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Estimation of crop nutritional status by UAV survey for site specific crop management

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F20%3A43919517" target="_blank" >RIV/62156489:43210/20:43919517 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://mnet.mendelu.cz/mendelnet2020/mnet_2020_full.pdf" target="_blank" >https://mnet.mendelu.cz/mendelnet2020/mnet_2020_full.pdf</a>

  • DOI - Digital Object Identifier

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Estimation of crop nutritional status by UAV survey for site specific crop management

  • Popis výsledku v původním jazyce

    This study is focused on the evaluation of UAV multispectral imaging for the diagnosis of nutritional status of winter wheat in precision agriculture. A field experiment was conducted in 2018 on two plots with the total area of 36 ha and 2019 at one plot with area 41.38 ha in ZD Kojcice (Pelhrimov, Czech Republic). During the vegetation period the field survey was carried out in stem elongation (BBCH 31) and heading (BBCH 51), both important vegetation stages for application of nitrogen fertilizers. The plant samples were taken on 56 and 53 sampling points distributed across the high - and low yielded zones and later analyzed for nitrogen content in plant tissues and total amount of above-ground biomass (fresh, dry). Simultaneously, unmanned aerial imaging was carried out by multispectral cameras Micasense RedEdge or Parrot Sequoia and the images were processed in photogrammetric software to create seamless ortho-mosaic in individual spectral bands (G, R, RE, NIR). A set of vegetation indices (NDVI, GNDVI, NDRE, NRERI, SAVI, MSAVI, EVI, EVI2, etc.) was calculated from these data and the mean value estimated by zonal statistics from 2m buffer zone around each sampling points. The statistical evaluation by correlation and regression analysis showed significant relationship between crop parameters and vegetation indices from UAV survey, thus it can be said that traditional field monitoring could be replaced by UAV survey even at a low number of calibration points. From the set of vegetation indices, NDVI showed better correlation values to estimate the amount of plant biomass, while the most sensitive vegetation index for estimation of nitrogen content in plants was NDRE index.

  • Název v anglickém jazyce

    Estimation of crop nutritional status by UAV survey for site specific crop management

  • Popis výsledku anglicky

    This study is focused on the evaluation of UAV multispectral imaging for the diagnosis of nutritional status of winter wheat in precision agriculture. A field experiment was conducted in 2018 on two plots with the total area of 36 ha and 2019 at one plot with area 41.38 ha in ZD Kojcice (Pelhrimov, Czech Republic). During the vegetation period the field survey was carried out in stem elongation (BBCH 31) and heading (BBCH 51), both important vegetation stages for application of nitrogen fertilizers. The plant samples were taken on 56 and 53 sampling points distributed across the high - and low yielded zones and later analyzed for nitrogen content in plant tissues and total amount of above-ground biomass (fresh, dry). Simultaneously, unmanned aerial imaging was carried out by multispectral cameras Micasense RedEdge or Parrot Sequoia and the images were processed in photogrammetric software to create seamless ortho-mosaic in individual spectral bands (G, R, RE, NIR). A set of vegetation indices (NDVI, GNDVI, NDRE, NRERI, SAVI, MSAVI, EVI, EVI2, etc.) was calculated from these data and the mean value estimated by zonal statistics from 2m buffer zone around each sampling points. The statistical evaluation by correlation and regression analysis showed significant relationship between crop parameters and vegetation indices from UAV survey, thus it can be said that traditional field monitoring could be replaced by UAV survey even at a low number of calibration points. From the set of vegetation indices, NDVI showed better correlation values to estimate the amount of plant biomass, while the most sensitive vegetation index for estimation of nitrogen content in plants was NDRE index.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    40106 - Agronomy, plant breeding and plant protection; (Agricultural biotechnology to be 4.4)

Návaznosti výsledku

  • Projekt

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2020

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    MendelNet 2020: Proceedings of International PhD Students Conference

  • ISBN

    978-80-7509-765-1

  • ISSN

  • e-ISSN

  • Počet stran výsledku

    6

  • Strana od-do

    26-31

  • Název nakladatele

    Mendelova univerzita v Brně

  • Místo vydání

    Brno

  • Místo konání akce

    Brno

  • Datum konání akce

    11. 11. 2020

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku