜“的英文怎么说？

拍黄瓜是中国的“传统大菜”，不仅遍布中国各地，在国外也有很好的反响。

美国《纽约时报》报道称，纽约餐馆都在学做拍黄瓜，从墨西哥餐厅到美式餐厅，拍黄瓜变得随处可见。

如此受欢迎的“拍黄瓜”的英文一定要记住，smashed cucumbers.

你有没有想过，黄瓜为什么一定要拍呢，切不行么？

不行！人们人发现，切片黄瓜(sliced cucumbers)表面光滑、不易入味，调料加在上面往往会滑落。拍黄瓜则不然，它不规则的棱角(craggy edges)，和粗糙的表面(rough surfaces)，极易吸收调料入味。

报道称，美国各餐厅拍黄瓜的方法各不相同，有的跟中国人学，用刀面直接拍；有的学日本人，用木锤(wooden mallet)，或者用擀面杖(rolling pin)。

拍黄瓜的动作时，动词除了用smash，还可以用smack。

做这样一道“大菜”，除了需要菜名里的“拍”(smash)和“黄瓜”(cucumbers)这两样，还需要什么材料呢？

soy sauce 酱油

sesame paste 麻酱

sesame oil 香油

garlic 大蒜

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