Hyperspectral diagnosis of nitrogen status in arbuscular mycorrhizal inoculated soybean leaves under three drought conditions
Abstract
Keywords: leaf nitrogen content, hyperspectral remote sensing, mycorrhizal effect, soybean, drought stress
DOI: 10.25165/j.ijabe.20181106.4019
Citation: Bi Y L, Kong W P, Huang W J. Hyperspectral diagnosis of nitrogen status in arbuscular mycorrhizal inoculated soybean leaves under three drought conditions. Int J Agric & Biol Eng, 2018; 11(6): 126–131.
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Zhang J, Wu J, Zhou L, Lei T, Liu M. Comparative study on remotely sensed methods of monitoring agricultural drought based on MODIS data. Remote Sensing Information, 2012; 27(5): 48–54.
Steward P R, Dougill A J, Thierfelder C, Pittelkow C M, Stringer L C, Kudzala M, et al. The adaptive capacity of maize-based conservation agriculture systems to climate stress in tropical and subtropical environments: A meta-regression of yields. Agriculture Ecosystems & Environment, 2018; 251: 194–202.
Bertolli S C, Rapchan G L, Souza G M. Photosynthetic limitations caused by different rates of water-deficit induction in Glycine max and Vigna unguiculata. Photosynthetica, 2012; 50(3): 329–36.
Gupta M L, Prasad A, Ram M, Kumar S. Effect of the vesicular-arbuscular mycorrhizal (VAM) fungus Glomus fasciculatum on the essential oil yield related characters and nutrient acquisition in the crops of different cultivars of menthol mint (Mentha arvensis) under field conditions. Bioresource Technology, 2002; 81(1): 77–9.
Bi Y L, Li X L, Wang H G, Christie P. Establishment of monoxenic culture between the arbuscular mycorrhizal fungus Glomus sinuosum and Ri T-DNA-transformed carrot roots. Plant and Soil, 2004; 261(1-2): 239–244.
Antunes P M, de Varennes A, Rajcan I, Goss M J. Accumulation of specific flavonoids in soybean (Glycine max L. Merr.) as a function of the early tripartite symbiosis with arbuscular mycorrhizal fungi and Bradyrhizobium japonicum (Kirchner) Jordan. Soil Biology & Biochemistry, 2006; 38(6): 1234–1242.
Feng W, Guo B B, Wang Z J, He L, Song X, Wang Y H, et al. Measuring leaf nitrogen concentration in-winter wheat using double-peak spectral reflection remote sensing data. Field Crops Research, 2014; 159: 43–52.
Chen P F, Haboudane D, Tremblay N, Wang J H, Vigneault P, Li B G. New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat. Remote Sensing of Environment, 2010; 114(9): 1987–1997.
Clevers J, Kooistra L. Using hyperspectral remote sensing data for retrieving canopy chlorophyll and nitrogen content. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012; 5(2): 574–583.
Wang H B, Feng R, Ji R P, Wu J W, Yu W Y, Zhang Y S. Hyperspectral characteristics of spring maize from jointing to silking stage under drought stress. Spectroscopy and Spectral Analysis, 2012; 32(12): 3358–3332.
Tian Y C, Gu K J, Chu X, Yao X, Cao W X, Zhu Y. Comparison of different hyperspectral vegetation indices for canopy leaf nitrogen concentration estimation in rice. Plant and Soil, 2014; 376(1-2): 193–209.
Ranjan R, Chopra U K, Sahoo R N, Singh A K, Pradhan S. Assessment of plant nitrogen stress in wheat (Triticum aestivum L.) through hyperspectral indices. International Journal Of Remote Sensing, 2012; 33(20): 6342–6360.
Herrmann I, Karnieli A, Bonfil D J, Cohen Y, Alchanatis V. SWIR-based spectral indices for assessing nitrogen content in potato fields. International Journal of Remote Sensing, 2010; 31(19): 5127–5143.
Lehnert L W, Meyer H, Meyer N, Reudenbach C, Bendix J. A hyperspectral indicator system for rangeland degradation on the Tibetan Plateau: A case study towards spaceborne monitoring. Ecol Indic, 2014; 39: 54–64.
Ryu C, Suguri M, Umeda M. Model for predicting the nitrogen content of rice at panicle initiation stage using data from airborne hyperspectral remote sensing. Biosystems Engineering, 2009; 104(4): 465–475.
Li F, Mistele B, Hu Y C, Chen X P, Schmidhalter U. Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression. European Journal of Agronomy, 2014; 52: 198–209.
Adjorlolo C, Mutanga O, Cho M A. Estimation of canopy nitrogen concentration across C3 and C4 grasslands using WorldView-2 multispectral data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014; 7(11): 4385–4392.
He T, Jing W, Lin Z J, Ye C. Spectral features of soil organic matter. Geomatics and Information Science of Wuhan University, 2006; 31(11): 975–979.
Phillips J M, Hayman D S. Improved procedures for clearing roots and staining parasitic and vesicular-arbuscular mycorrhizal fungi for rapid assessment of infection. Transactions of the British Mycological Society, 1970; 55: 158.
Tian Y H, Lei Y B, Zheng Y L, Cai Z Q. Synergistic effect of colonization with arbuscular mycorrhizal fungi improves growth and drought tolerance of Plukenetia volubilis seedlings. Acta Physiol Plant, 2013; 35(3): 687–696.
Li S, Bi Y, Chen P, Liu S, Zhang J, Zhou J, et al. Influence of exogenous calcium on the growth of maize under arid-stress in mine area. Journal of China University of Mining & Technology, 2013; 42(3): 477–482.
Boochs F, Kupfer G, Dockter K, Kuhbauch W. Shape of the red edge as vitality indicator for plants. International Journal of Remote Sensing, 1990; 11(10): 1741–1753.
Madakadze I C, Stewart K A, Madakadze R M, Peterson P R, Coulman B E, Smith D L. Field evaluation of the chlorophyll meter to predict yield and nitrogen concentration of switchgrass. Journal of Plant Nutrition, 1999; 22(6): 1001–1010.
Arregui L M, Lasa B, Lafarga A, Iraneta I, Baroja E, Quemada M. Evaluation of chlorophyll meters as tools for N fertilization in winter wheat under humid Mediterranean conditions. European Journal of Agronomy, 2006; 24(2): 140–148.
Demetriadesshah T H, Steven M D, Clark J A. High-resolution derivative spectra in remote-sensing. Remote Sensing of Environment, 1990; 33(1): 55–64.
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