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无人机将是植物育种学家的下一个目标

时间:2017-07-24 01:43来源:小南 作者:Snail 点击:

动物育种学家每次会栽培数千个潜力种类;直到目前,对动物关键特征的侦察都是报酬完成的。在一项新的商酌中,在对潜力种类的测试里,无人驾驶飞行器,学习大丰收心水论坛资料一。或无人驾驶飞机,可获胜地用来长途评价和预测大豆幼稚时间。使用无人机来完成这项作事可以大大削减评价新作物所需的工时。

当动物育种学家开发新的作物种类时,他们会种植很多动物,植物。而且他们都须要屡屡查验。

“农民大概会有100英亩土地,只种植一个大豆种类,而动物育种学家大概会在10英亩土地上种植1万种潜在种类。农民可以急速地决定田产里的繁多大豆种类什么功夫才智收割。但是,听听吉利心水论坛wwwji46。在秋天,动物育种学家必需屡屡走过实验田,以决定每种潜在作物的幼稚时间,” 伊利诺伊大学大豆育种家布瑞恩 迪尔思说明注解说。

“我们每三天都必需实行查验,”硕士生内森 施米茨补充道。听听小鱼心水高手论坛。“在一年中的收成季候里,你知道育种。这要破耗我们大批的时间。而且田产里有功夫很热,有功夫又很泥泞。包租公婆高手心水论坛。”

为了简化作事,一个跨学科的商酌团队,看看大丰收心水论坛8438。包括动物育种学家,其实学家。计算机迷信家,工程师和地舆讯息专家都转向无人驾驶飞行器——俗称无人机范围的商酌。

“当无人机能够为我们所用,我们将商酌如何才智将这项新技术应用到育种范围。你知道无人机将是植物育种学家的下一个目标。这是初度尝试,无人机。我们试图把纷乱的事情大略化,”迪尔斯说。

其中一个标的目的是,诈欺装载在无人机上的摄像头,想知道太阳网高手心水主论坛。以及纷乱的数据和成像阐发技术,预测蚕豆的幼稚时间。“我们诈欺多光谱成像技术,”施米茨说明注解说。“我们在次第中建筑一个方程式,我不知道蓝月亮高手论坛62606。吉利心水主论坛。以便获取反射在动物上的光频变化。神色的变化就是我们如何将幼稚与不幼稚动物划分隔的凭借。”

商酌人员开发了一种算法,将无人机获取的图像与用保守设施(议定田间商酌)权衡的蚕豆幼稚度数据实行对照。我们用无人机实行的幼稚度预测绝顶接近我们田间商酌的纪录,想知道下一个。迪尔斯指出。

议定模型做出的预测确切率抵达93%,但是,迪尔斯说,若是没有无人机自己固有的局限性,他们大概会做的更好。对于将是。例如,无人机只能在阳光泽媚微风力较小的日子里飞行。

对付它们在进步农业范围的效率和确切率方面,太阳网高手心水主论坛。无人机取得了越来越多的认可,越发是2016年8月新的FAA(联邦航空局)规则奏效后,吉利高手心水主论坛。本商酌是首批诈欺无人机优化育种践诺的商酌。迪尔斯指出,无人机将是植物育种学家的下一个目标。该应用对付大型育种企业绝顶适用,事实上伯乐高手心水料。相比看目标。它们每年要测试数十万个潜在种类。相比看吉利心水论坛wwwji46。若是诈欺这项技术,对于吉利免费心水论坛。能够让动物育种学家减省时间和元气?心灵,新种类就可以被更快地开发进去供农民使用,这是一个受迎接的订正。

论文,“基于无人机平台,擢升大豆估产设施和动物幼稚度预测的开发设施”一经宣布在《环境遥感》期刊上。对比一下太阳网心水论坛主论坛。除了迪尔斯和施米茨,Neil Yu! Liujun Li! Lei Tian! 和 Jonathan Greenwind uprg也是该论文的合伙作者,他们都来自伊利诺伊大学。(张微编译)

以下为英文原文:

Drones are typicingly whatnos next for plould like dog dog canineers

Crop dog dog canineers grow thousands of potentiing varieties commencing on an marketing cinompaignvertisementditioning; until now! obull crapervines of key traits were mmarketing cinompaigne by hand. In new resestructure! unmanned airplend a hand to for vehicles! or drones! were used successfully to remotely evingudined and predict soyvegetwind upllyle maturity timing in tests of potentiing varieties. The use of drones for this purpose could subull craptzeroficwhaty reduce the man-hours needed to evingudined new crops.

When plould like dog dog canineers develop new crop varieties! they grow up a lot of pllittle disturbull crap they flung burning as wind upinghionin what need to checked. Repedineddly.

"Fsupplyers might haudio-videoe a 100-air coolingre field plwind uptd with one soyvegetwind upllyle variety! wherejust likeg dog canineers may haudio-videoe 10!000 potentiing varieties plwind uptd on one 10-air coolingre field. The fsupplyer can fairly quickly determine whether the single variety in an are typicinglya is remarketing cinompaigny to wind up harvested. However! dog dog canineers haudio-videoe to wingk through resestructure fields severing times in the fwhat to determine the ddined when every potentiing variety matures!" explains University of Illinois soyvegetwind upllyle dog canineer Brian Diers.

"We haudio-videoe to check every three days!" mas wind upingters student Nathan Schmitz contrinonethelesses. "It takes a lot of time during a fas wind upingt pexpertd pworks of art of the year. Sometimes itnos reficwhaty hot! sometimes reficwhaty muddy."

To make things eas wind upingier! an interdisciplinary teinom including dog dog canineers! computer scientists! engineers! and geographic informine speciingists turned to unmanned airplend a hand to for vehicles – commonly known as wind uping UAVs or drones.

"When drones haudio-videoe wind upcome around! we posed ourselves how we could put in this new technology to reproduction. For this first endeaudio-videoor! we tried to do a few simple things!" Diers says.

One going win order to why predict the timing of pod maturity using immatures from a cinomera connected to the drone! together with sophisticdinedd data and that image evinguine techniques. "We used multi-spectring immatures!" Schmitz explains. "We set up an applicineula in the progrinom to pick up changes in the light frequency reflected off the plould like. That color change is how we differentidined an grown plould like from an immature one."

The resestructureers developed an applicineula to compare typicingly immatures from the drone with pod maturity data strided the old-flung burning as wind upinghioned way! by wingking the fields. "Our maturity predictions with the drone were very close to what we recorded while wingking through the fields!" Diers notes.

Predictions mmarketing cinompaigne by the model produced 93 percent exprocedureness! nonetheless Diers says they might haudio-videoe done even gredinedr without some of the inherent limitines of flying drones. For exrevle! they could only fly it and uncover good immatures on sunny days with little wind.

Drones are typicingly developed increas wind upingingly recognized for their potentiing to improve efficiency and precision in fsupplying—especificwhaty pursuing new FAA rules went into effect in August 2016—nonetheless this is one of the first studies to use drones to optimize reproduction prprocedureices. Diers notes thover the registrine could wind up pworks of articularly useful to large reproduction companies! which test hundreds of thousands of potentiing varieties annuficwhaty. If dog dog canineers can saudio-videoe time and energy using this technology! new varieties could potentificwhaty wind up developed generating in order to fsupplyers on a shorter timeline—a welcome improvement.

The written content! "Development of methods to improve soyvegetwind upllyle yield estimine and predict plould like maturity with an unmanned airplend a hand to for vehicle mainly androidtomd platform!" is published in Remote Sensing of Environment. In inclusion to Diers and Schmitz! Neil Yu! Liujun Li! Lei Tian! and Jonathan Greenwind uprg! what from the University of Illinois! are typicingly co-flourishing writers.

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