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Hyperspectral Analysis of Grapevine Water Stress

Year 2020, Volume: 8 Issue: 2, 475 - 489, 29.12.2020
https://doi.org/10.33202/comuagri.754784

Abstract

Viticulture is very sensitive to water stress, which is critical and influenced by all environmental factors, relating to the crop quality and productivity of vineyards. In this study, water stress was examined in veraison and harvest stages for nine different species with spectroradiometric measurements. Leaf water potential (LWP) values from field measurements and original spectra-based (OSB) and continuum removed spectra-based (CRSB) curves were analyzed with correlation and regression analysis to find the highest related wavelengths. The analysis was done for both specific dates of field measurements (i.e. 08.08.2012 and 06.09.2012) and also in aggregate i.e. all measured data. The specific date wavelength-based analysis revealed the “red edge region” as a major water stress indicator. The highest correlated wavelength was found to be 684 nm of CRSB curves with R=0.988. For the aggregate wavelength-based water stress analysis, the “violet and green regions” were identified as the best indicators. The highest correlated wavelength was found to be 410 nm of OSB curves with R=0.820. Furthermore, the Analysis of Variance (ANOVA) testing indicates that the results are significant at relatively high confidence levels. The spectral-based method performed in this study provides fast, flexible, and non-destructive water stress measurements of grapevines when compared to classical methods.

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Asma Su Stresinin Hiperspektral Analizi

Year 2020, Volume: 8 Issue: 2, 475 - 489, 29.12.2020
https://doi.org/10.33202/comuagri.754784

Abstract

Bağcılık, ürün kalitesi ve üzüm bağlarının verimliliği ile ilgili tüm çevresel faktörlerden etkilenen ve hayati bir etken olan su stresine son derece duyarlıdır. Bu çalışmada, dokuz farklı asma türü için ben düşme ve hasat dönemlerindeki asma su stresi spektroradyometrik ölçümlerle incelenmiştir. Arazi ölçümleri ile elde edilen yaprak su potansiyeli (LWP) değerleri ile en ilişkili dalga boylarını bulmak için orijinal spektrum temelli (OSB) ve sürekliliği kaldırılmış spektrum temelli (CRSB) eğriler korelasyon ve regresyon analizi ile analiz edilmiştir. Analizler hem ölçüm tarihleri için ayrı ayrı değerlendirmeler ile (yani 08.08.2012 ve 06.09.2012) hem de tüm ölçüm verileri için toplam tek bir veri seti olacak şekilde iki farklı yaklaşım ile gerçekleştirilmiştir. Ölçümlerin ayrı ayrı analizi, “kırmızı kenar bölgesini” önemli bir su stres göstergesi olarak ortaya çıkarmıştır. En yüksek korelasyonun R = 0.988 değeri ile CRSB eğrisinin 684 nm dalga boyu olduğu belirlenmiştir. Tüm ölçümlerin bir arada değerlendirildiği su stresi analizi için “mor ve yeşil bölgeleri” en iyi göstergeler olarak tespit edilmiştir. En yüksek korelasyonun R = 0.820 değeri ile OSB eğrisinin 410 nm dalga boyu olduğu belirlenmiştir. Ayrıca, Analysis of Variance (ANOVA) testinin sonuçları bu çalışmada elde edilen bulguların yüksek güven seviyelerinde anlamlı olduğunu göstermektedir. Bu çalışmada gerçekleştirilen spektral tabanlı yöntem, üzüm bağlarının / asma su stresi ölçmelerini klasik yöntemlere kıyasla hızlı, esnek ve tahribatsız bir şekilde sağlamaktadır.

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  • Demirel K., Çamoğlu G., Akçal A. (2018). Effect of Water Stress on Four Varieties of Gladiolus. Fresenius Environmental Bulletin, vol.27, no.12A/2018, pp.9300-9307.
  • Durgut, M.R. and Arın, S., 2005. Level and Problems of Trakya Region Vineyard Mechanization, Journal of Tekirdag Agricultural Faculty, 2(3), 287-297
  • Eamus, D. and Shanahan, S.T., 2002. A rate equation model of stomatal responses to vapour pressure deficit and drought. BMC Ecology. 2(8), 1-14, doi: 10.1186/1472-6785-2-8
  • Eitel, J.U.H., Gessler, P.E., Smith, A.M.S. and Robberecht, R., 2006. Suitability of existing and novel spectral indices to remotely detect water stress in Populus spp.. Forest Ecology and Management, 229(1-3), 170–182, http://dx.doi.org/10.1016/j.foreco.2006.03.027
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  • Filella, I. and Penuelas, J., 1994. The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status. International Journal of Remote Sensing, 15(7), doi: 10.1080/0143116940895417
  • Fitzgerald, G.J., Rodriguez, D., Christensen, L.K., Belford, R., Sadras, V.O. and Clarke, T. R., 2006. Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments. Precision Agriculture, 7(4), 233-248, doi:10.1007/s11119-006-9011-z
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  • Govender, M., Dye, P., Weiersbye, I., Witkowski, E. and Ahmed, F., 2009. Review of commonly used remote sensing and ground-based technologies to measure plant water stress. Water SA, 35(5), 741-752, http://dx.doi.org/10.4314/wsa.v35i5.49201
  • Greenspan, M. D., Schultz, H. R. and Matthews, M. A., 1996. Field evaluation of water transport in grape berries during water deficits. Physiologia Plantarum, 97(1), 55–62, doi: 10.1111/j.1399-3054.1996.tb00478.x
  • Greer, D.H. and Weedon, M.M., 2012. Interactions between light and growing season temperatures on, growth and development and gas exchange of Semillon (Vitis vinifera L.) vines grown in an irrigated vineyard. Plant Physiology and Biochemistry, 54, 59-69. http://dx.doi.org/10.1016/j.plaphy.2012.02.010
  • Gutierrez, M., Reynolds, M.P., and Klatt, A.R., 2010. Association of water spectral indices with plant and soil water relations in contrasting wheat genotypes. Journal of Experimental Botany, 61(12), 3291–3303, doi: 10.1093/jxb/erq156
  • Hunt, E.R. and Rock, B.N., 1989. Detection of changes in leaf water content using near- and middle infrared reflectances. Remote Sensing of Environment, 30(1), 43-54, http://dx.doi.org/10.1016/0034-4257(89)90046-1
  • İnce C., Özelkan E., Kaya Ş., 2014. Assessment of Thyme Reduction Using Multitemporal Satellite Data and In-Situ Spectroradiometric Measurement: Altioluk Plateau. Kocaeli-Turkey", FRESENIUS ENVIRONMENTAL BULLETIN, vol.23, pp.3007-3012.
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There are 60 citations in total.

Details

Primary Language English
Subjects Agricultural Engineering
Journal Section Articles
Authors

Emre Özelkan 0000-0002-2031-1610

Muhittin Karaman 0000-0002-8971-010X

Serkan Candar 0000-0002-2608-8691

Ertunga Özelkan This is me 0000-0002-4000-6955

Cankut Örmeci 0000-0003-4743-3236

Publication Date December 29, 2020
Published in Issue Year 2020 Volume: 8 Issue: 2

Cite

APA Özelkan, E., Karaman, M., Candar, S., Özelkan, E., et al. (2020). Hyperspectral Analysis of Grapevine Water Stress. ÇOMÜ Ziraat Fakültesi Dergisi, 8(2), 475-489. https://doi.org/10.33202/comuagri.754784