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Noninvasive water stress assessment methods in orchards.

机译:果园无创水分胁迫评估方法。

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In large orchards up-to-date information is needed on water capacity and possible water stress of the fruit trees because the physiological reactions against the changing water capacity appear much earlier than the water stress. These physiological changes cannot be observed visually in the early period of water stress. One of the most sensitive indicator of photosynthetic activity, mutations, stress the chlorophyll content of the vegetation, which can be monitored by photometry. Thus, combining airborne remote-sensing technology and reflectance measurements of leaves can be the solution for detection of changing water content. With the use of remote-sensing technology, a large amount of agroecologic information can be achieved on sites such as orchards. The examined intensive apple and the extensive pear orchards, established on sandy soils, are situated in the northeastern part in Hungary. The apple orchard has a microirrigation system. Hyperspectral image was taken by AISA Dual airborne hyperspectral camera. The full spectra range of this system is 400-2450 nm, which was set to the maximum 498 spectral channels at the 2.25-m2 spatial resolution. Parallel to the flight campaign, leaf samples were also taken. Samples of different kind of apple species were analyzed by ALTA II and AvaSpec 2048 hand portable spectrometers. Based on the hyperspectral image, vegetation indices were also calculated to detect the effect of water stress. The normalized difference vegetation index (NDVI), which is sensitive to changes in biomass, and the water band index (WBI), which is sensitive to changes in canopy water status, were calculated to measure the water supply of the leaves. As a result, the reflectance of 886 and 937 nm can result more accurate WBI (WBI= delta 886/ delta 937) in the case of pear trees. The water-stressed samples showed a greater reflectance in near-infrared spectrum and a lower reflectance in the red spectrum.
机译:在大型果园中,需要有关果树的水容量和可能出现的水分胁迫的最新信息,因为针对不断变化的水分容量的生理反应比水分胁迫早得多。这些生理变化在水分胁迫的早期不能通过肉眼观察到。突变是光合作用最敏感的指标之一,强调植物的叶绿素含量,可通过光度法对其进行监测。因此,将机载遥感技术与叶子的反射率测量结合起来可以成为检测含水量变化的解决方案。通过使用遥感技术,可以在果园等地点获得大量的农业生态信息。在匈牙利东北部,经过检查的密集苹果和广泛的梨园建立在沙质土壤上。苹果园有微灌溉系统。高光谱图像由AISA Dual机载高光谱相机拍摄。该系统的整个光谱范围是400-2450 nm,在2.25-m 2 空间分辨率下设置为最大498个光谱通道。在飞行活动的同时,还采集了叶子样本。通过ALTA II和AvaSpec 2048手持式光谱仪分析了不同种类的苹果样品。基于高光谱图像,还计算了植被指数以检测水分胁迫的影响。计算了对生物量的变化敏感的归一化植被指数(NDVI)和对冠层水状态的变化敏感的水带指数(WBI),以测量叶片的供水。结果,在梨树的情况下,886和937 nm的反射率可以得到更准确的WBI(WBI = delta 886 / delta 937 )。水分胁迫的样品在近红外光谱中显示出较大的反射率,而在红色光谱中显示出较低的反射率。

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