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Sirvi Autor "Kviesis, K." järgi

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  • Pisipilt
    Kirje
    Experimental analysis of IoT based camera SI-NDVI values for tomato plant health monitoring application
    (2020) Avotins, A.; Kviesis, K.; Bicans, J.; Alsina, I.; Dubova, L.
    This paper reveals an IoT based camera design to capture SI-NDVI parameters and describes first obtained data analysis regarding luminary spectrum impact on readings in real greenhouse application. For experimental comparison, measurements of Encore, Strabena, Audiance, Bolzano, Forticia and Chocomate tomato plants, both for the ‘best’ and the ‘weakest’ plant sample, using IoT based camera solution and portable leaf spectrometer. First experimental results show that this approach can be applied for tomato plant monitoring, and reveals some ideas about possible precision improvements.
  • Pisipilt
    Kirje
    Possibilities of cucumber powdery mildew detection by visible and near-infrared spectroscopy
    (Estonian University of Life Sciences, 2022) Alsiņa, I.; Bimšteine, G.; Dubova, L.; Kaņeps, J.; Kviesis, K.; Bankina, B.; Dūma, M.; Avotiņš, A.
    Cucumbers are one of the most demanded and widely grown greenhouse vegetables. Important factors that influence quality and quantity of yield are diseases. Powdery mildew (caused by Podosphaera xanthii and/or Golovinomyces cichoracearum), is one of the most harmful cucumber diseases. Early detection of mildew via non-destructive methods can optimize schemes of fungicide application. The study aimed to find regularities in the reflected light spectra, indices described in the literature, and severity of mildew. Plants were grown in the polycarbonate greenhouse under artificial lighting in a 16 h photoperiod with PAR at the tips of plants 200 ± 30 µmol m-2 s-1. Leaf reflection spectra were obtained using spectroradiometer RS-3500 (Ltd. Spectral Evolution). Spectral range 350–2,500 nm, bandwidth 1 nm. The severity of cucumber mildew was evaluated using 10 point scale (0- no symptoms, … 9 - the plant is dead). The vegetation indices found in the literature have been calculated. The obtained results show that the calculated indices have different sensitivities. The strongest correlation between the degree of cucumbers infection with powdery mildew and the light reflectance spectrum was found in the green range of visible light around 550 nm. Disease-Water Stress Index-2 (DSWI-2), Structure Intensive Pigment Index (SIPI), and Normalized Difference Vegetation Index (NDVI) are the most suitable indices for determining powdery mildew in cucumbers. New indices for detection of powdery mildew have been created. None of the studied indices allows determining the powdery mildew at the early stages of disease development when powdery mildew severity is below 10%.